AI Blitz 5 ⚡

Image colorization with U-NET GAN

Step 1: Preparation¶

In [ ]:

# Getting data
!pip install git+https://gitlab.aicrowd.com/yoogottamk/aicrowd-cli.git
from aicrowd.magic import *
!aicrowd login --api-key <key>
!aicrowd dataset download --jobs 5 --challenge imgcol *v2.zip

In [ ]:

# Moving things into the right locations
!rm -rf data
!mkdir data

!mv 'test_black_white_images-v2.zip ' test_black_white_images-v2.zip
!mv 'validation_black_white_images-v2.zip ' validation_black_white_images-v2.zip

!unzip train_black_white_images-v2.zip -d data/
!unzip train_color_images-v2.zip -d data/
!unzip validation_black_white_images-v2.zip -d data/
!unzip validation_color_images-v2.zip -d data/
!unzip test_black_white_images-v2.zip -d data/

Import modules¶

In [ ]:

import numpy as np
import pandas as pd
from glob import glob
from os.path import join
import matplotlib.pyplot as plt
from tqdm.notebook import tqdm
from skimage.color import *
import tensorflow as tf

Data Preparation¶

In [ ]:

# Important parameters
img_size = 512

In [ ]:

# Get filepath to all images
fimgs_tr_x = sorted(glob('data/train_black_white_images-v2/*'))
fimgs_tr_y = sorted(glob('data/train_color_images-v2/*'))
fimgs_va_x = sorted(glob('data/validation_black_white_images-v2/*'))
fimgs_va_y = sorted(glob('data/validation_color_images-v2/*'))
fimgs_te_x = sorted(glob('data/test_black_white_images-v2/*'))

In [ ]:

# Combine train and validation set
fx_train = fimgs_tr_x + fimgs_va_x
fy_train = fimgs_tr_y + fimgs_va_y

Note!!!¶

Most of the following code is originally coming from this medium post. I've adapted them slighty and changed some of the NN architecture but credit to it goes clearly to the original auhtor.

2. The GAN¶

In this section, we'll create our GAN model step-by-step with Keras. First, we'll implement the generator then the discriminator and finally the loss functions required by both of them.

A. Generator¶

Our generator ( represented as $G$ ) will take in grayscale image $x$ and produce a LAB image $G( x )$. Note, $x$ will be a tensor of shape $( \ batch \ size \ , \ 512 \ , \ 512 \ , \ 1 \ )$ and the output $G(x)$ will have a shape $( \ batch \ size \ , \ 512 \ , \ 512 \ , \ 3 \ )$

Our generator will have a encoder-decoder structure, similar to the UNet architecture. Additionally, we use Dilated convolutions to have a larger receptive field.
We introduce skip connections in our model so as to have better flow of information from the encoder to the decoder.

In [ ]:

from tensorflow.keras.layers import (
    BatchNormalization, Conv2D, Conv2DTranspose, Dense,
    Flatten, Dropout, UpSampling2D, Concatenate, ELU,
    Input, LeakyReLU, MaxPooling2D, Reshape, UpSampling2D)

In [ ]:

def get_generator_model(ndim=32):

    #activation = LeakyReLU
    activation = ELU

    inputs = Input(shape=(img_size, img_size, 1))

    conv1 = Conv2D(ndim*2**0, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(inputs)
    conv1 = BatchNormalization()(conv1)
    conv1 = activation()(conv1)
    conv1 = Conv2D(ndim*2**0, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv1)
    conv1 = BatchNormalization()(conv1)
    conv1 = activation()(conv1)
    pool1 = MaxPooling2D()(conv1)

    conv2 = Conv2D(ndim*2**1, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(pool1)
    conv2 = BatchNormalization()(conv2)
    conv2 = activation()(conv2)
    conv2 = Conv2D(ndim*2**1, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv2)
    conv2 = BatchNormalization()(conv2)
    conv2 = activation()(conv2)
    pool2 = MaxPooling2D()(conv2)

    conv3 = Conv2D(ndim*2**2, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(pool2)
    conv3 = BatchNormalization()(conv3)
    conv3 = activation()(conv3)
    conv3 = MaxPooling2D()(conv3)
    conv3 = Conv2D(ndim*2**2, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv3)
    conv3 = BatchNormalization()(conv3)
    conv3 = activation()(conv3)
    pool3 = MaxPooling2D()(conv3)

    conv4 = Conv2D(ndim*2**3, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(pool3)
    conv4 = BatchNormalization()(conv4)
    conv4 = activation()(conv4)
    conv4 = MaxPooling2D()(conv4)
    conv4 = Conv2D(ndim*2**3, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv4)
    conv4 = BatchNormalization()(conv4)
    conv4 = activation()(conv4)
    drop4 = Dropout(0.5)(conv4)
    pool4 = MaxPooling2D()(drop4)

    conv5 = Conv2D(ndim*2**4, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(pool4)
    conv5 = BatchNormalization()(conv5)
    conv5 = activation()(conv5)
    conv5 = MaxPooling2D()(conv5)
    conv5 = Conv2D(ndim*2**4, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv5)
    conv5 = BatchNormalization()(conv5)
    conv5 = activation()(conv5)
    drop5 = Dropout(0.5)(conv5)

    bottleneck = Flatten()(drop5)
    bottleneck = Dense(1024)(bottleneck)
    bottleneck = Dense(ndim*256)(bottleneck)
    bottleneck = Reshape((4, 4, 16*ndim))(bottleneck)

    conv_up_1 = Conv2DTranspose(ndim*2**4, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(bottleneck)
    merge_1 = Concatenate()([conv5, conv_up_1])
    conv_up_1 = BatchNormalization()(merge_1)
    conv_up_1 = activation()(conv_up_1)
    conv_up_1 = UpSampling2D()(conv_up_1)
    conv_up_1 = Conv2DTranspose(ndim*2**4, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_1)
    conv_up_1 = BatchNormalization()(conv_up_1)
    conv_up_1 = activation()(conv_up_1)
    conv_up_1 = UpSampling2D()(conv_up_1)

    conv_up_2 = Conv2DTranspose(ndim*2**3, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_1)
    merge_2 = Concatenate()([conv4, conv_up_2])
    conv_up_2 = BatchNormalization()(merge_2)
    conv_up_2 = activation()(conv_up_2)
    conv_up_2 = UpSampling2D()(conv_up_2)
    conv_up_2 = Conv2DTranspose(ndim*2**3, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_2)
    conv_up_2 = BatchNormalization()(conv_up_2)
    conv_up_2 = activation()(conv_up_2)
    conv_up_2 = UpSampling2D()(conv_up_2)

    conv_up_3 = Conv2DTranspose(ndim*2**2, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_2)
    merge_3 = Concatenate()([conv3, conv_up_3])
    conv_up_3 = BatchNormalization()(merge_3)
    conv_up_3 = activation()(conv_up_3)
    conv_up_3 = UpSampling2D()(conv_up_3)
    conv_up_3 = Conv2DTranspose(ndim*2**2, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_3)
    conv_up_3 = BatchNormalization()(conv_up_3)
    conv_up_3 = activation()(conv_up_3)
    conv_up_3 = UpSampling2D()(conv_up_3)

    conv_up_4 = Conv2DTranspose(ndim*2**1, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_3)
    merge_4 = Concatenate()([conv2, conv_up_4])
    conv_up_4 = BatchNormalization()(merge_4)
    conv_up_4 = activation()(conv_up_4)
    conv_up_4 = Conv2DTranspose(ndim*2**1, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_4)
    conv_up_4 = BatchNormalization()(conv_up_4)
    conv_up_4 = activation()(conv_up_4)
    conv_up_4 = UpSampling2D()(conv_up_4)

    conv_up_5 = Conv2DTranspose(ndim*2**0, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_4)
    merge_5 = Concatenate()([conv1, conv_up_5])
    conv_up_5 = BatchNormalization()(merge_5)
    conv_up_5 = activation()(conv_up_5)
    conv_up_5 = Conv2DTranspose(ndim*2**0, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_5)
    conv_up_5 = BatchNormalization()(conv_up_5)
    conv_up_5 = activation()(conv_up_5)

    outputs = Conv2DTranspose(3, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_5)

    model = tf.keras.models.Model(inputs, outputs)

    return model

In [ ]:

def get_generator_model(ndim=32):

    #activation = LeakyReLU
    activation = ELU

    inputs = Input(shape=(img_size, img_size, 1))

    conv1 = Conv2D(ndim*2**0, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(inputs)
    conv1 = BatchNormalization()(conv1)
    conv1 = activation()(conv1)
    conv1 = MaxPooling2D()(conv1)
    conv1 = Conv2D(ndim*2**0, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv1)
    conv1 = BatchNormalization()(conv1)
    conv1 = activation()(conv1)
    pool1 = MaxPooling2D()(conv1)

    conv2 = Conv2D(ndim*2**1, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(pool1)
    conv2 = BatchNormalization()(conv2)
    conv2 = activation()(conv2)
    conv2 = MaxPooling2D()(conv2)
    conv2 = Conv2D(ndim*2**1, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv2)
    conv2 = BatchNormalization()(conv2)
    conv2 = activation()(conv2)
    pool2 = MaxPooling2D()(conv2)

    conv3 = Conv2D(ndim*2**2, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(pool2)
    conv3 = BatchNormalization()(conv3)
    conv3 = activation()(conv3)
    conv3 = MaxPooling2D()(conv3)
    conv3 = Conv2D(ndim*2**2, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv3)
    conv3 = BatchNormalization()(conv3)
    conv3 = activation()(conv3)
    pool3 = MaxPooling2D()(conv3)

    conv4 = Conv2D(ndim*2**3, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(pool3)
    conv4 = BatchNormalization()(conv4)
    conv4 = activation()(conv4)
    conv4 = MaxPooling2D()(conv4)
    conv4 = Conv2D(ndim*2**3, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv4)
    conv4 = BatchNormalization()(conv4)
    conv4 = activation()(conv4)
    drop4 = Dropout(0.5)(conv4)

    bottleneck = Flatten()(drop4)
    bottleneck = Dense(1024)(bottleneck)
    bottleneck = Dense(ndim*128)(bottleneck)
    bottleneck = Reshape((4, 4, 8*ndim))(bottleneck)

    conv_up_1 = Conv2DTranspose(ndim*2**3, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(bottleneck)
    merge_1 = Concatenate()([conv4, conv_up_1])
    conv_up_1 = BatchNormalization()(merge_1)
    conv_up_1 = activation()(conv_up_1)
    conv_up_1 = UpSampling2D()(conv_up_1)
    conv_up_1 = Conv2DTranspose(ndim*2**3, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_1)
    conv_up_1 = BatchNormalization()(conv_up_1)
    conv_up_1 = activation()(conv_up_1)
    conv_up_1 = UpSampling2D()(conv_up_1)

    conv_up_2 = Conv2DTranspose(ndim*2**2, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_1)
    merge_2 = Concatenate()([conv3, conv_up_2])
    conv_up_2 = BatchNormalization()(merge_2)
    conv_up_2 = activation()(conv_up_2)
    conv_up_2 = UpSampling2D()(conv_up_2)
    conv_up_2 = Conv2DTranspose(ndim*2**2, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_2)
    conv_up_2 = BatchNormalization()(conv_up_2)
    conv_up_2 = activation()(conv_up_2)
    conv_up_2 = UpSampling2D()(conv_up_2)

    conv_up_3 = Conv2DTranspose(ndim*2**1, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_2)
    merge_3 = Concatenate()([conv2, conv_up_3])
    conv_up_3 = BatchNormalization()(merge_3)
    conv_up_3 = activation()(conv_up_3)
    conv_up_3 = UpSampling2D()(conv_up_3)
    conv_up_3 = Conv2DTranspose(ndim*2**1, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_3)
    conv_up_3 = BatchNormalization()(conv_up_3)
    conv_up_3 = activation()(conv_up_3)
    conv_up_3 = UpSampling2D()(conv_up_3)

    conv_up_4 = Conv2DTranspose(ndim*2**0, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_3)
    merge_4 = Concatenate()([conv1, conv_up_4])
    conv_up_4 = BatchNormalization()(merge_4)
    conv_up_4 = activation()(conv_up_4)
    conv_up_4 = UpSampling2D()(conv_up_4)
    conv_up_4 = Conv2DTranspose(ndim*2**0, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_4)
    conv_up_4 = BatchNormalization()(conv_up_4)
    conv_up_4 = activation()(conv_up_4)

    outputs = Conv2DTranspose(3, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv_up_4)

    model = tf.keras.models.Model(inputs, outputs)

    return model

B. Discriminator¶

The discriminator model, represented as $D$, will take in the real image $y$ ( from the training data ) and the generated image $G(x)$ ( from the generator ) to output two probabilities.

We train the discriminator in such a manner that is able to differentiate the real images and the generated images. So, we train the model such that $y$ produces a output of $1.0$ and $G(x)$ produces an output of $0.0$.
Note that instead of using hard labels like $1.0$ and $0.0$, we use soft labels which are close to 1 and 0. So for a hard label of $1.0$, the soft label will be $(1 - \epsilon)$ where $\epsilon$ is picked uniformly from $( 0 , 0.1 ]$

In [ ]:

def get_discriminator_model(ndim=64):

    #activation = LeakyReLU
    activation = ELU

    inputs = Input(shape=(img_size, img_size, 3))

    conv1 = Conv2D(ndim*2**0, kernel_size=(5, 5), strides=2, padding='same', kernel_initializer='he_normal')(inputs)
    conv1 = BatchNormalization()(conv1)
    conv1 = activation()(conv1)
    conv1 = Conv2D(ndim*2**0, kernel_size=(5, 5), strides=2, padding='same', kernel_initializer='he_normal')(conv1)
    conv1 = BatchNormalization()(conv1)
    conv1 = activation()(conv1)
    conv1 = MaxPooling2D()(conv1)

    conv2 = Conv2D(ndim*2**1, kernel_size=(4, 4), strides=2, padding='same', kernel_initializer='he_normal')(conv1)
    conv2 = BatchNormalization()(conv2)
    conv2 = activation()(conv2)
    conv2 = Conv2D(ndim*2**1, kernel_size=(4, 4), strides=2, padding='same', kernel_initializer='he_normal')(conv2)
    conv2 = BatchNormalization()(conv2)
    conv2 = activation()(conv2)
    conv2 = MaxPooling2D()(conv2)

    conv3 = Conv2D(ndim*2**2, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv2)
    conv3 = BatchNormalization()(conv3)
    conv3 = activation()(conv3)
    conv3 = Conv2D(ndim*2**2, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv3)
    conv3 = BatchNormalization()(conv3)
    conv3 = activation()(conv3)
    conv3 = MaxPooling2D()(conv3)

    conv4 = Conv2D(ndim*2**3, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv3)
    conv4 = BatchNormalization()(conv4)
    conv4 = activation()(conv4)
    conv4 = Conv2D(ndim*2**3, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv4)
    conv4 = BatchNormalization()(conv4)
    conv4 = activation()(conv4)
    conv4 = MaxPooling2D()(conv4)

    conv5 = Conv2D(ndim*2**4, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv4)
    conv5 = BatchNormalization()(conv5)
    conv5 = activation()(conv5)
    conv5 = Conv2D(ndim*2**4, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv5)
    conv5 = BatchNormalization()(conv5)
    conv5 = activation()(conv5)

    fully = Flatten()(conv5)
    fully = Dense(512)(fully)
    fully = BatchNormalization()(fully)
    fully = activation()(fully)
    fully = Dense(128)(fully)
    fully = BatchNormalization()(fully)
    fully = activation()(fully)
    fully = Dense(32)(fully)
    fully = BatchNormalization()(fully)
    fully = activation()(fully)
    fully = Dense(1, activation='sigmoid')(fully)

    model = tf.keras.models.Model(inputs, fully)

    return model

In [ ]:

def get_discriminator_model(ndim=64):

    #activation = LeakyReLU
    activation = ELU

    inputs = Input(shape=(img_size, img_size, 3))

    conv1 = Conv2D(ndim*2**0, kernel_size=(5, 5), strides=1, padding='same', kernel_initializer='he_normal')(inputs)
    conv1 = BatchNormalization()(conv1)
    conv1 = activation()(conv1)
    conv1 = MaxPooling2D()(conv1)
    conv1 = Conv2D(ndim*2**0, kernel_size=(5, 5), strides=1, padding='same', kernel_initializer='he_normal')(conv1)
    conv1 = BatchNormalization()(conv1)
    conv1 = activation()(conv1)
    conv1 = MaxPooling2D()(conv1)

    conv2 = Conv2D(ndim*2**1, kernel_size=(4, 4), strides=1, padding='same', kernel_initializer='he_normal')(conv1)
    conv2 = BatchNormalization()(conv2)
    conv2 = activation()(conv2)
    conv2 = MaxPooling2D()(conv2)
    conv2 = Conv2D(ndim*2**1, kernel_size=(4, 4), strides=1, padding='same', kernel_initializer='he_normal')(conv2)
    conv2 = BatchNormalization()(conv2)
    conv2 = activation()(conv2)
    conv2 = MaxPooling2D()(conv2)

    conv3 = Conv2D(ndim*2**2, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv2)
    conv3 = BatchNormalization()(conv3)
    conv3 = activation()(conv3)
    conv3 = MaxPooling2D()(conv3)
    conv3 = Conv2D(ndim*2**2, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv3)
    conv3 = BatchNormalization()(conv3)
    conv3 = activation()(conv3)
    conv3 = MaxPooling2D()(conv3)

    conv4 = Conv2D(ndim*2**3, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv3)
    conv4 = BatchNormalization()(conv4)
    conv4 = activation()(conv4)
    conv4 = MaxPooling2D()(conv4)
    conv4 = Conv2D(ndim*2**3, kernel_size=(3, 3), strides=1, padding='same', kernel_initializer='he_normal')(conv4)
    conv4 = BatchNormalization()(conv4)
    conv4 = activation()(conv4)

    fully = Flatten()(conv4)
    fully = Dense(512)(fully)
    fully = BatchNormalization()(fully)
    fully = activation()(fully)
    fully = Dense(128)(fully)
    fully = BatchNormalization()(fully)
    fully = activation()(fully)
    fully = Dense(32)(fully)
    fully = BatchNormalization()(fully)
    fully = activation()(fully)
    fully = Dense(1, activation='sigmoid')(fully)

    model = tf.keras.models.Model(inputs, fully)

    return model

C. Loss Functions¶

We'll now implement the loss functions for our GAN model. As you might know that we have two loss functions, one for the generator and another for the discriminator.

For our generator, we'll use the L2/MSE loss function.
For optimization, we use the Adam optimizer with a learning rate of 0.001

In [ ]:

cross_entropy = tf.keras.losses.BinaryCrossentropy()
mse = tf.keras.losses.MeanSquaredError()

def discriminator_loss(real_output, fake_output):
    real_loss = cross_entropy(tf.ones_like(real_output), real_output) # - tf.random.uniform( shape=real_output.shape , maxval=0.05) , real_output)
    fake_loss = cross_entropy(tf.zeros_like(fake_output), fake_output) # + tf.random.uniform( shape=fake_output.shape , maxval=0.05), fake_output)
    total_loss = real_loss + fake_loss
    return total_loss

def generator_loss(fake_output , real_y):
    real_y = tf.cast( real_y , 'float32' )
    return mse( fake_output , real_y )

generator_optimizer = tf.keras.optimizers.Adam()
discriminator_optimizer = tf.keras.optimizers.Adam()

generator = get_generator_model(ndim=32)
discriminator = get_discriminator_model(ndim=32)

In [ ]:

# Show generator graph
tf.keras.utils.plot_model(generator, rankdir="TB")

Out[ ]:

In [ ]:

# Show generator summary
generator.summary()

Model: "model_2"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_3 (InputLayer)            [(None, 512, 512, 1) 0                                            
__________________________________________________________________________________________________
conv2d_16 (Conv2D)              (None, 512, 512, 32) 320         input_3[0][0]                    
__________________________________________________________________________________________________
batch_normalization_27 (BatchNo (None, 512, 512, 32) 128         conv2d_16[0][0]                  
__________________________________________________________________________________________________
elu_27 (ELU)                    (None, 512, 512, 32) 0           batch_normalization_27[0][0]     
__________________________________________________________________________________________________
max_pooling2d_14 (MaxPooling2D) (None, 256, 256, 32) 0           elu_27[0][0]                     
__________________________________________________________________________________________________
conv2d_17 (Conv2D)              (None, 256, 256, 32) 9248        max_pooling2d_14[0][0]           
__________________________________________________________________________________________________
batch_normalization_28 (BatchNo (None, 256, 256, 32) 128         conv2d_17[0][0]                  
__________________________________________________________________________________________________
elu_28 (ELU)                    (None, 256, 256, 32) 0           batch_normalization_28[0][0]     
__________________________________________________________________________________________________
max_pooling2d_15 (MaxPooling2D) (None, 128, 128, 32) 0           elu_28[0][0]                     
__________________________________________________________________________________________________
conv2d_18 (Conv2D)              (None, 128, 128, 64) 18496       max_pooling2d_15[0][0]           
__________________________________________________________________________________________________
batch_normalization_29 (BatchNo (None, 128, 128, 64) 256         conv2d_18[0][0]                  
__________________________________________________________________________________________________
elu_29 (ELU)                    (None, 128, 128, 64) 0           batch_normalization_29[0][0]     
__________________________________________________________________________________________________
max_pooling2d_16 (MaxPooling2D) (None, 64, 64, 64)   0           elu_29[0][0]                     
__________________________________________________________________________________________________
conv2d_19 (Conv2D)              (None, 64, 64, 64)   36928       max_pooling2d_16[0][0]           
__________________________________________________________________________________________________
batch_normalization_30 (BatchNo (None, 64, 64, 64)   256         conv2d_19[0][0]                  
__________________________________________________________________________________________________
elu_30 (ELU)                    (None, 64, 64, 64)   0           batch_normalization_30[0][0]     
__________________________________________________________________________________________________
max_pooling2d_17 (MaxPooling2D) (None, 32, 32, 64)   0           elu_30[0][0]                     
__________________________________________________________________________________________________
conv2d_20 (Conv2D)              (None, 32, 32, 128)  73856       max_pooling2d_17[0][0]           
__________________________________________________________________________________________________
batch_normalization_31 (BatchNo (None, 32, 32, 128)  512         conv2d_20[0][0]                  
__________________________________________________________________________________________________
elu_31 (ELU)                    (None, 32, 32, 128)  0           batch_normalization_31[0][0]     
__________________________________________________________________________________________________
max_pooling2d_18 (MaxPooling2D) (None, 16, 16, 128)  0           elu_31[0][0]                     
__________________________________________________________________________________________________
conv2d_21 (Conv2D)              (None, 16, 16, 128)  147584      max_pooling2d_18[0][0]           
__________________________________________________________________________________________________
batch_normalization_32 (BatchNo (None, 16, 16, 128)  512         conv2d_21[0][0]                  
__________________________________________________________________________________________________
elu_32 (ELU)                    (None, 16, 16, 128)  0           batch_normalization_32[0][0]     
__________________________________________________________________________________________________
max_pooling2d_19 (MaxPooling2D) (None, 8, 8, 128)    0           elu_32[0][0]                     
__________________________________________________________________________________________________
conv2d_22 (Conv2D)              (None, 8, 8, 256)    295168      max_pooling2d_19[0][0]           
__________________________________________________________________________________________________
batch_normalization_33 (BatchNo (None, 8, 8, 256)    1024        conv2d_22[0][0]                  
__________________________________________________________________________________________________
elu_33 (ELU)                    (None, 8, 8, 256)    0           batch_normalization_33[0][0]     
__________________________________________________________________________________________________
max_pooling2d_20 (MaxPooling2D) (None, 4, 4, 256)    0           elu_33[0][0]                     
__________________________________________________________________________________________________
conv2d_23 (Conv2D)              (None, 4, 4, 256)    590080      max_pooling2d_20[0][0]           
__________________________________________________________________________________________________
batch_normalization_34 (BatchNo (None, 4, 4, 256)    1024        conv2d_23[0][0]                  
__________________________________________________________________________________________________
elu_34 (ELU)                    (None, 4, 4, 256)    0           batch_normalization_34[0][0]     
__________________________________________________________________________________________________
dropout_1 (Dropout)             (None, 4, 4, 256)    0           elu_34[0][0]                     
__________________________________________________________________________________________________
flatten_2 (Flatten)             (None, 4096)         0           dropout_1[0][0]                  
__________________________________________________________________________________________________
dense_6 (Dense)                 (None, 1024)         4195328     flatten_2[0][0]                  
__________________________________________________________________________________________________
dense_7 (Dense)                 (None, 4096)         4198400     dense_6[0][0]                    
__________________________________________________________________________________________________
reshape_1 (Reshape)             (None, 4, 4, 256)    0           dense_7[0][0]                    
__________________________________________________________________________________________________
conv2d_transpose_9 (Conv2DTrans (None, 4, 4, 256)    590080      reshape_1[0][0]                  
__________________________________________________________________________________________________
concatenate_4 (Concatenate)     (None, 4, 4, 512)    0           elu_34[0][0]                     
                                                                 conv2d_transpose_9[0][0]         
__________________________________________________________________________________________________
batch_normalization_35 (BatchNo (None, 4, 4, 512)    2048        concatenate_4[0][0]              
__________________________________________________________________________________________________
elu_35 (ELU)                    (None, 4, 4, 512)    0           batch_normalization_35[0][0]     
__________________________________________________________________________________________________
up_sampling2d_7 (UpSampling2D)  (None, 8, 8, 512)    0           elu_35[0][0]                     
__________________________________________________________________________________________________
conv2d_transpose_10 (Conv2DTran (None, 8, 8, 256)    1179904     up_sampling2d_7[0][0]            
__________________________________________________________________________________________________
batch_normalization_36 (BatchNo (None, 8, 8, 256)    1024        conv2d_transpose_10[0][0]        
__________________________________________________________________________________________________
elu_36 (ELU)                    (None, 8, 8, 256)    0           batch_normalization_36[0][0]     
__________________________________________________________________________________________________
up_sampling2d_8 (UpSampling2D)  (None, 16, 16, 256)  0           elu_36[0][0]                     
__________________________________________________________________________________________________
conv2d_transpose_11 (Conv2DTran (None, 16, 16, 128)  295040      up_sampling2d_8[0][0]            
__________________________________________________________________________________________________
concatenate_5 (Concatenate)     (None, 16, 16, 256)  0           elu_32[0][0]                     
                                                                 conv2d_transpose_11[0][0]        
__________________________________________________________________________________________________
batch_normalization_37 (BatchNo (None, 16, 16, 256)  1024        concatenate_5[0][0]              
__________________________________________________________________________________________________
elu_37 (ELU)                    (None, 16, 16, 256)  0           batch_normalization_37[0][0]     
__________________________________________________________________________________________________
up_sampling2d_9 (UpSampling2D)  (None, 32, 32, 256)  0           elu_37[0][0]                     
__________________________________________________________________________________________________
conv2d_transpose_12 (Conv2DTran (None, 32, 32, 128)  295040      up_sampling2d_9[0][0]            
__________________________________________________________________________________________________
batch_normalization_38 (BatchNo (None, 32, 32, 128)  512         conv2d_transpose_12[0][0]        
__________________________________________________________________________________________________
elu_38 (ELU)                    (None, 32, 32, 128)  0           batch_normalization_38[0][0]     
__________________________________________________________________________________________________
up_sampling2d_10 (UpSampling2D) (None, 64, 64, 128)  0           elu_38[0][0]                     
__________________________________________________________________________________________________
conv2d_transpose_13 (Conv2DTran (None, 64, 64, 64)   73792       up_sampling2d_10[0][0]           
__________________________________________________________________________________________________
concatenate_6 (Concatenate)     (None, 64, 64, 128)  0           elu_30[0][0]                     
                                                                 conv2d_transpose_13[0][0]        
__________________________________________________________________________________________________
batch_normalization_39 (BatchNo (None, 64, 64, 128)  512         concatenate_6[0][0]              
__________________________________________________________________________________________________
elu_39 (ELU)                    (None, 64, 64, 128)  0           batch_normalization_39[0][0]     
__________________________________________________________________________________________________
up_sampling2d_11 (UpSampling2D) (None, 128, 128, 128 0           elu_39[0][0]                     
__________________________________________________________________________________________________
conv2d_transpose_14 (Conv2DTran (None, 128, 128, 64) 73792       up_sampling2d_11[0][0]           
__________________________________________________________________________________________________
batch_normalization_40 (BatchNo (None, 128, 128, 64) 256         conv2d_transpose_14[0][0]        
__________________________________________________________________________________________________
elu_40 (ELU)                    (None, 128, 128, 64) 0           batch_normalization_40[0][0]     
__________________________________________________________________________________________________
up_sampling2d_12 (UpSampling2D) (None, 256, 256, 64) 0           elu_40[0][0]                     
__________________________________________________________________________________________________
conv2d_transpose_15 (Conv2DTran (None, 256, 256, 32) 18464       up_sampling2d_12[0][0]           
__________________________________________________________________________________________________
concatenate_7 (Concatenate)     (None, 256, 256, 64) 0           elu_28[0][0]                     
                                                                 conv2d_transpose_15[0][0]        
__________________________________________________________________________________________________
batch_normalization_41 (BatchNo (None, 256, 256, 64) 256         concatenate_7[0][0]              
__________________________________________________________________________________________________
elu_41 (ELU)                    (None, 256, 256, 64) 0           batch_normalization_41[0][0]     
__________________________________________________________________________________________________
up_sampling2d_13 (UpSampling2D) (None, 512, 512, 64) 0           elu_41[0][0]                     
__________________________________________________________________________________________________
conv2d_transpose_16 (Conv2DTran (None, 512, 512, 32) 18464       up_sampling2d_13[0][0]           
__________________________________________________________________________________________________
batch_normalization_42 (BatchNo (None, 512, 512, 32) 128         conv2d_transpose_16[0][0]        
__________________________________________________________________________________________________
elu_42 (ELU)                    (None, 512, 512, 32) 0           batch_normalization_42[0][0]     
__________________________________________________________________________________________________
conv2d_transpose_17 (Conv2DTran (None, 512, 512, 3)  867         elu_42[0][0]                     
==================================================================================================
Total params: 12,120,451
Trainable params: 12,115,651
Non-trainable params: 4,800
__________________________________________________________________________________________________

In [ ]:

# Show generator graph
tf.keras.utils.plot_model(discriminator, rankdir="TB")

Out[ ]:

In [ ]:

# Show discrimniator summary
discriminator.summary()

Model: "model_3"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
input_4 (InputLayer)         [(None, 512, 512, 3)]     0         
_________________________________________________________________
conv2d_24 (Conv2D)           (None, 512, 512, 32)      2432      
_________________________________________________________________
batch_normalization_43 (Batc (None, 512, 512, 32)      128       
_________________________________________________________________
elu_43 (ELU)                 (None, 512, 512, 32)      0         
_________________________________________________________________
max_pooling2d_21 (MaxPooling (None, 256, 256, 32)      0         
_________________________________________________________________
conv2d_25 (Conv2D)           (None, 256, 256, 32)      25632     
_________________________________________________________________
batch_normalization_44 (Batc (None, 256, 256, 32)      128       
_________________________________________________________________
elu_44 (ELU)                 (None, 256, 256, 32)      0         
_________________________________________________________________
max_pooling2d_22 (MaxPooling (None, 128, 128, 32)      0         
_________________________________________________________________
conv2d_26 (Conv2D)           (None, 128, 128, 64)      32832     
_________________________________________________________________
batch_normalization_45 (Batc (None, 128, 128, 64)      256       
_________________________________________________________________
elu_45 (ELU)                 (None, 128, 128, 64)      0         
_________________________________________________________________
max_pooling2d_23 (MaxPooling (None, 64, 64, 64)        0         
_________________________________________________________________
conv2d_27 (Conv2D)           (None, 64, 64, 64)        65600     
_________________________________________________________________
batch_normalization_46 (Batc (None, 64, 64, 64)        256       
_________________________________________________________________
elu_46 (ELU)                 (None, 64, 64, 64)        0         
_________________________________________________________________
max_pooling2d_24 (MaxPooling (None, 32, 32, 64)        0         
_________________________________________________________________
conv2d_28 (Conv2D)           (None, 32, 32, 128)       73856     
_________________________________________________________________
batch_normalization_47 (Batc (None, 32, 32, 128)       512       
_________________________________________________________________
elu_47 (ELU)                 (None, 32, 32, 128)       0         
_________________________________________________________________
max_pooling2d_25 (MaxPooling (None, 16, 16, 128)       0         
_________________________________________________________________
conv2d_29 (Conv2D)           (None, 16, 16, 128)       147584    
_________________________________________________________________
batch_normalization_48 (Batc (None, 16, 16, 128)       512       
_________________________________________________________________
elu_48 (ELU)                 (None, 16, 16, 128)       0         
_________________________________________________________________
max_pooling2d_26 (MaxPooling (None, 8, 8, 128)         0         
_________________________________________________________________
conv2d_30 (Conv2D)           (None, 8, 8, 256)         295168    
_________________________________________________________________
batch_normalization_49 (Batc (None, 8, 8, 256)         1024      
_________________________________________________________________
elu_49 (ELU)                 (None, 8, 8, 256)         0         
_________________________________________________________________
max_pooling2d_27 (MaxPooling (None, 4, 4, 256)         0         
_________________________________________________________________
conv2d_31 (Conv2D)           (None, 4, 4, 256)         590080    
_________________________________________________________________
batch_normalization_50 (Batc (None, 4, 4, 256)         1024      
_________________________________________________________________
elu_50 (ELU)                 (None, 4, 4, 256)         0         
_________________________________________________________________
flatten_3 (Flatten)          (None, 4096)              0         
_________________________________________________________________
dense_8 (Dense)              (None, 512)               2097664   
_________________________________________________________________
batch_normalization_51 (Batc (None, 512)               2048      
_________________________________________________________________
elu_51 (ELU)                 (None, 512)               0         
_________________________________________________________________
dense_9 (Dense)              (None, 128)               65664     
_________________________________________________________________
batch_normalization_52 (Batc (None, 128)               512       
_________________________________________________________________
elu_52 (ELU)                 (None, 128)               0         
_________________________________________________________________
dense_10 (Dense)             (None, 32)                4128      
_________________________________________________________________
batch_normalization_53 (Batc (None, 32)                128       
_________________________________________________________________
elu_53 (ELU)                 (None, 32)                0         
_________________________________________________________________
dense_11 (Dense)             (None, 1)                 33        
=================================================================
Total params: 3,407,201
Trainable params: 3,403,937
Non-trainable params: 3,264
_________________________________________________________________

3. Training The GAN¶

So finally, we'll train our GAN on the dataset, we prepared earlier.

In [ ]:

@tf.function
def train_step(input_x, real_y):
   
    with tf.GradientTape() as gen_tape, tf.GradientTape() as disc_tape:
        
        # Generate an image -> G( x )
        generated_images = generator( input_x , training=True)
        
        # Probability that the given image is real -> D( x )
        real_output = discriminator( real_y, training=True)
        
        # Probability that the given image is the one generated -> D( G( x ) )
        generated_output = discriminator(generated_images, training=True)
        
        # L2 Loss -> || y - G(x) ||^2
        gen_loss = generator_loss( generated_images , real_y )

        # Log loss for the discriminator
        disc_loss = discriminator_loss( real_output, generated_output )

    # Collect output
    average_loss = tf.keras.backend.mean(gen_loss)
    sum_loss = gen_loss + disc_loss

    # Compute the gradients
    gradients_of_generator = gen_tape.gradient(gen_loss, generator.trainable_variables)
    gradients_of_discriminator = disc_tape.gradient(disc_loss, discriminator.trainable_variables)

    # Optimize with Adam
    generator_optimizer.apply_gradients(zip(gradients_of_generator, generator.trainable_variables))
    discriminator_optimizer.apply_gradients(zip(gradients_of_discriminator, discriminator.trainable_variables))

    return average_loss, sum_loss

Train Model¶

In [ ]:

# Important parameters
batch_size = 16
num_epochs = 50

In [ ]:

def load_img(fname):
    # Load gray image and scale it to [-0.5, 0.5]
    return plt.imread(fname) / 255. - 0.5

In [ ]:

from skimage.color import *
def load_img_special(fname):

    # Transform color image to different representation than RGB
    return rgb2hsv(plt.imread(fname)) -0.5
    #return rgb2hed(plt.imread(fname))

In [ ]:

# Compute number of epochs which would cover whole dataset
N = np.arange(len(fx_train))
selecters = np.array_split(np.random.permutation(N), len(N)//(batch_size))
selecters = selecters * 3 # Loop through dataset x times
N_tot = len(selecters)

aloss = []
sloss = []

for s in tqdm(range(len(selecters))):
#for s in tqdm(range(num_epochs)):
    
    # Load some images
    x_train = tf.convert_to_tensor(np.array([load_img(fx_train[s]) for i in selecters[s]]))
    y_train = tf.convert_to_tensor(np.array([load_img(fy_train[s]) for i in selecters[s]]))
    #y_train = tf.convert_to_tensor(np.array([load_img_special(fy_train[s]) for i in selecters[s]]))
    
    average_loss, sum_loss = train_step(x_train, y_train)
    
    print('Batch: {:03d}/{:03d}: {:.6f} {:.6f}'.format((s+1), N_tot, average_loss, sum_loss))
    aloss.append(average_loss)
    sloss.append(sum_loss)

Batch: 001/4218: 13.856701 15.454262
Batch: 002/4218: 10.986278 12.817921
Batch: 003/4218: 7.454744 9.181112
Batch: 004/4218: 4.402051 6.114635
Batch: 005/4218: 3.124272 4.673289
Batch: 006/4218: 1.987583 3.624164
Batch: 007/4218: 2.161666 3.797322
Batch: 008/4218: 2.023706 3.555636
Batch: 009/4218: 1.849443 3.377069
Batch: 010/4218: 1.302416 2.799319
Batch: 011/4218: 1.394053 2.852011
Batch: 012/4218: 1.793783 3.229944
Batch: 013/4218: 1.062715 2.493350
Batch: 014/4218: 1.568413 3.055525
Batch: 015/4218: 1.371664 2.865692
Batch: 016/4218: 0.908023 2.349802
Batch: 017/4218: 0.498130 1.995643
Batch: 018/4218: 0.601359 2.048714
Batch: 019/4218: 0.931320 2.361793
Batch: 020/4218: 0.980373 2.386430
Batch: 021/4218: 0.597184 2.034515
Batch: 022/4218: 0.622238 2.025705
Batch: 023/4218: 0.764219 2.157167
Batch: 024/4218: 0.471046 1.914342
Batch: 025/4218: 0.492767 1.892964
Batch: 026/4218: 0.315369 1.726635
Batch: 027/4218: 0.404906 1.792079
Batch: 028/4218: 0.300454 1.697315
Batch: 029/4218: 0.344912 1.727081
Batch: 030/4218: 0.531135 1.906325
Batch: 031/4218: 0.301708 1.673385
Batch: 032/4218: 0.341078 1.713497
Batch: 033/4218: 0.380024 1.733419
Batch: 034/4218: 0.280259 1.663151
Batch: 035/4218: 0.605632 1.976556
Batch: 036/4218: 0.265118 1.629876
Batch: 037/4218: 0.315132 1.671332
Batch: 038/4218: 0.329761 1.684642
Batch: 039/4218: 0.180621 1.519595
Batch: 040/4218: 0.186003 1.543101
Batch: 041/4218: 0.197737 1.530772
Batch: 042/4218: 0.239804 1.582829
Batch: 043/4218: 0.281316 1.628276
Batch: 044/4218: 0.249316 1.568030
Batch: 045/4218: 0.233536 1.555366
Batch: 046/4218: 0.400754 1.716018
Batch: 047/4218: 0.296433 1.594469
Batch: 048/4218: 0.102311 1.418524
Batch: 049/4218: 0.245446 1.570299
Batch: 050/4218: 0.122285 1.422178
Batch: 051/4218: 0.202795 1.493275
Batch: 052/4218: 0.183138 1.462231
Batch: 053/4218: 0.201648 1.497308
Batch: 054/4218: 0.111485 1.374808
Batch: 055/4218: 0.154649 1.435580
Batch: 056/4218: 0.231485 1.513592
Batch: 057/4218: 0.245180 1.529755
Batch: 058/4218: 0.150571 1.439481
Batch: 059/4218: 0.205290 1.495679
Batch: 060/4218: 0.121056 1.374825
Batch: 061/4218: 0.287833 1.533249
Batch: 062/4218: 0.138111 1.386517
Batch: 063/4218: 0.161440 1.413049
Batch: 064/4218: 0.193563 1.436382
Batch: 065/4218: 0.093032 1.347794
Batch: 066/4218: 0.233084 1.467846
Batch: 067/4218: 0.107049 1.338848
Batch: 068/4218: 0.089974 1.328823
Batch: 069/4218: 0.113133 1.335953
Batch: 070/4218: 0.346550 1.561952
Batch: 071/4218: 0.171524 1.394494
Batch: 072/4218: 0.212944 1.423915
Batch: 073/4218: 0.096439 1.310811
Batch: 074/4218: 0.443668 1.659294
Batch: 075/4218: 0.342189 1.546861
Batch: 076/4218: 0.148856 1.371222
Batch: 077/4218: 0.097611 1.291675
Batch: 078/4218: 0.131865 1.321981
Batch: 079/4218: 0.163946 1.339202
Batch: 080/4218: 0.194024 1.400879
Batch: 081/4218: 0.117105 1.284898
Batch: 082/4218: 0.108041 1.283247
Batch: 083/4218: 0.101449 1.322793
Batch: 084/4218: 0.236860 1.408388
Batch: 085/4218: 0.098086 1.254466
Batch: 086/4218: 0.092960 1.247998
Batch: 087/4218: 0.091170 1.247114
Batch: 088/4218: 0.249493 1.391857
Batch: 089/4218: 0.215551 1.360325
Batch: 090/4218: 0.174228 1.326926
Batch: 091/4218: 0.091545 1.233622
Batch: 092/4218: 0.087588 1.223925
Batch: 093/4218: 0.203411 1.323055
Batch: 094/4218: 0.144001 1.277005
Batch: 095/4218: 0.105982 1.240356
Batch: 096/4218: 0.082360 1.225652
Batch: 097/4218: 0.089455 1.213207
Batch: 098/4218: 0.126595 1.236600
Batch: 099/4218: 0.086408 1.183770
Batch: 100/4218: 0.174935 1.278802
Batch: 101/4218: 0.045059 1.136256
Batch: 102/4218: 0.052257 1.157395
Batch: 103/4218: 0.107207 1.224223
Batch: 104/4218: 0.086479 1.177485
Batch: 105/4218: 0.100719 1.197317
Batch: 106/4218: 0.053857 1.133169
Batch: 107/4218: 0.053425 1.150563
Batch: 108/4218: 0.143603 1.234669
Batch: 109/4218: 0.074291 1.159427
Batch: 110/4218: 0.070703 1.152159
Batch: 111/4218: 0.175700 1.240628
Batch: 112/4218: 0.092390 1.170567
Batch: 113/4218: 0.042837 1.116817
Batch: 114/4218: 0.112269 1.178055
Batch: 115/4218: 0.099862 1.152806
Batch: 116/4218: 0.199387 1.251753
Batch: 117/4218: 0.126186 1.197196
Batch: 118/4218: 0.084184 1.128019
Batch: 119/4218: 0.054314 1.093222
Batch: 120/4218: 0.146271 1.186326
Batch: 121/4218: 0.091662 1.118148
Batch: 122/4218: 0.049296 1.079647
Batch: 123/4218: 0.098493 1.122637
Batch: 124/4218: 0.106617 1.137016
Batch: 125/4218: 0.111277 1.131712
Batch: 126/4218: 0.058384 1.068743
Batch: 127/4218: 0.119729 1.166041
Batch: 128/4218: 0.064271 1.066581
Batch: 129/4218: 0.059210 1.073128
Batch: 130/4218: 0.049630 1.066558
Batch: 131/4218: 0.090208 1.089375
Batch: 132/4218: 0.101132 1.091108
Batch: 133/4218: 0.064265 1.051494
Batch: 134/4218: 0.331313 1.311898
Batch: 135/4218: 0.240773 1.246734
Batch: 136/4218: 0.052202 1.080855
Batch: 137/4218: 0.077328 1.044426
Batch: 138/4218: 0.066444 1.027827
Batch: 139/4218: 0.119652 1.099632
Batch: 140/4218: 0.158524 1.119803
Batch: 141/4218: 0.066334 1.032057
Batch: 142/4218: 0.090871 1.060077
Batch: 143/4218: 0.042853 1.014156
Batch: 144/4218: 0.038761 0.990348
Batch: 145/4218: 0.048703 1.016891
Batch: 146/4218: 0.082583 1.024809
Batch: 147/4218: 0.138989 1.081239
Batch: 148/4218: 0.058963 1.013008
Batch: 149/4218: 0.092624 1.091620
Batch: 150/4218: 0.060424 1.029727
Batch: 151/4218: 0.156940 1.124045
Batch: 152/4218: 0.130039 1.050963
Batch: 153/4218: 0.033165 0.971299
Batch: 154/4218: 0.124945 1.050934
Batch: 155/4218: 0.074210 0.997576
Batch: 156/4218: 0.051938 0.986099
Batch: 157/4218: 0.074992 0.993705
Batch: 158/4218: 0.064497 0.997430
Batch: 159/4218: 0.078734 1.014772
Batch: 160/4218: 0.062941 0.959286
Batch: 161/4218: 0.046928 0.983028
Batch: 162/4218: 0.078865 0.984163
Batch: 163/4218: 0.045809 0.959673
Batch: 164/4218: 0.105385 0.998044
Batch: 165/4218: 0.075884 0.969138
Batch: 166/4218: 0.066567 0.969694
Batch: 167/4218: 0.078401 0.984305
Batch: 168/4218: 0.138204 1.020225
Batch: 169/4218: 0.088262 0.990757
Batch: 170/4218: 0.037277 0.927519
Batch: 171/4218: 0.027804 0.904362
Batch: 172/4218: 0.082182 0.937461
Batch: 173/4218: 0.040269 0.904915
Batch: 174/4218: 0.133354 0.988348
Batch: 175/4218: 0.101312 0.966983
Batch: 176/4218: 0.046527 0.894430
Batch: 177/4218: 0.093727 0.940682
Batch: 178/4218: 0.118475 0.993999
Batch: 179/4218: 0.029641 0.869311
Batch: 180/4218: 0.062847 0.924731
Batch: 181/4218: 0.032376 0.875225
Batch: 182/4218: 0.108886 0.960328
Batch: 183/4218: 0.054125 0.917203
Batch: 184/4218: 0.090771 0.923941
Batch: 185/4218: 0.168155 1.015887
Batch: 186/4218: 0.056112 0.899484
Batch: 187/4218: 0.128034 0.957891
Batch: 188/4218: 0.111172 0.931195
Batch: 189/4218: 0.047311 0.888503
Batch: 190/4218: 0.024712 0.851799
Batch: 191/4218: 0.167985 1.008482
Batch: 192/4218: 0.049678 0.864771
Batch: 193/4218: 0.071591 0.887584
Batch: 194/4218: 0.055182 0.859893
Batch: 195/4218: 0.052400 0.863048
Batch: 196/4218: 0.089520 0.888288
Batch: 197/4218: 0.037943 0.826063
Batch: 198/4218: 0.038038 0.836784
Batch: 199/4218: 0.030777 0.817343
Batch: 200/4218: 0.123611 0.936888
Batch: 201/4218: 0.233119 1.022120
Batch: 202/4218: 0.037024 0.887185
Batch: 203/4218: 0.058741 0.831857
Batch: 204/4218: 0.146840 0.951622
Batch: 205/4218: 0.044978 0.812416
Batch: 206/4218: 0.048381 0.812366
Batch: 207/4218: 0.036067 0.795385
Batch: 208/4218: 0.058816 0.814006
Batch: 209/4218: 0.039009 0.785778
Batch: 210/4218: 0.111369 0.871913
Batch: 211/4218: 0.068702 0.834637
Batch: 212/4218: 0.037100 0.791611
Batch: 213/4218: 0.173835 0.924401
Batch: 214/4218: 0.076798 0.832236
Batch: 215/4218: 0.044005 0.794190
Batch: 216/4218: 0.041023 0.778215
Batch: 217/4218: 0.038289 0.764170
Batch: 218/4218: 0.053522 0.826872
Batch: 219/4218: 0.052402 0.825992
Batch: 220/4218: 0.035772 0.771111
Batch: 221/4218: 0.073638 0.870629
Batch: 222/4218: 0.035696 0.773147
Batch: 223/4218: 0.137173 0.874571
Batch: 224/4218: 0.052829 0.786993
Batch: 225/4218: 0.044698 0.787712
Batch: 226/4218: 0.040612 0.767061
Batch: 227/4218: 0.080575 0.787847
Batch: 228/4218: 0.050670 0.764879
Batch: 229/4218: 0.043405 0.763794
Batch: 230/4218: 0.034538 0.769911
Batch: 231/4218: 0.069365 0.796040
Batch: 232/4218: 0.082797 0.781303
Batch: 233/4218: 0.056238 0.751265
Batch: 234/4218: 0.102821 0.802699
Batch: 235/4218: 0.045881 0.763727
Batch: 236/4218: 0.029639 0.744727
Batch: 237/4218: 0.035177 0.727046
Batch: 238/4218: 0.028744 0.717166
Batch: 239/4218: 0.050074 0.759753
Batch: 240/4218: 0.055833 0.762171
Batch: 241/4218: 0.082635 0.765642
Batch: 242/4218: 0.186733 0.919128
Batch: 243/4218: 0.028648 0.696209
Batch: 244/4218: 0.149510 0.885773
Batch: 245/4218: 0.116656 0.800736
Batch: 246/4218: 0.047961 0.702975
Batch: 247/4218: 0.062003 0.776219
Batch: 248/4218: 0.058989 0.769619
Batch: 249/4218: 0.085996 0.740494
Batch: 250/4218: 0.157650 0.813484
Batch: 251/4218: 0.068998 0.829157
Batch: 252/4218: 0.087388 0.754065
Batch: 253/4218: 0.051585 0.680003
Batch: 254/4218: 0.057775 0.776389
Batch: 255/4218: 0.128178 0.768458
Batch: 256/4218: 0.076805 0.718558
Batch: 257/4218: 0.035096 0.671449
Batch: 258/4218: 0.051158 0.685008
Batch: 259/4218: 0.031265 0.705975
Batch: 260/4218: 0.082673 0.726901
Batch: 261/4218: 0.024038 0.677514
Batch: 262/4218: 0.056531 0.684789
Batch: 263/4218: 0.033263 0.659765
Batch: 264/4218: 0.069076 0.695312
Batch: 265/4218: 0.043478 0.671683
Batch: 266/4218: 0.114625 0.736562
Batch: 267/4218: 0.050083 0.652658
Batch: 268/4218: 0.068535 0.702389
Batch: 269/4218: 0.118984 0.745972
Batch: 270/4218: 0.031189 0.630832
Batch: 271/4218: 0.049048 0.675762
Batch: 272/4218: 0.144616 0.750289
Batch: 273/4218: 0.072787 0.679020
Batch: 274/4218: 0.031517 0.635234
Batch: 275/4218: 0.075902 0.674037
Batch: 276/4218: 0.138643 0.728850
Batch: 277/4218: 0.076558 0.732993
Batch: 278/4218: 0.030286 0.606528
Batch: 279/4218: 0.036831 0.613326
Batch: 280/4218: 0.067895 0.687956
Batch: 281/4218: 0.048302 0.633050
Batch: 282/4218: 0.063257 0.718956
Batch: 283/4218: 0.063943 0.658569
Batch: 284/4218: 0.026701 0.599100
Batch: 285/4218: 0.054164 0.647080
Batch: 286/4218: 0.024692 0.594709
Batch: 287/4218: 0.060370 0.625603
Batch: 288/4218: 0.065067 0.628812
Batch: 289/4218: 0.080985 0.654953
Batch: 290/4218: 0.039922 0.719577
Batch: 291/4218: 0.061480 0.724108
Batch: 292/4218: 0.031769 0.619242
Batch: 293/4218: 0.039558 0.597645
Batch: 294/4218: 0.072920 0.686422
Batch: 295/4218: 0.135671 0.731324
Batch: 296/4218: 0.057398 0.612636
Batch: 297/4218: 0.032374 0.598770
Batch: 298/4218: 0.086092 0.640489
Batch: 299/4218: 0.024876 0.589416
Batch: 300/4218: 0.026946 0.577420
Batch: 301/4218: 0.105223 0.664532
Batch: 302/4218: 0.037693 0.618551
Batch: 303/4218: 0.036950 0.574248
Batch: 304/4218: 0.030781 0.586649
Batch: 305/4218: 0.027840 0.572971
Batch: 306/4218: 0.042987 0.611968
Batch: 307/4218: 0.031451 0.558902
Batch: 308/4218: 0.046370 0.586300
Batch: 309/4218: 0.035681 0.561618
Batch: 310/4218: 0.034300 0.563284
Batch: 311/4218: 0.050328 0.590532
Batch: 312/4218: 0.160565 0.737029
Batch: 313/4218: 0.054479 0.577242
Batch: 314/4218: 0.014887 0.541087
Batch: 315/4218: 0.033693 0.601780
Batch: 316/4218: 0.022889 0.557918
Batch: 317/4218: 0.048733 0.573914
Batch: 318/4218: 0.044484 0.625233
Batch: 319/4218: 0.081570 0.625144
Batch: 320/4218: 0.090692 0.629298
Batch: 321/4218: 0.014555 0.534712
Batch: 322/4218: 0.021374 0.520132
Batch: 323/4218: 0.086177 0.621685
Batch: 324/4218: 0.026149 0.538237
Batch: 325/4218: 0.112204 0.622566
Batch: 326/4218: 0.037280 0.617480
Batch: 327/4218: 0.068074 0.583015
Batch: 328/4218: 0.037859 0.520562
Batch: 329/4218: 0.045806 0.534194
Batch: 330/4218: 0.066839 0.554783
Batch: 331/4218: 0.051808 0.555649
Batch: 332/4218: 0.027295 0.529350
Batch: 333/4218: 0.055648 0.720054
Batch: 334/4218: 0.039900 0.531580
Batch: 335/4218: 0.033167 0.554087
Batch: 336/4218: 0.047467 0.558034
Batch: 337/4218: 0.061101 0.549596
Batch: 338/4218: 0.046971 0.527928
Batch: 339/4218: 0.028814 0.545569
Batch: 340/4218: 0.056300 0.552978
Batch: 341/4218: 0.021645 0.526122
Batch: 342/4218: 0.023071 0.492118
Batch: 343/4218: 0.034766 0.542000
Batch: 344/4218: 0.077048 0.590461
Batch: 345/4218: 0.077626 0.608494
Batch: 346/4218: 0.028976 0.522687
Batch: 347/4218: 0.024750 0.491450
Batch: 348/4218: 0.024349 0.609526
Batch: 349/4218: 0.041196 0.588995
Batch: 350/4218: 0.030725 0.544839
Batch: 351/4218: 0.019872 0.512249
Batch: 352/4218: 0.017137 0.472333
Batch: 353/4218: 0.059990 0.513582
Batch: 354/4218: 0.036246 0.609909
Batch: 355/4218: 0.071666 0.524304
Batch: 356/4218: 0.041028 0.525423
Batch: 357/4218: 0.047644 0.487292
Batch: 358/4218: 0.047913 0.513762
Batch: 359/4218: 0.029818 0.473574
Batch: 360/4218: 0.069502 0.527130
Batch: 361/4218: 0.038691 0.497575
Batch: 362/4218: 0.127165 0.585395
Batch: 363/4218: 0.026837 0.559304
Batch: 364/4218: 0.041754 0.510631
Batch: 365/4218: 0.101476 0.567239
Batch: 366/4218: 0.023372 0.455512
Batch: 367/4218: 0.037481 0.452655
Batch: 368/4218: 0.051915 0.490963
Batch: 369/4218: 0.055099 0.493270
Batch: 370/4218: 0.019741 0.449962
Batch: 371/4218: 0.012514 0.466106
Batch: 372/4218: 0.009010 0.444391
Batch: 373/4218: 0.017262 0.433438
Batch: 374/4218: 0.071054 0.498948
Batch: 375/4218: 0.041987 0.446457
Batch: 376/4218: 0.040323 0.450267
Batch: 377/4218: 0.044558 0.479723
Batch: 378/4218: 0.164799 0.583571
Batch: 379/4218: 0.033784 0.433319
Batch: 380/4218: 0.088790 0.487988
Batch: 381/4218: 0.047879 0.436618
Batch: 382/4218: 0.072804 0.549519
Batch: 383/4218: 0.020526 0.420567
Batch: 384/4218: 0.037450 0.494912
Batch: 385/4218: 0.087198 0.505383
Batch: 386/4218: 0.050463 0.457784
Batch: 387/4218: 0.025777 0.415773
Batch: 388/4218: 0.032467 0.486336
Batch: 389/4218: 0.070688 0.522021
Batch: 390/4218: 0.028750 0.408846
Batch: 391/4218: 0.068303 0.456363
Batch: 392/4218: 0.062421 0.460898
Batch: 393/4218: 0.027028 0.444309
Batch: 394/4218: 0.017248 0.420890
Batch: 395/4218: 0.050461 0.461783
Batch: 396/4218: 0.059601 0.427065
Batch: 397/4218: 0.038640 0.442173
Batch: 398/4218: 0.037084 0.421876
Batch: 399/4218: 0.077881 0.527891
Batch: 400/4218: 0.025648 0.407092
Batch: 401/4218: 0.071163 0.461677
Batch: 402/4218: 0.052142 0.430967
Batch: 403/4218: 0.019320 0.405776
Batch: 404/4218: 0.177066 0.569820
Batch: 405/4218: 0.039172 0.492124
Batch: 406/4218: 0.055211 0.428641
Batch: 407/4218: 0.055858 0.415477
Batch: 408/4218: 0.034024 0.388533
Batch: 409/4218: 0.052845 0.443575
Batch: 410/4218: 0.018359 0.412439
Batch: 411/4218: 0.043169 0.405011
Batch: 412/4218: 0.128502 0.492952
Batch: 413/4218: 0.025300 0.397882
Batch: 414/4218: 0.036516 0.392417
Batch: 415/4218: 0.053173 0.420198
Batch: 416/4218: 0.034226 0.425076
Batch: 417/4218: 0.040892 0.388533
Batch: 418/4218: 0.139009 0.573431
Batch: 419/4218: 0.049320 0.398533
Batch: 420/4218: 0.066080 0.427480
Batch: 421/4218: 0.034267 0.438880
Batch: 422/4218: 0.084150 0.423888
Batch: 423/4218: 0.060874 0.419748
Batch: 424/4218: 0.184239 0.579053
Batch: 425/4218: 0.023371 0.379329
Batch: 426/4218: 0.029470 0.395160
Batch: 427/4218: 0.057724 0.494757
Batch: 428/4218: 0.014473 0.371438
Batch: 429/4218: 0.056687 0.413255
Batch: 430/4218: 0.039960 0.389704
Batch: 431/4218: 0.030860 0.429843
Batch: 432/4218: 0.031664 0.385488
Batch: 433/4218: 0.035797 0.394355
Batch: 434/4218: 0.040855 0.390282
Batch: 435/4218: 0.046704 0.370083
Batch: 436/4218: 0.104443 0.436848
Batch: 437/4218: 0.024097 0.364966
Batch: 438/4218: 0.037916 0.357627
Batch: 439/4218: 0.030329 0.380393
Batch: 440/4218: 0.035271 0.360474
Batch: 441/4218: 0.011278 0.341002
Batch: 442/4218: 0.030547 0.353568
Batch: 443/4218: 0.063360 0.393963
Batch: 444/4218: 0.062839 0.380479
Batch: 445/4218: 0.011814 0.324709
Batch: 446/4218: 0.033553 0.353091
Batch: 447/4218: 0.028125 0.342681
Batch: 448/4218: 0.039466 0.350920
Batch: 449/4218: 0.189668 0.501600
Batch: 450/4218: 0.056011 0.370427
Batch: 451/4218: 0.028018 0.343776
Batch: 452/4218: 0.039442 0.362928
Batch: 453/4218: 0.048910 0.387684
Batch: 454/4218: 0.016903 0.315354
Batch: 455/4218: 0.020597 0.339760
Batch: 456/4218: 0.019775 0.360318
Batch: 457/4218: 0.052005 0.355874
Batch: 458/4218: 0.021425 0.349895
Batch: 459/4218: 0.053178 0.393145
Batch: 460/4218: 0.034137 0.333171
Batch: 461/4218: 0.020572 0.332537
Batch: 462/4218: 0.029884 0.323750
Batch: 463/4218: 0.134368 0.436595
Batch: 464/4218: 0.036219 0.336945
Batch: 465/4218: 0.025647 0.303361
Batch: 466/4218: 0.066326 0.355968
Batch: 467/4218: 0.156138 0.480860
Batch: 468/4218: 0.020887 0.320537
Batch: 469/4218: 0.032030 0.338577
Batch: 470/4218: 0.016611 0.318913
Batch: 471/4218: 0.164376 0.475411
Batch: 472/4218: 0.063436 0.373734
Batch: 473/4218: 0.094818 0.388641
Batch: 474/4218: 0.039776 0.372967
Batch: 475/4218: 0.023928 0.350587
Batch: 476/4218: 0.065861 0.405515
Batch: 477/4218: 0.124855 0.436742
Batch: 478/4218: 0.034131 0.353389
Batch: 479/4218: 0.018371 0.299512
Batch: 480/4218: 0.120680 0.395454
Batch: 481/4218: 0.024326 0.364964
Batch: 482/4218: 0.032814 0.301656
Batch: 483/4218: 0.058845 0.338724
Batch: 484/4218: 0.036654 0.308638
Batch: 485/4218: 0.186901 0.482038
Batch: 486/4218: 0.017233 0.331526
Batch: 487/4218: 0.031199 0.365737
Batch: 488/4218: 0.046246 0.357720
Batch: 489/4218: 0.025812 0.295559
Batch: 490/4218: 0.065777 0.372408
Batch: 491/4218: 0.016136 0.293832
Batch: 492/4218: 0.078894 0.381735
Batch: 493/4218: 0.048229 0.317666
Batch: 494/4218: 0.121480 0.392773
Batch: 495/4218: 0.071644 0.385931
Batch: 496/4218: 0.037247 0.325259
Batch: 497/4218: 0.050171 0.334137
Batch: 498/4218: 0.011645 0.285850
Batch: 499/4218: 0.029062 0.297956
Batch: 500/4218: 0.014704 0.338370
Batch: 501/4218: 0.017060 0.311403
Batch: 502/4218: 0.071212 0.349204
Batch: 503/4218: 0.043803 0.311077
Batch: 504/4218: 0.054990 0.317852
Batch: 505/4218: 0.028525 0.290620
Batch: 506/4218: 0.060108 0.339634
Batch: 507/4218: 0.038095 0.285014
Batch: 508/4218: 0.023543 0.283761
Batch: 509/4218: 0.068664 0.336707
Batch: 510/4218: 0.134923 0.386232
Batch: 511/4218: 0.026510 0.288499
Batch: 512/4218: 0.024702 0.264827
Batch: 513/4218: 0.055940 0.313343
Batch: 514/4218: 0.018087 0.285201
Batch: 515/4218: 0.031715 0.293253
Batch: 516/4218: 0.035281 0.281992
Batch: 517/4218: 0.036245 0.304459
Batch: 518/4218: 0.070413 0.336683
Batch: 519/4218: 0.041063 0.291203
Batch: 520/4218: 0.054473 0.305013
Batch: 521/4218: 0.029280 0.282105
Batch: 522/4218: 0.035093 0.263832
Batch: 523/4218: 0.038822 0.268530
Batch: 524/4218: 0.015707 0.256412
Batch: 525/4218: 0.017872 0.254012
Batch: 526/4218: 0.014534 0.278854
Batch: 527/4218: 0.008151 0.344734
Batch: 528/4218: 0.025792 0.269487
Batch: 529/4218: 0.044884 0.350579
Batch: 530/4218: 0.088780 0.313946
Batch: 531/4218: 0.037060 0.283344
Batch: 532/4218: 0.053251 0.282018
Batch: 533/4218: 0.012673 0.348438
Batch: 534/4218: 0.085211 0.319478
Batch: 535/4218: 0.014160 0.277744
Batch: 536/4218: 0.024236 0.262764
Batch: 537/4218: 0.019083 0.245593
Batch: 538/4218: 0.083769 0.319274
Batch: 539/4218: 0.038989 0.319583
Batch: 540/4218: 0.030357 0.304778
Batch: 541/4218: 0.019887 0.256451
Batch: 542/4218: 0.020007 0.248510
Batch: 543/4218: 0.030862 0.271105
Batch: 544/4218: 0.043999 0.252283
Batch: 545/4218: 0.037563 0.282682
Batch: 546/4218: 0.051323 0.334415
Batch: 547/4218: 0.037681 0.267756
Batch: 548/4218: 0.025372 0.261211
Batch: 549/4218: 0.042675 0.261489
Batch: 550/4218: 0.031476 0.277922
Batch: 551/4218: 0.016920 0.242294
Batch: 552/4218: 0.023993 0.251862
Batch: 553/4218: 0.027332 0.251961
Batch: 554/4218: 0.042208 0.266245
Batch: 555/4218: 0.024834 0.249549
Batch: 556/4218: 0.031715 0.271529
Batch: 557/4218: 0.064386 0.294317
Batch: 558/4218: 0.037235 0.356657
Batch: 559/4218: 0.012180 0.260820
Batch: 560/4218: 0.058602 0.275777
Batch: 561/4218: 0.027400 0.241351
Batch: 562/4218: 0.054992 0.268989
Batch: 563/4218: 0.026149 0.237975
Batch: 564/4218: 0.040542 0.247159
Batch: 565/4218: 0.025100 0.264253
Batch: 566/4218: 0.019759 0.219543
Batch: 567/4218: 0.053445 0.257508
Batch: 568/4218: 0.043606 0.240672
Batch: 569/4218: 0.037256 0.241759
Batch: 570/4218: 0.040315 0.259426
Batch: 571/4218: 0.065802 0.265458
Batch: 572/4218: 0.115232 0.329949
Batch: 573/4218: 0.091332 0.296759
Batch: 574/4218: 0.029852 0.263328
Batch: 575/4218: 0.032891 0.228668
Batch: 576/4218: 0.045805 0.258928
Batch: 577/4218: 0.080173 0.275510
Batch: 578/4218: 0.071286 0.321292
Batch: 579/4218: 0.058002 0.248624
Batch: 580/4218: 0.013194 0.257758
Batch: 581/4218: 0.024898 0.217445
Batch: 582/4218: 0.039948 0.249051
Batch: 583/4218: 0.029892 0.283862
Batch: 584/4218: 0.026045 0.226779
Batch: 585/4218: 0.022613 0.224326
Batch: 586/4218: 0.115028 0.311760
Batch: 587/4218: 0.022768 0.220144
Batch: 588/4218: 0.022550 0.236854
Batch: 589/4218: 0.022681 0.225351
Batch: 590/4218: 0.023687 0.225824
Batch: 591/4218: 0.064361 0.301493
Batch: 592/4218: 0.032717 0.257384
Batch: 593/4218: 0.033425 0.222805
Batch: 594/4218: 0.133248 0.324308
Batch: 595/4218: 0.029316 0.252560
Batch: 596/4218: 0.014587 0.207110
Batch: 597/4218: 0.021136 0.218578
Batch: 598/4218: 0.029232 0.210991
Batch: 599/4218: 0.068071 0.278781
Batch: 600/4218: 0.025129 0.208471
Batch: 601/4218: 0.034615 0.224631
Batch: 602/4218: 0.017809 0.194908
Batch: 603/4218: 0.038051 0.217667
Batch: 604/4218: 0.080437 0.300117
Batch: 605/4218: 0.044343 0.245437
Batch: 606/4218: 0.019119 0.234474
Batch: 607/4218: 0.190753 0.396555
Batch: 608/4218: 0.017774 0.201562
Batch: 609/4218: 0.180040 0.354261
Batch: 610/4218: 0.060428 0.267280
Batch: 611/4218: 0.040965 0.252472
Batch: 612/4218: 0.100041 0.306947
Batch: 613/4218: 0.072056 0.272183
Batch: 614/4218: 0.034365 0.206218
Batch: 615/4218: 0.016011 0.189593
Batch: 616/4218: 0.018187 0.206534
Batch: 617/4218: 0.018353 0.207436
Batch: 618/4218: 0.045050 0.261868
Batch: 619/4218: 0.072537 0.246157
Batch: 620/4218: 0.028154 0.203016
Batch: 621/4218: 0.016593 0.230201
Batch: 622/4218: 0.071746 0.258521
Batch: 623/4218: 0.021978 0.212559
Batch: 624/4218: 0.015367 0.181947
Batch: 625/4218: 0.037884 0.200610
Batch: 626/4218: 0.017500 0.206983
Batch: 627/4218: 0.033276 0.227146
Batch: 628/4218: 0.039479 0.224850
Batch: 629/4218: 0.133723 0.301209
Batch: 630/4218: 0.037666 0.199483
Batch: 631/4218: 0.013144 0.186889
Batch: 632/4218: 0.017758 0.183000
Batch: 633/4218: 0.192638 0.355373
Batch: 634/4218: 0.027405 0.243077
Batch: 635/4218: 0.021121 0.184867
Batch: 636/4218: 0.030996 0.204688
Batch: 637/4218: 0.133230 0.309471
Batch: 638/4218: 0.059750 0.213033
Batch: 639/4218: 0.074320 0.241017
Batch: 640/4218: 0.022458 0.175427
Batch: 641/4218: 0.032228 0.191384
Batch: 642/4218: 0.289373 0.467930
Batch: 643/4218: 0.020476 0.184630
Batch: 644/4218: 0.016208 0.168035
Batch: 645/4218: 0.108422 0.263559
Batch: 646/4218: 0.148635 0.303987
Batch: 647/4218: 0.022625 0.176219
Batch: 648/4218: 0.030200 0.210577
Batch: 649/4218: 0.044786 0.214733
Batch: 650/4218: 0.021419 0.180666
Batch: 651/4218: 0.096662 0.259788
Batch: 652/4218: 0.021073 0.177357
Batch: 653/4218: 0.019165 0.188473
Batch: 654/4218: 0.027127 0.173385
Batch: 655/4218: 0.041717 0.191027
Batch: 656/4218: 0.025714 0.182641
Batch: 657/4218: 0.033660 0.181630
Batch: 658/4218: 0.023320 0.213900
Batch: 659/4218: 0.019830 0.227436
Batch: 660/4218: 0.058336 0.242992
Batch: 661/4218: 0.050016 0.209949
Batch: 662/4218: 0.060655 0.230405
Batch: 663/4218: 0.019228 0.180209
Batch: 664/4218: 0.026780 0.195618
Batch: 665/4218: 0.049700 0.233490
Batch: 666/4218: 0.025069 0.170246
Batch: 667/4218: 0.062024 0.267917
Batch: 668/4218: 0.048129 0.209870
Batch: 669/4218: 0.054867 0.208978
Batch: 670/4218: 0.010995 0.156749
Batch: 671/4218: 0.044066 0.195563
Batch: 672/4218: 0.042293 0.180038
Batch: 673/4218: 0.026738 0.181088
Batch: 674/4218: 0.129570 0.308964
Batch: 675/4218: 0.055758 0.211064
Batch: 676/4218: 0.015397 0.168611
Batch: 677/4218: 0.024995 0.158535
Batch: 678/4218: 0.024491 0.170029
Batch: 679/4218: 0.038683 0.228839
Batch: 680/4218: 0.134133 0.283405
Batch: 681/4218: 0.050218 0.195351
Batch: 682/4218: 0.047527 0.202971
Batch: 683/4218: 0.065623 0.217490
Batch: 684/4218: 0.024010 0.159188
Batch: 685/4218: 0.069499 0.230079
Batch: 686/4218: 0.022050 0.168307
Batch: 687/4218: 0.048678 0.192185
Batch: 688/4218: 0.041620 0.192135
Batch: 689/4218: 0.016950 0.165812
Batch: 690/4218: 0.115422 0.258891
Batch: 691/4218: 0.020796 0.170040
Batch: 692/4218: 0.016234 0.147266
Batch: 693/4218: 0.017864 0.170975
Batch: 694/4218: 0.016260 0.162825
Batch: 695/4218: 0.023763 0.208020
Batch: 696/4218: 0.089244 0.232566
Batch: 697/4218: 0.020689 0.146034
Batch: 698/4218: 0.028680 0.157170
Batch: 699/4218: 0.055541 0.231441
Batch: 700/4218: 0.073539 0.205316
Batch: 701/4218: 0.020593 0.173341
Batch: 702/4218: 0.026835 0.185600
Batch: 703/4218: 0.018497 0.164174
Batch: 704/4218: 0.058399 0.195539
Batch: 705/4218: 0.237675 0.371267
Batch: 706/4218: 0.039429 0.174451
Batch: 707/4218: 0.032429 0.188781
Batch: 708/4218: 0.070972 0.223581
Batch: 709/4218: 0.046336 0.174627
Batch: 710/4218: 0.027288 0.174669
Batch: 711/4218: 0.026738 0.158626
Batch: 712/4218: 0.079032 0.219872
Batch: 713/4218: 0.029775 0.165811
Batch: 714/4218: 0.020565 0.143653
Batch: 715/4218: 0.034883 0.240914
Batch: 716/4218: 0.058872 0.216098
Batch: 717/4218: 0.013553 0.159718
Batch: 718/4218: 0.073685 0.198425
Batch: 719/4218: 0.028806 0.190699
Batch: 720/4218: 0.015571 0.163880
Batch: 721/4218: 0.052053 0.189408
Batch: 722/4218: 0.029551 0.150266
Batch: 723/4218: 0.053159 0.198787
Batch: 724/4218: 0.067927 0.185583
Batch: 725/4218: 0.014851 0.137235
Batch: 726/4218: 0.066891 0.181775
Batch: 727/4218: 0.042577 0.156257
Batch: 728/4218: 0.029935 0.159162
Batch: 729/4218: 0.026869 0.163661
Batch: 730/4218: 0.099266 0.236914
Batch: 731/4218: 0.155747 0.285034
Batch: 732/4218: 0.063980 0.206185
Batch: 733/4218: 0.076772 0.194626
Batch: 734/4218: 0.012256 0.149376
Batch: 735/4218: 0.014872 0.138274
Batch: 736/4218: 0.021186 0.143840
Batch: 737/4218: 0.019286 0.150224
Batch: 738/4218: 0.039956 0.201934
Batch: 739/4218: 0.047021 0.186516
Batch: 740/4218: 0.047711 0.196257
Batch: 741/4218: 0.018773 0.127712
Batch: 742/4218: 0.045411 0.213344
Batch: 743/4218: 0.011388 0.129930
Batch: 744/4218: 0.013503 0.133709
Batch: 745/4218: 0.021456 0.133206
Batch: 746/4218: 0.035356 0.166682
Batch: 747/4218: 0.267117 0.386626
Batch: 748/4218: 0.031232 0.167074
Batch: 749/4218: 0.067737 0.223322
Batch: 750/4218: 0.068459 0.194193
Batch: 751/4218: 0.039615 0.149219
Batch: 752/4218: 0.011985 0.140572
Batch: 753/4218: 0.027171 0.155659
Batch: 754/4218: 0.035188 0.155601
Batch: 755/4218: 0.039880 0.170787
Batch: 756/4218: 0.019636 0.139228
Batch: 757/4218: 0.097991 0.247332
Batch: 758/4218: 0.023815 0.145850
Batch: 759/4218: 0.021378 0.139303
Batch: 760/4218: 0.018410 0.124361
Batch: 761/4218: 0.050894 0.170269
Batch: 762/4218: 0.014084 0.129563
Batch: 763/4218: 0.018623 0.139922
Batch: 764/4218: 0.011028 0.178331
Batch: 765/4218: 0.030079 0.153980
Batch: 766/4218: 0.035322 0.161255
Batch: 767/4218: 0.016613 0.160191
Batch: 768/4218: 0.033556 0.153748
Batch: 769/4218: 0.044307 0.157625
Batch: 770/4218: 0.027255 0.155228
Batch: 771/4218: 0.019589 0.141582
Batch: 772/4218: 0.091171 0.206075
Batch: 773/4218: 0.051895 0.155846
Batch: 774/4218: 0.026943 0.144899
Batch: 775/4218: 0.015237 0.136641
Batch: 776/4218: 0.010796 0.181218
Batch: 777/4218: 0.013033 0.109897
Batch: 778/4218: 0.010473 0.114002
Batch: 779/4218: 0.035690 0.143066
Batch: 780/4218: 0.006789 0.102120
Batch: 781/4218: 0.035457 0.140522
Batch: 782/4218: 0.031875 0.135134
Batch: 783/4218: 0.044933 0.161846
Batch: 784/4218: 0.147966 0.265109
Batch: 785/4218: 0.056778 0.152738
Batch: 786/4218: 0.027750 0.159987
Batch: 787/4218: 0.045533 0.189843
Batch: 788/4218: 0.031870 0.142221
Batch: 789/4218: 0.057399 0.161750
Batch: 790/4218: 0.048294 0.159510
Batch: 791/4218: 0.011296 0.112007
Batch: 792/4218: 0.055318 0.170932
Batch: 793/4218: 0.030385 0.142009
Batch: 794/4218: 0.114553 0.217869
Batch: 795/4218: 0.030809 0.149211
Batch: 796/4218: 0.038029 0.144375
Batch: 797/4218: 0.023312 0.124475
Batch: 798/4218: 0.037181 0.132678
Batch: 799/4218: 0.032681 0.132714
Batch: 800/4218: 0.040429 0.138819
Batch: 801/4218: 0.093574 0.193869
Batch: 802/4218: 0.125453 0.223177
Batch: 803/4218: 0.031946 0.133434
Batch: 804/4218: 0.087448 0.184490
Batch: 805/4218: 0.020094 0.113241
Batch: 806/4218: 0.011819 0.109013
Batch: 807/4218: 0.037596 0.154375
Batch: 808/4218: 0.013803 0.123540
Batch: 809/4218: 0.014749 0.125450
Batch: 810/4218: 0.016055 0.109857
Batch: 811/4218: 0.035962 0.134785
Batch: 812/4218: 0.044541 0.140933
Batch: 813/4218: 0.037757 0.145884
Batch: 814/4218: 0.016604 0.115754
Batch: 815/4218: 0.157820 0.261003
Batch: 816/4218: 0.015884 0.130349
Batch: 817/4218: 0.010820 0.113903
Batch: 818/4218: 0.066222 0.162578
Batch: 819/4218: 0.021902 0.120227
Batch: 820/4218: 0.036352 0.130114
Batch: 821/4218: 0.021184 0.114858
Batch: 822/4218: 0.015496 0.111809
Batch: 823/4218: 0.048632 0.155165
Batch: 824/4218: 0.170108 0.275541
Batch: 825/4218: 0.045546 0.141059
Batch: 826/4218: 0.020643 0.107029
Batch: 827/4218: 0.025133 0.121916
Batch: 828/4218: 0.038460 0.130758
Batch: 829/4218: 0.018661 0.110555
Batch: 830/4218: 0.040098 0.139208
Batch: 831/4218: 0.059567 0.172009
Batch: 832/4218: 0.019105 0.112181
Batch: 833/4218: 0.019787 0.108879
Batch: 834/4218: 0.028470 0.114759
Batch: 835/4218: 0.011800 0.095168
Batch: 836/4218: 0.099533 0.188372
Batch: 837/4218: 0.084681 0.175742
Batch: 838/4218: 0.047299 0.127311
Batch: 839/4218: 0.021561 0.114525
Batch: 840/4218: 0.021891 0.124919
Batch: 841/4218: 0.033323 0.130645
Batch: 842/4218: 0.022343 0.119808
Batch: 843/4218: 0.034208 0.117352
Batch: 844/4218: 0.036514 0.122132
Batch: 845/4218: 0.022900 0.129070
Batch: 846/4218: 0.017380 0.107603
Batch: 847/4218: 0.021283 0.111432
Batch: 848/4218: 0.009609 0.120336
Batch: 849/4218: 0.099097 0.213619
Batch: 850/4218: 0.007484 0.091812
Batch: 851/4218: 0.020808 0.105746
Batch: 852/4218: 0.025997 0.104927
Batch: 853/4218: 0.026208 0.108875
Batch: 854/4218: 0.045980 0.133312
Batch: 855/4218: 0.026136 0.108083
Batch: 856/4218: 0.081890 0.206575
Batch: 857/4218: 0.012774 0.093422
Batch: 858/4218: 0.030247 0.117094
Batch: 859/4218: 0.018763 0.102087
Batch: 860/4218: 0.043755 0.126805
Batch: 861/4218: 0.115529 0.214366
Batch: 862/4218: 0.017000 0.110789
Batch: 863/4218: 0.030568 0.118805
Batch: 864/4218: 0.033767 0.121836
Batch: 865/4218: 0.030430 0.128579
Batch: 866/4218: 0.055055 0.143377
Batch: 867/4218: 0.025229 0.106043
Batch: 868/4218: 0.041094 0.140466
Batch: 869/4218: 0.047252 0.126841
Batch: 870/4218: 0.020911 0.106927
Batch: 871/4218: 0.076012 0.187028
Batch: 872/4218: 0.022521 0.108531
Batch: 873/4218: 0.023797 0.111617
Batch: 874/4218: 0.029305 0.109643
Batch: 875/4218: 0.040164 0.125796
Batch: 876/4218: 0.026753 0.108407
Batch: 877/4218: 0.036068 0.117261
Batch: 878/4218: 0.077295 0.159562
Batch: 879/4218: 0.014169 0.091771
Batch: 880/4218: 0.010336 0.101145
Batch: 881/4218: 0.026315 0.103905
Batch: 882/4218: 0.082384 0.161149
Batch: 883/4218: 0.031181 0.121889
Batch: 884/4218: 0.024146 0.117293
Batch: 885/4218: 0.029560 0.104522
Batch: 886/4218: 0.040942 0.117141
Batch: 887/4218: 0.020497 0.114502
Batch: 888/4218: 0.019517 0.113175
Batch: 889/4218: 0.064706 0.155677
Batch: 890/4218: 0.021460 0.132997
Batch: 891/4218: 0.015138 0.104640
Batch: 892/4218: 0.013217 0.096954
Batch: 893/4218: 0.010978 0.083849
Batch: 894/4218: 0.064662 0.144407
Batch: 895/4218: 0.038542 0.115518
Batch: 896/4218: 0.055925 0.135275
Batch: 897/4218: 0.129370 0.215262
Batch: 898/4218: 0.045925 0.124875
Batch: 899/4218: 0.054553 0.138996
Batch: 900/4218: 0.038362 0.113016
Batch: 901/4218: 0.050397 0.128327
Batch: 902/4218: 0.029504 0.101891
Batch: 903/4218: 0.062579 0.132391
Batch: 904/4218: 0.029297 0.103482
Batch: 905/4218: 0.031581 0.115594
Batch: 906/4218: 0.031580 0.128201
Batch: 907/4218: 0.043415 0.121436
Batch: 908/4218: 0.036053 0.120657
Batch: 909/4218: 0.020867 0.098357
Batch: 910/4218: 0.026995 0.129107
Batch: 911/4218: 0.025937 0.115359
Batch: 912/4218: 0.047871 0.152357
Batch: 913/4218: 0.043519 0.178785
Batch: 914/4218: 0.072954 0.154726
Batch: 915/4218: 0.024985 0.105702
Batch: 916/4218: 0.022872 0.097870
Batch: 917/4218: 0.075925 0.151055
Batch: 918/4218: 0.042442 0.131329
Batch: 919/4218: 0.016065 0.102273
Batch: 920/4218: 0.028656 0.094903
Batch: 921/4218: 0.056038 0.130118
Batch: 922/4218: 0.031828 0.107835
Batch: 923/4218: 0.016853 0.082226
Batch: 924/4218: 0.025894 0.099794
Batch: 925/4218: 0.022329 0.107137
Batch: 926/4218: 0.035509 0.112807
Batch: 927/4218: 0.231675 0.313464
Batch: 928/4218: 0.051380 0.152957
Batch: 929/4218: 0.121568 0.197745
Batch: 930/4218: 0.010700 0.084392
Batch: 931/4218: 0.024031 0.094150
Batch: 932/4218: 0.024557 0.101589
Batch: 933/4218: 0.032930 0.102636
Batch: 934/4218: 0.077966 0.147799
Batch: 935/4218: 0.063371 0.142299
Batch: 936/4218: 0.034526 0.101497
Batch: 937/4218: 0.026409 0.089226
Batch: 938/4218: 0.013957 0.089837
Batch: 939/4218: 0.026107 0.088599
Batch: 940/4218: 0.009051 0.088080
Batch: 941/4218: 0.038503 0.110232
Batch: 942/4218: 0.011237 0.074240
Batch: 943/4218: 0.027341 0.091002
Batch: 944/4218: 0.051143 0.122985
Batch: 945/4218: 0.039395 0.103909
Batch: 946/4218: 0.011874 0.076330
Batch: 947/4218: 0.033860 0.097520
Batch: 948/4218: 0.045875 0.124521
Batch: 949/4218: 0.054843 0.138428
Batch: 950/4218: 0.034374 0.114942
Batch: 951/4218: 0.064089 0.138355
Batch: 952/4218: 0.136191 0.202243
Batch: 953/4218: 0.042646 0.125200
Batch: 954/4218: 0.021808 0.084942
Batch: 955/4218: 0.034416 0.115124
Batch: 956/4218: 0.055337 0.128940
Batch: 957/4218: 0.047711 0.115106
Batch: 958/4218: 0.008965 0.070687
Batch: 959/4218: 0.035295 0.099621
Batch: 960/4218: 0.055726 0.126992
Batch: 961/4218: 0.126495 0.189844
Batch: 962/4218: 0.027398 0.095464
Batch: 963/4218: 0.014845 0.084454
Batch: 964/4218: 0.017374 0.083568
Batch: 965/4218: 0.025845 0.092467
Batch: 966/4218: 0.031489 0.096512
Batch: 967/4218: 0.022762 0.093579
Batch: 968/4218: 0.016955 0.084839
Batch: 969/4218: 0.012477 0.083705
Batch: 970/4218: 0.019918 0.086157
Batch: 971/4218: 0.034215 0.099577
Batch: 972/4218: 0.013927 0.077687
Batch: 973/4218: 0.023766 0.097138
Batch: 974/4218: 0.035092 0.097407
Batch: 975/4218: 0.019758 0.079650
Batch: 976/4218: 0.017822 0.075025
Batch: 977/4218: 0.016187 0.078000
Batch: 978/4218: 0.046375 0.113258
Batch: 979/4218: 0.009024 0.070740
Batch: 980/4218: 0.019652 0.084489
Batch: 981/4218: 0.029415 0.093865
Batch: 982/4218: 0.018473 0.076122
Batch: 983/4218: 0.022820 0.083086
Batch: 984/4218: 0.043965 0.100272
Batch: 985/4218: 0.012614 0.077060
Batch: 986/4218: 0.011446 0.079660
Batch: 987/4218: 0.051999 0.123587
Batch: 988/4218: 0.032331 0.092503
Batch: 989/4218: 0.049096 0.108381
Batch: 990/4218: 0.018417 0.081211
Batch: 991/4218: 0.008611 0.074427
Batch: 992/4218: 0.014035 0.077639
Batch: 993/4218: 0.034075 0.105465
Batch: 994/4218: 0.120078 0.185215
Batch: 995/4218: 0.023423 0.101088
Batch: 996/4218: 0.044061 0.116954
Batch: 997/4218: 0.030080 0.109673
Batch: 998/4218: 0.047486 0.113062
Batch: 999/4218: 0.061102 0.147432
Batch: 1000/4218: 0.022785 0.083822
Batch: 1001/4218: 0.036829 0.102930
Batch: 1002/4218: 0.052908 0.121525
Batch: 1003/4218: 0.021448 0.074619
Batch: 1004/4218: 0.037956 0.107651
Batch: 1005/4218: 0.103814 0.185436
Batch: 1006/4218: 0.015815 0.069647
Batch: 1007/4218: 0.021232 0.083320
Batch: 1008/4218: 0.025791 0.080912
Batch: 1009/4218: 0.038408 0.121408
Batch: 1010/4218: 0.169408 0.225257
Batch: 1011/4218: 0.029828 0.088319
Batch: 1012/4218: 0.086366 0.143684
Batch: 1013/4218: 0.033591 0.095483
Batch: 1014/4218: 0.014703 0.077681
Batch: 1015/4218: 0.031275 0.088000
Batch: 1016/4218: 0.043393 0.101934
Batch: 1017/4218: 0.019490 0.090537
Batch: 1018/4218: 0.015133 0.074001
Batch: 1019/4218: 0.022573 0.075696
Batch: 1020/4218: 0.037630 0.103317
Batch: 1021/4218: 0.058126 0.113465
Batch: 1022/4218: 0.120622 0.176414
Batch: 1023/4218: 0.027078 0.083140
Batch: 1024/4218: 0.019892 0.074722
Batch: 1025/4218: 0.036845 0.091006
Batch: 1026/4218: 0.048074 0.100926
Batch: 1027/4218: 0.062587 0.119308
Batch: 1028/4218: 0.049728 0.109002
Batch: 1029/4218: 0.026566 0.087510
Batch: 1030/4218: 0.030587 0.081997
Batch: 1031/4218: 0.023287 0.074719
Batch: 1032/4218: 0.056571 0.136537
Batch: 1033/4218: 0.022016 0.078895
Batch: 1034/4218: 0.014255 0.063539
Batch: 1035/4218: 0.081280 0.139451
Batch: 1036/4218: 0.043172 0.104353
Batch: 1037/4218: 0.013583 0.070317
Batch: 1038/4218: 0.017532 0.066563
Batch: 1039/4218: 0.026708 0.081874
Batch: 1040/4218: 0.019370 0.073382
Batch: 1041/4218: 0.016602 0.064693
Batch: 1042/4218: 0.083488 0.136781
Batch: 1043/4218: 0.010080 0.060706
Batch: 1044/4218: 0.033859 0.087629
Batch: 1045/4218: 0.044614 0.093268
Batch: 1046/4218: 0.016320 0.063181
Batch: 1047/4218: 0.019960 0.068655
Batch: 1048/4218: 0.014781 0.069944
Batch: 1049/4218: 0.038505 0.098244
Batch: 1050/4218: 0.016635 0.062154
Batch: 1051/4218: 0.058293 0.110608
Batch: 1052/4218: 0.018545 0.072490
Batch: 1053/4218: 0.044623 0.092865
Batch: 1054/4218: 0.017263 0.069759
Batch: 1055/4218: 0.021210 0.070136
Batch: 1056/4218: 0.035528 0.094329
Batch: 1057/4218: 0.014672 0.065846
Batch: 1058/4218: 0.038457 0.090791
Batch: 1059/4218: 0.023204 0.072781
Batch: 1060/4218: 0.019751 0.083120
Batch: 1061/4218: 0.165484 0.215205
Batch: 1062/4218: 0.113219 0.162640
Batch: 1063/4218: 0.037261 0.084574
Batch: 1064/4218: 0.026063 0.073487
Batch: 1065/4218: 0.012288 0.065802
Batch: 1066/4218: 0.021648 0.070381
Batch: 1067/4218: 0.071006 0.117616
Batch: 1068/4218: 0.043550 0.092824
Batch: 1069/4218: 0.014266 0.063562
Batch: 1070/4218: 0.025990 0.078411
Batch: 1071/4218: 0.065354 0.113084
Batch: 1072/4218: 0.046607 0.093787
Batch: 1073/4218: 0.024405 0.079776
Batch: 1074/4218: 0.029040 0.088239
Batch: 1075/4218: 0.019947 0.066739
Batch: 1076/4218: 0.040736 0.085735
Batch: 1077/4218: 0.037138 0.088350
Batch: 1078/4218: 0.128116 0.191194
Batch: 1079/4218: 0.028989 0.080644
Batch: 1080/4218: 0.038497 0.104875
Batch: 1081/4218: 0.120401 0.168622
Batch: 1082/4218: 0.048268 0.103780
Batch: 1083/4218: 0.032018 0.085022
Batch: 1084/4218: 0.069415 0.120639
Batch: 1085/4218: 0.023907 0.068051
Batch: 1086/4218: 0.087806 0.140610
Batch: 1087/4218: 0.026996 0.089301
Batch: 1088/4218: 0.055241 0.109126
Batch: 1089/4218: 0.020222 0.065573
Batch: 1090/4218: 0.026248 0.073427
Batch: 1091/4218: 0.012226 0.074877
Batch: 1092/4218: 0.044203 0.092803
Batch: 1093/4218: 0.097379 0.145119
Batch: 1094/4218: 0.028854 0.085590
Batch: 1095/4218: 0.076142 0.135805
Batch: 1096/4218: 0.025465 0.073354
Batch: 1097/4218: 0.053125 0.096390
Batch: 1098/4218: 0.025220 0.072119
Batch: 1099/4218: 0.017386 0.065893
Batch: 1100/4218: 0.093130 0.148424
Batch: 1101/4218: 0.089500 0.136118
Batch: 1102/4218: 0.023611 0.066471
Batch: 1103/4218: 0.060641 0.109547
Batch: 1104/4218: 0.013534 0.067733
Batch: 1105/4218: 0.055998 0.105429
Batch: 1106/4218: 0.026485 0.074980
Batch: 1107/4218: 0.078509 0.122067
Batch: 1108/4218: 0.011825 0.062535
Batch: 1109/4218: 0.026795 0.076543
Batch: 1110/4218: 0.013436 0.056575
Batch: 1111/4218: 0.009273 0.051853
Batch: 1112/4218: 0.027223 0.071253
Batch: 1113/4218: 0.058735 0.108537
Batch: 1114/4218: 0.155115 0.199762
Batch: 1115/4218: 0.013621 0.068448
Batch: 1116/4218: 0.021528 0.061391
Batch: 1117/4218: 0.015547 0.059497
Batch: 1118/4218: 0.049441 0.100148
Batch: 1119/4218: 0.018861 0.067882
Batch: 1120/4218: 0.011200 0.057100
Batch: 1121/4218: 0.031976 0.071466
Batch: 1122/4218: 0.030443 0.073062
Batch: 1123/4218: 0.025136 0.067905
Batch: 1124/4218: 0.105271 0.146868
Batch: 1125/4218: 0.050542 0.098433
Batch: 1126/4218: 0.062849 0.117601
Batch: 1127/4218: 0.099638 0.142064
Batch: 1128/4218: 0.030141 0.076891
Batch: 1129/4218: 0.027034 0.067226
Batch: 1130/4218: 0.028946 0.068649
Batch: 1131/4218: 0.029165 0.068321
Batch: 1132/4218: 0.008838 0.067368
Batch: 1133/4218: 0.025463 0.077154
Batch: 1134/4218: 0.016815 0.057416
Batch: 1135/4218: 0.046469 0.098660
Batch: 1136/4218: 0.071798 0.121253
Batch: 1137/4218: 0.023586 0.066959
Batch: 1138/4218: 0.071985 0.115621
Batch: 1139/4218: 0.053402 0.106996
Batch: 1140/4218: 0.019312 0.060379
Batch: 1141/4218: 0.014683 0.056086
Batch: 1142/4218: 0.039732 0.089736
Batch: 1143/4218: 0.013716 0.059216
Batch: 1144/4218: 0.039755 0.091369
Batch: 1145/4218: 0.010968 0.058103
Batch: 1146/4218: 0.073026 0.112525
Batch: 1147/4218: 0.018413 0.060651
Batch: 1148/4218: 0.053969 0.096799
Batch: 1149/4218: 0.015263 0.063905
Batch: 1150/4218: 0.020286 0.065602
Batch: 1151/4218: 0.048846 0.085705
Batch: 1152/4218: 0.136445 0.179001
Batch: 1153/4218: 0.008554 0.058638
Batch: 1154/4218: 0.008574 0.050743
Batch: 1155/4218: 0.007603 0.051603
Batch: 1156/4218: 0.032330 0.077768
Batch: 1157/4218: 0.037710 0.078190
Batch: 1158/4218: 0.046298 0.113692
Batch: 1159/4218: 0.018771 0.060638
Batch: 1160/4218: 0.039498 0.075699
Batch: 1161/4218: 0.050848 0.091549
Batch: 1162/4218: 0.033993 0.074013
Batch: 1163/4218: 0.028310 0.071434
Batch: 1164/4218: 0.006171 0.053341
Batch: 1165/4218: 0.047635 0.083058
Batch: 1166/4218: 0.010981 0.053352
Batch: 1167/4218: 0.063088 0.099745
Batch: 1168/4218: 0.005581 0.054509
Batch: 1169/4218: 0.016991 0.058424
Batch: 1170/4218: 0.010629 0.054993
Batch: 1171/4218: 0.007292 0.048320
Batch: 1172/4218: 0.046390 0.088043
Batch: 1173/4218: 0.010788 0.052047
Batch: 1174/4218: 0.027512 0.066356
Batch: 1175/4218: 0.024541 0.075944
Batch: 1176/4218: 0.025530 0.064522
Batch: 1177/4218: 0.027919 0.072981
Batch: 1178/4218: 0.027775 0.092115
Batch: 1179/4218: 0.114505 0.151889
Batch: 1180/4218: 0.091342 0.128637
Batch: 1181/4218: 0.035209 0.073018
Batch: 1182/4218: 0.019479 0.057397
Batch: 1183/4218: 0.074795 0.143843
Batch: 1184/4218: 0.017034 0.064912
Batch: 1185/4218: 0.043997 0.087613
Batch: 1186/4218: 0.033305 0.076206
Batch: 1187/4218: 0.010130 0.057225
Batch: 1188/4218: 0.037703 0.073296
Batch: 1189/4218: 0.012864 0.051633
Batch: 1190/4218: 0.021271 0.066009
Batch: 1191/4218: 0.013854 0.053536
Batch: 1192/4218: 0.029540 0.075065
Batch: 1193/4218: 0.016716 0.054441
Batch: 1194/4218: 0.018000 0.053625
Batch: 1195/4218: 0.004130 0.041544
Batch: 1196/4218: 0.023734 0.068149
Batch: 1197/4218: 0.020214 0.057550
Batch: 1198/4218: 0.057669 0.101317
Batch: 1199/4218: 0.045817 0.085373
Batch: 1200/4218: 0.008255 0.056833
Batch: 1201/4218: 0.130724 0.169989
Batch: 1202/4218: 0.023131 0.065945
Batch: 1203/4218: 0.024805 0.091523
Batch: 1204/4218: 0.018915 0.056966
Batch: 1205/4218: 0.020805 0.063601
Batch: 1206/4218: 0.094516 0.136698
Batch: 1207/4218: 0.046552 0.087449
Batch: 1208/4218: 0.013777 0.050024
Batch: 1209/4218: 0.087743 0.128756
Batch: 1210/4218: 0.035470 0.074936
Batch: 1211/4218: 0.108971 0.149557
Batch: 1212/4218: 0.011914 0.045027
Batch: 1213/4218: 0.025642 0.063477
Batch: 1214/4218: 0.012452 0.051036
Batch: 1215/4218: 0.024023 0.060221
Batch: 1216/4218: 0.054989 0.092200
Batch: 1217/4218: 0.018762 0.053228
Batch: 1218/4218: 0.014933 0.053957
Batch: 1219/4218: 0.025219 0.058455
Batch: 1220/4218: 0.024406 0.063881
Batch: 1221/4218: 0.009734 0.046111
Batch: 1222/4218: 0.020164 0.051798
Batch: 1223/4218: 0.030542 0.070337
Batch: 1224/4218: 0.022664 0.058136
Batch: 1225/4218: 0.103262 0.145000
Batch: 1226/4218: 0.015594 0.051019
Batch: 1227/4218: 0.057501 0.101647
Batch: 1228/4218: 0.014466 0.046786
Batch: 1229/4218: 0.013022 0.053361
Batch: 1230/4218: 0.008251 0.039833
Batch: 1231/4218: 0.025137 0.072432
Batch: 1232/4218: 0.033118 0.067370
Batch: 1233/4218: 0.029818 0.062377
Batch: 1234/4218: 0.044717 0.078835
Batch: 1235/4218: 0.016600 0.047284
Batch: 1236/4218: 0.012603 0.050091
Batch: 1237/4218: 0.220678 0.253763
Batch: 1238/4218: 0.018723 0.058580
Batch: 1239/4218: 0.157314 0.192871
Batch: 1240/4218: 0.020299 0.066938
Batch: 1241/4218: 0.126471 0.160760
Batch: 1242/4218: 0.022109 0.055847
Batch: 1243/4218: 0.019965 0.070103
Batch: 1244/4218: 0.020632 0.099090
Batch: 1245/4218: 0.031366 0.076696
Batch: 1246/4218: 0.064985 0.103787
Batch: 1247/4218: 0.023401 0.056408
Batch: 1248/4218: 0.097822 0.129386
Batch: 1249/4218: 0.037234 0.072781
Batch: 1250/4218: 0.087118 0.127406
Batch: 1251/4218: 0.008662 0.052235
Batch: 1252/4218: 0.014564 0.048390
Batch: 1253/4218: 0.014780 0.051453
Batch: 1254/4218: 0.041800 0.078929
Batch: 1255/4218: 0.018430 0.051929
Batch: 1256/4218: 0.037191 0.076237
Batch: 1257/4218: 0.023242 0.056455
Batch: 1258/4218: 0.017488 0.048484
Batch: 1259/4218: 0.052377 0.098280
Batch: 1260/4218: 0.086152 0.121883
Batch: 1261/4218: 0.018117 0.054597
Batch: 1262/4218: 0.039437 0.077922
Batch: 1263/4218: 0.060034 0.094749
Batch: 1264/4218: 0.012012 0.043558
Batch: 1265/4218: 0.027244 0.059839
Batch: 1266/4218: 0.059790 0.103472
Batch: 1267/4218: 0.035357 0.069078
Batch: 1268/4218: 0.047270 0.083097
Batch: 1269/4218: 0.023628 0.054505
Batch: 1270/4218: 0.031399 0.063768
Batch: 1271/4218: 0.030896 0.065116
Batch: 1272/4218: 0.056541 0.102376
Batch: 1273/4218: 0.027606 0.063273
Batch: 1274/4218: 0.008076 0.043836
Batch: 1275/4218: 0.042039 0.075678
Batch: 1276/4218: 0.024647 0.056109
Batch: 1277/4218: 0.052613 0.086245
Batch: 1278/4218: 0.052057 0.095588
Batch: 1279/4218: 0.032248 0.064045
Batch: 1280/4218: 0.015229 0.046372
Batch: 1281/4218: 0.050084 0.081564
Batch: 1282/4218: 0.051832 0.097840
Batch: 1283/4218: 0.068510 0.099526
Batch: 1284/4218: 0.055793 0.086035
Batch: 1285/4218: 0.028878 0.092404
Batch: 1286/4218: 0.064979 0.092398
Batch: 1287/4218: 0.039814 0.071440
Batch: 1288/4218: 0.045002 0.078518
Batch: 1289/4218: 0.084831 0.117209
Batch: 1290/4218: 0.038675 0.075921
Batch: 1291/4218: 0.030226 0.064861
Batch: 1292/4218: 0.025910 0.061453
Batch: 1293/4218: 0.026096 0.059250
Batch: 1294/4218: 0.017022 0.057553
Batch: 1295/4218: 0.035852 0.065427
Batch: 1296/4218: 0.063538 0.117702
Batch: 1297/4218: 0.007997 0.040477
Batch: 1298/4218: 0.014428 0.047259
Batch: 1299/4218: 0.022777 0.061458
Batch: 1300/4218: 0.029591 0.060927
Batch: 1301/4218: 0.014658 0.047425
Batch: 1302/4218: 0.020110 0.053258
Batch: 1303/4218: 0.080503 0.114163
Batch: 1304/4218: 0.070185 0.101071
Batch: 1305/4218: 0.035335 0.064497
Batch: 1306/4218: 0.059356 0.089123
Batch: 1307/4218: 0.028653 0.064855
Batch: 1308/4218: 0.058984 0.089323
Batch: 1309/4218: 0.024934 0.062776
Batch: 1310/4218: 0.018667 0.047202
Batch: 1311/4218: 0.027008 0.085006
Batch: 1312/4218: 0.032584 0.062550
Batch: 1313/4218: 0.007791 0.046334
Batch: 1314/4218: 0.015882 0.051701
Batch: 1315/4218: 0.019554 0.046510
Batch: 1316/4218: 0.013165 0.042342
Batch: 1317/4218: 0.022824 0.056000
Batch: 1318/4218: 0.033597 0.074046
Batch: 1319/4218: 0.013186 0.048628
Batch: 1320/4218: 0.012052 0.046508
Batch: 1321/4218: 0.032285 0.062059
Batch: 1322/4218: 0.021478 0.060392
Batch: 1323/4218: 0.019044 0.062072
Batch: 1324/4218: 0.020923 0.052058
Batch: 1325/4218: 0.020151 0.050645
Batch: 1326/4218: 0.015698 0.047836
Batch: 1327/4218: 0.042677 0.070342
Batch: 1328/4218: 0.018631 0.060434
Batch: 1329/4218: 0.027999 0.058056
Batch: 1330/4218: 0.012796 0.052806
Batch: 1331/4218: 0.056031 0.086393
Batch: 1332/4218: 0.052817 0.087279
Batch: 1333/4218: 0.095947 0.127978
Batch: 1334/4218: 0.035439 0.064675
Batch: 1335/4218: 0.026942 0.061335
Batch: 1336/4218: 0.024416 0.052115
Batch: 1337/4218: 0.024200 0.053045
Batch: 1338/4218: 0.022758 0.050685
Batch: 1339/4218: 0.038057 0.075592
Batch: 1340/4218: 0.078656 0.108324
Batch: 1341/4218: 0.013821 0.050279
Batch: 1342/4218: 0.011822 0.048578
Batch: 1343/4218: 0.024312 0.053576
Batch: 1344/4218: 0.019555 0.050917
Batch: 1345/4218: 0.024858 0.053227
Batch: 1346/4218: 0.018886 0.050898
Batch: 1347/4218: 0.032761 0.062311
Batch: 1348/4218: 0.005219 0.036064
Batch: 1349/4218: 0.014161 0.041929
Batch: 1350/4218: 0.006253 0.032624
Batch: 1351/4218: 0.022544 0.051386
Batch: 1352/4218: 0.030707 0.056261
Batch: 1353/4218: 0.143672 0.177659
Batch: 1354/4218: 0.012527 0.041667
Batch: 1355/4218: 0.015749 0.045457
Batch: 1356/4218: 0.035703 0.070036
Batch: 1357/4218: 0.076302 0.106685
Batch: 1358/4218: 0.050836 0.078597
Batch: 1359/4218: 0.025956 0.056362
Batch: 1360/4218: 0.060285 0.087505
Batch: 1361/4218: 0.010586 0.046545
Batch: 1362/4218: 0.031036 0.057559
Batch: 1363/4218: 0.033828 0.059665
Batch: 1364/4218: 0.059935 0.086121
Batch: 1365/4218: 0.012631 0.042823
Batch: 1366/4218: 0.070113 0.103018
Batch: 1367/4218: 0.020268 0.046565
Batch: 1368/4218: 0.020255 0.050295
Batch: 1369/4218: 0.042295 0.086860
Batch: 1370/4218: 0.018837 0.049402
Batch: 1371/4218: 0.063759 0.095470
Batch: 1372/4218: 0.027623 0.057227
Batch: 1373/4218: 0.135559 0.161566
Batch: 1374/4218: 0.015963 0.043396
Batch: 1375/4218: 0.010125 0.034832
Batch: 1376/4218: 0.011875 0.039192
Batch: 1377/4218: 0.051183 0.075802
Batch: 1378/4218: 0.040748 0.065925
Batch: 1379/4218: 0.033516 0.059267
Batch: 1380/4218: 0.011175 0.038002
Batch: 1381/4218: 0.011403 0.037880
Batch: 1382/4218: 0.013589 0.041980
Batch: 1383/4218: 0.023754 0.050453
Batch: 1384/4218: 0.015819 0.039235
Batch: 1385/4218: 0.060712 0.090552
Batch: 1386/4218: 0.025741 0.050441
Batch: 1387/4218: 0.040170 0.070280
Batch: 1388/4218: 0.017046 0.043388
Batch: 1389/4218: 0.021619 0.043808
Batch: 1390/4218: 0.010241 0.033713
Batch: 1391/4218: 0.038394 0.066214
Batch: 1392/4218: 0.032924 0.067777
Batch: 1393/4218: 0.009039 0.036745
Batch: 1394/4218: 0.044252 0.068468
Batch: 1395/4218: 0.028135 0.054724
Batch: 1396/4218: 0.060540 0.094405
Batch: 1397/4218: 0.037485 0.062591
Batch: 1398/4218: 0.037554 0.064600
Batch: 1399/4218: 0.009019 0.032870
Batch: 1400/4218: 0.034415 0.058297
Batch: 1401/4218: 0.031426 0.056167
Batch: 1402/4218: 0.016858 0.044383
Batch: 1403/4218: 0.022783 0.047631
Batch: 1404/4218: 0.014000 0.037321
Batch: 1405/4218: 0.019879 0.042162
Batch: 1406/4218: 0.008304 0.032351
Batch: 1407/4218: 0.077896 0.104040
Batch: 1408/4218: 0.011301 0.036575
Batch: 1409/4218: 0.039645 0.065504
Batch: 1410/4218: 0.013585 0.046606
Batch: 1411/4218: 0.046276 0.080057
Batch: 1412/4218: 0.010800 0.034501
Batch: 1413/4218: 0.021662 0.045873
Batch: 1414/4218: 0.090763 0.116366
Batch: 1415/4218: 0.018909 0.043276
Batch: 1416/4218: 0.023298 0.048804
Batch: 1417/4218: 0.047245 0.071292
Batch: 1418/4218: 0.016018 0.038675
Batch: 1419/4218: 0.051490 0.077852
Batch: 1420/4218: 0.013928 0.047476
Batch: 1421/4218: 0.028358 0.051668
Batch: 1422/4218: 0.022914 0.045827
Batch: 1423/4218: 0.053603 0.083878
Batch: 1424/4218: 0.093237 0.116402
Batch: 1425/4218: 0.026587 0.049963
Batch: 1426/4218: 0.022925 0.047268
Batch: 1427/4218: 0.032900 0.059637
Batch: 1428/4218: 0.012899 0.046004
Batch: 1429/4218: 0.022359 0.050861
Batch: 1430/4218: 0.014294 0.038123
Batch: 1431/4218: 0.027660 0.049099
Batch: 1432/4218: 0.019958 0.045924
Batch: 1433/4218: 0.027849 0.049457
Batch: 1434/4218: 0.012644 0.034628
Batch: 1435/4218: 0.095541 0.118416
Batch: 1436/4218: 0.031151 0.057520
Batch: 1437/4218: 0.029622 0.059431
Batch: 1438/4218: 0.014055 0.041697
Batch: 1439/4218: 0.027888 0.049420
Batch: 1440/4218: 0.012580 0.035763
Batch: 1441/4218: 0.020758 0.041095
Batch: 1442/4218: 0.061858 0.083501
Batch: 1443/4218: 0.024276 0.047004
Batch: 1444/4218: 0.070445 0.099375
Batch: 1445/4218: 0.049187 0.074512
Batch: 1446/4218: 0.011633 0.034199
Batch: 1447/4218: 0.078268 0.102534
Batch: 1448/4218: 0.030619 0.055695
Batch: 1449/4218: 0.018182 0.044265
Batch: 1450/4218: 0.033756 0.058613
Batch: 1451/4218: 0.021977 0.047497
Batch: 1452/4218: 0.013186 0.037147
Batch: 1453/4218: 0.026646 0.049703
Batch: 1454/4218: 0.012794 0.039774
Batch: 1455/4218: 0.040278 0.061366
Batch: 1456/4218: 0.046785 0.072520
Batch: 1457/4218: 0.013659 0.035145
Batch: 1458/4218: 0.023183 0.059852
Batch: 1459/4218: 0.022180 0.046855
Batch: 1460/4218: 0.015320 0.039306
Batch: 1461/4218: 0.014395 0.047659
Batch: 1462/4218: 0.047411 0.071683
Batch: 1463/4218: 0.034889 0.055160
Batch: 1464/4218: 0.068693 0.099641
Batch: 1465/4218: 0.039160 0.076768
Batch: 1466/4218: 0.054821 0.077134
Batch: 1467/4218: 0.238781 0.272787
Batch: 1468/4218: 0.059660 0.082198
Batch: 1469/4218: 0.014640 0.037721
Batch: 1470/4218: 0.021895 0.043242
Batch: 1471/4218: 0.038230 0.064044
Batch: 1472/4218: 0.022989 0.045285
Batch: 1473/4218: 0.021470 0.052562
Batch: 1474/4218: 0.020863 0.057771
Batch: 1475/4218: 0.014108 0.037959
Batch: 1476/4218: 0.030436 0.054886
Batch: 1477/4218: 0.019482 0.039671
Batch: 1478/4218: 0.014656 0.036996
Batch: 1479/4218: 0.134013 0.156089
Batch: 1480/4218: 0.034450 0.055827
Batch: 1481/4218: 0.016871 0.041886
Batch: 1482/4218: 0.029446 0.051281
Batch: 1483/4218: 0.013401 0.034659
Batch: 1484/4218: 0.033792 0.060427
Batch: 1485/4218: 0.030801 0.049233
Batch: 1486/4218: 0.038308 0.058031
Batch: 1487/4218: 0.135613 0.156820
Batch: 1488/4218: 0.012813 0.035107
Batch: 1489/4218: 0.021060 0.044665
Batch: 1490/4218: 0.030637 0.053807
Batch: 1491/4218: 0.029046 0.049983
Batch: 1492/4218: 0.013221 0.034228
Batch: 1493/4218: 0.019845 0.043837
Batch: 1494/4218: 0.025851 0.050273
Batch: 1495/4218: 0.154625 0.175517
Batch: 1496/4218: 0.018001 0.037565
Batch: 1497/4218: 0.030334 0.060908
Batch: 1498/4218: 0.141628 0.173761
Batch: 1499/4218: 0.083985 0.107283
Batch: 1500/4218: 0.071588 0.099659
Batch: 1501/4218: 0.026274 0.051773
Batch: 1502/4218: 0.011407 0.033518
Batch: 1503/4218: 0.057674 0.080433
Batch: 1504/4218: 0.044649 0.065655
Batch: 1505/4218: 0.023803 0.050344
Batch: 1506/4218: 0.035506 0.062410
Batch: 1507/4218: 0.068842 0.090970
Batch: 1508/4218: 0.063172 0.081481
Batch: 1509/4218: 0.019058 0.038413
Batch: 1510/4218: 0.053366 0.076097
Batch: 1511/4218: 0.021577 0.039834
Batch: 1512/4218: 0.023090 0.045235
Batch: 1513/4218: 0.026550 0.058745
Batch: 1514/4218: 0.038133 0.058625
Batch: 1515/4218: 0.015513 0.037832
Batch: 1516/4218: 0.065701 0.085298
Batch: 1517/4218: 0.061185 0.084401
Batch: 1518/4218: 0.039469 0.058458
Batch: 1519/4218: 0.036648 0.061497
Batch: 1520/4218: 0.008895 0.029910
Batch: 1521/4218: 0.021152 0.040752
Batch: 1522/4218: 0.032162 0.061606
Batch: 1523/4218: 0.047585 0.069224
Batch: 1524/4218: 0.028486 0.051209
Batch: 1525/4218: 0.020697 0.040013
Batch: 1526/4218: 0.026549 0.072783
Batch: 1527/4218: 0.026158 0.048621
Batch: 1528/4218: 0.028170 0.049732
Batch: 1529/4218: 0.040743 0.063770
Batch: 1530/4218: 0.012617 0.032475
Batch: 1531/4218: 0.024227 0.045561
Batch: 1532/4218: 0.019370 0.039827
Batch: 1533/4218: 0.029466 0.053740
Batch: 1534/4218: 0.012319 0.031521
Batch: 1535/4218: 0.037552 0.056149
Batch: 1536/4218: 0.023613 0.057553
Batch: 1537/4218: 0.030495 0.050248
Batch: 1538/4218: 0.026799 0.050150
Batch: 1539/4218: 0.017454 0.037564
Batch: 1540/4218: 0.051743 0.069884
Batch: 1541/4218: 0.014183 0.038677
Batch: 1542/4218: 0.022447 0.040818
Batch: 1543/4218: 0.022593 0.041361
Batch: 1544/4218: 0.023674 0.041410
Batch: 1545/4218: 0.071031 0.094573
Batch: 1546/4218: 0.053816 0.074466
Batch: 1547/4218: 0.028547 0.048485
Batch: 1548/4218: 0.045844 0.062945
Batch: 1549/4218: 0.092512 0.119406
Batch: 1550/4218: 0.018611 0.039441
Batch: 1551/4218: 0.049392 0.068198
Batch: 1552/4218: 0.031174 0.052383
Batch: 1553/4218: 0.018418 0.040780
Batch: 1554/4218: 0.063663 0.086558
Batch: 1555/4218: 0.086848 0.105236
Batch: 1556/4218: 0.012915 0.035735
Batch: 1557/4218: 0.036482 0.055324
Batch: 1558/4218: 0.082700 0.101511
Batch: 1559/4218: 0.024587 0.043156
Batch: 1560/4218: 0.117897 0.138032
Batch: 1561/4218: 0.022301 0.042007
Batch: 1562/4218: 0.073813 0.091145
Batch: 1563/4218: 0.027976 0.046612
Batch: 1564/4218: 0.025546 0.045032
Batch: 1565/4218: 0.026000 0.045065
Batch: 1566/4218: 0.018473 0.047892
Batch: 1567/4218: 0.014852 0.032798
Batch: 1568/4218: 0.016625 0.037680
Batch: 1569/4218: 0.042563 0.063090
Batch: 1570/4218: 0.017182 0.037349
Batch: 1571/4218: 0.047211 0.065791
Batch: 1572/4218: 0.029018 0.047032
Batch: 1573/4218: 0.029215 0.045747
Batch: 1574/4218: 0.017644 0.035783
Batch: 1575/4218: 0.013865 0.031157
Batch: 1576/4218: 0.031748 0.049990
Batch: 1577/4218: 0.043843 0.061497
Batch: 1578/4218: 0.023283 0.055263
Batch: 1579/4218: 0.053391 0.073412
Batch: 1580/4218: 0.134842 0.153833
Batch: 1581/4218: 0.013835 0.034780
Batch: 1582/4218: 0.041729 0.064657
Batch: 1583/4218: 0.032984 0.056846
Batch: 1584/4218: 0.081368 0.100473
Batch: 1585/4218: 0.019180 0.039287
Batch: 1586/4218: 0.025108 0.046613
Batch: 1587/4218: 0.040563 0.059331
Batch: 1588/4218: 0.017004 0.044357
Batch: 1589/4218: 0.020484 0.038006
Batch: 1590/4218: 0.011131 0.030859
Batch: 1591/4218: 0.022599 0.041329
Batch: 1592/4218: 0.012914 0.032398
Batch: 1593/4218: 0.022028 0.052632
Batch: 1594/4218: 0.037129 0.054168
Batch: 1595/4218: 0.018528 0.035476
Batch: 1596/4218: 0.035302 0.053479
Batch: 1597/4218: 0.015465 0.032929
Batch: 1598/4218: 0.024858 0.046344
Batch: 1599/4218: 0.044572 0.065200
Batch: 1600/4218: 0.158748 0.175653
Batch: 1601/4218: 0.007682 0.029918
Batch: 1602/4218: 0.009527 0.049987
Batch: 1603/4218: 0.034204 0.053941
Batch: 1604/4218: 0.014530 0.032327
Batch: 1605/4218: 0.012174 0.029807
Batch: 1606/4218: 0.017821 0.034258
Batch: 1607/4218: 0.020723 0.040416
Batch: 1608/4218: 0.047466 0.067599
Batch: 1609/4218: 0.020565 0.036147
Batch: 1610/4218: 0.045743 0.065574
Batch: 1611/4218: 0.012380 0.030874
Batch: 1612/4218: 0.036772 0.053316
Batch: 1613/4218: 0.061795 0.079088
Batch: 1614/4218: 0.026317 0.045797
Batch: 1615/4218: 0.018687 0.039203
Batch: 1616/4218: 0.014201 0.029834
Batch: 1617/4218: 0.020480 0.038075
Batch: 1618/4218: 0.021478 0.037671
Batch: 1619/4218: 0.149291 0.166402
Batch: 1620/4218: 0.049257 0.066804
Batch: 1621/4218: 0.022752 0.038422
Batch: 1622/4218: 0.032091 0.050272
Batch: 1623/4218: 0.023983 0.041906
Batch: 1624/4218: 0.025016 0.042807
Batch: 1625/4218: 0.037198 0.061129
Batch: 1626/4218: 0.008510 0.023883
Batch: 1627/4218: 0.038186 0.055774
Batch: 1628/4218: 0.010841 0.030733
Batch: 1629/4218: 0.014976 0.033905
Batch: 1630/4218: 0.013783 0.033358
Batch: 1631/4218: 0.016682 0.034690
Batch: 1632/4218: 0.023698 0.040300
Batch: 1633/4218: 0.017626 0.041382
Batch: 1634/4218: 0.021809 0.039148
Batch: 1635/4218: 0.038476 0.055425
Batch: 1636/4218: 0.057310 0.074894
Batch: 1637/4218: 0.044151 0.060580
Batch: 1638/4218: 0.031790 0.050358
Batch: 1639/4218: 0.059565 0.075815
Batch: 1640/4218: 0.040559 0.059407
Batch: 1641/4218: 0.019019 0.035080
Batch: 1642/4218: 0.025098 0.043853
Batch: 1643/4218: 0.015478 0.032711
Batch: 1644/4218: 0.016736 0.032066
Batch: 1645/4218: 0.019378 0.038336
Batch: 1646/4218: 0.030923 0.046083
Batch: 1647/4218: 0.099706 0.119642
Batch: 1648/4218: 0.017279 0.037934
Batch: 1649/4218: 0.021375 0.038826
Batch: 1650/4218: 0.047853 0.064169
Batch: 1651/4218: 0.015838 0.032687
Batch: 1652/4218: 0.038377 0.053813
Batch: 1653/4218: 0.038352 0.052981
Batch: 1654/4218: 0.009608 0.025534
Batch: 1655/4218: 0.011865 0.030035
Batch: 1656/4218: 0.020175 0.035119
Batch: 1657/4218: 0.037651 0.054385
Batch: 1658/4218: 0.030349 0.047735
Batch: 1659/4218: 0.089262 0.111283
Batch: 1660/4218: 0.047685 0.064293
Batch: 1661/4218: 0.045620 0.060338
Batch: 1662/4218: 0.010559 0.029709
Batch: 1663/4218: 0.042082 0.059341
Batch: 1664/4218: 0.037221 0.052959
Batch: 1665/4218: 0.015779 0.029828
Batch: 1666/4218: 0.027162 0.042130
Batch: 1667/4218: 0.037817 0.052965
Batch: 1668/4218: 0.055534 0.072014
Batch: 1669/4218: 0.029591 0.046923
Batch: 1670/4218: 0.013226 0.028254
Batch: 1671/4218: 0.083584 0.105754
Batch: 1672/4218: 0.068511 0.082984
Batch: 1673/4218: 0.011296 0.028246
Batch: 1674/4218: 0.039292 0.053910
Batch: 1675/4218: 0.064987 0.082533
Batch: 1676/4218: 0.053294 0.073171
Batch: 1677/4218: 0.015510 0.030938
Batch: 1678/4218: 0.044062 0.058704
Batch: 1679/4218: 0.036882 0.054413
Batch: 1680/4218: 0.016443 0.033331
Batch: 1681/4218: 0.086697 0.103171
Batch: 1682/4218: 0.068178 0.081613
Batch: 1683/4218: 0.047400 0.062284
Batch: 1684/4218: 0.018624 0.031894
Batch: 1685/4218: 0.021283 0.039240
Batch: 1686/4218: 0.022819 0.048867
Batch: 1687/4218: 0.043090 0.058398
Batch: 1688/4218: 0.030144 0.046214
Batch: 1689/4218: 0.018475 0.035708
Batch: 1690/4218: 0.049390 0.065690
Batch: 1691/4218: 0.056286 0.069722
Batch: 1692/4218: 0.029820 0.043424
Batch: 1693/4218: 0.040793 0.063885
Batch: 1694/4218: 0.045533 0.062220
Batch: 1695/4218: 0.007913 0.021113
Batch: 1696/4218: 0.046417 0.060037
Batch: 1697/4218: 0.094455 0.112764
Batch: 1698/4218: 0.039288 0.055579
Batch: 1699/4218: 0.012675 0.032275
Batch: 1700/4218: 0.025295 0.046303
Batch: 1701/4218: 0.011845 0.029984
Batch: 1702/4218: 0.030684 0.045936
Batch: 1703/4218: 0.016546 0.029790
Batch: 1704/4218: 0.004968 0.018526
Batch: 1705/4218: 0.007205 0.025339
Batch: 1706/4218: 0.031267 0.047108
Batch: 1707/4218: 0.017970 0.032213
Batch: 1708/4218: 0.024146 0.039485
Batch: 1709/4218: 0.034589 0.049321
Batch: 1710/4218: 0.023896 0.039872
Batch: 1711/4218: 0.011376 0.034636
Batch: 1712/4218: 0.056890 0.072384
Batch: 1713/4218: 0.073242 0.087307
Batch: 1714/4218: 0.016402 0.029804
Batch: 1715/4218: 0.054617 0.072281
Batch: 1716/4218: 0.050021 0.064339
Batch: 1717/4218: 0.058597 0.076248
Batch: 1718/4218: 0.039989 0.056203
Batch: 1719/4218: 0.163394 0.179137
Batch: 1720/4218: 0.020875 0.035058
Batch: 1721/4218: 0.091985 0.118346
Batch: 1722/4218: 0.071795 0.085787
Batch: 1723/4218: 0.033396 0.052118
Batch: 1724/4218: 0.007502 0.022325
Batch: 1725/4218: 0.025097 0.047699
Batch: 1726/4218: 0.063267 0.079958
Batch: 1727/4218: 0.021804 0.038052
Batch: 1728/4218: 0.021694 0.035693
Batch: 1729/4218: 0.027124 0.041679
Batch: 1730/4218: 0.007705 0.022511
Batch: 1731/4218: 0.043195 0.058102
Batch: 1732/4218: 0.036017 0.049675
Batch: 1733/4218: 0.145212 0.160475
Batch: 1734/4218: 0.030484 0.044531
Batch: 1735/4218: 0.012813 0.031759
Batch: 1736/4218: 0.061039 0.075230
Batch: 1737/4218: 0.035909 0.053121
Batch: 1738/4218: 0.028822 0.051154
Batch: 1739/4218: 0.015505 0.031471
Batch: 1740/4218: 0.024429 0.042728
Batch: 1741/4218: 0.021107 0.035697
Batch: 1742/4218: 0.014406 0.030884
Batch: 1743/4218: 0.011268 0.025197
Batch: 1744/4218: 0.057467 0.071430
Batch: 1745/4218: 0.029555 0.046050
Batch: 1746/4218: 0.061613 0.074343
Batch: 1747/4218: 0.080837 0.095952
Batch: 1748/4218: 0.072142 0.087021
Batch: 1749/4218: 0.051149 0.064660
Batch: 1750/4218: 0.153526 0.166141
Batch: 1751/4218: 0.051185 0.067970
Batch: 1752/4218: 0.066179 0.090804
Batch: 1753/4218: 0.021612 0.034448
Batch: 1754/4218: 0.023915 0.040107
Batch: 1755/4218: 0.026660 0.039982
Batch: 1756/4218: 0.049701 0.065129
Batch: 1757/4218: 0.022143 0.035180
Batch: 1758/4218: 0.027988 0.046816
Batch: 1759/4218: 0.033602 0.047274
Batch: 1760/4218: 0.018445 0.032257
Batch: 1761/4218: 0.023026 0.037854
Batch: 1762/4218: 0.039784 0.054840
Batch: 1763/4218: 0.007413 0.020513
Batch: 1764/4218: 0.054734 0.066786
Batch: 1765/4218: 0.025913 0.039524
Batch: 1766/4218: 0.019339 0.037407
Batch: 1767/4218: 0.011110 0.023153
Batch: 1768/4218: 0.042809 0.055831
Batch: 1769/4218: 0.008486 0.022484
Batch: 1770/4218: 0.114504 0.126095
Batch: 1771/4218: 0.018255 0.030322
Batch: 1772/4218: 0.020150 0.032979
Batch: 1773/4218: 0.026233 0.038636
Batch: 1774/4218: 0.023062 0.037643
Batch: 1775/4218: 0.012206 0.039179
Batch: 1776/4218: 0.013666 0.029473
Batch: 1777/4218: 0.027584 0.040592
Batch: 1778/4218: 0.011645 0.026661
Batch: 1779/4218: 0.026098 0.044882
Batch: 1780/4218: 0.011711 0.046243
Batch: 1781/4218: 0.039472 0.076925
Batch: 1782/4218: 0.024330 0.041524
Batch: 1783/4218: 0.071122 0.083089
Batch: 1784/4218: 0.012454 0.029289
Batch: 1785/4218: 0.033870 0.048957
Batch: 1786/4218: 0.022807 0.036127
Batch: 1787/4218: 0.029584 0.046061
Batch: 1788/4218: 0.010832 0.028355
Batch: 1789/4218: 0.031195 0.049282
Batch: 1790/4218: 0.018205 0.049103
Batch: 1791/4218: 0.006821 0.026335
Batch: 1792/4218: 0.120722 0.145500
Batch: 1793/4218: 0.120960 0.136401
Batch: 1794/4218: 0.020461 0.036235
Batch: 1795/4218: 0.055917 0.071962
Batch: 1796/4218: 0.021126 0.037856
Batch: 1797/4218: 0.027199 0.041472
Batch: 1798/4218: 0.051462 0.064754
Batch: 1799/4218: 0.023140 0.035736
Batch: 1800/4218: 0.015678 0.028325
Batch: 1801/4218: 0.103163 0.116923
Batch: 1802/4218: 0.025513 0.050068
Batch: 1803/4218: 0.014415 0.028309
Batch: 1804/4218: 0.017183 0.032959
Batch: 1805/4218: 0.017875 0.031211
Batch: 1806/4218: 0.020860 0.035142
Batch: 1807/4218: 0.110229 0.123417
Batch: 1808/4218: 0.043062 0.060047
Batch: 1809/4218: 0.018086 0.032038
Batch: 1810/4218: 0.075746 0.096831
Batch: 1811/4218: 0.043389 0.056090
Batch: 1812/4218: 0.026537 0.038974
Batch: 1813/4218: 0.044134 0.056958
Batch: 1814/4218: 0.073439 0.086722
Batch: 1815/4218: 0.013038 0.030091
Batch: 1816/4218: 0.016438 0.035868
Batch: 1817/4218: 0.019424 0.032827
Batch: 1818/4218: 0.052494 0.069867
Batch: 1819/4218: 0.033364 0.047206
Batch: 1820/4218: 0.066843 0.097801
Batch: 1821/4218: 0.035803 0.050039
Batch: 1822/4218: 0.021429 0.035565
Batch: 1823/4218: 0.034250 0.050916
Batch: 1824/4218: 0.102266 0.115387
Batch: 1825/4218: 0.012073 0.026017
Batch: 1826/4218: 0.020253 0.036478
Batch: 1827/4218: 0.061852 0.077845
Batch: 1828/4218: 0.123508 0.137646
Batch: 1829/4218: 0.049454 0.065251
Batch: 1830/4218: 0.029969 0.043448
Batch: 1831/4218: 0.022666 0.035418
Batch: 1832/4218: 0.023357 0.036590
Batch: 1833/4218: 0.055402 0.067216
Batch: 1834/4218: 0.121739 0.134139
Batch: 1835/4218: 0.042985 0.060590
Batch: 1836/4218: 0.019692 0.033917
Batch: 1837/4218: 0.061907 0.075798
Batch: 1838/4218: 0.041138 0.054283
Batch: 1839/4218: 0.025244 0.036967
Batch: 1840/4218: 0.027352 0.043705
Batch: 1841/4218: 0.012320 0.034026
Batch: 1842/4218: 0.024614 0.036631
Batch: 1843/4218: 0.085169 0.097220
Batch: 1844/4218: 0.032290 0.047801
Batch: 1845/4218: 0.089353 0.100710
Batch: 1846/4218: 0.014879 0.026813
Batch: 1847/4218: 0.035507 0.047790
Batch: 1848/4218: 0.017397 0.030017
Batch: 1849/4218: 0.073025 0.084366
Batch: 1850/4218: 0.102869 0.114212
Batch: 1851/4218: 0.022200 0.037567
Batch: 1852/4218: 0.030746 0.042774
Batch: 1853/4218: 0.041670 0.054679
Batch: 1854/4218: 0.012603 0.023574
Batch: 1855/4218: 0.020749 0.031447
Batch: 1856/4218: 0.028680 0.041984
Batch: 1857/4218: 0.034125 0.072539
Batch: 1858/4218: 0.022350 0.034840
Batch: 1859/4218: 0.011889 0.023145
Batch: 1860/4218: 0.032222 0.047190
Batch: 1861/4218: 0.120365 0.134223
Batch: 1862/4218: 0.065268 0.081521
Batch: 1863/4218: 0.058279 0.074365
Batch: 1864/4218: 0.018428 0.030832
Batch: 1865/4218: 0.053355 0.067466
Batch: 1866/4218: 0.009397 0.021256
Batch: 1867/4218: 0.014451 0.027015
Batch: 1868/4218: 0.003736 0.015198
Batch: 1869/4218: 0.018712 0.029498
Batch: 1870/4218: 0.020866 0.032374
Batch: 1871/4218: 0.025204 0.040465
Batch: 1872/4218: 0.012086 0.025382
Batch: 1873/4218: 0.040472 0.053096
Batch: 1874/4218: 0.016312 0.027786
Batch: 1875/4218: 0.043495 0.055090
Batch: 1876/4218: 0.059117 0.072927
Batch: 1877/4218: 0.027479 0.038813
Batch: 1878/4218: 0.079082 0.090471
Batch: 1879/4218: 0.011128 0.024311
Batch: 1880/4218: 0.034339 0.057277
Batch: 1881/4218: 0.113408 0.134674
Batch: 1882/4218: 0.021333 0.044010
Batch: 1883/4218: 0.027634 0.044597
Batch: 1884/4218: 0.016222 0.028615
Batch: 1885/4218: 0.051744 0.064632
Batch: 1886/4218: 0.029828 0.043157
Batch: 1887/4218: 0.004101 0.017556
Batch: 1888/4218: 0.041537 0.053671
Batch: 1889/4218: 0.091311 0.103185
Batch: 1890/4218: 0.155045 0.165943
Batch: 1891/4218: 0.053953 0.065450
Batch: 1892/4218: 0.016595 0.027815
Batch: 1893/4218: 0.058251 0.072525
Batch: 1894/4218: 0.018724 0.029759
Batch: 1895/4218: 0.027789 0.038845
Batch: 1896/4218: 0.011562 0.024528
Batch: 1897/4218: 0.020563 0.030913
Batch: 1898/4218: 0.069893 0.080914
Batch: 1899/4218: 0.023974 0.036484
Batch: 1900/4218: 0.024727 0.034753
Batch: 1901/4218: 0.015369 0.027454
Batch: 1902/4218: 0.029736 0.042456
Batch: 1903/4218: 0.011534 0.021097
Batch: 1904/4218: 0.012182 0.024786
Batch: 1905/4218: 0.018711 0.045377
Batch: 1906/4218: 0.032299 0.047211
Batch: 1907/4218: 0.022256 0.032733
Batch: 1908/4218: 0.012991 0.023262
Batch: 1909/4218: 0.062163 0.073780
Batch: 1910/4218: 0.014965 0.026441
Batch: 1911/4218: 0.033648 0.045237
Batch: 1912/4218: 0.030345 0.041992
Batch: 1913/4218: 0.022100 0.033378
Batch: 1914/4218: 0.013963 0.024491
Batch: 1915/4218: 0.026843 0.039262
Batch: 1916/4218: 0.129331 0.139779
Batch: 1917/4218: 0.007387 0.018360
Batch: 1918/4218: 0.193858 0.210139
Batch: 1919/4218: 0.051310 0.061304
Batch: 1920/4218: 0.049074 0.066121
Batch: 1921/4218: 0.021197 0.034105
Batch: 1922/4218: 0.008158 0.017860
Batch: 1923/4218: 0.026474 0.038426
Batch: 1924/4218: 0.049654 0.060170
Batch: 1925/4218: 0.028507 0.039970
Batch: 1926/4218: 0.044637 0.056635
Batch: 1927/4218: 0.072623 0.082356
Batch: 1928/4218: 0.012088 0.022961
Batch: 1929/4218: 0.101933 0.114808
Batch: 1930/4218: 0.024737 0.034323
Batch: 1931/4218: 0.029659 0.040328
Batch: 1932/4218: 0.014999 0.024527
Batch: 1933/4218: 0.023204 0.032721
Batch: 1934/4218: 0.033686 0.043986
Batch: 1935/4218: 0.037608 0.051923
Batch: 1936/4218: 0.018486 0.030541
Batch: 1937/4218: 0.076630 0.090130
Batch: 1938/4218: 0.050991 0.062053
Batch: 1939/4218: 0.009037 0.023504
Batch: 1940/4218: 0.016979 0.028111
Batch: 1941/4218: 0.034585 0.046186
Batch: 1942/4218: 0.025996 0.039579
Batch: 1943/4218: 0.045633 0.056716
Batch: 1944/4218: 0.036766 0.047920
Batch: 1945/4218: 0.046813 0.061391
Batch: 1946/4218: 0.060913 0.070653
Batch: 1947/4218: 0.016554 0.026814
Batch: 1948/4218: 0.014913 0.024671
Batch: 1949/4218: 0.014637 0.024215
Batch: 1950/4218: 0.037962 0.058302
Batch: 1951/4218: 0.021071 0.033741
Batch: 1952/4218: 0.040112 0.050507
Batch: 1953/4218: 0.021278 0.032066
Batch: 1954/4218: 0.129129 0.138560
Batch: 1955/4218: 0.027449 0.041384
Batch: 1956/4218: 0.043469 0.054092
Batch: 1957/4218: 0.045608 0.059172
Batch: 1958/4218: 0.084303 0.103007
Batch: 1959/4218: 0.028430 0.039950
Batch: 1960/4218: 0.099693 0.112414
Batch: 1961/4218: 0.245579 0.255571
Batch: 1962/4218: 0.034263 0.045873
Batch: 1963/4218: 0.028565 0.039995
Batch: 1964/4218: 0.043501 0.055239
Batch: 1965/4218: 0.006486 0.017843
Batch: 1966/4218: 0.029743 0.043727
Batch: 1967/4218: 0.029119 0.040697
Batch: 1968/4218: 0.019310 0.028646
Batch: 1969/4218: 0.045796 0.055662
Batch: 1970/4218: 0.101093 0.112603
Batch: 1971/4218: 0.018282 0.034087
Batch: 1972/4218: 0.030384 0.042967
Batch: 1973/4218: 0.061777 0.072139
Batch: 1974/4218: 0.017443 0.030417
Batch: 1975/4218: 0.031830 0.042548
Batch: 1976/4218: 0.025735 0.036316
Batch: 1977/4218: 0.017039 0.027440
Batch: 1978/4218: 0.124076 0.133602
Batch: 1979/4218: 0.069593 0.080067
Batch: 1980/4218: 0.012548 0.021726
Batch: 1981/4218: 0.083587 0.093587
Batch: 1982/4218: 0.014993 0.024497
Batch: 1983/4218: 0.007535 0.018237
Batch: 1984/4218: 0.018470 0.028469
Batch: 1985/4218: 0.042369 0.051372
Batch: 1986/4218: 0.154888 0.170095
Batch: 1987/4218: 0.022675 0.034038
Batch: 1988/4218: 0.042684 0.054718
Batch: 1989/4218: 0.031656 0.046080
Batch: 1990/4218: 0.023228 0.034146
Batch: 1991/4218: 0.009696 0.020253
Batch: 1992/4218: 0.014467 0.023455
Batch: 1993/4218: 0.024364 0.034934
Batch: 1994/4218: 0.008189 0.018655
Batch: 1995/4218: 0.030375 0.042330
Batch: 1996/4218: 0.030712 0.043110
Batch: 1997/4218: 0.049809 0.058987
Batch: 1998/4218: 0.027965 0.038527
Batch: 1999/4218: 0.012761 0.021541
Batch: 2000/4218: 0.046262 0.055580
Batch: 2001/4218: 0.017107 0.028273
Batch: 2002/4218: 0.042671 0.052301
Batch: 2003/4218: 0.022281 0.035962
Batch: 2004/4218: 0.022151 0.032975
Batch: 2005/4218: 0.049133 0.060264
Batch: 2006/4218: 0.016224 0.027052
Batch: 2007/4218: 0.100279 0.109300
Batch: 2008/4218: 0.029235 0.037979
Batch: 2009/4218: 0.081207 0.090775
Batch: 2010/4218: 0.013537 0.023104
Batch: 2011/4218: 0.055210 0.064702
Batch: 2012/4218: 0.015598 0.025760
Batch: 2013/4218: 0.031009 0.041669
Batch: 2014/4218: 0.022185 0.032077
Batch: 2015/4218: 0.014007 0.029900
Batch: 2016/4218: 0.032226 0.042042
Batch: 2017/4218: 0.028185 0.037025
Batch: 2018/4218: 0.044285 0.055142
Batch: 2019/4218: 0.010861 0.024298
Batch: 2020/4218: 0.112456 0.121557
Batch: 2021/4218: 0.026289 0.038560
Batch: 2022/4218: 0.010020 0.023616
Batch: 2023/4218: 0.026662 0.041770
Batch: 2024/4218: 0.012665 0.020822
Batch: 2025/4218: 0.012775 0.024056
Batch: 2026/4218: 0.027839 0.038048
Batch: 2027/4218: 0.177677 0.187928
Batch: 2028/4218: 0.017602 0.025863
Batch: 2029/4218: 0.016215 0.026236
Batch: 2030/4218: 0.025551 0.035897
Batch: 2031/4218: 0.014657 0.025541
Batch: 2032/4218: 0.010793 0.020870
Batch: 2033/4218: 0.020783 0.035390
Batch: 2034/4218: 0.011249 0.021472
Batch: 2035/4218: 0.067877 0.077239
Batch: 2036/4218: 0.016622 0.028797
Batch: 2037/4218: 0.016266 0.028639
Batch: 2038/4218: 0.094968 0.109137
Batch: 2039/4218: 0.039480 0.051130
Batch: 2040/4218: 0.017163 0.026923
Batch: 2041/4218: 0.039917 0.051484
Batch: 2042/4218: 0.020080 0.030675
Batch: 2043/4218: 0.012664 0.026203
Batch: 2044/4218: 0.015797 0.024834
Batch: 2045/4218: 0.057627 0.066103
Batch: 2046/4218: 0.049387 0.057598
Batch: 2047/4218: 0.007809 0.017790
Batch: 2048/4218: 0.021258 0.030901
Batch: 2049/4218: 0.040061 0.050644
Batch: 2050/4218: 0.014982 0.026246
Batch: 2051/4218: 0.013553 0.021873
Batch: 2052/4218: 0.022078 0.031045
Batch: 2053/4218: 0.008183 0.016332
Batch: 2054/4218: 0.023941 0.033944
Batch: 2055/4218: 0.035187 0.043720
Batch: 2056/4218: 0.017238 0.026665
Batch: 2057/4218: 0.050823 0.060806
Batch: 2058/4218: 0.031963 0.041815
Batch: 2059/4218: 0.105178 0.113641
Batch: 2060/4218: 0.010746 0.020725
Batch: 2061/4218: 0.012244 0.030436
Batch: 2062/4218: 0.046458 0.055458
Batch: 2063/4218: 0.107858 0.118077
Batch: 2064/4218: 0.034060 0.042219
Batch: 2065/4218: 0.026491 0.035624
Batch: 2066/4218: 0.040364 0.051901
Batch: 2067/4218: 0.045319 0.054357
Batch: 2068/4218: 0.007527 0.018078
Batch: 2069/4218: 0.058616 0.068077
Batch: 2070/4218: 0.044539 0.055905
Batch: 2071/4218: 0.040393 0.049277
Batch: 2072/4218: 0.046463 0.055404
Batch: 2073/4218: 0.036030 0.044912
Batch: 2074/4218: 0.107805 0.119491
Batch: 2075/4218: 0.035693 0.044066
Batch: 2076/4218: 0.019042 0.030233
Batch: 2077/4218: 0.060598 0.070552
Batch: 2078/4218: 0.026646 0.036585
Batch: 2079/4218: 0.174877 0.187642
Batch: 2080/4218: 0.012684 0.021935
Batch: 2081/4218: 0.023282 0.031595
Batch: 2082/4218: 0.034680 0.044542
Batch: 2083/4218: 0.124681 0.132967
Batch: 2084/4218: 0.033381 0.043719
Batch: 2085/4218: 0.051207 0.060541
Batch: 2086/4218: 0.044472 0.053227
Batch: 2087/4218: 0.028290 0.036042
Batch: 2088/4218: 0.063380 0.072610
Batch: 2089/4218: 0.043705 0.051943
Batch: 2090/4218: 0.047153 0.055666
Batch: 2091/4218: 0.102260 0.110302
Batch: 2092/4218: 0.047514 0.056735
Batch: 2093/4218: 0.110518 0.118189
Batch: 2094/4218: 0.062535 0.070586
Batch: 2095/4218: 0.029361 0.039734
Batch: 2096/4218: 0.025429 0.033866
Batch: 2097/4218: 0.142268 0.149839
Batch: 2098/4218: 0.076769 0.084634
Batch: 2099/4218: 0.022736 0.031143
Batch: 2100/4218: 0.018077 0.029164
Batch: 2101/4218: 0.015796 0.023978
Batch: 2102/4218: 0.023978 0.031906
Batch: 2103/4218: 0.034094 0.041965
Batch: 2104/4218: 0.026252 0.036954
Batch: 2105/4218: 0.027636 0.035783
Batch: 2106/4218: 0.055791 0.064471
Batch: 2107/4218: 0.024573 0.032679
Batch: 2108/4218: 0.029484 0.037017
Batch: 2109/4218: 0.014784 0.024247
Batch: 2110/4218: 0.019830 0.031344
Batch: 2111/4218: 0.019342 0.027965
Batch: 2112/4218: 0.015899 0.027096
Batch: 2113/4218: 0.012411 0.022253
Batch: 2114/4218: 0.022635 0.030469
Batch: 2115/4218: 0.026992 0.034774
Batch: 2116/4218: 0.076966 0.088492
Batch: 2117/4218: 0.040545 0.051473
Batch: 2118/4218: 0.013239 0.022876
Batch: 2119/4218: 0.016235 0.024294
Batch: 2120/4218: 0.015246 0.024634
Batch: 2121/4218: 0.116547 0.126654
Batch: 2122/4218: 0.007089 0.014833
Batch: 2123/4218: 0.038411 0.046254
Batch: 2124/4218: 0.035239 0.043258
Batch: 2125/4218: 0.011922 0.023037
Batch: 2126/4218: 0.034441 0.042988
Batch: 2127/4218: 0.037531 0.045892
Batch: 2128/4218: 0.015273 0.026967
Batch: 2129/4218: 0.129714 0.137051
Batch: 2130/4218: 0.019176 0.027623
Batch: 2131/4218: 0.035690 0.044573
Batch: 2132/4218: 0.016224 0.023631
Batch: 2133/4218: 0.102180 0.110279
Batch: 2134/4218: 0.059142 0.067441
Batch: 2135/4218: 0.081275 0.088810
Batch: 2136/4218: 0.026866 0.034989
Batch: 2137/4218: 0.025428 0.032596
Batch: 2138/4218: 0.011178 0.018390
Batch: 2139/4218: 0.025096 0.051687
Batch: 2140/4218: 0.027937 0.035631
Batch: 2141/4218: 0.020890 0.030011
Batch: 2142/4218: 0.044566 0.053018
Batch: 2143/4218: 0.011840 0.021314
Batch: 2144/4218: 0.030370 0.038955
Batch: 2145/4218: 0.020005 0.028788
Batch: 2146/4218: 0.108214 0.116119
Batch: 2147/4218: 0.030090 0.038454
Batch: 2148/4218: 0.030063 0.037696
Batch: 2149/4218: 0.034595 0.041865
Batch: 2150/4218: 0.011176 0.018567
Batch: 2151/4218: 0.044899 0.051957
Batch: 2152/4218: 0.047517 0.055104
Batch: 2153/4218: 0.025225 0.036839
Batch: 2154/4218: 0.053732 0.060407
Batch: 2155/4218: 0.033465 0.046933
Batch: 2156/4218: 0.026083 0.033910
Batch: 2157/4218: 0.150362 0.158459
Batch: 2158/4218: 0.015536 0.023704
Batch: 2159/4218: 0.049123 0.061881
Batch: 2160/4218: 0.019447 0.027012
Batch: 2161/4218: 0.023867 0.033165
Batch: 2162/4218: 0.012988 0.023048
Batch: 2163/4218: 0.098289 0.106694
Batch: 2164/4218: 0.017417 0.029344
Batch: 2165/4218: 0.029642 0.038104
Batch: 2166/4218: 0.011717 0.019669
Batch: 2167/4218: 0.032692 0.043558
Batch: 2168/4218: 0.028512 0.035894
Batch: 2169/4218: 0.015445 0.023048
Batch: 2170/4218: 0.038816 0.046248
Batch: 2171/4218: 0.017527 0.027887
Batch: 2172/4218: 0.024202 0.032790
Batch: 2173/4218: 0.033118 0.040733
Batch: 2174/4218: 0.020265 0.028410
Batch: 2175/4218: 0.042689 0.050077
Batch: 2176/4218: 0.046371 0.053406
Batch: 2177/4218: 0.016846 0.024221
Batch: 2178/4218: 0.119597 0.127383
Batch: 2179/4218: 0.051334 0.062128
Batch: 2180/4218: 0.019608 0.027020
Batch: 2181/4218: 0.039507 0.050879
Batch: 2182/4218: 0.024084 0.034758
Batch: 2183/4218: 0.016789 0.026370
Batch: 2184/4218: 0.013884 0.020815
Batch: 2185/4218: 0.074662 0.081660
Batch: 2186/4218: 0.025163 0.032131
Batch: 2187/4218: 0.029797 0.037163
Batch: 2188/4218: 0.263341 0.273313
Batch: 2189/4218: 0.028367 0.035227
Batch: 2190/4218: 0.038572 0.047386
Batch: 2191/4218: 0.023684 0.031503
Batch: 2192/4218: 0.017716 0.025396
Batch: 2193/4218: 0.026700 0.033293
Batch: 2194/4218: 0.071997 0.079229
Batch: 2195/4218: 0.023041 0.030278
Batch: 2196/4218: 0.017771 0.026092
Batch: 2197/4218: 0.021027 0.030240
Batch: 2198/4218: 0.025728 0.033008
Batch: 2199/4218: 0.008394 0.016175
Batch: 2200/4218: 0.026402 0.033403
Batch: 2201/4218: 0.011223 0.020206
Batch: 2202/4218: 0.015152 0.022280
Batch: 2203/4218: 0.012498 0.021780
Batch: 2204/4218: 0.023085 0.030423
Batch: 2205/4218: 0.028602 0.036262
Batch: 2206/4218: 0.035209 0.041837
Batch: 2207/4218: 0.044157 0.053835
Batch: 2208/4218: 0.083151 0.090253
Batch: 2209/4218: 0.020982 0.028451
Batch: 2210/4218: 0.023785 0.032755
Batch: 2211/4218: 0.063710 0.071029
Batch: 2212/4218: 0.095668 0.103833
Batch: 2213/4218: 0.008878 0.018581
Batch: 2214/4218: 0.122230 0.128849
Batch: 2215/4218: 0.016701 0.026277
Batch: 2216/4218: 0.034304 0.042512
Batch: 2217/4218: 0.010302 0.018778
Batch: 2218/4218: 0.088607 0.097039
Batch: 2219/4218: 0.026576 0.034127
Batch: 2220/4218: 0.013589 0.021148
Batch: 2221/4218: 0.045823 0.052885
Batch: 2222/4218: 0.014935 0.028418
Batch: 2223/4218: 0.028639 0.036967
Batch: 2224/4218: 0.051231 0.058755
Batch: 2225/4218: 0.020945 0.028536
Batch: 2226/4218: 0.027623 0.036909
Batch: 2227/4218: 0.011595 0.018765
Batch: 2228/4218: 0.025340 0.034489
Batch: 2229/4218: 0.072219 0.083459
Batch: 2230/4218: 0.009952 0.016704
Batch: 2231/4218: 0.047752 0.056274
Batch: 2232/4218: 0.117765 0.124782
Batch: 2233/4218: 0.009198 0.015810
Batch: 2234/4218: 0.019641 0.028134
Batch: 2235/4218: 0.127698 0.135876
Batch: 2236/4218: 0.015305 0.021991
Batch: 2237/4218: 0.026230 0.033292
Batch: 2238/4218: 0.081252 0.090317
Batch: 2239/4218: 0.017485 0.027595
Batch: 2240/4218: 0.023006 0.029537
Batch: 2241/4218: 0.022497 0.029453
Batch: 2242/4218: 0.014731 0.022189
Batch: 2243/4218: 0.076725 0.083624
Batch: 2244/4218: 0.011633 0.018557
Batch: 2245/4218: 0.020075 0.029717
Batch: 2246/4218: 0.012422 0.019757
Batch: 2247/4218: 0.045580 0.057219
Batch: 2248/4218: 0.029026 0.036728
Batch: 2249/4218: 0.028368 0.035940
Batch: 2250/4218: 0.013318 0.020176
Batch: 2251/4218: 0.016034 0.023473
Batch: 2252/4218: 0.018681 0.026995
Batch: 2253/4218: 0.020405 0.027067
Batch: 2254/4218: 0.012681 0.019112
Batch: 2255/4218: 0.028003 0.037219
Batch: 2256/4218: 0.030960 0.038226
Batch: 2257/4218: 0.054447 0.062744
Batch: 2258/4218: 0.024995 0.033016
Batch: 2259/4218: 0.008085 0.014681
Batch: 2260/4218: 0.041035 0.047549
Batch: 2261/4218: 0.013446 0.019733
Batch: 2262/4218: 0.089279 0.096861
Batch: 2263/4218: 0.095941 0.103561
Batch: 2264/4218: 0.018049 0.025453
Batch: 2265/4218: 0.039270 0.046053
Batch: 2266/4218: 0.111044 0.118095
Batch: 2267/4218: 0.057634 0.063920
Batch: 2268/4218: 0.136784 0.146729
Batch: 2269/4218: 0.109996 0.126355
Batch: 2270/4218: 0.026346 0.033556
Batch: 2271/4218: 0.104050 0.113815
Batch: 2272/4218: 0.017614 0.025543
Batch: 2273/4218: 0.074816 0.081281
Batch: 2274/4218: 0.011436 0.020470
Batch: 2275/4218: 0.013949 0.028167
Batch: 2276/4218: 0.032351 0.047595
Batch: 2277/4218: 0.024753 0.036801
Batch: 2278/4218: 0.019827 0.030975
Batch: 2279/4218: 0.049548 0.057880
Batch: 2280/4218: 0.019315 0.026961
Batch: 2281/4218: 0.023555 0.031748
Batch: 2282/4218: 0.055619 0.063011
Batch: 2283/4218: 0.010718 0.022446
Batch: 2284/4218: 0.021518 0.030624
Batch: 2285/4218: 0.048822 0.055619
Batch: 2286/4218: 0.084843 0.091414
Batch: 2287/4218: 0.025906 0.033232
Batch: 2288/4218: 0.054424 0.061742
Batch: 2289/4218: 0.040377 0.049390
Batch: 2290/4218: 0.008629 0.016405
Batch: 2291/4218: 0.053236 0.060774
Batch: 2292/4218: 0.018349 0.025854
Batch: 2293/4218: 0.012960 0.019894
Batch: 2294/4218: 0.039270 0.046633
Batch: 2295/4218: 0.018214 0.026129
Batch: 2296/4218: 0.011360 0.018099
Batch: 2297/4218: 0.027483 0.034346
Batch: 2298/4218: 0.053346 0.061647
Batch: 2299/4218: 0.015460 0.024698
Batch: 2300/4218: 0.091057 0.098011
Batch: 2301/4218: 0.084846 0.096325
Batch: 2302/4218: 0.014151 0.020957
Batch: 2303/4218: 0.012748 0.023507
Batch: 2304/4218: 0.019880 0.026412
Batch: 2305/4218: 0.019489 0.026372
Batch: 2306/4218: 0.012978 0.019672
Batch: 2307/4218: 0.028898 0.035541
Batch: 2308/4218: 0.027035 0.034672
Batch: 2309/4218: 0.126751 0.136130
Batch: 2310/4218: 0.010310 0.017366
Batch: 2311/4218: 0.028569 0.034855
Batch: 2312/4218: 0.036606 0.045398
Batch: 2313/4218: 0.038014 0.044757
Batch: 2314/4218: 0.048630 0.055471
Batch: 2315/4218: 0.084590 0.097509
Batch: 2316/4218: 0.028947 0.035491
Batch: 2317/4218: 0.024354 0.033692
Batch: 2318/4218: 0.021293 0.028053
Batch: 2319/4218: 0.012756 0.020577
Batch: 2320/4218: 0.034384 0.041599
Batch: 2321/4218: 0.006651 0.014235
Batch: 2322/4218: 0.057074 0.063979
Batch: 2323/4218: 0.016709 0.025118
Batch: 2324/4218: 0.023120 0.030351
Batch: 2325/4218: 0.010941 0.017983
Batch: 2326/4218: 0.017798 0.025225
Batch: 2327/4218: 0.031742 0.041205
Batch: 2328/4218: 0.042758 0.052077
Batch: 2329/4218: 0.057132 0.063465
Batch: 2330/4218: 0.008488 0.015097
Batch: 2331/4218: 0.024206 0.031233
Batch: 2332/4218: 0.015941 0.022775
Batch: 2333/4218: 0.020763 0.027048
Batch: 2334/4218: 0.028047 0.034060
Batch: 2335/4218: 0.023461 0.030692
Batch: 2336/4218: 0.061134 0.069342
Batch: 2337/4218: 0.038505 0.044476
Batch: 2338/4218: 0.024236 0.031377
Batch: 2339/4218: 0.112069 0.117942
Batch: 2340/4218: 0.062796 0.070346
Batch: 2341/4218: 0.061691 0.069792
Batch: 2342/4218: 0.077951 0.085058
Batch: 2343/4218: 0.185952 0.192152
Batch: 2344/4218: 0.063280 0.069934
Batch: 2345/4218: 0.026790 0.032980
Batch: 2346/4218: 0.013622 0.020805
Batch: 2347/4218: 0.051265 0.057892
Batch: 2348/4218: 0.029826 0.035805
Batch: 2349/4218: 0.037561 0.045742
Batch: 2350/4218: 0.027672 0.033708
Batch: 2351/4218: 0.022725 0.031239
Batch: 2352/4218: 0.025453 0.032106
Batch: 2353/4218: 0.049679 0.058357
Batch: 2354/4218: 0.031220 0.037021
Batch: 2355/4218: 0.029697 0.035590
Batch: 2356/4218: 0.015943 0.021849
Batch: 2357/4218: 0.023410 0.029365
Batch: 2358/4218: 0.010548 0.016938
Batch: 2359/4218: 0.023472 0.029379
Batch: 2360/4218: 0.047276 0.055397
Batch: 2361/4218: 0.036821 0.043109
Batch: 2362/4218: 0.054274 0.060675
Batch: 2363/4218: 0.038191 0.044195
Batch: 2364/4218: 0.037089 0.043703
Batch: 2365/4218: 0.027064 0.033134
Batch: 2366/4218: 0.051174 0.058238
Batch: 2367/4218: 0.060388 0.071256
Batch: 2368/4218: 0.022417 0.028894
Batch: 2369/4218: 0.041293 0.048530
Batch: 2370/4218: 0.008731 0.015306
Batch: 2371/4218: 0.026754 0.034437
Batch: 2372/4218: 0.026151 0.033996
Batch: 2373/4218: 0.056761 0.062260
Batch: 2374/4218: 0.087284 0.094122
Batch: 2375/4218: 0.009925 0.016637
Batch: 2376/4218: 0.036602 0.043574
Batch: 2377/4218: 0.153740 0.159776
Batch: 2378/4218: 0.070764 0.076820
Batch: 2379/4218: 0.056044 0.062654
Batch: 2380/4218: 0.059370 0.065248
Batch: 2381/4218: 0.044773 0.050756
Batch: 2382/4218: 0.047354 0.053561
Batch: 2383/4218: 0.130609 0.136290
Batch: 2384/4218: 0.051787 0.057675
Batch: 2385/4218: 0.047220 0.052519
Batch: 2386/4218: 0.042920 0.048161
Batch: 2387/4218: 0.043230 0.050243
Batch: 2388/4218: 0.011127 0.017156
Batch: 2389/4218: 0.040304 0.048034
Batch: 2390/4218: 0.043145 0.049164
Batch: 2391/4218: 0.035935 0.042216
Batch: 2392/4218: 0.021223 0.026722
Batch: 2393/4218: 0.054981 0.063534
Batch: 2394/4218: 0.021055 0.026952
Batch: 2395/4218: 0.009237 0.015941
Batch: 2396/4218: 0.047865 0.053935
Batch: 2397/4218: 0.039140 0.044785
Batch: 2398/4218: 0.011470 0.016693
Batch: 2399/4218: 0.017784 0.023848
Batch: 2400/4218: 0.022406 0.028944
Batch: 2401/4218: 0.072554 0.079301
Batch: 2402/4218: 0.012097 0.018709
Batch: 2403/4218: 0.017830 0.023013
Batch: 2404/4218: 0.018679 0.025437
Batch: 2405/4218: 0.021190 0.027187
Batch: 2406/4218: 0.011787 0.018431
Batch: 2407/4218: 0.012846 0.018790
Batch: 2408/4218: 0.028123 0.033928
Batch: 2409/4218: 0.040868 0.046377
Batch: 2410/4218: 0.024161 0.032817
Batch: 2411/4218: 0.012663 0.018065
Batch: 2412/4218: 0.022486 0.028631
Batch: 2413/4218: 0.022138 0.027446
Batch: 2414/4218: 0.079765 0.084994
Batch: 2415/4218: 0.031649 0.038059
Batch: 2416/4218: 0.067765 0.073534
Batch: 2417/4218: 0.011976 0.017141
Batch: 2418/4218: 0.011685 0.020939
Batch: 2419/4218: 0.013959 0.019990
Batch: 2420/4218: 0.056301 0.061616
Batch: 2421/4218: 0.009526 0.014702
Batch: 2422/4218: 0.009861 0.015278
Batch: 2423/4218: 0.059790 0.065591
Batch: 2424/4218: 0.172433 0.177798
Batch: 2425/4218: 0.036059 0.041915
Batch: 2426/4218: 0.039009 0.044860
Batch: 2427/4218: 0.150186 0.157646
Batch: 2428/4218: 0.024318 0.029692
Batch: 2429/4218: 0.020871 0.028149
Batch: 2430/4218: 0.048284 0.077323
Batch: 2431/4218: 0.018542 0.025496
Batch: 2432/4218: 0.036341 0.042676
Batch: 2433/4218: 0.030569 0.036099
Batch: 2434/4218: 0.016652 0.023072
Batch: 2435/4218: 0.010114 0.017100
Batch: 2436/4218: 0.027731 0.033444
Batch: 2437/4218: 0.183707 0.190311
Batch: 2438/4218: 0.034789 0.041503
Batch: 2439/4218: 0.074768 0.083184
Batch: 2440/4218: 0.018753 0.024493
Batch: 2441/4218: 0.012546 0.020621
Batch: 2442/4218: 0.008011 0.013503
Batch: 2443/4218: 0.025195 0.031319
Batch: 2444/4218: 0.018098 0.023437
Batch: 2445/4218: 0.061199 0.068764
Batch: 2446/4218: 0.011890 0.017026
Batch: 2447/4218: 0.018833 0.024086
Batch: 2448/4218: 0.012119 0.017721
Batch: 2449/4218: 0.129601 0.135862
Batch: 2450/4218: 0.014582 0.019868
Batch: 2451/4218: 0.113445 0.121238
Batch: 2452/4218: 0.041461 0.046749
Batch: 2453/4218: 0.024889 0.030244
Batch: 2454/4218: 0.052870 0.058712
Batch: 2455/4218: 0.023529 0.029079
Batch: 2456/4218: 0.031796 0.037899
Batch: 2457/4218: 0.037003 0.043050
Batch: 2458/4218: 0.033654 0.039761
Batch: 2459/4218: 0.011560 0.018107
Batch: 2460/4218: 0.057287 0.062608
Batch: 2461/4218: 0.047914 0.053568
Batch: 2462/4218: 0.021030 0.025929
Batch: 2463/4218: 0.009000 0.016704
Batch: 2464/4218: 0.029353 0.034497
Batch: 2465/4218: 0.021016 0.027039
Batch: 2466/4218: 0.046754 0.052544
Batch: 2467/4218: 0.023171 0.033559
Batch: 2468/4218: 0.022809 0.028010
Batch: 2469/4218: 0.011532 0.018847
Batch: 2470/4218: 0.056988 0.062911
Batch: 2471/4218: 0.024114 0.031282
Batch: 2472/4218: 0.009515 0.015386
Batch: 2473/4218: 0.015628 0.021889
Batch: 2474/4218: 0.047751 0.053774
Batch: 2475/4218: 0.038108 0.044951
Batch: 2476/4218: 0.016620 0.021912
Batch: 2477/4218: 0.017583 0.022564
Batch: 2478/4218: 0.007315 0.013240
Batch: 2479/4218: 0.035251 0.041277
Batch: 2480/4218: 0.065804 0.071403
Batch: 2481/4218: 0.039400 0.044603
Batch: 2482/4218: 0.013830 0.019959
Batch: 2483/4218: 0.059234 0.064479
Batch: 2484/4218: 0.009194 0.019957
Batch: 2485/4218: 0.019539 0.024839
Batch: 2486/4218: 0.009393 0.015024
Batch: 2487/4218: 0.074495 0.079964
Batch: 2488/4218: 0.019917 0.034931
Batch: 2489/4218: 0.018083 0.023211
Batch: 2490/4218: 0.030708 0.035940
Batch: 2491/4218: 0.012886 0.019050
Batch: 2492/4218: 0.026645 0.031701
Batch: 2493/4218: 0.091045 0.097535
Batch: 2494/4218: 0.013190 0.018286
Batch: 2495/4218: 0.013181 0.019819
Batch: 2496/4218: 0.069080 0.075177
Batch: 2497/4218: 0.034585 0.041785
Batch: 2498/4218: 0.018339 0.026060
Batch: 2499/4218: 0.062357 0.067433
Batch: 2500/4218: 0.029273 0.035325
Batch: 2501/4218: 0.020424 0.026178
Batch: 2502/4218: 0.028567 0.034730
Batch: 2503/4218: 0.014867 0.022461
Batch: 2504/4218: 0.023734 0.029126
Batch: 2505/4218: 0.016168 0.021589
Batch: 2506/4218: 0.173536 0.179566
Batch: 2507/4218: 0.037239 0.043143
Batch: 2508/4218: 0.040884 0.045905
Batch: 2509/4218: 0.032780 0.038180
Batch: 2510/4218: 0.037931 0.045093
Batch: 2511/4218: 0.021807 0.030614
Batch: 2512/4218: 0.021243 0.026696
Batch: 2513/4218: 0.030344 0.035702
Batch: 2514/4218: 0.242716 0.247714
Batch: 2515/4218: 0.068042 0.074565
Batch: 2516/4218: 0.013702 0.020465
Batch: 2517/4218: 0.030874 0.037718
Batch: 2518/4218: 0.026425 0.031974
Batch: 2519/4218: 0.137647 0.143820
Batch: 2520/4218: 0.081899 0.087641
Batch: 2521/4218: 0.038195 0.043302
Batch: 2522/4218: 0.020576 0.027144
Batch: 2523/4218: 0.020388 0.026406
Batch: 2524/4218: 0.019895 0.024462
Batch: 2525/4218: 0.046619 0.054224
Batch: 2526/4218: 0.025991 0.031668
Batch: 2527/4218: 0.051985 0.061423
Batch: 2528/4218: 0.108952 0.115584
Batch: 2529/4218: 0.032211 0.038537
Batch: 2530/4218: 0.008470 0.015791
Batch: 2531/4218: 0.026652 0.033725
Batch: 2532/4218: 0.028926 0.033693
Batch: 2533/4218: 0.019770 0.026255
Batch: 2534/4218: 0.027619 0.033426
Batch: 2535/4218: 0.039942 0.047561
Batch: 2536/4218: 0.038854 0.044739
Batch: 2537/4218: 0.020640 0.026075
Batch: 2538/4218: 0.021313 0.027012
Batch: 2539/4218: 0.032844 0.038264
Batch: 2540/4218: 0.012004 0.021004
Batch: 2541/4218: 0.023881 0.029772
Batch: 2542/4218: 0.023728 0.030981
Batch: 2543/4218: 0.029316 0.034696
Batch: 2544/4218: 0.082835 0.090936
Batch: 2545/4218: 0.026858 0.033311
Batch: 2546/4218: 0.028117 0.039336
Batch: 2547/4218: 0.009393 0.014458
Batch: 2548/4218: 0.035417 0.042383
Batch: 2549/4218: 0.027074 0.032841
Batch: 2550/4218: 0.011451 0.021505
Batch: 2551/4218: 0.014556 0.019671
Batch: 2552/4218: 0.010140 0.016346
Batch: 2553/4218: 0.037021 0.042978
Batch: 2554/4218: 0.010783 0.015788
Batch: 2555/4218: 0.028969 0.036720
Batch: 2556/4218: 0.012051 0.017404
Batch: 2557/4218: 0.017118 0.021897
Batch: 2558/4218: 0.039994 0.048060
Batch: 2559/4218: 0.019066 0.026047
Batch: 2560/4218: 0.048038 0.053544
Batch: 2561/4218: 0.056861 0.062780
Batch: 2562/4218: 0.107131 0.114292
Batch: 2563/4218: 0.051294 0.056339
Batch: 2564/4218: 0.015462 0.020615
Batch: 2565/4218: 0.010389 0.016209
Batch: 2566/4218: 0.039057 0.043667
Batch: 2567/4218: 0.015884 0.022919
Batch: 2568/4218: 0.019819 0.025641
Batch: 2569/4218: 0.013541 0.018102
Batch: 2570/4218: 0.020010 0.025360
Batch: 2571/4218: 0.019304 0.024618
Batch: 2572/4218: 0.016895 0.021656
Batch: 2573/4218: 0.018985 0.024748
Batch: 2574/4218: 0.015013 0.020991
Batch: 2575/4218: 0.087812 0.092788
Batch: 2576/4218: 0.017506 0.022123
Batch: 2577/4218: 0.017509 0.022348
Batch: 2578/4218: 0.041157 0.045681
Batch: 2579/4218: 0.016127 0.020807
Batch: 2580/4218: 0.032446 0.038937
Batch: 2581/4218: 0.116259 0.121275
Batch: 2582/4218: 0.027717 0.032487
Batch: 2583/4218: 0.026133 0.030817
Batch: 2584/4218: 0.071617 0.078507
Batch: 2585/4218: 0.032355 0.039439
Batch: 2586/4218: 0.014444 0.018882
Batch: 2587/4218: 0.013440 0.017834
Batch: 2588/4218: 0.018426 0.023146
Batch: 2589/4218: 0.023678 0.028194
Batch: 2590/4218: 0.015000 0.025191
Batch: 2591/4218: 0.014651 0.019585
Batch: 2592/4218: 0.020572 0.025006
Batch: 2593/4218: 0.044002 0.049345
Batch: 2594/4218: 0.025808 0.030519
Batch: 2595/4218: 0.065816 0.070435
Batch: 2596/4218: 0.022416 0.029841
Batch: 2597/4218: 0.019957 0.027502
Batch: 2598/4218: 0.008073 0.013003
Batch: 2599/4218: 0.015205 0.020372
Batch: 2600/4218: 0.017639 0.022424
Batch: 2601/4218: 0.085476 0.091250
Batch: 2602/4218: 0.020636 0.027370
Batch: 2603/4218: 0.132784 0.137709
Batch: 2604/4218: 0.024711 0.030166
Batch: 2605/4218: 0.046166 0.051631
Batch: 2606/4218: 0.093082 0.100429
Batch: 2607/4218: 0.036562 0.042411
Batch: 2608/4218: 0.033750 0.041224
Batch: 2609/4218: 0.010358 0.015314
Batch: 2610/4218: 0.027872 0.033879
Batch: 2611/4218: 0.022584 0.031372
Batch: 2612/4218: 0.010570 0.015428
Batch: 2613/4218: 0.009016 0.018233
Batch: 2614/4218: 0.026271 0.031381
Batch: 2615/4218: 0.015406 0.020075
Batch: 2616/4218: 0.058385 0.063931
Batch: 2617/4218: 0.029986 0.034785
Batch: 2618/4218: 0.069702 0.074219
Batch: 2619/4218: 0.087789 0.092508
Batch: 2620/4218: 0.031635 0.035963
Batch: 2621/4218: 0.009358 0.014017
Batch: 2622/4218: 0.012726 0.017383
Batch: 2623/4218: 0.017138 0.021882
Batch: 2624/4218: 0.017379 0.022483
Batch: 2625/4218: 0.035411 0.040286
Batch: 2626/4218: 0.010192 0.015692
Batch: 2627/4218: 0.067863 0.072686
Batch: 2628/4218: 0.044639 0.049614
Batch: 2629/4218: 0.022897 0.027680
Batch: 2630/4218: 0.091209 0.095495
Batch: 2631/4218: 0.054024 0.059395
Batch: 2632/4218: 0.030014 0.034165
Batch: 2633/4218: 0.014972 0.019822
Batch: 2634/4218: 0.021939 0.026998
Batch: 2635/4218: 0.008710 0.014075
Batch: 2636/4218: 0.049622 0.057931
Batch: 2637/4218: 0.013578 0.018190
Batch: 2638/4218: 0.015598 0.019915
Batch: 2639/4218: 0.056990 0.061231
Batch: 2640/4218: 0.009693 0.014416
Batch: 2641/4218: 0.037563 0.042024
Batch: 2642/4218: 0.033438 0.038162
Batch: 2643/4218: 0.014630 0.020385
Batch: 2644/4218: 0.011257 0.015368
Batch: 2645/4218: 0.016878 0.021954
Batch: 2646/4218: 0.039980 0.046100
Batch: 2647/4218: 0.013351 0.017543
Batch: 2648/4218: 0.036509 0.041072
Batch: 2649/4218: 0.018008 0.022314
Batch: 2650/4218: 0.013737 0.017948
Batch: 2651/4218: 0.043721 0.048193
Batch: 2652/4218: 0.013579 0.018500
Batch: 2653/4218: 0.012693 0.017514
Batch: 2654/4218: 0.034536 0.038708
Batch: 2655/4218: 0.045035 0.049292
Batch: 2656/4218: 0.048457 0.052588
Batch: 2657/4218: 0.021512 0.026265
Batch: 2658/4218: 0.040351 0.045875
Batch: 2659/4218: 0.071334 0.075349
Batch: 2660/4218: 0.055773 0.061481
Batch: 2661/4218: 0.030745 0.035466
Batch: 2662/4218: 0.018242 0.022528
Batch: 2663/4218: 0.024700 0.029435
Batch: 2664/4218: 0.044674 0.048577
Batch: 2665/4218: 0.095083 0.106217
Batch: 2666/4218: 0.015365 0.020407
Batch: 2667/4218: 0.034802 0.039070
Batch: 2668/4218: 0.020786 0.025232
Batch: 2669/4218: 0.083293 0.087539
Batch: 2670/4218: 0.039768 0.046848
Batch: 2671/4218: 0.024516 0.029055
Batch: 2672/4218: 0.086030 0.090256
Batch: 2673/4218: 0.024162 0.029101
Batch: 2674/4218: 0.022122 0.026696
Batch: 2675/4218: 0.059934 0.065449
Batch: 2676/4218: 0.036639 0.044483
Batch: 2677/4218: 0.021039 0.026219
Batch: 2678/4218: 0.071459 0.075919
Batch: 2679/4218: 0.142014 0.146029
Batch: 2680/4218: 0.014139 0.018191
Batch: 2681/4218: 0.073127 0.079006
Batch: 2682/4218: 0.070187 0.074763
Batch: 2683/4218: 0.038124 0.042299
Batch: 2684/4218: 0.029577 0.036582
Batch: 2685/4218: 0.024720 0.029024
Batch: 2686/4218: 0.016730 0.021280
Batch: 2687/4218: 0.038523 0.043651
Batch: 2688/4218: 0.030244 0.039071
Batch: 2689/4218: 0.061987 0.066321
Batch: 2690/4218: 0.160011 0.164776
Batch: 2691/4218: 0.067902 0.072086
Batch: 2692/4218: 0.104170 0.109733
Batch: 2693/4218: 0.020871 0.025595
Batch: 2694/4218: 0.125086 0.129302
Batch: 2695/4218: 0.016637 0.020830
Batch: 2696/4218: 0.041032 0.045402
Batch: 2697/4218: 0.041889 0.046056
Batch: 2698/4218: 0.035499 0.042278
Batch: 2699/4218: 0.016746 0.022033
Batch: 2700/4218: 0.038929 0.042855
Batch: 2701/4218: 0.025176 0.030325
Batch: 2702/4218: 0.023695 0.027898
Batch: 2703/4218: 0.016267 0.020741
Batch: 2704/4218: 0.028308 0.035838
Batch: 2705/4218: 0.033972 0.037914
Batch: 2706/4218: 0.041317 0.046392
Batch: 2707/4218: 0.128979 0.133004
Batch: 2708/4218: 0.022150 0.027327
Batch: 2709/4218: 0.038483 0.043066
Batch: 2710/4218: 0.006886 0.011151
Batch: 2711/4218: 0.043273 0.047965
Batch: 2712/4218: 0.033869 0.038127
Batch: 2713/4218: 0.028361 0.032860
Batch: 2714/4218: 0.017111 0.021434
Batch: 2715/4218: 0.021042 0.024839
Batch: 2716/4218: 0.024180 0.028318
Batch: 2717/4218: 0.067255 0.072749
Batch: 2718/4218: 0.024070 0.027916
Batch: 2719/4218: 0.011883 0.015859
Batch: 2720/4218: 0.059491 0.064611
Batch: 2721/4218: 0.035308 0.039947
Batch: 2722/4218: 0.041479 0.047156
Batch: 2723/4218: 0.010273 0.014206
Batch: 2724/4218: 0.052234 0.056175
Batch: 2725/4218: 0.032365 0.036449
Batch: 2726/4218: 0.058580 0.063930
Batch: 2727/4218: 0.011118 0.014777
Batch: 2728/4218: 0.014765 0.020300
Batch: 2729/4218: 0.034745 0.039425
Batch: 2730/4218: 0.075097 0.079038
Batch: 2731/4218: 0.006271 0.012479
Batch: 2732/4218: 0.016267 0.020105
Batch: 2733/4218: 0.011192 0.015189
Batch: 2734/4218: 0.023820 0.029429
Batch: 2735/4218: 0.023388 0.027541
Batch: 2736/4218: 0.099160 0.103391
Batch: 2737/4218: 0.066963 0.070743
Batch: 2738/4218: 0.009731 0.013464
Batch: 2739/4218: 0.028245 0.034234
Batch: 2740/4218: 0.028976 0.032821
Batch: 2741/4218: 0.015032 0.019606
Batch: 2742/4218: 0.031894 0.035822
Batch: 2743/4218: 0.011772 0.016368
Batch: 2744/4218: 0.025448 0.029908
Batch: 2745/4218: 0.017689 0.022007
Batch: 2746/4218: 0.083746 0.087471
Batch: 2747/4218: 0.006067 0.011596
Batch: 2748/4218: 0.010093 0.014909
Batch: 2749/4218: 0.010477 0.014505
Batch: 2750/4218: 0.022545 0.027119
Batch: 2751/4218: 0.022293 0.026813
Batch: 2752/4218: 0.012937 0.016750
Batch: 2753/4218: 0.026989 0.032272
Batch: 2754/4218: 0.019679 0.027630
Batch: 2755/4218: 0.027900 0.033306
Batch: 2756/4218: 0.039968 0.043558
Batch: 2757/4218: 0.022515 0.026369
Batch: 2758/4218: 0.038285 0.042103
Batch: 2759/4218: 0.035190 0.040234
Batch: 2760/4218: 0.020074 0.025035
Batch: 2761/4218: 0.031930 0.037120
Batch: 2762/4218: 0.014274 0.018372
Batch: 2763/4218: 0.022126 0.026354
Batch: 2764/4218: 0.021857 0.025713
Batch: 2765/4218: 0.022001 0.025885
Batch: 2766/4218: 0.046789 0.051794
Batch: 2767/4218: 0.033624 0.037562
Batch: 2768/4218: 0.041292 0.045347
Batch: 2769/4218: 0.019786 0.024925
Batch: 2770/4218: 0.028364 0.032068
Batch: 2771/4218: 0.027031 0.032120
Batch: 2772/4218: 0.066252 0.070394
Batch: 2773/4218: 0.028993 0.033087
Batch: 2774/4218: 0.007686 0.011327
Batch: 2775/4218: 0.005389 0.009260
Batch: 2776/4218: 0.016896 0.020918
Batch: 2777/4218: 0.030534 0.034093
Batch: 2778/4218: 0.011542 0.015335
Batch: 2779/4218: 0.030120 0.033930
Batch: 2780/4218: 0.009442 0.013096
Batch: 2781/4218: 0.007227 0.011270
Batch: 2782/4218: 0.011970 0.015643
Batch: 2783/4218: 0.012496 0.017964
Batch: 2784/4218: 0.046665 0.050248
Batch: 2785/4218: 0.024293 0.028611
Batch: 2786/4218: 0.043447 0.050123
Batch: 2787/4218: 0.072669 0.078334
Batch: 2788/4218: 0.009992 0.013803
Batch: 2789/4218: 0.014656 0.018403
Batch: 2790/4218: 0.013442 0.018548
Batch: 2791/4218: 0.026509 0.030190
Batch: 2792/4218: 0.015631 0.020919
Batch: 2793/4218: 0.044749 0.048901
Batch: 2794/4218: 0.127803 0.132190
Batch: 2795/4218: 0.120295 0.124278
Batch: 2796/4218: 0.006259 0.010083
Batch: 2797/4218: 0.014555 0.018358
Batch: 2798/4218: 0.011485 0.014922
Batch: 2799/4218: 0.035760 0.040644
Batch: 2800/4218: 0.025942 0.029570
Batch: 2801/4218: 0.020673 0.024658
Batch: 2802/4218: 0.020400 0.026576
Batch: 2803/4218: 0.071312 0.074989
Batch: 2804/4218: 0.013801 0.021218
Batch: 2805/4218: 0.014131 0.018966
Batch: 2806/4218: 0.006145 0.011540
Batch: 2807/4218: 0.025274 0.030000
Batch: 2808/4218: 0.016929 0.021522
Batch: 2809/4218: 0.221883 0.225575
Batch: 2810/4218: 0.017132 0.021350
Batch: 2811/4218: 0.020303 0.025755
Batch: 2812/4218: 0.026779 0.030674
Batch: 2813/4218: 0.096269 0.100489
Batch: 2814/4218: 0.011267 0.015732
Batch: 2815/4218: 0.036459 0.040831
Batch: 2816/4218: 0.129279 0.145062
Batch: 2817/4218: 0.017648 0.021537
Batch: 2818/4218: 0.018335 0.023759
Batch: 2819/4218: 0.029906 0.036759
Batch: 2820/4218: 0.036817 0.045444
Batch: 2821/4218: 0.028096 0.047541
Batch: 2822/4218: 0.020843 0.024586
Batch: 2823/4218: 0.016767 0.020871
Batch: 2824/4218: 0.139279 0.142942
Batch: 2825/4218: 0.031158 0.039710
Batch: 2826/4218: 0.047090 0.052125
Batch: 2827/4218: 0.030835 0.045159
Batch: 2828/4218: 0.009563 0.015620
Batch: 2829/4218: 0.008938 0.019723
Batch: 2830/4218: 0.072091 0.077207
Batch: 2831/4218: 0.059077 0.065086
Batch: 2832/4218: 0.022918 0.027372
Batch: 2833/4218: 0.026484 0.030045
Batch: 2834/4218: 0.042079 0.046997
Batch: 2835/4218: 0.036719 0.046671
Batch: 2836/4218: 0.049536 0.053882
Batch: 2837/4218: 0.046038 0.056589
Batch: 2838/4218: 0.015231 0.020016
Batch: 2839/4218: 0.041636 0.046729
Batch: 2840/4218: 0.068377 0.072967
Batch: 2841/4218: 0.025780 0.030088
Batch: 2842/4218: 0.198759 0.205553
Batch: 2843/4218: 0.018046 0.029585
Batch: 2844/4218: 0.011521 0.015751
Batch: 2845/4218: 0.022063 0.029862
Batch: 2846/4218: 0.077788 0.082510
Batch: 2847/4218: 0.013077 0.017572
Batch: 2848/4218: 0.023466 0.027061
Batch: 2849/4218: 0.006540 0.010386
Batch: 2850/4218: 0.028345 0.033886
Batch: 2851/4218: 0.032904 0.039359
Batch: 2852/4218: 0.023898 0.028453
Batch: 2853/4218: 0.025649 0.030630
Batch: 2854/4218: 0.010924 0.015442
Batch: 2855/4218: 0.006504 0.011485
Batch: 2856/4218: 0.050475 0.054547
Batch: 2857/4218: 0.022628 0.027835
Batch: 2858/4218: 0.018179 0.021917
Batch: 2859/4218: 0.013886 0.018047
Batch: 2860/4218: 0.033339 0.037694
Batch: 2861/4218: 0.011830 0.016797
Batch: 2862/4218: 0.055181 0.059518
Batch: 2863/4218: 0.093767 0.099586
Batch: 2864/4218: 0.137787 0.145624
Batch: 2865/4218: 0.033129 0.039078
Batch: 2866/4218: 0.020969 0.025243
Batch: 2867/4218: 0.015973 0.021564
Batch: 2868/4218: 0.018788 0.022993
Batch: 2869/4218: 0.022932 0.028747
Batch: 2870/4218: 0.008484 0.013272
Batch: 2871/4218: 0.072492 0.076949
Batch: 2872/4218: 0.023110 0.027446
Batch: 2873/4218: 0.006823 0.011589
Batch: 2874/4218: 0.028076 0.032582
Batch: 2875/4218: 0.026861 0.031621
Batch: 2876/4218: 0.027294 0.037439
Batch: 2877/4218: 0.022272 0.025831
Batch: 2878/4218: 0.010705 0.014454
Batch: 2879/4218: 0.009053 0.012899
Batch: 2880/4218: 0.015115 0.022718
Batch: 2881/4218: 0.015782 0.021700
Batch: 2882/4218: 0.029461 0.037672
Batch: 2883/4218: 0.044758 0.049290
Batch: 2884/4218: 0.083277 0.088807
Batch: 2885/4218: 0.010704 0.014630
Batch: 2886/4218: 0.042554 0.046876
Batch: 2887/4218: 0.036804 0.040735
Batch: 2888/4218: 0.019775 0.023928
Batch: 2889/4218: 0.020104 0.027630
Batch: 2890/4218: 0.028544 0.035403
Batch: 2891/4218: 0.038456 0.043598
Batch: 2892/4218: 0.020064 0.025346
Batch: 2893/4218: 0.033544 0.037327
Batch: 2894/4218: 0.072217 0.079084
Batch: 2895/4218: 0.018848 0.024520
Batch: 2896/4218: 0.048372 0.052116
Batch: 2897/4218: 0.019786 0.023385
Batch: 2898/4218: 0.030935 0.035874
Batch: 2899/4218: 0.059021 0.063296
Batch: 2900/4218: 0.013363 0.017044
Batch: 2901/4218: 0.014215 0.017874
Batch: 2902/4218: 0.032811 0.051777
Batch: 2903/4218: 0.093068 0.098318
Batch: 2904/4218: 0.083033 0.087133
Batch: 2905/4218: 0.013080 0.019251
Batch: 2906/4218: 0.039467 0.045303
Batch: 2907/4218: 0.013905 0.021686
Batch: 2908/4218: 0.043840 0.052244
Batch: 2909/4218: 0.040879 0.047609
Batch: 2910/4218: 0.027284 0.036307
Batch: 2911/4218: 0.023787 0.031283
Batch: 2912/4218: 0.028122 0.033890
Batch: 2913/4218: 0.022859 0.028743
Batch: 2914/4218: 0.043299 0.054758
Batch: 2915/4218: 0.035658 0.040540
Batch: 2916/4218: 0.025528 0.032037
Batch: 2917/4218: 0.029280 0.034778
Batch: 2918/4218: 0.015293 0.020846
Batch: 2919/4218: 0.053405 0.057610
Batch: 2920/4218: 0.021660 0.029892
Batch: 2921/4218: 0.012906 0.017763
Batch: 2922/4218: 0.009505 0.017060
Batch: 2923/4218: 0.011833 0.018800
Batch: 2924/4218: 0.027150 0.031748
Batch: 2925/4218: 0.024046 0.033546
Batch: 2926/4218: 0.030372 0.034169
Batch: 2927/4218: 0.069854 0.073752
Batch: 2928/4218: 0.029243 0.034608
Batch: 2929/4218: 0.071044 0.076030
Batch: 2930/4218: 0.009931 0.014122
Batch: 2931/4218: 0.014076 0.018290
Batch: 2932/4218: 0.079301 0.083442
Batch: 2933/4218: 0.017781 0.022052
Batch: 2934/4218: 0.053533 0.059874
Batch: 2935/4218: 0.017470 0.021506
Batch: 2936/4218: 0.072406 0.076362
Batch: 2937/4218: 0.023167 0.028583
Batch: 2938/4218: 0.045280 0.049356
Batch: 2939/4218: 0.008063 0.012323
Batch: 2940/4218: 0.006838 0.010505
Batch: 2941/4218: 0.017424 0.026202
Batch: 2942/4218: 0.026676 0.031331
Batch: 2943/4218: 0.037924 0.042073
Batch: 2944/4218: 0.055792 0.059997
Batch: 2945/4218: 0.031158 0.035602
Batch: 2946/4218: 0.073048 0.077433
Batch: 2947/4218: 0.026222 0.037279
Batch: 2948/4218: 0.051070 0.055358
Batch: 2949/4218: 0.035365 0.040359
Batch: 2950/4218: 0.068762 0.073020
Batch: 2951/4218: 0.008874 0.013834
Batch: 2952/4218: 0.035079 0.038800
Batch: 2953/4218: 0.026446 0.030719
Batch: 2954/4218: 0.018281 0.022211
Batch: 2955/4218: 0.014253 0.018293
Batch: 2956/4218: 0.048503 0.052160
Batch: 2957/4218: 0.015713 0.020064
Batch: 2958/4218: 0.023747 0.027619
Batch: 2959/4218: 0.010905 0.015995
Batch: 2960/4218: 0.025858 0.030595
Batch: 2961/4218: 0.017319 0.021370
Batch: 2962/4218: 0.067868 0.073146
Batch: 2963/4218: 0.098030 0.101786
Batch: 2964/4218: 0.053725 0.057969
Batch: 2965/4218: 0.021643 0.026971
Batch: 2966/4218: 0.027413 0.031251
Batch: 2967/4218: 0.007993 0.011942
Batch: 2968/4218: 0.036839 0.040544
Batch: 2969/4218: 0.040875 0.044775
Batch: 2970/4218: 0.040883 0.044644
Batch: 2971/4218: 0.017115 0.021189
Batch: 2972/4218: 0.028346 0.032315
Batch: 2973/4218: 0.011449 0.017762
Batch: 2974/4218: 0.018456 0.022021
Batch: 2975/4218: 0.022873 0.027415
Batch: 2976/4218: 0.038168 0.042926
Batch: 2977/4218: 0.016798 0.021328
Batch: 2978/4218: 0.014829 0.018727
Batch: 2979/4218: 0.016352 0.020459
Batch: 2980/4218: 0.005374 0.008893
Batch: 2981/4218: 0.027561 0.030931
Batch: 2982/4218: 0.020340 0.024499
Batch: 2983/4218: 0.023928 0.027362
Batch: 2984/4218: 0.091474 0.095299
Batch: 2985/4218: 0.016986 0.020733
Batch: 2986/4218: 0.032737 0.036297
Batch: 2987/4218: 0.014135 0.018039
Batch: 2988/4218: 0.019777 0.024086
Batch: 2989/4218: 0.021006 0.024761
Batch: 2990/4218: 0.028969 0.032464
Batch: 2991/4218: 0.027303 0.030799
Batch: 2992/4218: 0.032438 0.036102
Batch: 2993/4218: 0.019164 0.022517
Batch: 2994/4218: 0.083188 0.086414
Batch: 2995/4218: 0.098408 0.101963
Batch: 2996/4218: 0.060435 0.064328
Batch: 2997/4218: 0.021080 0.024948
Batch: 2998/4218: 0.018439 0.024508
Batch: 2999/4218: 0.032818 0.036667
Batch: 3000/4218: 0.022289 0.026101
Batch: 3001/4218: 0.037252 0.042285
Batch: 3002/4218: 0.040915 0.044694
Batch: 3003/4218: 0.020314 0.024605
Batch: 3004/4218: 0.044631 0.048445
Batch: 3005/4218: 0.021706 0.025281
Batch: 3006/4218: 0.010219 0.013545
Batch: 3007/4218: 0.016641 0.020149
Batch: 3008/4218: 0.025344 0.028898
Batch: 3009/4218: 0.015407 0.018753
Batch: 3010/4218: 0.033741 0.037024
Batch: 3011/4218: 0.039858 0.043270
Batch: 3012/4218: 0.018232 0.021790
Batch: 3013/4218: 0.074698 0.078037
Batch: 3014/4218: 0.062204 0.065886
Batch: 3015/4218: 0.029677 0.033309
Batch: 3016/4218: 0.045282 0.048610
Batch: 3017/4218: 0.049084 0.052825
Batch: 3018/4218: 0.065867 0.069397
Batch: 3019/4218: 0.015028 0.020164
Batch: 3020/4218: 0.030016 0.033450
Batch: 3021/4218: 0.038065 0.042782
Batch: 3022/4218: 0.053748 0.056941
Batch: 3023/4218: 0.043205 0.046332
Batch: 3024/4218: 0.036750 0.040438
Batch: 3025/4218: 0.017069 0.021034
Batch: 3026/4218: 0.037099 0.040693
Batch: 3027/4218: 0.039524 0.042757
Batch: 3028/4218: 0.056304 0.059405
Batch: 3029/4218: 0.015201 0.018468
Batch: 3030/4218: 0.033045 0.036500
Batch: 3031/4218: 0.056405 0.059748
Batch: 3032/4218: 0.010998 0.014230
Batch: 3033/4218: 0.013760 0.016962
Batch: 3034/4218: 0.027247 0.030433
Batch: 3035/4218: 0.041802 0.048303
Batch: 3036/4218: 0.094298 0.097867
Batch: 3037/4218: 0.024016 0.030635
Batch: 3038/4218: 0.010398 0.013528
Batch: 3039/4218: 0.030226 0.033500
Batch: 3040/4218: 0.033055 0.036093
Batch: 3041/4218: 0.089627 0.092637
Batch: 3042/4218: 0.011698 0.015048
Batch: 3043/4218: 0.014488 0.017997
Batch: 3044/4218: 0.024673 0.028600
Batch: 3045/4218: 0.031859 0.039474
Batch: 3046/4218: 0.013865 0.017984
Batch: 3047/4218: 0.039437 0.042571
Batch: 3048/4218: 0.048808 0.051873
Batch: 3049/4218: 0.024374 0.028178
Batch: 3050/4218: 0.011597 0.014532
Batch: 3051/4218: 0.013341 0.016620
Batch: 3052/4218: 0.017546 0.020698
Batch: 3053/4218: 0.024100 0.028583
Batch: 3054/4218: 0.047894 0.050944
Batch: 3055/4218: 0.009353 0.013058
Batch: 3056/4218: 0.043671 0.046993
Batch: 3057/4218: 0.004234 0.007412
Batch: 3058/4218: 0.028160 0.032290
Batch: 3059/4218: 0.042587 0.046332
Batch: 3060/4218: 0.044133 0.047859
Batch: 3061/4218: 0.051195 0.054456
Batch: 3062/4218: 0.011363 0.014824
Batch: 3063/4218: 0.015009 0.018084
Batch: 3064/4218: 0.066981 0.070267
Batch: 3065/4218: 0.024795 0.027997
Batch: 3066/4218: 0.090084 0.097445
Batch: 3067/4218: 0.043094 0.046006
Batch: 3068/4218: 0.019521 0.022407
Batch: 3069/4218: 0.018351 0.022288
Batch: 3070/4218: 0.029753 0.033885
Batch: 3071/4218: 0.070055 0.072985
Batch: 3072/4218: 0.033948 0.036928
Batch: 3073/4218: 0.032465 0.035276
Batch: 3074/4218: 0.036699 0.039770
Batch: 3075/4218: 0.012470 0.015436
Batch: 3076/4218: 0.012121 0.015210
Batch: 3077/4218: 0.006452 0.010075
Batch: 3078/4218: 0.008888 0.013516
Batch: 3079/4218: 0.041073 0.044558
Batch: 3080/4218: 0.108228 0.110996
Batch: 3081/4218: 0.024172 0.027066
Batch: 3082/4218: 0.021241 0.024259
Batch: 3083/4218: 0.009488 0.012754
Batch: 3084/4218: 0.013612 0.016599
Batch: 3085/4218: 0.055389 0.059055
Batch: 3086/4218: 0.032547 0.036947
Batch: 3087/4218: 0.025186 0.028071
Batch: 3088/4218: 0.009454 0.012353
Batch: 3089/4218: 0.011399 0.015029
Batch: 3090/4218: 0.040236 0.043332
Batch: 3091/4218: 0.017267 0.020941
Batch: 3092/4218: 0.022772 0.025997
Batch: 3093/4218: 0.024887 0.027858
Batch: 3094/4218: 0.019810 0.023006
Batch: 3095/4218: 0.145423 0.151261
Batch: 3096/4218: 0.038143 0.042100
Batch: 3097/4218: 0.029788 0.034215
Batch: 3098/4218: 0.033669 0.037406
Batch: 3099/4218: 0.024170 0.027578
Batch: 3100/4218: 0.030387 0.033151
Batch: 3101/4218: 0.034377 0.037294
Batch: 3102/4218: 0.016689 0.019900
Batch: 3103/4218: 0.010512 0.014081
Batch: 3104/4218: 0.082761 0.086098
Batch: 3105/4218: 0.027174 0.029983
Batch: 3106/4218: 0.028243 0.031156
Batch: 3107/4218: 0.047681 0.050579
Batch: 3108/4218: 0.010313 0.013507
Batch: 3109/4218: 0.025572 0.030826
Batch: 3110/4218: 0.070792 0.073715
Batch: 3111/4218: 0.013980 0.016761
Batch: 3112/4218: 0.017991 0.020874
Batch: 3113/4218: 0.051290 0.054673
Batch: 3114/4218: 0.018745 0.021553
Batch: 3115/4218: 0.034452 0.037916
Batch: 3116/4218: 0.144590 0.148208
Batch: 3117/4218: 0.039401 0.042265
Batch: 3118/4218: 0.005773 0.008442
Batch: 3119/4218: 0.034484 0.038196
Batch: 3120/4218: 0.026242 0.029391
Batch: 3121/4218: 0.013226 0.015945
Batch: 3122/4218: 0.030001 0.032848
Batch: 3123/4218: 0.038942 0.041998
Batch: 3124/4218: 0.009621 0.012221
Batch: 3125/4218: 0.021573 0.024529
Batch: 3126/4218: 0.030213 0.032956
Batch: 3127/4218: 0.055680 0.059561
Batch: 3128/4218: 0.008495 0.011074
Batch: 3129/4218: 0.022045 0.025070
Batch: 3130/4218: 0.022698 0.025450
Batch: 3131/4218: 0.050450 0.053500
Batch: 3132/4218: 0.042834 0.046050
Batch: 3133/4218: 0.050051 0.052734
Batch: 3134/4218: 0.103909 0.108544
Batch: 3135/4218: 0.018438 0.021432
Batch: 3136/4218: 0.069606 0.072203
Batch: 3137/4218: 0.059895 0.063067
Batch: 3138/4218: 0.023440 0.027362
Batch: 3139/4218: 0.014976 0.024347
Batch: 3140/4218: 0.026990 0.032473
Batch: 3141/4218: 0.099542 0.102933
Batch: 3142/4218: 0.017301 0.020155
Batch: 3143/4218: 0.104776 0.107594
Batch: 3144/4218: 0.053994 0.057441
Batch: 3145/4218: 0.037597 0.040415
Batch: 3146/4218: 0.058042 0.061173
Batch: 3147/4218: 0.027065 0.030564
Batch: 3148/4218: 0.063191 0.066122
Batch: 3149/4218: 0.022776 0.025651
Batch: 3150/4218: 0.078428 0.081536
Batch: 3151/4218: 0.015939 0.018891
Batch: 3152/4218: 0.023047 0.026095
Batch: 3153/4218: 0.029557 0.032757
Batch: 3154/4218: 0.071373 0.074051
Batch: 3155/4218: 0.025580 0.028938
Batch: 3156/4218: 0.052873 0.055971
Batch: 3157/4218: 0.019753 0.023878
Batch: 3158/4218: 0.065056 0.067871
Batch: 3159/4218: 0.033378 0.036250
Batch: 3160/4218: 0.015637 0.018296
Batch: 3161/4218: 0.031427 0.037045
Batch: 3162/4218: 0.057509 0.060272
Batch: 3163/4218: 0.041466 0.044666
Batch: 3164/4218: 0.026020 0.028493
Batch: 3165/4218: 0.011213 0.013912
Batch: 3166/4218: 0.030994 0.033886
Batch: 3167/4218: 0.056857 0.059670
Batch: 3168/4218: 0.010614 0.016176
Batch: 3169/4218: 0.014691 0.021691
Batch: 3170/4218: 0.062971 0.065761
Batch: 3171/4218: 0.104738 0.107892
Batch: 3172/4218: 0.037637 0.041017
Batch: 3173/4218: 0.032104 0.036219
Batch: 3174/4218: 0.052834 0.055421
Batch: 3175/4218: 0.023267 0.027089
Batch: 3176/4218: 0.021516 0.024389
Batch: 3177/4218: 0.081197 0.084002
Batch: 3178/4218: 0.064181 0.068260
Batch: 3179/4218: 0.014943 0.018833
Batch: 3180/4218: 0.022222 0.025345
Batch: 3181/4218: 0.026226 0.029103
Batch: 3182/4218: 0.043539 0.046237
Batch: 3183/4218: 0.029813 0.033144
Batch: 3184/4218: 0.067452 0.070799
Batch: 3185/4218: 0.056241 0.059124
Batch: 3186/4218: 0.023133 0.026218
Batch: 3187/4218: 0.036009 0.039897
Batch: 3188/4218: 0.022248 0.025811
Batch: 3189/4218: 0.017547 0.021967
Batch: 3190/4218: 0.021173 0.027268
Batch: 3191/4218: 0.055965 0.059579
Batch: 3192/4218: 0.069356 0.072180
Batch: 3193/4218: 0.013916 0.016327
Batch: 3194/4218: 0.054263 0.057481
Batch: 3195/4218: 0.023371 0.026316
Batch: 3196/4218: 0.021080 0.024491
Batch: 3197/4218: 0.020505 0.023453
Batch: 3198/4218: 0.043074 0.045722
Batch: 3199/4218: 0.011865 0.014421
Batch: 3200/4218: 0.025722 0.028649
Batch: 3201/4218: 0.043538 0.046266
Batch: 3202/4218: 0.015169 0.019221
Batch: 3203/4218: 0.033692 0.036807
Batch: 3204/4218: 0.080997 0.083634
Batch: 3205/4218: 0.100286 0.102833
Batch: 3206/4218: 0.046474 0.051078
Batch: 3207/4218: 0.024917 0.027427
Batch: 3208/4218: 0.051691 0.054979
Batch: 3209/4218: 0.080735 0.083639
Batch: 3210/4218: 0.030361 0.033165
Batch: 3211/4218: 0.039812 0.042430
Batch: 3212/4218: 0.129173 0.131692
Batch: 3213/4218: 0.030499 0.033039
Batch: 3214/4218: 0.084203 0.087137
Batch: 3215/4218: 0.053800 0.056388
Batch: 3216/4218: 0.010521 0.015087
Batch: 3217/4218: 0.020882 0.023580
Batch: 3218/4218: 0.017859 0.020604
Batch: 3219/4218: 0.032035 0.034800
Batch: 3220/4218: 0.030676 0.033615
Batch: 3221/4218: 0.020511 0.023024
Batch: 3222/4218: 0.022156 0.024794
Batch: 3223/4218: 0.016640 0.019679
Batch: 3224/4218: 0.038899 0.041901
Batch: 3225/4218: 0.122020 0.127189
Batch: 3226/4218: 0.027874 0.031669
Batch: 3227/4218: 0.027893 0.030191
Batch: 3228/4218: 0.014578 0.019229
Batch: 3229/4218: 0.113696 0.118696
Batch: 3230/4218: 0.022824 0.025581
Batch: 3231/4218: 0.033307 0.035824
Batch: 3232/4218: 0.134897 0.142414
Batch: 3233/4218: 0.019350 0.022805
Batch: 3234/4218: 0.007706 0.010218
Batch: 3235/4218: 0.010400 0.014243
Batch: 3236/4218: 0.094308 0.096802
Batch: 3237/4218: 0.009302 0.012195
Batch: 3238/4218: 0.012445 0.014932
Batch: 3239/4218: 0.024551 0.027343
Batch: 3240/4218: 0.032415 0.036680
Batch: 3241/4218: 0.018471 0.021408
Batch: 3242/4218: 0.060802 0.064051
Batch: 3243/4218: 0.020230 0.023868
Batch: 3244/4218: 0.034426 0.037256
Batch: 3245/4218: 0.056300 0.059140
Batch: 3246/4218: 0.097227 0.099911
Batch: 3247/4218: 0.018807 0.021400
Batch: 3248/4218: 0.037241 0.040367
Batch: 3249/4218: 0.023693 0.026163
Batch: 3250/4218: 0.056128 0.058587
Batch: 3251/4218: 0.024963 0.028160
Batch: 3252/4218: 0.009797 0.012773
Batch: 3253/4218: 0.009319 0.014096
Batch: 3254/4218: 0.008799 0.011933
Batch: 3255/4218: 0.050518 0.053170
Batch: 3256/4218: 0.025909 0.028858
Batch: 3257/4218: 0.032734 0.035493
Batch: 3258/4218: 0.069827 0.072969
Batch: 3259/4218: 0.017518 0.021361
Batch: 3260/4218: 0.020115 0.022467
Batch: 3261/4218: 0.015395 0.018276
Batch: 3262/4218: 0.068183 0.072860
Batch: 3263/4218: 0.028171 0.031977
Batch: 3264/4218: 0.034806 0.038003
Batch: 3265/4218: 0.005872 0.008371
Batch: 3266/4218: 0.009717 0.012254
Batch: 3267/4218: 0.016043 0.018533
Batch: 3268/4218: 0.118201 0.121271
Batch: 3269/4218: 0.023620 0.026999
Batch: 3270/4218: 0.079826 0.082600
Batch: 3271/4218: 0.010385 0.013976
Batch: 3272/4218: 0.015877 0.018302
Batch: 3273/4218: 0.091317 0.095242
Batch: 3274/4218: 0.077321 0.079638
Batch: 3275/4218: 0.027499 0.030048
Batch: 3276/4218: 0.020866 0.023992
Batch: 3277/4218: 0.052150 0.054647
Batch: 3278/4218: 0.011042 0.014543
Batch: 3279/4218: 0.075994 0.078488
Batch: 3280/4218: 0.027641 0.030637
Batch: 3281/4218: 0.024313 0.029279
Batch: 3282/4218: 0.014964 0.017558
Batch: 3283/4218: 0.044008 0.046815
Batch: 3284/4218: 0.036945 0.039193
Batch: 3285/4218: 0.033345 0.035807
Batch: 3286/4218: 0.059868 0.062763
Batch: 3287/4218: 0.054798 0.057018
Batch: 3288/4218: 0.032373 0.036703
Batch: 3289/4218: 0.007909 0.010642
Batch: 3290/4218: 0.010068 0.012888
Batch: 3291/4218: 0.068016 0.071512
Batch: 3292/4218: 0.059450 0.062176
Batch: 3293/4218: 0.023708 0.026046
Batch: 3294/4218: 0.025422 0.027737
Batch: 3295/4218: 0.041089 0.043271
Batch: 3296/4218: 0.024881 0.027400
Batch: 3297/4218: 0.030898 0.034735
Batch: 3298/4218: 0.013453 0.016086
Batch: 3299/4218: 0.037452 0.040206
Batch: 3300/4218: 0.013756 0.019448
Batch: 3301/4218: 0.007190 0.010447
Batch: 3302/4218: 0.022920 0.027591
Batch: 3303/4218: 0.028514 0.032593
Batch: 3304/4218: 0.010643 0.013939
Batch: 3305/4218: 0.037957 0.040468
Batch: 3306/4218: 0.033182 0.035568
Batch: 3307/4218: 0.007754 0.010156
Batch: 3308/4218: 0.004845 0.008320
Batch: 3309/4218: 0.089662 0.092057
Batch: 3310/4218: 0.014947 0.017335
Batch: 3311/4218: 0.011963 0.014257
Batch: 3312/4218: 0.006538 0.008902
Batch: 3313/4218: 0.004372 0.007334
Batch: 3314/4218: 0.018611 0.020949
Batch: 3315/4218: 0.013537 0.015733
Batch: 3316/4218: 0.061037 0.066030
Batch: 3317/4218: 0.014882 0.018553
Batch: 3318/4218: 0.044636 0.046857
Batch: 3319/4218: 0.010515 0.013144
Batch: 3320/4218: 0.011811 0.014727
Batch: 3321/4218: 0.025276 0.029587
Batch: 3322/4218: 0.012366 0.014546
Batch: 3323/4218: 0.012198 0.014777
Batch: 3324/4218: 0.043119 0.049582
Batch: 3325/4218: 0.120476 0.123126
Batch: 3326/4218: 0.155675 0.157984
Batch: 3327/4218: 0.026081 0.028754
Batch: 3328/4218: 0.057614 0.060039
Batch: 3329/4218: 0.038409 0.040783
Batch: 3330/4218: 0.023548 0.026049
Batch: 3331/4218: 0.023111 0.025753
Batch: 3332/4218: 0.014767 0.020443
Batch: 3333/4218: 0.017258 0.019450
Batch: 3334/4218: 0.064755 0.067472
Batch: 3335/4218: 0.014808 0.017074
Batch: 3336/4218: 0.057363 0.059870
Batch: 3337/4218: 0.027656 0.029863
Batch: 3338/4218: 0.017031 0.019474
Batch: 3339/4218: 0.014056 0.016271
Batch: 3340/4218: 0.021432 0.023608
Batch: 3341/4218: 0.019527 0.022196
Batch: 3342/4218: 0.053322 0.057334
Batch: 3343/4218: 0.030464 0.033456
Batch: 3344/4218: 0.114916 0.118349
Batch: 3345/4218: 0.019789 0.022006
Batch: 3346/4218: 0.086513 0.089872
Batch: 3347/4218: 0.018422 0.020597
Batch: 3348/4218: 0.019319 0.021588
Batch: 3349/4218: 0.024191 0.026503
Batch: 3350/4218: 0.009064 0.011236
Batch: 3351/4218: 0.010067 0.012371
Batch: 3352/4218: 0.007526 0.010614
Batch: 3353/4218: 0.049942 0.053622
Batch: 3354/4218: 0.053310 0.056131
Batch: 3355/4218: 0.005959 0.009176
Batch: 3356/4218: 0.025994 0.028446
Batch: 3357/4218: 0.052709 0.055105
Batch: 3358/4218: 0.009945 0.014277
Batch: 3359/4218: 0.031636 0.033955
Batch: 3360/4218: 0.030280 0.032999
Batch: 3361/4218: 0.030533 0.032734
Batch: 3362/4218: 0.109965 0.112141
Batch: 3363/4218: 0.050501 0.053240
Batch: 3364/4218: 0.028602 0.033220
Batch: 3365/4218: 0.078606 0.080764
Batch: 3366/4218: 0.047982 0.050094
Batch: 3367/4218: 0.033808 0.036168
Batch: 3368/4218: 0.029465 0.031646
Batch: 3369/4218: 0.019135 0.021960
Batch: 3370/4218: 0.029262 0.031516
Batch: 3371/4218: 0.014744 0.017436
Batch: 3372/4218: 0.052410 0.055031
Batch: 3373/4218: 0.011768 0.013884
Batch: 3374/4218: 0.027200 0.029484
Batch: 3375/4218: 0.095464 0.097675
Batch: 3376/4218: 0.014452 0.019531
Batch: 3377/4218: 0.015331 0.019292
Batch: 3378/4218: 0.043404 0.045801
Batch: 3379/4218: 0.024128 0.028612
Batch: 3380/4218: 0.025833 0.030673
Batch: 3381/4218: 0.052968 0.055122
Batch: 3382/4218: 0.017564 0.020019
Batch: 3383/4218: 0.013523 0.015826
Batch: 3384/4218: 0.036398 0.040027
Batch: 3385/4218: 0.019483 0.021794
Batch: 3386/4218: 0.051388 0.053867
Batch: 3387/4218: 0.042540 0.044945
Batch: 3388/4218: 0.138959 0.141611
Batch: 3389/4218: 0.026845 0.029520
Batch: 3390/4218: 0.045993 0.048389
Batch: 3391/4218: 0.007720 0.009836
Batch: 3392/4218: 0.056375 0.058705
Batch: 3393/4218: 0.016691 0.019143
Batch: 3394/4218: 0.012587 0.014868
Batch: 3395/4218: 0.018880 0.021003
Batch: 3396/4218: 0.070167 0.072745
Batch: 3397/4218: 0.055326 0.057642
Batch: 3398/4218: 0.028934 0.030960
Batch: 3399/4218: 0.113680 0.117140
Batch: 3400/4218: 0.012393 0.014873
Batch: 3401/4218: 0.014774 0.017802
Batch: 3402/4218: 0.039985 0.042332
Batch: 3403/4218: 0.021170 0.023192
Batch: 3404/4218: 0.037499 0.039665
Batch: 3405/4218: 0.004139 0.006451
Batch: 3406/4218: 0.012200 0.014386
Batch: 3407/4218: 0.034964 0.037752
Batch: 3408/4218: 0.013659 0.016001
Batch: 3409/4218: 0.010022 0.012181
Batch: 3410/4218: 0.019546 0.021725
Batch: 3411/4218: 0.011121 0.014031
Batch: 3412/4218: 0.032055 0.036173
Batch: 3413/4218: 0.021480 0.024041
Batch: 3414/4218: 0.022854 0.026869
Batch: 3415/4218: 0.011671 0.014326
Batch: 3416/4218: 0.032015 0.034052
Batch: 3417/4218: 0.063222 0.068165
Batch: 3418/4218: 0.045616 0.049060
Batch: 3419/4218: 0.009761 0.012426
Batch: 3420/4218: 0.030230 0.033557
Batch: 3421/4218: 0.023477 0.031869
Batch: 3422/4218: 0.015716 0.017939
Batch: 3423/4218: 0.044675 0.047708
Batch: 3424/4218: 0.019557 0.021615
Batch: 3425/4218: 0.044260 0.066343
Batch: 3426/4218: 0.027549 0.030250
Batch: 3427/4218: 0.033675 0.036949
Batch: 3428/4218: 0.041114 0.045064
Batch: 3429/4218: 0.018381 0.024356
Batch: 3430/4218: 0.027283 0.029402
Batch: 3431/4218: 0.044944 0.047385
Batch: 3432/4218: 0.018167 0.020325
Batch: 3433/4218: 0.025608 0.032388
Batch: 3434/4218: 0.048939 0.053356
Batch: 3435/4218: 0.022780 0.027200
Batch: 3436/4218: 0.053283 0.056440
Batch: 3437/4218: 0.015944 0.021927
Batch: 3438/4218: 0.047612 0.050659
Batch: 3439/4218: 0.011584 0.030609
Batch: 3440/4218: 0.052125 0.054581
Batch: 3441/4218: 0.029241 0.031606
Batch: 3442/4218: 0.031034 0.033457
Batch: 3443/4218: 0.053940 0.057227
Batch: 3444/4218: 0.011029 0.024649
Batch: 3445/4218: 0.005321 0.024862
Batch: 3446/4218: 0.028782 0.032031
Batch: 3447/4218: 0.048625 0.055431
Batch: 3448/4218: 0.017364 0.043035
Batch: 3449/4218: 0.031758 0.034312
Batch: 3450/4218: 0.045930 0.048176
Batch: 3451/4218: 0.023922 0.027531
Batch: 3452/4218: 0.018845 0.021104
Batch: 3453/4218: 0.087216 0.090099
Batch: 3454/4218: 0.050922 0.054619
Batch: 3455/4218: 0.019352 0.022837
Batch: 3456/4218: 0.038992 0.042884
Batch: 3457/4218: 0.025346 0.027659
Batch: 3458/4218: 0.023866 0.028382
Batch: 3459/4218: 0.037531 0.042003
Batch: 3460/4218: 0.020283 0.026483
Batch: 3461/4218: 0.017242 0.020400
Batch: 3462/4218: 0.024565 0.027264
Batch: 3463/4218: 0.021499 0.024114
Batch: 3464/4218: 0.093902 0.098372
Batch: 3465/4218: 0.037392 0.062831
Batch: 3466/4218: 0.035714 0.038267
Batch: 3467/4218: 0.074499 0.087506
Batch: 3468/4218: 0.022123 0.024671
Batch: 3469/4218: 0.014500 0.018227
Batch: 3470/4218: 0.010213 0.013150
Batch: 3471/4218: 0.095921 0.098638
Batch: 3472/4218: 0.029365 0.033385
Batch: 3473/4218: 0.046330 0.051671
Batch: 3474/4218: 0.018770 0.023118
Batch: 3475/4218: 0.010733 0.013417
Batch: 3476/4218: 0.014641 0.017711
Batch: 3477/4218: 0.008278 0.012434
Batch: 3478/4218: 0.009379 0.013443
Batch: 3479/4218: 0.025091 0.033317
Batch: 3480/4218: 0.013051 0.017198
Batch: 3481/4218: 0.031388 0.035627
Batch: 3482/4218: 0.032092 0.036496
Batch: 3483/4218: 0.102908 0.107018
Batch: 3484/4218: 0.018496 0.023562
Batch: 3485/4218: 0.004494 0.007212
Batch: 3486/4218: 0.033714 0.036944
Batch: 3487/4218: 0.013144 0.019313
Batch: 3488/4218: 0.051920 0.055188
Batch: 3489/4218: 0.051211 0.055629
Batch: 3490/4218: 0.030361 0.035147
Batch: 3491/4218: 0.055831 0.075232
Batch: 3492/4218: 0.020446 0.022980
Batch: 3493/4218: 0.029998 0.035194
Batch: 3494/4218: 0.019611 0.022692
Batch: 3495/4218: 0.024097 0.026656
Batch: 3496/4218: 0.041053 0.044225
Batch: 3497/4218: 0.033905 0.037095
Batch: 3498/4218: 0.012709 0.015222
Batch: 3499/4218: 0.022984 0.030700
Batch: 3500/4218: 0.028307 0.031066
Batch: 3501/4218: 0.034042 0.038012
Batch: 3502/4218: 0.011960 0.015074
Batch: 3503/4218: 0.040268 0.046371
Batch: 3504/4218: 0.028468 0.031456
Batch: 3505/4218: 0.023683 0.026260
Batch: 3506/4218: 0.014786 0.018166
Batch: 3507/4218: 0.040877 0.043822
Batch: 3508/4218: 0.017446 0.020731
Batch: 3509/4218: 0.027660 0.030347
Batch: 3510/4218: 0.086419 0.089181
Batch: 3511/4218: 0.092496 0.095169
Batch: 3512/4218: 0.033437 0.038677
Batch: 3513/4218: 0.012611 0.020016
Batch: 3514/4218: 0.019915 0.022810
Batch: 3515/4218: 0.019445 0.025240
Batch: 3516/4218: 0.024273 0.027205
Batch: 3517/4218: 0.068671 0.071347
Batch: 3518/4218: 0.024983 0.027708
Batch: 3519/4218: 0.015853 0.018829
Batch: 3520/4218: 0.019136 0.021805
Batch: 3521/4218: 0.009994 0.012649
Batch: 3522/4218: 0.023175 0.025741
Batch: 3523/4218: 0.085695 0.094028
Batch: 3524/4218: 0.022931 0.031466
Batch: 3525/4218: 0.023818 0.027278
Batch: 3526/4218: 0.018457 0.021008
Batch: 3527/4218: 0.030316 0.033933
Batch: 3528/4218: 0.038078 0.041020
Batch: 3529/4218: 0.006276 0.009959
Batch: 3530/4218: 0.017812 0.020838
Batch: 3531/4218: 0.004969 0.009708
Batch: 3532/4218: 0.077179 0.080073
Batch: 3533/4218: 0.048264 0.051350
Batch: 3534/4218: 0.029427 0.032601
Batch: 3535/4218: 0.012133 0.017026
Batch: 3536/4218: 0.032490 0.035321
Batch: 3537/4218: 0.095815 0.098436
Batch: 3538/4218: 0.029694 0.032278
Batch: 3539/4218: 0.018172 0.021041
Batch: 3540/4218: 0.017361 0.020257
Batch: 3541/4218: 0.015002 0.017781
Batch: 3542/4218: 0.057500 0.061051
Batch: 3543/4218: 0.105424 0.110426
Batch: 3544/4218: 0.108378 0.110786
Batch: 3545/4218: 0.057109 0.060034
Batch: 3546/4218: 0.045748 0.048485
Batch: 3547/4218: 0.046929 0.049556
Batch: 3548/4218: 0.038393 0.041362
Batch: 3549/4218: 0.028221 0.040939
Batch: 3550/4218: 0.020128 0.023121
Batch: 3551/4218: 0.022386 0.160848
Batch: 3552/4218: 0.017099 0.020280
Batch: 3553/4218: 0.022690 0.025443
Batch: 3554/4218: 0.028418 0.033699
Batch: 3555/4218: 0.007962 0.011398
Batch: 3556/4218: 0.085962 0.089055
Batch: 3557/4218: 0.019130 0.069295
Batch: 3558/4218: 0.037104 0.041307
Batch: 3559/4218: 0.031221 0.277971
Batch: 3560/4218: 0.027454 0.778131
Batch: 3561/4218: 0.013033 0.016157
Batch: 3562/4218: 0.048669 0.053986
Batch: 3563/4218: 0.077393 0.278094
Batch: 3564/4218: 0.023775 0.030299
Batch: 3565/4218: 0.045313 0.051783
Batch: 3566/4218: 0.028072 0.033661
Batch: 3567/4218: 0.012089 0.016485
Batch: 3568/4218: 0.235207 0.243754
Batch: 3569/4218: 0.011348 0.016228
Batch: 3570/4218: 0.033412 0.594966
Batch: 3571/4218: 0.008433 0.013739
Batch: 3572/4218: 0.022169 0.342873
Batch: 3573/4218: 0.048754 0.548939
Batch: 3574/4218: 0.034030 0.044072
Batch: 3575/4218: 0.016268 0.023292
Batch: 3576/4218: 0.013166 0.020175
Batch: 3577/4218: 0.054017 0.153324
Batch: 3578/4218: 0.009304 0.023174
Batch: 3579/4218: 0.018934 0.056692
Batch: 3580/4218: 0.071972 0.079666
Batch: 3581/4218: 0.047551 0.061155
Batch: 3582/4218: 0.009113 0.019269
Batch: 3583/4218: 0.005720 0.015011
Batch: 3584/4218: 0.019232 0.027950
Batch: 3585/4218: 0.033112 0.048737
Batch: 3586/4218: 0.019486 0.147608
Batch: 3587/4218: 0.039722 0.054423
Batch: 3588/4218: 0.050890 0.081594
Batch: 3589/4218: 0.053288 0.077115
Batch: 3590/4218: 0.214417 0.255706
Batch: 3591/4218: 0.027658 0.036168
Batch: 3592/4218: 0.023447 0.031882
Batch: 3593/4218: 0.053734 0.065879
Batch: 3594/4218: 0.040052 0.049057
Batch: 3595/4218: 0.009728 0.018925
Batch: 3596/4218: 0.078547 0.088093
Batch: 3597/4218: 0.037833 0.047474
Batch: 3598/4218: 0.031490 0.040719
Batch: 3599/4218: 0.021298 0.034650
Batch: 3600/4218: 0.020354 0.029766
Batch: 3601/4218: 0.024348 0.033397
Batch: 3602/4218: 0.039222 0.049707
Batch: 3603/4218: 0.012630 0.023333
Batch: 3604/4218: 0.041822 0.053294
Batch: 3605/4218: 0.023139 0.036835
Batch: 3606/4218: 0.018423 0.482294
Batch: 3607/4218: 0.019901 0.029967
Batch: 3608/4218: 0.011644 0.020748
Batch: 3609/4218: 0.015406 0.024801
Batch: 3610/4218: 0.010604 0.020061
Batch: 3611/4218: 0.028622 0.038432
Batch: 3612/4218: 0.015069 0.187507
Batch: 3613/4218: 0.070407 0.080583
Batch: 3614/4218: 0.073860 0.083348
Batch: 3615/4218: 0.010479 0.020052
Batch: 3616/4218: 0.029979 0.039421
Batch: 3617/4218: 0.017724 0.027145
Batch: 3618/4218: 0.026589 0.036186
Batch: 3619/4218: 0.020120 0.056634
Batch: 3620/4218: 0.054413 0.063842
Batch: 3621/4218: 0.027489 0.037119
Batch: 3622/4218: 0.028700 0.038541
Batch: 3623/4218: 0.020846 0.030987
Batch: 3624/4218: 0.013819 0.023797
Batch: 3625/4218: 0.040177 0.049967
Batch: 3626/4218: 0.012499 0.022076
Batch: 3627/4218: 0.092979 0.102250
Batch: 3628/4218: 0.025482 0.035015
Batch: 3629/4218: 0.050733 0.061229
Batch: 3630/4218: 0.011444 0.020425
Batch: 3631/4218: 0.058214 0.067929
Batch: 3632/4218: 0.080185 0.090363
Batch: 3633/4218: 0.020617 0.030630
Batch: 3634/4218: 0.050995 0.060249
Batch: 3635/4218: 0.029315 0.037990
Batch: 3636/4218: 0.093405 0.102007
Batch: 3637/4218: 0.081645 0.090578
Batch: 3638/4218: 0.090203 0.102741
Batch: 3639/4218: 0.010680 0.020571
Batch: 3640/4218: 0.020371 0.028982
Batch: 3641/4218: 0.017220 0.025454
Batch: 3642/4218: 0.011704 0.024257
Batch: 3643/4218: 0.014006 0.022740
Batch: 3644/4218: 0.013754 0.021711
Batch: 3645/4218: 0.009189 0.017286
Batch: 3646/4218: 0.014660 0.023216
Batch: 3647/4218: 0.058217 0.068491
Batch: 3648/4218: 0.011463 0.021398
Batch: 3649/4218: 0.006761 0.014282
Batch: 3650/4218: 0.015060 0.023186
Batch: 3651/4218: 0.025914 0.033371
Batch: 3652/4218: 0.021728 0.029346
Batch: 3653/4218: 0.022579 0.029877
Batch: 3654/4218: 0.020358 0.027665
Batch: 3655/4218: 0.042823 0.050188
Batch: 3656/4218: 0.025289 0.032354
Batch: 3657/4218: 0.023109 0.030663
Batch: 3658/4218: 0.026614 0.034040
Batch: 3659/4218: 0.033986 0.041052
Batch: 3660/4218: 0.045337 0.054013
Batch: 3661/4218: 0.016738 0.023744
Batch: 3662/4218: 0.034313 0.044417
Batch: 3663/4218: 0.038856 0.045575
Batch: 3664/4218: 0.026437 0.033109
Batch: 3665/4218: 0.051278 0.059387
Batch: 3666/4218: 0.056038 0.065032
Batch: 3667/4218: 0.051683 0.061907
Batch: 3668/4218: 0.009455 0.015901
Batch: 3669/4218: 0.017894 0.044434
Batch: 3670/4218: 0.029409 0.036012
Batch: 3671/4218: 0.089041 0.097752
Batch: 3672/4218: 0.014623 0.020803
Batch: 3673/4218: 0.017810 0.024101
Batch: 3674/4218: 0.066523 0.083550
Batch: 3675/4218: 0.037091 0.043346
Batch: 3676/4218: 0.029046 0.035899
Batch: 3677/4218: 0.025815 0.032486
Batch: 3678/4218: 0.038818 0.045299
Batch: 3679/4218: 0.050524 0.056641
Batch: 3680/4218: 0.041304 0.047398
Batch: 3681/4218: 0.027199 0.036097
Batch: 3682/4218: 0.013043 0.020256
Batch: 3683/4218: 0.050253 0.057008
Batch: 3684/4218: 0.084742 0.091241
Batch: 3685/4218: 0.032765 0.038773
Batch: 3686/4218: 0.020581 0.027771
Batch: 3687/4218: 0.116337 0.130152
Batch: 3688/4218: 0.088838 0.095114
Batch: 3689/4218: 0.022345 0.028304
Batch: 3690/4218: 0.078824 0.087330
Batch: 3691/4218: 0.038548 0.045423
Batch: 3692/4218: 0.040589 0.047376
Batch: 3693/4218: 0.024262 0.031664
Batch: 3694/4218: 0.058842 0.065274
Batch: 3695/4218: 0.037341 0.042864
Batch: 3696/4218: 0.094297 0.099745
Batch: 3697/4218: 0.020922 0.026593
Batch: 3698/4218: 0.036923 0.047786
Batch: 3699/4218: 0.012094 0.018166
Batch: 3700/4218: 0.038264 0.043895
Batch: 3701/4218: 0.010264 0.015764
Batch: 3702/4218: 0.059450 0.064721
Batch: 3703/4218: 0.025389 0.030620
Batch: 3704/4218: 0.003920 0.009590
Batch: 3705/4218: 0.012285 0.017713
Batch: 3706/4218: 0.013843 0.018933
Batch: 3707/4218: 0.018481 0.023423
Batch: 3708/4218: 0.013893 0.019080
Batch: 3709/4218: 0.013687 0.018810
Batch: 3710/4218: 0.015351 0.020587
Batch: 3711/4218: 0.035274 0.040280
Batch: 3712/4218: 0.034682 0.040448
Batch: 3713/4218: 0.011583 0.016568
Batch: 3714/4218: 0.016185 0.021677
Batch: 3715/4218: 0.002972 0.008988
Batch: 3716/4218: 0.013648 0.018341
Batch: 3717/4218: 0.023556 0.028655
Batch: 3718/4218: 0.012692 0.017488
Batch: 3719/4218: 0.019484 0.024268
Batch: 3720/4218: 0.043422 0.050030
Batch: 3721/4218: 0.019528 0.024148
Batch: 3722/4218: 0.013352 0.018192
Batch: 3723/4218: 0.036816 0.041601
Batch: 3724/4218: 0.029208 0.033859
Batch: 3725/4218: 0.078692 0.083487
Batch: 3726/4218: 0.002878 0.008233
Batch: 3727/4218: 0.032327 0.036856
Batch: 3728/4218: 0.022013 0.030524
Batch: 3729/4218: 0.023307 0.028034
Batch: 3730/4218: 0.027302 0.031918
Batch: 3731/4218: 0.011355 0.018353
Batch: 3732/4218: 0.029405 0.033825
Batch: 3733/4218: 0.045296 0.050320
Batch: 3734/4218: 0.020163 0.024709
Batch: 3735/4218: 0.008919 0.014225
Batch: 3736/4218: 0.035082 0.039522
Batch: 3737/4218: 0.015780 0.020723
Batch: 3738/4218: 0.043352 0.049603
Batch: 3739/4218: 0.007394 0.011633
Batch: 3740/4218: 0.013285 0.017509
Batch: 3741/4218: 0.015538 0.020931
Batch: 3742/4218: 0.013943 0.019341
Batch: 3743/4218: 0.032518 0.036996
Batch: 3744/4218: 0.022280 0.026637
Batch: 3745/4218: 0.006823 0.011409
Batch: 3746/4218: 0.026531 0.030632
Batch: 3747/4218: 0.056627 0.061101
Batch: 3748/4218: 0.013397 0.017962
Batch: 3749/4218: 0.024289 0.028405
Batch: 3750/4218: 0.026622 0.030726
Batch: 3751/4218: 0.076239 0.081009
Batch: 3752/4218: 0.028309 0.032809
Batch: 3753/4218: 0.016067 0.021158
Batch: 3754/4218: 0.013723 0.021038
Batch: 3755/4218: 0.023095 0.028434
Batch: 3756/4218: 0.045302 0.049626
Batch: 3757/4218: 0.032491 0.037757
Batch: 3758/4218: 0.040193 0.046521
Batch: 3759/4218: 0.046132 0.050793
Batch: 3760/4218: 0.033977 0.038172
Batch: 3761/4218: 0.030406 0.034335
Batch: 3762/4218: 0.006280 0.010460
Batch: 3763/4218: 0.020482 0.026317
Batch: 3764/4218: 0.037655 0.041830
Batch: 3765/4218: 0.011290 0.023466
Batch: 3766/4218: 0.017546 0.022228
Batch: 3767/4218: 0.020338 0.024364
Batch: 3768/4218: 0.025833 0.041153
Batch: 3769/4218: 0.030720 0.034551
Batch: 3770/4218: 0.013229 0.017152
Batch: 3771/4218: 0.057168 0.061271
Batch: 3772/4218: 0.031133 0.040506
Batch: 3773/4218: 0.097729 0.101680
Batch: 3774/4218: 0.024184 0.028301
Batch: 3775/4218: 0.020361 0.026263
Batch: 3776/4218: 0.019851 0.023669
Batch: 3777/4218: 0.046702 0.050595
Batch: 3778/4218: 0.021412 0.025467
Batch: 3779/4218: 0.012126 0.015757
Batch: 3780/4218: 0.019176 0.022861
Batch: 3781/4218: 0.019160 0.023347
Batch: 3782/4218: 0.021685 0.025682
Batch: 3783/4218: 0.052066 0.056127
Batch: 3784/4218: 0.005947 0.013046
Batch: 3785/4218: 0.019022 0.023159
Batch: 3786/4218: 0.111810 0.116451
Batch: 3787/4218: 0.065483 0.069132
Batch: 3788/4218: 0.027633 0.038244
Batch: 3789/4218: 0.027294 0.033399
Batch: 3790/4218: 0.058741 0.062231
Batch: 3791/4218: 0.020830 0.025200
Batch: 3792/4218: 0.012290 0.016036
Batch: 3793/4218: 0.041277 0.045123
Batch: 3794/4218: 0.146449 0.150155
Batch: 3795/4218: 0.007151 0.010908
Batch: 3796/4218: 0.016832 0.023535
Batch: 3797/4218: 0.021971 0.027076
Batch: 3798/4218: 0.016432 0.023673
Batch: 3799/4218: 0.006610 0.010270
Batch: 3800/4218: 0.023561 0.027057
Batch: 3801/4218: 0.032022 0.035491
Batch: 3802/4218: 0.075136 0.078570
Batch: 3803/4218: 0.063641 0.067378
Batch: 3804/4218: 0.019849 0.025055
Batch: 3805/4218: 0.015344 0.019013
Batch: 3806/4218: 0.022960 0.026733
Batch: 3807/4218: 0.028596 0.032002
Batch: 3808/4218: 0.033677 0.037384
Batch: 3809/4218: 0.015688 0.019301
Batch: 3810/4218: 0.018357 0.022261
Batch: 3811/4218: 0.016586 0.024238
Batch: 3812/4218: 0.013654 0.017055
Batch: 3813/4218: 0.034154 0.037577
Batch: 3814/4218: 0.007833 0.011982
Batch: 3815/4218: 0.146899 0.150229
Batch: 3816/4218: 0.078898 0.082223
Batch: 3817/4218: 0.014739 0.021257
Batch: 3818/4218: 0.020308 0.028077
Batch: 3819/4218: 0.039286 0.044381
Batch: 3820/4218: 0.018138 0.021662
Batch: 3821/4218: 0.030205 0.033443
Batch: 3822/4218: 0.023536 0.027375
Batch: 3823/4218: 0.057770 0.061031
Batch: 3824/4218: 0.012893 0.016515
Batch: 3825/4218: 0.021179 0.031630
Batch: 3826/4218: 0.014022 0.017789
Batch: 3827/4218: 0.093923 0.097806
Batch: 3828/4218: 0.040539 0.044014
Batch: 3829/4218: 0.135814 0.139295
Batch: 3830/4218: 0.063150 0.067663
Batch: 3831/4218: 0.027174 0.031764
Batch: 3832/4218: 0.029607 0.033029
Batch: 3833/4218: 0.016119 0.019964
Batch: 3834/4218: 0.023524 0.026844
Batch: 3835/4218: 0.020474 0.024844
Batch: 3836/4218: 0.012519 0.016032
Batch: 3837/4218: 0.076992 0.082139
Batch: 3838/4218: 0.038389 0.042221
Batch: 3839/4218: 0.016356 0.019463
Batch: 3840/4218: 0.011512 0.015027
Batch: 3841/4218: 0.068832 0.071930
Batch: 3842/4218: 0.038011 0.042054
Batch: 3843/4218: 0.014235 0.018408
Batch: 3844/4218: 0.016000 0.019971
Batch: 3845/4218: 0.023181 0.026204
Batch: 3846/4218: 0.011941 0.015423
Batch: 3847/4218: 0.013581 0.017139
Batch: 3848/4218: 0.011867 0.015988
Batch: 3849/4218: 0.029735 0.032995
Batch: 3850/4218: 0.052231 0.055191
Batch: 3851/4218: 0.014241 0.017268
Batch: 3852/4218: 0.085106 0.088207
Batch: 3853/4218: 0.008036 0.011022
Batch: 3854/4218: 0.006792 0.009733
Batch: 3855/4218: 0.039518 0.043679
Batch: 3856/4218: 0.020472 0.023884
Batch: 3857/4218: 0.020583 0.023638
Batch: 3858/4218: 0.012435 0.016730
Batch: 3859/4218: 0.043793 0.046715
Batch: 3860/4218: 0.050627 0.053802
Batch: 3861/4218: 0.018645 0.021589
Batch: 3862/4218: 0.025221 0.029329
Batch: 3863/4218: 0.017515 0.026760
Batch: 3864/4218: 0.029740 0.033039
Batch: 3865/4218: 0.025101 0.028379
Batch: 3866/4218: 0.081987 0.086605
Batch: 3867/4218: 0.021336 0.026795
Batch: 3868/4218: 0.057833 0.060686
Batch: 3869/4218: 0.017988 0.021004
Batch: 3870/4218: 0.040758 0.044129
Batch: 3871/4218: 0.027277 0.031005
Batch: 3872/4218: 0.036996 0.040047
Batch: 3873/4218: 0.034763 0.037908
Batch: 3874/4218: 0.018587 0.024281
Batch: 3875/4218: 0.024144 0.026915
Batch: 3876/4218: 0.027623 0.030612
Batch: 3877/4218: 0.027751 0.030603
Batch: 3878/4218: 0.052322 0.056246
Batch: 3879/4218: 0.013802 0.016634
Batch: 3880/4218: 0.018353 0.021188
Batch: 3881/4218: 0.042692 0.046082
Batch: 3882/4218: 0.023113 0.026257
Batch: 3883/4218: 0.012461 0.015111
Batch: 3884/4218: 0.016537 0.019441
Batch: 3885/4218: 0.087502 0.090675
Batch: 3886/4218: 0.019155 0.024623
Batch: 3887/4218: 0.028699 0.031767
Batch: 3888/4218: 0.059578 0.062895
Batch: 3889/4218: 0.015440 0.018471
Batch: 3890/4218: 0.016894 0.019900
Batch: 3891/4218: 0.009367 0.013130
Batch: 3892/4218: 0.028178 0.031442
Batch: 3893/4218: 0.038043 0.041256
Batch: 3894/4218: 0.023433 0.026939
Batch: 3895/4218: 0.108486 0.111360
Batch: 3896/4218: 0.051108 0.054405
Batch: 3897/4218: 0.007997 0.012666
Batch: 3898/4218: 0.045180 0.049060
Batch: 3899/4218: 0.042676 0.046531
Batch: 3900/4218: 0.012014 0.014796
Batch: 3901/4218: 0.006693 0.010345
Batch: 3902/4218: 0.013458 0.017332
Batch: 3903/4218: 0.015244 0.017916
Batch: 3904/4218: 0.008127 0.010913
Batch: 3905/4218: 0.008730 0.011674
Batch: 3906/4218: 0.029585 0.033495
Batch: 3907/4218: 0.015556 0.018564
Batch: 3908/4218: 0.045055 0.048222
Batch: 3909/4218: 0.065643 0.068093
Batch: 3910/4218: 0.055791 0.058359
Batch: 3911/4218: 0.015322 0.018829
Batch: 3912/4218: 0.111528 0.114361
Batch: 3913/4218: 0.026893 0.029509
Batch: 3914/4218: 0.019016 0.021833
Batch: 3915/4218: 0.034513 0.037577
Batch: 3916/4218: 0.008469 0.013154
Batch: 3917/4218: 0.027189 0.033852
Batch: 3918/4218: 0.028865 0.032116
Batch: 3919/4218: 0.037629 0.040233
Batch: 3920/4218: 0.018096 0.022161
Batch: 3921/4218: 0.005787 0.008398
Batch: 3922/4218: 0.046435 0.049967
Batch: 3923/4218: 0.010011 0.013206
Batch: 3924/4218: 0.014016 0.016983
Batch: 3925/4218: 0.016268 0.018915
Batch: 3926/4218: 0.010823 0.013318
Batch: 3927/4218: 0.011688 0.014997
Batch: 3928/4218: 0.035198 0.038048
Batch: 3929/4218: 0.021872 0.024777
Batch: 3930/4218: 0.047191 0.049573
Batch: 3931/4218: 0.023973 0.026469
Batch: 3932/4218: 0.010656 0.013408
Batch: 3933/4218: 0.097855 0.101632
Batch: 3934/4218: 0.147603 0.151046
Batch: 3935/4218: 0.032076 0.034666
Batch: 3936/4218: 0.026300 0.029559
Batch: 3937/4218: 0.030189 0.033978
Batch: 3938/4218: 0.028489 0.030950
Batch: 3939/4218: 0.006794 0.009202
Batch: 3940/4218: 0.010994 0.013389
Batch: 3941/4218: 0.020418 0.024346
Batch: 3942/4218: 0.040692 0.042989
Batch: 3943/4218: 0.022244 0.024609
Batch: 3944/4218: 0.006488 0.009420
Batch: 3945/4218: 0.010975 0.016418
Batch: 3946/4218: 0.018560 0.021191
Batch: 3947/4218: 0.101907 0.105347
Batch: 3948/4218: 0.038867 0.041346
Batch: 3949/4218: 0.006124 0.008445
Batch: 3950/4218: 0.036147 0.038396
Batch: 3951/4218: 0.011758 0.014305
Batch: 3952/4218: 0.016271 0.018931
Batch: 3953/4218: 0.018866 0.021164
Batch: 3954/4218: 0.027857 0.030379
Batch: 3955/4218: 0.033203 0.035722
Batch: 3956/4218: 0.034354 0.036680
Batch: 3957/4218: 0.008207 0.010918
Batch: 3958/4218: 0.025344 0.027747
Batch: 3959/4218: 0.043221 0.045756
Batch: 3960/4218: 0.066268 0.068685
Batch: 3961/4218: 0.017865 0.020262
Batch: 3962/4218: 0.066763 0.069219
Batch: 3963/4218: 0.090613 0.092939
Batch: 3964/4218: 0.018514 0.021321
Batch: 3965/4218: 0.022217 0.043258
Batch: 3966/4218: 0.015525 0.017813
Batch: 3967/4218: 0.033517 0.035941
Batch: 3968/4218: 0.009279 0.011546
Batch: 3969/4218: 0.058727 0.061182
Batch: 3970/4218: 0.013320 0.015569
Batch: 3971/4218: 0.012797 0.015211
Batch: 3972/4218: 0.014860 0.018663
Batch: 3973/4218: 0.009960 0.012854
Batch: 3974/4218: 0.016693 0.019294
Batch: 3975/4218: 0.020591 0.023765
Batch: 3976/4218: 0.025251 0.033099
Batch: 3977/4218: 0.014765 0.017498
Batch: 3978/4218: 0.114944 0.117474
Batch: 3979/4218: 0.016465 0.019035
Batch: 3980/4218: 0.027550 0.030406
Batch: 3981/4218: 0.023917 0.026168
Batch: 3982/4218: 0.025931 0.028929
Batch: 3983/4218: 0.043986 0.046370
Batch: 3984/4218: 0.017722 0.020387
Batch: 3985/4218: 0.031355 0.033834
Batch: 3986/4218: 0.022574 0.025031
Batch: 3987/4218: 0.023347 0.026641
Batch: 3988/4218: 0.051550 0.057467
Batch: 3989/4218: 0.022351 0.024793
Batch: 3990/4218: 0.014932 0.017650
Batch: 3991/4218: 0.034722 0.037578
Batch: 3992/4218: 0.055860 0.058081
Batch: 3993/4218: 0.008615 0.011427
Batch: 3994/4218: 0.009555 0.012084
Batch: 3995/4218: 0.041339 0.043493
Batch: 3996/4218: 0.017527 0.019703
Batch: 3997/4218: 0.036166 0.038680
Batch: 3998/4218: 0.138739 0.140911
Batch: 3999/4218: 0.077213 0.079386
Batch: 4000/4218: 0.154521 0.156884
Batch: 4001/4218: 0.031653 0.033897
Batch: 4002/4218: 0.018925 0.021313
Batch: 4003/4218: 0.018853 0.021042
Batch: 4004/4218: 0.159945 0.162108
Batch: 4005/4218: 0.025121 0.027833
Batch: 4006/4218: 0.032294 0.034479
Batch: 4007/4218: 0.025115 0.027975
Batch: 4008/4218: 0.059108 0.061878
Batch: 4009/4218: 0.053139 0.055271
Batch: 4010/4218: 0.054656 0.057364
Batch: 4011/4218: 0.027649 0.030772
Batch: 4012/4218: 0.039268 0.041518
Batch: 4013/4218: 0.013632 0.016526
Batch: 4014/4218: 0.014175 0.016466
Batch: 4015/4218: 0.040723 0.043466
Batch: 4016/4218: 0.079900 0.082333
Batch: 4017/4218: 0.047317 0.049744
Batch: 4018/4218: 0.044982 0.047437
Batch: 4019/4218: 0.081114 0.083402
Batch: 4020/4218: 0.078614 0.081535
Batch: 4021/4218: 0.040404 0.042479
Batch: 4022/4218: 0.038410 0.040507
Batch: 4023/4218: 0.105345 0.107565
Batch: 4024/4218: 0.037018 0.039160
Batch: 4025/4218: 0.013665 0.017830
Batch: 4026/4218: 0.033078 0.035343
Batch: 4027/4218: 0.098636 0.101103
Batch: 4028/4218: 0.133443 0.135882
Batch: 4029/4218: 0.168182 0.170527
Batch: 4030/4218: 0.084393 0.087040
Batch: 4031/4218: 0.147772 0.150095
Batch: 4032/4218: 0.112022 0.114671
Batch: 4033/4218: 0.038725 0.040840
Batch: 4034/4218: 0.028012 0.030066
Batch: 4035/4218: 0.020564 0.022778
Batch: 4036/4218: 0.022525 0.024729
Batch: 4037/4218: 0.020195 0.022247
Batch: 4038/4218: 0.089308 0.093216
Batch: 4039/4218: 0.032733 0.034936
Batch: 4040/4218: 0.025386 0.028650
Batch: 4041/4218: 0.018089 0.020329
Batch: 4042/4218: 0.023293 0.025391
Batch: 4043/4218: 0.121358 0.123829
Batch: 4044/4218: 0.057185 0.059375
Batch: 4045/4218: 0.039810 0.042697
Batch: 4046/4218: 0.065132 0.067139
Batch: 4047/4218: 0.044931 0.046991
Batch: 4048/4218: 0.052396 0.055207
Batch: 4049/4218: 0.022188 0.036385
Batch: 4050/4218: 0.043407 0.052753
Batch: 4051/4218: 0.020031 0.022081
Batch: 4052/4218: 0.036005 0.038894
Batch: 4053/4218: 0.016969 0.019362
Batch: 4054/4218: 0.017450 0.019403
Batch: 4055/4218: 0.082438 0.084471
Batch: 4056/4218: 0.044048 0.046093
Batch: 4057/4218: 0.016426 0.018870
Batch: 4058/4218: 0.014523 0.023197
Batch: 4059/4218: 0.010659 0.012677
Batch: 4060/4218: 0.053725 0.055737
Batch: 4061/4218: 0.040226 0.042307
Batch: 4062/4218: 0.016121 0.018661
Batch: 4063/4218: 0.075078 0.080368
Batch: 4064/4218: 0.016244 0.021906
Batch: 4065/4218: 0.015375 0.017579
Batch: 4066/4218: 0.025774 0.027781
Batch: 4067/4218: 0.019264 0.023267
Batch: 4068/4218: 0.007374 0.011936
Batch: 4069/4218: 0.019614 0.021588
Batch: 4070/4218: 0.039091 0.041340
Batch: 4071/4218: 0.032792 0.035646
Batch: 4072/4218: 0.003860 0.005898
Batch: 4073/4218: 0.007675 0.009580
Batch: 4074/4218: 0.007213 0.009187
Batch: 4075/4218: 0.020610 0.023970
Batch: 4076/4218: 0.030645 0.032864
Batch: 4077/4218: 0.024150 0.026156
Batch: 4078/4218: 0.028158 0.030376
Batch: 4079/4218: 0.010444 0.013107
Batch: 4080/4218: 0.009598 0.011710
Batch: 4081/4218: 0.085775 0.087944
Batch: 4082/4218: 0.009743 0.011930
Batch: 4083/4218: 0.014053 0.016095
Batch: 4084/4218: 0.022451 0.024582
Batch: 4085/4218: 0.034356 0.038981
Batch: 4086/4218: 0.009302 0.012321
Batch: 4087/4218: 0.003924 0.006515
Batch: 4088/4218: 0.008610 0.010619
Batch: 4089/4218: 0.019477 0.021404
Batch: 4090/4218: 0.019922 0.024993
Batch: 4091/4218: 0.006696 0.009046
Batch: 4092/4218: 0.020640 0.022951
Batch: 4093/4218: 0.042850 0.046503
Batch: 4094/4218: 0.007931 0.010457
Batch: 4095/4218: 0.024693 0.026617
Batch: 4096/4218: 0.023259 0.025158
Batch: 4097/4218: 0.039286 0.041227
Batch: 4098/4218: 0.022902 0.025145
Batch: 4099/4218: 0.014401 0.016578
Batch: 4100/4218: 0.008029 0.010083
Batch: 4101/4218: 0.019357 0.021204
Batch: 4102/4218: 0.031069 0.032895
Batch: 4103/4218: 0.056056 0.058207
Batch: 4104/4218: 0.012876 0.015019
Batch: 4105/4218: 0.024375 0.026752
Batch: 4106/4218: 0.011602 0.013628
Batch: 4107/4218: 0.038549 0.040606
Batch: 4108/4218: 0.017987 0.020004
Batch: 4109/4218: 0.032537 0.034710
Batch: 4110/4218: 0.030424 0.032387
Batch: 4111/4218: 0.023844 0.025736
Batch: 4112/4218: 0.012634 0.014396
Batch: 4113/4218: 0.031143 0.033168
Batch: 4114/4218: 0.011175 0.013086
Batch: 4115/4218: 0.011740 0.014974
Batch: 4116/4218: 0.056011 0.058384
Batch: 4117/4218: 0.017453 0.020240
Batch: 4118/4218: 0.057085 0.058889
Batch: 4119/4218: 0.016952 0.019935
Batch: 4120/4218: 0.031320 0.035830
Batch: 4121/4218: 0.038744 0.043683
Batch: 4122/4218: 0.023911 0.025864
Batch: 4123/4218: 0.017109 0.018986
Batch: 4124/4218: 0.012546 0.014336
Batch: 4125/4218: 0.009073 0.011418
Batch: 4126/4218: 0.029650 0.031755
Batch: 4127/4218: 0.030447 0.032628
Batch: 4128/4218: 0.120122 0.123246
Batch: 4129/4218: 0.024213 0.026097
Batch: 4130/4218: 0.017300 0.027139
Batch: 4131/4218: 0.038641 0.041905
Batch: 4132/4218: 0.027826 0.030601
Batch: 4133/4218: 0.104024 0.107234
Batch: 4134/4218: 0.057751 0.059756
Batch: 4135/4218: 0.007923 0.011065
Batch: 4136/4218: 0.033808 0.036055
Batch: 4137/4218: 0.011407 0.013612
Batch: 4138/4218: 0.020070 0.021845
Batch: 4139/4218: 0.039695 0.041449
Batch: 4140/4218: 0.118388 0.120897
Batch: 4141/4218: 0.027588 0.029711
Batch: 4142/4218: 0.015624 0.017463
Batch: 4143/4218: 0.014868 0.016676
Batch: 4144/4218: 0.018036 0.019888
Batch: 4145/4218: 0.015588 0.019675
Batch: 4146/4218: 0.016533 0.018387
Batch: 4147/4218: 0.011635 0.014264
Batch: 4148/4218: 0.025570 0.027441
Batch: 4149/4218: 0.023147 0.025067
Batch: 4150/4218: 0.009524 0.011475
Batch: 4151/4218: 0.022539 0.024486
Batch: 4152/4218: 0.047828 0.049620
Batch: 4153/4218: 0.007307 0.009415
Batch: 4154/4218: 0.009937 0.013824
Batch: 4155/4218: 0.054013 0.056354
Batch: 4156/4218: 0.020271 0.022158
Batch: 4157/4218: 0.103020 0.105818
Batch: 4158/4218: 0.063147 0.067678
Batch: 4159/4218: 0.012420 0.014122
Batch: 4160/4218: 0.050045 0.052127
Batch: 4161/4218: 0.024595 0.026839
Batch: 4162/4218: 0.161439 0.163674
Batch: 4163/4218: 0.026101 0.027987
Batch: 4164/4218: 0.055276 0.057016
Batch: 4165/4218: 0.035224 0.038508
Batch: 4166/4218: 0.029048 0.030800
Batch: 4167/4218: 0.024186 0.026019
Batch: 4168/4218: 0.022643 0.024587
Batch: 4169/4218: 0.026938 0.031445
Batch: 4170/4218: 0.038199 0.040249
Batch: 4171/4218: 0.019376 0.042827
Batch: 4172/4218: 0.019940 0.021698
Batch: 4173/4218: 0.073754 0.075686
Batch: 4174/4218: 0.015477 0.017807
Batch: 4175/4218: 0.012037 0.013820
Batch: 4176/4218: 0.010983 0.012814
Batch: 4177/4218: 0.017085 0.018920
Batch: 4178/4218: 0.024900 0.028617
Batch: 4179/4218: 0.101419 0.103353
Batch: 4180/4218: 0.033497 0.036246
Batch: 4181/4218: 0.013204 0.016824
Batch: 4182/4218: 0.011522 0.013531
Batch: 4183/4218: 0.022753 0.025344
Batch: 4184/4218: 0.013518 0.015256
Batch: 4185/4218: 0.050149 0.052083
Batch: 4186/4218: 0.024543 0.028193
Batch: 4187/4218: 0.047666 0.049611
Batch: 4188/4218: 0.020604 0.023571
Batch: 4189/4218: 0.012124 0.014582
Batch: 4190/4218: 0.046906 0.048608
Batch: 4191/4218: 0.019727 0.022605
Batch: 4192/4218: 0.023547 0.025440
Batch: 4193/4218: 0.020740 0.023053
Batch: 4194/4218: 0.024749 0.026631
Batch: 4195/4218: 0.035272 0.037125
Batch: 4196/4218: 0.033635 0.035274
Batch: 4197/4218: 0.008602 0.011729
Batch: 4198/4218: 0.029421 0.031225
Batch: 4199/4218: 0.036646 0.038773
Batch: 4200/4218: 0.010344 0.012531
Batch: 4201/4218: 0.027773 0.030510
Batch: 4202/4218: 0.045037 0.047138
Batch: 4203/4218: 0.010714 0.012516
Batch: 4204/4218: 0.012176 0.014356
Batch: 4205/4218: 0.025144 0.026920
Batch: 4206/4218: 0.038580 0.041043
Batch: 4207/4218: 0.011275 0.012884
Batch: 4208/4218: 0.012204 0.013871
Batch: 4209/4218: 0.030312 0.033369
Batch: 4210/4218: 0.037559 0.039477
Batch: 4211/4218: 0.027811 0.040460
Batch: 4212/4218: 0.015112 0.017266
Batch: 4213/4218: 0.018557 0.020630
Batch: 4214/4218: 0.059925 0.061729
Batch: 4215/4218: 0.019206 0.021092
Batch: 4216/4218: 0.037423 0.039287
Batch: 4217/4218: 0.038459 0.040419
Batch: 4218/4218: 0.034828 0.036852

In [ ]:

plt.figure(figsize=(12, 4))
plt.plot(aloss)
plt.plot(sloss)

Out[ ]:

[<matplotlib.lines.Line2D at 0x7ff1ef5b76d8>]

In [ ]:

plt.figure(figsize=(12, 4))
plt.plot(aloss[-500:])
plt.plot(sloss[-500:])

Out[ ]:

[<matplotlib.lines.Line2D at 0x7ff1ef2edd30>]

4. Results¶

We plot an image to see the results

In [ ]:

def revert_to_rgb(img):
    # Revert to RGB
    return np.clip((img + 0.5) * 255, 0, 255).astype('uint8')

In [ ]:

from skimage.color import *
def revert_img_special(img):
    # Transform color image to different representation
    
    img = hsv2rgb(img + 0.5)
    img = img - np.percentile(img, 1)
    img = img / np.percentile(img, 99)
    return np.clip(img*255, 0,255).astype('uint8')
    
    #return np.clip(((hed2rgb(img)-0.5)+1)*255, 0,255).astype('uint8')

In [ ]:

# Select a few images
n_examples = 20
selecter = np.random.choice(np.arange(len(fx_train)), n_examples)
x_valid = np.array([load_img(fx_train[s]) for s in selecter])
y_valid = np.array([load_img(fy_train[s]) for s in selecter])
#y_valid = np.array([load_img_special(fy_train[s]) for s in selecter])

In [ ]:

y_hat = np.array([revert_to_rgb(i) for i in tqdm(generator(x_valid).numpy())])
#y_hat = np.array([revert_img_special(i) for i in tqdm(generator(x_valid).numpy())])

In [ ]:

# Let's plot the prediction of one example
idx = 1
plt.imshow(y_hat[idx])

Out[ ]:

<matplotlib.image.AxesImage at 0x7ff1ef11f1d0>

In [ ]:

# Let's plot the original image
ex1 = revert_to_rgb(y_valid[1])
plt.imshow(ex1)

Out[ ]:

<matplotlib.image.AxesImage at 0x7ff1ef13eb38>

In [ ]:

# Let's get the prediction in transformed space
ex2 = y_hat[1]

In [ ]:

# Let's get target in transformed space
ex3 = y_valid[1]

In [ ]:

# Let's plot the RGB histograms for the target image in transformed space
plt.figure(figsize=(12, 5))
plt.title('Validation scaled')
for i in range(3):
    plt.hist(np.ravel(ex3[..., i]), bins=255, alpha=0.5)

In [ ]:

# Let's plot the RGB histograms for the target image in original space
plt.figure(figsize=(12, 5))
plt.title('Validation reversed')
for i in range(3):
    plt.hist(np.ravel(ex1[..., i]), bins=255, alpha=0.5)

In [ ]:

# Let's plot the RGB histograms for the prediction image in transformed space
plt.figure(figsize=(12, 5))
plt.title('Prediction')
for i in range(3):
    plt.hist(np.ravel(ex2[..., i]), bins=256, alpha=0.5)

In [ ]:

# Let's plot a few examples (original, target and prediction)
for i, y in enumerate(y_hat):
    fig, axs = plt.subplots(1, 3, figsize=(12, 4), sharey=True)
    axs[0].imshow(x_valid[i], cmap='gray')
    axs[0].set_title('Original')
    axs[1].imshow(revert_to_rgb(y_valid[i]))
    axs[1].set_title('Target')
    axs[2].imshow(y_hat[i])
    axs[2].set_title('Colorized')
    plt.show()

Output hidden; open in https://colab.research.google.com to view.

Save Test predictions¶

In [ ]:

!rm -rf test_color_images
!mkdir test_color_images

In [ ]:

from PIL import Image
from os.path import basename, join

# Select a few images
predictions = []

for f in tqdm(fimgs_te_x):
  out_file = join('test_color_images', basename(f))
  img = revert_to_rgb(generator(load_img(f)[None, ...]).numpy()[0])
  im = Image.fromarray(img)
  im.save(out_file)

In [ ]:

!zip -r "new_submission_hsv_16.zip" "test_color_images/"

Content

2730

Show Comments

Comments

You must login before you can post a comment.