Updated 27/Nov/2021 by Yoshihisa Nitta  

Wasserstein Generative Adversarial Network with Gradient Penalty for CelebA dataset with Tensorflow 2 on Google Colab (WGAN-GP)

Train Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) on CelebA dataset.

CelebA データセットに対して Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) をGoogle Colab 上の Tensorflow 2 で学習する

CelebA データセットに対して Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) を学習する。

In [1]:
#! pip install tensorflow==2.7.0
In [2]:
%tensorflow_version 2.x

import tensorflow as tf
print(tf.__version__)
2.7.0

Check the Google Colab runtime environment

Google Colab 実行環境を調べる

In [3]:
! nvidia-smi
! cat /proc/cpuinfo
! cat /etc/issue
! free -h
Sat Nov 27 16:54:58 2021       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 495.44       Driver Version: 460.32.03    CUDA Version: 11.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  Tesla P100-PCIE...  Off  | 00000000:00:04.0 Off |                    0 |
| N/A   37C    P0    26W / 250W |      0MiB / 16280MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+
processor	: 0
vendor_id	: GenuineIntel
cpu family	: 6
model		: 85
model name	: Intel(R) Xeon(R) CPU @ 2.00GHz
stepping	: 3
microcode	: 0x1
cpu MHz		: 2000.184
cache size	: 39424 KB
physical id	: 0
siblings	: 2
core id		: 0
cpu cores	: 1
apicid		: 0
initial apicid	: 0
fpu		: yes
fpu_exception	: yes
cpuid level	: 13
wp		: yes
flags		: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves arat md_clear arch_capabilities
bugs		: cpu_meltdown spectre_v1 spectre_v2 spec_store_bypass l1tf mds swapgs taa
bogomips	: 4000.36
clflush size	: 64
cache_alignment	: 64
address sizes	: 46 bits physical, 48 bits virtual
power management:

processor	: 1
vendor_id	: GenuineIntel
cpu family	: 6
model		: 85
model name	: Intel(R) Xeon(R) CPU @ 2.00GHz
stepping	: 3
microcode	: 0x1
cpu MHz		: 2000.184
cache size	: 39424 KB
physical id	: 0
siblings	: 2
core id		: 0
cpu cores	: 1
apicid		: 1
initial apicid	: 1
fpu		: yes
fpu_exception	: yes
cpuid level	: 13
wp		: yes
flags		: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves arat md_clear arch_capabilities
bugs		: cpu_meltdown spectre_v1 spectre_v2 spec_store_bypass l1tf mds swapgs taa
bogomips	: 4000.36
clflush size	: 64
cache_alignment	: 64
address sizes	: 46 bits physical, 48 bits virtual
power management:

Ubuntu 18.04.5 LTS \n \l

              total        used        free      shared  buff/cache   available
Mem:            12G        951M        3.6G        1.2M        8.2G         11G
Swap:            0B          0B          0B

Mount Google Drive from Google Colab

Google Colab から GoogleDrive をマウントする

In [4]:
from google.colab import drive
drive.mount('/content/drive')
Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount("/content/drive", force_remount=True).
In [5]:
! ls /content/drive
MyDrive  Shareddrives

Download source file from Google Drive or nw.tsuda.ac.jp

Basically, gdown from Google Drive. Download from nw.tsuda.ac.jp above only if the specifications of Google Drive change and you cannot download from Google Drive.

Google Drive または nw.tsuda.ac.jp からファイルをダウンロードする

基本的に、Google Drive から gdown してください。 Google Drive の仕様が変わってダウンロードができない場合にのみ、nw.tsuda.ac.jp からダウンロードしてください。

In [6]:
# Download source file
nw_path = './nw'
! rm -rf {nw_path}
! mkdir -p {nw_path}

if True:   # from Google Drive
    url_model =  'https://drive.google.com/uc?id=1aBMpQCSfvt-LuR0Is5syyRTXQ79iNh2T'
    ! (cd {nw_path}; gdown {url_model})
else:      # from nw.tsuda.ac.jp
    URL_NW = 'https://nw.tsuda.ac.jp/lec/GoogleColab/pub'
    url_model = f'{URL_NW}/models/WGANGP.py'
    ! wget -nd {url_model} -P {nw_path}
Downloading...
From: https://drive.google.com/uc?id=1aBMpQCSfvt-LuR0Is5syyRTXQ79iNh2T
To: /content/nw/WGANGP.py
100% 19.7k/19.7k [00:00<00:00, 17.3MB/s]
In [7]:
! cat {nw_path}/WGANGP.py
import tensorflow as tf
tf.compat.v1.disable_eager_execution()

import numpy as np
from functools import partial

import matplotlib.pyplot as plt

import os
import pickle as pkl
import datetime


def grad(y,x):
    V = tf.keras.layers.Lambda(
        lambda z: tf.keras.backend.gradients(z[0],z[1]),
        output_shape=[1]
        )([y,x])
    return V


class RandomWeightedAverage(tf.keras.layers.Layer):
    def __init__(self, batch_size):
        super().__init__()
        self.batch_size = batch_size
    '''Provides a (random) weighted average between real and generated image samples'''
    def call(self, inputs):
        alpha = tf.keras.backend.random_uniform((self.batch_size, 1, 1, 1))
        return (alpha * inputs[0]) + ((1 - alpha) * inputs[1])


class WGANGP():
    def __init__(
        self,
        input_dim,
        critic_conv_filters,
        critic_conv_kernel_size,
        critic_conv_strides,
        critic_batch_norm_momentum,
        critic_activation,
        critic_dropout_rate,
        critic_learning_rate,
        generator_initial_dense_layer_size,
        generator_upsample,
        generator_conv_filters,
        generator_conv_kernel_size,
        generator_conv_strides,
        generator_batch_norm_momentum,
        generator_activation,
        generator_dropout_rate,
        generator_learning_rate,
        optimizer,
        grad_weight,  # wgangp
        z_dim,
        batch_size,    # wgangp
        epoch = 0,
        d_losses = [],
        g_losses = []
    ):
        self.name = 'wgangp'
        self.input_dim = input_dim
        
        self.critic_conv_filters = critic_conv_filters
        self.critic_conv_kernel_size = critic_conv_kernel_size
        self.critic_conv_strides = critic_conv_strides
        self.critic_batch_norm_momentum = critic_batch_norm_momentum
        self.critic_activation = critic_activation
        self.critic_dropout_rate = critic_dropout_rate
        self.critic_learning_rate = critic_learning_rate
        
        self.generator_initial_dense_layer_size = generator_initial_dense_layer_size
        self.generator_upsample = generator_upsample
        self.generator_conv_filters = generator_conv_filters
        self.generator_conv_kernel_size = generator_conv_kernel_size
        self.generator_conv_strides = generator_conv_strides
        self.generator_batch_norm_momentum = generator_batch_norm_momentum
        self.generator_activation = generator_activation
        self.generator_dropout_rate = generator_dropout_rate
        self.generator_learning_rate = generator_learning_rate
        
        self.optimizer = optimizer
        self.z_dim = z_dim

        self.n_layers_critic = len(critic_conv_filters)
        self.n_layers_generator = len (generator_conv_filters)

        self.weight_init = tf.keras.initializers.RandomNormal(mean=0., stddev=0.02)
        self.grad_weight = grad_weight
        self.batch_size = batch_size

        self.epoch = epoch

        self.d_losses = d_losses
        self.g_losses = g_losses


        self._build_critic()
        self._build_generator()

        self._build_adversarial()


    def gradient_penalty_loss(self, y_true, y_pred, interpolated_samples):
        '''
        Computes gradient penalty based on prediction and weighted real/fake samples
        '''
        gradients = grad(y_pred, interpolated_samples)[0]

        # compute the euclidean norm by squaring ...
        gradients_sqr = tf.keras.backend.square(gradients)
        # ... summing over the rows ...
        gradients_sqr_sum = tf.keras.backend.sum(gradients_sqr, axis=np.arange(1, len(gradients_sqr.shape)))
        # ... and sqrt
        gradient_12_norm = tf.keras.backend.sqrt(gradients_sqr_sum)
        # compute lambda * (1 - || grad|| )^2 still for each single sample
        gradient_penalty = tf.keras.backend.square(1 - gradient_12_norm)
        # return the mean as loss over all the batch samples
        return tf.keras.backend.mean(gradient_penalty)


    def wasserstein(self, y_true, y_pred):
        return - tf.keras.backend.mean(y_true * y_pred)

    
    def get_activation(self, activation):
        if activation == 'leaky_relu':
            layer = tf.keras.layers.LeakyReLU(alpha = 0.2)
        else:
            layer = tf.keras.layers.Activation(activation)
        return layer


    def _build_critic(self):

        ### The Critic
        critic_input = tf.keras.layers.Input(shape=self.input_dim, name='critic_input')

        x = critic_input

        for i in range(self.n_layers_critic):
            x = tf.keras.layers.Conv2D(
                filters = self.critic_conv_filters[i],
                kernel_size = self.critic_conv_kernel_size[i],
                strides = self.critic_conv_strides[i],
                padding = 'same',
                name = 'critic_conv_' + str(i),
                kernel_initializer = self.weight_init
            )(x)
            if self.critic_batch_norm_momentum and i > 0:
                x = tf.keras.layers.BatchNormalization(momentum = self.critic_batch_norm_momentum)(x)
            x = self.get_activation(self.critic_activation)(x)
            if self.critic_dropout_rate:
                x = tf.keras.layers.Dropout(rate=self.critic_dropout_rate)(x)
        x = tf.keras.layers.Flatten()(x)
        critic_output = tf.keras.layers.Dense(1, activation=None, kernel_initializer = self.weight_init)(x)
        self.critic = tf.keras.models.Model(critic_input, critic_output)


    def _build_generator(self):
        ### The Generator
        generator_input = tf.keras.layers.Input(shape=(self.z_dim,), name='generator_input')

        x = generator_input
        x = tf.keras.layers.Dense(np.prod(self.generator_initial_dense_layer_size), kernel_initializer = self.weight_init)(x)

        if self.generator_batch_norm_momentum:
            x = tf.keras.layers.BatchNormalization(momentum=self.generator_batch_norm_momentum)(x)
        x = self.get_activation(self.generator_activation)(x)
        x = tf.keras.layers.Reshape(self.generator_initial_dense_layer_size)(x)
        if self.generator_dropout_rate:
            x = tf.keras.layers.Dropout(rate=self.generator_dropout_rate)(x)
        for i in range(self.n_layers_generator):
            if self.generator_upsample[i] == 2:
                x = tf.keras.layers.UpSampling2D()(x)
                x = tf.keras.layers.Conv2D(
                    filters=self.generator_conv_filters[i],
                    kernel_size=self.generator_conv_kernel_size[i],
                    padding='same',
                    #strides=self.generator_conv_strides[i],  # [自分へのメモ] 元ソースではなぜか stride は使っていない。BUG? ここでは元ソースの通りにstridesは指定しないことにする。
                    name='generator_conv_'+str(i),
                    kernel_initializer=self.weight_init
                )(x)
            else:
                x = tf.keras.layers.Conv2DTranspose(
                    filters=self.generator_conv_filters[i],
                    kernel_size=self.generator_conv_kernel_size[i],
                    padding='same',
                    strides=self.generator_conv_strides[i],
                    name='generator_conv_'+str(i),
                    kernel_initializer=self.weight_init
                )(x)

            if i < self.n_layers_generator -1:
                if self.generator_batch_norm_momentum:
                    x = tf.keras.layers.BatchNormalization(momentum=self.generator_batch_norm_momentum)(x)
                x = self.get_activation(self.generator_activation)(x)
            else:
                x = tf.keras.layers.Activation('tanh')(x)

        generator_output = x
        self.generator = tf.keras.models.Model(generator_input, generator_output)


    def get_opti(self, lr):
        if self.optimizer == 'adam':
            opti = tf.keras.optimizers.Adam(learning_rate=lr, beta_1=0.5)
        elif self.optimizer == 'rmsprop':
            opti = tf.keras.optimizers.RMSprop(learning_rate=lr)
        else:
            opti = tf.keras.optimizers.Adam(learning_rate=lr)
        return opti


    def set_trainable(self, m, val):
        m.trainable = val
        for l in m.layers:
            l.trainable = val


    def _build_adversarial(self):   # WGANと比較して、この作りが大幅に変わるようだ

        # --------------------------------------------
        # Construct Computational Graph for the Critic
        # --------------------------------------------

        # Freeze generator's layers while training critic
        self.set_trainable(self.generator, False)

        # Image input (real sample)
        real_img = tf.keras.layers.Input(shape=self.input_dim)

        # Fake Image
        z_disc = tf.keras.layers.Input(shape=(self.z_dim,))
        fake_img = self.generator(z_disc)

        # critic determines validity of the real and fake images
        fake = self.critic(fake_img)
        valid = self.critic(real_img)

        # Construct weighted average between real and fake images
        interpolated_img = RandomWeightedAverage(self.batch_size)([real_img, fake_img])

        # Determine validity of weighted sample
        validity_interpolated = self.critic(interpolated_img)

        # Use Python partial to provide loss function with additional 'interpolated_samples' argument
        partial_gp_loss = partial(self.gradient_penalty_loss, interpolated_samples=interpolated_img)
        partial_gp_loss.__name__ = 'gradient_penalty'  # Keras requires function names

        self.critic_model = tf.keras.models.Model(
            inputs=[real_img, z_disc], 
            outputs=[valid, fake, validity_interpolated]
        )
        
        ### Compile critic
        # When the Model has multiple outputs, you can use different losses for each output by passing a dictionary or list to loss.
        # Minimize the sum of individual losses weighted by the loss_weights factor.
        # Modelが複数のoutputを持つ場合は、lossに辞書かリストを渡すことで、各outputに異なる損失を用いることができる。
        # Model によって最小化されるのは loss_weights 係数で重みづけされた個々の損失の加重合計である。
        self.critic_model.compile(
            loss=[self.wasserstein, self.wasserstein, partial_gp_loss],
            optimizer=self.get_opti(self.critic_learning_rate),
            loss_weights = [1, 1, self.grad_weight]
        )

        #--------------------------------------------
        # Construct Computational Graph for Generator
        #--------------------------------------------

        # For the generator, the critic's layers are freezed
        self.set_trainable(self.critic, False)
        self.set_trainable(self.generator, True)

        # Sampled noise for input to generator
        model_input = tf.keras.layers.Input(shape=(self.z_dim,))
        # Generate images based of noise
        img = self.generator(model_input)
        # critic (Discriminator) determines validity
        model_output = self.critic(img)
        # Defines generator model
        self.model = tf.keras.models.Model(model_input, model_output)

        self.model.compile(
            optimizer=self.get_opti(self.generator_learning_rate),
            loss=self.wasserstein
        )

        self.set_trainable(self.critic, True)


    def train_critic(self, x_train, batch_size, using_generator):
        valid = np.ones((batch_size, 1), dtype=np.float32)
        fake = -np.ones((batch_size, 1), dtype=np.float32)
        dummy = np.zeros((batch_size, 1), dtype=np.float32) # Dummy gt for gradient penalty

        if using_generator:
            true_imgs = next(x_train)[0]
            if true_imgs.shape[0] != batch_size:
                true_imgs = next(x_train)[0]
        else:
            idx = np.random.randint(0, x_train.shape[0], batch_size)
            true_imgs = x_train[idx]

        noise = np.random.normal(0, 1, (batch_size, self.z_dim))
        d_loss = self.critic_model.train_on_batch([true_imgs, noise], [valid, fake, dummy])

        return d_loss


    def train_generator(self, batch_size):
        valid = np.ones((batch_size, 1), dtype=np.float32)
        noise = np.random.normal(0, 1, (batch_size, self.z_dim))
        return self.model.train_on_batch(noise, valid)


    def train(self, x_train, batch_size, epochs, run_folder, print_every_n_batches=100, n_critic=5, using_generator=False):
        start_time = datetime.datetime.now()

        for epoch in range(self.epoch, epochs):

            if (epoch+1) % 100 == 0:
                critic_loops = 5
            else:
                critic_loops = n_critic
                
            for _ in range(critic_loops):
                d_loss = self.train_critic(x_train, batch_size, using_generator)
            g_loss = self.train_generator(batch_size)

            elapsed_time = datetime.datetime.now() - start_time
            print(f'{epoch+1} ({critic_loops}, 1) [D loss: {d_loss[0]:.3f} R {d_loss[1]:.3f} F {d_loss[2]:.3f} G {d_loss[3]:.3f}][G loss: {g_loss:.3f}]  {elapsed_time}')

            self.d_losses.append(d_loss)
            self.g_losses.append(g_loss)

            self.epoch += 1

            if self.epoch % print_every_n_batches == 0:
                self.save(run_folder, self.epoch)
                self.save(run_folder)

        self.save(run_folder, self.epoch)
        self.save(run_folder)


    def save(self, folder, epoch=None):
        self.save_params(folder, epoch)
        self.save_weights(folder,epoch)


    @staticmethod
    def load(folder, epoch=None):
        params = WGANGP.load_params(folder, epoch)
        gan = WGANGP(*params)
        gan.load_weights(folder, epoch)

        return gan


    def save_weights(self, run_folder, epoch=None):
        if epoch is None:
            self.save_model_weights(self.critic, os.path.join(run_folder, 'weights/critic-weights.h5'))
            self.save_model_weights(self.generator, os.path.join(run_folder, 'weights/generator-weights.h5'))
            self.save_model_weights(self.model, os.path.join(run_folder, 'weights/weights.h5'))
        else:
            self.save_model_weights(self.critic, os.path.join(run_folder, f'weights/critic-weights_{epoch}.h5'))
            self.save_model_weights(self.generator, os.path.join(run_folder, f'weights/generator-weights_{epoch}.h5'))
            self.save_model_weights(self.model, os.path.join(run_folder, f'weights/weights_{epoch}.h5'))


    def load_weights(self, run_folder, epoch=None):
        if epoch is None:
            self.load_model_weights(self.critic, os.path.join(run_folder, 'weights/critic-weights.h5'))
            self.load_model_weights(self.generator, os.path.join(run_folder, 'weights/generator-weights.h5'))
            self.load_model_weights(self.model, os.path.join(run_folder, 'weights/weights.h5'))
        else:
            self.load_model_weights(self.critic, os.path.join(run_folder, f'weights/critic-weights_{epoch}.h5'))
            self.load_model_weights(self.generator, os.path.join(run_folder, f'weights/generator-weights_{epoch}.h5'))
            self.load_model_weights(self.model, os.path.join(run_folder, f'weights/weights_{epoch}.h5'))


    def save_model_weights(self, model, filepath):
        dpath, fname = os.path.split(filepath)
        if dpath != '' and not os.path.exists(dpath):
            os.makedirs(dpath)
        model.save_weights(filepath)


    def load_model_weights(self, model, filepath):
        model.load_weights(filepath)


    def save_params(self, folder, epoch=None):
        if epoch is None:
            filepath = os.path.join(folder, 'params.pkl')
        else:
            filepath = os.path.join(folder, f'params_{epoch}.pkl')

        dpath, fname = os.path.split(filepath)
        if dpath != '' and not os.path.exists(dpath):
            os.makedirs(dpath)

        with open(os.path.join(filepath), 'wb') as f:
            pkl.dump([
                self.input_dim,
                self.critic_conv_filters,
                self.critic_conv_kernel_size,
                self.critic_conv_strides,
                self.critic_batch_norm_momentum,
                self.critic_activation,
                self.critic_dropout_rate,
                self.critic_learning_rate,
                self.generator_initial_dense_layer_size,
                self.generator_upsample,
                self.generator_conv_filters,
                self.generator_conv_kernel_size,
                self.generator_conv_strides,
                self.generator_batch_norm_momentum,
                self.generator_activation,
                self.generator_dropout_rate,
                self.generator_learning_rate,
                self.optimizer,
                self.grad_weight,
                self.z_dim,
                self.batch_size,
                self.epoch,
                self.d_losses,
                self.g_losses
            ], f)


    @staticmethod
    def load_params(folder, epoch=None):
        if epoch is None:
            filepath = os.path.join(folder, 'params.pkl')
        else:
            filepath = os.path.join(folder, f'params_{epoch}.pkl')

        with open(filepath, 'rb') as f:
            params = pkl.load(f)
        return params


    def generate_images(self, noise=[], n=10):
        if len(noise) == 0:
            noise = np.random.normal(0, 1, (n, self.z_dim))

        imgs = self.generator.predict(noise)   # [-1.0,1.0]
        imgs = 0.5 * (imgs + 1)        # [0.0, 1.0]
        imgs = np.clip(imgs, 0, 1)

        return imgs


    @staticmethod
    def showImages(xs, rows=-1, cols=-1, w=2.8, h=2.8, filepath=None):
        N = len(xs)
        if rows < 0: rows = 1
        if cols < 0: cols = (N + rows - 1) // rows
        fig, ax = plt.subplots(rows, cols, figsize=(w*cols, h*rows))
        idx = 0
        for row in range(rows):
            for col in range(cols):
                if rows == 1 and cols == 1:
                    axis = ax
                elif cols == 1:
                    axis = ax[row]
                elif rows == 1:
                    axis = ax[col]
                else:
                    axis = ax[row][col]

                if idx < N:
                    axis.imshow(xs[idx], cmap='gray')
                axis.axis('off')
                idx += 1

        if not filepath is None:
            dpath, fname = os.path.split(filepath)
            if dpath != '' and not os.path.exists(dpath):
                os.makedirs(dpath)
            fig.savefig(filepath, dpi=600)
            plt.close()
        else:
            plt.show()


    def showLoss(self, xlim=[], ylim=[]):
        d = np.array(self.d_losses)
        g = np.array(self.g_losses)
        d_loss = d[:, 0]
        d_loss_real = d[:, 1]
        d_loss_fake = d[:, 2]
        d_loss_gen = d[:, 3]
        g_loss = g
        WGANGP.plot_history(
            [d_loss, d_loss_real, d_loss_fake, d_loss_gen, g_loss],
            ['d_loss', 'd_loss_real', 'd_loss_fake', 'd_loss_gen', 'g_loss'],
            xlim,
            ylim)


    @staticmethod
    def plot_history(vals, labels, xlim=[], ylim=[]):
        colors = ['red', 'blue', 'green', 'orange', 'black', 'pink']
        n = len(vals)
        fig, ax = plt.subplots(1, 1, figsize=(9,4))
        for i in range(n):
            ax.plot(vals[i], c=colors[i], label=labels[i])
        ax.legend(loc='upper right')
        ax.set_xlabel('epochs')
        # ax.set_ylabel('loss')

        if xlim != []:
            ax.set_xlim(xlim[0], xlim[1])
        if ylim != []:
            ax.set_ylim(ylim[0], ylim[1])
        
        plt.show()

Preparing CelebA dataset

Official WWW of CelebA dataset: https://mmlab.ie.cuhk.edu.hk/projects/CelebA.html

Google Drive of CelebA dataset: https://drive.google.com/drive/folders/0B7EVK8r0v71pWEZsZE9oNnFzTm8?resourcekey=0-5BR16BdXnb8hVj6CNHKzLg

img_align_celeba.zip mirrored on my Google Drive: https://drive.google.com/uc?id=1LFKeoI-hb96jlV0K10dO1o04iQPBoFdx

CelebA データセットを用意する

CelebA データセットの公式ページ: https://mmlab.ie.cuhk.edu.hk/projects/CelebA.html

CelebA データセットのGoogle Drive: https://drive.google.com/drive/folders/0B7EVK8r0v71pWEZsZE9oNnFzTm8?resourcekey=0-5BR16BdXnb8hVj6CNHKzLg

自分の Google Drive 上にミラーした img_align_celeba.zip: https://drive.google.com/uc?id=1LFKeoI-hb96jlV0K10dO1o04iQPBoFdx

In [8]:
# Download img_align_celeba.zip from GoogleDrive

MIRRORED_URL = 'https://drive.google.com/uc?id=1LFKeoI-hb96jlV0K10dO1o04iQPBoFdx'

! gdown {MIRRORED_URL}
Downloading...
From: https://drive.google.com/uc?id=1LFKeoI-hb96jlV0K10dO1o04iQPBoFdx
To: /content/img_align_celeba.zip
100% 1.44G/1.44G [00:06<00:00, 211MB/s]
In [9]:
# function to select all images with the specified label
# 指定したラベルの画像を全て選び出す関数

def choose_images(xs, ys, label):
    mask = ys.squeeze() == label
    return xs[mask]
In [10]:
! ls -l img_align_celeba.zip
-rw-r--r-- 1 root root 1443490838 Nov 27 16:55 img_align_celeba.zip
In [11]:
DATA_DIR = 'data'
DATA_SUBDIR = 'img_align_celeba'
In [12]:
! rm -rf {DATA_DIR}
! unzip -d {DATA_DIR} -q {DATA_SUBDIR}.zip
In [13]:
! ls -l {DATA_DIR}/{DATA_SUBDIR} | head
! ls {DATA_DIR}/{DATA_SUBDIR} | wc
total 1737936
-rw-r--r-- 1 root root 11440 Sep 28  2015 000001.jpg
-rw-r--r-- 1 root root  7448 Sep 28  2015 000002.jpg
-rw-r--r-- 1 root root  4253 Sep 28  2015 000003.jpg
-rw-r--r-- 1 root root 10747 Sep 28  2015 000004.jpg
-rw-r--r-- 1 root root  6351 Sep 28  2015 000005.jpg
-rw-r--r-- 1 root root  8073 Sep 28  2015 000006.jpg
-rw-r--r-- 1 root root  8203 Sep 28  2015 000007.jpg
-rw-r--r-- 1 root root  7725 Sep 28  2015 000008.jpg
-rw-r--r-- 1 root root  8641 Sep 28  2015 000009.jpg
 202599  202599 2228589

Check the CelebA dataset

CelebA データセットを確認する

In [14]:
# paths to all the image files.

import os
import glob
import numpy as np

all_file_paths = np.array(glob.glob(os.path.join(DATA_DIR, DATA_SUBDIR, '*.jpg')))
n_all_images = len(all_file_paths)

print(n_all_images)
202599
In [15]:
# slect some image files.

n_to_show = 10
selected_indices = np.random.choice(range(n_all_images), n_to_show)
selected_paths = all_file_paths[selected_indices]
In [16]:
# Display some images.
%matplotlib inline
import matplotlib.pyplot as plt

fig, ax = plt.subplots(1, n_to_show, figsize=(1.4 * n_to_show, 1.4))
for i, path in enumerate(selected_paths):
    img = tf.keras.preprocessing.image.load_img(path)
    ax[i].imshow(img)
    ax[i].axis('off')
plt.show()

Separate image files for train and test

画像ファイルを学習用とテスト用に分割する

In [17]:
TRAIN_DATA_DIR = 'train_data'
TEST_DATA_DIR = 'test_data'
In [18]:
import os

split = 0.05

indices = np.arange(n_all_images)
np.random.shuffle(indices)
train_indices = indices[: -int(n_all_images * split)]
test_indices = indices[-int(n_all_images * split):]

! rm -rf {TRAIN_DATA_DIR} {TEST_DATA_DIR}

dst=f'{TRAIN_DATA_DIR}/celeba'
if not os.path.exists(dst):
    os.makedirs(dst)
for idx in train_indices:
    path = all_file_paths[idx]
    dpath, fname = os.path.split(path)
    os.symlink(f'../../{path}', f'{dst}/{fname}')

dst=f'{TEST_DATA_DIR}/celeba'
if not os.path.exists(dst):
    os.makedirs(dst)
for idx in test_indices:
    path = all_file_paths[idx]
    dpath, fname = os.path.split(path)
    os.symlink(f'../../{path}', f'{dst}/{fname}')

Prepare ImageDataGenerator

flow_from_directory() requires to specify the parent directory of the directory where the image files are located.

ImageDataGenerator を用意する

flow_from_directory() では image files があるディレクトリの親ディレクトリを指定する必要がある。

In [19]:
IMAGE_SIZE = 64
BATCH_SIZE = 64
In [20]:
INPUT_DIM = (IMAGE_SIZE, IMAGE_SIZE, 3)
In [21]:
data_gen = tf.keras.preprocessing.image.ImageDataGenerator(
    preprocessing_function = lambda x: (x.astype('float32') - 127.5) / 127.5
    )

data_flow = data_gen.flow_from_directory(
    TRAIN_DATA_DIR,
    target_size = INPUT_DIM[:2],
    batch_size = BATCH_SIZE,
    shuffle=True,
    class_mode = 'input'
    )

val_data_flow = data_gen.flow_from_directory(
    TEST_DATA_DIR,
    target_size = INPUT_DIM[:2],
    batch_size = BATCH_SIZE,
    shuffle=True,
    class_mode = 'input'
    )
Found 192470 images belonging to 1 classes.
Found 10129 images belonging to 1 classes.
In [22]:
print(len(data_flow))
print(len(val_data_flow))
3008
159
In [23]:
# ImageDataGenerator.next() returns the same x and y when class_mode='input'
x, y = next(data_flow)
print(x[0].shape)

x = (x + 1) * 0.5      # [-1, 1] --> [0, 1]
x = np.clip(x, 0, 1)

y = (y + 1) * 0.5      # [-1, 1] --> [0, 1]
y = np.clip(y, 0, 1)

%matplotlib inline
import matplotlib.pyplot as plt

n_to_show = 10
fig, ax = plt.subplots(2, n_to_show, figsize=(1.4 * n_to_show, 1.4 * 2))
for i in range(n_to_show):
    ax[0][i].imshow(x[i])
    ax[0][i].axis('off')
    ax[1][i].imshow(y[i])
    ax[1][i].axis('off')
plt.show()
(64, 64, 3)

Define the Neural Network Model

ニューラルネットワーク・モデルを定義する

In [24]:
from nw.WGANGP import WGANGP

gan = WGANGP(
    input_dim = (IMAGE_SIZE, IMAGE_SIZE, 3),
    critic_conv_filters = [64, 128, 256, 512],
    critic_conv_kernel_size = [5,5,5,5],
    critic_conv_strides = [2,2,2,2],
    critic_batch_norm_momentum = None,
    critic_activation = 'leaky_relu',
    critic_dropout_rate = None,
    critic_learning_rate = 0.0002,
    generator_initial_dense_layer_size = (4,4,512),
    generator_upsample = [1,1,1,1],
    generator_conv_filters = [256, 128, 64, 3],
    generator_conv_kernel_size = [5,5,5,5],
    generator_conv_strides = [2,2,2,2],
    generator_batch_norm_momentum = 0.9,
    generator_activation = 'leaky_relu',
    generator_dropout_rate = None,
    generator_learning_rate = 0.0002,
    optimizer = 'adam',
    grad_weight = 10,
    z_dim = 100, 
    batch_size = BATCH_SIZE
)
WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/keras/layers/normalization/batch_normalization.py:532: _colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
In [25]:
gan.critic.summary()
Model: "model"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 critic_input (InputLayer)   [(None, 64, 64, 3)]       0         
                                                                 
 critic_conv_0 (Conv2D)      multiple                  4864      
                                                                 
 leaky_re_lu (LeakyReLU)     multiple                  0         
                                                                 
 critic_conv_1 (Conv2D)      multiple                  204928    
                                                                 
 leaky_re_lu_1 (LeakyReLU)   multiple                  0         
                                                                 
 critic_conv_2 (Conv2D)      multiple                  819456    
                                                                 
 leaky_re_lu_2 (LeakyReLU)   multiple                  0         
                                                                 
 critic_conv_3 (Conv2D)      multiple                  3277312   
                                                                 
 leaky_re_lu_3 (LeakyReLU)   multiple                  0         
                                                                 
 flatten (Flatten)           multiple                  0         
                                                                 
 dense (Dense)               multiple                  8193      
                                                                 
=================================================================
Total params: 4,314,753
Trainable params: 4,314,753
Non-trainable params: 0
_________________________________________________________________
In [26]:
gan.generator.summary()
Model: "model_1"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 generator_input (InputLayer  [(None, 100)]            0         
 )                                                               
                                                                 
 dense_1 (Dense)             (None, 8192)              827392    
                                                                 
 batch_normalization (BatchN  (None, 8192)             32768     
 ormalization)                                                   
                                                                 
 leaky_re_lu_4 (LeakyReLU)   (None, 8192)              0         
                                                                 
 reshape (Reshape)           (None, 4, 4, 512)         0         
                                                                 
 generator_conv_0 (Conv2DTra  (None, 8, 8, 256)        3277056   
 nspose)                                                         
                                                                 
 batch_normalization_1 (Batc  (None, 8, 8, 256)        1024      
 hNormalization)                                                 
                                                                 
 leaky_re_lu_5 (LeakyReLU)   (None, 8, 8, 256)         0         
                                                                 
 generator_conv_1 (Conv2DTra  (None, 16, 16, 128)      819328    
 nspose)                                                         
                                                                 
 batch_normalization_2 (Batc  (None, 16, 16, 128)      512       
 hNormalization)                                                 
                                                                 
 leaky_re_lu_6 (LeakyReLU)   (None, 16, 16, 128)       0         
                                                                 
 generator_conv_2 (Conv2DTra  (None, 32, 32, 64)       204864    
 nspose)                                                         
                                                                 
 batch_normalization_3 (Batc  (None, 32, 32, 64)       256       
 hNormalization)                                                 
                                                                 
 leaky_re_lu_7 (LeakyReLU)   (None, 32, 32, 64)        0         
                                                                 
 generator_conv_3 (Conv2DTra  (None, 64, 64, 3)        4803      
 nspose)                                                         
                                                                 
 activation (Activation)     (None, 64, 64, 3)         0         
                                                                 
=================================================================
Total params: 5,168,003
Trainable params: 5,150,723
Non-trainable params: 17,280
_________________________________________________________________
In [27]:
gan.critic_model.summary
Out[27]:
<bound method Model.summary of <keras.engine.functional.Functional object at 0x7f4bd7f350d0>>
In [28]:
gan.model.summary()
Model: "model_3"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 input_3 (InputLayer)        [(None, 100)]             0         
                                                                 
 model_1 (Functional)        (None, 64, 64, 3)         5168003   
                                                                 
 model (Functional)          (None, 1)                 4314753   
                                                                 
=================================================================
Total params: 5,168,003
Trainable params: 5,150,723
Non-trainable params: 17,280
_________________________________________________________________

Training

学習

At first, try training a small number of epoch.

まず、少ない回数だけ学習してみる

In [29]:
save_path1 = '/content/drive/MyDrive/ColabRun/WGANGP_CelebA01'
In [30]:
gan.train(
    data_flow,
    batch_size = BATCH_SIZE,
    epochs = 3,
    run_folder = save_path1,
    using_generator=True
)
WARNING:tensorflow:Discrepancy between trainable weights and collected trainable weights, did you set `model.trainable` without calling `model.compile` after ?
WARNING:tensorflow:Discrepancy between trainable weights and collected trainable weights, did you set `model.trainable` without calling `model.compile` after ?
1 (5, 1) [D loss: -1.452 R -6.831 F 0.076 G 0.530][G loss: -5.111]  0:00:08.568548
2 (5, 1) [D loss: -94.698 R -154.039 F 1.674 G 5.767][G loss: -59.722]  0:00:09.578428
3 (5, 1) [D loss: -125.352 R -212.060 F 2.328 G 8.438][G loss: -60.217]  0:00:10.445299
In [31]:
print(gan.epoch)
3
In [32]:
print(gan.d_losses[:3])
[[-1.4522681, -6.8312173, 0.07562452, 0.53033245], [-94.69839, -154.03935, 1.6740208, 5.766694], [-125.35213, -212.05988, 2.3275084, 8.438024]]
In [33]:
print(gan.g_losses[:3])
[-5.111105, -59.721878, -60.21668]
In [34]:
# Train the model a little more
# もう少し学習を進めてみる

gan.train(
    data_flow,
    batch_size = BATCH_SIZE,
    epochs = 10,
    run_folder = save_path1,
    using_generator=True
)
4 (5, 1) [D loss: -134.797 R -224.033 F 3.421 G 8.582][G loss: -70.592]  0:00:00.907660
5 (5, 1) [D loss: -141.399 R -220.096 F 4.467 G 7.423][G loss: -79.711]  0:00:01.781655
6 (5, 1) [D loss: -146.432 R -237.543 F 6.248 G 8.486][G loss: -79.515]  0:00:02.637618
7 (5, 1) [D loss: -134.878 R -256.607 F 10.219 G 11.151][G loss: -55.759]  0:00:03.697741
8 (5, 1) [D loss: -137.791 R -229.810 F 10.002 G 8.202][G loss: -89.419]  0:00:04.555707
9 (5, 1) [D loss: -152.717 R -255.131 F 14.374 G 8.804][G loss: -83.649]  0:00:05.414939
10 (5, 1) [D loss: -136.168 R -208.047 F 12.359 G 5.952][G loss: -79.789]  0:00:06.262849

Check the loss and accuracy of the training process.

学習過程のlossと精度を確認する

In [35]:
# Display the graph of losses in training
%matplotlib inline

gan.showLoss()

Check the saved files

保存されているファイルを確認する

In [36]:
! ls -lR {save_path1}
/content/drive/MyDrive/ColabRun/WGANGP_CelebA01:
total 8
-rw------- 1 root root 1239 Nov 27 16:56 params_10.pkl
-rw------- 1 root root  574 Nov 27 16:56 params_3.pkl
-rw------- 1 root root 1239 Nov 27 16:56 params.pkl
drwx------ 2 root root 4096 Nov 27 16:56 weights

/content/drive/MyDrive/ColabRun/WGANGP_CelebA01/weights:
total 222560
-rw------- 1 root root 17285328 Nov 27 16:56 critic-weights_10.h5
-rw------- 1 root root 17285328 Nov 27 16:56 critic-weights_3.h5
-rw------- 1 root root 17285328 Nov 27 16:56 critic-weights.h5
-rw------- 1 root root 20713304 Nov 27 16:56 generator-weights_10.h5
-rw------- 1 root root 20713304 Nov 27 16:56 generator-weights_3.h5
-rw------- 1 root root 20713304 Nov 27 16:56 generator-weights.h5
-rw------- 1 root root 37967552 Nov 27 16:56 weights_10.h5
-rw------- 1 root root 37967552 Nov 27 16:56 weights_3.h5
-rw------- 1 root root 37967552 Nov 27 16:56 weights.h5

Load the saved file and try further training.

Load the saved parameters and model weights, and try training further.

セーブしたファイルをロードして、さらに学習を進める

保存してあるパラメータとモデルの重みをロードして、追加の学習を試みる。

In [37]:
# Load the saved parameters and weights.
# 保存してある学習結果をロードする。

gan_work = WGANGP.load(save_path1)

# Display the epoch count of the model.
# training のepoch回数を表示する。

print(gan_work.epoch)
10
In [38]:
# Training in addition
# 追加で training する。

gan_work.train(
    data_flow,
    batch_size = BATCH_SIZE,
    epochs = 100,
    run_folder = save_path1,
    using_generator = True
)
11 (5, 1) [D loss: -145.111 R -230.313 F 16.396 G 6.881][G loss: -73.390]  0:00:04.370944
12 (5, 1) [D loss: -126.598 R -256.478 F 22.593 G 10.729][G loss: -62.728]  0:00:05.238850
13 (5, 1) [D loss: -135.129 R -238.813 F 20.494 G 8.319][G loss: -71.997]  0:00:06.113300
14 (5, 1) [D loss: -134.017 R -263.914 F 30.675 G 9.922][G loss: -47.495]  0:00:06.969948
15 (5, 1) [D loss: -145.220 R -256.435 F 27.660 G 8.356][G loss: -60.498]  0:00:07.813600
16 (5, 1) [D loss: -129.393 R -261.882 F 33.008 G 9.948][G loss: -41.802]  0:00:08.676386
17 (5, 1) [D loss: -138.552 R -237.740 F 22.880 G 7.631][G loss: -72.241]  0:00:09.521888
18 (5, 1) [D loss: -125.650 R -218.664 F 26.244 G 6.677][G loss: -71.150]  0:00:10.368980
19 (5, 1) [D loss: -133.469 R -245.930 F 39.784 G 7.268][G loss: -51.895]  0:00:11.218729
20 (5, 1) [D loss: -120.972 R -319.283 F 20.084 G 17.823][G loss: -70.760]  0:00:12.070377
21 (5, 1) [D loss: -144.967 R -239.862 F 33.331 G 6.156][G loss: -58.721]  0:00:12.920787
22 (5, 1) [D loss: -150.209 R -268.341 F 43.968 G 7.416][G loss: -19.464]  0:00:13.804492
23 (5, 1) [D loss: -113.359 R -231.177 F 38.637 G 7.918][G loss: -57.579]  0:00:14.656694
24 (5, 1) [D loss: -132.063 R -324.795 F 41.100 G 15.163][G loss: -50.111]  0:00:15.511502
25 (5, 1) [D loss: -146.535 R -235.117 F 7.651 G 8.093][G loss: -83.686]  0:00:16.356927
26 (5, 1) [D loss: -141.489 R -242.882 F 29.034 G 7.236][G loss: -15.168]  0:00:17.204203
27 (5, 1) [D loss: -169.945 R -279.019 F 22.390 G 8.668][G loss: 6.727]  0:00:18.046955
28 (5, 1) [D loss: -165.477 R -274.481 F -3.726 G 11.273][G loss: -21.804]  0:00:18.900753
29 (5, 1) [D loss: -123.379 R -248.187 F 15.835 G 10.897][G loss: -8.817]  0:00:19.761363
30 (5, 1) [D loss: -126.959 R -174.109 F -36.846 G 8.400][G loss: -53.027]  0:00:20.628938
31 (5, 1) [D loss: -117.694 R -195.887 F 15.101 G 6.309][G loss: -50.605]  0:00:21.494214
32 (5, 1) [D loss: -148.700 R -255.814 F 39.462 G 6.765][G loss: -42.688]  0:00:22.345911
33 (5, 1) [D loss: -104.812 R -232.278 F 45.874 G 8.159][G loss: -56.233]  0:00:23.217159
34 (5, 1) [D loss: -92.986 R -185.669 F -10.682 G 10.337][G loss: -75.491]  0:00:24.236400
35 (5, 1) [D loss: -98.295 R -198.583 F 45.233 G 5.506][G loss: -81.305]  0:00:25.088425
36 (5, 1) [D loss: -114.295 R -182.235 F -25.234 G 9.317][G loss: -40.916]  0:00:25.956363
37 (5, 1) [D loss: -100.453 R -155.963 F -33.475 G 8.898][G loss: -75.787]  0:00:26.802459
38 (5, 1) [D loss: -122.016 R -149.766 F -34.546 G 6.230][G loss: -82.670]  0:00:27.643675
39 (5, 1) [D loss: -93.556 R -167.086 F 3.401 G 7.013][G loss: -84.169]  0:00:28.484911
40 (5, 1) [D loss: -100.501 R -212.756 F 31.204 G 8.105][G loss: -100.559]  0:00:29.355415
41 (5, 1) [D loss: -92.502 R -185.588 F 43.946 G 4.914][G loss: -90.944]  0:00:30.198473
42 (5, 1) [D loss: -81.245 R -174.292 F 57.556 G 3.549][G loss: -74.101]  0:00:31.047991
43 (5, 1) [D loss: -67.547 R -148.203 F 45.681 G 3.497][G loss: -119.259]  0:00:31.905270
44 (5, 1) [D loss: -64.159 R -168.125 F 72.311 G 3.166][G loss: -86.911]  0:00:32.767905
45 (5, 1) [D loss: -64.325 R -240.039 F 146.501 G 2.921][G loss: -117.746]  0:00:33.630935
46 (5, 1) [D loss: -56.103 R -196.709 F 109.096 G 3.151][G loss: -129.560]  0:00:34.509328
47 (5, 1) [D loss: -54.678 R -228.294 F 143.295 G 3.032][G loss: -129.986]  0:00:35.358385
48 (5, 1) [D loss: -69.932 R -210.987 F 113.719 G 2.734][G loss: -119.549]  0:00:36.213254
49 (5, 1) [D loss: -62.751 R -222.649 F 126.991 G 3.291][G loss: -108.646]  0:00:37.065886
50 (5, 1) [D loss: -54.519 R -232.927 F 149.785 G 2.862][G loss: -102.381]  0:00:37.917820
51 (5, 1) [D loss: -71.450 R -181.845 F 84.298 G 2.610][G loss: -96.265]  0:00:38.781282
52 (5, 1) [D loss: -57.980 R -187.741 F 106.640 G 2.312][G loss: -136.908]  0:00:39.775929
53 (5, 1) [D loss: -56.402 R -197.477 F 113.674 G 2.740][G loss: -120.181]  0:00:40.632979
54 (5, 1) [D loss: -53.008 R -237.637 F 144.465 G 4.016][G loss: -85.626]  0:00:41.477399
55 (5, 1) [D loss: -60.025 R -169.693 F 82.193 G 2.747][G loss: -78.055]  0:00:42.335406
56 (5, 1) [D loss: -50.026 R -137.053 F 58.294 G 2.873][G loss: -102.563]  0:00:43.188491
57 (5, 1) [D loss: -52.666 R -133.684 F 57.325 G 2.369][G loss: -78.078]  0:00:44.065569
58 (5, 1) [D loss: -56.130 R -125.417 F 54.233 G 1.505][G loss: -105.563]  0:00:44.908529
59 (5, 1) [D loss: -51.088 R -143.794 F 76.083 G 1.662][G loss: -99.591]  0:00:45.763933
60 (5, 1) [D loss: -52.478 R -165.949 F 94.619 G 1.885][G loss: -118.852]  0:00:46.627463
61 (5, 1) [D loss: -58.142 R -143.662 F 54.152 G 3.137][G loss: -73.275]  0:00:47.483306
62 (5, 1) [D loss: -47.233 R -139.088 F 71.303 G 2.055][G loss: -70.528]  0:00:48.340135
63 (5, 1) [D loss: -38.867 R -139.288 F 81.939 G 1.848][G loss: -86.315]  0:00:49.221646
64 (5, 1) [D loss: -49.176 R -121.266 F 46.708 G 2.538][G loss: -74.021]  0:00:50.074793
65 (5, 1) [D loss: -41.553 R -137.738 F 72.070 G 2.411][G loss: -86.607]  0:00:50.913933
66 (5, 1) [D loss: -46.670 R -130.674 F 61.863 G 2.214][G loss: -66.681]  0:00:51.770523
67 (5, 1) [D loss: -41.853 R -110.674 F 48.183 G 2.064][G loss: -59.939]  0:00:52.632481
68 (5, 1) [D loss: -50.939 R -139.631 F 73.926 G 1.477][G loss: -60.528]  0:00:53.475338
69 (5, 1) [D loss: -42.995 R -111.627 F 55.394 G 1.324][G loss: -80.386]  0:00:54.374848
70 (5, 1) [D loss: -43.914 R -93.373 F 31.392 G 1.807][G loss: -66.543]  0:00:55.227174
71 (5, 1) [D loss: -39.270 R -75.695 F 14.451 G 2.197][G loss: -66.137]  0:00:56.066560
72 (5, 1) [D loss: -37.910 R -114.032 F 65.477 G 1.065][G loss: -77.272]  0:00:56.921586
73 (5, 1) [D loss: -34.927 R -144.212 F 92.801 G 1.648][G loss: -40.649]  0:00:57.781175
74 (5, 1) [D loss: -38.342 R -131.120 F 80.044 G 1.273][G loss: -74.023]  0:00:58.628358
75 (5, 1) [D loss: -35.317 R -90.067 F 36.642 G 1.811][G loss: -73.661]  0:00:59.477110
76 (5, 1) [D loss: -37.695 R -93.116 F 41.699 G 1.372][G loss: -64.380]  0:01:00.322531
77 (5, 1) [D loss: -34.193 R -100.876 F 57.706 G 0.898][G loss: -79.062]  0:01:01.169566
78 (5, 1) [D loss: -43.349 R -92.505 F 34.479 G 1.468][G loss: -42.055]  0:01:02.021755
79 (5, 1) [D loss: -34.964 R -93.349 F 48.320 G 1.007][G loss: -48.644]  0:01:02.881737
80 (5, 1) [D loss: -28.584 R -83.461 F 43.731 G 1.115][G loss: -74.697]  0:01:03.732202
81 (5, 1) [D loss: -44.133 R -46.994 F -12.585 G 1.545][G loss: -10.651]  0:01:04.713439
82 (5, 1) [D loss: -35.112 R -62.244 F 17.127 G 1.000][G loss: -33.026]  0:01:05.563244
83 (5, 1) [D loss: -38.966 R -57.334 F 5.047 G 1.332][G loss: -22.884]  0:01:06.440039
84 (5, 1) [D loss: -28.021 R -113.664 F 75.346 G 1.030][G loss: -40.105]  0:01:07.293749
85 (5, 1) [D loss: -40.027 R -149.321 F 83.605 G 2.569][G loss: -27.116]  0:01:08.142535
86 (5, 1) [D loss: -42.273 R -140.823 F 77.142 G 2.141][G loss: -48.069]  0:01:08.988193
87 (5, 1) [D loss: -42.439 R -102.331 F 49.092 G 1.080][G loss: -53.258]  0:01:09.865137
88 (5, 1) [D loss: -34.085 R -77.002 F 33.169 G 0.975][G loss: -55.080]  0:01:10.726872
89 (5, 1) [D loss: -45.267 R -52.051 F -6.020 G 1.280][G loss: -18.454]  0:01:11.570218
90 (5, 1) [D loss: -31.505 R -76.747 F 32.047 G 1.320][G loss: -32.475]  0:01:12.423127
91 (5, 1) [D loss: -35.169 R -92.738 F 48.543 G 0.903][G loss: -30.433]  0:01:13.280706
92 (5, 1) [D loss: -33.345 R -96.794 F 51.882 G 1.157][G loss: -45.731]  0:01:14.134492
93 (5, 1) [D loss: -41.520 R -96.284 F 42.007 G 1.276][G loss: -56.839]  0:01:15.114306
94 (5, 1) [D loss: -40.381 R -111.105 F 59.905 G 1.082][G loss: -93.016]  0:01:15.972681
95 (5, 1) [D loss: -35.221 R -121.100 F 72.997 G 1.288][G loss: -26.229]  0:01:16.822576
96 (5, 1) [D loss: -54.394 R -92.121 F 23.734 G 1.399][G loss: -72.498]  0:01:17.663575
97 (5, 1) [D loss: -33.637 R -173.059 F 106.653 G 3.277][G loss: -36.375]  0:01:18.528103
98 (5, 1) [D loss: -34.245 R -113.338 F 56.736 G 2.236][G loss: -44.705]  0:01:19.399050
99 (5, 1) [D loss: -49.461 R -141.162 F 62.161 G 2.954][G loss: -67.040]  0:01:20.256612
100 (5, 1) [D loss: -48.211 R -81.443 F 20.917 G 1.231][G loss: -40.527]  0:01:21.109332
In [39]:
%matplotlib inline 

# prepare the noise vectors
# ノイズ・ベクトルを用意する。

if False:
    rows, cols = 5, 5

    noise = np.random.normal(0, 1, (rows * cols, gan.z_dim))

    imgs = gan_work.generator.predict(noise)
    imgs = 0.5 * (imgs + 1)
    imgs = np.clip(imgs, 0, 1)
    #imgs = gan.generate_images(noise).squeeze()
    WGANGP.showImages(imgs, rows, cols, 1.4, 1.4)
In [40]:
# Training in addition
# 追加で training する。

gan_work.train(
    data_flow,
    batch_size = BATCH_SIZE,
    epochs = 500,
    run_folder = save_path1,
    print_every_n_batches = 2000,
    using_generator = True
)
101 (5, 1) [D loss: -49.996 R -98.056 F 25.117 G 2.294][G loss: -85.479]  0:00:00.896998
102 (5, 1) [D loss: -33.155 R -134.270 F 86.224 G 1.489][G loss: -101.347]  0:00:01.776530
103 (5, 1) [D loss: -40.341 R -129.443 F 70.217 G 1.888][G loss: -69.009]  0:00:02.663597
104 (5, 1) [D loss: -64.789 R -126.148 F 37.323 G 2.404][G loss: -137.173]  0:00:03.531095
105 (5, 1) [D loss: -49.857 R -127.659 F 59.476 G 1.833][G loss: -139.740]  0:00:04.387218
106 (5, 1) [D loss: -52.822 R -172.850 F 96.998 G 2.303][G loss: -138.717]  0:00:05.277584
107 (5, 1) [D loss: -61.973 R -179.439 F 92.783 G 2.468][G loss: -162.949]  0:00:06.151385
108 (5, 1) [D loss: -63.311 R -171.376 F 74.219 G 3.385][G loss: -162.178]  0:00:07.188435
109 (5, 1) [D loss: -51.003 R -167.492 F 97.332 G 1.916][G loss: -117.401]  0:00:08.144431
110 (5, 1) [D loss: -45.899 R -159.672 F 92.270 G 2.150][G loss: -111.124]  0:00:09.011090
111 (5, 1) [D loss: -44.189 R -136.465 F 71.075 G 2.120][G loss: -114.546]  0:00:09.876777
112 (5, 1) [D loss: -43.475 R -131.909 F 71.972 G 1.646][G loss: -47.113]  0:00:10.753081
113 (5, 1) [D loss: -35.505 R -96.962 F 43.462 G 1.799][G loss: -32.368]  0:00:11.641077
114 (5, 1) [D loss: -39.845 R -47.915 F -6.586 G 1.466][G loss: -39.148]  0:00:12.532797
115 (5, 1) [D loss: -43.575 R -96.611 F 31.754 G 2.128][G loss: -0.147]  0:00:13.407396
116 (5, 1) [D loss: -41.996 R -102.813 F 50.445 G 1.037][G loss: -139.174]  0:00:14.282549
117 (5, 1) [D loss: -28.275 R -42.746 F 7.137 G 0.733][G loss: -20.444]  0:00:15.171203
118 (5, 1) [D loss: -44.659 R -89.270 F 30.950 G 1.366][G loss: 3.469]  0:00:16.054308
119 (5, 1) [D loss: -42.003 R -94.867 F 41.651 G 1.121][G loss: -12.176]  0:00:16.953091
120 (5, 1) [D loss: -32.105 R -85.665 F 43.167 G 1.039][G loss: -26.721]  0:00:17.826209
121 (5, 1) [D loss: -39.969 R -80.987 F 31.650 G 0.937][G loss: -4.029]  0:00:18.705919
122 (5, 1) [D loss: -36.738 R -62.113 F 16.093 G 0.928][G loss: -3.224]  0:00:19.596712
123 (5, 1) [D loss: -36.847 R -71.997 F 22.354 G 1.280][G loss: -15.071]  0:00:20.473923
124 (5, 1) [D loss: -34.549 R -44.327 F -9.545 G 1.932][G loss: -3.151]  0:00:21.347588
125 (5, 1) [D loss: -52.426 R -73.156 F 2.480 G 1.825][G loss: 17.053]  0:00:22.235535
126 (5, 1) [D loss: -40.501 R -59.141 F 10.212 G 0.843][G loss: -4.185]  0:00:23.114657
127 (5, 1) [D loss: -37.944 R -98.001 F 49.430 G 1.063][G loss: -43.854]  0:00:23.990067
128 (5, 1) [D loss: -51.206 R -52.259 F -22.870 G 2.392][G loss: -12.286]  0:00:24.863396
129 (5, 1) [D loss: -51.599 R -65.015 F -0.285 G 1.370][G loss: 5.681]  0:00:25.732461
130 (5, 1) [D loss: -33.521 R -40.450 F -26.408 G 3.334][G loss: -31.909]  0:00:26.634908
131 (5, 1) [D loss: -56.992 R -78.336 F 2.798 G 1.855][G loss: -42.914]  0:00:27.506703
132 (5, 1) [D loss: -57.480 R -66.340 F -19.346 G 2.821][G loss: -45.103]  0:00:28.385425
133 (5, 1) [D loss: -63.928 R -89.381 F 9.373 G 1.608][G loss: -42.564]  0:00:29.263847
134 (5, 1) [D loss: -48.759 R -89.675 F 31.675 G 0.924][G loss: -41.814]  0:00:30.182012
135 (5, 1) [D loss: -61.062 R -87.626 F 5.775 G 2.079][G loss: -45.904]  0:00:31.066201
136 (5, 1) [D loss: -42.305 R -81.659 F 22.601 G 1.675][G loss: -56.792]  0:00:31.955644
137 (5, 1) [D loss: -43.307 R -98.750 F 39.790 G 1.565][G loss: -64.826]  0:00:32.837850
138 (5, 1) [D loss: -47.361 R -74.934 F 17.679 G 0.989][G loss: -47.662]  0:00:33.740231
139 (5, 1) [D loss: -45.261 R -70.851 F 14.268 G 1.132][G loss: -52.653]  0:00:34.652420
140 (5, 1) [D loss: -59.488 R -53.017 F -32.318 G 2.585][G loss: -47.076]  0:00:35.528758
141 (5, 1) [D loss: -36.177 R -56.773 F -7.711 G 2.831][G loss: -75.047]  0:00:36.415520
142 (5, 1) [D loss: -57.628 R -82.566 F 7.159 G 1.778][G loss: -46.598]  0:00:37.303986
143 (5, 1) [D loss: -48.723 R -105.277 F 44.735 G 1.182][G loss: -60.894]  0:00:38.174359
144 (5, 1) [D loss: -48.726 R -89.399 F 19.832 G 2.084][G loss: -47.013]  0:00:39.046638
145 (5, 1) [D loss: -39.675 R -102.904 F 46.901 G 1.633][G loss: -83.429]  0:00:39.964287
146 (5, 1) [D loss: -42.322 R -52.201 F -6.062 G 1.594][G loss: -48.284]  0:00:40.844306
147 (5, 1) [D loss: -23.610 R -55.184 F 8.064 G 2.351][G loss: -61.597]  0:00:41.717725
148 (5, 1) [D loss: -48.810 R -68.716 F 6.456 G 1.345][G loss: -24.754]  0:00:42.598964
149 (5, 1) [D loss: -37.880 R -88.144 F 35.443 G 1.482][G loss: -54.992]  0:00:43.482823
150 (5, 1) [D loss: -36.342 R -96.086 F 48.347 G 1.140][G loss: -72.906]  0:00:44.361800
151 (5, 1) [D loss: -37.060 R -94.659 F 44.066 G 1.353][G loss: -46.758]  0:00:45.424268
152 (5, 1) [D loss: -36.548 R -88.940 F 38.368 G 1.402][G loss: -56.899]  0:00:46.309903
153 (5, 1) [D loss: -36.500 R -72.706 F 25.233 G 1.097][G loss: -20.357]  0:00:47.200645
154 (5, 1) [D loss: -36.342 R -116.946 F 69.721 G 1.088][G loss: -52.502]  0:00:48.116866
155 (5, 1) [D loss: -38.131 R -104.540 F 52.880 G 1.353][G loss: -52.336]  0:00:49.020611
156 (5, 1) [D loss: -37.327 R -97.057 F 49.983 G 0.975][G loss: -69.739]  0:00:49.917509
157 (5, 1) [D loss: -39.365 R -90.342 F 38.859 G 1.212][G loss: -53.991]  0:00:50.820573
158 (5, 1) [D loss: -34.852 R -71.918 F 27.093 G 0.997][G loss: -22.977]  0:00:51.701137
159 (5, 1) [D loss: -37.736 R -114.626 F 62.721 G 1.417][G loss: -54.272]  0:00:52.586026
160 (5, 1) [D loss: -37.049 R -109.823 F 58.829 G 1.394][G loss: -71.928]  0:00:53.488343
161 (5, 1) [D loss: -33.977 R -145.923 F 93.547 G 1.840][G loss: -92.828]  0:00:54.371864
162 (5, 1) [D loss: -37.103 R -113.491 F 65.584 G 1.080][G loss: -48.721]  0:00:55.283667
163 (5, 1) [D loss: -35.489 R -98.254 F 53.145 G 0.962][G loss: -80.560]  0:00:56.177119
164 (5, 1) [D loss: -33.262 R -85.877 F 45.320 G 0.730][G loss: -60.712]  0:00:57.062673
165 (5, 1) [D loss: -35.680 R -107.297 F 61.750 G 0.987][G loss: -88.105]  0:00:57.942169
166 (5, 1) [D loss: -46.495 R -156.574 F 90.383 G 1.970][G loss: -114.764]  0:00:58.831568
167 (5, 1) [D loss: -37.125 R -146.997 F 98.574 G 1.130][G loss: -135.060]  0:00:59.870171
168 (5, 1) [D loss: -25.054 R -136.513 F 100.378 G 1.108][G loss: -70.138]  0:01:00.757547
169 (5, 1) [D loss: -40.350 R -135.197 F 84.127 G 1.072][G loss: -122.297]  0:01:01.634659
170 (5, 1) [D loss: -63.396 R -170.601 F 78.445 G 2.876][G loss: -177.831]  0:01:02.522331
171 (5, 1) [D loss: -25.965 R -136.254 F 100.304 G 0.998][G loss: -129.574]  0:01:03.390185
172 (5, 1) [D loss: -34.548 R -165.753 F 118.780 G 1.243][G loss: -125.784]  0:01:04.272087
173 (5, 1) [D loss: -39.649 R -158.511 F 104.691 G 1.417][G loss: -128.467]  0:01:05.165800
174 (5, 1) [D loss: -40.865 R -169.244 F 111.364 G 1.702][G loss: -179.116]  0:01:06.039405
175 (5, 1) [D loss: -27.495 R -124.214 F 90.315 G 0.640][G loss: -107.652]  0:01:06.906239
176 (5, 1) [D loss: -35.410 R -134.442 F 88.286 G 1.075][G loss: -93.485]  0:01:07.786722
177 (5, 1) [D loss: -32.560 R -145.340 F 104.857 G 0.792][G loss: -148.740]  0:01:08.662985
178 (5, 1) [D loss: -30.653 R -140.381 F 98.063 G 1.167][G loss: -121.807]  0:01:09.538534
179 (5, 1) [D loss: -33.812 R -134.824 F 89.094 G 1.192][G loss: -107.507]  0:01:10.432283
180 (5, 1) [D loss: -37.515 R -148.626 F 93.321 G 1.779][G loss: -91.785]  0:01:11.311099
181 (5, 1) [D loss: -29.212 R -137.283 F 89.955 G 1.812][G loss: -80.274]  0:01:12.215820
182 (5, 1) [D loss: -29.207 R -116.523 F 75.212 G 1.210][G loss: -57.540]  0:01:13.110288
183 (5, 1) [D loss: -31.678 R -98.357 F 55.813 G 1.087][G loss: -42.744]  0:01:13.989240
184 (5, 1) [D loss: -29.939 R -82.076 F 42.485 G 0.965][G loss: -40.459]  0:01:14.873298
185 (5, 1) [D loss: -32.224 R -87.539 F 44.683 G 1.063][G loss: -20.176]  0:01:15.754691
186 (5, 1) [D loss: -31.229 R -67.341 F 23.580 G 1.253][G loss: -11.692]  0:01:16.625982
187 (5, 1) [D loss: -31.004 R -69.582 F 26.966 G 1.161][G loss: -24.322]  0:01:17.509226
188 (5, 1) [D loss: -34.934 R -61.513 F 17.598 G 0.898][G loss: -9.751]  0:01:18.390703
189 (5, 1) [D loss: -29.963 R -77.370 F 35.101 G 1.231][G loss: -41.236]  0:01:19.277736
190 (5, 1) [D loss: -27.309 R -75.503 F 37.904 G 1.029][G loss: -29.750]  0:01:20.189715
191 (5, 1) [D loss: -38.705 R -75.433 F 24.045 G 1.268][G loss: -21.840]  0:01:21.070759
192 (5, 1) [D loss: -19.442 R -56.550 F 19.392 G 1.772][G loss: -22.516]  0:01:21.957037
193 (5, 1) [D loss: -24.978 R -78.598 F 45.798 G 0.782][G loss: -41.328]  0:01:22.824651
194 (5, 1) [D loss: -34.121 R -68.879 F 23.344 G 1.141][G loss: -35.858]  0:01:23.725410
195 (5, 1) [D loss: -46.076 R -73.623 F 14.738 G 1.281][G loss: -36.712]  0:01:24.599462
196 (5, 1) [D loss: -25.973 R -66.817 F 25.490 G 1.535][G loss: -40.006]  0:01:25.500609
197 (5, 1) [D loss: -37.639 R -65.460 F 13.288 G 1.453][G loss: -38.048]  0:01:26.390927
198 (5, 1) [D loss: -52.148 R -70.364 F 2.971 G 1.524][G loss: -42.078]  0:01:27.269474
199 (5, 1) [D loss: -56.486 R -61.395 F -18.475 G 2.338][G loss: -26.520]  0:01:28.143718
200 (5, 1) [D loss: -43.606 R -59.304 F -3.573 G 1.927][G loss: -37.632]  0:01:29.015065
201 (5, 1) [D loss: -54.599 R -89.325 F 25.479 G 0.925][G loss: -33.072]  0:01:29.896111
202 (5, 1) [D loss: -50.477 R -65.807 F 0.440 G 1.489][G loss: -30.475]  0:01:30.933255
203 (5, 1) [D loss: -45.869 R -57.705 F -4.547 G 1.638][G loss: -41.519]  0:01:31.815462
204 (5, 1) [D loss: -46.921 R -66.304 F -6.860 G 2.624][G loss: -57.171]  0:01:32.708896
205 (5, 1) [D loss: -40.693 R -86.962 F 35.199 G 1.107][G loss: -55.768]  0:01:33.576176
206 (5, 1) [D loss: -33.578 R -68.264 F 15.676 G 1.901][G loss: -49.050]  0:01:34.443612
207 (5, 1) [D loss: -31.954 R -70.562 F 27.121 G 1.149][G loss: -53.062]  0:01:35.350067
208 (5, 1) [D loss: -34.367 R -95.220 F 51.180 G 0.967][G loss: -62.566]  0:01:36.238609
209 (5, 1) [D loss: -39.279 R -69.128 F 12.574 G 1.727][G loss: -68.292]  0:01:37.110059
210 (5, 1) [D loss: -25.088 R -48.291 F 5.484 G 1.772][G loss: -45.571]  0:01:37.983076
211 (5, 1) [D loss: -30.421 R -92.928 F 54.847 G 0.766][G loss: -52.591]  0:01:38.871996
212 (5, 1) [D loss: -33.625 R -94.016 F 51.305 G 0.909][G loss: -54.679]  0:01:39.763959
213 (5, 1) [D loss: -28.694 R -80.976 F 41.217 G 1.107][G loss: -62.403]  0:01:40.648400
214 (5, 1) [D loss: -35.426 R -90.174 F 46.879 G 0.787][G loss: -41.680]  0:01:41.517866
215 (5, 1) [D loss: -33.687 R -107.841 F 66.300 G 0.785][G loss: -61.622]  0:01:42.396051
216 (5, 1) [D loss: -35.277 R -107.687 F 62.382 G 1.003][G loss: -67.777]  0:01:43.295574
217 (5, 1) [D loss: -33.946 R -114.954 F 71.465 G 0.954][G loss: -58.383]  0:01:44.177808
218 (5, 1) [D loss: -26.833 R -78.112 F 42.692 G 0.859][G loss: -77.255]  0:01:45.060282
219 (5, 1) [D loss: -23.450 R -98.390 F 68.668 G 0.627][G loss: -36.262]  0:01:46.076550
220 (5, 1) [D loss: -27.725 R -102.271 F 66.022 G 0.852][G loss: -63.038]  0:01:46.948215
221 (5, 1) [D loss: -26.844 R -119.043 F 86.024 G 0.617][G loss: -95.512]  0:01:47.829339
222 (5, 1) [D loss: -29.317 R -95.718 F 60.285 G 0.612][G loss: -61.974]  0:01:48.707191
223 (5, 1) [D loss: -21.772 R -139.435 F 106.477 G 1.119][G loss: -89.860]  0:01:49.582345
224 (5, 1) [D loss: -26.172 R -119.666 F 86.198 G 0.730][G loss: -80.386]  0:01:50.458938
225 (5, 1) [D loss: -28.205 R -139.433 F 102.956 G 0.827][G loss: -111.108]  0:01:51.337614
226 (5, 1) [D loss: -25.235 R -120.861 F 88.053 G 0.757][G loss: -91.438]  0:01:52.215617
227 (5, 1) [D loss: -25.785 R -112.336 F 78.925 G 0.763][G loss: -86.551]  0:01:53.096789
228 (5, 1) [D loss: -26.694 R -108.659 F 75.697 G 0.627][G loss: -87.017]  0:01:53.965770
229 (5, 1) [D loss: -31.088 R -125.516 F 85.991 G 0.844][G loss: -104.823]  0:01:54.848219
230 (5, 1) [D loss: -22.926 R -115.238 F 86.106 G 0.621][G loss: -94.325]  0:01:55.735271
231 (5, 1) [D loss: -23.607 R -122.741 F 93.047 G 0.609][G loss: -86.345]  0:01:56.621623
232 (5, 1) [D loss: -26.579 R -109.302 F 73.530 G 0.919][G loss: -63.882]  0:01:57.499832
233 (5, 1) [D loss: -23.069 R -119.056 F 87.918 G 0.807][G loss: -98.090]  0:01:58.385159
234 (5, 1) [D loss: -27.479 R -113.154 F 79.847 G 0.583][G loss: -86.415]  0:01:59.266457
235 (5, 1) [D loss: -26.334 R -114.159 F 79.541 G 0.828][G loss: -83.169]  0:02:00.130311
236 (5, 1) [D loss: -23.603 R -108.927 F 78.104 G 0.722][G loss: -72.527]  0:02:01.162103
237 (5, 1) [D loss: -24.777 R -95.152 F 64.307 G 0.607][G loss: -64.399]  0:02:02.043043
238 (5, 1) [D loss: -24.429 R -96.703 F 66.037 G 0.624][G loss: -72.176]  0:02:02.935980
239 (5, 1) [D loss: -27.131 R -108.026 F 73.706 G 0.719][G loss: -72.154]  0:02:03.817682
240 (5, 1) [D loss: -23.751 R -110.270 F 79.211 G 0.731][G loss: -79.539]  0:02:04.697731
241 (5, 1) [D loss: -31.201 R -101.416 F 62.262 G 0.795][G loss: -80.189]  0:02:05.589304
242 (5, 1) [D loss: -33.514 R -95.395 F 56.047 G 0.583][G loss: -86.154]  0:02:06.466101
243 (5, 1) [D loss: -28.309 R -125.985 F 88.650 G 0.903][G loss: -93.497]  0:02:07.326769
244 (5, 1) [D loss: -27.135 R -115.818 F 80.892 G 0.779][G loss: -88.726]  0:02:08.187113
245 (5, 1) [D loss: -14.304 R -127.728 F 102.553 G 1.087][G loss: -89.946]  0:02:09.044557
246 (5, 1) [D loss: -28.668 R -106.124 F 66.538 G 1.092][G loss: -65.386]  0:02:09.903910
247 (5, 1) [D loss: -24.525 R -93.165 F 63.372 G 0.527][G loss: -59.756]  0:02:10.798376
248 (5, 1) [D loss: -42.720 R -125.057 F 69.978 G 1.236][G loss: -134.119]  0:02:11.667969
249 (5, 1) [D loss: -19.679 R -76.548 F 51.203 G 0.567][G loss: -62.046]  0:02:12.535531
250 (5, 1) [D loss: -26.741 R -102.288 F 70.466 G 0.508][G loss: -61.959]  0:02:13.397449
251 (5, 1) [D loss: -23.656 R -98.425 F 67.044 G 0.773][G loss: -54.606]  0:02:14.308502
252 (5, 1) [D loss: -22.935 R -101.063 F 70.933 G 0.719][G loss: -74.081]  0:02:15.170079
253 (5, 1) [D loss: -21.759 R -101.731 F 72.044 G 0.793][G loss: -68.832]  0:02:16.098213
254 (5, 1) [D loss: -24.600 R -111.377 F 81.562 G 0.521][G loss: -77.093]  0:02:16.976895
255 (5, 1) [D loss: -22.663 R -115.059 F 82.862 G 0.953][G loss: -75.017]  0:02:17.852139
256 (5, 1) [D loss: -23.717 R -101.482 F 68.777 G 0.899][G loss: -63.670]  0:02:18.733982
257 (5, 1) [D loss: -28.541 R -109.735 F 75.398 G 0.580][G loss: -86.875]  0:02:19.611792
258 (5, 1) [D loss: -25.245 R -97.089 F 65.528 G 0.632][G loss: -68.762]  0:02:20.504622
259 (5, 1) [D loss: -27.279 R -88.502 F 54.617 G 0.661][G loss: -58.268]  0:02:21.378717
260 (5, 1) [D loss: -23.660 R -95.321 F 59.980 G 1.168][G loss: -67.079]  0:02:22.238370
261 (5, 1) [D loss: -21.471 R -114.322 F 85.427 G 0.742][G loss: -90.651]  0:02:23.114103
262 (5, 1) [D loss: -22.219 R -108.982 F 78.408 G 0.836][G loss: -77.800]  0:02:23.992693
263 (5, 1) [D loss: -29.315 R -105.069 F 71.182 G 0.457][G loss: -73.280]  0:02:24.883435
264 (5, 1) [D loss: -28.888 R -87.116 F 54.536 G 0.369][G loss: -56.608]  0:02:25.765377
265 (5, 1) [D loss: -23.437 R -95.785 F 65.345 G 0.700][G loss: -71.133]  0:02:26.666974
266 (5, 1) [D loss: -32.380 R -88.827 F 49.119 G 0.733][G loss: -58.715]  0:02:27.552672
267 (5, 1) [D loss: -26.609 R -90.294 F 57.300 G 0.638][G loss: -73.495]  0:02:28.427863
268 (5, 1) [D loss: -22.041 R -94.263 F 67.401 G 0.482][G loss: -66.186]  0:02:29.300377
269 (5, 1) [D loss: -22.443 R -79.817 F 53.029 G 0.434][G loss: -41.009]  0:02:30.189935
270 (5, 1) [D loss: -31.058 R -63.144 F 19.430 G 1.266][G loss: -48.159]  0:02:31.214943
271 (5, 1) [D loss: -28.341 R -85.126 F 48.548 G 0.824][G loss: -52.577]  0:02:32.103173
272 (5, 1) [D loss: -24.939 R -70.657 F 40.681 G 0.504][G loss: -36.725]  0:02:33.000534
273 (5, 1) [D loss: -22.904 R -73.574 F 46.459 G 0.421][G loss: -46.087]  0:02:33.879666
274 (5, 1) [D loss: -25.136 R -62.691 F 31.156 G 0.640][G loss: -37.450]  0:02:34.767804
275 (5, 1) [D loss: -24.481 R -78.218 F 47.380 G 0.636][G loss: -49.256]  0:02:35.670239
276 (5, 1) [D loss: -26.574 R -82.083 F 49.353 G 0.616][G loss: -53.665]  0:02:36.541461
277 (5, 1) [D loss: -29.053 R -97.305 F 61.425 G 0.683][G loss: -57.843]  0:02:37.417797
278 (5, 1) [D loss: -28.884 R -100.005 F 64.150 G 0.697][G loss: -68.618]  0:02:38.310387
279 (5, 1) [D loss: -25.545 R -113.663 F 80.251 G 0.787][G loss: -69.685]  0:02:39.186663
280 (5, 1) [D loss: -28.673 R -94.401 F 58.607 G 0.712][G loss: -67.328]  0:02:40.075441
281 (5, 1) [D loss: -24.197 R -127.508 F 93.450 G 0.986][G loss: -87.784]  0:02:40.977155
282 (5, 1) [D loss: -35.607 R -124.951 F 77.522 G 1.182][G loss: -116.877]  0:02:41.840881
283 (5, 1) [D loss: -36.165 R -158.259 F 106.994 G 1.510][G loss: -129.008]  0:02:42.709652
284 (5, 1) [D loss: -47.801 R -135.541 F 74.540 G 1.320][G loss: -128.568]  0:02:43.585450
285 (5, 1) [D loss: -59.061 R -167.278 F 82.483 G 2.573][G loss: -168.690]  0:02:44.467033
286 (5, 1) [D loss: -66.730 R -226.024 F 128.150 G 3.114][G loss: -254.833]  0:02:45.356881
287 (5, 1) [D loss: -52.576 R -153.951 F 74.807 G 2.657][G loss: -228.724]  0:02:46.383197
288 (5, 1) [D loss: -54.244 R -180.352 F 105.338 G 2.077][G loss: -235.740]  0:02:47.278977
289 (5, 1) [D loss: -44.086 R -164.235 F 90.762 G 2.939][G loss: -240.867]  0:02:48.170094
290 (5, 1) [D loss: -54.562 R -207.748 F 132.102 G 2.108][G loss: -268.720]  0:02:49.037239
291 (5, 1) [D loss: -62.312 R -245.181 F 153.968 G 2.890][G loss: -302.417]  0:02:49.909494
292 (5, 1) [D loss: -65.678 R -186.140 F 95.413 G 2.505][G loss: -182.379]  0:02:50.813817
293 (5, 1) [D loss: -60.915 R -149.356 F 33.450 G 5.499][G loss: -15.990]  0:02:51.699378
294 (5, 1) [D loss: -67.552 R -102.403 F 7.075 G 2.778][G loss: -24.115]  0:02:52.578698
295 (5, 1) [D loss: -90.861 R -137.755 F 3.186 G 4.371][G loss: -6.159]  0:02:53.439883
296 (5, 1) [D loss: -72.068 R -192.081 F 48.312 G 7.170][G loss: -12.688]  0:02:54.312117
297 (5, 1) [D loss: -97.646 R -196.098 F 49.842 G 4.861][G loss: -7.997]  0:02:55.178845
298 (5, 1) [D loss: -122.173 R -272.275 F 60.569 G 8.953][G loss: 15.001]  0:02:56.080723
299 (5, 1) [D loss: -87.078 R -199.309 F 28.022 G 8.421][G loss: 21.826]  0:02:56.956217
300 (5, 1) [D loss: -54.733 R -98.239 F -0.255 G 4.376][G loss: 3.477]  0:02:57.845313
301 (5, 1) [D loss: -53.487 R -95.220 F 22.737 G 1.900][G loss: 21.561]  0:02:58.731926
302 (5, 1) [D loss: -43.108 R -18.048 F -38.183 G 1.312][G loss: 48.565]  0:02:59.636343
303 (5, 1) [D loss: -47.245 R -38.109 F -38.694 G 2.956][G loss: 42.515]  0:03:00.579607
304 (5, 1) [D loss: -42.731 R -39.790 F -17.317 G 1.438][G loss: 51.230]  0:03:01.556588
305 (5, 1) [D loss: -52.070 R -5.355 F -71.963 G 2.525][G loss: 120.897]  0:03:02.447358
306 (5, 1) [D loss: -63.780 R -33.487 F -65.312 G 3.502][G loss: 21.086]  0:03:03.340014
307 (5, 1) [D loss: -82.261 R 10.854 F -107.768 G 1.465][G loss: 165.036]  0:03:04.214796
308 (5, 1) [D loss: -51.236 R -19.821 F -51.438 G 2.002][G loss: 29.703]  0:03:05.093371
309 (5, 1) [D loss: -83.527 R -66.590 F -78.115 G 6.118][G loss: -19.059]  0:03:05.999295
310 (5, 1) [D loss: -184.403 R -58.788 F -282.619 G 15.700][G loss: -104.865]  0:03:06.877071
311 (5, 1) [D loss: -133.456 R -39.136 F -127.777 G 3.346][G loss: -39.540]  0:03:07.750020
312 (5, 1) [D loss: -85.933 R -38.717 F -111.791 G 6.457][G loss: -38.285]  0:03:08.640287
313 (5, 1) [D loss: -86.086 R -28.813 F -121.659 G 6.439][G loss: -85.199]  0:03:09.539575
314 (5, 1) [D loss: -144.748 R -56.903 F -166.651 G 7.881][G loss: -122.071]  0:03:10.431095
315 (5, 1) [D loss: -67.983 R -34.580 F -84.470 G 5.107][G loss: -67.168]  0:03:11.323602
316 (5, 1) [D loss: -109.033 R -32.638 F -105.341 G 2.895][G loss: -77.067]  0:03:12.206232
317 (5, 1) [D loss: -155.764 R -9.893 F -264.729 G 11.886][G loss: -114.714]  0:03:13.072491
318 (5, 1) [D loss: -73.733 R -72.508 F -102.106 G 10.088][G loss: -98.708]  0:03:13.962849
319 (5, 1) [D loss: -105.364 R -13.621 F -128.796 G 3.705][G loss: -74.390]  0:03:14.861452
320 (5, 1) [D loss: -46.230 R -19.497 F -45.794 G 1.906][G loss: -27.232]  0:03:15.766199
321 (5, 1) [D loss: -67.488 R -27.379 F -70.458 G 3.035][G loss: -31.743]  0:03:16.787501
322 (5, 1) [D loss: -65.594 R -36.135 F -53.388 G 2.393][G loss: -52.900]  0:03:17.679561
323 (5, 1) [D loss: -88.563 R -41.467 F -75.202 G 2.811][G loss: -99.988]  0:03:18.582492
324 (5, 1) [D loss: -53.845 R -72.003 F -11.312 G 2.947][G loss: -80.713]  0:03:19.483270
325 (5, 1) [D loss: -39.233 R -145.064 F 96.744 G 0.909][G loss: -96.260]  0:03:20.378760
326 (5, 1) [D loss: -39.726 R -106.320 F 53.485 G 1.311][G loss: -32.760]  0:03:21.284132
327 (5, 1) [D loss: -37.460 R -146.181 F 93.184 G 1.554][G loss: -75.864]  0:03:22.172232
328 (5, 1) [D loss: -37.422 R -148.921 F 95.450 G 1.605][G loss: -69.882]  0:03:23.051616
329 (5, 1) [D loss: -38.952 R -151.844 F 97.916 G 1.498][G loss: -92.174]  0:03:23.956104
330 (5, 1) [D loss: -37.965 R -164.877 F 111.371 G 1.554][G loss: -86.212]  0:03:24.836075
331 (5, 1) [D loss: -40.571 R -121.638 F 71.312 G 0.976][G loss: -83.705]  0:03:25.709787
332 (5, 1) [D loss: -32.614 R -175.785 F 134.283 G 0.889][G loss: -137.821]  0:03:26.610924
333 (5, 1) [D loss: -44.123 R -197.670 F 139.720 G 1.383][G loss: -142.417]  0:03:27.499467
334 (5, 1) [D loss: -44.354 R -210.996 F 152.612 G 1.403][G loss: -179.618]  0:03:28.392604
335 (5, 1) [D loss: -40.555 R -157.171 F 109.174 G 0.744][G loss: -132.376]  0:03:29.278968
336 (5, 1) [D loss: -56.325 R -206.244 F 135.021 G 1.490][G loss: -204.043]  0:03:30.163217
337 (5, 1) [D loss: -59.234 R -217.815 F 137.290 G 2.129][G loss: -246.744]  0:03:31.064259
338 (5, 1) [D loss: -51.543 R -277.405 F 199.954 G 2.591][G loss: -287.087]  0:03:31.970269
339 (5, 1) [D loss: -52.928 R -252.599 F 186.872 G 1.280][G loss: -310.625]  0:03:32.874793
340 (5, 1) [D loss: -62.752 R -287.472 F 195.011 G 2.971][G loss: -334.230]  0:03:33.779527
341 (5, 1) [D loss: -44.453 R -342.816 F 263.037 G 3.533][G loss: -292.185]  0:03:34.686414
342 (5, 1) [D loss: -54.783 R -300.567 F 230.165 G 1.562][G loss: -356.299]  0:03:35.586602
343 (5, 1) [D loss: -47.178 R -335.488 F 270.235 G 1.807][G loss: -364.421]  0:03:36.634707
344 (5, 1) [D loss: -45.989 R -299.741 F 239.541 G 1.421][G loss: -260.377]  0:03:37.513939
345 (5, 1) [D loss: -48.745 R -264.455 F 200.331 G 1.538][G loss: -296.797]  0:03:38.418014
346 (5, 1) [D loss: -35.320 R -244.233 F 194.923 G 1.399][G loss: -259.847]  0:03:39.333454
347 (5, 1) [D loss: -43.614 R -269.015 F 212.911 G 1.249][G loss: -276.471]  0:03:40.211416
348 (5, 1) [D loss: -37.180 R -217.010 F 160.317 G 1.951][G loss: -87.587]  0:03:41.123935
349 (5, 1) [D loss: -41.699 R -211.342 F 152.341 G 1.730][G loss: -122.133]  0:03:42.030469
350 (5, 1) [D loss: -33.725 R -188.419 F 135.874 G 1.882][G loss: -88.791]  0:03:42.930275
351 (5, 1) [D loss: -38.865 R -163.657 F 110.958 G 1.383][G loss: -60.392]  0:03:43.834256
352 (5, 1) [D loss: -60.598 R -214.768 F 126.168 G 2.800][G loss: -79.344]  0:03:44.734017
353 (5, 1) [D loss: -34.619 R -105.128 F 57.612 G 1.290][G loss: -18.692]  0:03:45.633875
354 (5, 1) [D loss: -31.555 R -24.302 F -13.580 G 0.633][G loss: 37.659]  0:03:46.674830
355 (5, 1) [D loss: -29.773 R 39.245 F -78.187 G 0.917][G loss: 39.506]  0:03:47.570280
356 (5, 1) [D loss: -44.028 R -36.878 F -21.706 G 1.456][G loss: 74.464]  0:03:48.465481
357 (5, 1) [D loss: -39.600 R -1.207 F -53.919 G 1.553][G loss: 81.127]  0:03:49.374353
358 (5, 1) [D loss: -41.871 R -20.501 F -36.527 G 1.516][G loss: 47.163]  0:03:50.277648
359 (5, 1) [D loss: -36.856 R -7.590 F -63.966 G 3.470][G loss: 42.212]  0:03:51.177657
360 (5, 1) [D loss: -58.459 R -48.647 F -42.788 G 3.298][G loss: 53.843]  0:03:52.088280
361 (5, 1) [D loss: -39.823 R 17.700 F -79.029 G 2.151][G loss: 70.572]  0:03:52.991553
362 (5, 1) [D loss: -54.363 R 61.976 F -148.435 G 3.210][G loss: 149.636]  0:03:53.946373
363 (5, 1) [D loss: -45.539 R 72.408 F -150.726 G 3.278][G loss: 111.062]  0:03:54.833463
364 (5, 1) [D loss: -63.650 R 21.258 F -115.170 G 3.026][G loss: 72.666]  0:03:55.711468
365 (5, 1) [D loss: -81.436 R 14.404 F -117.989 G 2.215][G loss: 94.880]  0:03:56.621835
366 (5, 1) [D loss: -56.043 R 12.884 F -86.832 G 1.791][G loss: 84.206]  0:03:57.525233
367 (5, 1) [D loss: -50.767 R -7.066 F -60.250 G 1.655][G loss: 51.149]  0:03:58.415967
368 (5, 1) [D loss: -57.588 R -0.805 F -93.153 G 3.637][G loss: -3.900]  0:03:59.334737
369 (5, 1) [D loss: -59.975 R -26.410 F -65.284 G 3.172][G loss: 18.125]  0:04:00.242549
370 (5, 1) [D loss: -65.365 R 18.338 F -102.108 G 1.841][G loss: 27.164]  0:04:01.146695
371 (5, 1) [D loss: -65.135 R -4.175 F -81.159 G 2.020][G loss: 32.722]  0:04:02.065647
372 (5, 1) [D loss: -43.251 R -26.423 F -48.378 G 3.155][G loss: -5.480]  0:04:02.974382
373 (5, 1) [D loss: -48.935 R 7.168 F -95.921 G 3.982][G loss: -12.366]  0:04:03.865524
374 (5, 1) [D loss: -78.978 R -24.278 F -83.685 G 2.899][G loss: -15.614]  0:04:04.768917
375 (5, 1) [D loss: -60.310 R -35.171 F -46.435 G 2.130][G loss: -41.025]  0:04:05.670382
376 (5, 1) [D loss: -65.450 R -19.303 F -67.662 G 2.151][G loss: -48.450]  0:04:06.693595
377 (5, 1) [D loss: -73.859 R -60.560 F -34.047 G 2.075][G loss: -78.868]  0:04:07.586873
378 (5, 1) [D loss: -47.984 R -43.796 F -42.266 G 3.808][G loss: -40.566]  0:04:08.475605
379 (5, 1) [D loss: -60.056 R -40.424 F -39.526 G 1.989][G loss: -62.448]  0:04:09.373284
380 (5, 1) [D loss: -42.486 R -79.057 F 22.178 G 1.439][G loss: -83.313]  0:04:10.276622
381 (5, 1) [D loss: -47.782 R -96.715 F 29.833 G 1.910][G loss: -86.270]  0:04:11.171454
382 (5, 1) [D loss: -44.249 R -84.010 F 21.520 G 1.824][G loss: -77.313]  0:04:12.081905
383 (5, 1) [D loss: -40.844 R -138.376 F 84.155 G 1.338][G loss: -108.608]  0:04:12.975864
384 (5, 1) [D loss: -39.437 R -112.416 F 61.309 G 1.167][G loss: -68.268]  0:04:13.885990
385 (5, 1) [D loss: -40.186 R -215.599 F 157.165 G 1.825][G loss: -135.226]  0:04:14.795401
386 (5, 1) [D loss: -47.875 R -213.016 F 147.386 G 1.776][G loss: -180.994]  0:04:15.689232
387 (5, 1) [D loss: -52.342 R -274.005 F 200.594 G 2.107][G loss: -200.933]  0:04:16.706324
388 (5, 1) [D loss: -52.782 R -359.294 F 258.866 G 4.765][G loss: -236.619]  0:04:17.626205
389 (5, 1) [D loss: -49.099 R -246.729 F 187.439 G 1.019][G loss: -257.009]  0:04:18.524013
390 (5, 1) [D loss: -95.060 R -414.721 F 264.400 G 5.526][G loss: -361.819]  0:04:19.411881
391 (5, 1) [D loss: -72.270 R -400.453 F 290.755 G 3.743][G loss: -395.743]  0:04:20.305665
392 (5, 1) [D loss: -53.798 R -368.983 F 252.497 G 6.269][G loss: -285.625]  0:04:21.198768
393 (5, 1) [D loss: -89.490 R -286.704 F 175.414 G 2.180][G loss: -364.730]  0:04:22.120352
394 (5, 1) [D loss: -110.190 R -467.758 F 280.349 G 7.722][G loss: -440.462]  0:04:23.017876
395 (5, 1) [D loss: -142.702 R -506.047 F 279.802 G 8.354][G loss: -589.887]  0:04:23.946078
396 (5, 1) [D loss: -134.083 R -474.355 F 279.526 G 6.075][G loss: -657.304]  0:04:24.851359
397 (5, 1) [D loss: -112.560 R -387.740 F 217.151 G 5.803][G loss: -481.669]  0:04:25.747488
398 (5, 1) [D loss: -104.254 R -493.073 F 303.796 G 8.502][G loss: -493.549]  0:04:26.672908
399 (5, 1) [D loss: -103.605 R -413.806 F 253.933 G 5.627][G loss: -518.940]  0:04:27.583218
400 (5, 1) [D loss: -101.091 R -247.788 F 110.514 G 3.618][G loss: -192.307]  0:04:28.475465
401 (5, 1) [D loss: -109.339 R -276.449 F 111.470 G 5.564][G loss: -125.026]  0:04:29.360290
402 (5, 1) [D loss: -123.104 R -361.816 F 116.373 G 12.234][G loss: -66.189]  0:04:30.260841
403 (5, 1) [D loss: -137.505 R -367.746 F 127.685 G 10.256][G loss: -103.703]  0:04:31.171584
404 (5, 1) [D loss: -192.528 R -452.547 F 133.343 G 12.668][G loss: -75.053]  0:04:32.112611
405 (5, 1) [D loss: -137.779 R -300.435 F 112.705 G 4.995][G loss: -69.232]  0:04:33.034841
406 (5, 1) [D loss: -148.083 R -355.751 F 128.413 G 7.925][G loss: -75.590]  0:04:33.936431
407 (5, 1) [D loss: -136.551 R -360.073 F 154.612 G 6.891][G loss: -118.051]  0:04:34.861438
408 (5, 1) [D loss: -124.500 R -275.867 F 101.609 G 4.976][G loss: -65.777]  0:04:35.769187
409 (5, 1) [D loss: -70.202 R -238.052 F 114.543 G 5.331][G loss: -69.006]  0:04:36.708789
410 (5, 1) [D loss: -93.530 R -232.799 F 94.188 G 4.508][G loss: -31.429]  0:04:37.637260
411 (5, 1) [D loss: -98.075 R -225.903 F 71.501 G 5.633][G loss: -38.289]  0:04:38.580312
412 (5, 1) [D loss: -81.710 R -143.156 F 43.454 G 1.799][G loss: 7.637]  0:04:39.494578
413 (5, 1) [D loss: -115.412 R -211.426 F 23.214 G 7.280][G loss: 9.079]  0:04:40.443762
414 (5, 1) [D loss: -121.283 R -157.304 F -23.781 G 5.980][G loss: 9.997]  0:04:41.357211
415 (5, 1) [D loss: -102.286 R -186.998 F 48.312 G 3.640][G loss: -5.766]  0:04:42.292201
416 (5, 1) [D loss: -79.150 R -153.237 F 26.529 G 4.756][G loss: -13.860]  0:04:43.185364
417 (5, 1) [D loss: -73.875 R -223.234 F 116.748 G 3.261][G loss: -165.461]  0:04:44.088575
418 (5, 1) [D loss: -106.672 R -132.867 F -23.180 G 4.937][G loss: -32.210]  0:04:44.990752
419 (5, 1) [D loss: -91.029 R -132.011 F -14.677 G 5.566][G loss: -86.023]  0:04:45.903403
420 (5, 1) [D loss: -106.290 R -187.450 F 29.351 G 5.181][G loss: -99.326]  0:04:46.833400
421 (5, 1) [D loss: -142.815 R -187.344 F -58.137 G 10.267][G loss: -130.882]  0:04:47.738802
422 (5, 1) [D loss: -132.569 R -223.776 F 13.262 G 7.794][G loss: -201.194]  0:04:48.674789
423 (5, 1) [D loss: -110.809 R -206.795 F 62.724 G 3.326][G loss: -211.444]  0:04:49.587774
424 (5, 1) [D loss: -114.938 R -219.434 F 24.884 G 7.961][G loss: -266.827]  0:04:50.531329
425 (5, 1) [D loss: -130.992 R -214.872 F 11.581 G 7.230][G loss: -281.568]  0:04:51.456211
426 (5, 1) [D loss: -69.992 R -200.960 F 27.190 G 10.378][G loss: -157.329]  0:04:52.498912
427 (5, 1) [D loss: -126.982 R -199.727 F 34.452 G 3.829][G loss: -269.278]  0:04:53.408208
428 (5, 1) [D loss: -91.826 R -189.944 F 29.363 G 6.876][G loss: -230.309]  0:04:54.312768
429 (5, 1) [D loss: -69.891 R -218.446 F 86.709 G 6.185][G loss: -194.211]  0:04:55.209383
430 (5, 1) [D loss: -55.439 R -135.876 F 50.710 G 2.973][G loss: -157.214]  0:04:56.118200
431 (5, 1) [D loss: -63.104 R -127.140 F 46.135 G 1.790][G loss: -130.941]  0:04:57.047800
432 (5, 1) [D loss: -77.801 R -110.515 F 5.131 G 2.758][G loss: -118.272]  0:04:57.960835
433 (5, 1) [D loss: -53.483 R -95.087 F 20.109 G 2.150][G loss: -102.615]  0:04:58.899506
434 (5, 1) [D loss: -51.603 R -95.561 F 25.763 G 1.820][G loss: -87.895]  0:04:59.820902
435 (5, 1) [D loss: -39.107 R -54.163 F -0.847 G 1.590][G loss: -13.236]  0:05:00.713440
436 (5, 1) [D loss: -44.108 R -46.424 F -13.561 G 1.588][G loss: 27.764]  0:05:01.623011
437 (5, 1) [D loss: -44.449 R -35.514 F -18.893 G 0.996][G loss: 39.975]  0:05:02.525243
438 (5, 1) [D loss: -51.528 R -78.022 F 5.236 G 2.126][G loss: -25.086]  0:05:03.421343
439 (5, 1) [D loss: -48.621 R -132.257 F 67.148 G 1.649][G loss: -36.890]  0:05:04.343241
440 (5, 1) [D loss: -43.082 R -123.377 F 67.657 G 1.264][G loss: -63.690]  0:05:05.227627
441 (5, 1) [D loss: -37.536 R -109.723 F 55.329 G 1.686][G loss: -62.556]  0:05:06.130415
442 (5, 1) [D loss: -39.400 R -120.142 F 69.626 G 1.112][G loss: -67.638]  0:05:07.159149
443 (5, 1) [D loss: -57.128 R -154.798 F 70.706 G 2.696][G loss: -45.293]  0:05:08.088216
444 (5, 1) [D loss: -55.488 R 25.462 F -104.391 G 2.344][G loss: 87.483]  0:05:08.996046
445 (5, 1) [D loss: -40.814 R -146.005 F 87.425 G 1.777][G loss: -77.591]  0:05:09.915385
446 (5, 1) [D loss: -39.512 R -113.410 F 60.888 G 1.301][G loss: -51.653]  0:05:10.815301
447 (5, 1) [D loss: -35.220 R -112.101 F 66.048 G 1.083][G loss: -77.177]  0:05:11.755307
448 (5, 1) [D loss: -26.795 R -139.063 F 108.031 G 0.424][G loss: -118.376]  0:05:12.658421
449 (5, 1) [D loss: -36.675 R -135.992 F 90.836 G 0.848][G loss: -90.323]  0:05:13.551365
450 (5, 1) [D loss: -37.066 R -99.964 F 54.871 G 0.803][G loss: -44.767]  0:05:14.452402
451 (5, 1) [D loss: -34.625 R -72.443 F 27.425 G 1.039][G loss: -22.520]  0:05:15.345041
452 (5, 1) [D loss: -33.180 R -66.770 F 21.108 G 1.248][G loss: -24.192]  0:05:16.245019
453 (5, 1) [D loss: -37.748 R -49.264 F -1.712 G 1.323][G loss: -3.029]  0:05:17.162810
454 (5, 1) [D loss: -26.412 R -17.546 F -18.052 G 0.919][G loss: 19.602]  0:05:18.079739
455 (5, 1) [D loss: -30.216 R -14.845 F -24.191 G 0.882][G loss: 29.392]  0:05:18.998734
456 (5, 1) [D loss: -41.986 R -37.946 F -14.385 G 1.034][G loss: 10.996]  0:05:19.898378
457 (5, 1) [D loss: -39.790 R -78.392 F 28.175 G 1.043][G loss: -32.631]  0:05:20.771398
458 (5, 1) [D loss: -30.210 R -95.071 F 56.401 G 0.846][G loss: -66.021]  0:05:21.670051
459 (5, 1) [D loss: -30.714 R -126.347 F 85.182 G 1.045][G loss: -97.784]  0:05:22.721712
460 (5, 1) [D loss: -31.053 R -104.006 F 65.496 G 0.746][G loss: -86.558]  0:05:23.633544
461 (5, 1) [D loss: -39.012 R -142.838 F 94.305 G 0.952][G loss: -90.353]  0:05:24.518381
462 (5, 1) [D loss: -34.591 R -142.985 F 98.934 G 0.946][G loss: -97.764]  0:05:25.410439
463 (5, 1) [D loss: -30.432 R -157.877 F 118.493 G 0.895][G loss: -132.575]  0:05:26.307781
464 (5, 1) [D loss: -23.496 R -138.098 F 104.586 G 1.002][G loss: -129.651]  0:05:27.218218
465 (5, 1) [D loss: -35.163 R -98.385 F 45.992 G 1.723][G loss: -52.361]  0:05:28.113605
466 (5, 1) [D loss: -37.538 R -104.395 F 58.459 G 0.840][G loss: -53.411]  0:05:28.994897
467 (5, 1) [D loss: -34.399 R -68.291 F 25.629 G 0.826][G loss: -6.400]  0:05:29.902317
468 (5, 1) [D loss: -34.694 R -73.764 F 29.702 G 0.937][G loss: -10.677]  0:05:30.792218
469 (5, 1) [D loss: -23.231 R -26.913 F -9.787 G 1.347][G loss: -11.706]  0:05:31.691342
470 (5, 1) [D loss: -29.237 R -20.711 F -20.796 G 1.227][G loss: 6.295]  0:05:32.623822
471 (5, 1) [D loss: -23.036 R -68.807 F 38.088 G 0.768][G loss: -64.755]  0:05:33.548179
472 (5, 1) [D loss: -39.903 R -45.446 F -16.027 G 2.157][G loss: -8.238]  0:05:34.466870
473 (5, 1) [D loss: -30.850 R -84.555 F 47.820 G 0.588][G loss: -54.891]  0:05:35.383762
474 (5, 1) [D loss: -29.454 R -100.822 F 62.314 G 0.905][G loss: -26.875]  0:05:36.297554
475 (5, 1) [D loss: -27.259 R -55.611 F 18.429 G 0.992][G loss: -35.525]  0:05:37.235029
476 (5, 1) [D loss: -23.278 R -60.069 F 25.271 G 1.152][G loss: -55.386]  0:05:38.139772
477 (5, 1) [D loss: -31.117 R -85.552 F 45.848 G 0.859][G loss: -48.437]  0:05:39.051859
478 (5, 1) [D loss: -32.780 R -122.704 F 77.891 G 1.203][G loss: -46.490]  0:05:39.958297
479 (5, 1) [D loss: -34.238 R -136.998 F 90.016 G 1.274][G loss: -97.368]  0:05:40.873698
480 (5, 1) [D loss: -34.181 R -159.499 F 117.013 G 0.831][G loss: -161.384]  0:05:41.803736
481 (5, 1) [D loss: -38.351 R -162.377 F 111.466 G 1.256][G loss: -140.254]  0:05:42.752267
482 (5, 1) [D loss: -33.072 R -180.653 F 132.652 G 1.493][G loss: -119.977]  0:05:43.670549
483 (5, 1) [D loss: -47.681 R -209.465 F 149.470 G 1.231][G loss: -230.103]  0:05:44.603487
484 (5, 1) [D loss: -32.197 R -161.565 F 120.248 G 0.912][G loss: -155.297]  0:05:45.544558
485 (5, 1) [D loss: -36.333 R -227.361 F 176.793 G 1.424][G loss: -218.630]  0:05:46.474665
486 (5, 1) [D loss: -31.130 R -197.332 F 155.382 G 1.082][G loss: -149.826]  0:05:47.401349
487 (5, 1) [D loss: -43.522 R -220.004 F 166.264 G 1.022][G loss: -236.600]  0:05:48.314828
488 (5, 1) [D loss: -32.246 R -119.628 F 79.556 G 0.783][G loss: -129.056]  0:05:49.229773
489 (5, 1) [D loss: -33.297 R -171.097 F 117.918 G 1.988][G loss: -104.028]  0:05:50.149237
490 (5, 1) [D loss: -44.728 R -150.270 F 91.794 G 1.375][G loss: -100.280]  0:05:51.095485
491 (5, 1) [D loss: -54.081 R -131.006 F 55.748 G 2.118][G loss: -19.840]  0:05:52.158273
492 (5, 1) [D loss: -41.892 R -136.216 F 63.123 G 3.120][G loss: -43.248]  0:05:53.073931
493 (5, 1) [D loss: -65.781 R -121.417 F 31.736 G 2.390][G loss: -7.628]  0:05:54.004636
494 (5, 1) [D loss: -70.395 R -70.924 F -22.138 G 2.267][G loss: 4.008]  0:05:54.908626
495 (5, 1) [D loss: -66.772 R -46.087 F -62.368 G 4.168][G loss: -5.416]  0:05:55.827464
496 (5, 1) [D loss: -66.787 R -43.593 F -47.132 G 2.394][G loss: 10.075]  0:05:56.754676
497 (5, 1) [D loss: -51.891 R 12.514 F -99.263 G 3.486][G loss: 25.408]  0:05:57.705490
498 (5, 1) [D loss: -91.503 R -7.592 F -108.864 G 2.495][G loss: 26.696]  0:05:58.642166
499 (5, 1) [D loss: -74.115 R 1.070 F -88.624 G 1.344][G loss: 37.142]  0:05:59.605833
500 (5, 1) [D loss: -58.555 R 37.237 F -117.237 G 2.145][G loss: 57.598]  0:06:00.529591
In [41]:
# Training in addition
# 追加で training する。

gan_work.train(
    data_flow,
    batch_size = BATCH_SIZE,
    epochs = 1000,
    run_folder = save_path1,
    print_every_n_batches = 2000,
    using_generator = True
)
501 (5, 1) [D loss: -43.299 R 63.570 F -135.909 G 2.904][G loss: 66.481]  0:00:00.969720
502 (5, 1) [D loss: -43.223 R 35.855 F -109.093 G 3.002][G loss: 50.818]  0:00:01.923749
503 (5, 1) [D loss: -61.672 R 39.319 F -132.954 G 3.196][G loss: 51.177]  0:00:02.897205
504 (5, 1) [D loss: -44.974 R -8.825 F -44.407 G 0.826][G loss: 44.047]  0:00:04.087767
505 (5, 1) [D loss: -33.108 R 9.795 F -51.938 G 0.903][G loss: 64.168]  0:00:05.047283
506 (5, 1) [D loss: -41.600 R -46.524 F -7.684 G 1.261][G loss: 16.457]  0:00:06.003518
507 (5, 1) [D loss: -42.538 R -28.090 F -26.310 G 1.186][G loss: 19.883]  0:00:06.956091
508 (5, 1) [D loss: -30.591 R -30.930 F -13.543 G 1.388][G loss: -8.632]  0:00:07.927215
509 (5, 1) [D loss: -28.020 R -48.064 F 9.862 G 1.018][G loss: -17.795]  0:00:09.070329
510 (5, 1) [D loss: -38.337 R -51.344 F 2.887 G 1.012][G loss: 14.404]  0:00:10.040942
511 (5, 1) [D loss: -36.400 R -40.089 F -10.409 G 1.410][G loss: 8.019]  0:00:10.984342
512 (5, 1) [D loss: -32.429 R -64.869 F 24.157 G 0.828][G loss: -18.187]  0:00:11.944921
513 (5, 1) [D loss: -40.850 R -52.730 F -1.572 G 1.345][G loss: 20.662]  0:00:12.909633
514 (5, 1) [D loss: -38.608 R -43.581 F -7.392 G 1.237][G loss: -18.043]  0:00:13.872860
515 (5, 1) [D loss: -46.242 R -89.500 F 27.393 G 1.586][G loss: -61.728]  0:00:14.834705
516 (5, 1) [D loss: -49.730 R -130.931 F 57.865 G 2.334][G loss: -98.676]  0:00:15.799003
517 (5, 1) [D loss: -57.718 R -144.448 F 73.449 G 1.328][G loss: -127.340]  0:00:16.755831
518 (5, 1) [D loss: -48.699 R -207.847 F 120.043 G 3.910][G loss: -160.255]  0:00:17.697395
519 (5, 1) [D loss: -56.728 R -229.076 F 151.482 G 2.087][G loss: -243.113]  0:00:18.661393
520 (5, 1) [D loss: -41.598 R -231.381 F 173.553 G 1.623][G loss: -258.229]  0:00:19.622351
521 (5, 1) [D loss: -76.323 R -241.131 F 141.288 G 2.352][G loss: -325.759]  0:00:20.573042
522 (5, 1) [D loss: -63.061 R -341.745 F 221.626 G 5.706][G loss: -286.533]  0:00:21.639970
523 (5, 1) [D loss: -65.196 R -295.435 F 215.440 G 1.480][G loss: -400.274]  0:00:22.581428
524 (5, 1) [D loss: -55.787 R -269.991 F 198.864 G 1.534][G loss: -373.761]  0:00:23.542208
525 (5, 1) [D loss: -47.785 R -379.222 F 294.554 G 3.688][G loss: -403.620]  0:00:24.512053
526 (5, 1) [D loss: -54.561 R -378.831 F 292.200 G 3.207][G loss: -456.864]  0:00:25.464297
527 (5, 1) [D loss: -56.095 R -332.498 F 256.745 G 1.966][G loss: -376.796]  0:00:26.407917
528 (5, 1) [D loss: -61.179 R -388.321 F 291.849 G 3.529][G loss: -381.721]  0:00:27.345894
529 (5, 1) [D loss: -61.296 R -297.406 F 208.382 G 2.773][G loss: -322.796]  0:00:28.330167
530 (5, 1) [D loss: -87.312 R -278.970 F 163.646 G 2.801][G loss: -262.584]  0:00:29.270524
531 (5, 1) [D loss: -99.503 R -256.512 F 101.769 G 5.524][G loss: -100.867]  0:00:30.219915
532 (5, 1) [D loss: -110.103 R -276.620 F 98.597 G 6.792][G loss: -62.841]  0:00:31.157156
533 (5, 1) [D loss: -125.734 R -287.039 F 80.146 G 8.116][G loss: -43.057]  0:00:32.111743
534 (5, 1) [D loss: -132.560 R -287.417 F 94.546 G 6.031][G loss: -46.884]  0:00:33.047525
535 (5, 1) [D loss: -105.963 R -198.264 F -0.823 G 9.312][G loss: 45.331]  0:00:34.023683
536 (5, 1) [D loss: -115.457 R -247.307 F 78.677 G 5.317][G loss: 4.402]  0:00:34.945850
537 (5, 1) [D loss: -162.511 R -241.741 F -54.047 G 13.328][G loss: 28.717]  0:00:35.916938
538 (5, 1) [D loss: -117.323 R -188.817 F -23.117 G 9.461][G loss: -50.119]  0:00:36.859223
539 (5, 1) [D loss: -156.010 R -302.952 F 13.973 G 13.297][G loss: -54.893]  0:00:37.792549
540 (5, 1) [D loss: -144.105 R -116.275 F -113.271 G 8.544][G loss: 104.309]  0:00:38.773642
541 (5, 1) [D loss: -104.912 R -154.860 F 24.137 G 2.581][G loss: -54.415]  0:00:39.715087
542 (5, 1) [D loss: -58.557 R -115.811 F 25.654 G 3.160][G loss: -74.267]  0:00:40.661983
543 (5, 1) [D loss: -81.369 R -160.023 F 34.969 G 4.368][G loss: -127.523]  0:00:41.602895
544 (5, 1) [D loss: -80.230 R -160.826 F 45.594 G 3.500][G loss: -128.696]  0:00:42.548034
545 (5, 1) [D loss: -70.049 R -130.274 F 27.027 G 3.320][G loss: -117.122]  0:00:43.489838
546 (5, 1) [D loss: -57.643 R -127.191 F 45.159 G 2.439][G loss: -121.163]  0:00:44.424981
547 (5, 1) [D loss: -42.803 R -167.679 F 102.187 G 2.269][G loss: -171.797]  0:00:45.370719
548 (5, 1) [D loss: -58.804 R -166.442 F 90.706 G 1.693][G loss: -160.620]  0:00:46.306647
549 (5, 1) [D loss: -72.554 R -162.805 F 59.320 G 3.093][G loss: -171.065]  0:00:47.261592
550 (5, 1) [D loss: -60.268 R -167.289 F 73.183 G 3.384][G loss: -157.754]  0:00:48.214040
551 (5, 1) [D loss: -54.591 R -147.904 F 69.658 G 2.365][G loss: -155.579]  0:00:49.159540
552 (5, 1) [D loss: -46.921 R -166.029 F 101.253 G 1.786][G loss: -174.741]  0:00:50.091856
553 (5, 1) [D loss: -42.430 R -185.187 F 127.746 G 1.501][G loss: -168.893]  0:00:51.050912
554 (5, 1) [D loss: -34.671 R -213.513 F 171.122 G 0.772][G loss: -158.241]  0:00:51.969034
555 (5, 1) [D loss: -39.469 R -182.707 F 130.759 G 1.248][G loss: -148.684]  0:00:52.889519
556 (5, 1) [D loss: -50.488 R -148.926 F 80.534 G 1.790][G loss: -73.823]  0:00:53.839850
557 (5, 1) [D loss: -43.635 R -154.806 F 93.979 G 1.719][G loss: -122.684]  0:00:54.780951
558 (5, 1) [D loss: -46.943 R -154.653 F 93.340 G 1.437][G loss: -82.756]  0:00:55.716675
559 (5, 1) [D loss: -48.096 R -109.567 F 37.593 G 2.388][G loss: -99.379]  0:00:56.670844
560 (5, 1) [D loss: -43.205 R -115.165 F 55.804 G 1.616][G loss: -84.791]  0:00:57.608128
561 (5, 1) [D loss: -40.136 R -109.053 F 55.258 G 1.366][G loss: -35.408]  0:00:58.559762
562 (5, 1) [D loss: -36.449 R -126.041 F 75.338 G 1.425][G loss: -32.870]  0:00:59.517106
563 (5, 1) [D loss: -31.158 R -108.156 F 69.033 G 0.796][G loss: -32.834]  0:01:00.445694
564 (5, 1) [D loss: -36.677 R -135.297 F 89.602 G 0.902][G loss: -69.703]  0:01:01.385841
565 (5, 1) [D loss: -39.992 R -153.747 F 99.542 G 1.421][G loss: -94.985]  0:01:02.316824
566 (5, 1) [D loss: -34.371 R 5.284 F -50.457 G 1.080][G loss: 17.760]  0:01:03.271238
567 (5, 1) [D loss: -27.559 R -68.291 F 33.489 G 0.724][G loss: -36.457]  0:01:04.230061
568 (5, 1) [D loss: -35.300 R -80.606 F 34.952 G 1.035][G loss: -39.811]  0:01:05.152271
569 (5, 1) [D loss: -27.573 R -50.875 F 16.576 G 0.673][G loss: -11.940]  0:01:06.101047
570 (5, 1) [D loss: -25.880 R -23.711 F -11.408 G 0.924][G loss: 9.794]  0:01:07.035104
571 (5, 1) [D loss: -31.463 R -54.564 F 16.054 G 0.705][G loss: -28.212]  0:01:07.972758
572 (5, 1) [D loss: -30.194 R -56.947 F 18.367 G 0.839][G loss: -13.696]  0:01:09.041006
573 (5, 1) [D loss: -27.978 R -95.097 F 55.705 G 1.141][G loss: -45.652]  0:01:09.986035
574 (5, 1) [D loss: -34.125 R -67.541 F 24.394 G 0.902][G loss: -11.840]  0:01:10.904731
575 (5, 1) [D loss: -31.272 R -93.966 F 52.992 G 0.970][G loss: -39.604]  0:01:11.851017
576 (5, 1) [D loss: -41.322 R -69.385 F 15.797 G 1.227][G loss: 0.667]  0:01:12.786042
577 (5, 1) [D loss: -36.041 R -109.066 F 62.373 G 1.065][G loss: -53.626]  0:01:13.743401
578 (5, 1) [D loss: -37.306 R -96.532 F 44.657 G 1.457][G loss: -38.893]  0:01:14.690135
579 (5, 1) [D loss: -39.279 R -118.068 F 65.557 G 1.323][G loss: -53.601]  0:01:15.627541
580 (5, 1) [D loss: -39.508 R -114.295 F 60.694 G 1.409][G loss: -49.994]  0:01:16.553360
581 (5, 1) [D loss: -36.086 R -112.390 F 65.920 G 1.038][G loss: -63.865]  0:01:17.483773
582 (5, 1) [D loss: -28.254 R -129.955 F 92.168 G 0.953][G loss: -91.273]  0:01:18.417502
583 (5, 1) [D loss: -34.297 R -116.882 F 70.098 G 1.249][G loss: -71.951]  0:01:19.376166
584 (5, 1) [D loss: -23.718 R -115.661 F 81.728 G 1.021][G loss: -89.216]  0:01:20.310883
585 (5, 1) [D loss: -36.010 R -149.508 F 103.679 G 0.982][G loss: -89.000]  0:01:21.265782
586 (5, 1) [D loss: -35.479 R -157.549 F 111.337 G 1.073][G loss: -105.492]  0:01:22.204908
587 (5, 1) [D loss: -28.037 R -151.866 F 109.543 G 1.429][G loss: -115.406]  0:01:23.137456
588 (5, 1) [D loss: -33.301 R -140.302 F 97.784 G 0.922][G loss: -105.885]  0:01:24.202208
589 (5, 1) [D loss: -28.250 R -164.815 F 125.679 G 1.089][G loss: -120.327]  0:01:25.135599
590 (5, 1) [D loss: -20.076 R -149.648 F 118.194 G 1.138][G loss: -104.191]  0:01:26.080923
591 (5, 1) [D loss: -39.545 R -150.626 F 99.703 G 1.138][G loss: -119.853]  0:01:27.010827
592 (5, 1) [D loss: -26.759 R -145.408 F 110.672 G 0.798][G loss: -114.243]  0:01:27.926321
593 (5, 1) [D loss: -27.192 R -175.748 F 137.835 G 1.072][G loss: -143.225]  0:01:28.877574
594 (5, 1) [D loss: -28.632 R -191.222 F 154.483 G 0.811][G loss: -156.599]  0:01:29.809682
595 (5, 1) [D loss: -28.385 R -191.455 F 155.369 G 0.770][G loss: -151.580]  0:01:30.726724
596 (5, 1) [D loss: -28.902 R -195.670 F 159.487 G 0.728][G loss: -158.074]  0:01:31.661627
597 (5, 1) [D loss: -23.276 R -190.011 F 158.800 G 0.793][G loss: -157.036]  0:01:32.611714
598 (5, 1) [D loss: -24.279 R -175.842 F 143.367 G 0.820][G loss: -138.131]  0:01:33.540176
599 (5, 1) [D loss: -30.166 R -165.952 F 126.983 G 0.880][G loss: -125.554]  0:01:34.516457
600 (5, 1) [D loss: -28.294 R -185.560 F 148.631 G 0.864][G loss: -148.733]  0:01:35.467703
601 (5, 1) [D loss: -28.552 R -186.152 F 150.194 G 0.741][G loss: -149.741]  0:01:36.406877
602 (5, 1) [D loss: -30.234 R -179.255 F 139.850 G 0.917][G loss: -138.786]  0:01:37.344764
603 (5, 1) [D loss: -21.061 R -151.010 F 121.330 G 0.862][G loss: -108.108]  0:01:38.219297
604 (5, 1) [D loss: -26.398 R -146.017 F 109.651 G 0.997][G loss: -117.403]  0:01:39.116044
605 (5, 1) [D loss: -24.900 R -167.846 F 135.063 G 0.788][G loss: -132.951]  0:01:40.136959
606 (5, 1) [D loss: -29.695 R -170.604 F 129.992 G 1.092][G loss: -137.208]  0:01:41.013198
607 (5, 1) [D loss: -28.334 R -138.858 F 102.606 G 0.792][G loss: -97.303]  0:01:41.889945
608 (5, 1) [D loss: -27.782 R -122.402 F 88.054 G 0.657][G loss: -89.787]  0:01:42.777229
609 (5, 1) [D loss: -35.069 R -149.865 F 105.289 G 0.951][G loss: -114.449]  0:01:43.653682
610 (5, 1) [D loss: -30.470 R -155.593 F 116.238 G 0.889][G loss: -116.844]  0:01:44.583217
611 (5, 1) [D loss: -28.041 R -136.566 F 100.313 G 0.821][G loss: -90.213]  0:01:45.488868
612 (5, 1) [D loss: -23.657 R -125.464 F 88.329 G 1.348][G loss: -94.478]  0:01:46.425638
613 (5, 1) [D loss: -30.921 R -148.116 F 107.342 G 0.985][G loss: -111.477]  0:01:47.345884
614 (5, 1) [D loss: -26.569 R -154.525 F 118.660 G 0.930][G loss: -103.923]  0:01:48.257077
615 (5, 1) [D loss: -28.942 R -135.903 F 99.385 G 0.758][G loss: -105.546]  0:01:49.164356
616 (5, 1) [D loss: -27.943 R -137.399 F 100.993 G 0.846][G loss: -97.817]  0:01:50.074008
617 (5, 1) [D loss: -28.364 R -131.771 F 93.817 G 0.959][G loss: -96.525]  0:01:50.968204
618 (5, 1) [D loss: -26.750 R -130.239 F 94.792 G 0.870][G loss: -98.519]  0:01:51.872525
619 (5, 1) [D loss: -27.636 R -136.917 F 102.151 G 0.713][G loss: -99.099]  0:01:52.762372
620 (5, 1) [D loss: -27.822 R -133.586 F 97.228 G 0.854][G loss: -103.260]  0:01:53.655465
621 (5, 1) [D loss: -31.652 R -143.224 F 101.798 G 0.977][G loss: -102.726]  0:01:54.574613
622 (5, 1) [D loss: -25.023 R -118.623 F 86.881 G 0.672][G loss: -89.023]  0:01:55.497716
623 (5, 1) [D loss: -22.774 R -129.798 F 99.670 G 0.735][G loss: -96.276]  0:01:56.391791
624 (5, 1) [D loss: -28.657 R -132.535 F 97.152 G 0.673][G loss: -100.744]  0:01:57.305471
625 (5, 1) [D loss: -31.833 R -138.901 F 96.980 G 1.009][G loss: -98.356]  0:01:58.207886
626 (5, 1) [D loss: -23.792 R -103.199 F 71.695 G 0.771][G loss: -73.315]  0:01:59.096709
627 (5, 1) [D loss: -26.556 R -128.165 F 93.491 G 0.812][G loss: -94.037]  0:02:00.006294
628 (5, 1) [D loss: -26.653 R -127.110 F 93.285 G 0.717][G loss: -98.206]  0:02:00.914454
629 (5, 1) [D loss: -27.590 R -125.670 F 90.021 G 0.806][G loss: -93.286]  0:02:01.818277
630 (5, 1) [D loss: -23.566 R -125.728 F 95.919 G 0.624][G loss: -96.361]  0:02:02.715231
631 (5, 1) [D loss: -32.907 R -132.167 F 91.654 G 0.761][G loss: -94.618]  0:02:03.615626
632 (5, 1) [D loss: -28.331 R -128.275 F 93.356 G 0.659][G loss: -100.112]  0:02:04.524857
633 (5, 1) [D loss: -23.736 R -133.832 F 103.536 G 0.656][G loss: -102.173]  0:02:05.408052
634 (5, 1) [D loss: -22.797 R -138.043 F 96.431 G 1.882][G loss: -88.584]  0:02:06.307595
635 (5, 1) [D loss: -23.243 R -136.426 F 107.079 G 0.610][G loss: -113.094]  0:02:07.220887
636 (5, 1) [D loss: -26.525 R -146.010 F 113.114 G 0.637][G loss: -111.316]  0:02:08.135674
637 (5, 1) [D loss: -30.279 R -141.724 F 103.968 G 0.748][G loss: -104.510]  0:02:09.022793
638 (5, 1) [D loss: -26.955 R -137.536 F 103.397 G 0.718][G loss: -104.433]  0:02:09.913131
639 (5, 1) [D loss: -25.032 R -145.870 F 109.111 G 1.173][G loss: -115.659]  0:02:10.809158
640 (5, 1) [D loss: -26.141 R -158.248 F 119.571 G 1.254][G loss: -126.449]  0:02:11.696104
641 (5, 1) [D loss: -25.860 R -138.780 F 106.767 G 0.615][G loss: -107.409]  0:02:12.611524
642 (5, 1) [D loss: -28.887 R -138.651 F 101.857 G 0.791][G loss: -98.157]  0:02:13.532291
643 (5, 1) [D loss: -25.521 R -124.467 F 90.919 G 0.803][G loss: -98.327]  0:02:14.433695
644 (5, 1) [D loss: -25.151 R -129.087 F 91.280 G 1.266][G loss: -96.839]  0:02:15.337196
645 (5, 1) [D loss: -28.838 R -126.791 F 92.813 G 0.514][G loss: -95.879]  0:02:16.268240
646 (5, 1) [D loss: -24.685 R -125.284 F 92.769 G 0.783][G loss: -94.975]  0:02:17.187843
647 (5, 1) [D loss: -23.038 R -132.140 F 100.322 G 0.878][G loss: -97.094]  0:02:18.099125
648 (5, 1) [D loss: -26.105 R -133.118 F 100.397 G 0.662][G loss: -98.297]  0:02:19.011844
649 (5, 1) [D loss: -25.813 R -127.601 F 95.174 G 0.661][G loss: -96.657]  0:02:19.913548
650 (5, 1) [D loss: -25.991 R -131.228 F 97.173 G 0.806][G loss: -101.559]  0:02:20.824638
651 (5, 1) [D loss: -25.376 R -132.360 F 99.697 G 0.729][G loss: -95.480]  0:02:21.716520
652 (5, 1) [D loss: -14.323 R -115.500 F 92.416 G 0.876][G loss: -85.944]  0:02:22.636034
653 (5, 1) [D loss: -19.568 R -109.706 F 81.362 G 0.878][G loss: -86.299]  0:02:23.520537
654 (5, 1) [D loss: -21.977 R -116.579 F 86.988 G 0.761][G loss: -94.677]  0:02:24.416953
655 (5, 1) [D loss: -25.448 R -105.597 F 73.276 G 0.687][G loss: -72.499]  0:02:25.313030
656 (5, 1) [D loss: -26.572 R -118.526 F 84.837 G 0.712][G loss: -79.917]  0:02:26.200951
657 (5, 1) [D loss: -24.696 R -120.153 F 88.097 G 0.736][G loss: -80.984]  0:02:27.118532
658 (5, 1) [D loss: -28.613 R -123.260 F 87.479 G 0.717][G loss: -90.873]  0:02:28.027792
659 (5, 1) [D loss: -27.107 R -123.380 F 88.318 G 0.795][G loss: -89.591]  0:02:28.933464
660 (5, 1) [D loss: -28.189 R -120.548 F 83.913 G 0.845][G loss: -80.569]  0:02:29.823913
661 (5, 1) [D loss: -24.097 R -120.171 F 89.845 G 0.623][G loss: -91.500]  0:02:30.725745
662 (5, 1) [D loss: -28.099 R -130.358 F 94.044 G 0.821][G loss: -86.286]  0:02:31.616196
663 (5, 1) [D loss: -19.787 R -113.472 F 86.051 G 0.764][G loss: -82.059]  0:02:32.493285
664 (5, 1) [D loss: -25.332 R -111.439 F 80.000 G 0.611][G loss: -82.605]  0:02:33.398492
665 (5, 1) [D loss: -25.001 R -116.487 F 84.307 G 0.718][G loss: -88.688]  0:02:34.285588
666 (5, 1) [D loss: -27.595 R -116.794 F 82.844 G 0.636][G loss: -90.618]  0:02:35.174055
667 (5, 1) [D loss: -20.722 R -117.658 F 89.512 G 0.742][G loss: -89.809]  0:02:36.097469
668 (5, 1) [D loss: -22.215 R -129.341 F 100.131 G 0.700][G loss: -102.624]  0:02:36.989833
669 (5, 1) [D loss: -26.435 R -129.201 F 95.844 G 0.692][G loss: -105.557]  0:02:37.873716
670 (5, 1) [D loss: -20.515 R -127.275 F 94.376 G 1.238][G loss: -104.242]  0:02:38.775763
671 (5, 1) [D loss: -23.437 R -121.445 F 92.892 G 0.512][G loss: -99.860]  0:02:39.657132
672 (5, 1) [D loss: -26.088 R -130.020 F 97.600 G 0.633][G loss: -104.730]  0:02:40.550408
673 (5, 1) [D loss: -26.944 R -135.838 F 101.577 G 0.732][G loss: -107.024]  0:02:41.441287
674 (5, 1) [D loss: -20.667 R -132.753 F 103.980 G 0.811][G loss: -104.007]  0:02:42.353749
675 (5, 1) [D loss: -24.655 R -128.559 F 99.224 G 0.468][G loss: -102.854]  0:02:43.241872
676 (5, 1) [D loss: -29.744 R -125.384 F 89.234 G 0.641][G loss: -96.796]  0:02:44.137339
677 (5, 1) [D loss: -25.406 R -127.682 F 95.526 G 0.675][G loss: -103.057]  0:02:45.042342
678 (5, 1) [D loss: -22.967 R -146.975 F 118.351 G 0.566][G loss: -123.186]  0:02:45.930941
679 (5, 1) [D loss: -26.909 R -141.001 F 105.504 G 0.859][G loss: -100.517]  0:02:46.828818
680 (5, 1) [D loss: -26.535 R -135.088 F 101.797 G 0.676][G loss: -102.644]  0:02:47.723518
681 (5, 1) [D loss: -23.346 R -135.736 F 106.897 G 0.549][G loss: -108.191]  0:02:48.607817
682 (5, 1) [D loss: -26.605 R -148.543 F 115.049 G 0.689][G loss: -114.801]  0:02:49.490272
683 (5, 1) [D loss: -23.916 R -143.027 F 112.398 G 0.671][G loss: -107.796]  0:02:50.363018
684 (5, 1) [D loss: -27.036 R -146.039 F 112.729 G 0.627][G loss: -111.788]  0:02:51.252518
685 (5, 1) [D loss: -22.278 R -148.410 F 118.208 G 0.793][G loss: -107.973]  0:02:52.141951
686 (5, 1) [D loss: -22.622 R -137.029 F 107.542 G 0.686][G loss: -108.769]  0:02:53.011408
687 (5, 1) [D loss: -23.119 R -141.396 F 111.533 G 0.674][G loss: -112.031]  0:02:53.888310
688 (5, 1) [D loss: -27.862 R -127.335 F 90.804 G 0.867][G loss: -87.726]  0:02:54.787084
689 (5, 1) [D loss: -19.928 R -128.900 F 100.981 G 0.799][G loss: -94.364]  0:02:55.675231
690 (5, 1) [D loss: -24.274 R -130.896 F 99.970 G 0.665][G loss: -97.974]  0:02:56.567381
691 (5, 1) [D loss: -23.855 R -126.508 F 98.021 G 0.463][G loss: -93.068]  0:02:57.470343
692 (5, 1) [D loss: -28.719 R -126.648 F 91.991 G 0.594][G loss: -91.098]  0:02:58.349564
693 (5, 1) [D loss: -25.342 R -128.231 F 95.083 G 0.781][G loss: -95.434]  0:02:59.235747
694 (5, 1) [D loss: -24.367 R -114.522 F 84.369 G 0.579][G loss: -87.778]  0:03:00.153902
695 (5, 1) [D loss: -28.386 R -125.732 F 91.181 G 0.616][G loss: -89.296]  0:03:01.064855
696 (5, 1) [D loss: -33.293 R -144.752 F 94.905 G 1.655][G loss: -96.770]  0:03:01.943901
697 (5, 1) [D loss: -24.677 R -134.938 F 105.213 G 0.505][G loss: -109.236]  0:03:02.819420
698 (5, 1) [D loss: -26.964 R -139.714 F 104.933 G 0.782][G loss: -112.500]  0:03:03.705876
699 (5, 1) [D loss: -23.519 R -124.901 F 93.159 G 0.822][G loss: -100.987]  0:03:04.593315
700 (5, 1) [D loss: -23.118 R -127.183 F 95.999 G 0.807][G loss: -100.354]  0:03:05.476456
701 (5, 1) [D loss: -25.114 R -124.379 F 93.407 G 0.586][G loss: -93.975]  0:03:06.372592
702 (5, 1) [D loss: -28.071 R -129.654 F 94.712 G 0.687][G loss: -103.072]  0:03:07.246443
703 (5, 1) [D loss: -25.920 R -129.059 F 93.053 G 1.009][G loss: -108.190]  0:03:08.154705
704 (5, 1) [D loss: -23.099 R -131.891 F 103.104 G 0.569][G loss: -104.366]  0:03:09.036999
705 (5, 1) [D loss: -25.585 R -127.812 F 90.815 G 1.141][G loss: -111.585]  0:03:09.927387
706 (5, 1) [D loss: -26.323 R -126.308 F 92.833 G 0.715][G loss: -108.054]  0:03:10.805936
707 (5, 1) [D loss: -21.241 R -135.689 F 106.957 G 0.749][G loss: -103.623]  0:03:11.696742
708 (5, 1) [D loss: -22.242 R -122.583 F 94.261 G 0.608][G loss: -97.145]  0:03:12.576545
709 (5, 1) [D loss: -26.053 R -133.160 F 99.614 G 0.749][G loss: -95.468]  0:03:13.459039
710 (5, 1) [D loss: -21.518 R -110.702 F 82.409 G 0.678][G loss: -84.438]  0:03:14.334758
711 (5, 1) [D loss: -22.774 R -123.358 F 93.454 G 0.713][G loss: -92.681]  0:03:15.227204
712 (5, 1) [D loss: -18.918 R -111.561 F 82.963 G 0.968][G loss: -95.790]  0:03:16.105924
713 (5, 1) [D loss: -21.483 R -116.416 F 90.814 G 0.412][G loss: -85.591]  0:03:16.977460
714 (5, 1) [D loss: -28.366 R -130.982 F 96.552 G 0.606][G loss: -90.482]  0:03:17.872447
715 (5, 1) [D loss: -19.090 R -116.810 F 91.728 G 0.599][G loss: -85.635]  0:03:18.767270
716 (5, 1) [D loss: -20.627 R -104.778 F 78.302 G 0.585][G loss: -79.509]  0:03:19.641412
717 (5, 1) [D loss: -20.682 R -110.963 F 82.608 G 0.767][G loss: -72.883]  0:03:20.529020
718 (5, 1) [D loss: -21.033 R -106.324 F 78.768 G 0.652][G loss: -78.905]  0:03:21.402120
719 (5, 1) [D loss: -25.366 R -109.538 F 77.124 G 0.705][G loss: -76.233]  0:03:22.289873
720 (5, 1) [D loss: -25.655 R -110.889 F 78.694 G 0.654][G loss: -78.675]  0:03:23.161016
721 (5, 1) [D loss: -21.716 R -110.904 F 84.100 G 0.509][G loss: -81.624]  0:03:24.044567
722 (5, 1) [D loss: -21.747 R -110.122 F 82.894 G 0.548][G loss: -80.981]  0:03:24.935965
723 (5, 1) [D loss: -24.294 R -101.710 F 71.520 G 0.590][G loss: -72.638]  0:03:25.816609
724 (5, 1) [D loss: -20.765 R -98.690 F 72.130 G 0.580][G loss: -70.639]  0:03:26.716849
725 (5, 1) [D loss: -26.788 R -99.955 F 68.066 G 0.510][G loss: -76.414]  0:03:27.594876
726 (5, 1) [D loss: -25.189 R -101.040 F 70.628 G 0.522][G loss: -77.632]  0:03:28.485923
727 (5, 1) [D loss: -22.124 R -99.856 F 72.346 G 0.539][G loss: -73.713]  0:03:29.365416
728 (5, 1) [D loss: -23.935 R -97.311 F 66.750 G 0.663][G loss: -81.445]  0:03:30.250773
729 (5, 1) [D loss: -24.262 R -109.561 F 79.567 G 0.573][G loss: -84.648]  0:03:31.128050
730 (5, 1) [D loss: -27.488 R -112.486 F 78.107 G 0.689][G loss: -97.933]  0:03:32.016883
731 (5, 1) [D loss: -24.411 R -116.693 F 86.773 G 0.551][G loss: -97.283]  0:03:32.892731
732 (5, 1) [D loss: -25.254 R -122.514 F 92.305 G 0.496][G loss: -97.643]  0:03:33.803763
733 (5, 1) [D loss: -25.513 R -123.596 F 91.650 G 0.643][G loss: -95.007]  0:03:34.706176
734 (5, 1) [D loss: -26.570 R -121.032 F 88.829 G 0.563][G loss: -93.672]  0:03:35.601276
735 (5, 1) [D loss: -22.883 R -128.163 F 98.014 G 0.727][G loss: -98.612]  0:03:36.471409
736 (5, 1) [D loss: -21.584 R -129.542 F 102.272 G 0.569][G loss: -108.790]  0:03:37.358744
737 (5, 1) [D loss: -21.574 R -130.587 F 103.129 G 0.588][G loss: -109.935]  0:03:38.253627
738 (5, 1) [D loss: -28.947 R -134.785 F 96.635 G 0.920][G loss: -103.692]  0:03:39.127041
739 (5, 1) [D loss: -22.083 R -122.740 F 96.402 G 0.426][G loss: -95.475]  0:03:40.015427
740 (5, 1) [D loss: -24.399 R -121.629 F 90.016 G 0.721][G loss: -94.651]  0:03:40.931307
741 (5, 1) [D loss: -25.167 R -119.106 F 87.879 G 0.606][G loss: -92.947]  0:03:41.819181
742 (5, 1) [D loss: -19.524 R -122.851 F 96.472 G 0.685][G loss: -97.093]  0:03:42.694896
743 (5, 1) [D loss: -23.912 R -127.494 F 95.627 G 0.795][G loss: -102.412]  0:03:43.593210
744 (5, 1) [D loss: -29.084 R -129.102 F 94.909 G 0.511][G loss: -105.368]  0:03:44.465609
745 (5, 1) [D loss: -24.429 R -132.388 F 102.316 G 0.564][G loss: -107.902]  0:03:45.373111
746 (5, 1) [D loss: -24.569 R -133.698 F 102.934 G 0.620][G loss: -107.228]  0:03:46.262333
747 (5, 1) [D loss: -22.759 R -126.594 F 95.555 G 0.828][G loss: -104.059]  0:03:47.135336
748 (5, 1) [D loss: -25.415 R -125.664 F 93.971 G 0.628][G loss: -103.262]  0:03:48.027358
749 (5, 1) [D loss: -24.511 R -126.766 F 95.210 G 0.705][G loss: -102.448]  0:03:48.916503
750 (5, 1) [D loss: -11.781 R -126.148 F 104.499 G 0.987][G loss: -102.719]  0:03:49.790284
751 (5, 1) [D loss: -20.924 R -126.665 F 95.150 G 1.059][G loss: -93.122]  0:03:50.664284
752 (5, 1) [D loss: -17.171 R -107.706 F 83.202 G 0.733][G loss: -81.446]  0:03:51.550979
753 (5, 1) [D loss: -27.783 R -106.388 F 69.359 G 0.925][G loss: -79.573]  0:03:52.434750
754 (5, 1) [D loss: -25.781 R -124.575 F 92.494 G 0.630][G loss: -89.443]  0:03:53.321624
755 (5, 1) [D loss: -24.232 R -122.217 F 91.663 G 0.632][G loss: -89.898]  0:03:54.203615
756 (5, 1) [D loss: -27.008 R -106.507 F 72.477 G 0.702][G loss: -79.162]  0:03:55.088823
757 (5, 1) [D loss: -18.810 R -97.647 F 73.509 G 0.533][G loss: -78.097]  0:03:55.974940
758 (5, 1) [D loss: -21.818 R -110.116 F 83.065 G 0.523][G loss: -88.652]  0:03:56.877028
759 (5, 1) [D loss: -25.933 R -110.814 F 75.159 G 0.972][G loss: -81.641]  0:03:57.772016
760 (5, 1) [D loss: -20.515 R -116.649 F 91.192 G 0.494][G loss: -95.343]  0:03:58.645176
761 (5, 1) [D loss: -21.235 R -126.212 F 98.658 G 0.632][G loss: -96.285]  0:03:59.535155
762 (5, 1) [D loss: -21.730 R -117.738 F 89.735 G 0.627][G loss: -95.896]  0:04:00.441728
763 (5, 1) [D loss: -21.339 R -123.050 F 96.136 G 0.557][G loss: -97.795]  0:04:01.343399
764 (5, 1) [D loss: -20.596 R -122.523 F 95.869 G 0.606][G loss: -98.949]  0:04:02.228905
765 (5, 1) [D loss: -20.841 R -102.497 F 76.543 G 0.511][G loss: -82.272]  0:04:03.114631
766 (5, 1) [D loss: -18.413 R -119.217 F 92.208 G 0.860][G loss: -93.786]  0:04:04.008804
767 (5, 1) [D loss: -23.831 R -125.568 F 96.097 G 0.564][G loss: -107.234]  0:04:04.888190
768 (5, 1) [D loss: -19.253 R -113.980 F 88.912 G 0.582][G loss: -93.694]  0:04:05.785119
769 (5, 1) [D loss: -21.071 R -114.620 F 89.139 G 0.441][G loss: -102.197]  0:04:06.684528
770 (5, 1) [D loss: -20.397 R -114.925 F 88.763 G 0.577][G loss: -94.765]  0:04:07.566714
771 (5, 1) [D loss: -25.902 R -119.866 F 87.088 G 0.688][G loss: -91.411]  0:04:08.460308
772 (5, 1) [D loss: -22.821 R -119.132 F 91.121 G 0.519][G loss: -95.772]  0:04:09.359839
773 (5, 1) [D loss: -20.930 R -122.442 F 96.995 G 0.452][G loss: -96.903]  0:04:10.233528
774 (5, 1) [D loss: -21.117 R -123.055 F 97.083 G 0.485][G loss: -95.341]  0:04:11.128824
775 (5, 1) [D loss: -21.439 R -115.516 F 88.879 G 0.520][G loss: -89.883]  0:04:12.013827
776 (5, 1) [D loss: -21.482 R -113.766 F 85.918 G 0.637][G loss: -86.957]  0:04:12.897928
777 (5, 1) [D loss: -24.783 R -106.084 F 75.288 G 0.601][G loss: -74.138]  0:04:13.775708
778 (5, 1) [D loss: -30.069 R -112.989 F 75.401 G 0.752][G loss: -73.933]  0:04:14.656589
779 (5, 1) [D loss: -24.626 R -111.050 F 81.539 G 0.489][G loss: -76.889]  0:04:15.539909
780 (5, 1) [D loss: -27.962 R -113.527 F 77.538 G 0.803][G loss: -70.705]  0:04:16.415448
781 (5, 1) [D loss: -22.411 R -101.236 F 72.946 G 0.588][G loss: -71.965]  0:04:17.317279
782 (5, 1) [D loss: -21.387 R -103.279 F 73.695 G 0.820][G loss: -72.195]  0:04:18.191783
783 (5, 1) [D loss: -24.500 R -100.533 F 70.268 G 0.577][G loss: -68.526]  0:04:19.073490
784 (5, 1) [D loss: -23.743 R -106.472 F 76.574 G 0.615][G loss: -74.266]  0:04:19.954831
785 (5, 1) [D loss: -23.952 R -94.543 F 64.272 G 0.632][G loss: -69.194]  0:04:20.829973
786 (5, 1) [D loss: -25.044 R -96.658 F 64.368 G 0.725][G loss: -73.351]  0:04:21.711509
787 (5, 1) [D loss: -25.539 R -101.653 F 70.744 G 0.537][G loss: -81.443]  0:04:22.603752
788 (5, 1) [D loss: -17.376 R -99.184 F 73.780 G 0.803][G loss: -79.819]  0:04:23.491497
789 (5, 1) [D loss: -26.707 R -97.403 F 65.048 G 0.565][G loss: -80.463]  0:04:24.363513
790 (5, 1) [D loss: -23.613 R -98.971 F 70.073 G 0.529][G loss: -85.339]  0:04:25.242708
791 (5, 1) [D loss: -22.525 R -104.792 F 74.641 G 0.763][G loss: -86.562]  0:04:26.132750
792 (5, 1) [D loss: -23.293 R -112.120 F 80.470 G 0.836][G loss: -92.265]  0:04:27.016370
793 (5, 1) [D loss: -27.395 R -114.516 F 80.695 G 0.643][G loss: -102.676]  0:04:27.904634
794 (5, 1) [D loss: -22.824 R -88.482 F 61.019 G 0.464][G loss: -83.550]  0:04:28.798488
795 (5, 1) [D loss: -24.005 R -98.265 F 68.084 G 0.618][G loss: -78.388]  0:04:29.695680
796 (5, 1) [D loss: -25.173 R -110.915 F 79.656 G 0.609][G loss: -92.797]  0:04:30.581237
797 (5, 1) [D loss: -25.059 R -114.136 F 83.319 G 0.576][G loss: -105.780]  0:04:31.474814
798 (5, 1) [D loss: -23.670 R -120.021 F 91.598 G 0.475][G loss: -113.466]  0:04:32.349684
799 (5, 1) [D loss: -23.402 R -124.449 F 98.120 G 0.293][G loss: -123.179]  0:04:33.244144
800 (5, 1) [D loss: -19.988 R -119.006 F 95.385 G 0.363][G loss: -104.584]  0:04:34.125992
801 (5, 1) [D loss: -20.057 R -125.735 F 100.296 G 0.538][G loss: -102.149]  0:04:35.005845
802 (5, 1) [D loss: -17.331 R -122.236 F 100.962 G 0.394][G loss: -106.794]  0:04:35.881185
803 (5, 1) [D loss: -19.400 R -129.612 F 105.039 G 0.517][G loss: -113.995]  0:04:36.768651
804 (5, 1) [D loss: -21.502 R -132.504 F 103.737 G 0.727][G loss: -102.272]  0:04:37.657566
805 (5, 1) [D loss: -20.801 R -136.750 F 104.455 G 1.149][G loss: -84.591]  0:04:38.547082
806 (5, 1) [D loss: -12.004 R -117.579 F 97.920 G 0.765][G loss: -76.787]  0:04:39.455989
807 (5, 1) [D loss: -17.240 R -111.397 F 82.698 G 1.146][G loss: -77.432]  0:04:40.359883
808 (5, 1) [D loss: -30.387 R -139.814 F 102.953 G 0.647][G loss: -103.560]  0:04:41.263353
809 (5, 1) [D loss: -10.231 R -126.778 F 105.149 G 1.140][G loss: -98.054]  0:04:42.141268
810 (5, 1) [D loss: -27.430 R -122.260 F 88.986 G 0.584][G loss: -96.481]  0:04:43.035819
811 (5, 1) [D loss: -23.739 R -107.654 F 76.925 G 0.699][G loss: -83.806]  0:04:43.922394
812 (5, 1) [D loss: -26.101 R -115.255 F 82.032 G 0.712][G loss: -87.723]  0:04:44.801528
813 (5, 1) [D loss: -17.990 R -113.391 F 82.572 G 1.283][G loss: -94.949]  0:04:45.683078
814 (5, 1) [D loss: -11.663 R -108.720 F 84.736 G 1.232][G loss: -91.284]  0:04:46.567228
815 (5, 1) [D loss: -27.020 R -108.504 F 72.467 G 0.902][G loss: -85.726]  0:04:47.452281
816 (5, 1) [D loss: -27.588 R -112.459 F 76.285 G 0.859][G loss: -81.056]  0:04:48.341610
817 (5, 1) [D loss: -20.762 R -92.852 F 65.554 G 0.654][G loss: -62.259]  0:04:49.237582
818 (5, 1) [D loss: -29.002 R -108.878 F 72.286 G 0.759][G loss: -71.102]  0:04:50.129852
819 (5, 1) [D loss: -24.378 R -103.390 F 73.584 G 0.543][G loss: -83.855]  0:04:51.032891
820 (5, 1) [D loss: -14.012 R -83.796 F 56.680 G 1.310][G loss: -71.087]  0:04:51.918134
821 (5, 1) [D loss: -17.259 R -105.190 F 81.122 G 0.681][G loss: -85.025]  0:04:52.795232
822 (5, 1) [D loss: -26.926 R -101.478 F 68.252 G 0.630][G loss: -69.720]  0:04:53.671534
823 (5, 1) [D loss: -21.672 R -87.858 F 60.801 G 0.539][G loss: -64.467]  0:04:54.558969
824 (5, 1) [D loss: -21.261 R -89.998 F 63.404 G 0.533][G loss: -67.985]  0:04:55.452236
825 (5, 1) [D loss: -25.328 R -94.045 F 64.096 G 0.462][G loss: -78.027]  0:04:56.336503
826 (5, 1) [D loss: -19.028 R -95.576 F 70.541 G 0.601][G loss: -72.933]  0:04:57.224023
827 (5, 1) [D loss: -22.150 R -100.339 F 71.175 G 0.701][G loss: -78.723]  0:04:58.114982
828 (5, 1) [D loss: -27.493 R -104.803 F 70.491 G 0.682][G loss: -87.320]  0:04:58.999820
829 (5, 1) [D loss: -23.742 R -113.190 F 83.653 G 0.579][G loss: -94.842]  0:04:59.871821
830 (5, 1) [D loss: -27.752 R -114.355 F 80.429 G 0.617][G loss: -100.025]  0:05:00.751974
831 (5, 1) [D loss: -27.665 R -113.981 F 77.509 G 0.881][G loss: -117.289]  0:05:01.642166
832 (5, 1) [D loss: -29.540 R -131.669 F 92.619 G 0.951][G loss: -128.261]  0:05:02.530119
833 (5, 1) [D loss: -23.611 R -114.196 F 87.798 G 0.279][G loss: -112.756]  0:05:03.430262
834 (5, 1) [D loss: -19.244 R -135.819 F 110.798 G 0.578][G loss: -127.693]  0:05:04.309742
835 (5, 1) [D loss: -17.838 R -132.321 F 108.916 G 0.557][G loss: -119.694]  0:05:05.207355
836 (5, 1) [D loss: -20.550 R -137.923 F 111.310 G 0.606][G loss: -102.102]  0:05:06.087882
837 (5, 1) [D loss: -19.126 R -119.792 F 95.747 G 0.492][G loss: -108.098]  0:05:06.968241
838 (5, 1) [D loss: -23.992 R -142.413 F 111.410 G 0.701][G loss: -101.520]  0:05:07.866785
839 (5, 1) [D loss: -26.709 R -134.223 F 100.417 G 0.710][G loss: -99.233]  0:05:08.800559
840 (5, 1) [D loss: -26.238 R -133.072 F 97.249 G 0.959][G loss: -91.533]  0:05:09.693545
841 (5, 1) [D loss: -37.131 R -160.573 F 109.830 G 1.361][G loss: -127.032]  0:05:10.602210
842 (5, 1) [D loss: -27.324 R -157.051 F 114.320 G 1.541][G loss: -123.042]  0:05:11.498617
843 (5, 1) [D loss: -42.723 R -185.286 F 128.808 G 1.376][G loss: -145.381]  0:05:12.474056
844 (5, 1) [D loss: -47.088 R -179.042 F 115.319 G 1.664][G loss: -148.418]  0:05:13.391652
845 (5, 1) [D loss: -38.739 R -151.200 F 101.839 G 1.062][G loss: -137.101]  0:05:14.291976
846 (5, 1) [D loss: -35.560 R -149.487 F 106.720 G 0.721][G loss: -138.424]  0:05:15.201778
847 (5, 1) [D loss: -33.099 R -139.048 F 96.557 G 0.939][G loss: -126.743]  0:05:16.109952
848 (5, 1) [D loss: -46.306 R -156.232 F 99.833 G 1.009][G loss: -142.221]  0:05:17.035394
849 (5, 1) [D loss: -28.464 R -121.758 F 83.304 G 0.999][G loss: -120.894]  0:05:17.961540
850 (5, 1) [D loss: -33.603 R -150.739 F 110.615 G 0.652][G loss: -127.408]  0:05:18.865181
851 (5, 1) [D loss: -26.559 R -140.170 F 106.015 G 0.760][G loss: -117.178]  0:05:19.775065
852 (5, 1) [D loss: -27.285 R -126.212 F 90.811 G 0.812][G loss: -80.146]  0:05:20.689169
853 (5, 1) [D loss: -29.610 R -117.738 F 81.402 G 0.673][G loss: -74.177]  0:05:21.616883
854 (5, 1) [D loss: -28.510 R -117.136 F 80.795 G 0.783][G loss: -73.064]  0:05:22.549060
855 (5, 1) [D loss: -30.994 R -84.320 F 42.328 G 1.100][G loss: -44.909]  0:05:23.467140
856 (5, 1) [D loss: -24.724 R -142.215 F 106.893 G 1.060][G loss: -69.137]  0:05:24.362847
857 (5, 1) [D loss: -22.508 R -90.471 F 60.305 G 0.766][G loss: -57.524]  0:05:25.258261
858 (5, 1) [D loss: -26.914 R -93.628 F 60.013 G 0.670][G loss: -48.089]  0:05:26.150933
859 (5, 1) [D loss: -25.391 R -113.748 F 81.053 G 0.730][G loss: -71.787]  0:05:27.040683
860 (5, 1) [D loss: -19.195 R -120.706 F 92.091 G 0.942][G loss: -72.159]  0:05:27.960716
861 (5, 1) [D loss: -22.194 R -93.080 F 64.360 G 0.653][G loss: -50.658]  0:05:28.855959
862 (5, 1) [D loss: -40.576 R -96.717 F 47.438 G 0.870][G loss: -77.743]  0:05:29.751870
863 (5, 1) [D loss: -39.099 R -115.182 F 67.348 G 0.873][G loss: -114.950]  0:05:30.650027
864 (5, 1) [D loss: -47.539 R -170.465 F 106.184 G 1.674][G loss: -125.847]  0:05:31.573868
865 (5, 1) [D loss: -30.202 R -111.452 F 74.722 G 0.653][G loss: -114.095]  0:05:32.457807
866 (5, 1) [D loss: -45.110 R -165.866 F 104.683 G 1.607][G loss: -170.933]  0:05:33.367660
867 (5, 1) [D loss: -58.060 R -194.357 F 112.899 G 2.340][G loss: -238.831]  0:05:34.300752
868 (5, 1) [D loss: -49.348 R -198.753 F 123.531 G 2.587][G loss: -233.128]  0:05:35.210461
869 (5, 1) [D loss: -61.929 R -206.138 F 127.886 G 1.632][G loss: -278.814]  0:05:36.099127
870 (5, 1) [D loss: -49.438 R -205.439 F 137.362 G 1.864][G loss: -262.544]  0:05:37.022810
871 (5, 1) [D loss: -57.225 R -253.783 F 173.501 G 2.306][G loss: -364.289]  0:05:37.971399
872 (5, 1) [D loss: -33.199 R -167.506 F 122.408 G 1.190][G loss: -197.654]  0:05:38.884394
873 (5, 1) [D loss: -36.636 R -252.707 F 196.824 G 1.925][G loss: -204.954]  0:05:39.775148
874 (5, 1) [D loss: -42.055 R -240.462 F 183.047 G 1.536][G loss: -134.128]  0:05:40.665955
875 (5, 1) [D loss: -33.339 R -185.139 F 136.015 G 1.579][G loss: -124.348]  0:05:41.564355
876 (5, 1) [D loss: -34.473 R -159.430 F 110.510 G 1.445][G loss: -76.067]  0:05:42.450838
877 (5, 1) [D loss: -40.180 R -149.455 F 96.885 G 1.239][G loss: -59.962]  0:05:43.345985
878 (5, 1) [D loss: -35.212 R -134.563 F 88.418 G 1.093][G loss: -53.710]  0:05:44.241326
879 (5, 1) [D loss: -39.564 R -103.782 F 43.498 G 2.072][G loss: -11.745]  0:05:45.137922
880 (5, 1) [D loss: -64.635 R -104.639 F 13.202 G 2.680][G loss: 26.388]  0:05:46.017871
881 (5, 1) [D loss: -44.834 R -38.888 F -46.823 G 4.088][G loss: 24.033]  0:05:46.900030
882 (5, 1) [D loss: -35.966 R -82.042 F 36.731 G 0.934][G loss: -18.757]  0:05:47.778605
883 (5, 1) [D loss: -44.955 R -121.389 F 60.998 G 1.544][G loss: -37.190]  0:05:48.665646
884 (5, 1) [D loss: -36.343 R -88.249 F 41.985 G 0.992][G loss: -29.575]  0:05:49.520553
885 (5, 1) [D loss: -45.992 R -90.408 F 28.369 G 1.605][G loss: -24.084]  0:05:50.401423
886 (5, 1) [D loss: -44.238 R -108.750 F 46.337 G 1.817][G loss: -44.994]  0:05:51.280417
887 (5, 1) [D loss: -57.762 R -110.622 F 33.901 G 1.896][G loss: -46.514]  0:05:52.154950
888 (5, 1) [D loss: -22.323 R -89.042 F 34.047 G 3.267][G loss: -34.397]  0:05:53.047097
889 (5, 1) [D loss: -46.277 R -77.575 F 14.300 G 1.700][G loss: -33.652]  0:05:53.938016
890 (5, 1) [D loss: -48.079 R -86.157 F 11.739 G 2.634][G loss: -52.784]  0:05:54.822929
891 (5, 1) [D loss: -28.059 R -89.638 F 50.714 G 1.086][G loss: -70.844]  0:05:55.710868
892 (5, 1) [D loss: -54.431 R -91.330 F 12.033 G 2.487][G loss: -62.930]  0:05:56.586767
893 (5, 1) [D loss: -35.240 R -95.365 F 37.250 G 2.288][G loss: -75.824]  0:05:57.471906
894 (5, 1) [D loss: -46.309 R -120.819 F 63.246 G 1.126][G loss: -81.678]  0:05:58.359329
895 (5, 1) [D loss: -52.485 R -105.386 F 38.303 G 1.460][G loss: -107.192]  0:05:59.262725
896 (5, 1) [D loss: -57.336 R -126.058 F 48.212 G 2.051][G loss: -117.138]  0:06:00.152733
897 (5, 1) [D loss: -54.943 R -132.134 F 54.733 G 2.246][G loss: -124.877]  0:06:01.034005
898 (5, 1) [D loss: -74.028 R -123.065 F 9.048 G 3.999][G loss: -140.382]  0:06:01.910090
899 (5, 1) [D loss: -21.103 R -115.636 F 73.005 G 2.153][G loss: -119.409]  0:06:02.785967
900 (5, 1) [D loss: -44.624 R -144.579 F 82.094 G 1.786][G loss: -115.705]  0:06:03.663024
901 (5, 1) [D loss: -43.264 R -138.269 F 82.351 G 1.265][G loss: -102.415]  0:06:04.536269
902 (5, 1) [D loss: -38.596 R -150.615 F 95.690 G 1.633][G loss: -100.488]  0:06:05.418076
903 (5, 1) [D loss: -16.115 R -141.013 F 102.315 G 2.258][G loss: -140.440]  0:06:06.283395
904 (5, 1) [D loss: -38.566 R -147.573 F 83.284 G 2.572][G loss: -158.216]  0:06:07.174298
905 (5, 1) [D loss: -40.036 R -166.759 F 110.102 G 1.662][G loss: -150.032]  0:06:08.055545
906 (5, 1) [D loss: -43.113 R -158.356 F 102.631 G 1.261][G loss: -124.292]  0:06:08.936644
907 (5, 1) [D loss: -34.715 R -133.892 F 86.337 G 1.284][G loss: -81.651]  0:06:09.828343
908 (5, 1) [D loss: -30.358 R -144.659 F 102.467 G 1.183][G loss: -91.020]  0:06:10.727563
909 (5, 1) [D loss: -28.746 R -149.142 F 107.641 G 1.276][G loss: -101.139]  0:06:11.603828
910 (5, 1) [D loss: -35.044 R -139.855 F 90.654 G 1.416][G loss: -81.593]  0:06:12.495929
911 (5, 1) [D loss: -33.852 R -134.806 F 88.406 G 1.255][G loss: -117.325]  0:06:13.366068
912 (5, 1) [D loss: -63.399 R -134.199 F 43.978 G 2.682][G loss: -125.636]  0:06:14.255334
913 (5, 1) [D loss: -88.357 R -250.686 F 94.684 G 6.764][G loss: -214.610]  0:06:15.132395
914 (5, 1) [D loss: -92.659 R -194.525 F 67.315 G 3.455][G loss: -256.296]  0:06:16.017812
915 (5, 1) [D loss: -110.850 R -311.423 F 154.576 G 4.600][G loss: -389.018]  0:06:16.893073
916 (5, 1) [D loss: -104.470 R -301.467 F 142.411 G 5.459][G loss: -377.473]  0:06:17.767805
917 (5, 1) [D loss: -104.134 R -350.186 F 204.008 G 4.204][G loss: -542.999]  0:06:18.662533
918 (5, 1) [D loss: -90.313 R -366.067 F 218.018 G 5.774][G loss: -504.481]  0:06:19.541354
919 (5, 1) [D loss: -47.259 R -147.502 F 83.981 G 1.626][G loss: -107.761]  0:06:20.411445
920 (5, 1) [D loss: -53.910 R -256.330 F 176.868 G 2.555][G loss: -147.423]  0:06:21.286776
921 (5, 1) [D loss: -76.951 R -320.923 F 214.315 G 2.966][G loss: -196.444]  0:06:22.173381
922 (5, 1) [D loss: -80.450 R -308.812 F 199.735 G 2.863][G loss: -199.473]  0:06:23.067963
923 (5, 1) [D loss: -102.260 R -401.305 F 242.098 G 5.695][G loss: -216.096]  0:06:23.957317
924 (5, 1) [D loss: -118.130 R -423.485 F 232.832 G 7.252][G loss: -189.845]  0:06:24.841095
925 (5, 1) [D loss: -103.065 R -361.989 F 222.398 G 3.653][G loss: -184.268]  0:06:25.724378
926 (5, 1) [D loss: -118.030 R -412.089 F 222.602 G 7.146][G loss: -193.002]  0:06:26.604583
927 (5, 1) [D loss: -119.536 R -443.466 F 268.336 G 5.559][G loss: -204.398]  0:06:27.496831
928 (5, 1) [D loss: -167.971 R -514.897 F 251.013 G 9.591][G loss: -202.241]  0:06:28.386741
929 (5, 1) [D loss: -97.033 R -279.661 F 157.373 G 2.525][G loss: -149.835]  0:06:29.266779
930 (5, 1) [D loss: -118.766 R -501.712 F 295.595 G 8.735][G loss: -351.090]  0:06:30.155204
931 (5, 1) [D loss: -95.236 R -412.731 F 306.061 G 1.143][G loss: -383.824]  0:06:31.026212
932 (5, 1) [D loss: -93.091 R -419.813 F 230.068 G 9.665][G loss: -396.402]  0:06:31.898251
933 (5, 1) [D loss: -100.297 R -398.972 F 235.065 G 6.361][G loss: -405.413]  0:06:32.779001
934 (5, 1) [D loss: -78.013 R -410.354 F 256.128 G 7.621][G loss: -367.618]  0:06:33.655160
935 (5, 1) [D loss: -106.523 R -386.782 F 238.021 G 4.224][G loss: -404.678]  0:06:34.514185
936 (5, 1) [D loss: -62.260 R -338.941 F 247.849 G 2.883][G loss: -363.084]  0:06:35.390366
937 (5, 1) [D loss: -57.673 R -314.646 F 247.084 G 0.989][G loss: -350.081]  0:06:36.268016
938 (5, 1) [D loss: -46.291 R -304.059 F 243.639 G 1.413][G loss: -326.034]  0:06:37.127674
939 (5, 1) [D loss: -68.302 R -324.249 F 245.251 G 1.070][G loss: -382.198]  0:06:38.002818
940 (5, 1) [D loss: -34.825 R -282.996 F 229.468 G 1.870][G loss: -299.261]  0:06:38.869939
941 (5, 1) [D loss: -46.439 R -327.569 F 257.921 G 2.321][G loss: -285.848]  0:06:39.736552
942 (5, 1) [D loss: -47.939 R -305.067 F 244.769 G 1.236][G loss: -308.211]  0:06:40.608920
943 (5, 1) [D loss: -50.314 R -283.546 F 216.242 G 1.699][G loss: -256.307]  0:06:41.470982
944 (5, 1) [D loss: -58.373 R -280.261 F 197.715 G 2.417][G loss: -149.648]  0:06:42.326060
945 (5, 1) [D loss: -56.134 R -315.976 F 235.283 G 2.456][G loss: -188.922]  0:06:43.192379
946 (5, 1) [D loss: -52.745 R -308.897 F 234.973 G 2.118][G loss: -187.987]  0:06:44.061849
947 (5, 1) [D loss: -50.743 R -249.210 F 175.331 G 2.314][G loss: -174.180]  0:06:44.917625
948 (5, 1) [D loss: -53.948 R -257.678 F 184.870 G 1.886][G loss: -183.684]  0:06:45.793431
949 (5, 1) [D loss: -43.867 R -275.258 F 209.540 G 2.185][G loss: -180.225]  0:06:46.660747
950 (5, 1) [D loss: -54.482 R -302.317 F 228.952 G 1.888][G loss: -212.858]  0:06:47.525349
951 (5, 1) [D loss: -39.327 R -245.078 F 180.230 G 2.552][G loss: -186.328]  0:06:48.389947
952 (5, 1) [D loss: -50.759 R -275.715 F 198.747 G 2.621][G loss: -207.310]  0:06:49.245820
953 (5, 1) [D loss: -53.726 R -275.420 F 206.247 G 1.545][G loss: -208.939]  0:06:50.108646
954 (5, 1) [D loss: -46.379 R -256.639 F 199.877 G 1.038][G loss: -202.458]  0:06:50.969925
955 (5, 1) [D loss: -53.838 R -195.228 F 114.568 G 2.682][G loss: -161.230]  0:06:51.836391
956 (5, 1) [D loss: -51.444 R -219.036 F 153.835 G 1.376][G loss: -201.721]  0:06:52.694981
957 (5, 1) [D loss: -62.492 R -189.388 F 113.628 G 1.327][G loss: -236.617]  0:06:53.551985
958 (5, 1) [D loss: -75.160 R -216.250 F 121.951 G 1.914][G loss: -292.183]  0:06:54.406459
959 (5, 1) [D loss: -53.506 R -250.403 F 155.708 G 4.119][G loss: -236.284]  0:06:55.270613
960 (5, 1) [D loss: -70.731 R -242.662 F 141.791 G 3.014][G loss: -334.576]  0:06:56.135821
961 (5, 1) [D loss: -60.125 R -211.448 F 129.430 G 2.189][G loss: -285.995]  0:06:57.012162
962 (5, 1) [D loss: -59.701 R -242.203 F 158.599 G 2.390][G loss: -352.164]  0:06:57.868171
963 (5, 1) [D loss: -52.211 R -193.298 F 127.057 G 1.403][G loss: -255.527]  0:06:58.734999
964 (5, 1) [D loss: -48.216 R -126.703 F 63.390 G 1.510][G loss: -96.760]  0:06:59.592068
965 (5, 1) [D loss: -66.837 R -149.483 F 53.447 G 2.920][G loss: -133.130]  0:07:00.445780
966 (5, 1) [D loss: -62.674 R -188.665 F 97.604 G 2.839][G loss: -152.711]  0:07:01.319835
967 (5, 1) [D loss: -85.046 R -204.252 F 76.425 G 4.278][G loss: -145.508]  0:07:02.181755
968 (5, 1) [D loss: -99.326 R -230.373 F 52.756 G 7.829][G loss: -97.352]  0:07:03.048640
969 (5, 1) [D loss: -98.155 R -223.819 F 62.594 G 6.307][G loss: -74.581]  0:07:03.918937
970 (5, 1) [D loss: -116.732 R -277.033 F 69.865 G 9.044][G loss: -83.741]  0:07:04.780626
971 (5, 1) [D loss: -89.711 R -268.021 F 43.432 G 13.488][G loss: -161.569]  0:07:05.640677
972 (5, 1) [D loss: -125.685 R -322.276 F 125.096 G 7.149][G loss: -20.892]  0:07:06.495423
973 (5, 1) [D loss: -141.022 R -335.376 F 151.734 G 4.262][G loss: -59.596]  0:07:07.344000
974 (5, 1) [D loss: -139.479 R -393.479 F 137.295 G 11.670][G loss: -175.372]  0:07:08.195891
975 (5, 1) [D loss: -140.043 R -391.668 F 42.693 G 20.893][G loss: -78.949]  0:07:09.054315
976 (5, 1) [D loss: -157.884 R -438.906 F 191.063 G 8.996][G loss: -141.167]  0:07:09.916552
977 (5, 1) [D loss: -152.317 R -444.230 F 192.611 G 9.930][G loss: -158.685]  0:07:10.764458
978 (5, 1) [D loss: -114.751 R -440.514 F 255.109 G 7.065][G loss: -245.070]  0:07:11.620942
979 (5, 1) [D loss: -133.105 R -482.502 F 257.530 G 9.187][G loss: -213.211]  0:07:12.478686
980 (5, 1) [D loss: -101.561 R -358.815 F 184.784 G 7.247][G loss: -186.653]  0:07:13.337760
981 (5, 1) [D loss: -101.380 R -372.686 F 200.616 G 7.069][G loss: -222.683]  0:07:14.207428
982 (5, 1) [D loss: -78.174 R -319.277 F 190.964 G 5.014][G loss: -199.867]  0:07:15.069682
983 (5, 1) [D loss: -88.027 R -409.979 F 277.633 G 4.432][G loss: -380.137]  0:07:15.933346
984 (5, 1) [D loss: -44.121 R -288.179 F 236.917 G 0.714][G loss: -268.112]  0:07:16.793516
985 (5, 1) [D loss: -69.707 R -405.677 F 314.721 G 2.125][G loss: -324.693]  0:07:17.647208
986 (5, 1) [D loss: -54.949 R -365.866 F 262.010 G 4.891][G loss: -381.639]  0:07:18.510315
987 (5, 1) [D loss: -48.627 R -373.945 F 280.501 G 4.482][G loss: -371.901]  0:07:19.361625
988 (5, 1) [D loss: -53.906 R -349.743 F 277.991 G 1.784][G loss: -318.147]  0:07:20.207146
989 (5, 1) [D loss: -34.855 R -391.078 F 342.798 G 1.342][G loss: -357.093]  0:07:21.058882
990 (5, 1) [D loss: -36.692 R -489.974 F 441.014 G 1.227][G loss: -396.285]  0:07:21.908840
991 (5, 1) [D loss: -42.234 R -469.313 F 411.765 G 1.531][G loss: -402.747]  0:07:22.767575
992 (5, 1) [D loss: -40.539 R -363.650 F 313.193 G 0.992][G loss: -309.504]  0:07:23.630264
993 (5, 1) [D loss: -39.789 R -361.934 F 308.512 G 1.363][G loss: -250.445]  0:07:24.502736
994 (5, 1) [D loss: -35.418 R -257.840 F 212.924 G 0.950][G loss: -217.680]  0:07:25.351688
995 (5, 1) [D loss: -40.651 R -290.244 F 240.568 G 0.902][G loss: -247.429]  0:07:26.198905
996 (5, 1) [D loss: -41.586 R -295.060 F 241.747 G 1.173][G loss: -237.297]  0:07:27.052375
997 (5, 1) [D loss: -36.394 R -259.907 F 213.825 G 0.969][G loss: -219.070]  0:07:27.906497
998 (5, 1) [D loss: -32.982 R -253.094 F 206.929 G 1.318][G loss: -223.025]  0:07:28.763163
999 (5, 1) [D loss: -35.312 R -246.359 F 200.045 G 1.100][G loss: -208.990]  0:07:29.612242
1000 (5, 1) [D loss: -25.670 R -240.976 F 210.908 G 0.440][G loss: -207.235]  0:07:30.467060
In [42]:
# Training in addition
# 追加で training する。

gan_work.train(
    data_flow,
    batch_size = BATCH_SIZE,
    epochs = 6000,
    run_folder = save_path1,
    print_every_n_batches = 2000,
    using_generator = True
)
1001 (5, 1) [D loss: -34.160 R -253.075 F 202.181 G 1.673][G loss: -221.984]  0:00:00.850222
1002 (5, 1) [D loss: -23.337 R -264.218 F 235.694 G 0.519][G loss: -229.298]  0:00:01.714649
1003 (5, 1) [D loss: -26.666 R -234.612 F 199.319 G 0.863][G loss: -200.731]  0:00:02.566652
1004 (5, 1) [D loss: -28.621 R -229.981 F 194.607 G 0.675][G loss: -195.755]  0:00:03.616948
1005 (5, 1) [D loss: -22.541 R -257.497 F 227.861 G 0.709][G loss: -212.452]  0:00:04.473033
1006 (5, 1) [D loss: -23.314 R -242.337 F 211.859 G 0.716][G loss: -215.902]  0:00:05.326734
1007 (5, 1) [D loss: -18.562 R -134.019 F 104.429 G 1.103][G loss: -103.327]  0:00:06.171406
1008 (5, 1) [D loss: -21.065 R -148.791 F 123.580 G 0.415][G loss: -105.166]  0:00:07.016568
1009 (5, 1) [D loss: -24.632 R -160.066 F 129.658 G 0.578][G loss: -136.224]  0:00:07.863141
1010 (5, 1) [D loss: -24.875 R -120.810 F 87.501 G 0.843][G loss: -93.962]  0:00:08.904432
1011 (5, 1) [D loss: -21.061 R -120.793 F 91.923 G 0.781][G loss: -69.315]  0:00:09.800357
1012 (5, 1) [D loss: -23.421 R -42.620 F 13.092 G 0.611][G loss: -11.093]  0:00:10.670454
1013 (5, 1) [D loss: -22.875 R -76.589 F 47.217 G 0.650][G loss: -65.460]  0:00:11.525491
1014 (5, 1) [D loss: -23.862 R -122.905 F 92.507 G 0.654][G loss: -83.928]  0:00:12.375625
1015 (5, 1) [D loss: -18.759 R -50.680 F 25.318 G 0.660][G loss: -23.242]  0:00:13.230921
1016 (5, 1) [D loss: -21.894 R -54.173 F 26.431 G 0.585][G loss: -8.410]  0:00:14.079351
1017 (5, 1) [D loss: -19.190 R -21.475 F -4.191 G 0.648][G loss: 1.395]  0:00:14.923375
1018 (5, 1) [D loss: -23.697 R -4.665 F -24.522 G 0.549][G loss: 38.018]  0:00:15.779139
1019 (5, 1) [D loss: -20.118 R -39.707 F 13.827 G 0.576][G loss: 17.057]  0:00:16.622413
1020 (5, 1) [D loss: -22.780 R -59.084 F 30.942 G 0.536][G loss: -9.525]  0:00:17.473439
1021 (5, 1) [D loss: -21.177 R -65.662 F 37.297 G 0.719][G loss: -36.419]  0:00:18.329293
1022 (5, 1) [D loss: -21.259 R -22.729 F -6.683 G 0.815][G loss: 13.482]  0:00:19.177369
1023 (5, 1) [D loss: -30.387 R 2.183 F -44.814 G 1.224][G loss: 54.487]  0:00:20.020431
1024 (5, 1) [D loss: -26.034 R 17.270 F -53.554 G 1.025][G loss: 55.221]  0:00:20.870734
1025 (5, 1) [D loss: -29.145 R -21.366 F -15.322 G 0.754][G loss: 14.153]  0:00:21.724590
1026 (5, 1) [D loss: -31.315 R -60.513 F 24.198 G 0.500][G loss: -36.550]  0:00:22.583372
1027 (5, 1) [D loss: -26.969 R -100.615 F 65.184 G 0.846][G loss: -75.826]  0:00:23.429663
1028 (5, 1) [D loss: -20.735 R -121.324 F 95.019 G 0.557][G loss: -94.518]  0:00:24.286393
1029 (5, 1) [D loss: -26.893 R -155.533 F 118.841 G 0.980][G loss: -134.972]  0:00:25.147144
1030 (5, 1) [D loss: -24.539 R -142.460 F 112.041 G 0.588][G loss: -136.729]  0:00:26.001438
1031 (5, 1) [D loss: -20.810 R -99.318 F 72.432 G 0.608][G loss: -65.953]  0:00:26.860252
1032 (5, 1) [D loss: -23.357 R -139.703 F 109.132 G 0.721][G loss: -95.272]  0:00:27.707256
1033 (5, 1) [D loss: -22.628 R -135.008 F 106.304 G 0.608][G loss: -106.640]  0:00:28.549562
1034 (5, 1) [D loss: -27.306 R -122.987 F 81.423 G 1.426][G loss: -117.739]  0:00:29.399965
1035 (5, 1) [D loss: -17.485 R -129.241 F 99.051 G 1.271][G loss: -102.209]  0:00:30.254115
1036 (5, 1) [D loss: -21.488 R -129.031 F 102.350 G 0.519][G loss: -100.999]  0:00:31.095326
1037 (5, 1) [D loss: -20.606 R -150.432 F 123.497 G 0.633][G loss: -111.602]  0:00:31.954038
1038 (5, 1) [D loss: -16.147 R -122.514 F 98.911 G 0.746][G loss: -89.606]  0:00:32.785611
1039 (5, 1) [D loss: -18.649 R -136.976 F 112.180 G 0.615][G loss: -116.804]  0:00:33.623042
1040 (5, 1) [D loss: -20.275 R -125.006 F 99.604 G 0.513][G loss: -95.583]  0:00:34.474769
1041 (5, 1) [D loss: -27.196 R -136.620 F 103.783 G 0.564][G loss: -105.452]  0:00:35.320598
1042 (5, 1) [D loss: -18.372 R -117.934 F 92.123 G 0.744][G loss: -105.662]  0:00:36.167508
1043 (5, 1) [D loss: -12.501 R -93.406 F 65.828 G 1.508][G loss: -66.741]  0:00:37.013361
1044 (5, 1) [D loss: -22.903 R -94.960 F 65.755 G 0.630][G loss: -81.600]  0:00:37.860178
1045 (5, 1) [D loss: -23.800 R -93.105 F 62.021 G 0.728][G loss: -81.081]  0:00:38.704821
1046 (5, 1) [D loss: -25.220 R -84.260 F 53.607 G 0.543][G loss: -65.797]  0:00:39.546022
1047 (5, 1) [D loss: -27.231 R -61.229 F 27.321 G 0.668][G loss: -49.025]  0:00:40.388876
1048 (5, 1) [D loss: -16.029 R -35.393 F 15.368 G 0.400][G loss: -7.244]  0:00:41.245556
1049 (5, 1) [D loss: -24.794 R -67.685 F 35.633 G 0.726][G loss: -63.834]  0:00:42.094470
1050 (5, 1) [D loss: -16.977 R -81.199 F 59.920 G 0.430][G loss: -55.968]  0:00:42.945403
1051 (5, 1) [D loss: -25.310 R -87.551 F 57.046 G 0.519][G loss: -64.329]  0:00:43.782317
1052 (5, 1) [D loss: -27.623 R -103.095 F 70.997 G 0.447][G loss: -102.594]  0:00:44.619080
1053 (5, 1) [D loss: -18.070 R -83.515 F 60.734 G 0.471][G loss: -66.540]  0:00:45.468536
1054 (5, 1) [D loss: -20.932 R -86.198 F 61.118 G 0.415][G loss: -68.387]  0:00:46.329051
1055 (5, 1) [D loss: -19.688 R -81.455 F 58.230 G 0.354][G loss: -50.729]  0:00:47.172367
1056 (5, 1) [D loss: -24.629 R -45.688 F 12.792 G 0.827][G loss: 13.385]  0:00:48.012297
1057 (5, 1) [D loss: -30.095 R -28.614 F -11.797 G 1.032][G loss: 35.324]  0:00:48.855371
1058 (5, 1) [D loss: -30.091 R -10.408 F -35.259 G 1.558][G loss: 33.314]  0:00:49.708826
1059 (5, 1) [D loss: -34.722 R -36.345 F -6.352 G 0.798][G loss: 21.369]  0:00:50.544631
1060 (5, 1) [D loss: -30.288 R -26.811 F -14.548 G 1.107][G loss: 27.751]  0:00:51.389637
1061 (5, 1) [D loss: -15.198 R -31.040 F 5.716 G 1.013][G loss: -18.829]  0:00:52.228585
1062 (5, 1) [D loss: -28.597 R -74.977 F 28.155 G 1.822][G loss: -66.024]  0:00:53.062300
1063 (5, 1) [D loss: -40.731 R -112.422 F 62.158 G 0.953][G loss: -101.201]  0:00:53.907508
1064 (5, 1) [D loss: -35.972 R -125.231 F 84.215 G 0.504][G loss: -121.119]  0:00:54.746562
1065 (5, 1) [D loss: -33.966 R -145.531 F 96.308 G 1.526][G loss: -129.877]  0:00:55.577188
1066 (5, 1) [D loss: -26.622 R -120.178 F 88.656 G 0.490][G loss: -124.765]  0:00:56.411437
1067 (5, 1) [D loss: -17.280 R -169.603 F 132.956 G 1.937][G loss: -123.523]  0:00:57.263181
1068 (5, 1) [D loss: -31.009 R -158.763 F 120.545 G 0.721][G loss: -157.437]  0:00:58.120502
1069 (5, 1) [D loss: -30.344 R -156.094 F 116.787 G 0.896][G loss: -125.931]  0:00:58.968463
1070 (5, 1) [D loss: -22.900 R -154.444 F 125.090 G 0.645][G loss: -121.512]  0:00:59.806349
1071 (5, 1) [D loss: -27.395 R -149.056 F 113.803 G 0.786][G loss: -130.220]  0:01:00.648556
1072 (5, 1) [D loss: -24.309 R -135.484 F 104.691 G 0.648][G loss: -101.305]  0:01:01.493530
1073 (5, 1) [D loss: -26.803 R -120.591 F 86.513 G 0.727][G loss: -105.955]  0:01:02.334204
1074 (5, 1) [D loss: -22.695 R -118.018 F 83.873 G 1.145][G loss: -76.395]  0:01:03.180676
1075 (5, 1) [D loss: -26.489 R -117.982 F 82.632 G 0.886][G loss: -113.288]  0:01:04.017946
1076 (5, 1) [D loss: -23.974 R -108.557 F 79.762 G 0.482][G loss: -69.758]  0:01:04.859435
1077 (5, 1) [D loss: -23.398 R -120.417 F 90.690 G 0.633][G loss: -79.688]  0:01:05.689118
1078 (5, 1) [D loss: -21.651 R -99.081 F 69.155 G 0.827][G loss: -62.277]  0:01:06.529127
1079 (5, 1) [D loss: -21.319 R -105.102 F 78.201 G 0.558][G loss: -80.716]  0:01:07.364070
1080 (5, 1) [D loss: -15.612 R -86.118 F 61.716 G 0.879][G loss: -63.062]  0:01:08.206635
1081 (5, 1) [D loss: -24.338 R -111.482 F 77.364 G 0.978][G loss: -71.107]  0:01:09.054527
1082 (5, 1) [D loss: -32.892 R -94.990 F 56.530 G 0.557][G loss: -83.855]  0:01:09.902529
1083 (5, 1) [D loss: -34.454 R -108.025 F 62.088 G 1.148][G loss: -89.459]  0:01:10.738999
1084 (5, 1) [D loss: -41.551 R -146.965 F 96.799 G 0.861][G loss: -161.353]  0:01:11.573915
1085 (5, 1) [D loss: -37.104 R -138.421 F 89.679 G 1.164][G loss: -170.128]  0:01:12.420399
1086 (5, 1) [D loss: -49.330 R -196.956 F 134.416 G 1.321][G loss: -219.389]  0:01:13.276815
1087 (5, 1) [D loss: -41.948 R -184.992 F 134.892 G 0.815][G loss: -222.030]  0:01:14.116716
1088 (5, 1) [D loss: -42.628 R -217.688 F 154.997 G 2.006][G loss: -273.112]  0:01:14.962647
1089 (5, 1) [D loss: -47.637 R -221.817 F 162.194 G 1.199][G loss: -308.369]  0:01:15.798866
1090 (5, 1) [D loss: -51.862 R -216.038 F 154.043 G 1.013][G loss: -303.838]  0:01:16.640419
1091 (5, 1) [D loss: -22.619 R -156.580 F 127.184 G 0.678][G loss: -204.852]  0:01:17.516827
1092 (5, 1) [D loss: -23.652 R -151.303 F 118.730 G 0.892][G loss: -181.892]  0:01:18.359419
1093 (5, 1) [D loss: -52.364 R -171.373 F 104.170 G 1.484][G loss: -262.188]  0:01:19.197866
1094 (5, 1) [D loss: -31.430 R -110.228 F 69.426 G 0.937][G loss: -172.849]  0:01:20.039083
1095 (5, 1) [D loss: -30.291 R -62.631 F 24.310 G 0.803][G loss: -79.723]  0:01:20.882302
1096 (5, 1) [D loss: -46.246 R 43.439 F -105.552 G 1.587][G loss: 140.396]  0:01:21.725439
1097 (5, 1) [D loss: -73.735 R 74.734 F -177.401 G 2.893][G loss: 301.485]  0:01:22.561774
1098 (5, 1) [D loss: -66.514 R 165.407 F -281.754 G 4.983][G loss: 228.826]  0:01:23.407861
1099 (5, 1) [D loss: -83.084 R 51.943 F -155.838 G 2.081][G loss: 362.354]  0:01:24.258690
1100 (5, 1) [D loss: -82.221 R -7.762 F -131.903 G 5.744][G loss: 219.493]  0:01:25.100794
1101 (5, 1) [D loss: -43.958 R -10.112 F -62.613 G 2.877][G loss: 130.616]  0:01:25.947839
1102 (5, 1) [D loss: -44.829 R -23.163 F -35.463 G 1.380][G loss: 75.551]  0:01:26.781309
1103 (5, 1) [D loss: -43.266 R -77.334 F 11.523 G 2.254][G loss: 26.479]  0:01:27.618770
1104 (5, 1) [D loss: -31.795 R -132.725 F 96.142 G 0.479][G loss: -81.208]  0:01:28.474548
1105 (5, 1) [D loss: -36.133 R -120.715 F 64.794 G 1.979][G loss: -58.343]  0:01:29.316224
1106 (5, 1) [D loss: -26.547 R -148.492 F 101.193 G 2.075][G loss: -94.141]  0:01:30.153958
1107 (5, 1) [D loss: -63.690 R -169.831 F 79.713 G 2.643][G loss: -75.548]  0:01:31.011350
1108 (5, 1) [D loss: -56.939 R -231.252 F 158.520 G 1.579][G loss: -89.565]  0:01:31.869619
1109 (5, 1) [D loss: -44.261 R -205.199 F 142.677 G 1.826][G loss: -127.628]  0:01:32.716860
1110 (5, 1) [D loss: -46.494 R -100.981 F 16.834 G 3.765][G loss: -63.983]  0:01:33.559954
1111 (5, 1) [D loss: -52.618 R -100.169 F 22.541 G 2.501][G loss: -65.105]  0:01:34.394504
1112 (5, 1) [D loss: -55.676 R -125.679 F 48.254 G 2.175][G loss: -59.904]  0:01:35.235305
1113 (5, 1) [D loss: -79.198 R -102.638 F -33.558 G 5.700][G loss: -77.730]  0:01:36.070171
1114 (5, 1) [D loss: -62.393 R -105.739 F 15.652 G 2.769][G loss: -87.255]  0:01:36.902523
1115 (5, 1) [D loss: -58.152 R -102.644 F 27.673 G 1.682][G loss: -102.071]  0:01:37.736806
1116 (5, 1) [D loss: -47.841 R -110.900 F 36.824 G 2.623][G loss: -106.756]  0:01:38.577853
1117 (5, 1) [D loss: -51.211 R -125.330 F 48.685 G 2.543][G loss: -138.447]  0:01:39.422831
1118 (5, 1) [D loss: -55.246 R -136.616 F 71.950 G 0.942][G loss: -135.762]  0:01:40.260881
1119 (5, 1) [D loss: -53.566 R -145.518 F 68.146 G 2.381][G loss: -148.709]  0:01:41.103992
1120 (5, 1) [D loss: -45.083 R -138.944 F 79.687 G 1.417][G loss: -150.840]  0:01:41.941256
1121 (5, 1) [D loss: -62.977 R -165.462 F 83.396 G 1.909][G loss: -200.840]  0:01:42.783248
1122 (5, 1) [D loss: -42.472 R -134.230 F 80.449 G 1.131][G loss: -171.264]  0:01:43.633727
1123 (5, 1) [D loss: -52.993 R -157.319 F 70.974 G 3.335][G loss: -167.465]  0:01:44.475520
1124 (5, 1) [D loss: -52.852 R -138.146 F 71.136 G 1.416][G loss: -188.908]  0:01:45.316924
1125 (5, 1) [D loss: -51.032 R -158.514 F 94.294 G 1.319][G loss: -191.465]  0:01:46.155324
1126 (5, 1) [D loss: -37.796 R -137.208 F 84.858 G 1.455][G loss: -170.022]  0:01:47.000149
1127 (5, 1) [D loss: -31.229 R -135.749 F 100.017 G 0.450][G loss: -128.845]  0:01:47.836565
1128 (5, 1) [D loss: -24.969 R -151.242 F 117.429 G 0.884][G loss: -93.724]  0:01:48.679240
1129 (5, 1) [D loss: -31.886 R -126.071 F 85.080 G 0.911][G loss: -95.818]  0:01:49.523797
1130 (5, 1) [D loss: -27.175 R -235.949 F 190.305 G 1.847][G loss: -215.764]  0:01:50.364201
1131 (5, 1) [D loss: -22.831 R -165.568 F 133.803 G 0.893][G loss: -89.700]  0:01:51.201533
1132 (5, 1) [D loss: -25.840 R -138.698 F 102.818 G 1.004][G loss: -80.128]  0:01:52.030241
1133 (5, 1) [D loss: -24.752 R -111.274 F 78.093 G 0.843][G loss: -77.356]  0:01:52.867292
1134 (5, 1) [D loss: -26.233 R -75.157 F 37.010 G 1.191][G loss: -39.006]  0:01:53.707988
1135 (5, 1) [D loss: -40.490 R -88.046 F 36.670 G 1.089][G loss: -23.365]  0:01:54.547956
1136 (5, 1) [D loss: -49.076 R 14.300 F -80.842 G 1.747][G loss: 26.636]  0:01:55.382197
1137 (5, 1) [D loss: -74.131 R 19.480 F -119.155 G 2.554][G loss: 21.632]  0:01:56.230253
1138 (5, 1) [D loss: -57.428 R 24.618 F -114.576 G 3.253][G loss: -26.142]  0:01:57.070315
1139 (5, 1) [D loss: -51.639 R -57.988 F -20.893 G 2.724][G loss: -120.371]  0:01:57.904424
1140 (5, 1) [D loss: -78.002 R -155.515 F 42.013 G 3.550][G loss: -231.588]  0:01:58.786958
1141 (5, 1) [D loss: -74.040 R -241.181 F 112.255 G 5.489][G loss: -295.848]  0:01:59.629915
1142 (5, 1) [D loss: -67.746 R -189.205 F 87.241 G 3.422][G loss: -254.807]  0:02:00.464163
1143 (5, 1) [D loss: -57.455 R -36.287 F -39.450 G 1.828][G loss: -121.648]  0:02:01.296993
1144 (5, 1) [D loss: -48.490 R -86.936 F 16.096 G 2.235][G loss: -183.263]  0:02:02.136008
1145 (5, 1) [D loss: -48.890 R -80.975 F 10.776 G 2.131][G loss: -111.787]  0:02:02.970217
1146 (5, 1) [D loss: -54.151 R -103.373 F 28.008 G 2.121][G loss: -116.380]  0:02:03.816801
1147 (5, 1) [D loss: -62.709 R -150.913 F 61.187 G 2.702][G loss: -212.549]  0:02:04.667305
1148 (5, 1) [D loss: -66.398 R -74.735 F -10.521 G 1.886][G loss: -15.511]  0:02:05.502684
1149 (5, 1) [D loss: -71.196 R -39.535 F -58.617 G 2.696][G loss: 22.425]  0:02:06.335159
1150 (5, 1) [D loss: -109.125 R -89.273 F -61.271 G 4.142][G loss: 158.980]  0:02:07.164742
1151 (5, 1) [D loss: -119.430 R 2.686 F -191.859 G 6.974][G loss: 245.681]  0:02:07.999950
1152 (5, 1) [D loss: -134.143 R -151.882 F -50.967 G 6.871][G loss: 151.855]  0:02:08.834212
1153 (5, 1) [D loss: -145.587 R -110.078 F -115.396 G 7.989][G loss: 229.968]  0:02:09.670456
1154 (5, 1) [D loss: -127.419 R -3.692 F -173.390 G 4.966][G loss: 289.936]  0:02:10.507334
1155 (5, 1) [D loss: -148.282 R -87.606 F -145.833 G 8.516][G loss: 248.095]  0:02:11.343029
1156 (5, 1) [D loss: -161.129 R -77.334 F -169.150 G 8.536][G loss: 268.389]  0:02:12.179549
1157 (5, 1) [D loss: -133.121 R -6.734 F -179.456 G 5.307][G loss: 236.005]  0:02:13.011616
1158 (5, 1) [D loss: -157.045 R -100.934 F -130.845 G 7.473][G loss: 85.679]  0:02:13.851448
1159 (5, 1) [D loss: -130.409 R -127.261 F -49.168 G 4.602][G loss: -51.811]  0:02:14.683460
1160 (5, 1) [D loss: -81.336 R -152.595 F -78.061 G 14.932][G loss: -155.481]  0:02:15.521268
1161 (5, 1) [D loss: -70.455 R -191.857 F 73.540 G 4.786][G loss: -247.519]  0:02:16.345483
1162 (5, 1) [D loss: -38.938 R -314.739 F 241.809 G 3.399][G loss: -295.619]  0:02:17.186021
1163 (5, 1) [D loss: -42.437 R -332.599 F 274.398 G 1.576][G loss: -339.422]  0:02:18.010937
1164 (5, 1) [D loss: -49.403 R -460.001 F 386.670 G 2.393][G loss: -474.989]  0:02:18.844201
1165 (5, 1) [D loss: -63.251 R -552.212 F 468.774 G 2.019][G loss: -588.764]  0:02:19.699962
1166 (5, 1) [D loss: -56.451 R -582.632 F 495.161 G 3.102][G loss: -587.603]  0:02:20.521582
1167 (5, 1) [D loss: -37.542 R -578.578 F 516.986 G 2.405][G loss: -569.711]  0:02:21.350138
1168 (5, 1) [D loss: -43.023 R -662.973 F 590.791 G 2.916][G loss: -625.018]  0:02:22.178437
1169 (5, 1) [D loss: -37.746 R -689.213 F 643.051 G 0.842][G loss: -605.269]  0:02:23.013473
1170 (5, 1) [D loss: -23.204 R -447.889 F 418.199 G 0.649][G loss: -354.660]  0:02:23.842180
1171 (5, 1) [D loss: -42.980 R -498.759 F 444.884 G 1.089][G loss: -429.813]  0:02:24.687337
1172 (5, 1) [D loss: -33.841 R -501.267 F 441.400 G 2.603][G loss: -438.847]  0:02:25.514882
1173 (5, 1) [D loss: -39.983 R -530.629 F 477.063 G 1.358][G loss: -474.091]  0:02:26.340936
1174 (5, 1) [D loss: -32.691 R -375.970 F 335.671 G 0.761][G loss: -316.465]  0:02:27.178859
1175 (5, 1) [D loss: -40.248 R -386.548 F 332.877 G 1.342][G loss: -323.873]  0:02:28.034540
1176 (5, 1) [D loss: -37.737 R -374.221 F 322.774 G 1.371][G loss: -332.362]  0:02:28.875772
1177 (5, 1) [D loss: -37.826 R -296.386 F 235.360 G 2.320][G loss: -216.405]  0:02:29.708561
1178 (5, 1) [D loss: -44.789 R -249.245 F 189.659 G 1.480][G loss: -206.962]  0:02:30.545750
1179 (5, 1) [D loss: -55.984 R -253.560 F 180.234 G 1.734][G loss: -120.942]  0:02:31.374598
1180 (5, 1) [D loss: -42.839 R -271.687 F 210.131 G 1.872][G loss: -225.841]  0:02:32.215278
1181 (5, 1) [D loss: -45.964 R -282.242 F 217.504 G 1.877][G loss: -189.780]  0:02:33.046237
1182 (5, 1) [D loss: -41.448 R -181.350 F 114.770 G 2.513][G loss: -144.946]  0:02:33.875351
1183 (5, 1) [D loss: -38.904 R -186.354 F 122.700 G 2.475][G loss: -143.933]  0:02:34.706034
1184 (5, 1) [D loss: -33.336 R -254.067 F 199.202 G 2.153][G loss: -169.676]  0:02:35.542412
1185 (5, 1) [D loss: -58.871 R -156.628 F 80.516 G 1.724][G loss: -79.537]  0:02:36.366252
1186 (5, 1) [D loss: -37.540 R -213.069 F 157.524 G 1.800][G loss: -148.899]  0:02:37.210576
1187 (5, 1) [D loss: -31.036 R -153.945 F 105.156 G 1.775][G loss: -127.130]  0:02:38.031704
1188 (5, 1) [D loss: -44.053 R -126.596 F 54.766 G 2.778][G loss: -105.212]  0:02:38.869728
1189 (5, 1) [D loss: -37.980 R -136.767 F 79.129 G 1.966][G loss: -115.301]  0:02:39.695955
1190 (5, 1) [D loss: -46.666 R -135.828 F 76.325 G 1.284][G loss: -106.541]  0:02:40.541988
1191 (5, 1) [D loss: -40.089 R -134.024 F 80.746 G 1.319][G loss: -123.997]  0:02:41.375513
1192 (5, 1) [D loss: -41.005 R -101.162 F 44.011 G 1.615][G loss: -90.463]  0:02:42.213853
1193 (5, 1) [D loss: -46.915 R -94.764 F 28.059 G 1.979][G loss: -104.412]  0:02:43.070080
1194 (5, 1) [D loss: -38.538 R -49.240 F -10.412 G 2.111][G loss: -84.008]  0:02:43.900232
1195 (5, 1) [D loss: -42.071 R -22.555 F -38.685 G 1.917][G loss: -44.842]  0:02:44.736158
1196 (5, 1) [D loss: -25.314 R 8.535 F -50.429 G 1.658][G loss: -34.690]  0:02:45.567952
1197 (5, 1) [D loss: -40.521 R 5.231 F -58.670 G 1.292][G loss: -21.734]  0:02:46.403000
1198 (5, 1) [D loss: -29.952 R 86.657 F -124.399 G 0.779][G loss: 76.866]  0:02:47.257372
1199 (5, 1) [D loss: -34.873 R 71.954 F -115.896 G 0.907][G loss: 51.866]  0:02:48.102702
1200 (5, 1) [D loss: -33.097 R 84.510 F -128.417 G 1.081][G loss: 80.521]  0:02:48.929867
1201 (5, 1) [D loss: -38.056 R 138.714 F -191.633 G 1.486][G loss: 149.425]  0:02:49.769079
1202 (5, 1) [D loss: -51.506 R 187.083 F -253.785 G 1.520][G loss: 313.840]  0:02:50.620228
1203 (5, 1) [D loss: -46.238 R 204.984 F -278.673 G 2.745][G loss: 285.730]  0:02:51.476246
1204 (5, 1) [D loss: -46.190 R 156.547 F -220.307 G 1.757][G loss: 290.821]  0:02:52.283576
1205 (5, 1) [D loss: -42.010 R 105.545 F -158.685 G 1.113][G loss: 218.692]  0:02:53.083555
1206 (5, 1) [D loss: -37.847 R 39.443 F -85.125 G 0.783][G loss: 130.438]  0:02:53.899692
1207 (5, 1) [D loss: -26.598 R 27.824 F -64.911 G 1.049][G loss: 58.792]  0:02:54.700745
1208 (5, 1) [D loss: -43.112 R 14.564 F -74.777 G 1.710][G loss: 90.890]  0:02:55.520591
1209 (5, 1) [D loss: -34.867 R -55.715 F 6.083 G 1.476][G loss: 20.972]  0:02:56.319146
1210 (5, 1) [D loss: -39.775 R -121.388 F 72.851 G 0.876][G loss: -45.051]  0:02:57.129986
1211 (5, 1) [D loss: -71.908 R -152.072 F 49.135 G 3.103][G loss: -12.114]  0:02:57.927990
1212 (5, 1) [D loss: -55.458 R -222.799 F 150.458 G 1.688][G loss: -123.052]  0:02:58.730603
1213 (5, 1) [D loss: -50.352 R -231.203 F 150.321 G 3.053][G loss: -164.048]  0:02:59.535537
1214 (5, 1) [D loss: -43.481 R -229.503 F 165.651 G 2.037][G loss: -189.095]  0:03:00.338962
1215 (5, 1) [D loss: -48.616 R -292.375 F 221.267 G 2.249][G loss: -236.090]  0:03:01.155604
1216 (5, 1) [D loss: -33.770 R -311.755 F 271.583 G 0.640][G loss: -233.716]  0:03:01.970150
1217 (5, 1) [D loss: -53.643 R -209.819 F 120.684 G 3.549][G loss: -132.544]  0:03:02.773921
1218 (5, 1) [D loss: -67.764 R -193.359 F 99.034 G 2.656][G loss: -140.122]  0:03:03.582776
1219 (5, 1) [D loss: -40.103 R -210.657 F 151.724 G 1.883][G loss: -165.445]  0:03:04.390319
1220 (5, 1) [D loss: 1.738 R -219.232 F 160.388 G 6.058][G loss: -174.880]  0:03:05.198815
1221 (5, 1) [D loss: -47.704 R -175.571 F 83.967 G 4.390][G loss: -130.801]  0:03:06.004830
1222 (5, 1) [D loss: -45.796 R -159.074 F 85.564 G 2.771][G loss: -108.717]  0:03:06.820955
1223 (5, 1) [D loss: -74.822 R -206.459 F 106.132 G 2.551][G loss: -144.060]  0:03:07.635257
1224 (5, 1) [D loss: -52.371 R -174.234 F 107.442 G 1.442][G loss: -136.873]  0:03:08.437214
1225 (5, 1) [D loss: -60.397 R -192.453 F 111.024 G 2.103][G loss: -159.227]  0:03:09.251062
1226 (5, 1) [D loss: -66.337 R -188.355 F 94.948 G 2.707][G loss: -139.834]  0:03:10.069592
1227 (5, 1) [D loss: -43.996 R -153.694 F 98.838 G 1.086][G loss: -134.457]  0:03:10.881337
1228 (5, 1) [D loss: -59.373 R -205.537 F 123.466 G 2.270][G loss: -164.805]  0:03:11.698453
1229 (5, 1) [D loss: -36.712 R -153.623 F 108.663 G 0.825][G loss: -127.461]  0:03:12.511911
1230 (5, 1) [D loss: -43.465 R -143.297 F 72.794 G 2.704][G loss: -138.752]  0:03:13.327591
1231 (5, 1) [D loss: -51.203 R -150.071 F 87.974 G 1.089][G loss: -133.605]  0:03:14.142701
1232 (5, 1) [D loss: -42.252 R -149.673 F 88.255 G 1.917][G loss: -128.063]  0:03:14.944236
1233 (5, 1) [D loss: -63.722 R -155.661 F 69.030 G 2.291][G loss: -123.210]  0:03:15.750490
1234 (5, 1) [D loss: -50.111 R -125.297 F 61.903 G 1.328][G loss: -111.475]  0:03:16.564970
1235 (5, 1) [D loss: -64.206 R -142.399 F 53.418 G 2.477][G loss: -129.102]  0:03:17.375460
1236 (5, 1) [D loss: -57.388 R -130.645 F 55.262 G 1.799][G loss: -126.234]  0:03:18.174648
1237 (5, 1) [D loss: -40.908 R -111.468 F 60.990 G 0.957][G loss: -87.746]  0:03:18.977953
1238 (5, 1) [D loss: -44.567 R -130.641 F 70.235 G 1.584][G loss: -105.128]  0:03:19.782609
1239 (5, 1) [D loss: -42.354 R -146.397 F 87.864 G 1.618][G loss: -112.339]  0:03:20.586744
1240 (5, 1) [D loss: -31.308 R -150.235 F 101.944 G 1.698][G loss: -116.907]  0:03:21.395675
1241 (5, 1) [D loss: -42.375 R -136.716 F 76.445 G 1.790][G loss: -110.051]  0:03:22.195643
1242 (5, 1) [D loss: -30.395 R -94.135 F 49.118 G 1.462][G loss: -37.619]  0:03:23.003339
1243 (5, 1) [D loss: -34.747 R -70.121 F 15.205 G 2.017][G loss: -42.978]  0:03:23.809296
1244 (5, 1) [D loss: -42.779 R -54.864 F -4.688 G 1.677][G loss: -37.578]  0:03:24.618911
1245 (5, 1) [D loss: -23.937 R -24.534 F -12.333 G 1.293][G loss: 19.554]  0:03:25.427961
1246 (5, 1) [D loss: -30.641 R 20.394 F -63.370 G 1.233][G loss: 50.082]  0:03:26.232445
1247 (5, 1) [D loss: -43.397 R -5.254 F -51.055 G 1.291][G loss: 25.033]  0:03:27.041833
1248 (5, 1) [D loss: -31.388 R -1.069 F -41.270 G 1.095][G loss: 47.222]  0:03:27.852627
1249 (5, 1) [D loss: -33.255 R 27.475 F -75.598 G 1.487][G loss: 111.464]  0:03:28.654425
1250 (5, 1) [D loss: -36.602 R 30.429 F -80.146 G 1.312][G loss: 60.739]  0:03:29.451279
1251 (5, 1) [D loss: -38.137 R 10.385 F -59.672 G 1.115][G loss: 54.083]  0:03:30.254095
1252 (5, 1) [D loss: -44.640 R 11.164 F -65.509 G 0.971][G loss: 61.059]  0:03:31.069847
1253 (5, 1) [D loss: -57.977 R 19.090 F -94.134 G 1.707][G loss: 73.293]  0:03:31.875540
1254 (5, 1) [D loss: -32.901 R 43.984 F -92.880 G 1.599][G loss: 72.026]  0:03:32.691563
1255 (5, 1) [D loss: -56.662 R 51.967 F -126.051 G 1.742][G loss: 84.681]  0:03:33.490612
1256 (5, 1) [D loss: -54.848 R 37.025 F -115.997 G 2.412][G loss: 72.111]  0:03:34.304936
1257 (5, 1) [D loss: -38.774 R 82.437 F -135.626 G 1.441][G loss: 99.585]  0:03:35.123443
1258 (5, 1) [D loss: -56.206 R 24.232 F -100.756 G 2.032][G loss: 37.858]  0:03:35.923652
1259 (5, 1) [D loss: -55.902 R 33.881 F -114.185 G 2.440][G loss: 55.625]  0:03:36.740238
1260 (5, 1) [D loss: -52.624 R 70.722 F -151.284 G 2.794][G loss: 74.770]  0:03:37.545377
1261 (5, 1) [D loss: -65.023 R 138.618 F -224.536 G 2.089][G loss: 78.043]  0:03:38.357420
1262 (5, 1) [D loss: -93.970 R 62.740 F -201.346 G 4.464][G loss: -53.690]  0:03:39.162542
1263 (5, 1) [D loss: -95.831 R 63.263 F -192.060 G 3.297][G loss: -13.846]  0:03:39.964237
1264 (5, 1) [D loss: -112.063 R -40.775 F -154.255 G 8.297][G loss: -192.489]  0:03:40.775063
1265 (5, 1) [D loss: -84.102 R 11.675 F -152.779 G 5.700][G loss: -144.675]  0:03:41.590372
1266 (5, 1) [D loss: -94.374 R 22.596 F -172.231 G 5.526][G loss: -98.263]  0:03:42.401074
1267 (5, 1) [D loss: -78.959 R 66.121 F -175.576 G 3.050][G loss: -6.914]  0:03:43.227477
1268 (5, 1) [D loss: -96.645 R 54.878 F -195.480 G 4.396][G loss: 96.529]  0:03:44.028682
1269 (5, 1) [D loss: -110.917 R 68.905 F -224.057 G 4.423][G loss: 255.299]  0:03:44.832849
1270 (5, 1) [D loss: -105.597 R 140.669 F -324.292 G 7.803][G loss: 188.710]  0:03:45.631953
1271 (5, 1) [D loss: -128.188 R 62.133 F -277.911 G 8.759][G loss: 254.528]  0:03:46.438478
1272 (5, 1) [D loss: -131.885 R 82.439 F -311.805 G 9.748][G loss: 263.532]  0:03:47.251558
1273 (5, 1) [D loss: -187.711 R -4.976 F -270.985 G 8.825][G loss: 418.153]  0:03:48.046730
1274 (5, 1) [D loss: -148.358 R 98.320 F -513.800 G 26.712][G loss: 34.923]  0:03:48.857949
1275 (5, 1) [D loss: -198.414 R -179.508 F -76.455 G 5.755][G loss: 313.937]  0:03:49.671456
1276 (5, 1) [D loss: -174.779 R -45.538 F -233.830 G 10.459][G loss: 288.967]  0:03:50.482281
1277 (5, 1) [D loss: -184.356 R -23.332 F -236.403 G 7.538][G loss: 393.734]  0:03:51.287391
1278 (5, 1) [D loss: -172.295 R -40.549 F -245.145 G 11.340][G loss: 270.310]  0:03:52.092121
1279 (5, 1) [D loss: -140.764 R -64.454 F -112.835 G 3.653][G loss: 232.601]  0:03:52.894907
1280 (5, 1) [D loss: -166.011 R -104.836 F -143.354 G 8.218][G loss: 253.205]  0:03:53.705593
1281 (5, 1) [D loss: -142.249 R -145.199 F -66.121 G 6.907][G loss: 137.108]  0:03:54.526028
1282 (5, 1) [D loss: -103.896 R -164.500 F 15.852 G 4.475][G loss: 50.541]  0:03:55.332309
1283 (5, 1) [D loss: -109.128 R -267.422 F 101.036 G 5.726][G loss: -85.592]  0:03:56.140731
1284 (5, 1) [D loss: -79.426 R -349.009 F 221.469 G 4.811][G loss: -184.107]  0:03:56.945048
1285 (5, 1) [D loss: -75.109 R -436.328 F 324.492 G 3.673][G loss: -327.159]  0:03:57.752432
1286 (5, 1) [D loss: -56.579 R -643.545 F 571.512 G 1.545][G loss: -602.370]  0:03:58.558887
1287 (5, 1) [D loss: -67.048 R -638.071 F 535.971 G 3.505][G loss: -506.332]  0:03:59.358968
1288 (5, 1) [D loss: -61.654 R -721.510 F 638.377 G 2.148][G loss: -667.520]  0:04:00.167453
1289 (5, 1) [D loss: -78.458 R -422.134 F 323.846 G 1.983][G loss: -333.669]  0:04:00.974915
1290 (5, 1) [D loss: -70.521 R -547.495 F 459.871 G 1.710][G loss: -511.711]  0:04:01.777007
1291 (5, 1) [D loss: -44.914 R -598.127 F 542.993 G 1.022][G loss: -464.954]  0:04:02.584997
1292 (5, 1) [D loss: -46.522 R -534.327 F 469.813 G 1.799][G loss: -538.304]  0:04:03.394362
1293 (5, 1) [D loss: -70.899 R -517.124 F 417.922 G 2.830][G loss: -492.527]  0:04:04.206634
1294 (5, 1) [D loss: -66.427 R -518.327 F 428.136 G 2.376][G loss: -515.778]  0:04:05.010917
1295 (5, 1) [D loss: -57.361 R -440.884 F 360.506 G 2.302][G loss: -449.249]  0:04:05.811746
1296 (5, 1) [D loss: -61.448 R -491.954 F 401.150 G 2.936][G loss: -485.684]  0:04:06.609851
1297 (5, 1) [D loss: -66.271 R -481.463 F 377.386 G 3.781][G loss: -468.689]  0:04:07.419194
1298 (5, 1) [D loss: -31.080 R -511.301 F 434.213 G 4.601][G loss: -442.266]  0:04:08.219020
1299 (5, 1) [D loss: -61.286 R -475.862 F 379.638 G 3.494][G loss: -453.607]  0:04:09.016559
1300 (5, 1) [D loss: -84.241 R -499.251 F 387.957 G 2.705][G loss: -510.466]  0:04:09.820852
1301 (5, 1) [D loss: -42.507 R -479.152 F 405.039 G 3.161][G loss: -463.869]  0:04:10.620195
1302 (5, 1) [D loss: -71.426 R -424.828 F 335.969 G 1.743][G loss: -456.216]  0:04:11.425600
1303 (5, 1) [D loss: -68.418 R -445.334 F 341.040 G 3.588][G loss: -461.912]  0:04:12.230436
1304 (5, 1) [D loss: -39.032 R -422.840 F 365.553 G 1.826][G loss: -423.815]  0:04:13.045286
1305 (5, 1) [D loss: -56.518 R -469.353 F 383.486 G 2.935][G loss: -446.493]  0:04:13.870419
1306 (5, 1) [D loss: -50.326 R -446.099 F 382.102 G 1.367][G loss: -450.904]  0:04:14.673639
1307 (5, 1) [D loss: -33.623 R -502.258 F 438.030 G 3.061][G loss: -433.882]  0:04:15.483201
1308 (5, 1) [D loss: -47.085 R -478.917 F 409.507 G 2.232][G loss: -438.303]  0:04:16.309701
1309 (5, 1) [D loss: -44.441 R -373.401 F 316.775 G 1.219][G loss: -319.962]  0:04:17.121732
1310 (5, 1) [D loss: -49.535 R -378.310 F 312.687 G 1.609][G loss: -338.106]  0:04:17.927047
1311 (5, 1) [D loss: -50.382 R -384.392 F 316.732 G 1.728][G loss: -347.912]  0:04:18.730121
1312 (5, 1) [D loss: -50.271 R -321.818 F 255.577 G 1.597][G loss: -279.973]  0:04:19.537431
1313 (5, 1) [D loss: -41.221 R -293.512 F 241.935 G 1.036][G loss: -243.068]  0:04:20.342864
1314 (5, 1) [D loss: -41.866 R -300.473 F 240.874 G 1.773][G loss: -276.752]  0:04:21.153020
1315 (5, 1) [D loss: -47.101 R -186.848 F 123.132 G 1.662][G loss: -111.779]  0:04:21.962784
1316 (5, 1) [D loss: -43.425 R -196.964 F 140.171 G 1.337][G loss: -141.445]  0:04:22.772124
1317 (5, 1) [D loss: -32.179 R -188.555 F 143.043 G 1.333][G loss: -122.110]  0:04:23.574779
1318 (5, 1) [D loss: -35.848 R -115.296 F 65.934 G 1.351][G loss: -79.145]  0:04:24.399823
1319 (5, 1) [D loss: -43.029 R -89.922 F 32.876 G 1.402][G loss: -32.041]  0:04:25.204758
1320 (5, 1) [D loss: -33.886 R -88.833 F 42.895 G 1.205][G loss: -69.351]  0:04:26.007851
1321 (5, 1) [D loss: -40.466 R -80.117 F 26.819 G 1.283][G loss: -35.726]  0:04:26.824253
1322 (5, 1) [D loss: -40.158 R -39.497 F -17.045 G 1.638][G loss: -36.403]  0:04:27.632394
1323 (5, 1) [D loss: -48.437 R -60.659 F -7.435 G 1.966][G loss: -47.520]  0:04:28.440684
1324 (5, 1) [D loss: -38.335 R -48.018 F -6.148 G 1.583][G loss: -24.242]  0:04:29.241016
1325 (5, 1) [D loss: -38.417 R -73.320 F 16.484 G 1.842][G loss: -55.143]  0:04:30.049918
1326 (5, 1) [D loss: -43.009 R -67.038 F 7.381 G 1.665][G loss: -65.310]  0:04:30.859874
1327 (5, 1) [D loss: -50.716 R -59.704 F -8.902 G 1.789][G loss: 2.203]  0:04:31.672404
1328 (5, 1) [D loss: -60.840 R -70.445 F -18.036 G 2.764][G loss: 37.205]  0:04:32.476697
1329 (5, 1) [D loss: -45.353 R -45.469 F -16.605 G 1.672][G loss: 19.584]  0:04:33.285822
1330 (5, 1) [D loss: -51.032 R -49.451 F -20.847 G 1.927][G loss: 16.442]  0:04:34.094821
1331 (5, 1) [D loss: -70.442 R -37.432 F -58.779 G 2.577][G loss: 98.452]  0:04:34.907987
1332 (5, 1) [D loss: -74.637 R -3.738 F -114.426 G 4.353][G loss: 141.526]  0:04:35.712576
1333 (5, 1) [D loss: -101.569 R 18.930 F -160.986 G 4.049][G loss: 217.545]  0:04:36.515349
1334 (5, 1) [D loss: -119.457 R 51.050 F -207.233 G 3.673][G loss: 254.990]  0:04:37.330146
1335 (5, 1) [D loss: -175.484 R 106.306 F -418.197 G 13.641][G loss: 169.502]  0:04:38.144324
1336 (5, 1) [D loss: -185.210 R 81.744 F -386.382 G 11.943][G loss: 101.757]  0:04:38.949093
1337 (5, 1) [D loss: -182.423 R 120.138 F -412.822 G 11.026][G loss: 79.533]  0:04:39.754358
1338 (5, 1) [D loss: -150.782 R 24.063 F -217.084 G 4.224][G loss: -34.050]  0:04:40.562807
1339 (5, 1) [D loss: -207.525 R 12.534 F -330.722 G 11.066][G loss: -94.193]  0:04:41.366050
1340 (5, 1) [D loss: -195.136 R -34.226 F -244.676 G 8.377][G loss: -114.230]  0:04:42.166688
1341 (5, 1) [D loss: -145.477 R 33.150 F -273.119 G 9.449][G loss: -90.680]  0:04:42.988339
1342 (5, 1) [D loss: -114.480 R -13.600 F -139.978 G 3.910][G loss: -89.102]  0:04:43.784362
1343 (5, 1) [D loss: -45.324 R -52.922 F -6.744 G 1.434][G loss: -63.023]  0:04:44.581883
1344 (5, 1) [D loss: -37.476 R -112.015 F 53.286 G 2.125][G loss: -105.762]  0:04:45.395039
1345 (5, 1) [D loss: -65.417 R -181.675 F 94.125 G 2.213][G loss: -145.458]  0:04:46.197577
1346 (5, 1) [D loss: -64.346 R -219.501 F 117.835 G 3.732][G loss: -198.674]  0:04:47.014956
1347 (5, 1) [D loss: -57.555 R -279.630 F 201.750 G 2.033][G loss: -223.904]  0:04:47.825683
1348 (5, 1) [D loss: -49.659 R -270.914 F 193.301 G 2.795][G loss: -210.996]  0:04:48.636799
1349 (5, 1) [D loss: -62.247 R -333.784 F 235.716 G 3.582][G loss: -256.777]  0:04:49.463811
1350 (5, 1) [D loss: -70.770 R -363.616 F 266.837 G 2.601][G loss: -259.958]  0:04:50.274493
1351 (5, 1) [D loss: -35.720 R -268.262 F 203.871 G 2.867][G loss: -219.128]  0:04:51.081010
1352 (5, 1) [D loss: -49.624 R -284.961 F 219.351 G 1.599][G loss: -209.838]  0:04:51.879038
1353 (5, 1) [D loss: -47.498 R -273.147 F 207.153 G 1.850][G loss: -210.176]  0:04:52.693319
1354 (5, 1) [D loss: -47.890 R -278.753 F 213.258 G 1.760][G loss: -225.746]  0:04:53.493662
1355 (5, 1) [D loss: -53.908 R -287.399 F 213.657 G 1.983][G loss: -221.729]  0:04:54.307364
1356 (5, 1) [D loss: -54.114 R -344.786 F 270.625 G 2.005][G loss: -280.121]  0:04:55.126357
1357 (5, 1) [D loss: -44.148 R -357.430 F 292.744 G 2.054][G loss: -310.878]  0:04:55.928082
1358 (5, 1) [D loss: -44.758 R -374.689 F 310.444 G 1.949][G loss: -301.095]  0:04:56.740686
1359 (5, 1) [D loss: -21.018 R -342.097 F 298.029 G 2.305][G loss: -315.719]  0:04:57.548295
1360 (5, 1) [D loss: -46.852 R -231.805 F 167.894 G 1.706][G loss: -206.993]  0:04:58.355544
1361 (5, 1) [D loss: -53.959 R -301.578 F 230.895 G 1.672][G loss: -232.934]  0:04:59.174288
1362 (5, 1) [D loss: -53.138 R -274.286 F 206.582 G 1.457][G loss: -249.660]  0:04:59.978916
1363 (5, 1) [D loss: -41.551 R -219.749 F 166.512 G 1.169][G loss: -209.241]  0:05:00.781474
1364 (5, 1) [D loss: -62.135 R -130.134 F 55.676 G 1.232][G loss: -162.298]  0:05:01.584124
1365 (5, 1) [D loss: -73.640 R -240.543 F 134.903 G 3.200][G loss: -264.302]  0:05:02.391659
1366 (5, 1) [D loss: -60.569 R -207.984 F 118.140 G 2.927][G loss: -209.545]  0:05:03.199531
1367 (5, 1) [D loss: -72.971 R -228.328 F 112.885 G 4.247][G loss: -234.720]  0:05:04.003009
1368 (5, 1) [D loss: -103.302 R -213.094 F 68.264 G 4.153][G loss: -342.853]  0:05:04.814627
1369 (5, 1) [D loss: -72.250 R -161.429 F 45.487 G 4.369][G loss: -181.191]  0:05:05.620641
1370 (5, 1) [D loss: -88.195 R -126.728 F 1.079 G 3.745][G loss: -228.797]  0:05:06.445901
1371 (5, 1) [D loss: -112.894 R -200.717 F 19.122 G 6.870][G loss: -372.812]  0:05:07.257443
1372 (5, 1) [D loss: -99.673 R -148.042 F -14.896 G 6.326][G loss: -230.181]  0:05:08.055888
1373 (5, 1) [D loss: -94.959 R -114.665 F -23.232 G 4.294][G loss: -228.355]  0:05:08.872986
1374 (5, 1) [D loss: -77.536 R -146.914 F 26.462 G 4.292][G loss: -273.121]  0:05:09.680485
1375 (5, 1) [D loss: -83.547 R -179.070 F 54.973 G 4.055][G loss: -315.393]  0:05:10.500620
1376 (5, 1) [D loss: -77.723 R -92.162 F -14.973 G 2.941][G loss: -88.214]  0:05:11.307297
1377 (5, 1) [D loss: -89.781 R -96.699 F -46.624 G 5.354][G loss: 20.167]  0:05:12.120321
1378 (5, 1) [D loss: -113.500 R -127.383 F -25.188 G 3.907][G loss: 19.845]  0:05:12.930674
1379 (5, 1) [D loss: -152.406 R -173.558 F -47.296 G 6.845][G loss: 148.463]  0:05:13.751528
1380 (5, 1) [D loss: -133.313 R -97.046 F -83.872 G 4.760][G loss: 115.360]  0:05:14.557280
1381 (5, 1) [D loss: -158.549 R -55.676 F -162.972 G 6.010][G loss: 303.188]  0:05:15.364055
1382 (5, 1) [D loss: -147.993 R -60.438 F -137.884 G 5.033][G loss: 261.605]  0:05:16.168453
1383 (5, 1) [D loss: -139.060 R -77.936 F -137.240 G 7.612][G loss: 214.918]  0:05:16.978498
1384 (5, 1) [D loss: -162.767 R -39.794 F -179.406 G 5.643][G loss: 321.490]  0:05:17.790247
1385 (5, 1) [D loss: -155.937 R -62.015 F -212.872 G 11.895][G loss: 248.223]  0:05:18.601357
1386 (5, 1) [D loss: -171.409 R -96.533 F -210.709 G 13.583][G loss: 228.017]  0:05:19.409526
1387 (5, 1) [D loss: -174.619 R -103.255 F -161.655 G 9.029][G loss: 218.708]  0:05:20.210534
1388 (5, 1) [D loss: -160.121 R -102.603 F -179.746 G 12.223][G loss: 151.796]  0:05:21.023715
1389 (5, 1) [D loss: -186.251 R -136.336 F -143.218 G 9.330][G loss: 212.656]  0:05:21.843928
1390 (5, 1) [D loss: -163.292 R -136.770 F -121.689 G 9.517][G loss: 124.891]  0:05:22.669990
1391 (5, 1) [D loss: -158.462 R -170.002 F -76.042 G 8.758][G loss: 40.729]  0:05:23.494464
1392 (5, 1) [D loss: -145.386 R -189.710 F -33.908 G 7.823][G loss: -46.200]  0:05:24.318268
1393 (5, 1) [D loss: -157.031 R -202.512 F -24.025 G 6.951][G loss: -154.964]  0:05:25.139256
1394 (5, 1) [D loss: -108.206 R -238.152 F 72.991 G 5.695][G loss: -267.549]  0:05:25.940382
1395 (5, 1) [D loss: -114.419 R -290.456 F 143.227 G 3.281][G loss: -262.828]  0:05:26.748726
1396 (5, 1) [D loss: -111.316 R -327.981 F 167.745 G 4.892][G loss: -347.484]  0:05:27.563884
1397 (5, 1) [D loss: -71.116 R -293.279 F 157.700 G 6.446][G loss: -303.145]  0:05:28.364352
1398 (5, 1) [D loss: -53.705 R -303.930 F 185.447 G 6.478][G loss: -296.366]  0:05:29.174746
1399 (5, 1) [D loss: -111.275 R -327.030 F 169.845 G 4.591][G loss: -340.027]  0:05:29.978598
1400 (5, 1) [D loss: -67.970 R -321.995 F 218.827 G 3.520][G loss: -323.869]  0:05:30.785902
1401 (5, 1) [D loss: -49.536 R -381.149 F 310.575 G 2.104][G loss: -381.183]  0:05:31.604599
1402 (5, 1) [D loss: -30.794 R -349.956 F 290.585 G 2.858][G loss: -342.087]  0:05:32.408961
1403 (5, 1) [D loss: -58.310 R -378.189 F 295.978 G 2.390][G loss: -330.702]  0:05:33.214764
1404 (5, 1) [D loss: -44.872 R -391.139 F 324.086 G 2.218][G loss: -372.516]  0:05:34.018433
1405 (5, 1) [D loss: -41.099 R -448.240 F 394.085 G 1.306][G loss: -411.772]  0:05:34.829604
1406 (5, 1) [D loss: -44.138 R -498.152 F 426.679 G 2.734][G loss: -453.786]  0:05:35.641093
1407 (5, 1) [D loss: -38.838 R -488.483 F 433.156 G 1.649][G loss: -446.911]  0:05:36.446567
1408 (5, 1) [D loss: -50.707 R -534.994 F 470.036 G 1.425][G loss: -494.748]  0:05:37.250630
1409 (5, 1) [D loss: -62.762 R -503.482 F 421.150 G 1.957][G loss: -472.434]  0:05:38.058963
1410 (5, 1) [D loss: -35.135 R -448.411 F 398.562 G 1.471][G loss: -409.195]  0:05:38.869409
1411 (5, 1) [D loss: -44.679 R -478.577 F 408.028 G 2.587][G loss: -420.177]  0:05:39.684530
1412 (5, 1) [D loss: -42.807 R -448.926 F 376.574 G 2.954][G loss: -386.133]  0:05:40.491612
1413 (5, 1) [D loss: -40.165 R -416.836 F 357.310 G 1.936][G loss: -321.043]  0:05:41.302849
1414 (5, 1) [D loss: -52.736 R -397.199 F 323.871 G 2.059][G loss: -299.564]  0:05:42.110263
1415 (5, 1) [D loss: -42.156 R -355.737 F 297.795 G 1.579][G loss: -272.515]  0:05:42.940515
1416 (5, 1) [D loss: -43.227 R -340.214 F 283.632 G 1.336][G loss: -237.523]  0:05:43.757539
1417 (5, 1) [D loss: -38.157 R -294.105 F 239.455 G 1.649][G loss: -220.470]  0:05:44.567833
1418 (5, 1) [D loss: -40.797 R -310.076 F 243.656 G 2.562][G loss: -235.854]  0:05:45.381539
1419 (5, 1) [D loss: -47.593 R -303.332 F 237.960 G 1.778][G loss: -234.560]  0:05:46.202801
1420 (5, 1) [D loss: -55.390 R -288.323 F 215.063 G 1.787][G loss: -202.513]  0:05:47.019808
1421 (5, 1) [D loss: -50.335 R -276.215 F 207.316 G 1.856][G loss: -196.228]  0:05:47.848676
1422 (5, 1) [D loss: -56.119 R -238.164 F 164.630 G 1.742][G loss: -194.712]  0:05:48.657564
1423 (5, 1) [D loss: -49.492 R -260.403 F 192.082 G 1.883][G loss: -194.675]  0:05:49.467174
1424 (5, 1) [D loss: -37.233 R -257.328 F 202.023 G 1.807][G loss: -190.338]  0:05:50.280161
1425 (5, 1) [D loss: -37.802 R -232.614 F 180.769 G 1.404][G loss: -178.618]  0:05:51.091681
1426 (5, 1) [D loss: -47.485 R -167.174 F 104.751 G 1.494][G loss: -157.558]  0:05:51.910123
1427 (5, 1) [D loss: -38.911 R -202.086 F 137.124 G 2.605][G loss: -139.298]  0:05:52.721987
1428 (5, 1) [D loss: -54.985 R -168.417 F 96.012 G 1.742][G loss: -148.910]  0:05:53.528373
1429 (5, 1) [D loss: -58.513 R -141.934 F 67.828 G 1.559][G loss: -130.918]  0:05:54.350726
1430 (5, 1) [D loss: -46.414 R -125.034 F 65.628 G 1.299][G loss: -126.041]  0:05:55.189698
1431 (5, 1) [D loss: -47.072 R -104.877 F 42.162 G 1.564][G loss: -91.950]  0:05:56.010395
1432 (5, 1) [D loss: -36.133 R -91.607 F 34.821 G 2.065][G loss: -93.886]  0:05:56.836970
1433 (5, 1) [D loss: -43.376 R -61.202 F -1.644 G 1.947][G loss: -83.557]  0:05:57.659954
1434 (5, 1) [D loss: -58.598 R -62.954 F -12.141 G 1.650][G loss: -89.777]  0:05:58.486334
1435 (5, 1) [D loss: -50.779 R -35.074 F -38.645 G 2.294][G loss: -69.177]  0:05:59.302788
1436 (5, 1) [D loss: -40.436 R 19.702 F -79.591 G 1.945][G loss: 20.401]  0:06:00.120691
1437 (5, 1) [D loss: -47.134 R -52.777 F -18.580 G 2.422][G loss: -50.322]  0:06:00.935699
1438 (5, 1) [D loss: -57.095 R 54.187 F -128.408 G 1.713][G loss: -6.048]  0:06:01.740472
1439 (5, 1) [D loss: -61.315 R 43.292 F -126.352 G 2.175][G loss: 56.205]  0:06:02.550273
1440 (5, 1) [D loss: -66.480 R 67.070 F -153.689 G 2.014][G loss: 90.372]  0:06:03.366158
1441 (5, 1) [D loss: -79.706 R 57.550 F -183.153 G 4.590][G loss: 178.560]  0:06:04.182901
1442 (5, 1) [D loss: -64.271 R 87.352 F -203.819 G 5.220][G loss: 185.888]  0:06:04.991296
1443 (5, 1) [D loss: -89.778 R 66.124 F -192.540 G 3.664][G loss: 277.341]  0:06:05.795393
1444 (5, 1) [D loss: -87.531 R 99.131 F -248.553 G 6.189][G loss: 276.195]  0:06:06.601449
1445 (5, 1) [D loss: -68.932 R 86.827 F -207.954 G 5.220][G loss: 244.501]  0:06:07.409496
1446 (5, 1) [D loss: -90.204 R 65.366 F -194.909 G 3.934][G loss: 238.099]  0:06:08.227038
1447 (5, 1) [D loss: -89.746 R 88.482 F -235.997 G 5.777][G loss: 295.866]  0:06:09.030981
1448 (5, 1) [D loss: -136.178 R 63.257 F -269.963 G 7.053][G loss: 388.776]  0:06:09.849600
1449 (5, 1) [D loss: -89.638 R 105.537 F -241.913 G 4.674][G loss: 236.401]  0:06:10.658438
1450 (5, 1) [D loss: -122.553 R 51.916 F -232.711 G 5.824][G loss: 279.157]  0:06:11.469909
1451 (5, 1) [D loss: -81.082 R 54.317 F -173.698 G 3.830][G loss: 191.233]  0:06:12.280145
1452 (5, 1) [D loss: -89.096 R 10.511 F -145.730 G 4.612][G loss: 116.438]  0:06:13.082309
1453 (5, 1) [D loss: -74.773 R -56.128 F -66.300 G 4.765][G loss: 51.584]  0:06:13.898970
1454 (5, 1) [D loss: -54.243 R -121.503 F -16.293 G 8.355][G loss: -41.473]  0:06:14.707148
1455 (5, 1) [D loss: -103.181 R -93.431 F -57.097 G 4.735][G loss: -57.642]  0:06:15.515340
1456 (5, 1) [D loss: -87.491 R -137.967 F 7.537 G 4.294][G loss: -105.296]  0:06:16.325738
1457 (5, 1) [D loss: -41.405 R -147.913 F 71.795 G 3.471][G loss: -114.020]  0:06:17.127005
1458 (5, 1) [D loss: -67.774 R -192.622 F 99.550 G 2.530][G loss: -147.709]  0:06:17.923491
1459 (5, 1) [D loss: -58.278 R -184.757 F 83.033 G 4.345][G loss: -167.447]  0:06:18.731933
1460 (5, 1) [D loss: -73.529 R -163.728 F 59.893 G 3.031][G loss: -130.256]  0:06:19.547986
1461 (5, 1) [D loss: -66.285 R -163.145 F 79.294 G 1.757][G loss: -138.051]  0:06:20.369778
1462 (5, 1) [D loss: -40.208 R -146.366 F 89.126 G 1.703][G loss: -136.057]  0:06:21.171838
1463 (5, 1) [D loss: -40.575 R -152.558 F 100.162 G 1.182][G loss: -147.632]  0:06:21.974497
1464 (5, 1) [D loss: -29.978 R -177.294 F 124.644 G 2.267][G loss: -161.157]  0:06:22.780287
1465 (5, 1) [D loss: -57.923 R -218.110 F 144.370 G 1.582][G loss: -180.958]  0:06:23.583957
1466 (5, 1) [D loss: -40.151 R -226.576 F 171.234 G 1.519][G loss: -196.403]  0:06:24.408800
1467 (5, 1) [D loss: -49.443 R -228.001 F 163.303 G 1.526][G loss: -190.458]  0:06:25.222823
1468 (5, 1) [D loss: -36.751 R -219.730 F 171.640 G 1.134][G loss: -178.793]  0:06:26.036179
1469 (5, 1) [D loss: -23.854 R -220.442 F 166.466 G 3.012][G loss: -173.896]  0:06:26.848809
1470 (5, 1) [D loss: -39.246 R -247.861 F 198.669 G 0.995][G loss: -173.085]  0:06:27.653351
1471 (5, 1) [D loss: -41.108 R -172.018 F 106.178 G 2.473][G loss: -162.349]  0:06:28.486090
1472 (5, 1) [D loss: -35.792 R -180.116 F 134.200 G 1.012][G loss: -145.706]  0:06:29.310438
1473 (5, 1) [D loss: -33.261 R -219.412 F 173.279 G 1.287][G loss: -149.536]  0:06:30.121277
1474 (5, 1) [D loss: -41.431 R -192.265 F 132.439 G 1.839][G loss: -138.089]  0:06:30.931233
1475 (5, 1) [D loss: -27.455 R -191.866 F 153.291 G 1.112][G loss: -157.611]  0:06:31.737503
1476 (5, 1) [D loss: -33.374 R -216.275 F 171.412 G 1.149][G loss: -154.116]  0:06:32.554183
1477 (5, 1) [D loss: -35.669 R -197.237 F 149.479 G 1.209][G loss: -137.297]  0:06:33.365200
1478 (5, 1) [D loss: -34.303 R -175.820 F 130.654 G 1.086][G loss: -127.768]  0:06:34.168338
1479 (5, 1) [D loss: -40.164 R -180.364 F 128.934 G 1.127][G loss: -124.339]  0:06:34.979624
1480 (5, 1) [D loss: -35.697 R -132.873 F 82.954 G 1.422][G loss: -97.782]  0:06:35.788887
1481 (5, 1) [D loss: -37.564 R -133.390 F 87.878 G 0.795][G loss: -87.242]  0:06:36.605406
1482 (5, 1) [D loss: -36.647 R -148.283 F 99.816 G 1.182][G loss: -93.474]  0:06:37.416360
1483 (5, 1) [D loss: -30.444 R -110.690 F 71.506 G 0.874][G loss: -68.764]  0:06:38.219537
1484 (5, 1) [D loss: -34.351 R -103.036 F 57.962 G 1.072][G loss: -56.229]  0:06:39.030659
1485 (5, 1) [D loss: -26.139 R -95.308 F 59.531 G 0.964][G loss: -54.493]  0:06:39.838396
1486 (5, 1) [D loss: -28.508 R -101.113 F 63.033 G 0.957][G loss: -52.218]  0:06:40.643570
1487 (5, 1) [D loss: -37.418 R -107.579 F 59.891 G 1.027][G loss: -58.444]  0:06:41.452566
1488 (5, 1) [D loss: -34.783 R -102.341 F 57.232 G 1.032][G loss: -53.089]  0:06:42.259282
1489 (5, 1) [D loss: -29.218 R -78.669 F 37.350 G 1.210][G loss: -39.823]  0:06:43.079785
1490 (5, 1) [D loss: -31.355 R -89.453 F 49.975 G 0.812][G loss: -48.474]  0:06:43.884280
1491 (5, 1) [D loss: -33.894 R -120.130 F 75.310 G 1.093][G loss: -80.536]  0:06:44.705587
1492 (5, 1) [D loss: -30.486 R -74.407 F 33.969 G 0.995][G loss: -39.268]  0:06:45.512301
1493 (5, 1) [D loss: -28.174 R -96.069 F 59.854 G 0.804][G loss: -53.599]  0:06:46.311353
1494 (5, 1) [D loss: -33.535 R -78.728 F 35.636 G 0.956][G loss: -38.811]  0:06:47.126433
1495 (5, 1) [D loss: -27.581 R -63.583 F 27.503 G 0.850][G loss: -34.443]  0:06:47.928245
1496 (5, 1) [D loss: -32.761 R -85.461 F 43.081 G 0.962][G loss: -41.263]  0:06:48.749014
1497 (5, 1) [D loss: -33.294 R -102.517 F 60.352 G 0.887][G loss: -63.394]  0:06:49.566176
1498 (5, 1) [D loss: -27.223 R -85.685 F 47.435 G 1.103][G loss: -49.298]  0:06:50.376334
1499 (5, 1) [D loss: -29.118 R -76.996 F 40.235 G 0.764][G loss: -37.063]  0:06:51.195301
1500 (5, 1) [D loss: -27.979 R -76.794 F 42.351 G 0.646][G loss: -39.397]  0:06:52.003718
1501 (5, 1) [D loss: -31.880 R -72.905 F 33.160 G 0.786][G loss: -43.308]  0:06:52.816580
1502 (5, 1) [D loss: -27.914 R -106.186 F 71.297 G 0.698][G loss: -68.237]  0:06:53.639698
1503 (5, 1) [D loss: -27.241 R -121.277 F 86.171 G 0.786][G loss: -75.797]  0:06:54.464889
1504 (5, 1) [D loss: -26.451 R -105.560 F 71.673 G 0.744][G loss: -66.396]  0:06:55.285857
1505 (5, 1) [D loss: -33.266 R -108.081 F 64.918 G 0.990][G loss: -64.344]  0:06:56.095041
1506 (5, 1) [D loss: -34.011 R -107.361 F 62.005 G 1.135][G loss: -62.652]  0:06:56.907295
1507 (5, 1) [D loss: -28.181 R -120.491 F 84.532 G 0.778][G loss: -87.451]  0:06:57.718098
1508 (5, 1) [D loss: -29.837 R -132.163 F 93.541 G 0.879][G loss: -92.918]  0:06:58.579201
1509 (5, 1) [D loss: -31.980 R -131.831 F 91.547 G 0.830][G loss: -81.505]  0:06:59.416769
1510 (5, 1) [D loss: -26.169 R -114.634 F 78.067 G 1.040][G loss: -82.351]  0:07:00.227010
1511 (5, 1) [D loss: -40.166 R -102.357 F 52.915 G 0.928][G loss: -56.219]  0:07:01.049718
1512 (5, 1) [D loss: -30.638 R -103.713 F 66.039 G 0.704][G loss: -66.396]  0:07:01.871003
1513 (5, 1) [D loss: -27.539 R -116.745 F 81.274 G 0.793][G loss: -77.325]  0:07:02.690941
1514 (5, 1) [D loss: -29.908 R -105.665 F 68.328 G 0.743][G loss: -69.403]  0:07:03.520545
1515 (5, 1) [D loss: -28.995 R -96.127 F 59.877 G 0.726][G loss: -59.090]  0:07:04.332416
1516 (5, 1) [D loss: -34.035 R -100.706 F 56.594 G 1.008][G loss: -61.448]  0:07:05.141050
1517 (5, 1) [D loss: -30.133 R -86.648 F 48.247 G 0.827][G loss: -43.275]  0:07:05.960391
1518 (5, 1) [D loss: -29.074 R -96.472 F 60.637 G 0.676][G loss: -59.286]  0:07:06.769302
1519 (5, 1) [D loss: -28.203 R -78.025 F 42.705 G 0.712][G loss: -45.716]  0:07:07.586418
1520 (5, 1) [D loss: -33.160 R -96.122 F 54.834 G 0.813][G loss: -66.364]  0:07:08.406916
1521 (5, 1) [D loss: -23.952 R -81.366 F 48.685 G 0.873][G loss: -48.400]  0:07:09.231308
1522 (5, 1) [D loss: -29.142 R -85.427 F 44.398 G 1.189][G loss: -44.434]  0:07:10.055713
1523 (5, 1) [D loss: -27.802 R -80.914 F 45.676 G 0.744][G loss: -39.153]  0:07:10.879759
1524 (5, 1) [D loss: -33.078 R -76.272 F 34.980 G 0.821][G loss: -37.190]  0:07:11.689760
1525 (5, 1) [D loss: -30.145 R -82.763 F 42.631 G 0.999][G loss: -47.130]  0:07:12.507621
1526 (5, 1) [D loss: -33.420 R -96.471 F 54.485 G 0.857][G loss: -62.545]  0:07:13.332621
1527 (5, 1) [D loss: -30.269 R -74.246 F 36.994 G 0.698][G loss: -41.161]  0:07:14.147294
1528 (5, 1) [D loss: -30.939 R -80.621 F 40.249 G 0.943][G loss: -49.436]  0:07:14.958596
1529 (5, 1) [D loss: -26.283 R -66.917 F 31.704 G 0.893][G loss: -27.377]  0:07:15.770004
1530 (5, 1) [D loss: -26.760 R -51.945 F 16.812 G 0.837][G loss: -18.213]  0:07:16.579611
1531 (5, 1) [D loss: -28.152 R -63.520 F 25.984 G 0.938][G loss: -23.187]  0:07:17.382964
1532 (5, 1) [D loss: -27.540 R -65.211 F 29.927 G 0.774][G loss: -29.579]  0:07:18.197758
1533 (5, 1) [D loss: -29.688 R -59.443 F 20.993 G 0.876][G loss: -24.533]  0:07:19.010583
1534 (5, 1) [D loss: -27.135 R -56.055 F 20.862 G 0.806][G loss: -19.400]  0:07:19.820341
1535 (5, 1) [D loss: -27.414 R -52.710 F 16.955 G 0.834][G loss: -18.099]  0:07:20.632594
1536 (5, 1) [D loss: -26.552 R -36.372 F -1.706 G 1.153][G loss: 17.399]  0:07:21.442914
1537 (5, 1) [D loss: -21.835 R -27.699 F -0.860 G 0.672][G loss: 11.088]  0:07:22.252704
1538 (5, 1) [D loss: -17.717 R -34.120 F 7.610 G 0.879][G loss: -18.797]  0:07:23.066160
1539 (5, 1) [D loss: -26.242 R -42.926 F 8.847 G 0.784][G loss: -17.843]  0:07:23.884122
1540 (5, 1) [D loss: -25.296 R -61.360 F 28.770 G 0.729][G loss: -28.021]  0:07:24.706976
1541 (5, 1) [D loss: -26.813 R -49.429 F 13.153 G 0.946][G loss: -23.767]  0:07:25.519401
1542 (5, 1) [D loss: -26.919 R -54.257 F 21.239 G 0.610][G loss: -26.335]  0:07:26.331746
1543 (5, 1) [D loss: -23.818 R -50.189 F 19.241 G 0.713][G loss: -31.823]  0:07:27.151199
1544 (5, 1) [D loss: -23.916 R -54.705 F 20.986 G 0.980][G loss: -22.395]  0:07:27.976912
1545 (5, 1) [D loss: -24.766 R -59.868 F 29.235 G 0.587][G loss: -44.420]  0:07:28.792555
1546 (5, 1) [D loss: -23.022 R -70.405 F 40.830 G 0.655][G loss: -36.427]  0:07:29.611725
1547 (5, 1) [D loss: -26.543 R -55.933 F 21.099 G 0.829][G loss: -24.048]  0:07:30.417254
1548 (5, 1) [D loss: -26.942 R -57.339 F 22.556 G 0.784][G loss: -18.653]  0:07:31.222022
1549 (5, 1) [D loss: -25.698 R -63.054 F 30.778 G 0.658][G loss: -42.100]  0:07:32.029664
1550 (5, 1) [D loss: -28.400 R -84.646 F 47.532 G 0.871][G loss: -40.893]  0:07:32.843658
1551 (5, 1) [D loss: -27.373 R -86.107 F 53.415 G 0.532][G loss: -53.668]  0:07:33.646276
1552 (5, 1) [D loss: -24.417 R -87.786 F 55.133 G 0.824][G loss: -59.886]  0:07:34.480173
1553 (5, 1) [D loss: -29.354 R -94.571 F 55.546 G 0.967][G loss: -53.425]  0:07:35.286133
1554 (5, 1) [D loss: -24.612 R -85.063 F 53.490 G 0.696][G loss: -48.069]  0:07:36.093301
1555 (5, 1) [D loss: -29.789 R -102.485 F 65.496 G 0.720][G loss: -63.090]  0:07:36.915804
1556 (5, 1) [D loss: -27.954 R -89.758 F 54.964 G 0.684][G loss: -55.866]  0:07:37.721246
1557 (5, 1) [D loss: -23.660 R -106.875 F 74.352 G 0.886][G loss: -76.770]  0:07:38.534466
1558 (5, 1) [D loss: -34.053 R -96.707 F 45.056 G 1.760][G loss: -43.493]  0:07:39.342748
1559 (5, 1) [D loss: -22.106 R -92.357 F 66.304 G 0.395][G loss: -60.204]  0:07:40.147631
1560 (5, 1) [D loss: -25.284 R -84.696 F 45.338 G 1.407][G loss: -43.813]  0:07:40.963668
1561 (5, 1) [D loss: -23.186 R -74.415 F 44.220 G 0.701][G loss: -46.587]  0:07:41.766822
1562 (5, 1) [D loss: -22.533 R -92.375 F 62.286 G 0.756][G loss: -63.097]  0:07:42.596497
1563 (5, 1) [D loss: -27.068 R -96.881 F 62.103 G 0.771][G loss: -66.007]  0:07:43.405696
1564 (5, 1) [D loss: -30.670 R -121.906 F 79.855 G 1.138][G loss: -80.427]  0:07:44.205322
1565 (5, 1) [D loss: -25.140 R -111.879 F 78.978 G 0.776][G loss: -78.112]  0:07:45.009452
1566 (5, 1) [D loss: -24.347 R -108.751 F 77.788 G 0.662][G loss: -79.228]  0:07:45.808408
1567 (5, 1) [D loss: -21.856 R -101.596 F 73.076 G 0.666][G loss: -74.894]  0:07:46.607175
1568 (5, 1) [D loss: -26.489 R -95.600 F 55.941 G 1.317][G loss: -66.949]  0:07:47.419563
1569 (5, 1) [D loss: -28.452 R -104.910 F 69.107 G 0.735][G loss: -73.058]  0:07:48.233660
1570 (5, 1) [D loss: -25.523 R -115.518 F 84.475 G 0.552][G loss: -85.424]  0:07:49.044109
1571 (5, 1) [D loss: -24.668 R -108.834 F 71.736 G 1.243][G loss: -84.080]  0:07:49.860635
1572 (5, 1) [D loss: -29.256 R -109.281 F 72.661 G 0.736][G loss: -80.021]  0:07:50.687576
1573 (5, 1) [D loss: -24.399 R -100.761 F 69.210 G 0.715][G loss: -70.066]  0:07:51.503294
1574 (5, 1) [D loss: -31.851 R -101.847 F 61.401 G 0.859][G loss: -66.441]  0:07:52.332701
1575 (5, 1) [D loss: -21.664 R -103.628 F 73.055 G 0.891][G loss: -74.534]  0:07:53.155015
1576 (5, 1) [D loss: -25.220 R -109.459 F 78.216 G 0.602][G loss: -78.456]  0:07:53.977382
1577 (5, 1) [D loss: -20.625 R -101.832 F 75.567 G 0.564][G loss: -77.664]  0:07:54.793197
1578 (5, 1) [D loss: -16.107 R -97.035 F 73.416 G 0.751][G loss: -67.229]  0:07:55.609776
1579 (5, 1) [D loss: -22.692 R -85.812 F 57.821 G 0.530][G loss: -61.949]  0:07:56.427281
1580 (5, 1) [D loss: -23.352 R -98.820 F 68.865 G 0.660][G loss: -71.186]  0:07:57.238358
1581 (5, 1) [D loss: -21.517 R -82.284 F 54.438 G 0.633][G loss: -52.325]  0:07:58.054280
1582 (5, 1) [D loss: -15.121 R -76.185 F 54.395 G 0.667][G loss: -42.956]  0:07:58.871888
1583 (5, 1) [D loss: -24.053 R -69.961 F 40.687 G 0.522][G loss: -52.342]  0:07:59.684739
1584 (5, 1) [D loss: -26.328 R -79.005 F 46.917 G 0.576][G loss: -43.750]  0:08:00.510623
1585 (5, 1) [D loss: -22.295 R -67.095 F 37.208 G 0.759][G loss: -36.139]  0:08:01.318989
1586 (5, 1) [D loss: -21.962 R -52.785 F 26.602 G 0.422][G loss: -24.088]  0:08:02.141438
1587 (5, 1) [D loss: -17.569 R -46.202 F 22.224 G 0.641][G loss: -23.654]  0:08:02.961911
1588 (5, 1) [D loss: -22.778 R -49.646 F 20.904 G 0.596][G loss: -27.058]  0:08:03.773884
1589 (5, 1) [D loss: -25.856 R -58.809 F 27.853 G 0.510][G loss: -29.192]  0:08:04.593472
1590 (5, 1) [D loss: -19.425 R -45.354 F 21.090 G 0.484][G loss: -17.656]  0:08:05.410590
1591 (5, 1) [D loss: -21.126 R -50.872 F 24.695 G 0.505][G loss: -25.330]  0:08:06.227216
1592 (5, 1) [D loss: -20.303 R -64.902 F 37.624 G 0.697][G loss: -36.682]  0:08:07.034592
1593 (5, 1) [D loss: -18.092 R -62.364 F 39.352 G 0.492][G loss: -43.822]  0:08:07.869266
1594 (5, 1) [D loss: -26.177 R -77.481 F 44.490 G 0.681][G loss: -37.700]  0:08:08.681832
1595 (5, 1) [D loss: -25.059 R -71.718 F 39.335 G 0.732][G loss: -40.246]  0:08:09.496224
1596 (5, 1) [D loss: -26.285 R -64.136 F 33.073 G 0.478][G loss: -33.873]  0:08:10.309415
1597 (5, 1) [D loss: -21.967 R -53.827 F 25.681 G 0.618][G loss: -28.780]  0:08:11.115520
1598 (5, 1) [D loss: -21.524 R -69.722 F 42.797 G 0.540][G loss: -45.115]  0:08:11.926366
1599 (5, 1) [D loss: -29.677 R -63.355 F 27.596 G 0.608][G loss: -35.558]  0:08:12.729641
1600 (5, 1) [D loss: -23.098 R -77.144 F 46.930 G 0.712][G loss: -47.597]  0:08:13.546423
1601 (5, 1) [D loss: -16.303 R -84.559 F 61.878 G 0.638][G loss: -53.781]  0:08:14.353961
1602 (5, 1) [D loss: -25.344 R -74.706 F 43.899 G 0.546][G loss: -43.962]  0:08:15.158912
1603 (5, 1) [D loss: -22.507 R -53.412 F 23.321 G 0.758][G loss: -32.384]  0:08:15.964836
1604 (5, 1) [D loss: -18.698 R -54.623 F 28.903 G 0.702][G loss: -38.821]  0:08:16.768793
1605 (5, 1) [D loss: -23.756 R -60.832 F 29.020 G 0.806][G loss: -42.200]  0:08:17.576983
1606 (5, 1) [D loss: -22.680 R -69.074 F 41.885 G 0.451][G loss: -45.975]  0:08:18.395708
1607 (5, 1) [D loss: -28.859 R -81.314 F 46.862 G 0.559][G loss: -51.133]  0:08:19.202489
1608 (5, 1) [D loss: -21.420 R -74.167 F 43.987 G 0.876][G loss: -48.366]  0:08:20.015805
1609 (5, 1) [D loss: -20.827 R -71.869 F 45.281 G 0.576][G loss: -49.713]  0:08:20.826865
1610 (5, 1) [D loss: -14.762 R -76.803 F 56.520 G 0.552][G loss: -48.135]  0:08:21.636758
1611 (5, 1) [D loss: -21.240 R -75.919 F 48.304 G 0.637][G loss: -60.080]  0:08:22.447334
1612 (5, 1) [D loss: -22.108 R -84.298 F 56.000 G 0.619][G loss: -64.214]  0:08:23.251145
1613 (5, 1) [D loss: -19.604 R -95.620 F 71.764 G 0.425][G loss: -67.157]  0:08:24.072642
1614 (5, 1) [D loss: -21.346 R -86.058 F 56.729 G 0.798][G loss: -59.559]  0:08:24.895979
1615 (5, 1) [D loss: -22.249 R -95.215 F 65.638 G 0.733][G loss: -64.129]  0:08:25.708539
1616 (5, 1) [D loss: -27.971 R -100.242 F 65.905 G 0.637][G loss: -67.782]  0:08:26.524141
1617 (5, 1) [D loss: -13.953 R -99.307 F 79.490 G 0.586][G loss: -71.755]  0:08:27.332003
1618 (5, 1) [D loss: -22.510 R -94.400 F 64.534 G 0.736][G loss: -70.721]  0:08:28.145513
1619 (5, 1) [D loss: -24.159 R -97.136 F 62.862 G 1.012][G loss: -69.926]  0:08:28.963894
1620 (5, 1) [D loss: -32.711 R -97.253 F 55.826 G 0.872][G loss: -68.683]  0:08:29.776345
1621 (5, 1) [D loss: -21.656 R -96.551 F 70.148 G 0.475][G loss: -66.914]  0:08:30.602097
1622 (5, 1) [D loss: -23.089 R -98.892 F 65.104 G 1.070][G loss: -72.354]  0:08:31.411497
1623 (5, 1) [D loss: -28.680 R -103.312 F 66.006 G 0.863][G loss: -78.115]  0:08:32.231427
1624 (5, 1) [D loss: -28.084 R -94.055 F 57.637 G 0.833][G loss: -68.504]  0:08:33.039353
1625 (5, 1) [D loss: -27.768 R -104.517 F 68.935 G 0.781][G loss: -77.178]  0:08:33.864895
1626 (5, 1) [D loss: -25.835 R -104.864 F 71.856 G 0.717][G loss: -74.900]  0:08:34.680667
1627 (5, 1) [D loss: -26.775 R -108.930 F 76.896 G 0.526][G loss: -75.112]  0:08:35.484692
1628 (5, 1) [D loss: -21.343 R -105.061 F 77.959 G 0.576][G loss: -83.749]  0:08:36.293230
1629 (5, 1) [D loss: -22.362 R -99.406 F 70.943 G 0.610][G loss: -76.356]  0:08:37.114423
1630 (5, 1) [D loss: -20.000 R -104.354 F 79.131 G 0.522][G loss: -79.305]  0:08:37.922232
1631 (5, 1) [D loss: -19.092 R -99.455 F 74.220 G 0.614][G loss: -74.601]  0:08:38.741737
1632 (5, 1) [D loss: -22.078 R -100.518 F 73.241 G 0.520][G loss: -74.587]  0:08:39.548636
1633 (5, 1) [D loss: -28.919 R -97.463 F 59.944 G 0.860][G loss: -76.248]  0:08:40.375297
1634 (5, 1) [D loss: -19.811 R -95.157 F 70.836 G 0.451][G loss: -74.321]  0:08:41.190536
1635 (5, 1) [D loss: -21.740 R -95.357 F 67.523 G 0.609][G loss: -69.934]  0:08:42.005599
1636 (5, 1) [D loss: -26.876 R -86.595 F 54.877 G 0.484][G loss: -59.493]  0:08:42.813879
1637 (5, 1) [D loss: -23.861 R -75.849 F 44.755 G 0.723][G loss: -51.150]  0:08:43.625799
1638 (5, 1) [D loss: -22.003 R -71.296 F 44.120 G 0.517][G loss: -43.450]  0:08:44.438158
1639 (5, 1) [D loss: -20.045 R -59.182 F 32.942 G 0.619][G loss: -31.221]  0:08:45.256354
1640 (5, 1) [D loss: -19.475 R -54.336 F 29.045 G 0.582][G loss: -29.090]  0:08:46.060396
1641 (5, 1) [D loss: -22.139 R -51.097 F 22.392 G 0.657][G loss: -28.056]  0:08:46.863509
1642 (5, 1) [D loss: -24.384 R -45.108 F 14.224 G 0.650][G loss: -23.588]  0:08:47.677651
1643 (5, 1) [D loss: -27.638 R -44.866 F 11.367 G 0.586][G loss: -23.436]  0:08:48.490029
1644 (5, 1) [D loss: -26.817 R -35.640 F 0.637 G 0.819][G loss: -11.991]  0:08:49.310695
1645 (5, 1) [D loss: -23.980 R -41.957 F 13.939 G 0.404][G loss: -14.783]  0:08:50.120737
1646 (5, 1) [D loss: -21.601 R -46.336 F 19.941 G 0.479][G loss: -14.415]  0:08:50.925708
1647 (5, 1) [D loss: -22.759 R -41.420 F 11.975 G 0.669][G loss: -15.363]  0:08:51.735737
1648 (5, 1) [D loss: -20.198 R -36.852 F 11.339 G 0.531][G loss: -13.473]  0:08:52.532501
1649 (5, 1) [D loss: -18.728 R -42.274 F 18.752 G 0.479][G loss: -13.610]  0:08:53.345329
1650 (5, 1) [D loss: -21.319 R -31.764 F 4.744 G 0.570][G loss: 1.627]  0:08:54.159332
1651 (5, 1) [D loss: -21.727 R -26.225 F -2.833 G 0.733][G loss: 2.032]  0:08:54.985026
1652 (5, 1) [D loss: -25.600 R -28.334 F -3.100 G 0.583][G loss: 2.082]  0:08:55.793342
1653 (5, 1) [D loss: -20.703 R -29.301 F 4.265 G 0.433][G loss: -0.230]  0:08:56.593586
1654 (5, 1) [D loss: -21.596 R -27.140 F -0.060 G 0.560][G loss: -3.939]  0:08:57.410765
1655 (5, 1) [D loss: -22.801 R -34.604 F 6.632 G 0.517][G loss: -3.401]  0:08:58.224057
1656 (5, 1) [D loss: -23.810 R -32.215 F 2.666 G 0.574][G loss: 10.311]  0:08:59.029116
1657 (5, 1) [D loss: -23.989 R -26.693 F -2.875 G 0.558][G loss: 11.226]  0:08:59.838652
1658 (5, 1) [D loss: -23.368 R -19.123 F -11.275 G 0.703][G loss: 7.922]  0:09:00.647041
1659 (5, 1) [D loss: -22.662 R -29.341 F -0.304 G 0.698][G loss: -5.618]  0:09:01.460084
1660 (5, 1) [D loss: -27.450 R -28.357 F -4.746 G 0.565][G loss: -3.005]  0:09:02.269505
1661 (5, 1) [D loss: -20.055 R -24.689 F -1.744 G 0.638][G loss: -12.321]  0:09:03.097763
1662 (5, 1) [D loss: -23.239 R -28.351 F -2.296 G 0.741][G loss: -6.010]  0:09:03.916497
1663 (5, 1) [D loss: -25.001 R -29.324 F -3.711 G 0.803][G loss: -8.417]  0:09:04.734643
1664 (5, 1) [D loss: -22.667 R -33.701 F 3.739 G 0.729][G loss: -26.653]  0:09:05.547514
1665 (5, 1) [D loss: -17.836 R -27.010 F -0.835 G 1.001][G loss: -28.811]  0:09:06.370065
1666 (5, 1) [D loss: -25.799 R -57.608 F 27.253 G 0.456][G loss: -27.560]  0:09:07.173025
1667 (5, 1) [D loss: -22.365 R -51.921 F 24.446 G 0.511][G loss: -30.956]  0:09:07.976913
1668 (5, 1) [D loss: -30.982 R -60.896 F 23.481 G 0.643][G loss: -34.177]  0:09:08.779382
1669 (5, 1) [D loss: -16.394 R -50.549 F 24.354 G 0.980][G loss: -27.618]  0:09:09.588305
1670 (5, 1) [D loss: -14.165 R -55.959 F 34.780 G 0.701][G loss: -36.282]  0:09:10.421053
1671 (5, 1) [D loss: -29.886 R -75.743 F 40.125 G 0.573][G loss: -43.781]  0:09:11.225003
1672 (5, 1) [D loss: -20.331 R -63.492 F 38.636 G 0.452][G loss: -40.656]  0:09:12.031991
1673 (5, 1) [D loss: -20.176 R -71.948 F 45.720 G 0.605][G loss: -48.643]  0:09:12.850989
1674 (5, 1) [D loss: -20.176 R -82.783 F 58.329 G 0.428][G loss: -58.123]  0:09:13.691964
1675 (5, 1) [D loss: -20.862 R -81.856 F 55.644 G 0.535][G loss: -61.763]  0:09:14.516895
1676 (5, 1) [D loss: -16.116 R -77.776 F 55.841 G 0.582][G loss: -58.455]  0:09:15.338329
1677 (5, 1) [D loss: -20.655 R -74.537 F 45.721 G 0.816][G loss: -47.914]  0:09:16.152339
1678 (5, 1) [D loss: -20.076 R -77.097 F 52.981 G 0.404][G loss: -53.226]  0:09:16.969329
1679 (5, 1) [D loss: -21.640 R -84.705 F 55.477 G 0.759][G loss: -55.742]  0:09:17.787922
1680 (5, 1) [D loss: -19.995 R -91.038 F 66.431 G 0.461][G loss: -64.271]  0:09:18.604692
1681 (5, 1) [D loss: -26.642 R -87.018 F 53.858 G 0.652][G loss: -58.091]  0:09:19.423123
1682 (5, 1) [D loss: -14.149 R -95.880 F 74.324 G 0.741][G loss: -64.890]  0:09:20.239470
1683 (5, 1) [D loss: -21.783 R -92.094 F 66.319 G 0.399][G loss: -65.953]  0:09:21.046692
1684 (5, 1) [D loss: -23.247 R -94.346 F 62.069 G 0.903][G loss: -67.512]  0:09:21.854908
1685 (5, 1) [D loss: -20.410 R -83.898 F 56.570 G 0.692][G loss: -61.936]  0:09:22.661484
1686 (5, 1) [D loss: -18.581 R -95.502 F 64.557 G 1.236][G loss: -73.717]  0:09:23.470262
1687 (5, 1) [D loss: -20.492 R -89.115 F 63.413 G 0.521][G loss: -63.947]  0:09:24.290766
1688 (5, 1) [D loss: -31.946 R -80.478 F 38.894 G 0.964][G loss: -70.194]  0:09:25.100446
1689 (5, 1) [D loss: -19.229 R -89.880 F 61.122 G 0.953][G loss: -72.098]  0:09:25.904960
1690 (5, 1) [D loss: -24.127 R -85.444 F 55.427 G 0.589][G loss: -59.588]  0:09:26.718834
1691 (5, 1) [D loss: -26.713 R -86.031 F 53.582 G 0.574][G loss: -59.958]  0:09:27.526580
1692 (5, 1) [D loss: -24.425 R -89.117 F 58.291 G 0.640][G loss: -57.731]  0:09:28.343594
1693 (5, 1) [D loss: -26.166 R -82.549 F 45.900 G 1.048][G loss: -65.673]  0:09:29.166232
1694 (5, 1) [D loss: -21.816 R -94.772 F 67.660 G 0.530][G loss: -66.949]  0:09:29.971262
1695 (5, 1) [D loss: -14.425 R -78.710 F 59.017 G 0.527][G loss: -55.390]  0:09:30.779383
1696 (5, 1) [D loss: -19.541 R -78.479 F 54.454 G 0.448][G loss: -53.186]  0:09:31.582483
1697 (5, 1) [D loss: -20.496 R -77.791 F 52.738 G 0.456][G loss: -53.590]  0:09:32.403142
1698 (5, 1) [D loss: -19.770 R -58.836 F 33.019 G 0.605][G loss: -32.033]  0:09:33.226686
1699 (5, 1) [D loss: -18.038 R -49.335 F 24.803 G 0.649][G loss: -24.358]  0:09:34.026821
1700 (5, 1) [D loss: -21.747 R -53.365 F 26.903 G 0.471][G loss: -27.448]  0:09:34.841362
1701 (5, 1) [D loss: -25.104 R -43.732 F 11.669 G 0.696][G loss: -20.910]  0:09:35.673579
1702 (5, 1) [D loss: -14.196 R -34.326 F 13.987 G 0.614][G loss: -15.853]  0:09:36.489517
1703 (5, 1) [D loss: -24.066 R -34.706 F 2.221 G 0.842][G loss: -9.241]  0:09:37.308232
1704 (5, 1) [D loss: -19.730 R -41.047 F 16.517 G 0.480][G loss: -23.242]  0:09:38.110665
1705 (5, 1) [D loss: -21.127 R -44.774 F 17.762 G 0.589][G loss: -20.230]  0:09:38.924686
1706 (5, 1) [D loss: -24.700 R -40.985 F 11.000 G 0.528][G loss: -10.889]  0:09:39.739727
1707 (5, 1) [D loss: -19.643 R -37.959 F 14.172 G 0.414][G loss: -12.875]  0:09:40.547127
1708 (5, 1) [D loss: -19.625 R -31.448 F 6.453 G 0.537][G loss: -9.407]  0:09:41.360118
1709 (5, 1) [D loss: -20.627 R -29.880 F 3.277 G 0.598][G loss: -10.903]  0:09:42.166880
1710 (5, 1) [D loss: -13.181 R -11.889 F -9.275 G 0.798][G loss: 4.590]  0:09:42.988250
1711 (5, 1) [D loss: -20.329 R -24.283 F -0.115 G 0.407][G loss: 3.597]  0:09:43.790550
1712 (5, 1) [D loss: -16.869 R -26.981 F 3.823 G 0.629][G loss: -0.101]  0:09:44.594380
1713 (5, 1) [D loss: -18.986 R -20.188 F -3.025 G 0.423][G loss: 2.699]  0:09:45.406276
1714 (5, 1) [D loss: -18.688 R -22.728 F -0.238 G 0.428][G loss: 3.736]  0:09:46.239132
1715 (5, 1) [D loss: -20.327 R -21.158 F -2.957 G 0.379][G loss: 2.623]  0:09:47.056524
1716 (5, 1) [D loss: -15.572 R -19.352 F -2.230 G 0.601][G loss: 5.769]  0:09:47.876422
1717 (5, 1) [D loss: -19.156 R -19.456 F -4.166 G 0.447][G loss: 5.475]  0:09:48.689428
1718 (5, 1) [D loss: -18.413 R -28.950 F 5.604 G 0.493][G loss: -4.019]  0:09:49.509649
1719 (5, 1) [D loss: -18.012 R -25.456 F 2.222 G 0.522][G loss: -4.988]  0:09:50.329460
1720 (5, 1) [D loss: -22.838 R -33.356 F 5.608 G 0.491][G loss: -7.290]  0:09:51.142339
1721 (5, 1) [D loss: -19.583 R -26.883 F 1.266 G 0.603][G loss: -3.072]  0:09:51.962445
1722 (5, 1) [D loss: -18.423 R -36.479 F 13.624 G 0.443][G loss: -13.307]  0:09:52.776177
1723 (5, 1) [D loss: -26.022 R -35.895 F 4.890 G 0.498][G loss: -13.629]  0:09:53.596949
1724 (5, 1) [D loss: -19.502 R -40.467 F 16.873 G 0.409][G loss: -20.536]  0:09:54.426926
1725 (5, 1) [D loss: -21.331 R -41.205 F 15.217 G 0.466][G loss: -16.301]  0:09:55.240380
1726 (5, 1) [D loss: -21.063 R -37.955 F 11.506 G 0.539][G loss: -13.481]  0:09:56.054444
1727 (5, 1) [D loss: -20.861 R -42.771 F 14.818 G 0.709][G loss: -20.835]  0:09:56.892312
1728 (5, 1) [D loss: -20.022 R -54.244 F 27.716 G 0.651][G loss: -33.371]  0:09:57.711991
1729 (5, 1) [D loss: -16.951 R -58.415 F 37.421 G 0.404][G loss: -40.984]  0:09:58.525212
1730 (5, 1) [D loss: -19.521 R -61.032 F 37.498 G 0.401][G loss: -39.116]  0:09:59.330590
1731 (5, 1) [D loss: -22.827 R -62.554 F 34.735 G 0.499][G loss: -33.239]  0:10:00.144004
1732 (5, 1) [D loss: -19.080 R -69.933 F 46.734 G 0.412][G loss: -49.564]  0:10:00.950351
1733 (5, 1) [D loss: -12.606 R -52.762 F 32.839 G 0.732][G loss: -45.444]  0:10:01.762766
1734 (5, 1) [D loss: -21.998 R -68.093 F 42.545 G 0.355][G loss: -43.892]  0:10:02.577805
1735 (5, 1) [D loss: -20.427 R -73.015 F 47.106 G 0.548][G loss: -42.182]  0:10:03.397394
1736 (5, 1) [D loss: -15.220 R -73.202 F 53.621 G 0.436][G loss: -52.384]  0:10:04.200035
1737 (5, 1) [D loss: -24.242 R -79.950 F 45.931 G 0.978][G loss: -44.629]  0:10:05.020420
1738 (5, 1) [D loss: -22.756 R -75.438 F 47.118 G 0.556][G loss: -46.811]  0:10:05.842007
1739 (5, 1) [D loss: -24.687 R -78.792 F 47.198 G 0.691][G loss: -51.381]  0:10:06.657541
1740 (5, 1) [D loss: -26.285 R -77.332 F 45.642 G 0.541][G loss: -58.270]  0:10:07.469774
1741 (5, 1) [D loss: -20.651 R -91.200 F 63.348 G 0.720][G loss: -65.106]  0:10:08.288936
1742 (5, 1) [D loss: -19.414 R -91.185 F 65.707 G 0.606][G loss: -65.467]  0:10:09.108581
1743 (5, 1) [D loss: -3.714 R -80.063 F 62.540 G 1.381][G loss: -64.403]  0:10:09.930939
1744 (5, 1) [D loss: -24.007 R -81.436 F 47.473 G 0.996][G loss: -60.792]  0:10:10.758176
1745 (5, 1) [D loss: -23.085 R -92.599 F 62.574 G 0.694][G loss: -74.085]  0:10:11.570304
1746 (5, 1) [D loss: -24.730 R -89.913 F 59.473 G 0.571][G loss: -67.615]  0:10:12.394100
1747 (5, 1) [D loss: -25.913 R -93.023 F 60.733 G 0.638][G loss: -65.253]  0:10:13.208817
1748 (5, 1) [D loss: -26.130 R -90.466 F 59.564 G 0.477][G loss: -67.905]  0:10:14.012226
1749 (5, 1) [D loss: -17.906 R -87.532 F 57.929 G 1.170][G loss: -80.486]  0:10:14.830339
1750 (5, 1) [D loss: -23.313 R -92.531 F 62.952 G 0.627][G loss: -73.680]  0:10:15.643553
1751 (5, 1) [D loss: -15.320 R -83.468 F 61.970 G 0.618][G loss: -80.028]  0:10:16.461776
1752 (5, 1) [D loss: -29.276 R -78.336 F 42.143 G 0.692][G loss: -52.455]  0:10:17.286830
1753 (5, 1) [D loss: -21.556 R -84.750 F 60.616 G 0.258][G loss: -60.285]  0:10:18.102392
1754 (5, 1) [D loss: -21.958 R -76.027 F 47.274 G 0.680][G loss: -37.013]  0:10:18.916690
1755 (5, 1) [D loss: -25.884 R -61.772 F 29.980 G 0.591][G loss: -30.996]  0:10:19.747007
1756 (5, 1) [D loss: -21.200 R -77.626 F 49.801 G 0.662][G loss: -57.947]  0:10:20.575760
1757 (5, 1) [D loss: -20.560 R -68.038 F 33.441 G 1.404][G loss: -61.005]  0:10:21.395206
1758 (5, 1) [D loss: -23.844 R -88.875 F 58.944 G 0.609][G loss: -69.955]  0:10:22.207903
1759 (5, 1) [D loss: -23.574 R -82.482 F 52.929 G 0.598][G loss: -59.396]  0:10:23.022028
1760 (5, 1) [D loss: -27.290 R -71.376 F 38.721 G 0.537][G loss: -30.609]  0:10:23.840192
1761 (5, 1) [D loss: -24.104 R -55.149 F 24.803 G 0.624][G loss: -15.424]  0:10:24.661505
1762 (5, 1) [D loss: -20.301 R -49.592 F 23.169 G 0.612][G loss: -23.293]  0:10:25.484411
1763 (5, 1) [D loss: -18.597 R -48.289 F 22.809 G 0.688][G loss: -12.889]  0:10:26.294382
1764 (5, 1) [D loss: -20.268 R -41.430 F 15.094 G 0.607][G loss: -7.078]  0:10:27.112414
1765 (5, 1) [D loss: -20.777 R -43.145 F 17.676 G 0.469][G loss: -14.383]  0:10:27.934800
1766 (5, 1) [D loss: -27.248 R -28.619 F -8.486 G 0.986][G loss: 0.231]  0:10:28.754904
1767 (5, 1) [D loss: -35.013 R -27.762 F -13.698 G 0.645][G loss: 1.455]  0:10:29.570980
1768 (5, 1) [D loss: -15.708 R -1.859 F -22.417 G 0.857][G loss: 1.059]  0:10:30.378837
1769 (5, 1) [D loss: -22.740 R -4.203 F -28.767 G 1.023][G loss: 1.729]  0:10:31.192587
1770 (5, 1) [D loss: -32.372 R 1.192 F -45.102 G 1.154][G loss: 8.077]  0:10:32.010228
1771 (5, 1) [D loss: -34.564 R 16.588 F -69.250 G 1.810][G loss: 8.684]  0:10:32.823004
1772 (5, 1) [D loss: -22.672 R 28.390 F -65.754 G 1.469][G loss: 14.317]  0:10:33.627191
1773 (5, 1) [D loss: -38.178 R 7.539 F -55.450 G 0.973][G loss: 2.085]  0:10:34.443566
1774 (5, 1) [D loss: -46.046 R 21.797 F -84.375 G 1.653][G loss: 6.250]  0:10:35.262674
1775 (5, 1) [D loss: -37.223 R 18.506 F -73.958 G 1.823][G loss: -6.368]  0:10:36.063725
1776 (5, 1) [D loss: -38.077 R 56.997 F -113.136 G 1.806][G loss: -0.682]  0:10:36.863338
1777 (5, 1) [D loss: -30.419 R 19.167 F -72.014 G 2.243][G loss: -41.017]  0:10:37.671052
1778 (5, 1) [D loss: -30.398 R 19.220 F -58.655 G 0.904][G loss: -8.170]  0:10:38.480230
1779 (5, 1) [D loss: -40.849 R -12.791 F -38.554 G 1.050][G loss: -53.245]  0:10:39.304486
1780 (5, 1) [D loss: -41.171 R -1.700 F -49.639 G 1.017][G loss: -47.411]  0:10:40.113237
1781 (5, 1) [D loss: -33.473 R 8.655 F -56.995 G 1.487][G loss: -35.485]  0:10:40.926689
1782 (5, 1) [D loss: -28.704 R 2.330 F -41.013 G 0.998][G loss: -8.390]  0:10:41.736827
1783 (5, 1) [D loss: -39.053 R -26.975 F -23.130 G 1.105][G loss: 45.594]  0:10:42.541117
1784 (5, 1) [D loss: -55.567 R -24.175 F -61.263 G 2.987][G loss: 133.466]  0:10:43.363960
1785 (5, 1) [D loss: -53.719 R 11.942 F -83.193 G 1.753][G loss: 144.011]  0:10:44.166208
1786 (5, 1) [D loss: -45.251 R 19.385 F -85.733 G 2.110][G loss: 139.413]  0:10:44.979252
1787 (5, 1) [D loss: -44.944 R -17.491 F -38.399 G 1.095][G loss: 109.457]  0:10:45.781138
1788 (5, 1) [D loss: -32.259 R -38.463 F 1.115 G 0.509][G loss: 25.939]  0:10:46.586798
1789 (5, 1) [D loss: -32.429 R -49.397 F -0.419 G 1.739][G loss: 46.270]  0:10:47.406794
1790 (5, 1) [D loss: -45.646 R -51.105 F -1.080 G 0.654][G loss: 39.227]  0:10:48.213050
1791 (5, 1) [D loss: -50.291 R -68.147 F 9.226 G 0.863][G loss: 58.230]  0:10:49.015272
1792 (5, 1) [D loss: -70.638 R -39.561 F -50.054 G 1.898][G loss: 131.722]  0:10:49.833509
1793 (5, 1) [D loss: -34.440 R -57.584 F 0.978 G 2.217][G loss: 31.782]  0:10:50.642352
1794 (5, 1) [D loss: -62.618 R -15.613 F -63.914 G 1.691][G loss: 58.472]  0:10:51.477026
1795 (5, 1) [D loss: -45.539 R 56.124 F -142.880 G 4.122][G loss: 70.184]  0:10:52.300664
1796 (5, 1) [D loss: -47.999 R -21.869 F -44.778 G 1.865][G loss: 40.414]  0:10:53.110076
1797 (5, 1) [D loss: -79.506 R -24.567 F -91.555 G 3.662][G loss: 80.660]  0:10:53.928720
1798 (5, 1) [D loss: -68.986 R -0.452 F -89.232 G 2.070][G loss: 85.204]  0:10:54.730963
1799 (5, 1) [D loss: -34.991 R 25.704 F -88.781 G 2.809][G loss: 44.371]  0:10:55.542507
1800 (5, 1) [D loss: -40.279 R 23.732 F -96.884 G 3.287][G loss: 47.260]  0:10:56.351935
1801 (5, 1) [D loss: -55.960 R 4.279 F -81.582 G 2.134][G loss: 44.390]  0:10:57.163921
1802 (5, 1) [D loss: -51.064 R 42.702 F -127.121 G 3.336][G loss: 50.923]  0:10:57.986235
1803 (5, 1) [D loss: -47.914 R 29.209 F -106.349 G 2.923][G loss: 47.621]  0:10:58.811234
1804 (5, 1) [D loss: -45.930 R 11.640 F -77.923 G 2.035][G loss: 37.821]  0:10:59.612818
1805 (5, 1) [D loss: -60.992 R 16.958 F -97.210 G 1.926][G loss: 43.329]  0:11:00.439949
1806 (5, 1) [D loss: -57.851 R 0.871 F -66.976 G 0.825][G loss: 22.061]  0:11:01.249034
1807 (5, 1) [D loss: -70.807 R 33.457 F -127.777 G 2.351][G loss: 34.878]  0:11:02.055356
1808 (5, 1) [D loss: -54.620 R 28.351 F -99.454 G 1.648][G loss: 20.062]  0:11:02.870217
1809 (5, 1) [D loss: -71.068 R -14.353 F -67.037 G 1.032][G loss: 3.103]  0:11:03.671261
1810 (5, 1) [D loss: -50.394 R 38.914 F -106.460 G 1.715][G loss: 17.210]  0:11:04.483552
1811 (5, 1) [D loss: -70.716 R -0.180 F -89.955 G 1.942][G loss: -6.761]  0:11:05.289354
1812 (5, 1) [D loss: -48.082 R 10.222 F -78.332 G 2.003][G loss: -13.888]  0:11:06.106430
1813 (5, 1) [D loss: -44.130 R -10.366 F -46.664 G 1.290][G loss: -23.962]  0:11:06.919029
1814 (5, 1) [D loss: -45.139 R -35.514 F -21.975 G 1.235][G loss: -37.636]  0:11:07.729853
1815 (5, 1) [D loss: -32.040 R -32.253 F -10.030 G 1.024][G loss: -13.401]  0:11:08.548696
1816 (5, 1) [D loss: -39.767 R -43.040 F -7.574 G 1.085][G loss: 20.072]  0:11:09.370558
1817 (5, 1) [D loss: -27.599 R -20.360 F -17.819 G 1.058][G loss: 41.573]  0:11:10.184390
1818 (5, 1) [D loss: -30.872 R -34.518 F -7.017 G 1.066][G loss: 13.452]  0:11:11.000174
1819 (5, 1) [D loss: -37.289 R -63.340 F 12.701 G 1.335][G loss: -27.378]  0:11:11.806926
1820 (5, 1) [D loss: -36.571 R -80.421 F 34.207 G 0.964][G loss: -61.774]  0:11:12.609655
1821 (5, 1) [D loss: -28.330 R -83.699 F 45.519 G 0.985][G loss: -35.478]  0:11:13.430788
1822 (5, 1) [D loss: -34.373 R -66.932 F 18.152 G 1.441][G loss: 8.616]  0:11:14.237460
1823 (5, 1) [D loss: -37.502 R -54.430 F 6.337 G 1.059][G loss: 4.384]  0:11:15.055280
1824 (5, 1) [D loss: -45.792 R -56.078 F -14.512 G 2.480][G loss: 11.533]  0:11:15.868055
1825 (5, 1) [D loss: -48.597 R -49.262 F -13.679 G 1.434][G loss: 21.047]  0:11:16.675289
1826 (5, 1) [D loss: -49.628 R -39.396 F -31.178 G 2.095][G loss: -17.741]  0:11:17.487025
1827 (5, 1) [D loss: -66.238 R -11.754 F -70.015 G 1.553][G loss: -26.726]  0:11:18.297684
1828 (5, 1) [D loss: -53.899 R 2.908 F -73.548 G 1.674][G loss: -25.645]  0:11:19.116130
1829 (5, 1) [D loss: -62.567 R -20.351 F -61.987 G 1.977][G loss: -60.078]  0:11:19.928945
1830 (5, 1) [D loss: -48.795 R -17.558 F -52.948 G 2.171][G loss: -26.657]  0:11:20.735089
1831 (5, 1) [D loss: -74.209 R -29.768 F -75.853 G 3.141][G loss: -93.362]  0:11:21.539500
1832 (5, 1) [D loss: -71.888 R -59.846 F -40.871 G 2.883][G loss: -173.258]  0:11:22.345673
1833 (5, 1) [D loss: -40.771 R -67.974 F 2.911 G 2.429][G loss: -115.411]  0:11:23.167419
1834 (5, 1) [D loss: -44.615 R -91.983 F 17.080 G 3.029][G loss: -133.116]  0:11:23.984847
1835 (5, 1) [D loss: -50.079 R -81.875 F 7.373 G 2.442][G loss: -161.461]  0:11:24.788275
1836 (5, 1) [D loss: -43.904 R -70.793 F 8.160 G 1.873][G loss: -67.701]  0:11:25.615875
1837 (5, 1) [D loss: -50.888 R -120.352 F 48.105 G 2.136][G loss: -149.161]  0:11:26.425873
1838 (5, 1) [D loss: -69.234 R -136.613 F 38.439 G 2.894][G loss: -176.400]  0:11:27.245543
1839 (5, 1) [D loss: -68.808 R -167.760 F 72.244 G 2.671][G loss: -178.698]  0:11:28.062281
1840 (5, 1) [D loss: -64.358 R -151.400 F 67.839 G 1.920][G loss: -107.411]  0:11:28.871379
1841 (5, 1) [D loss: -70.854 R -167.630 F 67.779 G 2.900][G loss: -74.899]  0:11:29.708360
1842 (5, 1) [D loss: -86.249 R -198.818 F 70.333 G 4.224][G loss: -69.920]  0:11:30.515572
1843 (5, 1) [D loss: -84.150 R -152.065 F 27.101 G 4.081][G loss: -16.057]  0:11:31.337769
1844 (5, 1) [D loss: -82.798 R -215.228 F 60.071 G 7.236][G loss: -70.694]  0:11:32.144247
1845 (5, 1) [D loss: -87.698 R -156.624 F 45.155 G 2.377][G loss: 72.254]  0:11:32.965987
1846 (5, 1) [D loss: -120.872 R -236.433 F 12.059 G 10.350][G loss: 7.614]  0:11:33.770549
1847 (5, 1) [D loss: -125.570 R -196.587 F 31.490 G 3.953][G loss: 58.081]  0:11:34.570839
1848 (5, 1) [D loss: -133.392 R -180.190 F 9.780 G 3.702][G loss: 128.869]  0:11:35.381736
1849 (5, 1) [D loss: -115.209 R -112.377 F -91.089 G 8.826][G loss: 73.982]  0:11:36.199068
1850 (5, 1) [D loss: -104.195 R -72.025 F -132.254 G 10.008][G loss: 78.676]  0:11:37.019429
1851 (5, 1) [D loss: -125.381 R -83.343 F -135.427 G 9.339][G loss: 66.259]  0:11:37.829406
1852 (5, 1) [D loss: -82.018 R -66.771 F -46.006 G 3.076][G loss: 11.684]  0:11:38.631515
1853 (5, 1) [D loss: -83.902 R -70.767 F -62.582 G 4.945][G loss: 10.605]  0:11:39.444441
1854 (5, 1) [D loss: -44.571 R -92.031 F 24.941 G 2.252][G loss: -45.965]  0:11:40.253479
1855 (5, 1) [D loss: -45.208 R -83.720 F 16.255 G 2.226][G loss: -64.319]  0:11:41.074052
1856 (5, 1) [D loss: -42.210 R -134.642 F 66.627 G 2.581][G loss: -140.528]  0:11:41.885119
1857 (5, 1) [D loss: -29.792 R -163.184 F 107.278 G 2.611][G loss: -244.294]  0:11:42.689916
1858 (5, 1) [D loss: -53.747 R -153.491 F 86.717 G 1.303][G loss: -135.533]  0:11:43.508359
1859 (5, 1) [D loss: -57.802 R -217.569 F 131.624 G 2.814][G loss: -197.199]  0:11:44.312903
1860 (5, 1) [D loss: -45.956 R -299.222 F 227.361 G 2.591][G loss: -314.198]  0:11:45.124594
1861 (5, 1) [D loss: -65.499 R -387.278 F 308.176 G 1.360][G loss: -234.569]  0:11:45.935972
1862 (5, 1) [D loss: -34.112 R -275.951 F 228.691 G 1.315][G loss: -275.257]  0:11:46.741353
1863 (5, 1) [D loss: -39.088 R -324.773 F 266.443 G 1.924][G loss: -314.197]  0:11:47.553636
1864 (5, 1) [D loss: -32.952 R -399.448 F 361.550 G 0.495][G loss: -356.722]  0:11:48.357873
1865 (5, 1) [D loss: -32.855 R -457.763 F 417.908 G 0.700][G loss: -388.551]  0:11:49.177905
1866 (5, 1) [D loss: -32.763 R -576.780 F 531.670 G 1.235][G loss: -437.086]  0:11:50.000807
1867 (5, 1) [D loss: -36.327 R -490.468 F 444.499 G 0.964][G loss: -406.922]  0:11:50.813818
1868 (5, 1) [D loss: -37.287 R -444.113 F 392.242 G 1.458][G loss: -365.058]  0:11:51.615972
1869 (5, 1) [D loss: -39.529 R -382.092 F 326.365 G 1.620][G loss: -332.038]  0:11:52.422578
1870 (5, 1) [D loss: -33.745 R -231.108 F 164.587 G 3.278][G loss: -165.346]  0:11:53.229231
1871 (5, 1) [D loss: -29.098 R -241.311 F 208.063 G 0.415][G loss: -241.846]  0:11:54.038898
1872 (5, 1) [D loss: -32.410 R -306.205 F 261.979 G 1.182][G loss: -281.479]  0:11:54.848593
1873 (5, 1) [D loss: -39.528 R -364.906 F 308.424 G 1.695][G loss: -303.705]  0:11:55.658097
1874 (5, 1) [D loss: -34.925 R -354.216 F 308.962 G 1.033][G loss: -323.660]  0:11:56.458848
1875 (5, 1) [D loss: -34.983 R -367.685 F 319.291 G 1.341][G loss: -313.534]  0:11:57.268082
1876 (5, 1) [D loss: -31.453 R -337.740 F 294.636 G 1.165][G loss: -291.429]  0:11:58.079963
1877 (5, 1) [D loss: -31.958 R -312.182 F 264.402 G 1.582][G loss: -267.435]  0:11:58.929741
1878 (5, 1) [D loss: -24.633 R -301.048 F 262.331 G 1.408][G loss: -250.822]  0:11:59.761984
1879 (5, 1) [D loss: -32.965 R -264.907 F 224.518 G 0.742][G loss: -237.988]  0:12:00.566993
1880 (5, 1) [D loss: -25.725 R -238.156 F 202.987 G 0.944][G loss: -197.036]  0:12:01.389920
1881 (5, 1) [D loss: -24.058 R -203.414 F 168.179 G 1.118][G loss: -167.458]  0:12:02.206353
1882 (5, 1) [D loss: -33.574 R -172.136 F 129.767 G 0.880][G loss: -153.002]  0:12:03.019759
1883 (5, 1) [D loss: -32.899 R -155.518 F 115.294 G 0.732][G loss: -136.003]  0:12:03.839238
1884 (5, 1) [D loss: -23.504 R -121.920 F 86.694 G 1.172][G loss: -110.632]  0:12:04.668929
1885 (5, 1) [D loss: -31.414 R -90.639 F 51.254 G 0.797][G loss: -74.202]  0:12:05.470988
1886 (5, 1) [D loss: -36.480 R -37.389 F -10.098 G 1.101][G loss: -46.969]  0:12:06.270766
1887 (5, 1) [D loss: -34.696 R 0.661 F -44.934 G 0.958][G loss: 8.845]  0:12:07.084147
1888 (5, 1) [D loss: -42.938 R 52.165 F -104.218 G 0.912][G loss: 17.059]  0:12:07.889182
1889 (5, 1) [D loss: -39.767 R 116.571 F -169.349 G 1.301][G loss: 102.159]  0:12:08.693150
1890 (5, 1) [D loss: -38.675 R 176.032 F -229.244 G 1.454][G loss: 175.613]  0:12:09.506572
1891 (5, 1) [D loss: -35.091 R 117.956 F -164.711 G 1.166][G loss: 105.772]  0:12:10.327223
1892 (5, 1) [D loss: -26.770 R 114.130 F -154.258 G 1.336][G loss: 159.245]  0:12:11.136530
1893 (5, 1) [D loss: -37.089 R 116.242 F -166.775 G 1.344][G loss: 105.413]  0:12:11.951041
1894 (5, 1) [D loss: -31.621 R 154.533 F -196.141 G 0.999][G loss: 180.761]  0:12:12.770565
1895 (5, 1) [D loss: -31.019 R 143.619 F -193.390 G 1.875][G loss: 224.340]  0:12:13.586407
1896 (5, 1) [D loss: -29.671 R 108.112 F -143.657 G 0.587][G loss: 165.395]  0:12:14.393094
1897 (5, 1) [D loss: -26.266 R 92.842 F -127.888 G 0.878][G loss: 129.364]  0:12:15.193226
1898 (5, 1) [D loss: -24.721 R 44.765 F -73.908 G 0.442][G loss: 82.494]  0:12:15.999115
1899 (5, 1) [D loss: -22.778 R 23.738 F -60.237 G 1.372][G loss: 85.787]  0:12:16.810610
1900 (5, 1) [D loss: -22.140 R -26.906 F -1.325 G 0.609][G loss: 0.511]  0:12:17.619690
1901 (5, 1) [D loss: -35.392 R -54.700 F 4.300 G 1.501][G loss: 49.258]  0:12:18.432603
1902 (5, 1) [D loss: -31.217 R -57.427 F 17.139 G 0.907][G loss: 7.396]  0:12:19.250524
1903 (5, 1) [D loss: -41.899 R -80.936 F 26.234 G 1.280][G loss: 7.317]  0:12:20.060782
1904 (5, 1) [D loss: -39.015 R -102.234 F 50.861 G 1.236][G loss: -38.803]  0:12:20.870891
1905 (5, 1) [D loss: -24.194 R -102.219 F 65.185 G 1.284][G loss: -58.620]  0:12:21.683326
1906 (5, 1) [D loss: -40.839 R -98.209 F 45.631 G 1.174][G loss: -29.741]  0:12:22.501585
1907 (5, 1) [D loss: -37.763 R -90.719 F 44.176 G 0.878][G loss: -30.094]  0:12:23.300089
1908 (5, 1) [D loss: -47.547 R -92.239 F 27.774 G 1.692][G loss: -33.382]  0:12:24.107729
1909 (5, 1) [D loss: -51.653 R -102.519 F 26.229 G 2.464][G loss: -35.002]  0:12:24.921685
1910 (5, 1) [D loss: -53.058 R -99.563 F 26.995 G 1.951][G loss: -48.815]  0:12:25.733616
1911 (5, 1) [D loss: -44.200 R -115.162 F 52.090 G 1.887][G loss: -74.444]  0:12:26.544439
1912 (5, 1) [D loss: -34.437 R -128.290 F 76.953 G 1.690][G loss: -87.078]  0:12:27.347342
1913 (5, 1) [D loss: -42.094 R -161.435 F 109.696 G 0.965][G loss: -115.746]  0:12:28.157560
1914 (5, 1) [D loss: -46.619 R -122.397 F 56.417 G 1.936][G loss: -92.981]  0:12:28.969962
1915 (5, 1) [D loss: -56.522 R -123.237 F 33.446 G 3.327][G loss: -86.996]  0:12:29.789540
1916 (5, 1) [D loss: -34.311 R -79.408 F 26.763 G 1.833][G loss: -76.760]  0:12:30.598144
1917 (5, 1) [D loss: -19.114 R -84.568 F 45.125 G 2.033][G loss: -72.011]  0:12:31.438115
1918 (5, 1) [D loss: -30.344 R -94.495 F 48.587 G 1.556][G loss: -74.083]  0:12:32.249095
1919 (5, 1) [D loss: -40.660 R -106.529 F 56.842 G 0.903][G loss: -84.735]  0:12:33.064938
1920 (5, 1) [D loss: -16.233 R -101.161 F 73.542 G 1.139][G loss: -79.136]  0:12:33.876298
1921 (5, 1) [D loss: -30.439 R -103.595 F 61.024 G 1.213][G loss: -79.799]  0:12:34.693064
1922 (5, 1) [D loss: -11.409 R -96.032 F 74.020 G 1.060][G loss: -81.525]  0:12:35.498063
1923 (5, 1) [D loss: -32.939 R -108.028 F 68.699 G 0.639][G loss: -78.068]  0:12:36.305098
1924 (5, 1) [D loss: -33.570 R -108.614 F 66.241 G 0.880][G loss: -76.856]  0:12:37.124438
1925 (5, 1) [D loss: -32.054 R -101.432 F 59.617 G 0.976][G loss: -66.229]  0:12:37.943939
1926 (5, 1) [D loss: -22.471 R -101.846 F 68.956 G 1.042][G loss: -73.371]  0:12:38.747793
1927 (5, 1) [D loss: -37.913 R -113.707 F 62.412 G 1.338][G loss: -78.067]  0:12:39.553221
1928 (5, 1) [D loss: -28.890 R -109.346 F 72.559 G 0.790][G loss: -59.514]  0:12:40.360616
1929 (5, 1) [D loss: -30.472 R -110.828 F 69.765 G 1.059][G loss: -67.256]  0:12:41.173526
1930 (5, 1) [D loss: -25.216 R -97.218 F 65.229 G 0.677][G loss: -59.788]  0:12:41.992081
1931 (5, 1) [D loss: -43.238 R -101.800 F 49.397 G 0.916][G loss: -38.621]  0:12:42.793384
1932 (5, 1) [D loss: -31.481 R -91.691 F 51.341 G 0.887][G loss: -56.855]  0:12:43.615112
1933 (5, 1) [D loss: -27.878 R -127.082 F 89.234 G 0.997][G loss: -81.712]  0:12:44.422458
1934 (5, 1) [D loss: -27.626 R -97.353 F 59.998 G 0.973][G loss: -64.590]  0:12:45.230732
1935 (5, 1) [D loss: -28.309 R -112.352 F 75.093 G 0.895][G loss: -79.511]  0:12:46.040809
1936 (5, 1) [D loss: -17.332 R -126.166 F 93.646 G 1.519][G loss: -87.550]  0:12:46.848880
1937 (5, 1) [D loss: -35.118 R -106.137 F 58.108 G 1.291][G loss: -80.413]  0:12:47.650734
1938 (5, 1) [D loss: -16.065 R -90.253 F 67.256 G 0.693][G loss: -69.466]  0:12:48.461099
1939 (5, 1) [D loss: -25.917 R -99.852 F 63.977 G 0.996][G loss: -63.349]  0:12:49.272282
1940 (5, 1) [D loss: -27.472 R -94.925 F 56.199 G 1.125][G loss: -65.272]  0:12:50.093381
1941 (5, 1) [D loss: -29.877 R -95.220 F 57.684 G 0.766][G loss: -73.819]  0:12:50.896544
1942 (5, 1) [D loss: -30.632 R -90.965 F 53.695 G 0.664][G loss: -74.138]  0:12:51.704392
1943 (5, 1) [D loss: -24.464 R -69.516 F 38.853 G 0.620][G loss: -48.457]  0:12:52.516561
1944 (5, 1) [D loss: -34.441 R -82.512 F 39.615 G 0.846][G loss: -62.444]  0:12:53.325842
1945 (5, 1) [D loss: -25.225 R -56.129 F 19.293 G 1.161][G loss: -37.733]  0:12:54.156636
1946 (5, 1) [D loss: -28.140 R -58.409 F 22.773 G 0.750][G loss: -56.831]  0:12:54.964325
1947 (5, 1) [D loss: -16.241 R -45.953 F 24.385 G 0.533][G loss: -32.147]  0:12:55.763843
1948 (5, 1) [D loss: -27.441 R -64.111 F 30.441 G 0.623][G loss: -43.030]  0:12:56.568440
1949 (5, 1) [D loss: -26.877 R -30.875 F -1.315 G 0.531][G loss: -26.941]  0:12:57.374163
1950 (5, 1) [D loss: -23.168 R -37.349 F 6.739 G 0.744][G loss: -29.338]  0:12:58.180903
1951 (5, 1) [D loss: -25.608 R -44.694 F 12.589 G 0.650][G loss: -3.330]  0:12:58.979025
1952 (5, 1) [D loss: -29.130 R -20.633 F -16.612 G 0.811][G loss: 33.133]  0:12:59.773608
1953 (5, 1) [D loss: -28.685 R -14.427 F -22.088 G 0.783][G loss: 39.099]  0:13:00.572641
1954 (5, 1) [D loss: -18.262 R -30.777 F 7.703 G 0.481][G loss: -7.308]  0:13:01.394235
1955 (5, 1) [D loss: -26.680 R -51.788 F 18.835 G 0.627][G loss: -0.816]  0:13:02.207615
1956 (5, 1) [D loss: -34.490 R -54.238 F 12.983 G 0.677][G loss: -6.589]  0:13:03.013860
1957 (5, 1) [D loss: -22.094 R -54.112 F 26.748 G 0.527][G loss: -26.391]  0:13:03.825476
1958 (5, 1) [D loss: -15.016 R -47.119 F 18.161 G 1.394][G loss: -6.752]  0:13:04.659758
1959 (5, 1) [D loss: -23.879 R -48.564 F 15.402 G 0.928][G loss: -8.241]  0:13:05.488605
1960 (5, 1) [D loss: -28.575 R -58.025 F 22.429 G 0.702][G loss: -18.178]  0:13:06.315155
1961 (5, 1) [D loss: -21.437 R -76.194 F 49.614 G 0.514][G loss: -54.492]  0:13:07.128237
1962 (5, 1) [D loss: -32.615 R -69.011 F 21.647 G 1.475][G loss: -15.996]  0:13:07.932958
1963 (5, 1) [D loss: -39.151 R -70.133 F 21.369 G 0.961][G loss: -24.465]  0:13:08.748494
1964 (5, 1) [D loss: -40.182 R -63.557 F 15.001 G 0.837][G loss: -28.726]  0:13:09.563272
1965 (5, 1) [D loss: -31.898 R -78.911 F 29.021 G 1.799][G loss: -40.038]  0:13:10.383927
1966 (5, 1) [D loss: -31.391 R -72.925 F 26.803 G 1.473][G loss: -52.108]  0:13:11.209509
1967 (5, 1) [D loss: -27.585 R -68.348 F 28.442 G 1.232][G loss: -43.940]  0:13:12.007351
1968 (5, 1) [D loss: -21.609 R -62.757 F 27.539 G 1.361][G loss: -45.775]  0:13:12.826749
1969 (5, 1) [D loss: -37.385 R -81.382 F 36.121 G 0.788][G loss: -49.876]  0:13:13.634212
1970 (5, 1) [D loss: -18.601 R -67.206 F 39.055 G 0.955][G loss: -40.192]  0:13:14.436856
1971 (5, 1) [D loss: -23.818 R -68.352 F 35.803 G 0.873][G loss: -46.242]  0:13:15.251500
1972 (5, 1) [D loss: -32.170 R -67.498 F 24.747 G 1.058][G loss: -44.219]  0:13:16.063390
1973 (5, 1) [D loss: -28.393 R -61.894 F 23.070 G 1.043][G loss: -47.274]  0:13:16.867383
1974 (5, 1) [D loss: -40.350 R -60.317 F 4.630 G 1.534][G loss: -46.438]  0:13:17.676297
1975 (5, 1) [D loss: -23.705 R -55.472 F 18.213 G 1.355][G loss: -46.241]  0:13:18.477429
1976 (5, 1) [D loss: -24.856 R -54.502 F 21.697 G 0.795][G loss: -32.035]  0:13:19.287893
1977 (5, 1) [D loss: -26.186 R -60.465 F 27.169 G 0.711][G loss: -31.187]  0:13:20.090007
1978 (5, 1) [D loss: -21.035 R -55.368 F 20.440 G 1.389][G loss: -30.419]  0:13:20.895772
1979 (5, 1) [D loss: -23.810 R -60.908 F 30.088 G 0.701][G loss: -7.458]  0:13:21.701196
1980 (5, 1) [D loss: -26.659 R -51.576 F 16.209 G 0.871][G loss: -30.187]  0:13:22.506176
1981 (5, 1) [D loss: -27.682 R -56.647 F 22.225 G 0.674][G loss: -26.790]  0:13:23.316552
1982 (5, 1) [D loss: -30.060 R -59.668 F 23.707 G 0.590][G loss: -21.161]  0:13:24.128916
1983 (5, 1) [D loss: -25.891 R -45.509 F 11.134 G 0.848][G loss: -3.370]  0:13:24.934889
1984 (5, 1) [D loss: -28.898 R -48.414 F 11.370 G 0.815][G loss: -3.140]  0:13:25.742347
1985 (5, 1) [D loss: -36.796 R -48.601 F 2.957 G 0.885][G loss: 0.153]  0:13:26.549285
1986 (5, 1) [D loss: -30.302 R -72.310 F 31.879 G 1.013][G loss: -25.397]  0:13:27.352797
1987 (5, 1) [D loss: -40.730 R -78.703 F 27.716 G 1.026][G loss: -37.748]  0:13:28.159917
1988 (5, 1) [D loss: -41.898 R -54.446 F 2.445 G 1.010][G loss: -41.749]  0:13:28.970157
1989 (5, 1) [D loss: -34.481 R -65.809 F 23.319 G 0.801][G loss: -49.740]  0:13:29.771129
1990 (5, 1) [D loss: -24.162 R -108.171 F 75.368 G 0.864][G loss: -84.695]  0:13:30.574369
1991 (5, 1) [D loss: -23.812 R -92.367 F 61.603 G 0.695][G loss: -63.777]  0:13:31.379319
1992 (5, 1) [D loss: -28.587 R -82.828 F 47.024 G 0.722][G loss: -56.470]  0:13:32.187541
1993 (5, 1) [D loss: -26.916 R -65.685 F 31.518 G 0.725][G loss: -64.560]  0:13:32.997082
1994 (5, 1) [D loss: -26.654 R -78.533 F 45.557 G 0.632][G loss: -59.786]  0:13:33.809936
1995 (5, 1) [D loss: -12.284 R -74.931 F 55.239 G 0.741][G loss: -53.085]  0:13:34.624742
1996 (5, 1) [D loss: -24.066 R -63.430 F 33.132 G 0.623][G loss: -45.019]  0:13:35.438417
1997 (5, 1) [D loss: -21.853 R -66.833 F 39.564 G 0.542][G loss: -43.430]  0:13:36.237806
1998 (5, 1) [D loss: -21.373 R -71.192 F 43.941 G 0.588][G loss: -44.035]  0:13:37.036769
1999 (5, 1) [D loss: -21.750 R -74.984 F 48.319 G 0.491][G loss: -52.573]  0:13:37.871165
2000 (5, 1) [D loss: -24.252 R -77.455 F 46.971 G 0.623][G loss: -65.310]  0:13:38.688383
2001 (5, 1) [D loss: -18.092 R -99.365 F 76.158 G 0.511][G loss: -86.906]  0:13:41.736539
2002 (5, 1) [D loss: -18.505 R -109.723 F 85.757 G 0.546][G loss: -88.378]  0:13:42.538152
2003 (5, 1) [D loss: -20.682 R -123.922 F 98.427 G 0.481][G loss: -94.696]  0:13:43.359486
2004 (5, 1) [D loss: -24.025 R -126.925 F 97.327 G 0.557][G loss: -110.100]  0:13:44.168086
2005 (5, 1) [D loss: -20.433 R -117.480 F 92.496 G 0.455][G loss: -90.556]  0:13:44.995602
2006 (5, 1) [D loss: -17.382 R -103.898 F 79.758 G 0.676][G loss: -93.021]  0:13:45.852084
2007 (5, 1) [D loss: -20.869 R -109.360 F 84.491 G 0.400][G loss: -81.020]  0:13:46.675879
2008 (5, 1) [D loss: -21.292 R -117.780 F 87.769 G 0.872][G loss: -71.819]  0:13:47.483377
2009 (5, 1) [D loss: -13.475 R -115.780 F 92.801 G 0.950][G loss: -74.044]  0:13:48.437552
2010 (5, 1) [D loss: -35.975 R -132.120 F 87.830 G 0.831][G loss: -75.724]  0:13:49.260479
2011 (5, 1) [D loss: -21.345 R -120.256 F 89.240 G 0.967][G loss: -78.797]  0:13:50.076820
2012 (5, 1) [D loss: -34.058 R -121.942 F 79.863 G 0.802][G loss: -75.736]  0:13:50.888708
2013 (5, 1) [D loss: -27.518 R -117.533 F 82.109 G 0.791][G loss: -83.871]  0:13:51.688236
2014 (5, 1) [D loss: -36.678 R -134.896 F 83.233 G 1.499][G loss: -94.533]  0:13:52.500087
2015 (5, 1) [D loss: -27.239 R -121.855 F 81.051 G 1.357][G loss: -105.439]  0:13:53.306565
2016 (5, 1) [D loss: -26.915 R -133.650 F 99.898 G 0.684][G loss: -105.175]  0:13:54.117776
2017 (5, 1) [D loss: -30.019 R -126.968 F 91.073 G 0.588][G loss: -95.469]  0:13:54.927140
2018 (5, 1) [D loss: -23.168 R -117.179 F 86.337 G 0.767][G loss: -91.019]  0:13:55.734856
2019 (5, 1) [D loss: -24.963 R -111.091 F 72.014 G 1.411][G loss: -89.842]  0:13:56.538676
2020 (5, 1) [D loss: -29.730 R -112.022 F 71.165 G 1.113][G loss: -95.795]  0:13:57.349421
2021 (5, 1) [D loss: -48.802 R -114.518 F 52.959 G 1.276][G loss: -92.014]  0:13:58.162673
2022 (5, 1) [D loss: -21.657 R -120.814 F 94.327 G 0.483][G loss: -96.165]  0:13:58.974938
2023 (5, 1) [D loss: -23.361 R -100.901 F 71.461 G 0.608][G loss: -80.542]  0:13:59.781506
2024 (5, 1) [D loss: -19.546 R -80.466 F 52.987 G 0.793][G loss: -43.631]  0:14:00.583739
2025 (5, 1) [D loss: -25.017 R -67.906 F 37.691 G 0.520][G loss: -40.981]  0:14:01.378426
2026 (5, 1) [D loss: -22.513 R -66.421 F 34.217 G 0.969][G loss: -48.072]  0:14:02.188216
2027 (5, 1) [D loss: -10.627 R -66.465 F 45.968 G 0.987][G loss: -26.966]  0:14:02.993159
2028 (5, 1) [D loss: -21.089 R -61.619 F 36.518 G 0.401][G loss: -37.108]  0:14:03.805842
2029 (5, 1) [D loss: -26.007 R -68.437 F 36.130 G 0.630][G loss: -44.848]  0:14:04.606783
2030 (5, 1) [D loss: -18.811 R -52.430 F 25.922 G 0.770][G loss: -13.920]  0:14:05.407190
2031 (5, 1) [D loss: -20.706 R -65.385 F 39.493 G 0.519][G loss: -43.384]  0:14:06.225057
2032 (5, 1) [D loss: -24.635 R -83.924 F 54.438 G 0.485][G loss: -55.610]  0:14:07.027280
2033 (5, 1) [D loss: -17.536 R -72.436 F 48.555 G 0.634][G loss: -36.865]  0:14:07.828391
2034 (5, 1) [D loss: -22.725 R -63.760 F 35.937 G 0.510][G loss: -34.862]  0:14:08.656503
2035 (5, 1) [D loss: -19.926 R -47.331 F 22.374 G 0.503][G loss: -23.705]  0:14:09.471080
2036 (5, 1) [D loss: -15.741 R -46.085 F 19.822 G 1.052][G loss: -14.805]  0:14:10.298189
2037 (5, 1) [D loss: -24.341 R -50.226 F 22.095 G 0.379][G loss: -29.488]  0:14:11.124432
2038 (5, 1) [D loss: -19.022 R -43.428 F 19.247 G 0.516][G loss: -31.514]  0:14:11.941882
2039 (5, 1) [D loss: -21.966 R -57.285 F 25.992 G 0.933][G loss: -40.648]  0:14:12.744953
2040 (5, 1) [D loss: -51.973 R -61.819 F -0.986 G 1.083][G loss: -66.702]  0:14:13.554276
2041 (5, 1) [D loss: -18.142 R -57.093 F 32.804 G 0.615][G loss: -52.017]  0:14:14.363877
2042 (5, 1) [D loss: -24.733 R -73.560 F 32.426 G 1.640][G loss: -84.296]  0:14:15.172145
2043 (5, 1) [D loss: -39.266 R -79.010 F 31.912 G 0.783][G loss: -74.584]  0:14:15.983497
2044 (5, 1) [D loss: -33.610 R -85.252 F 46.742 G 0.490][G loss: -87.822]  0:14:16.795237
2045 (5, 1) [D loss: -12.413 R -89.210 F 68.512 G 0.828][G loss: -85.252]  0:14:17.597829
2046 (5, 1) [D loss: -29.229 R -86.342 F 36.629 G 2.048][G loss: -109.122]  0:14:18.404248
2047 (5, 1) [D loss: -30.156 R -82.553 F 44.816 G 0.758][G loss: -109.713]  0:14:19.214041
2048 (5, 1) [D loss: -29.843 R -104.553 F 65.753 G 0.896][G loss: -118.718]  0:14:20.012551
2049 (5, 1) [D loss: -20.714 R -108.417 F 80.294 G 0.741][G loss: -122.513]  0:14:20.812275
2050 (5, 1) [D loss: -30.068 R -110.085 F 74.724 G 0.529][G loss: -111.132]  0:14:21.615950
2051 (5, 1) [D loss: -23.968 R -108.441 F 79.584 G 0.489][G loss: -98.966]  0:14:22.437090
2052 (5, 1) [D loss: -22.652 R -117.834 F 90.190 G 0.499][G loss: -83.118]  0:14:23.233377
2053 (5, 1) [D loss: -23.956 R -133.908 F 99.836 G 1.012][G loss: -72.471]  0:14:24.031613
2054 (5, 1) [D loss: -35.035 R -114.929 F 61.750 G 1.814][G loss: -27.720]  0:14:24.836276
2055 (5, 1) [D loss: -30.761 R -132.895 F 88.355 G 1.378][G loss: -45.045]  0:14:25.645374
2056 (5, 1) [D loss: -20.006 R -117.732 F 94.176 G 0.355][G loss: -94.233]  0:14:26.461443
2057 (5, 1) [D loss: -21.644 R -141.716 F 114.417 G 0.566][G loss: -101.799]  0:14:27.269289
2058 (5, 1) [D loss: -31.273 R -148.834 F 111.632 G 0.593][G loss: -89.024]  0:14:28.068622
2059 (5, 1) [D loss: -18.693 R -139.862 F 103.987 G 1.718][G loss: -74.652]  0:14:28.863204
2060 (5, 1) [D loss: -19.683 R -157.804 F 121.166 G 1.696][G loss: -86.603]  0:14:29.679598
2061 (5, 1) [D loss: -47.166 R -144.862 F 86.487 G 1.121][G loss: -82.410]  0:14:30.479327
2062 (5, 1) [D loss: -26.083 R -137.279 F 95.785 G 1.541][G loss: -91.548]  0:14:31.276700
2063 (5, 1) [D loss: -22.888 R -141.015 F 100.271 G 1.786][G loss: -104.801]  0:14:32.099509
2064 (5, 1) [D loss: -56.708 R -150.410 F 74.307 G 1.939][G loss: -106.067]  0:14:32.896702
2065 (5, 1) [D loss: -37.699 R -138.837 F 93.929 G 0.721][G loss: -106.826]  0:14:33.719900
2066 (5, 1) [D loss: -22.396 R -124.410 F 86.486 G 1.553][G loss: -109.837]  0:14:34.526263
2067 (5, 1) [D loss: -41.439 R -144.004 F 90.929 G 1.164][G loss: -119.879]  0:14:35.323552
2068 (5, 1) [D loss: -66.349 R -148.981 F 60.681 G 2.195][G loss: -129.592]  0:14:36.129763
2069 (5, 1) [D loss: -38.632 R -141.672 F 94.936 G 0.810][G loss: -129.773]  0:14:36.949859
2070 (5, 1) [D loss: -28.198 R -147.619 F 109.635 G 0.979][G loss: -135.609]  0:14:37.762808
2071 (5, 1) [D loss: -24.189 R -143.978 F 106.885 G 1.290][G loss: -139.537]  0:14:38.578372
2072 (5, 1) [D loss: -23.356 R -153.511 F 119.133 G 1.102][G loss: -137.539]  0:14:39.374714
2073 (5, 1) [D loss: -22.240 R -148.350 F 116.094 G 1.002][G loss: -127.182]  0:14:40.185076
2074 (5, 1) [D loss: -20.157 R -127.432 F 93.550 G 1.373][G loss: -124.084]  0:14:40.987720
2075 (5, 1) [D loss: -27.904 R -135.672 F 97.525 G 1.024][G loss: -125.898]  0:14:41.795509
2076 (5, 1) [D loss: -35.744 R -122.941 F 76.669 G 1.053][G loss: -115.774]  0:14:42.602587
2077 (5, 1) [D loss: -28.588 R -113.183 F 79.133 G 0.546][G loss: -88.746]  0:14:43.418444
2078 (5, 1) [D loss: -34.230 R -105.612 F 63.758 G 0.763][G loss: -83.059]  0:14:44.245311
2079 (5, 1) [D loss: -21.723 R -82.863 F 50.344 G 1.080][G loss: -43.813]  0:14:45.049653
2080 (5, 1) [D loss: -21.649 R -51.480 F 18.750 G 1.108][G loss: -2.567]  0:14:45.866470
2081 (5, 1) [D loss: -18.436 R -56.978 F 31.644 G 0.690][G loss: -30.159]  0:14:46.675259
2082 (5, 1) [D loss: -28.068 R -70.711 F 35.152 G 0.749][G loss: -23.847]  0:14:47.479354
2083 (5, 1) [D loss: -24.604 R -66.739 F 33.188 G 0.895][G loss: -33.073]  0:14:48.283837
2084 (5, 1) [D loss: -23.558 R -68.729 F 37.150 G 0.802][G loss: -34.448]  0:14:49.084256
2085 (5, 1) [D loss: -16.671 R -70.961 F 47.395 G 0.689][G loss: -47.308]  0:14:49.889422
2086 (5, 1) [D loss: -24.103 R -69.432 F 37.598 G 0.773][G loss: -27.723]  0:14:50.705573
2087 (5, 1) [D loss: -26.063 R -58.313 F 25.789 G 0.646][G loss: -29.669]  0:14:51.510731
2088 (5, 1) [D loss: -23.647 R -59.011 F 27.659 G 0.771][G loss: -25.158]  0:14:52.318489
2089 (5, 1) [D loss: -27.342 R -54.941 F 20.195 G 0.740][G loss: -20.065]  0:14:53.126856
2090 (5, 1) [D loss: -21.311 R -44.952 F 17.116 G 0.652][G loss: -18.701]  0:14:53.927675
2091 (5, 1) [D loss: -29.181 R -68.135 F 26.583 G 1.237][G loss: -14.319]  0:14:54.730873
2092 (5, 1) [D loss: -28.041 R -44.896 F 9.039 G 0.782][G loss: -4.413]  0:14:55.549750
2093 (5, 1) [D loss: -33.893 R -44.527 F 0.861 G 0.977][G loss: 1.973]  0:14:56.352088
2094 (5, 1) [D loss: -29.596 R -30.165 F -7.547 G 0.812][G loss: -1.337]  0:14:57.155552
2095 (5, 1) [D loss: -21.890 R -28.829 F -4.153 G 1.109][G loss: -0.069]  0:14:57.972560
2096 (5, 1) [D loss: -23.893 R -31.303 F -5.489 G 1.290][G loss: -6.658]  0:14:58.770056
2097 (5, 1) [D loss: -18.587 R -38.703 F 12.853 G 0.726][G loss: -11.014]  0:14:59.583016
2098 (5, 1) [D loss: -23.773 R -47.219 F 15.041 G 0.841][G loss: -25.704]  0:15:00.394364
2099 (5, 1) [D loss: -29.650 R -55.029 F 13.725 G 1.165][G loss: -31.752]  0:15:01.194363
2100 (5, 1) [D loss: -29.720 R -62.620 F 21.819 G 1.108][G loss: -45.879]  0:15:01.999386
2101 (5, 1) [D loss: -21.291 R -68.267 F 39.309 G 0.767][G loss: -50.217]  0:15:02.815536
2102 (5, 1) [D loss: -10.385 R -77.951 F 57.800 G 0.977][G loss: -69.852]  0:15:03.616422
2103 (5, 1) [D loss: -39.446 R -85.547 F 32.163 G 1.394][G loss: -73.165]  0:15:04.424668
2104 (5, 1) [D loss: -28.256 R -88.506 F 47.603 G 1.265][G loss: -80.948]  0:15:05.223722
2105 (5, 1) [D loss: -20.724 R -95.577 F 69.371 G 0.548][G loss: -80.979]  0:15:06.024387
2106 (5, 1) [D loss: -20.453 R -97.516 F 72.620 G 0.444][G loss: -88.679]  0:15:06.830670
2107 (5, 1) [D loss: -23.704 R -88.766 F 60.418 G 0.464][G loss: -79.637]  0:15:07.626472
2108 (5, 1) [D loss: -23.274 R -102.933 F 74.463 G 0.520][G loss: -82.661]  0:15:08.437206
2109 (5, 1) [D loss: -16.805 R -111.659 F 89.353 G 0.550][G loss: -91.977]  0:15:09.240121
2110 (5, 1) [D loss: -14.887 R -100.310 F 80.402 G 0.502][G loss: -92.544]  0:15:10.045757
2111 (5, 1) [D loss: -29.075 R -82.020 F 45.432 G 0.751][G loss: -85.052]  0:15:10.859131
2112 (5, 1) [D loss: -19.090 R -71.375 F 49.894 G 0.239][G loss: -59.480]  0:15:11.659261
2113 (5, 1) [D loss: -20.529 R -99.350 F 75.255 G 0.357][G loss: -74.771]  0:15:12.472974
2114 (5, 1) [D loss: -26.435 R -114.329 F 81.156 G 0.674][G loss: -63.598]  0:15:13.284493
2115 (5, 1) [D loss: -19.236 R -116.945 F 93.144 G 0.457][G loss: -93.688]  0:15:14.097171
2116 (5, 1) [D loss: -18.150 R -119.000 F 96.153 G 0.470][G loss: -106.889]  0:15:14.903083
2117 (5, 1) [D loss: -19.109 R -116.846 F 93.463 G 0.427][G loss: -102.471]  0:15:15.714293
2118 (5, 1) [D loss: -22.990 R -134.086 F 106.926 G 0.417][G loss: -98.367]  0:15:16.524670
2119 (5, 1) [D loss: -21.663 R -120.125 F 93.528 G 0.493][G loss: -86.034]  0:15:17.344578
2120 (5, 1) [D loss: -20.637 R -126.696 F 98.587 G 0.747][G loss: -87.745]  0:15:18.168274
2121 (5, 1) [D loss: -25.367 R -129.619 F 92.953 G 1.130][G loss: -84.349]  0:15:18.987702
2122 (5, 1) [D loss: -22.706 R -147.240 F 118.400 G 0.613][G loss: -108.347]  0:15:19.788915
2123 (5, 1) [D loss: -19.593 R -142.659 F 120.116 G 0.295][G loss: -125.921]  0:15:20.600867
2124 (5, 1) [D loss: -19.096 R -130.702 F 105.461 G 0.614][G loss: -95.761]  0:15:21.411222
2125 (5, 1) [D loss: -13.547 R -112.279 F 87.879 G 1.085][G loss: -75.231]  0:15:22.212462
2126 (5, 1) [D loss: -36.312 R -113.509 F 70.292 G 0.690][G loss: -82.236]  0:15:23.016073
2127 (5, 1) [D loss: -33.422 R -120.417 F 74.088 G 1.291][G loss: -85.239]  0:15:23.829477
2128 (5, 1) [D loss: -23.935 R -127.210 F 93.012 G 1.026][G loss: -101.680]  0:15:24.635968
2129 (5, 1) [D loss: -30.405 R -134.578 F 97.698 G 0.647][G loss: -115.067]  0:15:25.441696
2130 (5, 1) [D loss: -21.297 R -127.657 F 98.674 G 0.769][G loss: -106.942]  0:15:26.237516
2131 (5, 1) [D loss: -19.966 R -123.917 F 96.916 G 0.703][G loss: -104.557]  0:15:27.040082
2132 (5, 1) [D loss: -29.466 R -127.865 F 91.296 G 0.710][G loss: -101.004]  0:15:27.839689
2133 (5, 1) [D loss: -15.786 R -116.081 F 95.104 G 0.519][G loss: -88.142]  0:15:28.646369
2134 (5, 1) [D loss: -34.450 R -94.297 F 55.165 G 0.468][G loss: -82.628]  0:15:29.457749
2135 (5, 1) [D loss: -14.229 R -103.979 F 82.074 G 0.768][G loss: -85.696]  0:15:30.270739
2136 (5, 1) [D loss: -18.376 R -112.767 F 84.494 G 0.990][G loss: -92.134]  0:15:31.073490
2137 (5, 1) [D loss: -24.530 R -115.018 F 87.228 G 0.326][G loss: -93.564]  0:15:31.874751
2138 (5, 1) [D loss: -30.050 R -109.275 F 74.164 G 0.506][G loss: -93.285]  0:15:32.687176
2139 (5, 1) [D loss: -31.433 R -102.439 F 65.940 G 0.507][G loss: -90.140]  0:15:33.490242
2140 (5, 1) [D loss: -33.950 R -108.497 F 63.141 G 1.141][G loss: -98.315]  0:15:34.314574
2141 (5, 1) [D loss: -39.555 R -123.948 F 74.086 G 1.031][G loss: -108.571]  0:15:35.113829
2142 (5, 1) [D loss: -26.081 R -109.211 F 75.895 G 0.723][G loss: -108.656]  0:15:35.909799
2143 (5, 1) [D loss: -16.417 R -102.106 F 76.051 G 0.964][G loss: -105.556]  0:15:36.712319
2144 (5, 1) [D loss: -20.507 R -119.536 F 90.345 G 0.868][G loss: -105.730]  0:15:37.512711
2145 (5, 1) [D loss: -26.463 R -104.814 F 72.651 G 0.570][G loss: -94.375]  0:15:38.316369
2146 (5, 1) [D loss: -22.180 R -100.303 F 73.462 G 0.466][G loss: -73.189]  0:15:39.118796
2147 (5, 1) [D loss: -16.746 R -104.240 F 82.283 G 0.521][G loss: -78.177]  0:15:39.938361
2148 (5, 1) [D loss: -20.268 R -102.416 F 76.151 G 0.600][G loss: -79.315]  0:15:40.736541
2149 (5, 1) [D loss: -21.074 R -97.576 F 70.597 G 0.590][G loss: -60.733]  0:15:41.550403
2150 (5, 1) [D loss: -25.261 R -88.618 F 56.504 G 0.685][G loss: -43.125]  0:15:42.347289
2151 (5, 1) [D loss: -26.375 R -89.237 F 56.877 G 0.598][G loss: -50.249]  0:15:43.152190
2152 (5, 1) [D loss: -25.474 R -99.645 F 69.325 G 0.485][G loss: -61.368]  0:15:43.962928
2153 (5, 1) [D loss: -23.170 R -114.707 F 86.035 G 0.550][G loss: -77.045]  0:15:44.765904
2154 (5, 1) [D loss: -28.686 R -114.984 F 79.994 G 0.630][G loss: -68.220]  0:15:45.586652
2155 (5, 1) [D loss: -35.780 R -99.309 F 57.791 G 0.574][G loss: -69.639]  0:15:46.382819
2156 (5, 1) [D loss: -17.672 R -96.651 F 57.749 G 2.123][G loss: -48.708]  0:15:47.189985
2157 (5, 1) [D loss: -19.967 R -60.656 F 24.155 G 1.653][G loss: -49.570]  0:15:48.010240
2158 (5, 1) [D loss: -21.696 R -83.678 F 51.605 G 1.038][G loss: -48.518]  0:15:48.815560
2159 (5, 1) [D loss: -42.328 R -86.751 F 32.144 G 1.228][G loss: -52.563]  0:15:49.642044
2160 (5, 1) [D loss: -30.836 R -75.954 F 36.090 G 0.903][G loss: -66.031]  0:15:50.474021
2161 (5, 1) [D loss: -9.873 R -59.421 F 25.479 G 2.407][G loss: -44.821]  0:15:51.282629
2162 (5, 1) [D loss: -38.117 R -60.020 F 6.819 G 1.508][G loss: -70.695]  0:15:52.086175
2163 (5, 1) [D loss: -29.860 R -78.568 F 37.575 G 1.113][G loss: -69.579]  0:15:52.889906
2164 (5, 1) [D loss: -42.814 R -65.730 F 10.407 G 1.251][G loss: -63.734]  0:15:53.714565
2165 (5, 1) [D loss: -44.945 R -90.158 F 34.781 G 1.043][G loss: -94.313]  0:15:54.520598
2166 (5, 1) [D loss: -56.353 R -67.071 F -1.805 G 1.252][G loss: -108.712]  0:15:55.333451
2167 (5, 1) [D loss: -30.123 R -116.121 F 57.767 G 2.823][G loss: -113.737]  0:15:56.139384
2168 (5, 1) [D loss: -22.866 R -87.371 F 52.127 G 1.238][G loss: -99.659]  0:15:56.946874
2169 (5, 1) [D loss: -25.069 R -101.147 F 63.450 G 1.263][G loss: -104.221]  0:15:57.755577
2170 (5, 1) [D loss: -38.216 R -118.335 F 71.386 G 0.873][G loss: -127.548]  0:15:58.558133
2171 (5, 1) [D loss: -31.660 R -94.941 F 47.775 G 1.551][G loss: -125.831]  0:15:59.356799
2172 (5, 1) [D loss: -37.259 R -102.659 F 48.499 G 1.690][G loss: -144.870]  0:16:00.168841
2173 (5, 1) [D loss: -29.398 R -124.145 F 88.995 G 0.575][G loss: -131.010]  0:16:00.976669
2174 (5, 1) [D loss: -20.334 R -107.456 F 82.660 G 0.446][G loss: -91.438]  0:16:01.781689
2175 (5, 1) [D loss: -30.778 R -133.889 F 94.804 G 0.831][G loss: -136.355]  0:16:02.587823
2176 (5, 1) [D loss: -19.866 R -121.062 F 93.804 G 0.739][G loss: -132.290]  0:16:03.401786
2177 (5, 1) [D loss: -30.956 R -125.186 F 86.197 G 0.803][G loss: -144.530]  0:16:04.200297
2178 (5, 1) [D loss: -20.573 R -123.417 F 99.407 G 0.344][G loss: -89.956]  0:16:04.999496
2179 (5, 1) [D loss: -38.417 R -155.243 F 104.536 G 1.229][G loss: -45.372]  0:16:05.804172
2180 (5, 1) [D loss: -29.202 R -129.712 F 95.522 G 0.499][G loss: -74.760]  0:16:06.602414
2181 (5, 1) [D loss: -30.250 R -130.989 F 93.175 G 0.756][G loss: -67.750]  0:16:07.415768
2182 (5, 1) [D loss: -23.150 R -111.494 F 84.283 G 0.406][G loss: -79.158]  0:16:08.214870
2183 (5, 1) [D loss: -30.296 R -126.007 F 84.155 G 1.156][G loss: -43.178]  0:16:09.014243
2184 (5, 1) [D loss: -20.497 R -129.506 F 104.048 G 0.496][G loss: -88.615]  0:16:09.832638
2185 (5, 1) [D loss: -33.668 R -142.115 F 99.495 G 0.895][G loss: -70.062]  0:16:10.634085
2186 (5, 1) [D loss: -38.068 R -148.866 F 95.610 G 1.519][G loss: -77.767]  0:16:11.445996
2187 (5, 1) [D loss: -52.787 R -159.991 F 93.178 G 1.403][G loss: -84.174]  0:16:12.250750
2188 (5, 1) [D loss: -33.970 R -131.477 F 90.103 G 0.740][G loss: -76.911]  0:16:13.055658
2189 (5, 1) [D loss: -30.232 R -119.602 F 81.180 G 0.819][G loss: -78.814]  0:16:13.853787
2190 (5, 1) [D loss: -45.607 R -123.874 F 61.180 G 1.709][G loss: -75.419]  0:16:14.673386
2191 (5, 1) [D loss: -33.357 R -121.464 F 74.147 G 1.396][G loss: -84.172]  0:16:15.470267
2192 (5, 1) [D loss: -31.394 R -102.166 F 62.842 G 0.793][G loss: -76.185]  0:16:16.273216
2193 (5, 1) [D loss: -31.929 R -93.098 F 54.855 G 0.631][G loss: -67.976]  0:16:17.078784
2194 (5, 1) [D loss: -31.758 R -101.588 F 61.054 G 0.878][G loss: -71.390]  0:16:17.884751
2195 (5, 1) [D loss: -33.176 R -86.263 F 45.491 G 0.760][G loss: -68.652]  0:16:18.694954
2196 (5, 1) [D loss: -28.967 R -101.467 F 63.929 G 0.857][G loss: -83.094]  0:16:19.492371
2197 (5, 1) [D loss: -15.623 R -81.780 F 57.831 G 0.833][G loss: -73.338]  0:16:20.298577
2198 (5, 1) [D loss: -21.468 R -89.787 F 62.270 G 0.605][G loss: -61.810]  0:16:21.136329
2199 (5, 1) [D loss: -21.575 R -99.906 F 71.208 G 0.712][G loss: -76.995]  0:16:21.949254
2200 (5, 1) [D loss: -21.387 R -105.764 F 74.625 G 0.975][G loss: -94.644]  0:16:22.776160
2201 (5, 1) [D loss: -25.687 R -101.636 F 65.820 G 1.013][G loss: -97.253]  0:16:23.602561
2202 (5, 1) [D loss: -20.085 R -108.883 F 78.897 G 0.990][G loss: -93.903]  0:16:24.421483
2203 (5, 1) [D loss: -23.906 R -111.691 F 79.370 G 0.842][G loss: -88.361]  0:16:25.235122
2204 (5, 1) [D loss: -28.487 R -135.180 F 100.458 G 0.624][G loss: -120.739]  0:16:26.033147
2205 (5, 1) [D loss: -22.122 R -116.789 F 85.772 G 0.889][G loss: -99.615]  0:16:26.837923
2206 (5, 1) [D loss: -24.927 R -130.574 F 98.718 G 0.693][G loss: -96.706]  0:16:27.635052
2207 (5, 1) [D loss: -24.345 R -128.312 F 95.877 G 0.809][G loss: -103.815]  0:16:28.435539
2208 (5, 1) [D loss: -23.584 R -129.357 F 98.555 G 0.722][G loss: -93.657]  0:16:29.235846
2209 (5, 1) [D loss: -20.805 R -137.213 F 110.329 G 0.608][G loss: -109.818]  0:16:30.042342
2210 (5, 1) [D loss: -19.799 R -140.735 F 116.512 G 0.442][G loss: -111.360]  0:16:30.858268
2211 (5, 1) [D loss: -18.802 R -137.223 F 113.270 G 0.515][G loss: -114.859]  0:16:31.668829
2212 (5, 1) [D loss: -22.243 R -134.841 F 106.252 G 0.635][G loss: -110.960]  0:16:32.477418
2213 (5, 1) [D loss: -18.817 R -121.689 F 97.287 G 0.559][G loss: -91.364]  0:16:33.288156
2214 (5, 1) [D loss: -19.660 R -118.724 F 94.551 G 0.451][G loss: -87.540]  0:16:34.097588
2215 (5, 1) [D loss: -21.012 R -116.370 F 92.089 G 0.327][G loss: -94.266]  0:16:34.907590
2216 (5, 1) [D loss: -17.440 R -129.073 F 102.757 G 0.888][G loss: -103.206]  0:16:35.717433
2217 (5, 1) [D loss: -26.753 R -122.113 F 88.693 G 0.667][G loss: -89.931]  0:16:36.518675
2218 (5, 1) [D loss: -22.273 R -122.520 F 94.734 G 0.551][G loss: -90.870]  0:16:37.320889
2219 (5, 1) [D loss: -12.938 R -118.402 F 100.517 G 0.495][G loss: -99.358]  0:16:38.137923
2220 (5, 1) [D loss: -19.927 R -113.338 F 89.084 G 0.433][G loss: -91.193]  0:16:38.943420
2221 (5, 1) [D loss: -20.906 R -125.853 F 100.194 G 0.475][G loss: -97.265]  0:16:39.750944
2222 (5, 1) [D loss: -29.347 R -139.416 F 97.386 G 1.268][G loss: -106.255]  0:16:40.558326
2223 (5, 1) [D loss: -18.466 R -114.702 F 93.618 G 0.262][G loss: -93.722]  0:16:41.356512
2224 (5, 1) [D loss: -14.546 R -99.715 F 79.786 G 0.538][G loss: -86.516]  0:16:42.181049
2225 (5, 1) [D loss: -19.744 R -110.140 F 85.801 G 0.460][G loss: -89.135]  0:16:42.985630
2226 (5, 1) [D loss: -26.817 R -112.718 F 81.049 G 0.485][G loss: -83.452]  0:16:43.797269
2227 (5, 1) [D loss: -27.141 R -113.088 F 76.427 G 0.952][G loss: -87.852]  0:16:44.605004
2228 (5, 1) [D loss: -23.175 R -94.001 F 68.098 G 0.273][G loss: -68.221]  0:16:45.406578
2229 (5, 1) [D loss: -21.553 R -103.300 F 77.414 G 0.433][G loss: -76.205]  0:16:46.221258
2230 (5, 1) [D loss: -20.018 R -103.573 F 78.472 G 0.508][G loss: -82.635]  0:16:47.025880
2231 (5, 1) [D loss: -26.511 R -95.659 F 63.481 G 0.567][G loss: -72.258]  0:16:47.833218
2232 (5, 1) [D loss: -14.302 R -87.215 F 68.094 G 0.482][G loss: -73.996]  0:16:48.629617
2233 (5, 1) [D loss: -17.243 R -77.987 F 56.466 G 0.428][G loss: -57.778]  0:16:49.426175
2234 (5, 1) [D loss: -19.870 R -80.413 F 55.954 G 0.459][G loss: -57.349]  0:16:50.225697
2235 (5, 1) [D loss: -20.778 R -79.360 F 54.298 G 0.428][G loss: -57.288]  0:16:51.024400
2236 (5, 1) [D loss: -12.903 R -79.330 F 61.238 G 0.519][G loss: -56.528]  0:16:51.830772
2237 (5, 1) [D loss: -19.614 R -76.786 F 53.363 G 0.381][G loss: -51.992]  0:16:52.631582
2238 (5, 1) [D loss: -16.197 R -72.919 F 50.978 G 0.574][G loss: -49.658]  0:16:53.445979
2239 (5, 1) [D loss: -14.550 R -77.548 F 58.205 G 0.479][G loss: -49.216]  0:16:54.247297
2240 (5, 1) [D loss: -18.788 R -78.967 F 56.510 G 0.367][G loss: -54.658]  0:16:55.053258
2241 (5, 1) [D loss: -19.024 R -75.933 F 50.565 G 0.634][G loss: -58.331]  0:16:55.879997
2242 (5, 1) [D loss: -19.456 R -88.796 F 65.917 G 0.342][G loss: -63.238]  0:16:56.695623
2243 (5, 1) [D loss: -20.578 R -80.998 F 53.475 G 0.695][G loss: -61.519]  0:16:57.510819
2244 (5, 1) [D loss: -18.857 R -92.464 F 70.593 G 0.301][G loss: -73.844]  0:16:58.326155
2245 (5, 1) [D loss: -15.786 R -93.889 F 74.683 G 0.342][G loss: -75.104]  0:16:59.128409
2246 (5, 1) [D loss: -21.747 R -99.302 F 74.118 G 0.344][G loss: -73.296]  0:16:59.934421
2247 (5, 1) [D loss: -18.929 R -93.236 F 70.917 G 0.339][G loss: -69.889]  0:17:00.734517
2248 (5, 1) [D loss: -21.940 R -95.188 F 67.404 G 0.584][G loss: -61.329]  0:17:01.550829
2249 (5, 1) [D loss: -5.820 R -84.717 F 69.544 G 0.935][G loss: -71.140]  0:17:02.348496
2250 (5, 1) [D loss: -17.989 R -102.176 F 81.295 G 0.289][G loss: -79.485]  0:17:03.183099
2251 (5, 1) [D loss: -22.368 R -96.278 F 67.235 G 0.667][G loss: -76.950]  0:17:03.995207
2252 (5, 1) [D loss: -21.962 R -104.220 F 77.889 G 0.437][G loss: -81.495]  0:17:04.798815
2253 (5, 1) [D loss: -16.190 R -104.080 F 82.572 G 0.532][G loss: -87.309]  0:17:05.615220
2254 (5, 1) [D loss: -21.144 R -117.882 F 92.666 G 0.407][G loss: -93.814]  0:17:06.424834
2255 (5, 1) [D loss: -20.045 R -116.873 F 92.806 G 0.402][G loss: -90.302]  0:17:07.226745
2256 (5, 1) [D loss: -20.434 R -108.424 F 83.391 G 0.460][G loss: -85.607]  0:17:08.041733
2257 (5, 1) [D loss: -17.737 R -105.711 F 81.300 G 0.667][G loss: -90.496]  0:17:08.845704
2258 (5, 1) [D loss: -28.714 R -112.423 F 77.214 G 0.650][G loss: -93.502]  0:17:09.676403
2259 (5, 1) [D loss: -22.821 R -109.409 F 82.435 G 0.415][G loss: -94.332]  0:17:10.489416
2260 (5, 1) [D loss: -11.720 R -106.059 F 91.109 G 0.323][G loss: -92.217]  0:17:11.290285
2261 (5, 1) [D loss: -19.062 R -125.006 F 100.882 G 0.506][G loss: -97.565]  0:17:12.105319
2262 (5, 1) [D loss: -17.092 R -108.448 F 87.661 G 0.370][G loss: -87.136]  0:17:12.909348
2263 (5, 1) [D loss: -17.021 R -119.989 F 98.636 G 0.433][G loss: -95.015]  0:17:13.722504
2264 (5, 1) [D loss: -12.898 R -117.052 F 100.089 G 0.406][G loss: -94.566]  0:17:14.523553
2265 (5, 1) [D loss: -18.664 R -111.001 F 88.991 G 0.335][G loss: -92.885]  0:17:15.318019
2266 (5, 1) [D loss: -19.167 R -114.246 F 91.026 G 0.405][G loss: -94.292]  0:17:16.129386
2267 (5, 1) [D loss: -21.604 R -124.263 F 97.484 G 0.517][G loss: -96.925]  0:17:16.936377
2268 (5, 1) [D loss: -18.802 R -91.332 F 68.719 G 0.381][G loss: -69.526]  0:17:17.740630
2269 (5, 1) [D loss: -15.925 R -103.156 F 83.129 G 0.410][G loss: -77.659]  0:17:18.550470
2270 (5, 1) [D loss: -16.742 R -95.876 F 73.136 G 0.600][G loss: -80.471]  0:17:19.356401
2271 (5, 1) [D loss: -16.682 R -97.528 F 77.547 G 0.330][G loss: -77.223]  0:17:20.157311
2272 (5, 1) [D loss: -18.717 R -89.412 F 66.522 G 0.417][G loss: -73.912]  0:17:20.961932
2273 (5, 1) [D loss: -16.841 R -89.755 F 68.856 G 0.406][G loss: -75.622]  0:17:21.761258
2274 (5, 1) [D loss: -17.273 R -99.796 F 77.441 G 0.508][G loss: -75.556]  0:17:22.564514
2275 (5, 1) [D loss: -15.578 R -87.579 F 67.529 G 0.447][G loss: -62.404]  0:17:23.370525
2276 (5, 1) [D loss: -17.097 R -87.382 F 66.245 G 0.404][G loss: -64.657]  0:17:24.177630
2277 (5, 1) [D loss: -13.591 R -77.307 F 56.448 G 0.727][G loss: -67.156]  0:17:24.978638
2278 (5, 1) [D loss: -19.404 R -86.192 F 62.332 G 0.446][G loss: -66.784]  0:17:25.782549
2279 (5, 1) [D loss: -16.532 R -87.409 F 67.844 G 0.303][G loss: -67.030]  0:17:26.588506
2280 (5, 1) [D loss: -18.223 R -79.410 F 56.794 G 0.439][G loss: -54.248]  0:17:27.388228
2281 (5, 1) [D loss: -17.642 R -78.293 F 54.810 G 0.584][G loss: -53.771]  0:17:28.185035
2282 (5, 1) [D loss: -18.135 R -85.556 F 64.239 G 0.318][G loss: -61.690]  0:17:29.010669
2283 (5, 1) [D loss: -21.225 R -82.977 F 57.957 G 0.379][G loss: -59.910]  0:17:29.816660
2284 (5, 1) [D loss: -17.547 R -82.640 F 61.385 G 0.371][G loss: -59.383]  0:17:30.621743
2285 (5, 1) [D loss: -17.746 R -76.168 F 53.910 G 0.451][G loss: -52.187]  0:17:31.426688
2286 (5, 1) [D loss: -17.772 R -84.372 F 63.081 G 0.352][G loss: -62.099]  0:17:32.234866
2287 (5, 1) [D loss: -17.832 R -77.472 F 55.383 G 0.426][G loss: -61.043]  0:17:33.039523
2288 (5, 1) [D loss: -15.626 R -77.226 F 58.263 G 0.334][G loss: -54.249]  0:17:33.849985
2289 (5, 1) [D loss: -11.247 R -74.906 F 57.623 G 0.604][G loss: -56.873]  0:17:34.652235
2290 (5, 1) [D loss: -26.255 R -83.675 F 50.961 G 0.646][G loss: -59.795]  0:17:35.454730
2291 (5, 1) [D loss: -16.229 R -76.564 F 57.169 G 0.317][G loss: -56.608]  0:17:36.253661
2292 (5, 1) [D loss: -19.299 R -80.986 F 57.765 G 0.392][G loss: -59.542]  0:17:37.051810
2293 (5, 1) [D loss: -17.794 R -71.588 F 50.550 G 0.324][G loss: -51.384]  0:17:37.854738
2294 (5, 1) [D loss: -16.772 R -71.421 F 50.472 G 0.418][G loss: -58.642]  0:17:38.654644
2295 (5, 1) [D loss: -15.644 R -73.181 F 52.870 G 0.467][G loss: -54.698]  0:17:39.467767
2296 (5, 1) [D loss: -21.507 R -84.061 F 57.546 G 0.501][G loss: -66.977]  0:17:40.266154
2297 (5, 1) [D loss: -22.592 R -77.575 F 50.850 G 0.413][G loss: -58.541]  0:17:41.079170
2298 (5, 1) [D loss: -18.362 R -85.021 F 62.407 G 0.425][G loss: -65.172]  0:17:41.875581
2299 (5, 1) [D loss: -18.094 R -87.128 F 65.288 G 0.375][G loss: -71.074]  0:17:42.673678
2300 (5, 1) [D loss: -15.962 R -97.188 F 75.419 G 0.581][G loss: -77.211]  0:17:43.493464
2301 (5, 1) [D loss: -27.472 R -102.545 F 69.393 G 0.568][G loss: -86.859]  0:17:44.290770
2302 (5, 1) [D loss: -20.712 R -92.286 F 69.130 G 0.244][G loss: -74.000]  0:17:45.096258
2303 (5, 1) [D loss: -19.403 R -100.598 F 76.513 G 0.468][G loss: -80.192]  0:17:45.911505
2304 (5, 1) [D loss: -19.353 R -92.608 F 69.701 G 0.355][G loss: -72.538]  0:17:46.710147
2305 (5, 1) [D loss: -18.971 R -95.097 F 72.351 G 0.378][G loss: -68.634]  0:17:47.510166
2306 (5, 1) [D loss: -16.204 R -88.326 F 66.788 G 0.533][G loss: -64.763]  0:17:48.314628
2307 (5, 1) [D loss: -18.167 R -95.505 F 72.867 G 0.447][G loss: -72.091]  0:17:49.119627
2308 (5, 1) [D loss: -16.570 R -95.416 F 73.239 G 0.561][G loss: -74.195]  0:17:49.917778
2309 (5, 1) [D loss: -19.234 R -96.862 F 73.392 G 0.424][G loss: -81.197]  0:17:50.731475
2310 (5, 1) [D loss: -17.843 R -94.151 F 72.313 G 0.400][G loss: -72.790]  0:17:51.539707
2311 (5, 1) [D loss: -21.921 R -92.246 F 62.441 G 0.788][G loss: -57.012]  0:17:52.357837
2312 (5, 1) [D loss: -7.647 R -92.796 F 81.421 G 0.373][G loss: -72.246]  0:17:53.153286
2313 (5, 1) [D loss: -13.557 R -97.152 F 79.966 G 0.363][G loss: -75.683]  0:17:53.968277
2314 (5, 1) [D loss: -17.095 R -88.393 F 67.023 G 0.428][G loss: -64.246]  0:17:54.783634
2315 (5, 1) [D loss: -23.087 R -87.719 F 58.831 G 0.580][G loss: -64.501]  0:17:55.586612
2316 (5, 1) [D loss: -22.048 R -93.469 F 67.163 G 0.426][G loss: -68.723]  0:17:56.402325
2317 (5, 1) [D loss: -20.987 R -87.698 F 60.135 G 0.658][G loss: -69.143]  0:17:57.210025
2318 (5, 1) [D loss: -20.752 R -101.203 F 76.293 G 0.416][G loss: -77.324]  0:17:58.010361
2319 (5, 1) [D loss: -19.293 R -83.518 F 54.215 G 1.001][G loss: -60.776]  0:17:58.824344
2320 (5, 1) [D loss: -22.839 R -81.239 F 53.955 G 0.444][G loss: -60.204]  0:17:59.628866
2321 (5, 1) [D loss: -13.882 R -78.001 F 58.742 G 0.538][G loss: -59.800]  0:18:00.428048
2322 (5, 1) [D loss: -22.015 R -77.806 F 49.797 G 0.599][G loss: -56.635]  0:18:01.242893
2323 (5, 1) [D loss: -15.417 R -74.093 F 54.590 G 0.409][G loss: -58.500]  0:18:02.065728
2324 (5, 1) [D loss: -14.831 R -67.021 F 44.430 G 0.776][G loss: -54.576]  0:18:02.897494
2325 (5, 1) [D loss: -19.547 R -66.718 F 43.418 G 0.375][G loss: -56.013]  0:18:03.704347
2326 (5, 1) [D loss: -17.995 R -83.737 F 60.598 G 0.514][G loss: -68.338]  0:18:04.506033
2327 (5, 1) [D loss: -16.473 R -90.058 F 70.329 G 0.325][G loss: -75.720]  0:18:05.307005
2328 (5, 1) [D loss: -21.268 R -88.468 F 62.444 G 0.476][G loss: -72.338]  0:18:06.118229
2329 (5, 1) [D loss: -20.077 R -100.582 F 76.782 G 0.372][G loss: -77.919]  0:18:06.920005
2330 (5, 1) [D loss: 1.057 R -78.521 F 74.383 G 0.519][G loss: -62.831]  0:18:07.728597
2331 (5, 1) [D loss: -23.058 R -86.262 F 59.414 G 0.379][G loss: -70.535]  0:18:08.532433
2332 (5, 1) [D loss: -19.337 R -94.582 F 69.059 G 0.619][G loss: -83.185]  0:18:09.336725
2333 (5, 1) [D loss: -17.437 R -101.435 F 79.943 G 0.406][G loss: -89.642]  0:18:10.150223
2334 (5, 1) [D loss: -16.951 R -108.205 F 86.276 G 0.498][G loss: -83.471]  0:18:10.952821
2335 (5, 1) [D loss: -17.529 R -103.741 F 82.442 G 0.377][G loss: -80.414]  0:18:11.766587
2336 (5, 1) [D loss: -17.482 R -113.260 F 90.664 G 0.511][G loss: -81.487]  0:18:12.572779
2337 (5, 1) [D loss: -18.346 R -99.731 F 77.273 G 0.411][G loss: -75.650]  0:18:13.374078
2338 (5, 1) [D loss: -17.926 R -89.423 F 67.765 G 0.373][G loss: -67.790]  0:18:14.179605
2339 (5, 1) [D loss: -15.918 R -88.102 F 68.313 G 0.387][G loss: -72.232]  0:18:14.986073
2340 (5, 1) [D loss: -18.746 R -92.376 F 69.609 G 0.402][G loss: -74.349]  0:18:15.793158
2341 (5, 1) [D loss: -20.734 R -96.146 F 71.518 G 0.389][G loss: -73.732]  0:18:16.609064
2342 (5, 1) [D loss: -18.110 R -102.652 F 80.444 G 0.410][G loss: -80.203]  0:18:17.411888
2343 (5, 1) [D loss: -15.875 R -98.687 F 78.636 G 0.418][G loss: -74.970]  0:18:18.224509
2344 (5, 1) [D loss: -17.802 R -103.881 F 81.368 G 0.471][G loss: -76.817]  0:18:19.028656
2345 (5, 1) [D loss: -17.608 R -100.514 F 77.448 G 0.546][G loss: -75.262]  0:18:19.831378
2346 (5, 1) [D loss: -17.668 R -84.523 F 62.781 G 0.407][G loss: -64.371]  0:18:20.636514
2347 (5, 1) [D loss: -17.951 R -89.957 F 68.019 G 0.399][G loss: -68.402]  0:18:21.452976
2348 (5, 1) [D loss: -15.505 R -96.250 F 76.112 G 0.463][G loss: -75.894]  0:18:22.267133
2349 (5, 1) [D loss: -16.485 R -84.467 F 63.585 G 0.440][G loss: -61.992]  0:18:23.064347
2350 (5, 1) [D loss: -20.704 R -97.981 F 70.904 G 0.637][G loss: -69.781]  0:18:23.878752
2351 (5, 1) [D loss: -18.460 R -96.104 F 71.029 G 0.662][G loss: -75.823]  0:18:24.691607
2352 (5, 1) [D loss: -19.337 R -91.733 F 67.801 G 0.460][G loss: -72.606]  0:18:25.507603
2353 (5, 1) [D loss: -23.290 R -89.566 F 61.309 G 0.497][G loss: -64.866]  0:18:26.326669
2354 (5, 1) [D loss: -19.819 R -90.904 F 67.236 G 0.385][G loss: -76.193]  0:18:27.146926
2355 (5, 1) [D loss: -18.480 R -97.593 F 75.006 G 0.411][G loss: -81.173]  0:18:27.940447
2356 (5, 1) [D loss: -19.091 R -84.257 F 61.300 G 0.387][G loss: -70.489]  0:18:28.749936
2357 (5, 1) [D loss: -17.853 R -104.128 F 79.807 G 0.647][G loss: -85.883]  0:18:29.561769
2358 (5, 1) [D loss: -18.582 R -94.831 F 71.360 G 0.489][G loss: -80.267]  0:18:30.362537
2359 (5, 1) [D loss: -29.354 R -101.379 F 63.793 G 0.823][G loss: -81.183]  0:18:31.172054
2360 (5, 1) [D loss: -29.834 R -95.174 F 59.867 G 0.547][G loss: -83.652]  0:18:31.973678
2361 (5, 1) [D loss: -32.644 R -111.899 F 73.809 G 0.545][G loss: -93.664]  0:18:32.779703
2362 (5, 1) [D loss: -25.524 R -103.115 F 71.845 G 0.575][G loss: -88.503]  0:18:33.601590
2363 (5, 1) [D loss: -30.963 R -108.800 F 72.795 G 0.504][G loss: -86.074]  0:18:34.402590
2364 (5, 1) [D loss: -17.857 R -100.069 F 80.133 G 0.208][G loss: -90.708]  0:18:35.218071
2365 (5, 1) [D loss: -15.424 R -105.395 F 83.660 G 0.631][G loss: -95.305]  0:18:36.021872
2366 (5, 1) [D loss: -18.499 R -108.992 F 86.588 G 0.390][G loss: -92.234]  0:18:36.820538
2367 (5, 1) [D loss: -19.001 R -110.407 F 85.591 G 0.582][G loss: -84.281]  0:18:37.645407
2368 (5, 1) [D loss: -10.086 R -102.280 F 86.830 G 0.536][G loss: -88.421]  0:18:38.459956
2369 (5, 1) [D loss: -19.275 R -107.518 F 83.984 G 0.426][G loss: -78.839]  0:18:39.257689
2370 (5, 1) [D loss: -19.805 R -103.329 F 78.591 G 0.493][G loss: -81.900]  0:18:40.059292
2371 (5, 1) [D loss: -13.801 R -94.888 F 75.993 G 0.509][G loss: -76.563]  0:18:40.853290
2372 (5, 1) [D loss: -15.509 R -100.718 F 80.837 G 0.437][G loss: -69.807]  0:18:41.668379
2373 (5, 1) [D loss: -10.147 R -92.510 F 76.667 G 0.570][G loss: -69.076]  0:18:42.469909
2374 (5, 1) [D loss: -19.641 R -75.986 F 52.329 G 0.401][G loss: -52.304]  0:18:43.272566
2375 (5, 1) [D loss: -14.926 R -82.766 F 61.636 G 0.620][G loss: -60.907]  0:18:44.081695
2376 (5, 1) [D loss: -10.085 R -80.195 F 65.068 G 0.504][G loss: -57.696]  0:18:44.884557
2377 (5, 1) [D loss: -28.685 R -88.745 F 48.910 G 1.115][G loss: -43.837]  0:18:45.693569
2378 (5, 1) [D loss: -18.318 R -89.501 F 67.675 G 0.351][G loss: -66.523]  0:18:46.493571
2379 (5, 1) [D loss: -17.999 R -83.813 F 61.797 G 0.402][G loss: -58.716]  0:18:47.301055
2380 (5, 1) [D loss: -22.800 R -85.731 F 58.070 G 0.486][G loss: -59.577]  0:18:48.116781
2381 (5, 1) [D loss: -26.578 R -84.237 F 51.784 G 0.587][G loss: -56.628]  0:18:48.942777
2382 (5, 1) [D loss: -19.720 R -73.551 F 48.553 G 0.528][G loss: -55.472]  0:18:49.755346
2383 (5, 1) [D loss: -23.214 R -69.993 F 41.219 G 0.556][G loss: -51.454]  0:18:50.565657
2384 (5, 1) [D loss: -24.281 R -75.368 F 45.858 G 0.523][G loss: -53.601]  0:18:51.365767
2385 (5, 1) [D loss: -30.412 R -72.664 F 34.991 G 0.726][G loss: -40.055]  0:18:52.171076
2386 (5, 1) [D loss: -23.989 R -73.392 F 44.166 G 0.524][G loss: -53.260]  0:18:52.988696
2387 (5, 1) [D loss: -21.122 R -70.929 F 45.072 G 0.474][G loss: -51.856]  0:18:53.786916
2388 (5, 1) [D loss: -22.816 R -61.648 F 34.806 G 0.403][G loss: -43.212]  0:18:54.586258
2389 (5, 1) [D loss: -22.645 R -64.205 F 36.916 G 0.464][G loss: -49.272]  0:18:55.397199
2390 (5, 1) [D loss: -20.472 R -69.247 F 41.203 G 0.757][G loss: -58.403]  0:18:56.195337
2391 (5, 1) [D loss: -18.238 R -60.803 F 35.510 G 0.705][G loss: -60.265]  0:18:56.998032
2392 (5, 1) [D loss: -13.880 R -72.910 F 53.590 G 0.544][G loss: -65.603]  0:18:57.818413
2393 (5, 1) [D loss: -19.034 R -72.338 F 47.163 G 0.614][G loss: -66.895]  0:18:58.623176
2394 (5, 1) [D loss: -23.935 R -73.467 F 44.530 G 0.500][G loss: -62.889]  0:18:59.433948
2395 (5, 1) [D loss: -29.565 R -85.802 F 48.174 G 0.806][G loss: -67.158]  0:19:00.235143
2396 (5, 1) [D loss: -17.219 R -87.332 F 65.730 G 0.438][G loss: -74.527]  0:19:01.035855
2397 (5, 1) [D loss: -16.537 R -90.006 F 66.562 G 0.691][G loss: -76.954]  0:19:01.840594
2398 (5, 1) [D loss: -20.445 R -86.844 F 62.637 G 0.376][G loss: -77.154]  0:19:02.650473
2399 (5, 1) [D loss: -24.281 R -81.894 F 50.546 G 0.707][G loss: -75.749]  0:19:03.491800
2400 (5, 1) [D loss: -13.181 R -77.047 F 59.208 G 0.466][G loss: -56.997]  0:19:04.288656
2401 (5, 1) [D loss: -15.659 R -82.706 F 63.363 G 0.368][G loss: -62.480]  0:19:05.103520
2402 (5, 1) [D loss: -19.581 R -86.549 F 63.199 G 0.377][G loss: -71.434]  0:19:05.899697
2403 (5, 1) [D loss: -18.882 R -82.897 F 59.944 G 0.407][G loss: -68.744]  0:19:06.703572
2404 (5, 1) [D loss: -15.333 R -80.828 F 61.196 G 0.430][G loss: -60.787]  0:19:07.508389
2405 (5, 1) [D loss: -19.112 R -84.968 F 60.929 G 0.493][G loss: -60.105]  0:19:08.340587
2406 (5, 1) [D loss: -19.069 R -84.173 F 60.714 G 0.439][G loss: -57.310]  0:19:09.193565
2407 (5, 1) [D loss: -18.021 R -80.657 F 58.107 G 0.453][G loss: -58.371]  0:19:09.998693
2408 (5, 1) [D loss: -15.641 R -78.122 F 57.678 G 0.480][G loss: -61.087]  0:19:10.794044
2409 (5, 1) [D loss: -17.486 R -88.552 F 65.961 G 0.511][G loss: -63.111]  0:19:11.607837
2410 (5, 1) [D loss: -19.461 R -89.102 F 64.339 G 0.530][G loss: -60.080]  0:19:12.413145
2411 (5, 1) [D loss: -22.849 R -84.095 F 56.861 G 0.439][G loss: -49.507]  0:19:13.233643
2412 (5, 1) [D loss: -21.107 R -82.494 F 55.852 G 0.554][G loss: -51.244]  0:19:14.040308
2413 (5, 1) [D loss: -20.298 R -78.970 F 53.188 G 0.548][G loss: -51.473]  0:19:14.848801
2414 (5, 1) [D loss: -16.537 R -80.756 F 57.811 G 0.641][G loss: -53.321]  0:19:15.667291
2415 (5, 1) [D loss: -26.302 R -95.794 F 62.503 G 0.699][G loss: -63.715]  0:19:16.465472
2416 (5, 1) [D loss: -27.455 R -79.458 F 46.685 G 0.532][G loss: -58.473]  0:19:17.274539
2417 (5, 1) [D loss: -29.681 R -92.190 F 57.199 G 0.531][G loss: -60.004]  0:19:18.077329
2418 (5, 1) [D loss: -22.419 R -89.653 F 60.830 G 0.640][G loss: -56.088]  0:19:18.879869
2419 (5, 1) [D loss: -28.330 R -83.703 F 49.159 G 0.621][G loss: -63.669]  0:19:19.687881
2420 (5, 1) [D loss: -18.218 R -67.432 F 45.093 G 0.412][G loss: -57.798]  0:19:20.496675
2421 (5, 1) [D loss: -23.899 R -79.083 F 49.992 G 0.519][G loss: -59.201]  0:19:21.299523
2422 (5, 1) [D loss: -23.113 R -76.983 F 47.531 G 0.634][G loss: -58.161]  0:19:22.100041
2423 (5, 1) [D loss: -28.678 R -90.840 F 56.119 G 0.604][G loss: -69.253]  0:19:22.921342
2424 (5, 1) [D loss: -28.453 R -78.195 F 44.441 G 0.530][G loss: -62.206]  0:19:23.725808
2425 (5, 1) [D loss: -21.717 R -78.427 F 47.889 G 0.882][G loss: -59.816]  0:19:24.531533
2426 (5, 1) [D loss: -8.239 R -58.902 F 38.979 G 1.168][G loss: -52.696]  0:19:25.338582
2427 (5, 1) [D loss: -29.716 R -81.067 F 42.444 G 0.891][G loss: -58.819]  0:19:26.137974
2428 (5, 1) [D loss: -23.353 R -81.012 F 54.046 G 0.361][G loss: -72.874]  0:19:26.935753
2429 (5, 1) [D loss: -19.587 R -87.646 F 61.362 G 0.670][G loss: -81.206]  0:19:27.736478
2430 (5, 1) [D loss: -21.668 R -85.960 F 60.239 G 0.405][G loss: -77.810]  0:19:28.538271
2431 (5, 1) [D loss: -28.761 R -81.513 F 43.518 G 0.923][G loss: -78.070]  0:19:29.344376
2432 (5, 1) [D loss: -17.098 R -71.953 F 51.784 G 0.307][G loss: -68.356]  0:19:30.170555
2433 (5, 1) [D loss: -19.221 R -80.401 F 54.705 G 0.647][G loss: -73.717]  0:19:30.985744
2434 (5, 1) [D loss: -15.158 R -67.774 F 44.871 G 0.775][G loss: -62.697]  0:19:31.785761
2435 (5, 1) [D loss: -18.651 R -87.901 F 65.181 G 0.407][G loss: -81.099]  0:19:32.582866
2436 (5, 1) [D loss: -22.396 R -83.600 F 54.141 G 0.706][G loss: -68.612]  0:19:33.388796
2437 (5, 1) [D loss: -23.860 R -92.176 F 62.682 G 0.563][G loss: -78.628]  0:19:34.223781
2438 (5, 1) [D loss: -20.029 R -88.776 F 63.339 G 0.541][G loss: -51.828]  0:19:35.025397
2439 (5, 1) [D loss: -19.838 R -89.013 F 64.691 G 0.448][G loss: -68.105]  0:19:35.862319
2440 (5, 1) [D loss: -16.844 R -87.018 F 66.602 G 0.357][G loss: -64.671]  0:19:36.683403
2441 (5, 1) [D loss: -21.003 R -94.653 F 68.417 G 0.523][G loss: -68.906]  0:19:37.485642
2442 (5, 1) [D loss: -20.840 R -82.148 F 53.893 G 0.742][G loss: -42.131]  0:19:38.294915
2443 (5, 1) [D loss: -17.232 R -81.681 F 60.521 G 0.393][G loss: -52.092]  0:19:39.102665
2444 (5, 1) [D loss: -18.712 R -81.536 F 57.911 G 0.491][G loss: -57.232]  0:19:39.925538
2445 (5, 1) [D loss: -17.616 R -84.658 F 61.847 G 0.519][G loss: -55.172]  0:19:40.731999
2446 (5, 1) [D loss: -24.211 R -92.622 F 63.197 G 0.521][G loss: -61.698]  0:19:41.553340
2447 (5, 1) [D loss: -20.556 R -78.798 F 48.729 G 0.951][G loss: -53.019]  0:19:42.353049
2448 (5, 1) [D loss: -17.931 R -85.088 F 57.738 G 0.942][G loss: -66.910]  0:19:43.170745
2449 (5, 1) [D loss: -24.354 R -97.785 F 68.442 G 0.499][G loss: -68.871]  0:19:43.984332
2450 (5, 1) [D loss: -28.372 R -85.304 F 49.695 G 0.724][G loss: -59.271]  0:19:44.781505
2451 (5, 1) [D loss: -33.360 R -89.211 F 50.857 G 0.499][G loss: -69.048]  0:19:45.596244
2452 (5, 1) [D loss: -26.293 R -93.182 F 59.483 G 0.741][G loss: -76.104]  0:19:46.399078
2453 (5, 1) [D loss: -12.312 R -81.892 F 62.199 G 0.738][G loss: -68.540]  0:19:47.202797
2454 (5, 1) [D loss: -16.945 R -91.561 F 70.438 G 0.418][G loss: -77.047]  0:19:48.012507
2455 (5, 1) [D loss: -26.253 R -86.023 F 53.230 G 0.654][G loss: -65.970]  0:19:48.815849
2456 (5, 1) [D loss: -26.562 R -94.869 F 63.088 G 0.522][G loss: -77.029]  0:19:49.633255
2457 (5, 1) [D loss: -20.176 R -77.083 F 48.685 G 0.822][G loss: -54.058]  0:19:50.440366
2458 (5, 1) [D loss: -17.135 R -87.957 F 64.808 G 0.601][G loss: -71.296]  0:19:51.243447
2459 (5, 1) [D loss: -18.826 R -91.743 F 67.419 G 0.550][G loss: -69.465]  0:19:52.043121
2460 (5, 1) [D loss: -18.628 R -81.505 F 58.843 G 0.403][G loss: -60.598]  0:19:52.846277
2461 (5, 1) [D loss: -20.543 R -81.570 F 55.373 G 0.565][G loss: -58.903]  0:19:53.643874
2462 (5, 1) [D loss: -19.103 R -69.233 F 45.455 G 0.467][G loss: -53.211]  0:19:54.468517
2463 (5, 1) [D loss: -22.128 R -69.463 F 44.107 G 0.323][G loss: -48.851]  0:19:55.274239
2464 (5, 1) [D loss: -17.853 R -63.947 F 40.630 G 0.546][G loss: -46.695]  0:19:56.079490
2465 (5, 1) [D loss: -15.802 R -67.582 F 46.314 G 0.547][G loss: -46.478]  0:19:56.895499
2466 (5, 1) [D loss: -19.167 R -66.145 F 42.396 G 0.458][G loss: -49.984]  0:19:57.697887
2467 (5, 1) [D loss: -17.567 R -67.154 F 45.257 G 0.433][G loss: -49.830]  0:19:58.508478
2468 (5, 1) [D loss: -15.482 R -58.641 F 36.752 G 0.641][G loss: -43.515]  0:19:59.317913
2469 (5, 1) [D loss: -15.905 R -68.023 F 46.392 G 0.573][G loss: -54.398]  0:20:00.141506
2470 (5, 1) [D loss: -18.373 R -69.078 F 47.001 G 0.370][G loss: -54.591]  0:20:00.940504
2471 (5, 1) [D loss: -17.204 R -69.353 F 47.037 G 0.511][G loss: -51.162]  0:20:01.747279
2472 (5, 1) [D loss: -16.362 R -57.017 F 37.204 G 0.345][G loss: -45.865]  0:20:02.551654
2473 (5, 1) [D loss: -18.303 R -58.878 F 36.783 G 0.379][G loss: -45.777]  0:20:03.353356
2474 (5, 1) [D loss: -9.676 R -64.444 F 45.115 G 0.965][G loss: -47.141]  0:20:04.153009
2475 (5, 1) [D loss: -16.274 R -68.798 F 49.466 G 0.306][G loss: -54.083]  0:20:04.956598
2476 (5, 1) [D loss: -18.477 R -58.937 F 36.472 G 0.399][G loss: -39.336]  0:20:05.770245
2477 (5, 1) [D loss: -17.680 R -55.591 F 34.135 G 0.378][G loss: -41.048]  0:20:06.563565
2478 (5, 1) [D loss: -20.747 R -59.218 F 34.446 G 0.402][G loss: -37.206]  0:20:07.363019
2479 (5, 1) [D loss: -13.902 R -54.393 F 35.940 G 0.455][G loss: -35.841]  0:20:08.170418
2480 (5, 1) [D loss: -17.272 R -59.611 F 38.275 G 0.406][G loss: -41.723]  0:20:08.979646
2481 (5, 1) [D loss: -14.141 R -49.481 F 29.118 G 0.622][G loss: -44.325]  0:20:09.791676
2482 (5, 1) [D loss: -17.628 R -62.274 F 40.101 G 0.454][G loss: -37.814]  0:20:10.604314
2483 (5, 1) [D loss: -13.255 R -65.089 F 47.479 G 0.435][G loss: -34.479]  0:20:11.401060
2484 (5, 1) [D loss: -15.941 R -55.378 F 34.823 G 0.461][G loss: -31.667]  0:20:12.207875
2485 (5, 1) [D loss: -19.886 R -62.130 F 37.551 G 0.469][G loss: -34.025]  0:20:13.017859
2486 (5, 1) [D loss: -17.012 R -65.159 F 43.499 G 0.465][G loss: -42.669]  0:20:13.838156
2487 (5, 1) [D loss: -23.583 R -68.851 F 40.440 G 0.483][G loss: -38.358]  0:20:14.641668
2488 (5, 1) [D loss: -23.236 R -64.936 F 35.851 G 0.585][G loss: -37.385]  0:20:15.455307
2489 (5, 1) [D loss: -26.086 R -63.834 F 32.160 G 0.559][G loss: -33.314]  0:20:16.256270
2490 (5, 1) [D loss: -41.270 R -71.452 F 22.498 G 0.768][G loss: -28.060]  0:20:17.058447
2491 (5, 1) [D loss: -18.142 R -46.677 F 26.648 G 0.189][G loss: -34.483]  0:20:17.864779
2492 (5, 1) [D loss: -17.724 R -60.786 F 36.409 G 0.665][G loss: -40.404]  0:20:18.681576
2493 (5, 1) [D loss: -19.333 R -70.402 F 45.047 G 0.602][G loss: -43.544]  0:20:19.487159
2494 (5, 1) [D loss: -28.059 R -68.033 F 32.819 G 0.715][G loss: -50.330]  0:20:20.280512
2495 (5, 1) [D loss: -24.609 R -66.424 F 37.324 G 0.449][G loss: -50.686]  0:20:21.113364
2496 (5, 1) [D loss: -29.083 R -68.012 F 30.837 G 0.809][G loss: -52.496]  0:20:21.923980
2497 (5, 1) [D loss: -15.658 R -63.320 F 42.474 G 0.519][G loss: -51.671]  0:20:22.730851
2498 (5, 1) [D loss: -21.799 R -63.918 F 34.858 G 0.726][G loss: -52.555]  0:20:23.533973
2499 (5, 1) [D loss: -15.157 R -70.623 F 45.535 G 0.993][G loss: -44.255]  0:20:24.343780
2500 (5, 1) [D loss: -28.829 R -59.066 F 23.567 G 0.667][G loss: -51.123]  0:20:25.152374
2501 (5, 1) [D loss: -21.131 R -48.848 F 16.688 G 1.103][G loss: -49.742]  0:20:25.970757
2502 (5, 1) [D loss: -17.087 R -63.871 F 36.906 G 0.988][G loss: -61.981]  0:20:26.774625
2503 (5, 1) [D loss: -14.899 R -53.588 F 31.178 G 0.751][G loss: -64.051]  0:20:27.578963
2504 (5, 1) [D loss: -22.620 R -76.443 F 48.416 G 0.541][G loss: -77.482]  0:20:28.370659
2505 (5, 1) [D loss: -28.736 R -85.637 F 49.725 G 0.718][G loss: -79.709]  0:20:29.184826
2506 (5, 1) [D loss: -24.038 R -78.653 F 50.176 G 0.444][G loss: -76.433]  0:20:29.987714
2507 (5, 1) [D loss: -16.022 R -69.444 F 47.423 G 0.600][G loss: -69.824]  0:20:30.790431
2508 (5, 1) [D loss: -22.374 R -77.933 F 50.036 G 0.552][G loss: -66.182]  0:20:31.626750
2509 (5, 1) [D loss: -17.836 R -93.163 F 71.696 G 0.363][G loss: -70.937]  0:20:32.433557
2510 (5, 1) [D loss: -28.000 R -82.272 F 46.274 G 0.800][G loss: -73.057]  0:20:33.246365
2511 (5, 1) [D loss: -14.569 R -88.832 F 71.093 G 0.317][G loss: -72.239]  0:20:34.067409
2512 (5, 1) [D loss: -18.522 R -95.749 F 69.681 G 0.755][G loss: -68.957]  0:20:34.883544
2513 (5, 1) [D loss: -15.600 R -104.172 F 83.157 G 0.542][G loss: -73.250]  0:20:35.699878
2514 (5, 1) [D loss: -22.407 R -96.031 F 69.463 G 0.416][G loss: -62.989]  0:20:36.498470
2515 (5, 1) [D loss: -12.714 R -79.232 F 58.062 G 0.846][G loss: -48.447]  0:20:37.320012
2516 (5, 1) [D loss: -32.507 R -87.055 F 44.095 G 1.045][G loss: -24.316]  0:20:38.133882
2517 (5, 1) [D loss: -19.836 R -95.131 F 62.705 G 1.259][G loss: -52.858]  0:20:38.933400
2518 (5, 1) [D loss: -17.618 R -87.634 F 66.606 G 0.341][G loss: -62.941]  0:20:39.747519
2519 (5, 1) [D loss: -25.863 R -85.229 F 53.529 G 0.584][G loss: -51.458]  0:20:40.553943
2520 (5, 1) [D loss: -22.452 R -82.444 F 48.320 G 1.167][G loss: -55.609]  0:20:41.381782
2521 (5, 1) [D loss: -34.616 R -117.702 F 69.385 G 1.370][G loss: -81.036]  0:20:42.188970
2522 (5, 1) [D loss: -31.717 R -114.826 F 70.311 G 1.280][G loss: -88.967]  0:20:42.997248
2523 (5, 1) [D loss: -32.554 R -97.652 F 57.552 G 0.755][G loss: -71.376]  0:20:43.815395
2524 (5, 1) [D loss: -27.310 R -81.414 F 40.449 G 1.365][G loss: -66.349]  0:20:44.621831
2525 (5, 1) [D loss: -22.139 R -68.734 F 38.859 G 0.774][G loss: -50.658]  0:20:45.433685
2526 (5, 1) [D loss: -28.052 R -86.667 F 45.589 G 1.303][G loss: -60.103]  0:20:46.227976
2527 (5, 1) [D loss: -28.863 R -93.029 F 53.712 G 1.045][G loss: -70.774]  0:20:47.034927
2528 (5, 1) [D loss: -22.650 R -76.751 F 48.757 G 0.534][G loss: -51.292]  0:20:47.844672
2529 (5, 1) [D loss: -23.244 R -85.715 F 56.007 G 0.646][G loss: -67.689]  0:20:48.639799
2530 (5, 1) [D loss: -29.136 R -98.851 F 58.197 G 1.152][G loss: -73.786]  0:20:49.449802
2531 (5, 1) [D loss: -19.822 R -72.449 F 48.322 G 0.431][G loss: -57.915]  0:20:50.251680
2532 (5, 1) [D loss: -18.177 R -67.448 F 44.130 G 0.514][G loss: -69.720]  0:20:51.056834
2533 (5, 1) [D loss: -19.918 R -83.286 F 60.463 G 0.291][G loss: -72.397]  0:20:51.857479
2534 (5, 1) [D loss: -21.885 R -74.866 F 48.584 G 0.440][G loss: -59.807]  0:20:52.667309
2535 (5, 1) [D loss: -15.417 R -80.484 F 61.009 G 0.406][G loss: -76.486]  0:20:53.468614
2536 (5, 1) [D loss: -21.874 R -88.493 F 62.827 G 0.379][G loss: -71.348]  0:20:54.281483
2537 (5, 1) [D loss: -12.579 R -86.632 F 68.424 G 0.563][G loss: -66.637]  0:20:55.091295
2538 (5, 1) [D loss: -18.880 R -85.323 F 60.751 G 0.569][G loss: -72.251]  0:20:55.885605
2539 (5, 1) [D loss: -18.984 R -87.551 F 63.865 G 0.470][G loss: -79.432]  0:20:56.696629
2540 (5, 1) [D loss: -19.827 R -89.185 F 63.751 G 0.561][G loss: -76.821]  0:20:57.505627
2541 (5, 1) [D loss: -18.003 R -87.526 F 65.329 G 0.419][G loss: -72.404]  0:20:58.302780
2542 (5, 1) [D loss: -21.291 R -81.816 F 56.150 G 0.438][G loss: -67.743]  0:20:59.110026
2543 (5, 1) [D loss: -18.166 R -74.708 F 51.702 G 0.484][G loss: -56.845]  0:20:59.911503
2544 (5, 1) [D loss: -19.313 R -73.698 F 50.775 G 0.361][G loss: -61.244]  0:21:00.710164
2545 (5, 1) [D loss: -18.894 R -74.546 F 50.986 G 0.467][G loss: -56.199]  0:21:01.508514
2546 (5, 1) [D loss: -17.865 R -67.444 F 44.250 G 0.533][G loss: -53.517]  0:21:02.310555
2547 (5, 1) [D loss: -18.613 R -63.423 F 40.518 G 0.429][G loss: -45.703]  0:21:03.115867
2548 (5, 1) [D loss: -19.115 R -67.141 F 43.700 G 0.433][G loss: -52.123]  0:21:03.926119
2549 (5, 1) [D loss: -18.015 R -62.910 F 40.349 G 0.455][G loss: -39.714]  0:21:04.730306
2550 (5, 1) [D loss: -15.121 R -56.301 F 36.962 G 0.422][G loss: -40.791]  0:21:05.539873
2551 (5, 1) [D loss: -17.979 R -66.180 F 43.398 G 0.480][G loss: -46.286]  0:21:06.338068
2552 (5, 1) [D loss: -22.991 R -67.331 F 39.534 G 0.481][G loss: -37.453]  0:21:07.142551
2553 (5, 1) [D loss: -14.297 R -62.073 F 40.236 G 0.754][G loss: -32.399]  0:21:07.940480
2554 (5, 1) [D loss: -23.256 R -59.461 F 30.403 G 0.580][G loss: -30.085]  0:21:08.753704
2555 (5, 1) [D loss: -37.203 R -67.737 F 22.256 G 0.828][G loss: -31.816]  0:21:09.561715
2556 (5, 1) [D loss: -22.262 R -45.225 F 19.878 G 0.309][G loss: -29.316]  0:21:10.363477
2557 (5, 1) [D loss: -27.859 R -50.762 F 13.133 G 0.977][G loss: -14.253]  0:21:11.174318
2558 (5, 1) [D loss: -16.029 R -49.019 F 27.032 G 0.596][G loss: -30.629]  0:21:11.978266
2559 (5, 1) [D loss: -9.817 R -43.430 F 27.103 G 0.651][G loss: -24.457]  0:21:12.786863
2560 (5, 1) [D loss: -28.117 R -42.068 F 2.322 G 1.163][G loss: -16.179]  0:21:13.592499
2561 (5, 1) [D loss: -30.156 R -46.795 F 3.387 G 1.325][G loss: -20.129]  0:21:14.387763
2562 (5, 1) [D loss: -30.806 R -55.447 F 21.200 G 0.344][G loss: -53.374]  0:21:15.198357
2563 (5, 1) [D loss: -17.248 R -39.359 F 16.853 G 0.526][G loss: -32.960]  0:21:15.995412
2564 (5, 1) [D loss: -27.572 R -35.754 F -1.213 G 0.939][G loss: -40.327]  0:21:16.803883
2565 (5, 1) [D loss: -30.931 R -57.229 F 20.803 G 0.549][G loss: -46.981]  0:21:17.608545
2566 (5, 1) [D loss: -15.373 R -50.967 F 29.202 G 0.639][G loss: -59.400]  0:21:18.409876
2567 (5, 1) [D loss: -12.643 R -38.161 F 17.713 G 0.780][G loss: -48.687]  0:21:19.219701
2568 (5, 1) [D loss: -29.079 R -52.412 F 15.098 G 0.824][G loss: -52.826]  0:21:20.028325
2569 (5, 1) [D loss: -27.055 R -55.116 F 23.676 G 0.439][G loss: -59.532]  0:21:20.853793
2570 (5, 1) [D loss: -29.034 R -48.301 F 11.481 G 0.779][G loss: -54.092]  0:21:21.669855
2571 (5, 1) [D loss: -26.432 R -68.585 F 38.910 G 0.324][G loss: -60.013]  0:21:22.478917
2572 (5, 1) [D loss: -19.147 R -66.870 F 42.445 G 0.528][G loss: -57.293]  0:21:23.317097
2573 (5, 1) [D loss: -22.648 R -76.501 F 48.051 G 0.580][G loss: -66.859]  0:21:24.130285
2574 (5, 1) [D loss: -23.314 R -73.162 F 45.268 G 0.458][G loss: -41.142]  0:21:24.936519
2575 (5, 1) [D loss: -22.416 R -69.504 F 40.675 G 0.641][G loss: -43.605]  0:21:25.753894
2576 (5, 1) [D loss: -26.805 R -59.162 F 24.008 G 0.835][G loss: -1.824]  0:21:26.557782
2577 (5, 1) [D loss: -19.942 R -60.907 F 33.299 G 0.767][G loss: -54.868]  0:21:27.371387
2578 (5, 1) [D loss: -20.879 R -66.051 F 39.141 G 0.603][G loss: -20.558]  0:21:28.166981
2579 (5, 1) [D loss: -31.146 R -60.878 F 15.966 G 1.377][G loss: 12.364]  0:21:28.974928
2580 (5, 1) [D loss: -44.014 R -64.933 F 5.078 G 1.584][G loss: 20.498]  0:21:29.773595
2581 (5, 1) [D loss: -28.473 R -73.362 F 35.410 G 0.948][G loss: -18.060]  0:21:30.573221
2582 (5, 1) [D loss: -26.320 R -67.204 F 32.362 G 0.852][G loss: -29.387]  0:21:31.380368
2583 (5, 1) [D loss: -44.194 R -95.608 F 35.038 G 1.638][G loss: -35.155]  0:21:32.179847
2584 (5, 1) [D loss: -37.103 R -95.509 F 45.989 G 1.242][G loss: -53.348]  0:21:32.987152
2585 (5, 1) [D loss: -32.888 R -96.376 F 52.241 G 1.125][G loss: -62.642]  0:21:33.791662
2586 (5, 1) [D loss: -30.650 R -95.630 F 43.359 G 2.162][G loss: -69.962]  0:21:34.594621
2587 (5, 1) [D loss: -31.906 R -110.729 F 50.621 G 2.820][G loss: -78.431]  0:21:35.393869
2588 (5, 1) [D loss: -43.888 R -115.361 F 55.123 G 1.635][G loss: -100.468]  0:21:36.195097
2589 (5, 1) [D loss: -33.281 R -107.009 F 54.155 G 1.957][G loss: -86.701]  0:21:36.992728
2590 (5, 1) [D loss: -18.285 R -106.912 F 71.861 G 1.677][G loss: -85.893]  0:21:37.801323
2591 (5, 1) [D loss: -29.047 R -86.046 F 43.870 G 1.313][G loss: -80.752]  0:21:38.600522
2592 (5, 1) [D loss: -31.160 R -87.895 F 49.421 G 0.731][G loss: -76.490]  0:21:39.406367
2593 (5, 1) [D loss: -31.215 R -86.688 F 44.470 G 1.100][G loss: -74.228]  0:21:40.199739
2594 (5, 1) [D loss: -22.698 R -69.121 F 35.967 G 1.046][G loss: -67.120]  0:21:41.009469
2595 (5, 1) [D loss: -26.854 R -76.931 F 42.831 G 0.725][G loss: -70.158]  0:21:41.815847
2596 (5, 1) [D loss: -17.093 R -47.325 F 24.326 G 0.591][G loss: -51.051]  0:21:42.611304
2597 (5, 1) [D loss: -23.552 R -66.780 F 36.947 G 0.628][G loss: -26.691]  0:21:43.414359
2598 (5, 1) [D loss: -27.805 R -59.934 F 26.912 G 0.522][G loss: -28.013]  0:21:44.219566
2599 (5, 1) [D loss: -21.780 R -54.817 F 21.635 G 1.140][G loss: -26.006]  0:21:45.036640
2600 (5, 1) [D loss: -19.020 R -69.536 F 43.182 G 0.733][G loss: -41.510]  0:21:45.834093
2601 (5, 1) [D loss: -20.023 R -77.370 F 48.964 G 0.838][G loss: -34.867]  0:21:46.636758
2602 (5, 1) [D loss: -16.006 R -75.206 F 52.340 G 0.686][G loss: -65.328]  0:21:47.442374
2603 (5, 1) [D loss: -22.016 R -93.137 F 65.976 G 0.515][G loss: -58.758]  0:21:48.248912
2604 (5, 1) [D loss: -23.026 R -96.177 F 68.230 G 0.492][G loss: -65.746]  0:21:49.058013
2605 (5, 1) [D loss: -25.505 R -103.877 F 72.095 G 0.628][G loss: -66.040]  0:21:49.858393
2606 (5, 1) [D loss: -26.238 R -101.782 F 70.911 G 0.463][G loss: -64.921]  0:21:50.679352
2607 (5, 1) [D loss: -23.320 R -95.787 F 66.677 G 0.579][G loss: -63.710]  0:21:51.479334
2608 (5, 1) [D loss: -28.931 R -96.519 F 62.043 G 0.554][G loss: -75.216]  0:21:52.289441
2609 (5, 1) [D loss: -27.506 R -110.029 F 77.710 G 0.481][G loss: -84.646]  0:21:53.106775
2610 (5, 1) [D loss: -17.988 R -98.339 F 73.868 G 0.648][G loss: -76.431]  0:21:53.920123
2611 (5, 1) [D loss: -24.335 R -103.279 F 61.491 G 1.745][G loss: -71.304]  0:21:54.739973
2612 (5, 1) [D loss: -15.110 R -116.321 F 86.876 G 1.433][G loss: -87.746]  0:21:55.542456
2613 (5, 1) [D loss: -19.672 R -128.319 F 105.049 G 0.360][G loss: -106.548]  0:21:56.352837
2614 (5, 1) [D loss: -12.857 R -96.068 F 75.255 G 0.796][G loss: -82.732]  0:21:57.160801
2615 (5, 1) [D loss: -19.712 R -104.682 F 80.513 G 0.446][G loss: -86.819]  0:21:57.974631
2616 (5, 1) [D loss: -13.909 R -97.209 F 79.545 G 0.376][G loss: -84.134]  0:21:58.814035
2617 (5, 1) [D loss: -12.348 R -82.374 F 61.153 G 0.887][G loss: -84.429]  0:21:59.624747
2618 (5, 1) [D loss: -8.405 R -93.591 F 77.202 G 0.798][G loss: -73.336]  0:22:00.420232
2619 (5, 1) [D loss: -9.979 R -99.253 F 84.505 G 0.477][G loss: -82.108]  0:22:01.226783
2620 (5, 1) [D loss: -23.335 R -92.039 F 64.585 G 0.412][G loss: -67.095]  0:22:02.026694
2621 (5, 1) [D loss: -20.726 R -96.950 F 71.893 G 0.433][G loss: -63.368]  0:22:02.841446
2622 (5, 1) [D loss: -17.831 R -94.537 F 73.546 G 0.316][G loss: -67.138]  0:22:03.642009
2623 (5, 1) [D loss: -17.083 R -81.798 F 60.710 G 0.400][G loss: -61.330]  0:22:04.466191
2624 (5, 1) [D loss: -22.999 R -68.453 F 41.353 G 0.410][G loss: -39.879]  0:22:05.269120
2625 (5, 1) [D loss: -20.156 R -68.326 F 43.504 G 0.467][G loss: -42.416]  0:22:06.066083
2626 (5, 1) [D loss: -18.417 R -63.355 F 39.942 G 0.500][G loss: -38.530]  0:22:06.868134
2627 (5, 1) [D loss: -19.265 R -62.613 F 38.299 G 0.505][G loss: -39.663]  0:22:07.672159
2628 (5, 1) [D loss: -17.192 R -62.899 F 41.220 G 0.449][G loss: -43.221]  0:22:08.472941
2629 (5, 1) [D loss: -13.878 R -57.531 F 38.959 G 0.469][G loss: -39.147]  0:22:09.267771
2630 (5, 1) [D loss: -18.645 R -66.390 F 43.712 G 0.403][G loss: -41.473]  0:22:10.085993
2631 (5, 1) [D loss: -18.920 R -64.345 F 40.277 G 0.515][G loss: -36.848]  0:22:10.882272
2632 (5, 1) [D loss: -13.862 R -66.592 F 48.245 G 0.448][G loss: -42.853]  0:22:11.692299
2633 (5, 1) [D loss: -14.677 R -70.022 F 51.651 G 0.369][G loss: -49.448]  0:22:12.500167
2634 (5, 1) [D loss: -18.693 R -74.650 F 50.953 G 0.500][G loss: -53.084]  0:22:13.317815
2635 (5, 1) [D loss: -17.907 R -65.817 F 44.148 G 0.376][G loss: -47.250]  0:22:14.136120
2636 (5, 1) [D loss: -14.308 R -65.801 F 46.750 G 0.474][G loss: -40.830]  0:22:14.952700
2637 (5, 1) [D loss: -14.466 R -63.186 F 41.856 G 0.686][G loss: -43.970]  0:22:15.758131
2638 (5, 1) [D loss: -15.405 R -71.896 F 52.363 G 0.413][G loss: -50.377]  0:22:16.575067
2639 (5, 1) [D loss: -20.508 R -75.574 F 51.356 G 0.371][G loss: -50.162]  0:22:17.382574
2640 (5, 1) [D loss: -15.702 R -72.332 F 51.900 G 0.473][G loss: -48.763]  0:22:18.193340
2641 (5, 1) [D loss: -20.418 R -57.921 F 30.536 G 0.697][G loss: -27.670]  0:22:19.001578
2642 (5, 1) [D loss: -20.857 R -67.372 F 43.435 G 0.308][G loss: -46.029]  0:22:19.800569
2643 (5, 1) [D loss: -18.780 R -68.444 F 46.044 G 0.362][G loss: -43.759]  0:22:20.603291
2644 (5, 1) [D loss: -17.823 R -67.726 F 46.224 G 0.368][G loss: -47.256]  0:22:21.400225
2645 (5, 1) [D loss: -20.727 R -62.779 F 35.180 G 0.687][G loss: -45.070]  0:22:22.212543
2646 (5, 1) [D loss: -5.524 R -68.964 F 58.028 G 0.541][G loss: -54.284]  0:22:23.007096
2647 (5, 1) [D loss: -17.422 R -71.933 F 50.503 G 0.401][G loss: -55.474]  0:22:23.818563
2648 (5, 1) [D loss: -14.260 R -47.786 F 27.878 G 0.565][G loss: -38.939]  0:22:24.618850
2649 (5, 1) [D loss: -17.980 R -62.891 F 41.484 G 0.343][G loss: -45.266]  0:22:25.438382
2650 (5, 1) [D loss: -13.847 R -58.701 F 40.386 G 0.447][G loss: -45.821]  0:22:26.272905
2651 (5, 1) [D loss: -13.199 R -60.590 F 43.221 G 0.417][G loss: -44.420]  0:22:27.075806
2652 (5, 1) [D loss: -17.273 R -65.917 F 44.998 G 0.365][G loss: -44.172]  0:22:27.886911
2653 (5, 1) [D loss: -21.411 R -58.933 F 33.423 G 0.410][G loss: -31.955]  0:22:28.687545
2654 (5, 1) [D loss: -17.239 R -50.669 F 29.161 G 0.427][G loss: -34.119]  0:22:29.492383
2655 (5, 1) [D loss: -17.630 R -58.632 F 37.566 G 0.344][G loss: -33.322]  0:22:30.293527
2656 (5, 1) [D loss: -18.552 R -60.938 F 38.458 G 0.393][G loss: -42.306]  0:22:31.099525
2657 (5, 1) [D loss: -17.993 R -50.603 F 28.811 G 0.380][G loss: -32.736]  0:22:31.903189
2658 (5, 1) [D loss: -20.657 R -61.047 F 35.464 G 0.493][G loss: -44.191]  0:22:32.698494
2659 (5, 1) [D loss: -16.988 R -64.197 F 42.787 G 0.442][G loss: -47.603]  0:22:33.506800
2660 (5, 1) [D loss: -18.640 R -66.913 F 44.595 G 0.368][G loss: -42.391]  0:22:34.308147
2661 (5, 1) [D loss: -19.272 R -63.640 F 40.302 G 0.407][G loss: -40.186]  0:22:35.123369
2662 (5, 1) [D loss: -15.388 R -55.928 F 37.252 G 0.329][G loss: -30.322]  0:22:35.930294
2663 (5, 1) [D loss: -17.558 R -61.308 F 39.628 G 0.412][G loss: -38.000]  0:22:36.727791
2664 (5, 1) [D loss: -19.480 R -56.862 F 33.091 G 0.429][G loss: -36.392]  0:22:37.527846
2665 (5, 1) [D loss: -16.318 R -57.062 F 37.002 G 0.374][G loss: -35.262]  0:22:38.330746
2666 (5, 1) [D loss: -16.253 R -60.490 F 40.256 G 0.398][G loss: -33.913]  0:22:39.150020
2667 (5, 1) [D loss: -16.926 R -55.911 F 35.778 G 0.321][G loss: -37.318]  0:22:39.949384
2668 (5, 1) [D loss: -16.566 R -62.580 F 41.527 G 0.449][G loss: -41.759]  0:22:40.763539
2669 (5, 1) [D loss: -17.656 R -53.434 F 31.258 G 0.452][G loss: -30.683]  0:22:41.566649
2670 (5, 1) [D loss: -15.829 R -58.489 F 39.183 G 0.348][G loss: -34.947]  0:22:42.366039
2671 (5, 1) [D loss: -11.851 R -62.485 F 45.507 G 0.513][G loss: -36.691]  0:22:43.172927
2672 (5, 1) [D loss: -19.699 R -54.967 F 30.632 G 0.464][G loss: -27.835]  0:22:43.994242
2673 (5, 1) [D loss: -11.280 R -49.576 F 33.571 G 0.472][G loss: -28.595]  0:22:44.807297
2674 (5, 1) [D loss: -24.044 R -55.023 F 25.366 G 0.561][G loss: -28.980]  0:22:45.608667
2675 (5, 1) [D loss: -26.420 R -54.828 F 23.105 G 0.530][G loss: -28.646]  0:22:46.426738
2676 (5, 1) [D loss: -19.488 R -46.670 F 21.276 G 0.591][G loss: -31.971]  0:22:47.243430
2677 (5, 1) [D loss: -12.066 R -47.675 F 31.057 G 0.455][G loss: -33.642]  0:22:48.040628
2678 (5, 1) [D loss: -19.507 R -63.467 F 40.036 G 0.392][G loss: -43.067]  0:22:48.857010
2679 (5, 1) [D loss: -16.681 R -51.559 F 31.426 G 0.345][G loss: -38.056]  0:22:49.657822
2680 (5, 1) [D loss: -17.918 R -65.197 F 43.261 G 0.402][G loss: -43.607]  0:22:50.456208
2681 (5, 1) [D loss: -18.379 R -59.702 F 37.887 G 0.344][G loss: -42.477]  0:22:51.275533
2682 (5, 1) [D loss: -16.251 R -57.919 F 37.301 G 0.437][G loss: -43.179]  0:22:52.081020
2683 (5, 1) [D loss: -17.369 R -58.055 F 36.871 G 0.381][G loss: -32.019]  0:22:52.893224
2684 (5, 1) [D loss: -17.012 R -54.381 F 33.662 G 0.371][G loss: -37.144]  0:22:53.701213
2685 (5, 1) [D loss: -15.099 R -58.074 F 38.498 G 0.448][G loss: -38.660]  0:22:54.505360
2686 (5, 1) [D loss: -16.667 R -56.471 F 36.218 G 0.359][G loss: -36.426]  0:22:55.301979
2687 (5, 1) [D loss: -16.900 R -53.068 F 32.531 G 0.364][G loss: -32.224]  0:22:56.105835
2688 (5, 1) [D loss: -15.528 R -46.846 F 26.446 G 0.487][G loss: -29.920]  0:22:56.905358
2689 (5, 1) [D loss: -22.351 R -59.089 F 31.947 G 0.479][G loss: -41.399]  0:22:57.708806
2690 (5, 1) [D loss: -19.842 R -48.533 F 24.624 G 0.407][G loss: -27.634]  0:22:58.522203
2691 (5, 1) [D loss: -15.049 R -52.117 F 33.548 G 0.352][G loss: -33.229]  0:22:59.337326
2692 (5, 1) [D loss: -16.743 R -51.627 F 30.466 G 0.442][G loss: -34.427]  0:23:00.161202
2693 (5, 1) [D loss: -16.257 R -49.449 F 28.333 G 0.486][G loss: -27.067]  0:23:00.982491
2694 (5, 1) [D loss: -15.250 R -51.882 F 33.459 G 0.317][G loss: -36.410]  0:23:01.799156
2695 (5, 1) [D loss: -19.047 R -56.810 F 33.255 G 0.451][G loss: -30.729]  0:23:02.603299
2696 (5, 1) [D loss: -16.654 R -55.427 F 34.525 G 0.425][G loss: -29.934]  0:23:03.401649
2697 (5, 1) [D loss: -19.540 R -53.747 F 30.291 G 0.392][G loss: -29.282]  0:23:04.219157
2698 (5, 1) [D loss: -16.200 R -52.915 F 32.453 G 0.426][G loss: -33.247]  0:23:05.025866
2699 (5, 1) [D loss: -18.510 R -55.092 F 32.012 G 0.457][G loss: -29.159]  0:23:05.838720
2700 (5, 1) [D loss: -18.350 R -57.931 F 35.467 G 0.411][G loss: -37.916]  0:23:06.651638
2701 (5, 1) [D loss: -18.067 R -55.419 F 32.852 G 0.450][G loss: -35.987]  0:23:07.463341
2702 (5, 1) [D loss: -19.768 R -54.402 F 30.854 G 0.378][G loss: -33.875]  0:23:08.274268
2703 (5, 1) [D loss: -20.050 R -56.117 F 30.701 G 0.537][G loss: -31.388]  0:23:09.092955
2704 (5, 1) [D loss: -17.016 R -55.934 F 35.221 G 0.370][G loss: -35.716]  0:23:09.895816
2705 (5, 1) [D loss: -15.918 R -52.887 F 31.704 G 0.526][G loss: -35.124]  0:23:10.706845
2706 (5, 1) [D loss: -12.656 R -59.327 F 42.797 G 0.387][G loss: -39.073]  0:23:11.509960
2707 (5, 1) [D loss: -19.598 R -60.634 F 37.175 G 0.386][G loss: -38.810]  0:23:12.321693
2708 (5, 1) [D loss: -18.189 R -58.389 F 35.527 G 0.467][G loss: -36.804]  0:23:13.125271
2709 (5, 1) [D loss: -9.884 R -51.671 F 36.388 G 0.540][G loss: -26.949]  0:23:13.922383
2710 (5, 1) [D loss: -14.494 R -59.392 F 40.243 G 0.465][G loss: -32.290]  0:23:14.742341
2711 (5, 1) [D loss: -10.340 R -48.140 F 32.675 G 0.512][G loss: -24.914]  0:23:15.549089
2712 (5, 1) [D loss: -17.486 R -57.734 F 36.665 G 0.358][G loss: -32.177]  0:23:16.360412
2713 (5, 1) [D loss: -17.146 R -57.798 F 36.900 G 0.375][G loss: -34.961]  0:23:17.179221
2714 (5, 1) [D loss: -19.340 R -51.426 F 27.136 G 0.495][G loss: -25.379]  0:23:17.981963
2715 (5, 1) [D loss: -16.636 R -49.816 F 29.786 G 0.339][G loss: -29.162]  0:23:18.796919
2716 (5, 1) [D loss: -13.767 R -52.148 F 33.796 G 0.459][G loss: -33.756]  0:23:19.600513
2717 (5, 1) [D loss: -18.749 R -56.281 F 33.791 G 0.374][G loss: -34.122]  0:23:20.407246
2718 (5, 1) [D loss: -17.344 R -53.930 F 32.310 G 0.428][G loss: -30.723]  0:23:21.224021
2719 (5, 1) [D loss: -16.606 R -53.148 F 32.756 G 0.379][G loss: -32.279]  0:23:22.033935
2720 (5, 1) [D loss: -14.766 R -41.541 F 22.317 G 0.446][G loss: -32.008]  0:23:22.850897
2721 (5, 1) [D loss: -19.391 R -48.848 F 22.847 G 0.661][G loss: -26.582]  0:23:23.652455
2722 (5, 1) [D loss: -13.064 R -54.058 F 37.608 G 0.339][G loss: -37.922]  0:23:24.479410
2723 (5, 1) [D loss: -15.013 R -57.207 F 38.369 G 0.383][G loss: -33.883]  0:23:25.288557
2724 (5, 1) [D loss: -17.294 R -52.784 F 31.286 G 0.420][G loss: -31.846]  0:23:26.110999
2725 (5, 1) [D loss: -16.352 R -43.518 F 21.086 G 0.608][G loss: -22.473]  0:23:26.919424
2726 (5, 1) [D loss: -18.296 R -44.343 F 21.459 G 0.459][G loss: -18.661]  0:23:27.728784
2727 (5, 1) [D loss: -18.089 R -60.668 F 38.320 G 0.426][G loss: -35.677]  0:23:28.531346
2728 (5, 1) [D loss: -15.461 R -63.117 F 44.002 G 0.365][G loss: -44.979]  0:23:29.343734
2729 (5, 1) [D loss: -15.772 R -61.479 F 41.999 G 0.371][G loss: -42.527]  0:23:30.152645
2730 (5, 1) [D loss: -18.400 R -68.390 F 44.877 G 0.511][G loss: -47.835]  0:23:30.970712
2731 (5, 1) [D loss: -19.729 R -63.710 F 39.640 G 0.434][G loss: -43.398]  0:23:31.798603
2732 (5, 1) [D loss: -17.756 R -60.116 F 38.898 G 0.346][G loss: -37.005]  0:23:32.624430
2733 (5, 1) [D loss: -16.209 R -55.012 F 34.068 G 0.473][G loss: -37.177]  0:23:33.444431
2734 (5, 1) [D loss: -14.751 R -54.950 F 34.285 G 0.591][G loss: -32.466]  0:23:34.243471
2735 (5, 1) [D loss: -18.040 R -55.303 F 32.987 G 0.428][G loss: -36.792]  0:23:35.048508
2736 (5, 1) [D loss: -17.436 R -51.014 F 30.358 G 0.322][G loss: -28.817]  0:23:35.858855
2737 (5, 1) [D loss: -18.472 R -52.430 F 30.459 G 0.350][G loss: -30.360]  0:23:36.669496
2738 (5, 1) [D loss: -17.090 R -50.328 F 28.894 G 0.434][G loss: -32.758]  0:23:37.485527
2739 (5, 1) [D loss: -15.616 R -54.339 F 34.525 G 0.420][G loss: -35.180]  0:23:38.297784
2740 (5, 1) [D loss: -16.495 R -60.294 F 40.459 G 0.334][G loss: -34.707]  0:23:39.101869
2741 (5, 1) [D loss: -17.291 R -61.214 F 39.731 G 0.419][G loss: -38.717]  0:23:39.905699
2742 (5, 1) [D loss: -17.317 R -63.448 F 41.294 G 0.484][G loss: -41.095]  0:23:40.714095
2743 (5, 1) [D loss: -18.647 R -58.523 F 35.811 G 0.407][G loss: -35.898]  0:23:41.532898
2744 (5, 1) [D loss: -18.127 R -58.245 F 36.135 G 0.398][G loss: -33.610]  0:23:42.331578
2745 (5, 1) [D loss: -15.835 R -51.763 F 31.711 G 0.422][G loss: -32.111]  0:23:43.137681
2746 (5, 1) [D loss: -14.133 R -50.315 F 31.479 G 0.470][G loss: -27.680]  0:23:43.944439
2747 (5, 1) [D loss: -15.809 R -47.466 F 27.622 G 0.404][G loss: -32.014]  0:23:44.748725
2748 (5, 1) [D loss: -17.872 R -53.070 F 31.094 G 0.410][G loss: -28.449]  0:23:45.571339
2749 (5, 1) [D loss: -16.552 R -51.373 F 30.217 G 0.460][G loss: -31.510]  0:23:46.369480
2750 (5, 1) [D loss: -17.128 R -51.481 F 30.808 G 0.355][G loss: -32.374]  0:23:47.175008
2751 (5, 1) [D loss: -16.029 R -45.834 F 24.832 G 0.497][G loss: -23.413]  0:23:47.976645
2752 (5, 1) [D loss: -17.676 R -48.094 F 27.154 G 0.326][G loss: -26.983]  0:23:48.788332
2753 (5, 1) [D loss: -16.106 R -49.328 F 29.759 G 0.346][G loss: -32.299]  0:23:49.621297
2754 (5, 1) [D loss: -16.830 R -41.588 F 21.001 G 0.376][G loss: -25.476]  0:23:50.429807
2755 (5, 1) [D loss: -15.565 R -37.111 F 17.790 G 0.376][G loss: -19.566]  0:23:51.229342
2756 (5, 1) [D loss: -18.069 R -40.978 F 19.029 G 0.388][G loss: -19.694]  0:23:52.027290
2757 (5, 1) [D loss: -16.856 R -37.026 F 15.927 G 0.424][G loss: -21.836]  0:23:52.841209
2758 (5, 1) [D loss: -20.887 R -41.787 F 17.126 G 0.377][G loss: -24.153]  0:23:53.641052
2759 (5, 1) [D loss: -14.694 R -45.283 F 24.997 G 0.559][G loss: -26.919]  0:23:54.467713
2760 (5, 1) [D loss: -20.520 R -46.754 F 21.924 G 0.431][G loss: -23.297]  0:23:55.280918
2761 (5, 1) [D loss: -20.299 R -54.200 F 29.416 G 0.448][G loss: -30.153]  0:23:56.083099
2762 (5, 1) [D loss: -16.876 R -50.519 F 28.060 G 0.558][G loss: -28.191]  0:23:56.903265
2763 (5, 1) [D loss: -16.641 R -45.917 F 25.170 G 0.411][G loss: -28.299]  0:23:57.711394
2764 (5, 1) [D loss: -16.126 R -44.176 F 24.028 G 0.402][G loss: -23.288]  0:23:58.515873
2765 (5, 1) [D loss: -17.580 R -43.774 F 20.960 G 0.523][G loss: -19.569]  0:23:59.319206
2766 (5, 1) [D loss: -16.653 R -46.018 F 25.567 G 0.380][G loss: -27.232]  0:24:00.124461
2767 (5, 1) [D loss: -17.324 R -43.596 F 21.884 G 0.439][G loss: -24.914]  0:24:00.934854
2768 (5, 1) [D loss: -19.207 R -45.657 F 22.277 G 0.417][G loss: -27.451]  0:24:01.732903
2769 (5, 1) [D loss: -17.794 R -49.156 F 27.640 G 0.372][G loss: -33.373]  0:24:02.532470
2770 (5, 1) [D loss: -16.764 R -43.122 F 22.541 G 0.382][G loss: -24.764]  0:24:03.335675
2771 (5, 1) [D loss: -18.152 R -44.588 F 22.592 G 0.384][G loss: -23.622]  0:24:04.133717
2772 (5, 1) [D loss: -18.921 R -51.500 F 28.700 G 0.388][G loss: -33.584]  0:24:04.932487
2773 (5, 1) [D loss: -16.713 R -37.108 F 16.927 G 0.347][G loss: -23.334]  0:24:05.759899
2774 (5, 1) [D loss: -17.071 R -39.425 F 18.290 G 0.406][G loss: -20.978]  0:24:06.583605
2775 (5, 1) [D loss: -18.473 R -47.238 F 24.490 G 0.427][G loss: -28.494]  0:24:07.392888
2776 (5, 1) [D loss: -15.694 R -36.727 F 17.042 G 0.399][G loss: -20.770]  0:24:08.190684
2777 (5, 1) [D loss: -15.727 R -50.506 F 31.252 G 0.353][G loss: -24.487]  0:24:09.001934
2778 (5, 1) [D loss: -17.189 R -47.417 F 27.056 G 0.317][G loss: -21.769]  0:24:09.805651
2779 (5, 1) [D loss: -15.690 R -46.447 F 26.971 G 0.379][G loss: -23.620]  0:24:10.609202
2780 (5, 1) [D loss: -14.829 R -38.766 F 20.221 G 0.372][G loss: -22.491]  0:24:11.407615
2781 (5, 1) [D loss: -16.889 R -43.955 F 23.067 G 0.400][G loss: -17.420]  0:24:12.209921
2782 (5, 1) [D loss: -14.358 R -40.285 F 22.609 G 0.332][G loss: -19.736]  0:24:13.015943
2783 (5, 1) [D loss: -17.596 R -41.557 F 20.121 G 0.384][G loss: -19.112]  0:24:13.822779
2784 (5, 1) [D loss: -20.514 R -42.749 F 18.402 G 0.383][G loss: -19.898]  0:24:14.616484
2785 (5, 1) [D loss: -17.737 R -41.609 F 18.986 G 0.489][G loss: -24.406]  0:24:15.410946
2786 (5, 1) [D loss: -11.495 R -33.887 F 17.048 G 0.534][G loss: -10.990]  0:24:16.211462
2787 (5, 1) [D loss: -17.983 R -38.668 F 17.126 G 0.356][G loss: -17.304]  0:24:17.020197
2788 (5, 1) [D loss: -18.590 R -45.753 F 22.794 G 0.437][G loss: -23.761]  0:24:17.823680
2789 (5, 1) [D loss: -15.997 R -37.281 F 17.679 G 0.361][G loss: -22.818]  0:24:18.631361
2790 (5, 1) [D loss: -17.237 R -41.464 F 18.811 G 0.542][G loss: -22.417]  0:24:19.437351
2791 (5, 1) [D loss: -18.991 R -43.152 F 19.200 G 0.496][G loss: -21.816]  0:24:20.235749
2792 (5, 1) [D loss: -15.907 R -38.875 F 19.508 G 0.346][G loss: -23.746]  0:24:21.047629
2793 (5, 1) [D loss: -15.545 R -38.609 F 16.316 G 0.675][G loss: -23.831]  0:24:21.848147
2794 (5, 1) [D loss: -11.564 R -38.966 F 22.311 G 0.509][G loss: -27.672]  0:24:22.657222
2795 (5, 1) [D loss: -17.475 R -48.110 F 25.967 G 0.467][G loss: -31.234]  0:24:23.459604
2796 (5, 1) [D loss: -18.298 R -52.273 F 30.484 G 0.349][G loss: -35.875]  0:24:24.275592
2797 (5, 1) [D loss: -12.659 R -48.884 F 32.457 G 0.377][G loss: -35.309]  0:24:25.094448
2798 (5, 1) [D loss: -18.001 R -51.810 F 30.599 G 0.321][G loss: -37.893]  0:24:25.911827
2799 (5, 1) [D loss: -19.308 R -50.094 F 27.093 G 0.369][G loss: -34.631]  0:24:26.732076
2800 (5, 1) [D loss: -14.235 R -46.740 F 28.999 G 0.351][G loss: -34.521]  0:24:27.551022
2801 (5, 1) [D loss: -17.565 R -51.454 F 29.539 G 0.435][G loss: -36.529]  0:24:28.347856
2802 (5, 1) [D loss: -17.024 R -55.691 F 34.750 G 0.392][G loss: -34.932]  0:24:29.159244
2803 (5, 1) [D loss: -16.920 R -53.889 F 33.004 G 0.397][G loss: -31.713]  0:24:29.976323
2804 (5, 1) [D loss: -16.245 R -48.793 F 28.356 G 0.419][G loss: -26.506]  0:24:30.779184
2805 (5, 1) [D loss: -17.009 R -52.973 F 32.685 G 0.328][G loss: -31.553]  0:24:31.600444
2806 (5, 1) [D loss: -14.634 R -44.419 F 25.194 G 0.459][G loss: -28.254]  0:24:32.405783
2807 (5, 1) [D loss: -21.255 R -52.423 F 26.853 G 0.431][G loss: -24.596]  0:24:33.224672
2808 (5, 1) [D loss: -22.584 R -45.705 F 17.598 G 0.552][G loss: -28.898]  0:24:34.036841
2809 (5, 1) [D loss: -18.322 R -48.746 F 26.035 G 0.439][G loss: -29.799]  0:24:34.843067
2810 (5, 1) [D loss: -22.732 R -54.299 F 26.498 G 0.507][G loss: -25.335]  0:24:35.658709
2811 (5, 1) [D loss: -12.297 R -50.149 F 33.595 G 0.426][G loss: -30.137]  0:24:36.464487
2812 (5, 1) [D loss: -16.633 R -56.162 F 34.777 G 0.475][G loss: -27.875]  0:24:37.276993
2813 (5, 1) [D loss: -9.321 R -46.127 F 31.976 G 0.483][G loss: -28.929]  0:24:38.107097
2814 (5, 1) [D loss: -16.895 R -45.996 F 24.282 G 0.482][G loss: -19.502]  0:24:38.927979
2815 (5, 1) [D loss: -10.256 R -38.564 F 23.306 G 0.500][G loss: -18.731]  0:24:39.727499
2816 (5, 1) [D loss: -15.275 R -37.843 F 17.667 G 0.490][G loss: -16.043]  0:24:40.533016
2817 (5, 1) [D loss: -20.622 R -47.661 F 21.776 G 0.526][G loss: -19.512]  0:24:41.350624
2818 (5, 1) [D loss: -23.535 R -43.655 F 16.398 G 0.372][G loss: -24.045]  0:24:42.163640
2819 (5, 1) [D loss: -16.798 R -40.904 F 20.672 G 0.343][G loss: -21.229]  0:24:42.976725
2820 (5, 1) [D loss: -17.918 R -44.316 F 22.652 G 0.375][G loss: -26.578]  0:24:43.786559
2821 (5, 1) [D loss: -17.571 R -42.909 F 21.954 G 0.338][G loss: -24.677]  0:24:44.589432
2822 (5, 1) [D loss: -18.960 R -44.971 F 22.052 G 0.396][G loss: -26.630]  0:24:45.401411
2823 (5, 1) [D loss: -15.995 R -50.699 F 29.885 G 0.482][G loss: -27.954]  0:24:46.208631
2824 (5, 1) [D loss: -17.203 R -45.511 F 24.945 G 0.336][G loss: -26.708]  0:24:47.024890
2825 (5, 1) [D loss: -15.300 R -51.403 F 32.348 G 0.376][G loss: -27.687]  0:24:47.841606
2826 (5, 1) [D loss: -17.136 R -47.132 F 26.463 G 0.353][G loss: -27.659]  0:24:48.649282
2827 (5, 1) [D loss: -17.984 R -44.055 F 21.085 G 0.499][G loss: -23.948]  0:24:49.459524
2828 (5, 1) [D loss: -22.342 R -50.331 F 23.542 G 0.445][G loss: -25.304]  0:24:50.264020
2829 (5, 1) [D loss: -18.692 R -44.343 F 21.314 G 0.434][G loss: -32.736]  0:24:51.076941
2830 (5, 1) [D loss: -19.822 R -38.705 F 16.145 G 0.274][G loss: -23.004]  0:24:51.890954
2831 (5, 1) [D loss: -13.134 R -38.238 F 21.988 G 0.312][G loss: -30.711]  0:24:52.698349
2832 (5, 1) [D loss: -17.504 R -45.662 F 24.807 G 0.335][G loss: -26.549]  0:24:53.510890
2833 (5, 1) [D loss: -17.609 R -41.952 F 20.528 G 0.382][G loss: -20.566]  0:24:54.331260
2834 (5, 1) [D loss: -18.128 R -44.202 F 22.752 G 0.332][G loss: -22.524]  0:24:55.160154
2835 (5, 1) [D loss: -19.025 R -40.415 F 16.919 G 0.447][G loss: -22.998]  0:24:55.967124
2836 (5, 1) [D loss: -13.438 R -37.054 F 18.981 G 0.463][G loss: -21.081]  0:24:56.779336
2837 (5, 1) [D loss: -15.676 R -46.762 F 27.624 G 0.346][G loss: -29.343]  0:24:57.585083
2838 (5, 1) [D loss: -15.348 R -44.537 F 23.275 G 0.591][G loss: -27.678]  0:24:58.390485
2839 (5, 1) [D loss: -18.230 R -42.535 F 20.991 G 0.331][G loss: -23.320]  0:24:59.209281
2840 (5, 1) [D loss: -13.551 R -44.697 F 27.329 G 0.382][G loss: -25.962]  0:25:00.023665
2841 (5, 1) [D loss: -12.863 R -55.554 F 37.354 G 0.534][G loss: -26.975]  0:25:00.849000
2842 (5, 1) [D loss: -17.364 R -51.820 F 31.216 G 0.324][G loss: -27.256]  0:25:01.669541
2843 (5, 1) [D loss: -19.114 R -41.963 F 18.806 G 0.404][G loss: -19.912]  0:25:02.471794
2844 (5, 1) [D loss: -16.764 R -44.000 F 22.591 G 0.465][G loss: -17.154]  0:25:03.280793
2845 (5, 1) [D loss: -17.568 R -43.392 F 21.968 G 0.386][G loss: -19.099]  0:25:04.086567
2846 (5, 1) [D loss: -16.020 R -40.357 F 20.881 G 0.346][G loss: -23.592]  0:25:04.901511
2847 (5, 1) [D loss: -18.439 R -41.980 F 19.412 G 0.413][G loss: -21.081]  0:25:05.711800
2848 (5, 1) [D loss: -21.762 R -48.395 F 22