MNIST Data Classification using Tensorflow Estimator API

In this tutorial, we'll be using Tensorflow's estimator API for Fashion MNIST data classification. So, let's get started...

Step-1: Import Dependencies

In [1]:
# Import Dependencies
import numpy as np
import pandas as pd
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
from sklearn.model_selection import train_test_split
import matplotlib.pyplot as plt
%matplotlib inline
/home/anuj_dutt_ml/.local/lib/python3.5/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/contrib/learn/python/learn/datasets/base.py:198: retry (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.
Instructions for updating:
Use the retry module or similar alternatives.

Step-2: Load Dataset

The Fashion MNIST dataset contains 10 different types of things like shoes, coat, sandal etc. The aim is to classify them using their images.

The first step here is to load the dataset. For this, we can use the same line of code that we use for loading the MNIST data from Tensorflow. The only difference here is that, we download the Fashion MNIST dataset files into the "dataset" directory and tensorflow will do the rest.

In [2]:
# Load Dataset
fashion_mnist = input_data.read_data_sets('./dataset/')
WARNING:tensorflow:From <ipython-input-2-22fe90ae7521>:2: read_data_sets (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use alternatives such as official/mnist/dataset.py from tensorflow/models.
WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:260: maybe_download (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.
Instructions for updating:
Please write your own downloading logic.
WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:262: extract_images (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use tf.data to implement this functionality.
Extracting ./dataset/train-images-idx3-ubyte.gz
WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:267: extract_labels (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use tf.data to implement this functionality.
Extracting ./dataset/train-labels-idx1-ubyte.gz
Extracting ./dataset/t10k-images-idx3-ubyte.gz
Extracting ./dataset/t10k-labels-idx1-ubyte.gz
WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:290: DataSet.__init__ (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use alternatives such as official/mnist/dataset.py from tensorflow/models.

Next, we'll write a function that processes the images to load the training and test data. The labels for this data are present as is which need to be converted to type of np.int32.

In [3]:
# Function to Process Images into Right Format
def process_data(data=None):
    return data.images, data.labels.astype(np.int32)
In [4]:
# Load Training Data
X, y = process_data(data=fashion_mnist.train)[0], process_data(data=fashion_mnist.train)[1]
In [5]:
# Load Test Data
X_test, y_test = process_data(data=fashion_mnist.test)[0], process_data(data=fashion_mnist.test)[1]
In [6]:
X.shape, y.shape
Out[6]:
((55000, 784), (55000,))

Once we have loaded the data, we will divide the training data into Train and Validation sets. This will help us to validate the model performance before testing the model on the test data.

In [7]:
# Train Validation Split
X_train, X_val, y_train, y_val = train_test_split(X, y, test_size=0.2, random_state=101)
X_train.shape, y_train.shape, X_val.shape, y_val.shape
Out[7]:
((44000, 784), (44000,), (11000, 784), (11000,))

Step-3: Visualize Sample Data

The lines of code below helps to plot some sample images from the training dataset to show how the dataset looks like.

In [8]:
# Plot some images from Dataset
fig = plt.figure(figsize=(20,5))
for i in range(36):
    ax = fig.add_subplot(3,12, i+1, xticks=[], yticks=[])
    ax.imshow(np.squeeze(X_train[i].reshape(28,28)))

Step-4: Define Training Input and Create Estimator Model

Next, we'll define the training feature columns. Since the feature values are numerical values, we'll create the numerical columns.

In [9]:
# Define Feature Column
feat_cols = [tf.feature_column.numeric_column('x', shape=[28,28])]
In [10]:
# Define Training Input
train_input = tf.estimator.inputs.numpy_input_fn(x={'x':X_train}, y=y_train, num_epochs=None, batch_size=50, shuffle=True)
In [11]:
# DNN Classifier Model
dnn_model = tf.estimator.DNNClassifier(feature_columns=feat_cols, hidden_units=[256, 32], optimizer=tf.train.AdamOptimizer(1e-4), n_classes=10, dropout=0.1, model_dir='./mnist_model')
INFO:tensorflow:Using default config.
INFO:tensorflow:Using config: {'_save_checkpoints_steps': None, '_task_type': 'worker', '_global_id_in_cluster': 0, '_master': '', '_is_chief': True, '_save_summary_steps': 100, '_num_worker_replicas': 1, '_keep_checkpoint_max': 5, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f4c65b24630>, '_log_step_count_steps': 100, '_tf_random_seed': None, '_task_id': 0, '_model_dir': './mnist_model', '_service': None, '_save_checkpoints_secs': 600, '_evaluation_master': '', '_session_config': None, '_num_ps_replicas': 0, '_keep_checkpoint_every_n_hours': 10000}
In [12]:
# Training the Model
dnn_model.train(input_fn=train_input, steps=100000)
INFO:tensorflow:Calling model_fn.
INFO:tensorflow:Done calling model_fn.
INFO:tensorflow:Create CheckpointSaverHook.
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from ./mnist_model/model.ckpt-214000
INFO:tensorflow:Running local_init_op.
INFO:tensorflow:Done running local_init_op.
INFO:tensorflow:Saving checkpoints for 214001 into ./mnist_model/model.ckpt.
INFO:tensorflow:step = 214000, loss = 4.4047165
INFO:tensorflow:global_step/sec: 361.023
INFO:tensorflow:step = 214100, loss = 2.8470101 (0.278 sec)
INFO:tensorflow:global_step/sec: 466.876
INFO:tensorflow:step = 214200, loss = 4.1019764 (0.214 sec)
INFO:tensorflow:global_step/sec: 470.862
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INFO:tensorflow:global_step/sec: 470.079
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INFO:tensorflow:global_step/sec: 469.099
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INFO:tensorflow:global_step/sec: 471.336
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INFO:tensorflow:global_step/sec: 459.635
INFO:tensorflow:step = 214700, loss = 0.50377756 (0.217 sec)
INFO:tensorflow:global_step/sec: 473.088
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INFO:tensorflow:global_step/sec: 463.843
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INFO:tensorflow:global_step/sec: 466.892
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INFO:tensorflow:global_step/sec: 466.455
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INFO:tensorflow:global_step/sec: 470.433
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INFO:tensorflow:global_step/sec: 465.114
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INFO:tensorflow:global_step/sec: 480.58
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INFO:tensorflow:global_step/sec: 469.056
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INFO:tensorflow:global_step/sec: 479.152
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INFO:tensorflow:global_step/sec: 485.521
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INFO:tensorflow:global_step/sec: 481.288
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INFO:tensorflow:global_step/sec: 491.994
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INFO:tensorflow:global_step/sec: 471.853
INFO:tensorflow:step = 228500, loss = 2.3510535 (0.212 sec)
INFO:tensorflow:global_step/sec: 470.227
INFO:tensorflow:step = 228600, loss = 1.0225965 (0.212 sec)
INFO:tensorflow:global_step/sec: 473.03
INFO:tensorflow:step = 228700, loss = 0.2706992 (0.211 sec)
INFO:tensorflow:global_step/sec: 467.266
INFO:tensorflow:step = 228800, loss = 2.2464252 (0.214 sec)
INFO:tensorflow:global_step/sec: 458.587
INFO:tensorflow:step = 228900, loss = 0.73202 (0.218 sec)
INFO:tensorflow:global_step/sec: 473.398
INFO:tensorflow:step = 229000, loss = 0.23800716 (0.211 sec)
INFO:tensorflow:global_step/sec: 475.1
INFO:tensorflow:step = 229100, loss = 11.932999 (0.210 sec)
INFO:tensorflow:global_step/sec: 463.913
INFO:tensorflow:step = 229200, loss = 0.31813708 (0.216 sec)
INFO:tensorflow:global_step/sec: 466.879
INFO:tensorflow:step = 229300, loss = 2.3007598 (0.214 sec)
INFO:tensorflow:global_step/sec: 472.748
INFO:tensorflow:step = 229400, loss = 0.083568096 (0.212 sec)
INFO:tensorflow:global_step/sec: 474.207
INFO:tensorflow:step = 229500, loss = 2.5192318 (0.211 sec)
INFO:tensorflow:global_step/sec: 480.906
INFO:tensorflow:step = 229600, loss = 1.6315649 (0.210 sec)
INFO:tensorflow:global_step/sec: 465.038
INFO:tensorflow:step = 229700, loss = 1.5279796 (0.215 sec)
INFO:tensorflow:global_step/sec: 450.607
INFO:tensorflow:step = 229800, loss = 5.5733643 (0.220 sec)
INFO:tensorflow:global_step/sec: 470.19
INFO:tensorflow:step = 229900, loss = 0.3253654 (0.212 sec)
INFO:tensorflow:global_step/sec: 460.164
INFO:tensorflow:step = 230000, loss = 3.256432 (0.218 sec)
INFO:tensorflow:global_step/sec: 475.563
INFO:tensorflow:step = 230100, loss = 0.54738677 (0.210 sec)
INFO:tensorflow:global_step/sec: 468.035
INFO:tensorflow:step = 230200, loss = 2.8638897 (0.214 sec)
INFO:tensorflow:global_step/sec: 469.544
INFO:tensorflow:step = 230300, loss = 0.49210554 (0.213 sec)
INFO:tensorflow:global_step/sec: 475.568
INFO:tensorflow:step = 230400, loss = 1.6774603 (0.210 sec)
INFO:tensorflow:global_step/sec: 471.041
INFO:tensorflow:step = 230500, loss = 0.2823835 (0.213 sec)
INFO:tensorflow:global_step/sec: 467.294
INFO:tensorflow:step = 230600, loss = 0.7200226 (0.214 sec)
INFO:tensorflow:global_step/sec: 471.003
INFO:tensorflow:step = 230700, loss = 2.162878 (0.213 sec)
INFO:tensorflow:global_step/sec: 466.356
INFO:tensorflow:step = 230800, loss = 0.33799922 (0.214 sec)
INFO:tensorflow:global_step/sec: 471.842
INFO:tensorflow:step = 230900, loss = 0.061303496 (0.212 sec)
INFO:tensorflow:global_step/sec: 454.668
INFO:tensorflow:step = 231000, loss = 1.1896036 (0.220 sec)
INFO:tensorflow:global_step/sec: 458.396
INFO:tensorflow:step = 231100, loss = 1.0440559 (0.218 sec)
INFO:tensorflow:global_step/sec: 468.416
INFO:tensorflow:step = 231200, loss = 0.12856391 (0.213 sec)
INFO:tensorflow:global_step/sec: 472.319
INFO:tensorflow:step = 231300, loss = 0.43921837 (0.212 sec)
INFO:tensorflow:global_step/sec: 475.109
INFO:tensorflow:step = 231400, loss = 2.0674343 (0.210 sec)
INFO:tensorflow:global_step/sec: 464.333
INFO:tensorflow:step = 231500, loss = 0.7997259 (0.215 sec)
INFO:tensorflow:global_step/sec: 465.363
INFO:tensorflow:step = 231600, loss = 0.33111396 (0.215 sec)
INFO:tensorflow:global_step/sec: 462.349
INFO:tensorflow:step = 231700, loss = 0.34560803 (0.216 sec)
INFO:tensorflow:global_step/sec: 469.058
INFO:tensorflow:step = 231800, loss = 4.4316425 (0.213 sec)
INFO:tensorflow:global_step/sec: 476.966
INFO:tensorflow:step = 231900, loss = 0.13167672 (0.211 sec)
INFO:tensorflow:global_step/sec: 454.949
INFO:tensorflow:step = 232000, loss = 0.58271956 (0.219 sec)
INFO:tensorflow:global_step/sec: 467.784
INFO:tensorflow:step = 232100, loss = 0.17745477 (0.214 sec)
INFO:tensorflow:global_step/sec: 475.023
INFO:tensorflow:step = 232200, loss = 2.1893282 (0.211 sec)
INFO:tensorflow:global_step/sec: 478.858
INFO:tensorflow:step = 232300, loss = 0.24528025 (0.209 sec)
INFO:tensorflow:global_step/sec: 474.081
INFO:tensorflow:step = 232400, loss = 0.788628 (0.211 sec)
INFO:tensorflow:global_step/sec: 459.286
INFO:tensorflow:step = 232500, loss = 2.9122877 (0.218 sec)
INFO:tensorflow:global_step/sec: 464.915
INFO:tensorflow:step = 232600, loss = 0.5949832 (0.215 sec)
INFO:tensorflow:global_step/sec: 474.896
INFO:tensorflow:step = 232700, loss = 0.15858772 (0.211 sec)
INFO:tensorflow:global_step/sec: 476.544
INFO:tensorflow:step = 232800, loss = 1.9849036 (0.210 sec)
INFO:tensorflow:global_step/sec: 461.905
INFO:tensorflow:step = 232900, loss = 10.419424 (0.216 sec)
INFO:tensorflow:global_step/sec: 458.249
INFO:tensorflow:step = 233000, loss = 0.08642523 (0.218 sec)
INFO:tensorflow:global_step/sec: 467.153
INFO:tensorflow:step = 233100, loss = 2.3065348 (0.214 sec)
INFO:tensorflow:global_step/sec: 477.82
INFO:tensorflow:step = 233200, loss = 0.5189451 (0.209 sec)
INFO:tensorflow:global_step/sec: 475.27
INFO:tensorflow:step = 233300, loss = 2.8742514 (0.211 sec)
INFO:tensorflow:global_step/sec: 476.858
INFO:tensorflow:step = 233400, loss = 0.91007996 (0.210 sec)
INFO:tensorflow:global_step/sec: 477.305
INFO:tensorflow:step = 233500, loss = 0.6381906 (0.210 sec)
INFO:tensorflow:global_step/sec: 472.072
INFO:tensorflow:step = 233600, loss = 4.3273115 (0.212 sec)
INFO:tensorflow:global_step/sec: 465.959
INFO:tensorflow:step = 233700, loss = 0.24073297 (0.214 sec)
INFO:tensorflow:global_step/sec: 470.668
INFO:tensorflow:step = 233800, loss = 0.6414058 (0.212 sec)
INFO:tensorflow:global_step/sec: 456.788
INFO:tensorflow:step = 233900, loss = 0.09655949 (0.219 sec)
INFO:tensorflow:global_step/sec: 458.57
INFO:tensorflow:step = 234000, loss = 0.09315111 (0.218 sec)
INFO:tensorflow:global_step/sec: 466.223
INFO:tensorflow:step = 234100, loss = 4.068782 (0.214 sec)
INFO:tensorflow:global_step/sec: 459.674
INFO:tensorflow:step = 234200, loss = 0.4758309 (0.220 sec)
INFO:tensorflow:global_step/sec: 460.142
INFO:tensorflow:step = 234300, loss = 1.4781373 (0.215 sec)
INFO:tensorflow:global_step/sec: 463.183
INFO:tensorflow:step = 234400, loss = 1.148347 (0.216 sec)
INFO:tensorflow:global_step/sec: 455.214
INFO:tensorflow:step = 234500, loss = 1.2569373 (0.220 sec)
INFO:tensorflow:global_step/sec: 468.531
INFO:tensorflow:step = 234600, loss = 0.1415101 (0.214 sec)
INFO:tensorflow:global_step/sec: 466.636
INFO:tensorflow:step = 234700, loss = 0.15472017 (0.214 sec)
INFO:tensorflow:global_step/sec: 470.859
INFO:tensorflow:step = 234800, loss = 2.815172 (0.212 sec)
INFO:tensorflow:global_step/sec: 456.398
INFO:tensorflow:step = 234900, loss = 1.5424176 (0.219 sec)
INFO:tensorflow:global_step/sec: 468.492
INFO:tensorflow:step = 235000, loss = 0.27428117 (0.213 sec)
INFO:tensorflow:global_step/sec: 468.434
INFO:tensorflow:step = 235100, loss = 0.44933605 (0.214 sec)
INFO:tensorflow:global_step/sec: 472.095
INFO:tensorflow:step = 235200, loss = 0.14541058 (0.212 sec)
INFO:tensorflow:global_step/sec: 470.476
INFO:tensorflow:step = 235300, loss = 0.15908682 (0.213 sec)
INFO:tensorflow:global_step/sec: 462.571
INFO:tensorflow:step = 235400, loss = 0.50626016 (0.216 sec)
INFO:tensorflow:global_step/sec: 467.629
INFO:tensorflow:step = 235500, loss = 0.77015066 (0.214 sec)
INFO:tensorflow:global_step/sec: 461.402
INFO:tensorflow:step = 235600, loss = 2.256819 (0.217 sec)
INFO:tensorflow:global_step/sec: 467.361
INFO:tensorflow:step = 235700, loss = 1.1912134 (0.214 sec)
INFO:tensorflow:global_step/sec: 455.566
INFO:tensorflow:step = 235800, loss = 0.41413417 (0.219 sec)
INFO:tensorflow:global_step/sec: 469.902
INFO:tensorflow:step = 235900, loss = 0.9647351 (0.213 sec)
INFO:tensorflow:global_step/sec: 464.2
INFO:tensorflow:step = 236000, loss = 0.10574846 (0.215 sec)
INFO:tensorflow:global_step/sec: 455.802
INFO:tensorflow:step = 236100, loss = 0.13254881 (0.219 sec)
INFO:tensorflow:global_step/sec: 462.969
INFO:tensorflow:step = 236200, loss = 0.24639295 (0.216 sec)
INFO:tensorflow:global_step/sec: 464.742
INFO:tensorflow:step = 236300, loss = 0.19395995 (0.215 sec)
INFO:tensorflow:global_step/sec: 462.417
INFO:tensorflow:step = 236400, loss = 3.0037599 (0.216 sec)
INFO:tensorflow:global_step/sec: 466.821
INFO:tensorflow:step = 236500, loss = 1.0073681 (0.214 sec)
INFO:tensorflow:global_step/sec: 458.651
INFO:tensorflow:step = 236600, loss = 0.2203187 (0.218 sec)
INFO:tensorflow:global_step/sec: 462.904
INFO:tensorflow:step = 236700, loss = 1.1463474 (0.216 sec)
INFO:tensorflow:global_step/sec: 465.08
INFO:tensorflow:step = 236800, loss = 0.85998315 (0.215 sec)
INFO:tensorflow:global_step/sec: 459.265
INFO:tensorflow:step = 236900, loss = 0.98631036 (0.218 sec)
INFO:tensorflow:global_step/sec: 463.002
INFO:tensorflow:step = 237000, loss = 0.50453216 (0.216 sec)
INFO:tensorflow:global_step/sec: 453.469
INFO:tensorflow:step = 237100, loss = 2.332663 (0.220 sec)
INFO:tensorflow:global_step/sec: 467.293
INFO:tensorflow:step = 237200, loss = 0.080410734 (0.214 sec)
INFO:tensorflow:global_step/sec: 465.651
INFO:tensorflow:step = 237300, loss = 3.2874126 (0.215 sec)
INFO:tensorflow:global_step/sec: 462.074
INFO:tensorflow:step = 237400, loss = 0.2976181 (0.216 sec)
INFO:tensorflow:global_step/sec: 463.838
INFO:tensorflow:step = 237500, loss = 1.7414224 (0.215 sec)
INFO:tensorflow:global_step/sec: 471.489
INFO:tensorflow:step = 237600, loss = 0.8393284 (0.212 sec)
INFO:tensorflow:global_step/sec: 457.496
INFO:tensorflow:step = 237700, loss = 0.95602477 (0.218 sec)
INFO:tensorflow:global_step/sec: 460.667
INFO:tensorflow:step = 237800, loss = 3.0050583 (0.217 sec)
INFO:tensorflow:global_step/sec: 462.627
INFO:tensorflow:step = 237900, loss = 2.1325378 (0.216 sec)
INFO:tensorflow:global_step/sec: 478.784
INFO:tensorflow:step = 238000, loss = 3.6949272 (0.209 sec)
INFO:tensorflow:global_step/sec: 477.641
INFO:tensorflow:step = 238100, loss = 2.465623 (0.209 sec)
INFO:tensorflow:global_step/sec: 483.475
INFO:tensorflow:step = 238200, loss = 0.24580568 (0.207 sec)
INFO:tensorflow:global_step/sec: 477.437
INFO:tensorflow:step = 238300, loss = 0.8516282 (0.210 sec)
INFO:tensorflow:global_step/sec: 477.86
INFO:tensorflow:step = 238400, loss = 0.26573864 (0.210 sec)
INFO:tensorflow:global_step/sec: 480.524
INFO:tensorflow:step = 238500, loss = 0.3126948 (0.208 sec)
INFO:tensorflow:global_step/sec: 467.223
INFO:tensorflow:step = 238600, loss = 0.8899884 (0.214 sec)
INFO:tensorflow:global_step/sec: 475.119
INFO:tensorflow:step = 238700, loss = 0.25815403 (0.210 sec)
INFO:tensorflow:global_step/sec: 471.166
INFO:tensorflow:step = 238800, loss = 1.1169372 (0.212 sec)
INFO:tensorflow:global_step/sec: 459.084
INFO:tensorflow:step = 238900, loss = 1.8862324 (0.218 sec)
INFO:tensorflow:global_step/sec: 466.143
INFO:tensorflow:step = 239000, loss = 0.2503826 (0.215 sec)
INFO:tensorflow:global_step/sec: 459.108
INFO:tensorflow:step = 239100, loss = 0.31988984 (0.218 sec)
INFO:tensorflow:global_step/sec: 472.196
INFO:tensorflow:step = 239200, loss = 5.8338666 (0.212 sec)
INFO:tensorflow:global_step/sec: 468.721
INFO:tensorflow:step = 239300, loss = 0.4675037 (0.213 sec)
INFO:tensorflow:global_step/sec: 472.233
INFO:tensorflow:step = 239400, loss = 0.8844903 (0.212 sec)
INFO:tensorflow:global_step/sec: 468.052
INFO:tensorflow:step = 239500, loss = 1.6195822 (0.214 sec)
INFO:tensorflow:global_step/sec: 466.641
INFO:tensorflow:step = 239600, loss = 0.09199192 (0.214 sec)
INFO:tensorflow:global_step/sec: 453.215
INFO:tensorflow:step = 239700, loss = 3.183813 (0.221 sec)
INFO:tensorflow:global_step/sec: 458.218
INFO:tensorflow:step = 239800, loss = 0.8713079 (0.218 sec)
INFO:tensorflow:global_step/sec: 456.248
INFO:tensorflow:step = 239900, loss = 0.14510123 (0.219 sec)
INFO:tensorflow:global_step/sec: 453.183
INFO:tensorflow:step = 240000, loss = 0.39132363 (0.221 sec)
INFO:tensorflow:global_step/sec: 463.376
INFO:tensorflow:step = 240100, loss = 0.22916712 (0.216 sec)
INFO:tensorflow:global_step/sec: 460.228
INFO:tensorflow:step = 240200, loss = 0.80678827 (0.217 sec)
INFO:tensorflow:global_step/sec: 465.712
INFO:tensorflow:step = 240300, loss = 3.1760323 (0.214 sec)
INFO:tensorflow:global_step/sec: 455.068
INFO:tensorflow:step = 240400, loss = 2.3214595 (0.220 sec)
INFO:tensorflow:global_step/sec: 457.148
INFO:tensorflow:step = 240500, loss = 0.45948976 (0.219 sec)
INFO:tensorflow:global_step/sec: 467.637
INFO:tensorflow:step = 240600, loss = 0.3977327 (0.214 sec)
INFO:tensorflow:global_step/sec: 470.807
INFO:tensorflow:step = 240700, loss = 0.25620922 (0.212 sec)
INFO:tensorflow:global_step/sec: 449.012
INFO:tensorflow:step = 240800, loss = 0.13792126 (0.223 sec)
INFO:tensorflow:global_step/sec: 463.551
INFO:tensorflow:step = 240900, loss = 4.0309334 (0.216 sec)
INFO:tensorflow:global_step/sec: 461.457
INFO:tensorflow:step = 241000, loss = 1.0963851 (0.217 sec)
INFO:tensorflow:global_step/sec: 464.303
INFO:tensorflow:step = 241100, loss = 0.6795362 (0.215 sec)
INFO:tensorflow:global_step/sec: 461.041
INFO:tensorflow:step = 241200, loss = 2.3840325 (0.217 sec)
INFO:tensorflow:global_step/sec: 463.295
INFO:tensorflow:step = 241300, loss = 0.30005962 (0.216 sec)
INFO:tensorflow:global_step/sec: 466.602
INFO:tensorflow:step = 241400, loss = 0.24796128 (0.214 sec)
INFO:tensorflow:global_step/sec: 468.163
INFO:tensorflow:step = 241500, loss = 0.71981144 (0.214 sec)
INFO:tensorflow:global_step/sec: 457.482
INFO:tensorflow:step = 241600, loss = 0.56097335 (0.219 sec)
INFO:tensorflow:global_step/sec: 460.457
INFO:tensorflow:step = 241700, loss = 0.17329887 (0.217 sec)
INFO:tensorflow:global_step/sec: 458.94
INFO:tensorflow:step = 241800, loss = 1.5377414 (0.218 sec)
INFO:tensorflow:global_step/sec: 457.56
INFO:tensorflow:step = 241900, loss = 0.26396322 (0.218 sec)
INFO:tensorflow:global_step/sec: 462.269
INFO:tensorflow:step = 242000, loss = 2.1439018 (0.216 sec)
INFO:tensorflow:global_step/sec: 466.778
INFO:tensorflow:step = 242100, loss = 1.0154365 (0.214 sec)
INFO:tensorflow:global_step/sec: 464.361
INFO:tensorflow:step = 242200, loss = 0.97752154 (0.215 sec)
INFO:tensorflow:global_step/sec: 468.028
INFO:tensorflow:step = 242300, loss = 0.2592151 (0.214 sec)
INFO:tensorflow:global_step/sec: 460.63
INFO:tensorflow:step = 242400, loss = 0.5990661 (0.217 sec)
INFO:tensorflow:global_step/sec: 466.828
INFO:tensorflow:step = 242500, loss = 1.0591576 (0.214 sec)
INFO:tensorflow:global_step/sec: 453.161
INFO:tensorflow:step = 242600, loss = 4.410249 (0.221 sec)
INFO:tensorflow:global_step/sec: 457.532
INFO:tensorflow:step = 242700, loss = 4.481204 (0.220 sec)
INFO:tensorflow:global_step/sec: 460.26
INFO:tensorflow:step = 242800, loss = 1.0023199 (0.216 sec)
INFO:tensorflow:global_step/sec: 467.571
INFO:tensorflow:step = 242900, loss = 0.8825953 (0.214 sec)
INFO:tensorflow:global_step/sec: 469.882
INFO:tensorflow:step = 243000, loss = 0.54299253 (0.213 sec)
INFO:tensorflow:global_step/sec: 460.275
INFO:tensorflow:step = 243100, loss = 2.968597 (0.217 sec)
INFO:tensorflow:global_step/sec: 466.139
INFO:tensorflow:step = 243200, loss = 0.60825086 (0.215 sec)
INFO:tensorflow:global_step/sec: 462.023
INFO:tensorflow:step = 243300, loss = 1.4804775 (0.216 sec)
INFO:tensorflow:global_step/sec: 462.043
INFO:tensorflow:step = 243400, loss = 0.18283819 (0.217 sec)
INFO:tensorflow:global_step/sec: 467.379
INFO:tensorflow:step = 243500, loss = 0.3941102 (0.214 sec)
INFO:tensorflow:global_step/sec: 464.428
INFO:tensorflow:step = 243600, loss = 0.50029624 (0.215 sec)
INFO:tensorflow:global_step/sec: 466.623
INFO:tensorflow:step = 243700, loss = 1.4098248 (0.214 sec)
INFO:tensorflow:global_step/sec: 467.159
INFO:tensorflow:step = 243800, loss = 3.2710886 (0.214 sec)
INFO:tensorflow:global_step/sec: 457.236
INFO:tensorflow:step = 243900, loss = 0.6008466 (0.219 sec)
INFO:tensorflow:global_step/sec: 461.407
INFO:tensorflow:step = 244000, loss = 1.0692052 (0.217 sec)
INFO:tensorflow:global_step/sec: 461.463
INFO:tensorflow:step = 244100, loss = 0.37890404 (0.216 sec)
INFO:tensorflow:global_step/sec: 464.582
INFO:tensorflow:step = 244200, loss = 0.91724914 (0.216 sec)
INFO:tensorflow:global_step/sec: 462.204
INFO:tensorflow:step = 244300, loss = 0.66502696 (0.216 sec)
INFO:tensorflow:global_step/sec: 459.968
INFO:tensorflow:step = 244400, loss = 1.7529447 (0.217 sec)
INFO:tensorflow:global_step/sec: 466.752
INFO:tensorflow:step = 244500, loss = 0.67861927 (0.214 sec)
INFO:tensorflow:global_step/sec: 465.57
INFO:tensorflow:step = 244600, loss = 0.053728607 (0.215 sec)
INFO:tensorflow:global_step/sec: 469.459
INFO:tensorflow:step = 244700, loss = 0.0811224 (0.213 sec)
INFO:tensorflow:global_step/sec: 464.661
INFO:tensorflow:step = 244800, loss = 2.1916742 (0.215 sec)
INFO:tensorflow:global_step/sec: 467.032
INFO:tensorflow:step = 244900, loss = 0.19149438 (0.214 sec)
INFO:tensorflow:global_step/sec: 459.672
INFO:tensorflow:step = 245000, loss = 0.5939156 (0.218 sec)
INFO:tensorflow:global_step/sec: 462.888
INFO:tensorflow:step = 245100, loss = 1.430043 (0.216 sec)
INFO:tensorflow:global_step/sec: 467.64
INFO:tensorflow:step = 245200, loss = 0.05944563 (0.214 sec)
INFO:tensorflow:global_step/sec: 461.519
INFO:tensorflow:step = 245300, loss = 1.5213947 (0.217 sec)
INFO:tensorflow:global_step/sec: 460.268
INFO:tensorflow:step = 245400, loss = 2.2781055 (0.217 sec)
INFO:tensorflow:global_step/sec: 469.498
INFO:tensorflow:step = 245500, loss = 0.071664944 (0.213 sec)
INFO:tensorflow:global_step/sec: 466.52
INFO:tensorflow:step = 245600, loss = 0.7583659 (0.214 sec)
INFO:tensorflow:global_step/sec: 460.683
INFO:tensorflow:step = 245700, loss = 2.1823523 (0.218 sec)
INFO:tensorflow:global_step/sec: 457.451
INFO:tensorflow:step = 245800, loss = 2.7986314 (0.217 sec)
INFO:tensorflow:global_step/sec: 463.782
INFO:tensorflow:step = 245900, loss = 1.3610001 (0.215 sec)
INFO:tensorflow:global_step/sec: 469.02
INFO:tensorflow:step = 246000, loss = 2.0809925 (0.213 sec)
INFO:tensorflow:global_step/sec: 465.954
INFO:tensorflow:step = 246100, loss = 2.1979764 (0.215 sec)
INFO:tensorflow:global_step/sec: 460.478
INFO:tensorflow:step = 246200, loss = 4.535287 (0.217 sec)
INFO:tensorflow:global_step/sec: 460.55
INFO:tensorflow:step = 246300, loss = 0.93364966 (0.217 sec)
INFO:tensorflow:global_step/sec: 460.303
INFO:tensorflow:step = 246400, loss = 1.1112924 (0.217 sec)
INFO:tensorflow:global_step/sec: 461.26
INFO:tensorflow:step = 246500, loss = 0.30066428 (0.217 sec)
INFO:tensorflow:global_step/sec: 466.838
INFO:tensorflow:step = 246600, loss = 4.576683 (0.214 sec)
INFO:tensorflow:global_step/sec: 457.951
INFO:tensorflow:step = 246700, loss = 0.5156861 (0.219 sec)
INFO:tensorflow:global_step/sec: 459.756
INFO:tensorflow:step = 246800, loss = 0.27368653 (0.217 sec)
INFO:tensorflow:global_step/sec: 457.014
INFO:tensorflow:step = 246900, loss = 4.6331964 (0.219 sec)
INFO:tensorflow:global_step/sec: 457.268
INFO:tensorflow:step = 247000, loss = 0.53216815 (0.219 sec)
INFO:tensorflow:global_step/sec: 457.317
INFO:tensorflow:step = 247100, loss = 0.5635681 (0.219 sec)
INFO:tensorflow:global_step/sec: 456.425
INFO:tensorflow:step = 247200, loss = 0.72183704 (0.220 sec)
INFO:tensorflow:global_step/sec: 452.574
INFO:tensorflow:step = 247300, loss = 2.9004345 (0.220 sec)
INFO:tensorflow:global_step/sec: 461.895
INFO:tensorflow:step = 247400, loss = 0.1744974 (0.216 sec)
INFO:tensorflow:global_step/sec: 466.631
INFO:tensorflow:step = 247500, loss = 0.13641433 (0.214 sec)
INFO:tensorflow:global_step/sec: 461.58
INFO:tensorflow:step = 247600, loss = 0.5580989 (0.216 sec)
INFO:tensorflow:global_step/sec: 471.928
INFO:tensorflow:step = 247700, loss = 3.2571013 (0.212 sec)
INFO:tensorflow:global_step/sec: 466.842
INFO:tensorflow:step = 247800, loss = 0.25001162 (0.214 sec)
INFO:tensorflow:global_step/sec: 465.828
INFO:tensorflow:step = 247900, loss = 0.29120484 (0.215 sec)
INFO:tensorflow:global_step/sec: 465.827
INFO:tensorflow:step = 248000, loss = 0.89329183 (0.215 sec)
INFO:tensorflow:global_step/sec: 450.448
INFO:tensorflow:step = 248100, loss = 1.2630398 (0.222 sec)
INFO:tensorflow:global_step/sec: 460.922
INFO:tensorflow:step = 248200, loss = 0.9461041 (0.217 sec)
INFO:tensorflow:global_step/sec: 465.86
INFO:tensorflow:step = 248300, loss = 8.313844 (0.215 sec)
INFO:tensorflow:global_step/sec: 454.615
INFO:tensorflow:step = 248400, loss = 0.33889332 (0.220 sec)
INFO:tensorflow:global_step/sec: 465.16
INFO:tensorflow:step = 248500, loss = 0.2877738 (0.215 sec)
INFO:tensorflow:global_step/sec: 457.016
INFO:tensorflow:step = 248600, loss = 0.9398958 (0.219 sec)
INFO:tensorflow:global_step/sec: 468.542
INFO:tensorflow:step = 248700, loss = 0.29390156 (0.213 sec)
INFO:tensorflow:global_step/sec: 467.683
INFO:tensorflow:step = 248800, loss = 3.6963603 (0.214 sec)
INFO:tensorflow:global_step/sec: 471.672
INFO:tensorflow:step = 248900, loss = 0.3925845 (0.212 sec)
INFO:tensorflow:global_step/sec: 472.222
INFO:tensorflow:step = 249000, loss = 1.785097 (0.212 sec)
INFO:tensorflow:global_step/sec: 457.384
INFO:tensorflow:step = 249100, loss = 0.21868339 (0.219 sec)
INFO:tensorflow:global_step/sec: 465.534
INFO:tensorflow:step = 249200, loss = 1.5309972 (0.215 sec)
INFO:tensorflow:global_step/sec: 462.71
INFO:tensorflow:step = 249300, loss = 0.8501617 (0.216 sec)
INFO:tensorflow:global_step/sec: 468.251
INFO:tensorflow:step = 249400, loss = 1.9982628 (0.213 sec)
INFO:tensorflow:global_step/sec: 459.705
INFO:tensorflow:step = 249500, loss = 0.55241203 (0.218 sec)
INFO:tensorflow:global_step/sec: 456.157
INFO:tensorflow:step = 249600, loss = 0.45502418 (0.219 sec)
INFO:tensorflow:global_step/sec: 459.172
INFO:tensorflow:step = 249700, loss = 1.1718221 (0.218 sec)
INFO:tensorflow:global_step/sec: 462.953
INFO:tensorflow:step = 249800, loss = 1.2556643 (0.216 sec)
INFO:tensorflow:global_step/sec: 463.881
INFO:tensorflow:step = 249900, loss = 2.0843346 (0.216 sec)
INFO:tensorflow:global_step/sec: 465.623
INFO:tensorflow:step = 250000, loss = 1.2226229 (0.215 sec)
INFO:tensorflow:global_step/sec: 464.713
INFO:tensorflow:step = 250100, loss = 1.7107219 (0.215 sec)
INFO:tensorflow:global_step/sec: 468.386
INFO:tensorflow:step = 250200, loss = 2.5498307 (0.213 sec)
INFO:tensorflow:global_step/sec: 473.769
INFO:tensorflow:step = 250300, loss = 1.0188375 (0.211 sec)
INFO:tensorflow:global_step/sec: 463.304
INFO:tensorflow:step = 250400, loss = 1.9441651 (0.216 sec)
INFO:tensorflow:global_step/sec: 460.546
INFO:tensorflow:step = 250500, loss = 2.460581 (0.217 sec)
INFO:tensorflow:global_step/sec: 470.276
INFO:tensorflow:step = 250600, loss = 0.6094702 (0.212 sec)
INFO:tensorflow:global_step/sec: 463.55
INFO:tensorflow:step = 250700, loss = 0.15865341 (0.216 sec)
INFO:tensorflow:global_step/sec: 469.717
INFO:tensorflow:step = 250800, loss = 0.7618376 (0.213 sec)
INFO:tensorflow:global_step/sec: 465.193
INFO:tensorflow:step = 250900, loss = 0.37422425 (0.215 sec)
INFO:tensorflow:global_step/sec: 466.634
INFO:tensorflow:step = 251000, loss = 0.22197464 (0.216 sec)
INFO:tensorflow:global_step/sec: 457.749
INFO:tensorflow:step = 251100, loss = 2.0787501 (0.217 sec)
INFO:tensorflow:global_step/sec: 467.401
INFO:tensorflow:step = 251200, loss = 1.5849631 (0.214 sec)
INFO:tensorflow:global_step/sec: 464.728
INFO:tensorflow:step = 251300, loss = 0.35416776 (0.215 sec)
INFO:tensorflow:global_step/sec: 461.46
INFO:tensorflow:step = 251400, loss = 0.707073 (0.217 sec)
INFO:tensorflow:global_step/sec: 458.592
INFO:tensorflow:step = 251500, loss = 0.18219602 (0.218 sec)
INFO:tensorflow:global_step/sec: 465.392
INFO:tensorflow:step = 251600, loss = 1.0395368 (0.216 sec)
INFO:tensorflow:global_step/sec: 468.683
INFO:tensorflow:step = 251700, loss = 0.9763887 (0.212 sec)
INFO:tensorflow:global_step/sec: 464.856
INFO:tensorflow:step = 251800, loss = 4.7100735 (0.215 sec)
INFO:tensorflow:global_step/sec: 451.398
INFO:tensorflow:step = 251900, loss = 0.63899064 (0.221 sec)
INFO:tensorflow:global_step/sec: 463.822
INFO:tensorflow:step = 252000, loss = 0.4983093 (0.216 sec)
INFO:tensorflow:global_step/sec: 471.973
INFO:tensorflow:step = 252100, loss = 1.0293198 (0.212 sec)
INFO:tensorflow:global_step/sec: 465.296
INFO:tensorflow:step = 252200, loss = 1.6595874 (0.215 sec)
INFO:tensorflow:global_step/sec: 461.126
INFO:tensorflow:step = 252300, loss = 0.42467347 (0.217 sec)
INFO:tensorflow:global_step/sec: 466.498
INFO:tensorflow:step = 252400, loss = 3.3486454 (0.214 sec)
INFO:tensorflow:global_step/sec: 458.842
INFO:tensorflow:step = 252500, loss = 0.88263977 (0.218 sec)
INFO:tensorflow:global_step/sec: 469.942
INFO:tensorflow:step = 252600, loss = 2.2187479 (0.213 sec)
INFO:tensorflow:global_step/sec: 466.372
INFO:tensorflow:step = 252700, loss = 0.43561885 (0.215 sec)
INFO:tensorflow:global_step/sec: 467.127
INFO:tensorflow:step = 252800, loss = 0.5818982 (0.214 sec)
INFO:tensorflow:global_step/sec: 468.41
INFO:tensorflow:step = 252900, loss = 0.21272698 (0.213 sec)
INFO:tensorflow:global_step/sec: 461.903
INFO:tensorflow:step = 253000, loss = 0.08500454 (0.216 sec)
INFO:tensorflow:global_step/sec: 472.283
INFO:tensorflow:step = 253100, loss = 1.0540165 (0.212 sec)
INFO:tensorflow:global_step/sec: 466.443
INFO:tensorflow:step = 253200, loss = 3.759421 (0.214 sec)
INFO:tensorflow:global_step/sec: 466.471
INFO:tensorflow:step = 253300, loss = 0.38023555 (0.214 sec)
INFO:tensorflow:global_step/sec: 458.276
INFO:tensorflow:step = 253400, loss = 0.30077913 (0.218 sec)
INFO:tensorflow:global_step/sec: 464.104
INFO:tensorflow:step = 253500, loss = 0.6484309 (0.215 sec)
INFO:tensorflow:global_step/sec: 475.055
INFO:tensorflow:step = 253600, loss = 0.14018467 (0.211 sec)
INFO:tensorflow:global_step/sec: 449.004
INFO:tensorflow:step = 253700, loss = 0.18149064 (0.222 sec)
INFO:tensorflow:global_step/sec: 462.189
INFO:tensorflow:step = 253800, loss = 2.268966 (0.217 sec)
INFO:tensorflow:global_step/sec: 459.146
INFO:tensorflow:step = 253900, loss = 0.84710413 (0.217 sec)
INFO:tensorflow:global_step/sec: 443.689
INFO:tensorflow:step = 254000, loss = 0.088886596 (0.225 sec)
INFO:tensorflow:global_step/sec: 459.476
INFO:tensorflow:step = 254100, loss = 2.892403 (0.218 sec)
INFO:tensorflow:global_step/sec: 439.336
INFO:tensorflow:step = 254200, loss = 1.2323366 (0.228 sec)
INFO:tensorflow:global_step/sec: 445.919
INFO:tensorflow:step = 254300, loss = 1.5933855 (0.224 sec)
INFO:tensorflow:global_step/sec: 454.089
INFO:tensorflow:step = 254400, loss = 1.7306885 (0.220 sec)
INFO:tensorflow:global_step/sec: 453.623
INFO:tensorflow:step = 254500, loss = 0.020230714 (0.220 sec)
INFO:tensorflow:global_step/sec: 455.676
INFO:tensorflow:step = 254600, loss = 3.6723652 (0.220 sec)
INFO:tensorflow:global_step/sec: 456.871
INFO:tensorflow:step = 254700, loss = 3.3225489 (0.219 sec)
INFO:tensorflow:global_step/sec: 452.71
INFO:tensorflow:step = 254800, loss = 0.15858093 (0.221 sec)
INFO:tensorflow:global_step/sec: 454.015
INFO:tensorflow:step = 254900, loss = 0.24682271 (0.220 sec)
INFO:tensorflow:global_step/sec: 453.932
INFO:tensorflow:step = 255000, loss = 0.7000899 (0.220 sec)
INFO:tensorflow:global_step/sec: 458.284
INFO:tensorflow:step = 255100, loss = 0.1831062 (0.218 sec)
INFO:tensorflow:global_step/sec: 458.892
INFO:tensorflow:step = 255200, loss = 0.96875906 (0.218 sec)
INFO:tensorflow:global_step/sec: 463.076
INFO:tensorflow:step = 255300, loss = 0.4805606 (0.216 sec)
INFO:tensorflow:global_step/sec: 469.401
INFO:tensorflow:step = 255400, loss = 1.957561 (0.213 sec)
INFO:tensorflow:global_step/sec: 461.132
INFO:tensorflow:step = 255500, loss = 0.16102068 (0.217 sec)
INFO:tensorflow:global_step/sec: 459.733
INFO:tensorflow:step = 255600, loss = 0.7170687 (0.218 sec)
INFO:tensorflow:global_step/sec: 465.574
INFO:tensorflow:step = 255700, loss = 8.04015 (0.215 sec)
INFO:tensorflow:global_step/sec: 454.715
INFO:tensorflow:step = 255800, loss = 1.2149708 (0.220 sec)
INFO:tensorflow:global_step/sec: 473.623
INFO:tensorflow:step = 255900, loss = 0.14055695 (0.212 sec)
INFO:tensorflow:global_step/sec: 462.132
INFO:tensorflow:step = 256000, loss = 0.56406593 (0.216 sec)
INFO:tensorflow:global_step/sec: 450.344
INFO:tensorflow:step = 256100, loss = 0.26694602 (0.222 sec)
INFO:tensorflow:global_step/sec: 469.988
INFO:tensorflow:step = 256200, loss = 0.9735346 (0.213 sec)
INFO:tensorflow:global_step/sec: 465.616
INFO:tensorflow:step = 256300, loss = 0.119019076 (0.215 sec)
INFO:tensorflow:global_step/sec: 461.689
INFO:tensorflow:step = 256400, loss = 1.6542263 (0.217 sec)
INFO:tensorflow:global_step/sec: 468.374
INFO:tensorflow:step = 256500, loss = 2.7338896 (0.214 sec)
INFO:tensorflow:global_step/sec: 464.851
INFO:tensorflow:step = 256600, loss = 0.26121622 (0.215 sec)
INFO:tensorflow:global_step/sec: 469.128
INFO:tensorflow:step = 256700, loss = 0.85864985 (0.213 sec)
INFO:tensorflow:global_step/sec: 468.127
INFO:tensorflow:step = 256800, loss = 1.2947443 (0.214 sec)
INFO:tensorflow:global_step/sec: 466.461
INFO:tensorflow:step = 256900, loss = 0.021219011 (0.214 sec)
INFO:tensorflow:global_step/sec: 462.552
INFO:tensorflow:step = 257000, loss = 0.27189916 (0.216 sec)
INFO:tensorflow:global_step/sec: 460.146
INFO:tensorflow:step = 257100, loss = 4.423374 (0.218 sec)
INFO:tensorflow:global_step/sec: 467.427
INFO:tensorflow:step = 257200, loss = 0.23317502 (0.214 sec)
INFO:tensorflow:global_step/sec: 463.104
INFO:tensorflow:step = 257300, loss = 0.44950664 (0.216 sec)
INFO:tensorflow:global_step/sec: 462.551
INFO:tensorflow:step = 257400, loss = 2.3689444 (0.216 sec)
INFO:tensorflow:global_step/sec: 464.437
INFO:tensorflow:step = 257500, loss = 4.616068 (0.215 sec)
INFO:tensorflow:global_step/sec: 470.782
INFO:tensorflow:step = 257600, loss = 0.15548174 (0.213 sec)
INFO:tensorflow:global_step/sec: 461.253
INFO:tensorflow:step = 257700, loss = 0.17047985 (0.217 sec)
INFO:tensorflow:global_step/sec: 463.71
INFO:tensorflow:step = 257800, loss = 1.7033081 (0.216 sec)
INFO:tensorflow:global_step/sec: 461.833
INFO:tensorflow:step = 257900, loss = 0.10091227 (0.216 sec)
INFO:tensorflow:global_step/sec: 464.955
INFO:tensorflow:step = 258000, loss = 0.16724205 (0.217 sec)
INFO:tensorflow:global_step/sec: 454.757
INFO:tensorflow:step = 258100, loss = 0.7766413 (0.219 sec)
INFO:tensorflow:global_step/sec: 463.746
INFO:tensorflow:step = 258200, loss = 1.2370403 (0.216 sec)
INFO:tensorflow:global_step/sec: 454.321
INFO:tensorflow:step = 258300, loss = 1.14797 (0.220 sec)
INFO:tensorflow:global_step/sec: 468.271
INFO:tensorflow:step = 258400, loss = 0.44415087 (0.213 sec)
INFO:tensorflow:global_step/sec: 468.042
INFO:tensorflow:step = 258500, loss = 6.247117 (0.214 sec)
INFO:tensorflow:global_step/sec: 471.507
INFO:tensorflow:step = 258600, loss = 0.6436235 (0.212 sec)
INFO:tensorflow:global_step/sec: 471.955
INFO:tensorflow:step = 258700, loss = 1.1043876 (0.212 sec)
INFO:tensorflow:global_step/sec: 469.002
INFO:tensorflow:step = 258800, loss = 0.10249841 (0.214 sec)
INFO:tensorflow:global_step/sec: 458.452
INFO:tensorflow:step = 258900, loss = 0.4659457 (0.218 sec)
INFO:tensorflow:global_step/sec: 463.773
INFO:tensorflow:step = 259000, loss = 2.4896796 (0.216 sec)
INFO:tensorflow:global_step/sec: 470.343
INFO:tensorflow:step = 259100, loss = 0.8691821 (0.213 sec)
INFO:tensorflow:global_step/sec: 470.811
INFO:tensorflow:step = 259200, loss = 3.3410316 (0.213 sec)
INFO:tensorflow:global_step/sec: 458.039
INFO:tensorflow:step = 259300, loss = 0.32278562 (0.218 sec)
INFO:tensorflow:global_step/sec: 457.615
INFO:tensorflow:step = 259400, loss = 1.0513127 (0.219 sec)
INFO:tensorflow:global_step/sec: 461.281
INFO:tensorflow:step = 259500, loss = 0.44731012 (0.217 sec)
INFO:tensorflow:global_step/sec: 471.37
INFO:tensorflow:step = 259600, loss = 1.2898655 (0.212 sec)
INFO:tensorflow:global_step/sec: 469.806
INFO:tensorflow:step = 259700, loss = 0.12969583 (0.213 sec)
INFO:tensorflow:global_step/sec: 470.622
INFO:tensorflow:step = 259800, loss = 2.8033278 (0.213 sec)
INFO:tensorflow:global_step/sec: 461.513
INFO:tensorflow:step = 259900, loss = 0.8608284 (0.216 sec)
INFO:tensorflow:global_step/sec: 467.948
INFO:tensorflow:step = 260000, loss = 0.5881908 (0.214 sec)
INFO:tensorflow:global_step/sec: 470.781
INFO:tensorflow:step = 260100, loss = 0.57916653 (0.212 sec)
INFO:tensorflow:global_step/sec: 467.298
INFO:tensorflow:step = 260200, loss = 4.8259296 (0.214 sec)
INFO:tensorflow:global_step/sec: 461.66
INFO:tensorflow:step = 260300, loss = 0.18299812 (0.217 sec)
INFO:tensorflow:global_step/sec: 464.263
INFO:tensorflow:step = 260400, loss = 0.045551986 (0.215 sec)
INFO:tensorflow:global_step/sec: 466.478
INFO:tensorflow:step = 260500, loss = 0.5096746 (0.214 sec)
INFO:tensorflow:global_step/sec: 456.231
INFO:tensorflow:step = 260600, loss = 0.7376305 (0.220 sec)
INFO:tensorflow:global_step/sec: 467.562
INFO:tensorflow:step = 260700, loss = 1.024693 (0.214 sec)
INFO:tensorflow:global_step/sec: 469.293
INFO:tensorflow:step = 260800, loss = 1.9741486 (0.213 sec)
INFO:tensorflow:global_step/sec: 468.295
INFO:tensorflow:step = 260900, loss = 0.45637232 (0.213 sec)
INFO:tensorflow:global_step/sec: 471.419
INFO:tensorflow:step = 261000, loss = 0.10452688 (0.212 sec)
INFO:tensorflow:global_step/sec: 454.799
INFO:tensorflow:step = 261100, loss = 1.6227154 (0.220 sec)
INFO:tensorflow:global_step/sec: 464.507
INFO:tensorflow:step = 261200, loss = 0.13677248 (0.215 sec)
INFO:tensorflow:global_step/sec: 464.878
INFO:tensorflow:step = 261300, loss = 0.5964668 (0.215 sec)
INFO:tensorflow:global_step/sec: 466.074
INFO:tensorflow:step = 261400, loss = 1.4011662 (0.215 sec)
INFO:tensorflow:global_step/sec: 466.368
INFO:tensorflow:step = 261500, loss = 7.334218 (0.214 sec)
INFO:tensorflow:global_step/sec: 458.683
INFO:tensorflow:step = 261600, loss = 2.3328223 (0.218 sec)
INFO:tensorflow:global_step/sec: 465.416
INFO:tensorflow:step = 261700, loss = 0.829334 (0.215 sec)
INFO:tensorflow:global_step/sec: 459.737
INFO:tensorflow:step = 261800, loss = 0.4422386 (0.218 sec)
INFO:tensorflow:global_step/sec: 464.401
INFO:tensorflow:step = 261900, loss = 0.16085054 (0.215 sec)
INFO:tensorflow:global_step/sec: 468.089
INFO:tensorflow:step = 262000, loss = 2.6209164 (0.214 sec)
INFO:tensorflow:global_step/sec: 462.624
INFO:tensorflow:step = 262100, loss = 1.7513745 (0.216 sec)
INFO:tensorflow:global_step/sec: 457.203
INFO:tensorflow:step = 262200, loss = 0.6736344 (0.219 sec)
INFO:tensorflow:global_step/sec: 462.545
INFO:tensorflow:step = 262300, loss = 0.6399909 (0.216 sec)
INFO:tensorflow:global_step/sec: 471.513
INFO:tensorflow:step = 262400, loss = 1.1860476 (0.212 sec)
INFO:tensorflow:global_step/sec: 461.349
INFO:tensorflow:step = 262500, loss = 0.72913873 (0.217 sec)
INFO:tensorflow:global_step/sec: 458.94
INFO:tensorflow:step = 262600, loss = 0.10025199 (0.218 sec)
INFO:tensorflow:global_step/sec: 463.183
INFO:tensorflow:step = 262700, loss = 1.3801582 (0.216 sec)
INFO:tensorflow:global_step/sec: 469.97
INFO:tensorflow:step = 262800, loss = 0.12263126 (0.213 sec)
INFO:tensorflow:global_step/sec: 468.648
INFO:tensorflow:step = 262900, loss = 4.035146 (0.214 sec)
INFO:tensorflow:global_step/sec: 456.743
INFO:tensorflow:step = 263000, loss = 0.30159009 (0.219 sec)
INFO:tensorflow:global_step/sec: 456.966
INFO:tensorflow:step = 263100, loss = 0.48766902 (0.220 sec)
INFO:tensorflow:global_step/sec: 455.952
INFO:tensorflow:step = 263200, loss = 0.6503994 (0.218 sec)
INFO:tensorflow:global_step/sec: 460.338
INFO:tensorflow:step = 263300, loss = 0.5629767 (0.217 sec)
INFO:tensorflow:global_step/sec: 463.531
INFO:tensorflow:step = 263400, loss = 3.0712261 (0.216 sec)
INFO:tensorflow:global_step/sec: 465.141
INFO:tensorflow:step = 263500, loss = 2.818836 (0.215 sec)
INFO:tensorflow:global_step/sec: 462.081
INFO:tensorflow:step = 263600, loss = 0.5570686 (0.216 sec)
INFO:tensorflow:global_step/sec: 460.309
INFO:tensorflow:step = 263700, loss = 3.8713388 (0.218 sec)
INFO:tensorflow:global_step/sec: 471.157
INFO:tensorflow:step = 263800, loss = 0.13704875 (0.212 sec)
INFO:tensorflow:global_step/sec: 461.498
INFO:tensorflow:step = 263900, loss = 0.21216775 (0.217 sec)
INFO:tensorflow:global_step/sec: 463.794
INFO:tensorflow:step = 264000, loss = 0.16177116 (0.215 sec)
INFO:tensorflow:global_step/sec: 457.471
INFO:tensorflow:step = 264100, loss = 0.2181692 (0.218 sec)
INFO:tensorflow:global_step/sec: 469.663
INFO:tensorflow:step = 264200, loss = 2.6830437 (0.213 sec)
INFO:tensorflow:global_step/sec: 471.775
INFO:tensorflow:step = 264300, loss = 0.35194945 (0.212 sec)
INFO:tensorflow:global_step/sec: 460.043
INFO:tensorflow:step = 264400, loss = 3.1770892 (0.217 sec)
INFO:tensorflow:global_step/sec: 458.726
INFO:tensorflow:step = 264500, loss = 1.220999 (0.218 sec)
INFO:tensorflow:global_step/sec: 467.827
INFO:tensorflow:step = 264600, loss = 0.38105056 (0.214 sec)
INFO:tensorflow:global_step/sec: 468.078
INFO:tensorflow:step = 264700, loss = 1.840487 (0.214 sec)
INFO:tensorflow:global_step/sec: 455.92
INFO:tensorflow:step = 264800, loss = 0.2513899 (0.219 sec)
INFO:tensorflow:global_step/sec: 468.124
INFO:tensorflow:step = 264900, loss = 2.945358 (0.214 sec)
INFO:tensorflow:global_step/sec: 466.818
INFO:tensorflow:step = 265000, loss = 0.080511846 (0.214 sec)
INFO:tensorflow:global_step/sec: 460.502
INFO:tensorflow:step = 265100, loss = 1.2173613 (0.217 sec)
INFO:tensorflow:global_step/sec: 477.449
INFO:tensorflow:step = 265200, loss = 0.29684106 (0.210 sec)
INFO:tensorflow:global_step/sec: 458.678
INFO:tensorflow:step = 265300, loss = 6.8422265 (0.218 sec)
INFO:tensorflow:global_step/sec: 449.97
INFO:tensorflow:step = 265400, loss = 1.0363463 (0.222 sec)
INFO:tensorflow:global_step/sec: 444.553
INFO:tensorflow:step = 265500, loss = 0.5470272 (0.225 sec)
INFO:tensorflow:global_step/sec: 459.296
INFO:tensorflow:step = 265600, loss = 2.7666159 (0.218 sec)
INFO:tensorflow:global_step/sec: 475.208
INFO:tensorflow:step = 265700, loss = 0.20006 (0.211 sec)
INFO:tensorflow:global_step/sec: 462.829
INFO:tensorflow:step = 265800, loss = 0.60243857 (0.216 sec)
INFO:tensorflow:global_step/sec: 461.353
INFO:tensorflow:step = 265900, loss = 1.0802892 (0.217 sec)
INFO:tensorflow:global_step/sec: 456.807
INFO:tensorflow:step = 266000, loss = 0.052432664 (0.219 sec)
INFO:tensorflow:global_step/sec: 473.254
INFO:tensorflow:step = 266100, loss = 0.12038606 (0.211 sec)
INFO:tensorflow:global_step/sec: 473.408
INFO:tensorflow:step = 266200, loss = 0.35974807 (0.212 sec)
INFO:tensorflow:global_step/sec: 466.677
INFO:tensorflow:step = 266300, loss = 0.79025537 (0.214 sec)
INFO:tensorflow:global_step/sec: 460.96
INFO:tensorflow:step = 266400, loss = 0.9692792 (0.217 sec)
INFO:tensorflow:global_step/sec: 472.758
INFO:tensorflow:step = 266500, loss = 0.53894794 (0.212 sec)
INFO:tensorflow:global_step/sec: 467.035
INFO:tensorflow:step = 266600, loss = 0.2129329 (0.214 sec)
INFO:tensorflow:global_step/sec: 456.987
INFO:tensorflow:step = 266700, loss = 0.07537304 (0.219 sec)
INFO:tensorflow:global_step/sec: 456.418
INFO:tensorflow:step = 266800, loss = 0.22306618 (0.219 sec)
INFO:tensorflow:global_step/sec: 453.285
INFO:tensorflow:step = 266900, loss = 0.9553504 (0.220 sec)
INFO:tensorflow:global_step/sec: 466.635
INFO:tensorflow:step = 267000, loss = 0.06414246 (0.214 sec)
INFO:tensorflow:global_step/sec: 464.673
INFO:tensorflow:step = 267100, loss = 0.4327541 (0.215 sec)
INFO:tensorflow:global_step/sec: 471.534
INFO:tensorflow:step = 267200, loss = 1.8091887 (0.212 sec)
INFO:tensorflow:global_step/sec: 462.784
INFO:tensorflow:step = 267300, loss = 0.34038475 (0.216 sec)
INFO:tensorflow:global_step/sec: 469.846
INFO:tensorflow:step = 267400, loss = 0.28149322 (0.213 sec)
INFO:tensorflow:global_step/sec: 470.47
INFO:tensorflow:step = 267500, loss = 0.5153234 (0.214 sec)
INFO:tensorflow:global_step/sec: 460.227
INFO:tensorflow:step = 267600, loss = 0.538492 (0.216 sec)
INFO:tensorflow:global_step/sec: 458.562
INFO:tensorflow:step = 267700, loss = 0.8684747 (0.218 sec)
INFO:tensorflow:global_step/sec: 467.401
INFO:tensorflow:step = 267800, loss = 0.090736 (0.214 sec)
INFO:tensorflow:global_step/sec: 473.171
INFO:tensorflow:step = 267900, loss = 0.09490872 (0.212 sec)
INFO:tensorflow:global_step/sec: 465.793
INFO:tensorflow:step = 268000, loss = 0.8801706 (0.215 sec)
INFO:tensorflow:global_step/sec: 461.912
INFO:tensorflow:step = 268100, loss = 2.9683084 (0.216 sec)
INFO:tensorflow:global_step/sec: 467.188
INFO:tensorflow:step = 268200, loss = 4.0795074 (0.214 sec)
INFO:tensorflow:global_step/sec: 466.263
INFO:tensorflow:step = 268300, loss = 0.13467151 (0.215 sec)
INFO:tensorflow:global_step/sec: 459.33
INFO:tensorflow:step = 268400, loss = 2.4207988 (0.218 sec)
INFO:tensorflow:global_step/sec: 467.36
INFO:tensorflow:step = 268500, loss = 0.51818746 (0.214 sec)
INFO:tensorflow:global_step/sec: 468.589
INFO:tensorflow:step = 268600, loss = 0.57434064 (0.213 sec)
INFO:tensorflow:global_step/sec: 462.375
INFO:tensorflow:step = 268700, loss = 2.2291064 (0.216 sec)
INFO:tensorflow:global_step/sec: 462.44
INFO:tensorflow:step = 268800, loss = 0.21683726 (0.216 sec)
INFO:tensorflow:global_step/sec: 461.091
INFO:tensorflow:step = 268900, loss = 0.116345964 (0.219 sec)
INFO:tensorflow:global_step/sec: 455.554
INFO:tensorflow:step = 269000, loss = 2.535994 (0.218 sec)
INFO:tensorflow:global_step/sec: 465.704
INFO:tensorflow:step = 269100, loss = 1.0111411 (0.214 sec)
INFO:tensorflow:global_step/sec: 466.424
INFO:tensorflow:step = 269200, loss = 0.10083568 (0.216 sec)
INFO:tensorflow:global_step/sec: 462.104
INFO:tensorflow:step = 269300, loss = 0.8752371 (0.215 sec)
INFO:tensorflow:global_step/sec: 467.035
INFO:tensorflow:step = 269400, loss = 0.2923449 (0.216 sec)
INFO:tensorflow:global_step/sec: 454.086
INFO:tensorflow:step = 269500, loss = 0.25274205 (0.218 sec)
INFO:tensorflow:global_step/sec: 466.471
INFO:tensorflow:step = 269600, loss = 3.954739 (0.215 sec)
INFO:tensorflow:global_step/sec: 461.316
INFO:tensorflow:step = 269700, loss = 0.37631977 (0.217 sec)
INFO:tensorflow:global_step/sec: 457.202
INFO:tensorflow:step = 269800, loss = 3.6293554 (0.219 sec)
INFO:tensorflow:global_step/sec: 465.736
INFO:tensorflow:step = 269900, loss = 0.7284784 (0.215 sec)
INFO:tensorflow:global_step/sec: 460.333
INFO:tensorflow:step = 270000, loss = 2.3669558 (0.217 sec)
INFO:tensorflow:global_step/sec: 466.007
INFO:tensorflow:step = 270100, loss = 3.717673 (0.215 sec)
INFO:tensorflow:global_step/sec: 471.912
INFO:tensorflow:step = 270200, loss = 0.28021348 (0.212 sec)
INFO:tensorflow:global_step/sec: 474.981
INFO:tensorflow:step = 270300, loss = 1.8404846 (0.211 sec)
INFO:tensorflow:global_step/sec: 460.217
INFO:tensorflow:step = 270400, loss = 1.0084732 (0.217 sec)
INFO:tensorflow:global_step/sec: 459.904
INFO:tensorflow:step = 270500, loss = 1.0318731 (0.218 sec)
INFO:tensorflow:global_step/sec: 463.056
INFO:tensorflow:step = 270600, loss = 1.3568155 (0.216 sec)
INFO:tensorflow:global_step/sec: 478.724
INFO:tensorflow:step = 270700, loss = 0.76607805 (0.209 sec)
INFO:tensorflow:global_step/sec: 469.245
INFO:tensorflow:step = 270800, loss = 0.27208716 (0.213 sec)
INFO:tensorflow:global_step/sec: 471.273
INFO:tensorflow:step = 270900, loss = 0.13203846 (0.212 sec)
INFO:tensorflow:global_step/sec: 460.296
INFO:tensorflow:step = 271000, loss = 0.56258816 (0.217 sec)
INFO:tensorflow:global_step/sec: 467.56
INFO:tensorflow:step = 271100, loss = 3.2982163 (0.214 sec)
INFO:tensorflow:global_step/sec: 472.336
INFO:tensorflow:step = 271200, loss = 1.038218 (0.212 sec)
INFO:tensorflow:global_step/sec: 470.232
INFO:tensorflow:step = 271300, loss = 0.16942139 (0.213 sec)
INFO:tensorflow:global_step/sec: 460.034
INFO:tensorflow:step = 271400, loss = 0.39259607 (0.217 sec)
INFO:tensorflow:global_step/sec: 465.73
INFO:tensorflow:step = 271500, loss = 2.1608768 (0.215 sec)
INFO:tensorflow:global_step/sec: 479.636
INFO:tensorflow:step = 271600, loss = 0.24528761 (0.209 sec)
INFO:tensorflow:global_step/sec: 485.563
INFO:tensorflow:step = 271700, loss = 1.3524206 (0.206 sec)
INFO:tensorflow:global_step/sec: 487.753
INFO:tensorflow:step = 271800, loss = 0.4585328 (0.205 sec)
INFO:tensorflow:global_step/sec: 480.459
INFO:tensorflow:step = 271900, loss = 1.2855403 (0.208 sec)
INFO:tensorflow:global_step/sec: 476.886
INFO:tensorflow:step = 272000, loss = 0.15671113 (0.210 sec)
INFO:tensorflow:global_step/sec: 484.076
INFO:tensorflow:step = 272100, loss = 0.12430384 (0.206 sec)
INFO:tensorflow:global_step/sec: 492.172
INFO:tensorflow:step = 272200, loss = 0.25717106 (0.203 sec)
INFO:tensorflow:global_step/sec: 480.543
INFO:tensorflow:step = 272300, loss = 1.0357486 (0.208 sec)
INFO:tensorflow:global_step/sec: 479.042
INFO:tensorflow:step = 272400, loss = 0.33807844 (0.209 sec)
INFO:tensorflow:global_step/sec: 482.426
INFO:tensorflow:step = 272500, loss = 1.534416 (0.207 sec)
INFO:tensorflow:global_step/sec: 490.549
INFO:tensorflow:step = 272600, loss = 3.6757264 (0.204 sec)
INFO:tensorflow:global_step/sec: 480.989
INFO:tensorflow:step = 272700, loss = 1.2144866 (0.208 sec)
INFO:tensorflow:global_step/sec: 490.492
INFO:tensorflow:step = 272800, loss = 0.4842405 (0.204 sec)
INFO:tensorflow:global_step/sec: 484.135
INFO:tensorflow:step = 272900, loss = 0.24914938 (0.206 sec)
INFO:tensorflow:global_step/sec: 487.967
INFO:tensorflow:step = 273000, loss = 0.09830764 (0.205 sec)
INFO:tensorflow:global_step/sec: 485.767
INFO:tensorflow:step = 273100, loss = 1.2981756 (0.206 sec)
INFO:tensorflow:global_step/sec: 475.541
INFO:tensorflow:step = 273200, loss = 3.648411 (0.210 sec)
INFO:tensorflow:global_step/sec: 483.236
INFO:tensorflow:step = 273300, loss = 1.2493577 (0.207 sec)
INFO:tensorflow:global_step/sec: 488.101
INFO:tensorflow:step = 273400, loss = 0.8395519 (0.205 sec)
INFO:tensorflow:global_step/sec: 486.684
INFO:tensorflow:step = 273500, loss = 8.400174 (0.206 sec)
INFO:tensorflow:global_step/sec: 491.701
INFO:tensorflow:step = 273600, loss = 3.6669421 (0.203 sec)
INFO:tensorflow:global_step/sec: 479.048
INFO:tensorflow:step = 273700, loss = 2.5023046 (0.209 sec)
INFO:tensorflow:global_step/sec: 474.336
INFO:tensorflow:step = 273800, loss = 0.96744746 (0.211 sec)
INFO:tensorflow:global_step/sec: 486.882
INFO:tensorflow:step = 273900, loss = 0.19526277 (0.205 sec)
INFO:tensorflow:global_step/sec: 486.666
INFO:tensorflow:step = 274000, loss = 4.2975 (0.207 sec)
INFO:tensorflow:global_step/sec: 476.754
INFO:tensorflow:step = 274100, loss = 0.8327924 (0.208 sec)
INFO:tensorflow:global_step/sec: 483.136
INFO:tensorflow:step = 274200, loss = 0.3150554 (0.207 sec)
INFO:tensorflow:global_step/sec: 488.627
INFO:tensorflow:step = 274300, loss = 0.67196304 (0.205 sec)
INFO:tensorflow:global_step/sec: 485.848
INFO:tensorflow:step = 274400, loss = 3.0920887 (0.206 sec)
INFO:tensorflow:global_step/sec: 482.23
INFO:tensorflow:step = 274500, loss = 0.92843217 (0.207 sec)
INFO:tensorflow:global_step/sec: 479.226
INFO:tensorflow:step = 274600, loss = 1.9649677 (0.209 sec)
INFO:tensorflow:global_step/sec: 482.786
INFO:tensorflow:step = 274700, loss = 5.2275805 (0.207 sec)
INFO:tensorflow:global_step/sec: 474.331
INFO:tensorflow:step = 274800, loss = 0.6251996 (0.211 sec)
INFO:tensorflow:global_step/sec: 488.155
INFO:tensorflow:step = 274900, loss = 0.19593325 (0.207 sec)
INFO:tensorflow:global_step/sec: 484.868
INFO:tensorflow:step = 275000, loss = 0.33453822 (0.204 sec)
INFO:tensorflow:global_step/sec: 482.534
INFO:tensorflow:step = 275100, loss = 3.8746114 (0.207 sec)
INFO:tensorflow:global_step/sec: 496.953
INFO:tensorflow:step = 275200, loss = 0.2969979 (0.201 sec)
INFO:tensorflow:global_step/sec: 489.627
INFO:tensorflow:step = 275300, loss = 0.4635393 (0.204 sec)
INFO:tensorflow:global_step/sec: 485.382
INFO:tensorflow:step = 275400, loss = 0.11777875 (0.206 sec)
INFO:tensorflow:global_step/sec: 479.475
INFO:tensorflow:step = 275500, loss = 1.968998 (0.209 sec)
INFO:tensorflow:global_step/sec: 485.785
INFO:tensorflow:step = 275600, loss = 1.009282 (0.206 sec)
INFO:tensorflow:global_step/sec: 486.323
INFO:tensorflow:step = 275700, loss = 4.045884 (0.205 sec)
INFO:tensorflow:global_step/sec: 474.557
INFO:tensorflow:step = 275800, loss = 1.0288247 (0.211 sec)
INFO:tensorflow:global_step/sec: 487.941
INFO:tensorflow:step = 275900, loss = 0.13058957 (0.205 sec)
INFO:tensorflow:global_step/sec: 485.785
INFO:tensorflow:step = 276000, loss = 0.341488 (0.206 sec)
INFO:tensorflow:global_step/sec: 484.106
INFO:tensorflow:step = 276100, loss = 0.83812547 (0.207 sec)
INFO:tensorflow:global_step/sec: 486.767
INFO:tensorflow:step = 276200, loss = 2.2498465 (0.205 sec)
INFO:tensorflow:global_step/sec: 484.74
INFO:tensorflow:step = 276300, loss = 0.09570042 (0.206 sec)
INFO:tensorflow:global_step/sec: 483.496
INFO:tensorflow:step = 276400, loss = 1.5957891 (0.207 sec)
INFO:tensorflow:global_step/sec: 482.154
INFO:tensorflow:step = 276500, loss = 0.76052284 (0.208 sec)
INFO:tensorflow:global_step/sec: 489.3
INFO:tensorflow:step = 276600, loss = 0.015549202 (0.204 sec)
INFO:tensorflow:global_step/sec: 487.047
INFO:tensorflow:step = 276700, loss = 0.08570874 (0.205 sec)
INFO:tensorflow:global_step/sec: 488.686
INFO:tensorflow:step = 276800, loss = 0.779719 (0.205 sec)
INFO:tensorflow:global_step/sec: 484.336
INFO:tensorflow:step = 276900, loss = 0.78754246 (0.207 sec)
INFO:tensorflow:global_step/sec: 484.891
INFO:tensorflow:step = 277000, loss = 0.21728279 (0.206 sec)
INFO:tensorflow:global_step/sec: 484.594
INFO:tensorflow:step = 277100, loss = 0.33942214 (0.206 sec)
INFO:tensorflow:global_step/sec: 482.656
INFO:tensorflow:step = 277200, loss = 4.658767 (0.207 sec)
INFO:tensorflow:global_step/sec: 485.435
INFO:tensorflow:step = 277300, loss = 0.11509995 (0.206 sec)
INFO:tensorflow:global_step/sec: 484.144
INFO:tensorflow:step = 277400, loss = 0.20118287 (0.206 sec)
INFO:tensorflow:global_step/sec: 492.194
INFO:tensorflow:step = 277500, loss = 0.07209318 (0.203 sec)
INFO:tensorflow:global_step/sec: 490.187
INFO:tensorflow:step = 277600, loss = 0.5742978 (0.204 sec)
INFO:tensorflow:global_step/sec: 488.041
INFO:tensorflow:step = 277700, loss = 0.09627565 (0.205 sec)
INFO:tensorflow:global_step/sec: 483.72
INFO:tensorflow:step = 277800, loss = 1.4856551 (0.207 sec)
INFO:tensorflow:global_step/sec: 491.584
INFO:tensorflow:step = 277900, loss = 0.08039311 (0.205 sec)
INFO:tensorflow:global_step/sec: 486.283
INFO:tensorflow:step = 278000, loss = 1.0887151 (0.205 sec)
INFO:tensorflow:global_step/sec: 482.874
INFO:tensorflow:step = 278100, loss = 1.8900195 (0.207 sec)
INFO:tensorflow:global_step/sec: 493.365
INFO:tensorflow:step = 278200, loss = 0.5997604 (0.203 sec)
INFO:tensorflow:global_step/sec: 481.009
INFO:tensorflow:step = 278300, loss = 0.0556909 (0.208 sec)
INFO:tensorflow:global_step/sec: 483.452
INFO:tensorflow:step = 278400, loss = 1.2685254 (0.207 sec)
INFO:tensorflow:global_step/sec: 498.033
INFO:tensorflow:step = 278500, loss = 1.0909734 (0.201 sec)
INFO:tensorflow:global_step/sec: 477.17
INFO:tensorflow:step = 278600, loss = 1.9693666 (0.210 sec)
INFO:tensorflow:global_step/sec: 487.655
INFO:tensorflow:step = 278700, loss = 0.56093234 (0.205 sec)
INFO:tensorflow:global_step/sec: 479.81
INFO:tensorflow:step = 278800, loss = 0.3494661 (0.208 sec)
INFO:tensorflow:global_step/sec: 476.66
INFO:tensorflow:step = 278900, loss = 0.098697364 (0.211 sec)
INFO:tensorflow:global_step/sec: 489.888
INFO:tensorflow:step = 279000, loss = 2.572043 (0.203 sec)
INFO:tensorflow:global_step/sec: 491.361
INFO:tensorflow:step = 279100, loss = 0.7181123 (0.204 sec)
INFO:tensorflow:global_step/sec: 475.307
INFO:tensorflow:step = 279200, loss = 1.446013 (0.211 sec)
INFO:tensorflow:global_step/sec: 473.429
INFO:tensorflow:step = 279300, loss = 1.9392552 (0.211 sec)
INFO:tensorflow:global_step/sec: 490.331
INFO:tensorflow:step = 279400, loss = 0.3797472 (0.204 sec)
INFO:tensorflow:global_step/sec: 484.931
INFO:tensorflow:step = 279500, loss = 6.812481 (0.206 sec)
INFO:tensorflow:global_step/sec: 486.433
INFO:tensorflow:step = 279600, loss = 1.722871 (0.206 sec)
INFO:tensorflow:global_step/sec: 481.171
INFO:tensorflow:step = 279700, loss = 0.0783626 (0.208 sec)
INFO:tensorflow:global_step/sec: 472.551
INFO:tensorflow:step = 279800, loss = 0.2321423 (0.212 sec)
INFO:tensorflow:global_step/sec: 490.153
INFO:tensorflow:step = 279900, loss = 0.460909 (0.204 sec)
INFO:tensorflow:global_step/sec: 486.961
INFO:tensorflow:step = 280000, loss = 0.65760446 (0.205 sec)
INFO:tensorflow:global_step/sec: 491.8
INFO:tensorflow:step = 280100, loss = 4.028965 (0.203 sec)
INFO:tensorflow:global_step/sec: 493.305
INFO:tensorflow:step = 280200, loss = 0.06471885 (0.203 sec)
INFO:tensorflow:global_step/sec: 477.403
INFO:tensorflow:step = 280300, loss = 5.3535714 (0.210 sec)
INFO:tensorflow:global_step/sec: 473.941
INFO:tensorflow:step = 280400, loss = 0.8062311 (0.211 sec)
INFO:tensorflow:global_step/sec: 487.639
INFO:tensorflow:step = 280500, loss = 0.09811453 (0.205 sec)
INFO:tensorflow:global_step/sec: 487.957
INFO:tensorflow:step = 280600, loss = 0.94098747 (0.205 sec)
INFO:tensorflow:global_step/sec: 484.816
INFO:tensorflow:step = 280700, loss = 0.46037823 (0.206 sec)
INFO:tensorflow:global_step/sec: 487.622
INFO:tensorflow:step = 280800, loss = 1.4753544 (0.205 sec)
INFO:tensorflow:global_step/sec: 489.742
INFO:tensorflow:step = 280900, loss = 0.60709596 (0.204 sec)
INFO:tensorflow:global_step/sec: 491.592
INFO:tensorflow:step = 281000, loss = 0.027233694 (0.203 sec)
INFO:tensorflow:global_step/sec: 483.363
INFO:tensorflow:step = 281100, loss = 0.8888534 (0.207 sec)
INFO:tensorflow:global_step/sec: 478.048
INFO:tensorflow:step = 281200, loss = 1.5147442 (0.209 sec)
INFO:tensorflow:global_step/sec: 483.643
INFO:tensorflow:step = 281300, loss = 0.11010057 (0.207 sec)
INFO:tensorflow:global_step/sec: 483.01
INFO:tensorflow:step = 281400, loss = 1.0133591 (0.207 sec)
INFO:tensorflow:global_step/sec: 474.384
INFO:tensorflow:step = 281500, loss = 0.2569079 (0.211 sec)
INFO:tensorflow:global_step/sec: 475.435
INFO:tensorflow:step = 281600, loss = 4.255569 (0.210 sec)
INFO:tensorflow:global_step/sec: 477.482
INFO:tensorflow:step = 281700, loss = 0.60686547 (0.209 sec)
INFO:tensorflow:global_step/sec: 483.444
INFO:tensorflow:step = 281800, loss = 0.047530297 (0.207 sec)
INFO:tensorflow:global_step/sec: 476.205
INFO:tensorflow:step = 281900, loss = 1.9304138 (0.210 sec)
INFO:tensorflow:global_step/sec: 482.488
INFO:tensorflow:step = 282000, loss = 0.43716294 (0.207 sec)
INFO:tensorflow:global_step/sec: 485.314
INFO:tensorflow:step = 282100, loss = 0.36247724 (0.206 sec)
INFO:tensorflow:global_step/sec: 478.059
INFO:tensorflow:step = 282200, loss = 3.287364 (0.209 sec)
INFO:tensorflow:global_step/sec: 488.789
INFO:tensorflow:step = 282300, loss = 1.4121273 (0.205 sec)
INFO:tensorflow:global_step/sec: 485.654
INFO:tensorflow:step = 282400, loss = 0.05497732 (0.206 sec)
INFO:tensorflow:global_step/sec: 474.063
INFO:tensorflow:step = 282500, loss = 0.4546707 (0.211 sec)
INFO:tensorflow:global_step/sec: 483.768
INFO:tensorflow:step = 282600, loss = 3.2367976 (0.206 sec)
INFO:tensorflow:global_step/sec: 485.86
INFO:tensorflow:step = 282700, loss = 0.10886495 (0.206 sec)
INFO:tensorflow:global_step/sec: 483.205
INFO:tensorflow:step = 282800, loss = 3.6685553 (0.207 sec)
INFO:tensorflow:global_step/sec: 486.431
INFO:tensorflow:step = 282900, loss = 3.2546074 (0.205 sec)
INFO:tensorflow:global_step/sec: 485.631
INFO:tensorflow:step = 283000, loss = 0.47914955 (0.206 sec)
INFO:tensorflow:global_step/sec: 487.956
INFO:tensorflow:step = 283100, loss = 0.5353771 (0.205 sec)
INFO:tensorflow:global_step/sec: 482.467
INFO:tensorflow:step = 283200, loss = 2.6805754 (0.207 sec)
INFO:tensorflow:global_step/sec: 486.395
INFO:tensorflow:step = 283300, loss = 1.1067137 (0.206 sec)
INFO:tensorflow:global_step/sec: 490.131
INFO:tensorflow:step = 283400, loss = 5.719832 (0.204 sec)
INFO:tensorflow:global_step/sec: 478.353
INFO:tensorflow:step = 283500, loss = 0.3164988 (0.209 sec)
INFO:tensorflow:global_step/sec: 477.512
INFO:tensorflow:step = 283600, loss = 0.35738012 (0.209 sec)
INFO:tensorflow:global_step/sec: 476.586
INFO:tensorflow:step = 283700, loss = 0.05080071 (0.209 sec)
INFO:tensorflow:global_step/sec: 493.707
INFO:tensorflow:step = 283800, loss = 0.50182027 (0.203 sec)
INFO:tensorflow:global_step/sec: 471.682
INFO:tensorflow:step = 283900, loss = 0.2609684 (0.212 sec)
INFO:tensorflow:global_step/sec: 485.769
INFO:tensorflow:step = 284000, loss = 0.14118825 (0.206 sec)
INFO:tensorflow:global_step/sec: 480.64
INFO:tensorflow:step = 284100, loss = 0.4218206 (0.208 sec)
INFO:tensorflow:global_step/sec: 481.909
INFO:tensorflow:step = 284200, loss = 5.1973677 (0.207 sec)
INFO:tensorflow:global_step/sec: 488.394
INFO:tensorflow:step = 284300, loss = 0.2766311 (0.205 sec)
INFO:tensorflow:global_step/sec: 492.488
INFO:tensorflow:step = 284400, loss = 0.18890768 (0.203 sec)
INFO:tensorflow:global_step/sec: 467.364
INFO:tensorflow:step = 284500, loss = 0.07081251 (0.214 sec)
INFO:tensorflow:global_step/sec: 483.703
INFO:tensorflow:step = 284600, loss = 0.8219839 (0.207 sec)
INFO:tensorflow:global_step/sec: 483.128
INFO:tensorflow:step = 284700, loss = 0.06900106 (0.207 sec)
INFO:tensorflow:global_step/sec: 489.647
INFO:tensorflow:step = 284800, loss = 2.2118826 (0.204 sec)
INFO:tensorflow:global_step/sec: 484.999
INFO:tensorflow:step = 284900, loss = 0.48227403 (0.206 sec)
INFO:tensorflow:global_step/sec: 482.152
INFO:tensorflow:step = 285000, loss = 0.5266315 (0.207 sec)
INFO:tensorflow:global_step/sec: 480.424
INFO:tensorflow:step = 285100, loss = 0.25465587 (0.208 sec)
INFO:tensorflow:global_step/sec: 486.831
INFO:tensorflow:step = 285200, loss = 0.33012 (0.205 sec)
INFO:tensorflow:global_step/sec: 489.852
INFO:tensorflow:step = 285300, loss = 0.7434609 (0.204 sec)
INFO:tensorflow:global_step/sec: 488.391
INFO:tensorflow:step = 285400, loss = 2.615423 (0.205 sec)
INFO:tensorflow:global_step/sec: 484.34
INFO:tensorflow:step = 285500, loss = 5.2717705 (0.208 sec)
INFO:tensorflow:global_step/sec: 475.669
INFO:tensorflow:step = 285600, loss = 1.8280867 (0.209 sec)
INFO:tensorflow:global_step/sec: 484.957
INFO:tensorflow:step = 285700, loss = 0.8276904 (0.206 sec)
INFO:tensorflow:global_step/sec: 492.86
INFO:tensorflow:step = 285800, loss = 1.1398816 (0.203 sec)
INFO:tensorflow:global_step/sec: 483.222
INFO:tensorflow:step = 285900, loss = 0.21165547 (0.207 sec)
INFO:tensorflow:global_step/sec: 486.817
INFO:tensorflow:step = 286000, loss = 0.57607704 (0.206 sec)
INFO:tensorflow:global_step/sec: 472.075
INFO:tensorflow:step = 286100, loss = 0.96695375 (0.212 sec)
INFO:tensorflow:global_step/sec: 480.037
INFO:tensorflow:step = 286200, loss = 3.8679993 (0.208 sec)
INFO:tensorflow:global_step/sec: 491.674
INFO:tensorflow:step = 286300, loss = 2.586308 (0.203 sec)
INFO:tensorflow:global_step/sec: 482.147
INFO:tensorflow:step = 286400, loss = 0.06982355 (0.207 sec)
INFO:tensorflow:global_step/sec: 487.094
INFO:tensorflow:step = 286500, loss = 0.02444655 (0.205 sec)
INFO:tensorflow:global_step/sec: 483.066
INFO:tensorflow:step = 286600, loss = 2.3740373 (0.207 sec)
INFO:tensorflow:global_step/sec: 478.181
INFO:tensorflow:step = 286700, loss = 0.71887636 (0.209 sec)
INFO:tensorflow:global_step/sec: 488.365
INFO:tensorflow:step = 286800, loss = 0.14689954 (0.205 sec)
INFO:tensorflow:global_step/sec: 479.61
INFO:tensorflow:step = 286900, loss = 1.1905601 (0.209 sec)
INFO:tensorflow:global_step/sec: 474.779
INFO:tensorflow:step = 287000, loss = 0.9119834 (0.211 sec)
INFO:tensorflow:global_step/sec: 477.514
INFO:tensorflow:step = 287100, loss = 0.13571689 (0.209 sec)
INFO:tensorflow:global_step/sec: 493.313
INFO:tensorflow:step = 287200, loss = 0.74413097 (0.203 sec)
INFO:tensorflow:global_step/sec: 483.668
INFO:tensorflow:step = 287300, loss = 0.42744923 (0.207 sec)
INFO:tensorflow:global_step/sec: 481.539
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INFO:tensorflow:global_step/sec: 485.824
INFO:tensorflow:step = 287500, loss = 1.5964181 (0.206 sec)
INFO:tensorflow:global_step/sec: 487.911
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INFO:tensorflow:global_step/sec: 476.818
INFO:tensorflow:step = 287700, loss = 1.6860957 (0.210 sec)
INFO:tensorflow:global_step/sec: 476.542
INFO:tensorflow:step = 287800, loss = 4.698303 (0.210 sec)
INFO:tensorflow:global_step/sec: 476.152
INFO:tensorflow:step = 287900, loss = 0.15686306 (0.210 sec)
INFO:tensorflow:global_step/sec: 464.681
INFO:tensorflow:step = 288000, loss = 0.3259024 (0.215 sec)
INFO:tensorflow:global_step/sec: 467.377
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INFO:tensorflow:global_step/sec: 473.811
INFO:tensorflow:step = 288200, loss = 0.60766405 (0.211 sec)
INFO:tensorflow:global_step/sec: 458.805
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INFO:tensorflow:global_step/sec: 454.68
INFO:tensorflow:step = 288400, loss = 0.864584 (0.220 sec)
INFO:tensorflow:global_step/sec: 465.332
INFO:tensorflow:step = 288500, loss = 0.8001609 (0.215 sec)
INFO:tensorflow:global_step/sec: 480.113
INFO:tensorflow:step = 288600, loss = 0.16623572 (0.210 sec)
INFO:tensorflow:global_step/sec: 470.52
INFO:tensorflow:step = 288700, loss = 1.0587002 (0.211 sec)
INFO:tensorflow:global_step/sec: 457.988
INFO:tensorflow:step = 288800, loss = 0.059452586 (0.218 sec)
INFO:tensorflow:global_step/sec: 468.75
INFO:tensorflow:step = 288900, loss = 0.36288163 (0.214 sec)
INFO:tensorflow:global_step/sec: 460.46
INFO:tensorflow:step = 289000, loss = 1.7218386 (0.217 sec)
INFO:tensorflow:global_step/sec: 471.78
INFO:tensorflow:step = 289100, loss = 0.42634228 (0.212 sec)
INFO:tensorflow:global_step/sec: 461.581
INFO:tensorflow:step = 289200, loss = 1.74754 (0.217 sec)
INFO:tensorflow:global_step/sec: 459.302
INFO:tensorflow:step = 289300, loss = 0.8373272 (0.218 sec)
INFO:tensorflow:global_step/sec: 452.956
INFO:tensorflow:step = 289400, loss = 3.966342 (0.221 sec)
INFO:tensorflow:global_step/sec: 457.666
INFO:tensorflow:step = 289500, loss = 2.7454758 (0.218 sec)
INFO:tensorflow:global_step/sec: 459.699
INFO:tensorflow:step = 289600, loss = 0.010310674 (0.218 sec)
INFO:tensorflow:global_step/sec: 460.992
INFO:tensorflow:step = 289700, loss = 0.46932116 (0.217 sec)
INFO:tensorflow:global_step/sec: 457.06
INFO:tensorflow:step = 289800, loss = 3.0177982 (0.219 sec)
INFO:tensorflow:global_step/sec: 455.044
INFO:tensorflow:step = 289900, loss = 3.6093605 (0.220 sec)
INFO:tensorflow:global_step/sec: 457.615
INFO:tensorflow:step = 290000, loss = 1.5449567 (0.219 sec)
INFO:tensorflow:global_step/sec: 454.962
INFO:tensorflow:step = 290100, loss = 0.028115902 (0.220 sec)
INFO:tensorflow:global_step/sec: 462.173
INFO:tensorflow:step = 290200, loss = 0.49440032 (0.216 sec)
INFO:tensorflow:global_step/sec: 463.24
INFO:tensorflow:step = 290300, loss = 0.13990653 (0.216 sec)
INFO:tensorflow:global_step/sec: 454.092
INFO:tensorflow:step = 290400, loss = 0.41489017 (0.220 sec)
INFO:tensorflow:global_step/sec: 450.357
INFO:tensorflow:step = 290500, loss = 0.6904538 (0.222 sec)
INFO:tensorflow:global_step/sec: 447.798
INFO:tensorflow:step = 290600, loss = 0.23617214 (0.223 sec)
INFO:tensorflow:global_step/sec: 451.99
INFO:tensorflow:step = 290700, loss = 0.6693327 (0.221 sec)
INFO:tensorflow:global_step/sec: 461.971
INFO:tensorflow:step = 290800, loss = 0.7268792 (0.216 sec)
INFO:tensorflow:global_step/sec: 453.353
INFO:tensorflow:step = 290900, loss = 0.32758504 (0.221 sec)
INFO:tensorflow:global_step/sec: 458.93
INFO:tensorflow:step = 291000, loss = 1.9275707 (0.218 sec)
INFO:tensorflow:global_step/sec: 454.169
INFO:tensorflow:step = 291100, loss = 0.12751913 (0.220 sec)
INFO:tensorflow:global_step/sec: 449.475
INFO:tensorflow:step = 291200, loss = 0.15440905 (0.222 sec)
INFO:tensorflow:global_step/sec: 457.161
INFO:tensorflow:step = 291300, loss = 1.615394 (0.219 sec)
INFO:tensorflow:global_step/sec: 450.229
INFO:tensorflow:step = 291400, loss = 2.8686035 (0.222 sec)
INFO:tensorflow:global_step/sec: 456.687
INFO:tensorflow:step = 291500, loss = 0.06457131 (0.219 sec)
INFO:tensorflow:global_step/sec: 449.784
INFO:tensorflow:step = 291600, loss = 0.7693165 (0.222 sec)
INFO:tensorflow:global_step/sec: 451.569
INFO:tensorflow:step = 291700, loss = 4.0389643 (0.221 sec)
INFO:tensorflow:global_step/sec: 465.587
INFO:tensorflow:step = 291800, loss = 0.6288546 (0.215 sec)
INFO:tensorflow:global_step/sec: 456.401
INFO:tensorflow:step = 291900, loss = 0.19998103 (0.219 sec)
INFO:tensorflow:global_step/sec: 451.623
INFO:tensorflow:step = 292000, loss = 0.1329102 (0.221 sec)
INFO:tensorflow:global_step/sec: 448.084
INFO:tensorflow:step = 292100, loss = 0.50293446 (0.223 sec)
INFO:tensorflow:global_step/sec: 457.606
INFO:tensorflow:step = 292200, loss = 1.7859702 (0.219 sec)
INFO:tensorflow:global_step/sec: 462.448
INFO:tensorflow:step = 292300, loss = 0.052347586 (0.216 sec)
INFO:tensorflow:global_step/sec: 451.922
INFO:tensorflow:step = 292400, loss = 0.49075997 (0.221 sec)
INFO:tensorflow:global_step/sec: 459.335
INFO:tensorflow:step = 292500, loss = 0.07882075 (0.217 sec)
INFO:tensorflow:global_step/sec: 467.313
INFO:tensorflow:step = 292600, loss = 6.650978 (0.214 sec)
INFO:tensorflow:global_step/sec: 453.547
INFO:tensorflow:step = 292700, loss = 1.6233883 (0.220 sec)
INFO:tensorflow:global_step/sec: 465.187
INFO:tensorflow:step = 292800, loss = 1.365056 (0.215 sec)
INFO:tensorflow:global_step/sec: 467.017
INFO:tensorflow:step = 292900, loss = 0.3204738 (0.214 sec)
INFO:tensorflow:global_step/sec: 465.176
INFO:tensorflow:step = 293000, loss = 0.702471 (0.215 sec)
INFO:tensorflow:global_step/sec: 468.759
INFO:tensorflow:step = 293100, loss = 3.009309 (0.213 sec)
INFO:tensorflow:global_step/sec: 467.399
INFO:tensorflow:step = 293200, loss = 1.5477567 (0.214 sec)
INFO:tensorflow:global_step/sec: 462.374
INFO:tensorflow:step = 293300, loss = 4.046189 (0.216 sec)
INFO:tensorflow:global_step/sec: 461.423
INFO:tensorflow:step = 293400, loss = 0.90941846 (0.217 sec)
INFO:tensorflow:global_step/sec: 469.133
INFO:tensorflow:step = 293500, loss = 0.10350247 (0.213 sec)
INFO:tensorflow:global_step/sec: 459.755
INFO:tensorflow:step = 293600, loss = 0.2091563 (0.217 sec)
INFO:tensorflow:global_step/sec: 470.183
INFO:tensorflow:step = 293700, loss = 0.32454306 (0.213 sec)
INFO:tensorflow:global_step/sec: 464.496
INFO:tensorflow:step = 293800, loss = 0.06099197 (0.215 sec)
INFO:tensorflow:global_step/sec: 464.436
INFO:tensorflow:step = 293900, loss = 0.28563267 (0.215 sec)
INFO:tensorflow:global_step/sec: 464.637
INFO:tensorflow:step = 294000, loss = 0.29230505 (0.215 sec)
INFO:tensorflow:global_step/sec: 468.206
INFO:tensorflow:step = 294100, loss = 0.5504123 (0.214 sec)
INFO:tensorflow:global_step/sec: 455.035
INFO:tensorflow:step = 294200, loss = 3.6002247 (0.222 sec)
INFO:tensorflow:global_step/sec: 464.398
INFO:tensorflow:step = 294300, loss = 0.05874029 (0.214 sec)
INFO:tensorflow:global_step/sec: 460.737
INFO:tensorflow:step = 294400, loss = 0.099870995 (0.217 sec)
INFO:tensorflow:global_step/sec: 459.29
INFO:tensorflow:step = 294500, loss = 1.4441608 (0.218 sec)
INFO:tensorflow:global_step/sec: 448.13
INFO:tensorflow:step = 294600, loss = 0.056146633 (0.223 sec)
INFO:tensorflow:global_step/sec: 458.196
INFO:tensorflow:step = 294700, loss = 0.05304179 (0.218 sec)
INFO:tensorflow:global_step/sec: 458.142
INFO:tensorflow:step = 294800, loss = 3.5842419 (0.218 sec)
INFO:tensorflow:global_step/sec: 469.75
INFO:tensorflow:step = 294900, loss = 0.25648966 (0.213 sec)
INFO:tensorflow:global_step/sec: 472.601
INFO:tensorflow:step = 295000, loss = 0.69022804 (0.211 sec)
INFO:tensorflow:global_step/sec: 466.367
INFO:tensorflow:step = 295100, loss = 2.6477053 (0.214 sec)
INFO:tensorflow:global_step/sec: 470.676
INFO:tensorflow:step = 295200, loss = 0.014228305 (0.212 sec)
INFO:tensorflow:global_step/sec: 464.919
INFO:tensorflow:step = 295300, loss = 0.187181 (0.215 sec)
INFO:tensorflow:global_step/sec: 456.021
INFO:tensorflow:step = 295400, loss = 1.851346 (0.219 sec)
INFO:tensorflow:global_step/sec: 455.338
INFO:tensorflow:step = 295500, loss = 0.30237854 (0.220 sec)
INFO:tensorflow:global_step/sec: 458.808
INFO:tensorflow:step = 295600, loss = 1.6027024 (0.218 sec)
INFO:tensorflow:global_step/sec: 468.2
INFO:tensorflow:step = 295700, loss = 0.28368658 (0.213 sec)
INFO:tensorflow:global_step/sec: 466.83
INFO:tensorflow:step = 295800, loss = 2.6937485 (0.214 sec)
INFO:tensorflow:global_step/sec: 470.26
INFO:tensorflow:step = 295900, loss = 0.39026642 (0.212 sec)
INFO:tensorflow:global_step/sec: 470.22
INFO:tensorflow:step = 296000, loss = 0.5766183 (0.213 sec)
INFO:tensorflow:global_step/sec: 460.546
INFO:tensorflow:step = 296100, loss = 0.37965935 (0.217 sec)
INFO:tensorflow:global_step/sec: 459.502
INFO:tensorflow:step = 296200, loss = 1.4572479 (0.218 sec)
INFO:tensorflow:global_step/sec: 461.429
INFO:tensorflow:step = 296300, loss = 1.0049202 (0.217 sec)
INFO:tensorflow:global_step/sec: 457.351
INFO:tensorflow:step = 296400, loss = 0.20772032 (0.219 sec)
INFO:tensorflow:global_step/sec: 463.078
INFO:tensorflow:step = 296500, loss = 4.6435285 (0.216 sec)
INFO:tensorflow:global_step/sec: 456.052
INFO:tensorflow:step = 296600, loss = 3.092372 (0.220 sec)
INFO:tensorflow:global_step/sec: 451.732
INFO:tensorflow:step = 296700, loss = 0.3021154 (0.221 sec)
INFO:tensorflow:global_step/sec: 462.355
INFO:tensorflow:step = 296800, loss = 0.11326461 (0.217 sec)
INFO:tensorflow:global_step/sec: 452.702
INFO:tensorflow:step = 296900, loss = 0.55423 (0.221 sec)
INFO:tensorflow:global_step/sec: 455.234
INFO:tensorflow:step = 297000, loss = 0.14147335 (0.220 sec)
INFO:tensorflow:global_step/sec: 453.488
INFO:tensorflow:step = 297100, loss = 0.050282635 (0.220 sec)
INFO:tensorflow:global_step/sec: 452.235
INFO:tensorflow:step = 297200, loss = 0.34376287 (0.221 sec)
INFO:tensorflow:global_step/sec: 460.93
INFO:tensorflow:step = 297300, loss = 4.327422 (0.217 sec)
INFO:tensorflow:global_step/sec: 462.105
INFO:tensorflow:step = 297400, loss = 0.43878657 (0.216 sec)
INFO:tensorflow:global_step/sec: 450.404
INFO:tensorflow:step = 297500, loss = 3.3922985 (0.222 sec)
INFO:tensorflow:global_step/sec: 456.086
INFO:tensorflow:step = 297600, loss = 0.22484648 (0.219 sec)
INFO:tensorflow:global_step/sec: 460.594
INFO:tensorflow:step = 297700, loss = 0.38100296 (0.219 sec)
INFO:tensorflow:global_step/sec: 452.899
INFO:tensorflow:step = 297800, loss = 0.75442463 (0.219 sec)
INFO:tensorflow:global_step/sec: 456.024
INFO:tensorflow:step = 297900, loss = 2.434833 (0.219 sec)
INFO:tensorflow:global_step/sec: 447.532
INFO:tensorflow:step = 298000, loss = 0.75274897 (0.223 sec)
INFO:tensorflow:global_step/sec: 458.052
INFO:tensorflow:step = 298100, loss = 0.7987398 (0.219 sec)
INFO:tensorflow:global_step/sec: 455.641
INFO:tensorflow:step = 298200, loss = 0.067772225 (0.219 sec)
INFO:tensorflow:global_step/sec: 457.616
INFO:tensorflow:step = 298300, loss = 0.4595974 (0.219 sec)
INFO:tensorflow:global_step/sec: 457.738
INFO:tensorflow:step = 298400, loss = 0.38647708 (0.218 sec)
INFO:tensorflow:global_step/sec: 453.034
INFO:tensorflow:step = 298500, loss = 0.41817355 (0.221 sec)
INFO:tensorflow:global_step/sec: 443.878
INFO:tensorflow:step = 298600, loss = 0.2615833 (0.225 sec)
INFO:tensorflow:global_step/sec: 461.518
INFO:tensorflow:step = 298700, loss = 3.2089813 (0.217 sec)
INFO:tensorflow:global_step/sec: 454.419
INFO:tensorflow:step = 298800, loss = 1.0830296 (0.220 sec)
INFO:tensorflow:global_step/sec: 452.239
INFO:tensorflow:step = 298900, loss = 1.3332835 (0.221 sec)
INFO:tensorflow:global_step/sec: 448.578
INFO:tensorflow:step = 299000, loss = 4.8903217 (0.223 sec)
INFO:tensorflow:global_step/sec: 454.805
INFO:tensorflow:step = 299100, loss = 4.640608 (0.220 sec)
INFO:tensorflow:global_step/sec: 447.302
INFO:tensorflow:step = 299200, loss = 2.8800523 (0.225 sec)
INFO:tensorflow:global_step/sec: 446.317
INFO:tensorflow:step = 299300, loss = 0.11146888 (0.222 sec)
INFO:tensorflow:global_step/sec: 446.9
INFO:tensorflow:step = 299400, loss = 0.1967468 (0.224 sec)
INFO:tensorflow:global_step/sec: 451.571
INFO:tensorflow:step = 299500, loss = 0.8887358 (0.221 sec)
INFO:tensorflow:global_step/sec: 452.574
INFO:tensorflow:step = 299600, loss = 0.22839324 (0.221 sec)
INFO:tensorflow:global_step/sec: 447.94
INFO:tensorflow:step = 299700, loss = 0.43267268 (0.223 sec)
INFO:tensorflow:global_step/sec: 457.433
INFO:tensorflow:step = 299800, loss = 0.5276636 (0.218 sec)
INFO:tensorflow:global_step/sec: 452.766
INFO:tensorflow:step = 299900, loss = 0.42041934 (0.221 sec)
INFO:tensorflow:global_step/sec: 457.581
INFO:tensorflow:step = 300000, loss = 2.0550697 (0.218 sec)
INFO:tensorflow:global_step/sec: 459.107
INFO:tensorflow:step = 300100, loss = 0.07694152 (0.218 sec)
INFO:tensorflow:global_step/sec: 465.615
INFO:tensorflow:step = 300200, loss = 4.0558796 (0.215 sec)
INFO:tensorflow:global_step/sec: 466.973
INFO:tensorflow:step = 300300, loss = 0.08516134 (0.214 sec)
INFO:tensorflow:global_step/sec: 466.339
INFO:tensorflow:step = 300400, loss = 5.039366 (0.214 sec)
INFO:tensorflow:global_step/sec: 462.746
INFO:tensorflow:step = 300500, loss = 0.40309528 (0.216 sec)
INFO:tensorflow:global_step/sec: 454.819
INFO:tensorflow:step = 300600, loss = 1.8768958 (0.220 sec)
INFO:tensorflow:global_step/sec: 463.692
INFO:tensorflow:step = 300700, loss = 1.8490446 (0.216 sec)
INFO:tensorflow:global_step/sec: 463.789
INFO:tensorflow:step = 300800, loss = 0.36232883 (0.216 sec)
INFO:tensorflow:global_step/sec: 466.562
INFO:tensorflow:step = 300900, loss = 0.9815284 (0.214 sec)
INFO:tensorflow:global_step/sec: 459.451
INFO:tensorflow:step = 301000, loss = 4.852131 (0.217 sec)
INFO:tensorflow:global_step/sec: 463.959
INFO:tensorflow:step = 301100, loss = 0.021272033 (0.216 sec)
INFO:tensorflow:global_step/sec: 469.416
INFO:tensorflow:step = 301200, loss = 0.23740605 (0.213 sec)
INFO:tensorflow:global_step/sec: 455.384
INFO:tensorflow:step = 301300, loss = 2.5744839 (0.219 sec)
INFO:tensorflow:global_step/sec: 456.614
INFO:tensorflow:step = 301400, loss = 0.030146211 (0.219 sec)
INFO:tensorflow:global_step/sec: 462.495
INFO:tensorflow:step = 301500, loss = 0.277924 (0.216 sec)
INFO:tensorflow:global_step/sec: 462.197
INFO:tensorflow:step = 301600, loss = 0.6177288 (0.216 sec)
INFO:tensorflow:global_step/sec: 464.943
INFO:tensorflow:step = 301700, loss = 0.9822917 (0.215 sec)
INFO:tensorflow:global_step/sec: 454.443
INFO:tensorflow:step = 301800, loss = 1.3133432 (0.220 sec)
INFO:tensorflow:global_step/sec: 443.8
INFO:tensorflow:step = 301900, loss = 3.2380307 (0.225 sec)
INFO:tensorflow:global_step/sec: 450.206
INFO:tensorflow:step = 302000, loss = 0.4649796 (0.222 sec)
INFO:tensorflow:global_step/sec: 452.244
INFO:tensorflow:step = 302100, loss = 0.3204699 (0.221 sec)
INFO:tensorflow:global_step/sec: 457.958
INFO:tensorflow:step = 302200, loss = 0.5138853 (0.218 sec)
INFO:tensorflow:global_step/sec: 451.037
INFO:tensorflow:step = 302300, loss = 3.847061 (0.221 sec)
INFO:tensorflow:global_step/sec: 458.309
INFO:tensorflow:step = 302400, loss = 0.32249293 (0.218 sec)
INFO:tensorflow:global_step/sec: 456.41
INFO:tensorflow:step = 302500, loss = 0.31344023 (0.219 sec)
INFO:tensorflow:global_step/sec: 451.576
INFO:tensorflow:step = 302600, loss = 0.6306782 (0.221 sec)
INFO:tensorflow:global_step/sec: 456.706
INFO:tensorflow:step = 302700, loss = 2.7062235 (0.219 sec)
INFO:tensorflow:global_step/sec: 453.903
INFO:tensorflow:step = 302800, loss = 2.466474 (0.222 sec)
INFO:tensorflow:global_step/sec: 452.389
INFO:tensorflow:step = 302900, loss = 0.013394915 (0.219 sec)
INFO:tensorflow:global_step/sec: 460.068
INFO:tensorflow:step = 303000, loss = 0.11149244 (0.217 sec)
INFO:tensorflow:global_step/sec: 462.617
INFO:tensorflow:step = 303100, loss = 1.5145017 (0.216 sec)
INFO:tensorflow:global_step/sec: 449.439
INFO:tensorflow:step = 303200, loss = 1.4959098 (0.223 sec)
INFO:tensorflow:global_step/sec: 457.271
INFO:tensorflow:step = 303300, loss = 0.22332565 (0.219 sec)
INFO:tensorflow:global_step/sec: 446.71
INFO:tensorflow:step = 303400, loss = 1.7314788 (0.224 sec)
INFO:tensorflow:global_step/sec: 461.159
INFO:tensorflow:step = 303500, loss = 3.6799748 (0.216 sec)
INFO:tensorflow:global_step/sec: 457.328
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INFO:tensorflow:global_step/sec: 459.048
INFO:tensorflow:step = 303700, loss = 0.16458884 (0.218 sec)
INFO:tensorflow:global_step/sec: 454.006
INFO:tensorflow:step = 303800, loss = 3.3564873 (0.220 sec)
INFO:tensorflow:global_step/sec: 454.991
INFO:tensorflow:step = 303900, loss = 0.24278855 (0.220 sec)
INFO:tensorflow:global_step/sec: 457.434
INFO:tensorflow:step = 304000, loss = 0.5800425 (0.219 sec)
INFO:tensorflow:global_step/sec: 461.209
INFO:tensorflow:step = 304100, loss = 0.28575778 (0.217 sec)
INFO:tensorflow:global_step/sec: 458.223
INFO:tensorflow:step = 304200, loss = 0.8488497 (0.218 sec)
INFO:tensorflow:global_step/sec: 452.997
INFO:tensorflow:step = 304300, loss = 0.9923061 (0.221 sec)
INFO:tensorflow:global_step/sec: 462.669
INFO:tensorflow:step = 304400, loss = 0.36094642 (0.216 sec)
INFO:tensorflow:global_step/sec: 453.764
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INFO:tensorflow:global_step/sec: 451.534
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INFO:tensorflow:global_step/sec: 448.156
INFO:tensorflow:step = 304700, loss = 0.19011995 (0.223 sec)
INFO:tensorflow:global_step/sec: 456.322
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INFO:tensorflow:global_step/sec: 460.851
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INFO:tensorflow:global_step/sec: 459.959
INFO:tensorflow:step = 305000, loss = 5.0466747 (0.217 sec)
INFO:tensorflow:global_step/sec: 472.299
INFO:tensorflow:step = 305100, loss = 0.05112976 (0.212 sec)
INFO:tensorflow:global_step/sec: 461.275
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INFO:tensorflow:global_step/sec: 455.737
INFO:tensorflow:step = 305300, loss = 1.5995021 (0.219 sec)
INFO:tensorflow:global_step/sec: 461.503
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INFO:tensorflow:global_step/sec: 468.918
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INFO:tensorflow:global_step/sec: 468.538
INFO:tensorflow:step = 305600, loss = 4.9986715 (0.214 sec)
INFO:tensorflow:global_step/sec: 468.092
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INFO:tensorflow:global_step/sec: 457.565
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INFO:tensorflow:global_step/sec: 458.548
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INFO:tensorflow:global_step/sec: 466.845
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INFO:tensorflow:global_step/sec: 461.391
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INFO:tensorflow:global_step/sec: 467.339
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INFO:tensorflow:global_step/sec: 453.148
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INFO:tensorflow:global_step/sec: 445.812
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INFO:tensorflow:global_step/sec: 465.57
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INFO:tensorflow:global_step/sec: 463.603
INFO:tensorflow:step = 306700, loss = 7.9360766 (0.216 sec)
INFO:tensorflow:global_step/sec: 461.549
INFO:tensorflow:step = 306800, loss = 0.79822415 (0.217 sec)
INFO:tensorflow:global_step/sec: 456.682
INFO:tensorflow:step = 306900, loss = 0.24511929 (0.219 sec)
INFO:tensorflow:global_step/sec: 463.56
INFO:tensorflow:step = 307000, loss = 0.022133503 (0.216 sec)
INFO:tensorflow:global_step/sec: 463.142
INFO:tensorflow:step = 307100, loss = 0.051352758 (0.216 sec)
INFO:tensorflow:global_step/sec: 460.902
INFO:tensorflow:step = 307200, loss = 0.589818 (0.217 sec)
INFO:tensorflow:global_step/sec: 462.044
INFO:tensorflow:step = 307300, loss = 0.35978746 (0.216 sec)
INFO:tensorflow:global_step/sec: 456.924
INFO:tensorflow:step = 307400, loss = 0.50613415 (0.219 sec)
INFO:tensorflow:global_step/sec: 449.745
INFO:tensorflow:step = 307500, loss = 0.12221098 (0.222 sec)
INFO:tensorflow:global_step/sec: 459.358
INFO:tensorflow:step = 307600, loss = 0.10336357 (0.218 sec)
INFO:tensorflow:global_step/sec: 449.531
INFO:tensorflow:step = 307700, loss = 0.43595475 (0.222 sec)
INFO:tensorflow:global_step/sec: 455.964
INFO:tensorflow:step = 307800, loss = 0.22585687 (0.219 sec)
INFO:tensorflow:global_step/sec: 463.175
INFO:tensorflow:step = 307900, loss = 0.09710163 (0.216 sec)
INFO:tensorflow:global_step/sec: 455.811
INFO:tensorflow:step = 308000, loss = 0.4786095 (0.219 sec)
INFO:tensorflow:global_step/sec: 466.657
INFO:tensorflow:step = 308100, loss = 0.10056452 (0.214 sec)
INFO:tensorflow:global_step/sec: 458.262
INFO:tensorflow:step = 308200, loss = 3.105733 (0.218 sec)
INFO:tensorflow:global_step/sec: 463.57
INFO:tensorflow:step = 308300, loss = 0.032690812 (0.216 sec)
INFO:tensorflow:global_step/sec: 466.009
INFO:tensorflow:step = 308400, loss = 0.4502321 (0.214 sec)
INFO:tensorflow:global_step/sec: 450.036
INFO:tensorflow:step = 308500, loss = 3.3409798 (0.222 sec)
INFO:tensorflow:global_step/sec: 466.345
INFO:tensorflow:step = 308600, loss = 1.9184487 (0.215 sec)
INFO:tensorflow:global_step/sec: 458.587
INFO:tensorflow:step = 308700, loss = 1.7018256 (0.218 sec)
INFO:tensorflow:global_step/sec: 459.329
INFO:tensorflow:step = 308800, loss = 0.36313868 (0.218 sec)
INFO:tensorflow:global_step/sec: 456.596
INFO:tensorflow:step = 308900, loss = 0.2504376 (0.219 sec)
INFO:tensorflow:global_step/sec: 462.445
INFO:tensorflow:step = 309000, loss = 0.5746926 (0.216 sec)
INFO:tensorflow:global_step/sec: 462.959
INFO:tensorflow:step = 309100, loss = 1.7032282 (0.216 sec)
INFO:tensorflow:global_step/sec: 459.879
INFO:tensorflow:step = 309200, loss = 7.001949 (0.217 sec)
INFO:tensorflow:global_step/sec: 451.325
INFO:tensorflow:step = 309300, loss = 0.18353951 (0.222 sec)
INFO:tensorflow:global_step/sec: 458.018
INFO:tensorflow:step = 309400, loss = 3.4073641 (0.218 sec)
INFO:tensorflow:global_step/sec: 465.95
INFO:tensorflow:step = 309500, loss = 1.8451743 (0.215 sec)
INFO:tensorflow:global_step/sec: 463.282
INFO:tensorflow:step = 309600, loss = 0.27952737 (0.216 sec)
INFO:tensorflow:global_step/sec: 467.724
INFO:tensorflow:step = 309700, loss = 1.9611139 (0.214 sec)
INFO:tensorflow:global_step/sec: 466.523
INFO:tensorflow:step = 309800, loss = 1.5687158 (0.214 sec)
INFO:tensorflow:global_step/sec: 460.907
INFO:tensorflow:step = 309900, loss = 0.3215941 (0.217 sec)
INFO:tensorflow:global_step/sec: 462.871
INFO:tensorflow:step = 310000, loss = 0.14739172 (0.216 sec)
INFO:tensorflow:global_step/sec: 460.635
INFO:tensorflow:step = 310100, loss = 0.061620716 (0.217 sec)
INFO:tensorflow:global_step/sec: 459.323
INFO:tensorflow:step = 310200, loss = 1.3810755 (0.218 sec)
INFO:tensorflow:global_step/sec: 465.032
INFO:tensorflow:step = 310300, loss = 0.32848585 (0.215 sec)
INFO:tensorflow:global_step/sec: 460.404
INFO:tensorflow:step = 310400, loss = 0.027677307 (0.217 sec)
INFO:tensorflow:global_step/sec: 466.636
INFO:tensorflow:step = 310500, loss = 0.33544752 (0.214 sec)
INFO:tensorflow:global_step/sec: 465.929
INFO:tensorflow:step = 310600, loss = 1.125744 (0.214 sec)
INFO:tensorflow:global_step/sec: 471.69
INFO:tensorflow:step = 310700, loss = 0.8222596 (0.212 sec)
INFO:tensorflow:global_step/sec: 458.203
INFO:tensorflow:step = 310800, loss = 2.1620774 (0.219 sec)
INFO:tensorflow:global_step/sec: 467.036
INFO:tensorflow:step = 310900, loss = 0.11320391 (0.214 sec)
INFO:tensorflow:global_step/sec: 461.448
INFO:tensorflow:step = 311000, loss = 0.19821554 (0.216 sec)
INFO:tensorflow:global_step/sec: 463.354
INFO:tensorflow:step = 311100, loss = 1.5364566 (0.216 sec)
INFO:tensorflow:global_step/sec: 461.164
INFO:tensorflow:step = 311200, loss = 6.606591 (0.217 sec)
INFO:tensorflow:global_step/sec: 466.714
INFO:tensorflow:step = 311300, loss = 0.2159519 (0.214 sec)
INFO:tensorflow:global_step/sec: 464.599
INFO:tensorflow:step = 311400, loss = 0.5377669 (0.216 sec)
INFO:tensorflow:global_step/sec: 460.486
INFO:tensorflow:step = 311500, loss = 0.37682015 (0.218 sec)
INFO:tensorflow:global_step/sec: 465.254
INFO:tensorflow:step = 311600, loss = 0.11825697 (0.214 sec)
INFO:tensorflow:global_step/sec: 463.577
INFO:tensorflow:step = 311700, loss = 1.4722342 (0.215 sec)
INFO:tensorflow:global_step/sec: 465.687
INFO:tensorflow:step = 311800, loss = 1.7159263 (0.215 sec)
INFO:tensorflow:global_step/sec: 465.893
INFO:tensorflow:step = 311900, loss = 0.4829618 (0.215 sec)
INFO:tensorflow:global_step/sec: 457.375
INFO:tensorflow:step = 312000, loss = 0.012169083 (0.219 sec)
INFO:tensorflow:global_step/sec: 458.795
INFO:tensorflow:step = 312100, loss = 0.55270845 (0.218 sec)
INFO:tensorflow:global_step/sec: 456.7
INFO:tensorflow:step = 312200, loss = 0.6105227 (0.220 sec)
INFO:tensorflow:global_step/sec: 457.031
INFO:tensorflow:step = 312300, loss = 0.09295833 (0.218 sec)
INFO:tensorflow:global_step/sec: 456.95
INFO:tensorflow:step = 312400, loss = 8.81128 (0.219 sec)
INFO:tensorflow:global_step/sec: 469.088
INFO:tensorflow:step = 312500, loss = 0.26261008 (0.213 sec)
INFO:tensorflow:global_step/sec: 458.695
INFO:tensorflow:step = 312600, loss = 0.2760912 (0.218 sec)
INFO:tensorflow:global_step/sec: 454.729
INFO:tensorflow:step = 312700, loss = 0.37025392 (0.220 sec)
INFO:tensorflow:global_step/sec: 451.056
INFO:tensorflow:step = 312800, loss = 4.0906334 (0.222 sec)
INFO:tensorflow:global_step/sec: 460.095
INFO:tensorflow:step = 312900, loss = 0.821187 (0.218 sec)
INFO:tensorflow:global_step/sec: 459.939
INFO:tensorflow:step = 313000, loss = 0.7164849 (0.217 sec)
INFO:tensorflow:global_step/sec: 459.534
INFO:tensorflow:step = 313100, loss = 0.14260876 (0.218 sec)
INFO:tensorflow:global_step/sec: 460.259
INFO:tensorflow:step = 313200, loss = 1.5231879 (0.217 sec)
INFO:tensorflow:global_step/sec: 461.339
INFO:tensorflow:step = 313300, loss = 0.09379765 (0.217 sec)
INFO:tensorflow:global_step/sec: 465.369
INFO:tensorflow:step = 313400, loss = 3.0053518 (0.215 sec)
INFO:tensorflow:global_step/sec: 455.577
INFO:tensorflow:step = 313500, loss = 0.5162148 (0.220 sec)
INFO:tensorflow:global_step/sec: 454.868
INFO:tensorflow:step = 313600, loss = 0.094989255 (0.220 sec)
INFO:tensorflow:global_step/sec: 455.827
INFO:tensorflow:step = 313700, loss = 0.62853986 (0.219 sec)
INFO:tensorflow:global_step/sec: 457.384
INFO:tensorflow:step = 313800, loss = 0.41709673 (0.219 sec)
INFO:tensorflow:global_step/sec: 463.841
INFO:tensorflow:step = 313900, loss = 0.6498879 (0.216 sec)
INFO:tensorflow:Saving checkpoints for 314000 into ./mnist_model/model.ckpt.
INFO:tensorflow:Loss for final step: 0.26178497.
Out[12]:
<tensorflow.python.estimator.canned.dnn.DNNClassifier at 0x7f4c65b28da0>

Step-5: Validating the Trained Model

In [13]:
# Validation/Evaluation Input
eval_input = tf.estimator.inputs.numpy_input_fn(x={'x':X_val}, y=y_val, num_epochs=1000, batch_size=20, shuffle=False)
In [14]:
# Validate the Model Performance
dnn_model.evaluate(input_fn=eval_input)
INFO:tensorflow:Calling model_fn.
INFO:tensorflow:Done calling model_fn.
INFO:tensorflow:Starting evaluation at 2018-06-09-13:12:50
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from ./mnist_model/model.ckpt-314000
INFO:tensorflow:Running local_init_op.
INFO:tensorflow:Done running local_init_op.
INFO:tensorflow:Finished evaluation at 2018-06-09-13:30:30
INFO:tensorflow:Saving dict for global step 314000: accuracy = 0.8940909, average_loss = 0.71235186, global_step = 314000, loss = 14.247037
Out[14]:
{'accuracy': 0.8940909,
 'average_loss': 0.71235186,
 'global_step': 314000,
 'loss': 14.247037}

Step-6: Test Model Performance on Test Data

In [15]:
# Test Input
test_input = tf.estimator.inputs.numpy_input_fn(x={'x':X_test}, y=y_test, num_epochs=1, batch_size=10, shuffle=False)
In [16]:
# Predict Labels for Test Data
y_pred = dnn_model.predict(input_fn=test_input)
In [17]:
# List of Predictions
predicted_labels = list(y_pred)
INFO:tensorflow:Calling model_fn.
INFO:tensorflow:Done calling model_fn.
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from ./mnist_model/model.ckpt-314000
INFO:tensorflow:Running local_init_op.
INFO:tensorflow:Done running local_init_op.
In [18]:
predicted_labels
Out[18]:
[{'class_ids': array([9]),
  'classes': array([b'9'], dtype=object),
  'logits': array([-26.624592 , -19.360931 , -18.109446 , -19.622164 , -18.231052 ,
          -3.7047343, -35.45777  ,  -3.3021495, -14.17699  ,  15.240501 ],
        dtype=float32),
  'probabilities': array([6.5799261e-19, 9.3926615e-16, 3.2832418e-15, 7.2333204e-16,
         2.9072934e-15, 5.9181837e-09, 9.5944463e-23, 8.8517540e-09,
         1.6755045e-13, 1.0000000e+00], dtype=float32)},
 {'class_ids': array([2]),
  'classes': array([b'2'], dtype=object),
  'logits': array([ -6.683204, -19.03279 ,  17.00539 , -30.744827, -11.657295,
         -30.23733 , -23.731298, -34.82696 , -18.80138 , -25.266024],
        dtype=float32),
  'probabilities': array([5.1543506e-11, 2.2326383e-16, 1.0000000e+00, 1.8295490e-21,
         3.5641330e-13, 3.0391119e-21, 2.0336759e-18, 3.0867089e-23,
         2.8139554e-16, 4.3828578e-19], dtype=float32)},
 {'class_ids': array([1]),
  'classes': array([b'1'], dtype=object),
  'logits': array([-24.404518 ,  44.32851  , -49.390697 , -12.385275 ,   4.8761563,
         -39.198265 , -32.089146 , -43.166477 , -10.394265 , -52.780956 ],
        dtype=float32),
  'probabilities': array([1.4113132e-30, 1.0000000e+00, 0.0000000e+00, 2.3416224e-25,
         7.3461563e-18, 5.3061644e-37, 6.4898354e-34, 0.0000000e+00,
         1.7147507e-24, 0.0000000e+00], dtype=float32)},
 {'class_ids': array([1]),
  'classes': array([b'1'], dtype=object),
  'logits': array([-20.729057 ,  39.39118  , -41.644547 ,  -0.8023188,  -5.2638555,
         -28.959558 , -25.019138 , -41.68048  , -14.927917 , -42.927807 ],
        dtype=float32),
  'probabilities': array([7.7644998e-27, 1.0000000e+00, 6.4066882e-36, 3.5009522e-18,
         4.0417137e-20, 2.0684805e-30, 1.0640327e-28, 6.1805547e-36,
         2.5675360e-24, 1.7754933e-36], dtype=float32)},
 {'class_ids': array([6]),
  'classes': array([b'6'], dtype=object),
  'logits': array([  7.0127773, -23.480667 , -13.637526 , -11.146068 , -22.05953  ,
          -9.258272 ,   8.438017 , -27.276    , -14.026039 , -14.181794 ],
        dtype=float32),
  'probabilities': array([1.93841502e-01, 1.10741935e-14, 2.08513498e-10, 2.51861043e-09,
         4.58673864e-14, 1.66348819e-08, 8.06158483e-01, 2.48897402e-16,
         1.41385501e-10, 1.20993188e-10], dtype=float32)},
 {'class_ids': array([1]),
  'classes': array([b'1'], dtype=object),
  'logits': array([-19.819988 ,  34.61724  , -39.671284 ,  -7.0262957,   3.510443 ,
         -27.687746 , -25.350843 , -35.29691  ,  -8.401282 , -38.090233 ],
        dtype=float32),
  'probabilities': array([2.2814544e-24, 1.0000000e+00, 5.4563476e-33, 8.2118738e-19,
         3.0937784e-14, 8.7355204e-28, 9.0404708e-27, 4.3318025e-31,
         2.0763106e-19, 2.6518280e-32], dtype=float32)},
 {'class_ids': array([4]),
  'classes': array([b'4'], dtype=object),
  'logits': array([-37.15525  , -16.380613 ,  -3.7173793, -29.00453  ,  16.939344 ,
         -44.173416 , -12.581152 , -22.69493  , -17.96591  , -33.552692 ],
        dtype=float32),
  'probabilities': array([3.2137720e-24, 3.3831887e-15, 1.0688067e-09, 1.1138556e-20,
         1.0000000e+00, 2.8778258e-27, 1.5115110e-13, 6.1242612e-18,
         6.9317137e-16, 1.1792010e-22], dtype=float32)},
 {'class_ids': array([6]),
  'classes': array([b'6'], dtype=object),
  'logits': array([-16.022202, -23.692463,  -9.970935, -15.781093,  -4.46225 ,
         -23.369926,  10.955582, -26.013832, -14.262355, -29.475252],
        dtype=float32),
  'probabilities': array([1.9217527e-12, 8.9648972e-16, 8.1607260e-10, 2.4457348e-12,
         2.0142843e-07, 1.2377162e-15, 9.9999976e-01, 8.7980717e-17,
         1.1168345e-11, 2.7612943e-18], dtype=float32)},
 {'class_ids': array([5]),
  'classes': array([b'5'], dtype=object),
  'logits': array([-10.222782, -30.536327, -22.058416, -10.149363, -38.94569 ,
          17.449451, -18.261904, -15.290388, -11.780202, -16.762606],
        dtype=float32),
  'probabilities': array([9.5962528e-13, 1.4455763e-21, 6.9494727e-18, 1.0327313e-12,
         3.2203361e-25, 1.0000000e+00, 3.0956698e-16, 6.0432307e-15,
         2.0217305e-13, 1.3864096e-15], dtype=float32)},
 {'class_ids': array([7]),
  'classes': array([b'7'], dtype=object),
  'logits': array([-26.445284 , -16.977564 , -21.604677 , -17.707575 , -19.6526   ,
          -3.8333154, -32.172142 ,  19.446222 , -12.6327915,  -8.264458 ],
        dtype=float32),
  'probabilities': array([1.1737405e-20, 1.5182757e-16, 1.4853228e-18, 7.3166269e-17,
         1.0461565e-17, 7.7593522e-11, 3.8232264e-23, 1.0000000e+00,
         1.1702033e-14, 9.2343125e-13], dtype=float32)},
 {'class_ids': array([4]),
  'classes': array([b'4'], dtype=object),
  'logits': array([-14.544636 ,  -9.833386 ,   1.2059274, -17.69975  ,   7.429704 ,
         -19.984715 ,  -7.143113 , -17.020021 , -10.904423 , -13.523083 ],
        dtype=float32),
  'probabilities': array([2.8563088e-10, 3.1759612e-08, 1.9778258e-03, 1.2177442e-11,
         9.9802172e-01, 1.2393930e-12, 4.6800017e-07, 2.4030281e-11,
         1.0882523e-08, 7.9334128e-10], dtype=float32)},
 {'class_ids': array([5]),
  'classes': array([b'5'], dtype=object),
  'logits': array([-14.24751  , -21.821302 , -23.802053 , -19.545544 , -31.390804 ,
          18.424395 , -25.469769 , -12.071745 , -11.132126 ,  -3.7653754],
        dtype=float32),
  'probabilities': array([6.4680253e-15, 3.3228892e-18, 4.5844433e-19, 3.2349270e-17,
         2.3202414e-22, 1.0000000e+00, 8.6498057e-20, 5.6976383e-14,
         1.4580293e-13, 2.3073073e-10], dtype=float32)},
 {'class_ids': array([5]),
  'classes': array([b'5'], dtype=object),
  'logits': array([-44.751343 , -27.918156 , -28.104277 ,  -8.443188 , -33.949173 ,
          15.922576 , -41.820694 ,   5.8016887,   9.986111 , -25.054121 ],
        dtype=float32),
  'probabilities': array([4.4513168e-27, 9.1001545e-20, 7.5547174e-20, 2.6116794e-11,
         2.1868110e-22, 9.9732566e-01, 8.3416716e-26, 4.0122803e-05,
         2.6342857e-03, 1.5954529e-18], dtype=float32)},
 {'class_ids': array([3]),
  'classes': array([b'3'], dtype=object),
  'logits': array([-18.234495, -10.444492, -11.851149,  17.214655, -23.576124,
         -15.723511, -14.161603, -27.495564, -14.670075, -28.761099],
        dtype=float32),
  'probabilities': array([4.0237382e-16, 9.7226567e-13, 2.3816718e-13, 1.0000000e+00,
         1.9265917e-18, 4.9560677e-15, 2.3630010e-14, 3.8247054e-20,
         1.4211410e-14, 1.0789065e-20], dtype=float32)},
 {'class_ids': array([4]),
  'classes': array([b'4'], dtype=object),
  'logits': array([-18.975399  , -11.763992  ,   0.06607708, -24.197004  ,
          12.6106825 , -28.238846  , -12.418782  , -22.236458  ,
          -7.885646  , -25.976328  ], dtype=float32),
  'probabilities': array([1.91574255e-14, 2.59544174e-11, 3.56406485e-06, 1.03424529e-16,
         9.99996424e-01, 1.81665861e-18, 1.34846604e-11, 7.34644539e-16,
         1.25474697e-09, 1.74531238e-17], dtype=float32)},
 {'class_ids': array([1]),
  'classes': array([b'1'], dtype=object),
  'logits': array([-13.020408 ,  24.081293 , -26.92085  ,  -4.2719197,   2.933519 ,
         -18.416716 , -16.897215 , -20.663128 ,  -5.39655  , -24.760693 ],
        dtype=float32),
  'probabilities': array([7.7079072e-17, 1.0000000e+00, 7.0802791e-23, 4.8568679e-13,
         6.5409156e-10, 3.4942125e-19, 1.5968351e-18, 3.6961028e-20,
         1.5773747e-13, 6.1403666e-22], dtype=float32)},
 {'class_ids': array([2]),
  'classes': array([b'2'], dtype=object),
  'logits': array([ -7.6653023, -18.613144 ,  12.897045 , -20.280548 , -16.805834 ,
         -16.871452 ,  -8.462091 , -24.34289  , -15.246223 , -21.584606 ],
        dtype=float32),
  'probabilities': array([1.1745891e-09, 2.0668016e-14, 1.0000000e+00, 3.9008057e-15,
         1.2595156e-13, 1.1795213e-13, 5.2947424e-10, 6.7127566e-17,
         5.9914747e-13, 1.0587882e-15], dtype=float32)},
 {'class_ids': array([2]),
  'classes': array([b'2'], dtype=object),
  'logits': array([-13.393716 , -14.939782 ,   5.2041035, -18.943977 ,   3.5353637,
         -25.166489 ,  -6.205145 , -24.877008 ,  -8.843702 , -21.94471  ],
        dtype=float32),
  'probabilities': array([7.0480901e-09, 1.5018390e-09, 8.4139931e-01, 2.7392009e-11,
         1.5859067e-01, 5.4352756e-14, 9.3331564e-06, 7.2600766e-14,
         6.6698738e-07, 1.3627694e-12], dtype=float32)},
 {'class_ids': array([8]),
  'classes': array([b'8'], dtype=object),
  'logits': array([-17.435074 , -10.21949  , -23.140356 ,  -4.629963 , -18.340315 ,
          -4.291097 , -26.363771 , -13.19902  ,  18.819405 ,  -5.1031184],
        dtype=float32),
  'probabilities': array([1.7983743e-16, 2.4466301e-13, 5.9855854e-19, 6.5474036e-11,
         7.2734097e-17, 9.1883258e-11, 2.3833993e-20, 1.2432965e-14,
         1.0000000e+00, 4.0792474e-11], dtype=float32)},
 {'class_ids': array([0]),
  'classes': array([b'0'], dtype=object),
  'logits': array([  7.061627 ,  -5.238357 ,   0.6706838,  -7.1666327, -16.699192 ,
          -8.049111 ,  -2.2222972, -15.621019 , -12.08059  ,  -9.103286 ],
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  'logits': array([-11.404757, -25.702856, -15.143238, -11.962195, -10.309947,
         -17.420168,  12.623195, -25.169407, -13.91034 , -28.619726],
        dtype=float32),
  'probabilities': array([3.67107907e-11, 2.26572926e-17, 8.73355533e-13, 2.10232925e-11,
         1.09714265e-10, 8.96053251e-14, 1.00000000e+00, 3.86261351e-17,
         2.99662313e-12, 1.22582201e-18], dtype=float32)},
 {'class_ids': array([6]),
  'classes': array([b'6'], dtype=object),
  'logits': array([-18.351292 , -26.112656 , -15.810071 , -16.191795 ,  -3.9195225,
         -23.12594  ,  11.745484 , -24.704706 , -10.49293  , -36.203304 ],
        dtype=float32),
  'probabilities': array([8.4944767e-14, 3.6175881e-17, 1.0783863e-12, 7.3619680e-13,
         1.5731641e-07, 7.1702154e-16, 9.9999988e-01, 1.4787098e-16,
         2.1977542e-10, 1.5000509e-21], dtype=float32)},
 {'class_ids': array([3]),
  'classes': array([b'3'], dtype=object),
  'logits': array([-17.330004 , -11.846447 ,  -6.274291 ,  12.993745 , -14.103394 ,
         -12.9349575, -13.038375 , -19.863062 ,  -8.371333 , -21.475613 ],
        dtype=float32),
  'probabilities': array([6.7695984e-14, 1.6294542e-11, 4.2854689e-09, 1.0000000e+00,
         1.7055433e-12, 5.4866493e-12, 4.9475936e-12, 5.3761291e-15,
         5.2633775e-10, 1.0718860e-15], dtype=float32)},
 {'class_ids': array([2]),
  'classes': array([b'2'], dtype=object),
  'logits': array([-21.911827 , -23.686798 ,  14.058168 , -23.93956  ,  -6.7969856,
         -29.404781 , -10.213868 , -30.590536 , -16.646143 , -27.041794 ],
        dtype=float32),
  'probabilities': array([2.3901780e-16, 4.0510737e-17, 1.0000000e+00, 3.1462777e-17,
         8.7643898e-10, 1.3313122e-19, 2.8759942e-11, 4.0673728e-20,
         4.6268667e-14, 1.4142104e-18], dtype=float32)},
 {'class_ids': array([3]),
  'classes': array([b'3'], dtype=object),
  'logits': array([ -6.046111, -14.06991 , -21.0878  ,  20.285225, -29.69663 ,
         -16.93356 ,  -9.909226, -42.340275, -20.723314, -24.75759 ],
        dtype=float32),
  'probabilities': array([3.6681378e-12, 1.2015871e-15, 1.0762769e-18, 1.0000000e+00,
         1.9640620e-22, 6.8562605e-17, 7.7040093e-14, 6.3400261e-28,
         1.5495962e-18, 2.7425432e-20], dtype=float32)},
 {'class_ids': array([5]),
  'classes': array([b'5'], dtype=object),
  'logits': array([-24.02551  , -25.620167 , -18.076458 , -17.525557 , -28.15555  ,
          15.194006 , -33.306847 ,   7.3647337,  -1.9321651, -14.926072 ],
        dtype=float32),
  'probabilities': array([9.2684587e-18, 1.8812999e-18, 3.5534409e-15, 6.1645550e-15,
         1.4905765e-19, 9.9960226e-01, 8.6332392e-22, 3.9775667e-04,
         3.6477545e-08, 8.2955107e-14], dtype=float32)},
 {'class_ids': array([2]),
  'classes': array([b'2'], dtype=object),
  'logits': array([ -9.33598  ,  -9.705941 ,   5.285156 , -20.648514 ,   0.4971928,
         -18.858452 ,  -2.568307 , -17.904066 ,  -7.466987 , -18.944206 ],
        dtype=float32),
  'probabilities': array([4.4294543e-07, 3.0596962e-07, 9.9135405e-01, 5.4122640e-12,
         8.2573928e-03, 3.2418509e-11, 3.8504659e-04, 8.4193291e-11,
         2.8710681e-06, 2.9754341e-11], dtype=float32)},
 {'class_ids': array([9]),
  'classes': array([b'9'], dtype=object),
  'logits': array([-24.349566 , -21.071398 , -14.8635845, -24.7445   , -22.318872 ,
          -9.847402 , -41.094273 ,   2.1120696, -15.342699 ,  15.9352865],
        dtype=float32),
  'probabilities': array([3.1952955e-18, 8.4762005e-17, 4.2094004e-14, 2.1527456e-18,
         2.4346124e-17, 6.3492202e-12, 1.7075614e-25, 9.9232182e-07,
         2.6070144e-14, 9.9999905e-01], dtype=float32)},
 {'class_ids': array([0]),
  'classes': array([b'0'], dtype=object),
  'logits': array([  5.2332544 ,  -5.7446885 ,  -7.2991085 ,   4.388054  ,
         -18.865637  ,  -4.961327  ,  -0.03345198, -19.661251  ,
         -15.425387  ,  -8.9868965 ], dtype=float32),
  'probabilities': array([6.97014391e-01, 1.19009455e-05, 2.51481265e-06, 2.99347639e-01,
         2.38355863e-11, 2.60489996e-05, 3.59699829e-03, 1.07571157e-11,
         7.43545614e-10, 4.65059685e-07], dtype=float32)},
 {'class_ids': array([4]),
  'classes': array([b'4'], dtype=object),
  'logits': array([-30.7378   , -23.066454 ,   6.3729186, -34.926334 ,  14.84483  ,
         -38.390396 , -12.415724 , -29.672564 , -20.817293 , -28.969135 ],
        dtype=float32),
  'probabilities': array([1.5981751e-20, 3.4296285e-17, 2.0922096e-04, 2.4241935e-22,
         9.9979085e-01, 7.5882992e-24, 1.4481090e-12, 4.6371396e-20,
         3.2512113e-16, 9.3701385e-20], dtype=float32)},
 {'class_ids': array([7]),
  'classes': array([b'7'], dtype=object),
  'logits': array([-17.5713   , -17.891716 , -26.444233 , -13.788149 , -15.248075 ,
          -2.2911954, -17.746851 ,  16.164537 ,  -3.5015554, -11.763952 ],
        dtype=float32),
  'probabilities': array([2.2320860e-15, 1.6201599e-15, 3.1278457e-19, 9.8110078e-14,
         2.2786391e-14, 9.6555555e-09, 1.8727126e-15, 1.0000000e+00,
         2.8782254e-09, 7.4269589e-13], dtype=float32)},
 {'class_ids': array([7]),
  'classes': array([b'7'], dtype=object),
  'logits': array([-23.325466 , -18.447058 , -19.04484  , -13.637037 , -17.377853 ,
          -7.9884963, -23.344053 ,  17.99044  , -14.775355 , -10.066398 ],
        dtype=float32),
  'probabilities': array([1.1395406e-18, 1.4975966e-16, 8.2372637e-17, 1.8380654e-14,
         4.3625977e-16, 5.2178422e-12, 1.1185533e-18, 1.0000000e+00,
         5.8883727e-15, 6.5323533e-13], dtype=float32)},
 ...]
In [19]:
for preds in predicted_labels:
    print(preds['probabilities'])
[6.5799261e-19 9.3926615e-16 3.2832418e-15 7.2333204e-16 2.9072934e-15
 5.9181837e-09 9.5944463e-23 8.8517540e-09 1.6755045e-13 1.0000000e+00]
[5.1543506e-11 2.2326383e-16 1.0000000e+00 1.8295490e-21 3.5641330e-13
 3.0391119e-21 2.0336759e-18 3.0867089e-23 2.8139554e-16 4.3828578e-19]
[1.4113132e-30 1.0000000e+00 0.0000000e+00 2.3416224e-25 7.3461563e-18
 5.3061644e-37 6.4898354e-34 0.0000000e+00 1.7147507e-24 0.0000000e+00]
[7.7644998e-27 1.0000000e+00 6.4066882e-36 3.5009522e-18 4.0417137e-20
 2.0684805e-30 1.0640327e-28 6.1805547e-36 2.5675360e-24 1.7754933e-36]
[1.93841502e-01 1.10741935e-14 2.08513498e-10 2.51861043e-09
 4.58673864e-14 1.66348819e-08 8.06158483e-01 2.48897402e-16
 1.41385501e-10 1.20993188e-10]
[2.2814544e-24 1.0000000e+00 5.4563476e-33 8.2118738e-19 3.0937784e-14
 8.7355204e-28 9.0404708e-27 4.3318025e-31 2.0763106e-19 2.6518280e-32]
[3.2137720e-24 3.3831887e-15 1.0688067e-09 1.1138556e-20 1.0000000e+00
 2.8778258e-27 1.5115110e-13 6.1242612e-18 6.9317137e-16 1.1792010e-22]
[1.9217527e-12 8.9648972e-16 8.1607260e-10 2.4457348e-12 2.0142843e-07
 1.2377162e-15 9.9999976e-01 8.7980717e-17 1.1168345e-11 2.7612943e-18]
[9.5962528e-13 1.4455763e-21 6.9494727e-18 1.0327313e-12 3.2203361e-25
 1.0000000e+00 3.0956698e-16 6.0432307e-15 2.0217305e-13 1.3864096e-15]
[1.1737405e-20 1.5182757e-16 1.4853228e-18 7.3166269e-17 1.0461565e-17
 7.7593522e-11 3.8232264e-23 1.0000000e+00 1.1702033e-14 9.2343125e-13]
[2.8563088e-10 3.1759612e-08 1.9778258e-03 1.2177442e-11 9.9802172e-01
 1.2393930e-12 4.6800017e-07 2.4030281e-11 1.0882523e-08 7.9334128e-10]
[6.4680253e-15 3.3228892e-18 4.5844433e-19 3.2349270e-17 2.3202414e-22
 1.0000000e+00 8.6498057e-20 5.6976383e-14 1.4580293e-13 2.3073073e-10]
[4.4513168e-27 9.1001545e-20 7.5547174e-20 2.6116794e-11 2.1868110e-22
 9.9732566e-01 8.3416716e-26 4.0122803e-05 2.6342857e-03 1.5954529e-18]
[4.0237382e-16 9.7226567e-13 2.3816718e-13 1.0000000e+00 1.9265917e-18
 4.9560677e-15 2.3630010e-14 3.8247054e-20 1.4211410e-14 1.0789065e-20]
[1.91574255e-14 2.59544174e-11 3.56406485e-06 1.03424529e-16
 9.99996424e-01 1.81665861e-18 1.34846604e-11 7.34644539e-16
 1.25474697e-09 1.74531238e-17]
[7.7079072e-17 1.0000000e+00 7.0802791e-23 4.8568679e-13 6.5409156e-10
 3.4942125e-19 1.5968351e-18 3.6961028e-20 1.5773747e-13 6.1403666e-22]
[1.1745891e-09 2.0668016e-14 1.0000000e+00 3.9008057e-15 1.2595156e-13
 1.1795213e-13 5.2947424e-10 6.7127566e-17 5.9914747e-13 1.0587882e-15]
[7.0480901e-09 1.5018390e-09 8.4139931e-01 2.7392009e-11 1.5859067e-01
 5.4352756e-14 9.3331564e-06 7.2600766e-14 6.6698738e-07 1.3627694e-12]
[1.7983743e-16 2.4466301e-13 5.9855854e-19 6.5474036e-11 7.2734097e-17
 9.1883258e-11 2.3833993e-20 1.2432965e-14 1.0000000e+00 4.0792474e-11]
[9.9822789e-01 4.5437509e-06 1.6737030e-03 6.6065519e-07 4.7867123e-11
 2.7335011e-07 9.2741197e-05 1.4069601e-10 4.8514344e-09 9.5257043e-08]
[4.2589878e-08 3.6334656e-13 1.0000000e+00 1.6252259e-12 8.3813945e-12
 2.2509351e-12 9.4691388e-10 9.9337292e-16 4.2406580e-09 2.5860326e-11]
[5.4990672e-11 5.4817294e-13 1.4027274e-12 7.4828070e-14 2.5761093e-17
 9.9990451e-01 1.3193868e-17 9.4938652e-05 3.5242781e-08 5.1596822e-07]
[3.11510857e-24 1.26016425e-17 2.17700305e-17 2.90802399e-16
 1.20919181e-16 1.55036595e-09 1.91296018e-21 1.00000000e+00
 8.40841407e-14 2.55511823e-12]
[1.0624303e-13 7.6383626e-16 3.5113338e-16 5.7012216e-15 1.6639401e-17
 9.9999976e-01 1.1251434e-18 8.6731667e-08 9.8634159e-09 1.1572622e-07]
[3.0188097e-29 1.0000000e+00 2.6613777e-37 2.6402652e-21 7.6445948e-18
 1.5290851e-33 8.7082006e-29 1.0326414e-37 4.2729367e-22 0.0000000e+00]
[6.4153499e-10 7.1005934e-09 1.8131347e-01 7.9513124e-10 8.1861365e-01
 3.5691256e-11 7.2755895e-05 2.8157232e-09 6.2883572e-08 5.3558413e-10]
[2.19468221e-09 1.64869967e-08 5.40167652e-02 1.13299634e-10
 1.66798886e-02 6.39744369e-11 9.29301739e-01 1.44888115e-10
 1.52289135e-06 1.53933764e-13]
[9.9976522e-01 1.9194699e-09 2.1374313e-12 2.0416064e-06 1.3049741e-12
 8.3639629e-10 2.3274959e-04 5.5476901e-13 1.4469213e-11 2.4379315e-10]
[2.6557631e-24 4.4420333e-19 1.4206319e-18 4.5846930e-22 1.3093425e-17
 1.2237843e-13 5.6881786e-31 5.4664601e-05 1.3606590e-18 9.9994528e-01]
[1.8544776e-02 1.3915023e-04 3.0045933e-04 9.5258087e-01 1.4086523e-03
 3.2318074e-03 1.6100269e-02 1.5714825e-06 7.4289162e-03 2.6346633e-04]
[0.0000000e+00 1.0746759e-27 0.0000000e+00 1.6690618e-20 4.7363730e-29
 2.4996180e-22 1.5828339e-38 1.0069044e-32 1.0000000e+00 8.0142525e-32]
[1.1554579e-23 1.7328201e-17 7.2368069e-21 2.6675674e-11 2.7557339e-14
 1.7603533e-13 1.9238271e-29 4.0940007e-23 1.0000000e+00 8.6933198e-24]
[1.7789478e-11 3.0173396e-06 3.7379930e-08 9.9999702e-01 2.1897550e-11
 4.6242796e-09 3.8378521e-14 8.7936181e-17 8.1284235e-10 9.7113463e-12]
[5.3760161e-08 1.1308617e-08 9.2756009e-06 9.9941480e-01 1.1966691e-07
 3.6447717e-10 5.7443435e-04 3.9337361e-10 1.1801885e-06 2.9858938e-11]
[0.0000000e+00 1.0754858e-31 0.0000000e+00 1.4394840e-22 1.9721879e-27
 1.6230314e-21 0.0000000e+00 3.7720819e-34 1.0000000e+00 0.0000000e+00]
[1.0000000e+00 1.1696392e-17 2.5746216e-13 9.1390410e-14 1.1383886e-19
 1.0241968e-11 6.1504526e-09 1.1604222e-24 1.1875571e-14 3.5088493e-13]
[8.4865248e-18 5.7547209e-12 3.5579606e-12 1.4002255e-12 1.0811825e-17
 1.2322778e-11 7.8570389e-21 1.0000000e+00 7.0166376e-15 2.2197940e-12]
[1.4244960e-13 7.2797586e-19 3.0998549e-15 1.2956714e-12 5.9950791e-23
 1.0000000e+00 4.5932728e-16 5.6399097e-11 2.0054253e-11 6.4583209e-12]
[1.99347905e-28 4.10794597e-20 1.97400230e-19 1.10831176e-20
 3.73738379e-23 9.89181393e-12 1.76907017e-29 1.00000000e+00
 3.36600910e-19 1.92001273e-16]
[3.7315475e-28 2.3397093e-27 2.7176561e-25 2.3323028e-28 9.4274548e-29
 1.6915949e-17 1.2811905e-33 1.3664215e-14 3.8436055e-26 1.0000000e+00]
[9.9914384e-01 5.4987503e-19 3.4509572e-14 7.9033960e-16 2.1198904e-21
 1.4741366e-12 8.5610041e-04 3.4140774e-22 3.3998585e-15 5.0330315e-14]
[4.2779791e-28 1.0000000e+00 1.5251290e-34 2.1450726e-20 2.4581716e-15
 1.6701497e-29 4.9955890e-29 6.2661131e-36 8.1998808e-20 3.7054061e-35]
[1.4736156e-02 2.4709583e-05 6.2876147e-06 3.2106144e-03 5.4836776e-03
 6.3366053e-07 9.7589546e-01 1.4380577e-06 6.4072141e-04 4.2000602e-07]
[6.4664329e-23 4.4293957e-17 5.1617410e-18 1.3213289e-17 3.6299067e-20
 1.8971741e-06 1.8708477e-28 9.9979609e-01 7.2129218e-15 2.0204602e-04]
[4.2500727e-09 1.5131774e-09 7.7429856e-04 9.0812545e-11 8.5570607e-03
 7.3090102e-12 9.9066848e-01 2.9189824e-11 9.4769476e-08 1.1225542e-13]
[9.9124852e-15 3.8461042e-13 5.1311354e-11 1.4731629e-11 7.1729732e-15
 4.7133395e-05 1.8025328e-17 9.9995279e-01 4.3471573e-09 1.3711501e-07]
[2.8312357e-07 2.5281886e-06 9.9752420e-01 7.6846993e-07 1.4907782e-04
 8.4752187e-08 2.2050489e-03 1.9512884e-08 1.1789900e-04 3.4576644e-08]
[5.8444663e-15 1.0000000e+00 1.2602687e-19 2.4893243e-09 1.5108446e-10
 5.6349497e-16 3.5662201e-17 2.5199763e-19 1.0924891e-12 1.9621703e-19]
[2.0867086e-12 1.6438314e-13 9.6039319e-01 2.3988228e-10 4.6846051e-07
 4.4334168e-11 3.9606348e-02 3.5562827e-14 1.0928850e-09 5.9361882e-15]
[2.5557929e-06 1.8663955e-09 1.4363655e-01 1.3237925e-10 2.2462523e-07
 1.3463362e-09 8.5636044e-01 2.2962879e-13 3.0702131e-07 9.4195172e-12]
[1.5427479e-14 1.6080909e-11 1.0934951e-09 3.5794690e-19 9.9999762e-01
 1.2001068e-19 2.4073372e-06 2.0899472e-14 1.9278154e-10 3.8842004e-20]
[8.4155447e-11 2.1804700e-11 9.9831271e-01 1.3875476e-13 1.3459392e-03
 3.0581176e-14 3.4135123e-04 1.5367358e-14 3.2375056e-09 3.3445973e-13]
[1.1116643e-11 1.2127540e-12 4.4748211e-12 2.9582305e-11 1.9003046e-18
 9.9999833e-01 2.2026120e-16 1.6477735e-06 3.0403431e-09 4.1153263e-09]
[3.2863388e-14 2.9777925e-12 9.5107003e-17 1.5365180e-09 5.7886569e-17
 2.1824228e-11 1.3335826e-14 6.8696269e-13 1.0000000e+00 3.7589074e-09]
[7.2953888e-13 9.8519847e-13 9.9999785e-01 5.1165482e-12 2.1779513e-06
 1.5988465e-14 8.2901563e-10 2.3222913e-14 2.9803490e-12 7.6344562e-13]
[2.2040358e-09 1.5850241e-12 9.9954623e-01 1.0202675e-16 1.7749685e-10
 8.0674528e-14 4.5378963e-04 2.0660279e-15 1.2862875e-12 3.8084969e-15]
[1.42148217e-22 1.32479656e-20 7.03923784e-30 1.36610744e-16
 6.07923547e-21 2.05172160e-19 8.65979569e-23 2.03238337e-23
 1.00000000e+00 5.44567739e-19]
[7.5712640e-13 4.7680151e-11 5.3177644e-02 4.4107005e-12 8.7783355e-01
 1.8129412e-14 6.8988882e-02 2.3307451e-11 2.4545537e-09 2.0996549e-13]
[1.1388881e-19 1.8333218e-21 3.2296795e-29 1.0736874e-14 1.4748247e-21
 5.2906809e-15 2.1288322e-22 5.6945105e-21 1.0000000e+00 8.3999580e-16]
[9.9990594e-01 2.6465587e-15 3.8345561e-13 7.8757010e-13 3.4011098e-18
 2.6511770e-11 9.4011681e-05 1.0755881e-19 1.2965765e-14 1.2731476e-12]
[1.4366305e-16 1.1876665e-13 2.4105541e-14 1.2826944e-14 4.5176490e-15
 3.9907967e-08 5.9708078e-19 1.0000000e+00 1.3441465e-11 8.9631781e-11]
[5.6162455e-20 4.1549184e-16 1.6531342e-17 1.1905052e-14 2.4414075e-14
 1.2498572e-07 2.3958979e-19 9.9999988e-01 5.4115504e-11 2.0395634e-08]
[2.5898786e-29 1.6386755e-16 1.1467479e-27 6.1977581e-16 6.6976808e-20
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[9.9998963e-01 1.2562200e-10 5.8193676e-11 6.7318091e-08 1.4415734e-15
 3.3602024e-11 1.0201858e-05 1.7365807e-17 2.1075113e-14 2.4935286e-12]
[0.0000000e+00 5.8900865e-28 0.0000000e+00 1.8511142e-22 4.5446055e-26
 1.3178418e-26 0.0000000e+00 1.4718394e-37 1.0000000e+00 0.0000000e+00]
[2.3857572e-06 1.7853752e-07 9.9976677e-01 5.0333615e-08 2.0447636e-05
 7.2530981e-09 2.1007464e-04 5.6414824e-09 1.6076265e-07 2.6865170e-09]
[4.66253994e-07 4.45878595e-06 1.82773838e-10 2.50554812e-13
 2.00818664e-13 2.14520749e-02 1.48409420e-17 6.13175399e-10
 1.08515475e-14 9.78543043e-01]
[2.8835675e-01 1.6112170e-05 1.1609030e-02 2.1307745e-03 1.9210429e-09
 1.4465624e-03 6.9643062e-01 1.1564475e-10 5.3467653e-07 9.5554806e-06]
[1.5058862e-23 1.1870955e-21 1.7600058e-19 1.9076823e-23 6.4424695e-21
 3.1638169e-15 6.3319497e-29 7.1111694e-10 1.5254358e-21 1.0000000e+00]
[1.6094479e-01 8.0515870e-09 5.7910674e-04 1.1964728e-11 2.1850743e-11
 4.1766899e-11 8.3847612e-01 8.1826046e-14 1.5190714e-08 2.9385001e-11]
[1.00000000e+00 4.43791976e-13 7.05237557e-09 4.30085698e-12
 7.04739816e-17 5.56345822e-13 1.48764878e-09 8.68600793e-21
 1.32626445e-14 4.89421160e-14]
[1.2040619e-19 9.1184560e-14 4.3374965e-07 1.6889471e-21 9.9999952e-01
 1.4163974e-24 1.5490551e-10 4.7068562e-19 1.7938770e-14 1.0172170e-22]
[2.1963968e-25 1.0000000e+00 4.0952163e-32 1.4311474e-19 2.3947986e-14
 1.8044861e-28 1.6887118e-26 1.4092567e-32 2.7624960e-18 2.9119840e-33]
[1.2846123e-11 3.7694647e-13 9.9999714e-01 5.2523205e-14 5.1745864e-08
 6.7364181e-16 2.6468124e-06 2.6047092e-17 9.2497345e-08 1.0990569e-12]
[2.0705183e-14 1.5265402e-23 4.2782102e-12 1.8064186e-16 4.3123641e-16
 1.7090753e-17 1.0000000e+00 1.9166772e-22 8.4101266e-15 7.7700827e-24]
[1.6032307e-10 5.3645222e-10 2.3957416e-03 5.5105204e-10 9.8667997e-01
 3.3772594e-12 1.0924378e-02 1.0966108e-09 4.3027297e-09 2.6770317e-10]
[5.0692353e-22 2.2684108e-20 3.1394940e-34 4.8364372e-28 1.0768653e-34
 9.7219354e-01 0.0000000e+00 1.7225217e-25 9.5512988e-23 2.7806396e-02]
[4.7488406e-28 1.0000000e+00 7.5283332e-36 3.7169154e-20 1.5930532e-15
 4.2425164e-29 2.8132606e-29 2.4103916e-34 3.3426314e-19 6.2706627e-34]
[7.0292859e-14 2.1830523e-14 6.0924565e-10 2.3796376e-13 1.0000000e+00
 1.0357986e-20 3.7924648e-21 1.7981989e-20 5.0928020e-12 1.2748186e-18]
[4.0029052e-22 2.7880218e-17 4.5889880e-21 3.6412838e-21 1.2110741e-18
 1.0952964e-10 7.0091738e-30 1.3560959e-10 1.1468101e-18 1.0000000e+00]
[4.1613776e-16 7.8901966e-15 1.1912279e-15 5.7929238e-17 8.0451676e-16
 5.6642613e-05 5.3117858e-19 9.9994338e-01 2.7466734e-10 2.9023978e-11]
[1.3376339e-09 2.0574546e-06 7.9994206e-10 7.4029767e-06 5.1731575e-09
 2.2888135e-07 1.3212801e-14 1.6899142e-10 9.9999034e-01 1.7057058e-08]
[1.1428824e-13 4.6387052e-15 1.0000000e+00 2.8900741e-17 6.2705829e-14
 2.7909191e-15 7.8929208e-10 1.6569855e-17 1.5528488e-13 1.4685553e-19]
[2.3202217e-12 1.1168055e-17 7.3852924e-11 1.7581567e-15 2.8559489e-07
 2.5414207e-16 9.9999976e-01 8.0675034e-16 2.4921575e-11 3.7111786e-19]
[2.1365403e-01 9.5789142e-07 1.4330356e-04 1.2345312e-05 4.6036217e-10
 5.5269552e-06 7.8618300e-01 4.3390458e-10 3.5395138e-07 4.9225616e-07]
[3.9136471e-21 3.8093736e-15 2.1843372e-15 3.6980839e-19 2.9977091e-15
 3.4823472e-08 6.5881497e-26 3.0332705e-02 5.5286688e-15 9.6966726e-01]
[2.1289083e-19 1.0593134e-15 4.6290665e-17 1.8849901e-15 1.5864613e-15
 1.5978775e-10 9.3970141e-20 1.0000000e+00 3.1087988e-13 8.1272922e-12]
[2.5264586e-23 1.4710350e-17 2.4686030e-22 1.6912703e-12 4.8830519e-21
 1.2745435e-15 1.0535738e-24 1.5086016e-21 1.0000000e+00 1.9065841e-15]
[7.5823785e-27 1.4635738e-32 1.1707837e-29 1.9683697e-27 8.1422352e-38
 1.0000000e+00 1.6280825e-32 1.8732985e-15 2.0477749e-17 1.5650487e-17]
[9.9979752e-01 8.3074386e-18 3.6953051e-16 4.5112516e-18 1.1564110e-21
 2.5733392e-17 2.0248398e-04 5.7160528e-22 1.7120567e-17 4.7496989e-17]
[9.7485887e-30 6.5124548e-26 3.4212515e-24 2.9589305e-29 1.7518027e-24
 4.9894439e-19 7.3488279e-38 1.7628777e-12 4.8223062e-25 1.0000000e+00]
[1.9338906e-02 2.6065152e-07 3.3964352e-07 1.2619722e-08 2.1184067e-11
 3.9705932e-09 9.8066050e-01 1.7077076e-13 2.3633720e-10 8.3227830e-10]
[9.9999988e-01 2.9236491e-14 2.3812177e-09 1.2244651e-13 2.7379252e-18
 1.5901200e-12 1.0256747e-07 3.8639169e-21 2.8749365e-14 4.5218516e-13]
[9.9675912e-01 1.7166555e-09 4.0501348e-08 1.3691640e-06 1.5951264e-16
 2.8155043e-07 3.2391753e-03 2.7257301e-13 2.3860851e-11 4.5537734e-09]
[4.7781203e-18 6.0177159e-16 9.2343277e-21 1.6649463e-14 3.6693541e-20
 1.1160829e-15 1.7186713e-19 6.7807498e-18 1.0000000e+00 2.7886994e-12]
[1.0252038e-29 1.0000000e+00 0.0000000e+00 1.2384200e-23 2.8881137e-16
 6.3245505e-33 3.3206608e-32 2.7690965e-36 9.3594724e-23 6.5857384e-38]
[4.1294611e-06 1.4778574e-06 1.3163401e-10 9.9999428e-01 1.1657685e-13
 2.5563092e-11 9.1392955e-08 1.9693853e-14 3.3591248e-13 1.4538353e-14]
[2.8401279e-01 1.2171593e-08 7.1598721e-01 3.0066876e-09 3.9359847e-15
 2.3758648e-09 5.2701787e-10 9.9778873e-11 6.3144432e-09 8.7437644e-15]
[3.0204740e-18 1.7553375e-13 8.2772404e-16 1.9159885e-16 2.3176014e-14
 1.5105429e-09 1.1351140e-20 1.0000000e+00 2.5341933e-13 8.2781343e-10]
[4.1949967e-35 0.0000000e+00 7.2674247e-38 2.6851667e-31 0.0000000e+00
 1.0000000e+00 0.0000000e+00 2.7037387e-32 2.8163465e-26 1.2059776e-22]
[7.0220414e-24 2.6462472e-19 7.0669112e-26 7.6099541e-15 5.9818785e-22
 4.9688643e-15 3.9237673e-26 1.5029143e-22 1.0000000e+00 5.3429391e-18]
[1.9395315e-25 6.8529442e-21 9.9957937e-01 6.5690843e-19 4.2057881e-04
 6.9283889e-27 1.2734494e-10 8.2726286e-22 1.0182478e-17 1.4151040e-19]
[0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00
 1.0000000e+00 0.0000000e+00 7.2662105e-29 8.1009033e-31 1.3541381e-23]
[4.7431204e-01 6.9527127e-16 1.9639332e-08 4.7469553e-13 2.3779459e-23
 1.3546803e-08 5.2568793e-01 4.5512533e-24 1.5820482e-16 7.5521991e-15]
[0.0000000e+00 1.9707213e-27 0.0000000e+00 5.2561931e-18 5.0521776e-23
 1.3517396e-21 0.0000000e+00 2.4555225e-35 1.0000000e+00 0.0000000e+00]
[1.6118633e-29 1.1050897e-29 3.7141082e-28 1.3720082e-32 1.3638750e-29
 1.5391486e-21 0.0000000e+00 4.2362169e-18 2.0639966e-29 1.0000000e+00]
[4.1971652e-24 1.0000000e+00 6.1915228e-30 8.0633480e-17 1.1974010e-14
 1.4959967e-25 1.1675392e-25 6.8548262e-31 5.2872632e-18 1.0041590e-30]
[7.5199349e-33 8.3124754e-27 1.2682736e-28 1.6196190e-34 5.3680020e-27
 2.1863147e-18 0.0000000e+00 3.4439579e-16 8.5686071e-31 1.0000000e+00]
[1.7719041e-17 1.0000000e+00 3.3449732e-22 6.2318744e-12 1.8611959e-12
 2.2329062e-20 6.3182082e-18 7.7984151e-23 4.3887229e-15 1.0036068e-24]
[1.0494901e-17 5.0212859e-14 2.4689897e-14 4.1352717e-09 1.6552052e-08
 1.0538300e-11 3.3866794e-20 6.3450730e-16 1.0000000e+00 1.0689771e-18]
[3.0815794e-23 1.0000000e+00 4.1464978e-30 2.1324971e-15 2.5353961e-14
 6.5515353e-23 7.2047302e-25 2.5624302e-30 9.7999900e-18 3.7925401e-27]
[1.1211655e-14 6.7571443e-19 2.2333292e-15 3.4392414e-14 3.0973308e-19
 9.9999988e-01 1.5366104e-18 3.5877406e-08 6.6741670e-08 1.4096733e-13]
In [20]:
final_preds = []

for preds in predicted_labels:
    max_val = max(preds['probabilities'])
    label_val = np.where(preds['probabilities'] == max_val)
    print(label_val[0][0])
    final_preds.append(label_val[0][0])
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In [21]:
# Final Predicted Labels as Numpy Array
final_preds = np.array(final_preds).astype(np.int32)
In [22]:
# Predicted Labels
final_preds
Out[22]:
array([9, 2, 1, ..., 8, 1, 5], dtype=int32)
In [23]:
# Test Labels
y_test
Out[23]:
array([9, 2, 1, ..., 8, 1, 5], dtype=int32)

Step-7: Get Model Performance Metrics

In [24]:
# Import Dependencies for Model Performance
from sklearn.metrics import mean_squared_error, classification_report
In [25]:
# Root Mean Squared Error
mean_squared_error(y_test,final_preds)**0.5
Out[25]:
1.2236829654775783
In [26]:
# Classification Report for the Model
print('Classification Report: \n',classification_report(y_test, final_preds))
Classification Report: 
              precision    recall  f1-score   support

          0       0.83      0.85      0.84      1000
          1       0.98      0.97      0.98      1000
          2       0.79      0.83      0.81      1000
          3       0.89      0.91      0.90      1000
          4       0.82      0.83      0.83      1000
          5       0.96      0.97      0.97      1000
          6       0.76      0.68      0.72      1000
          7       0.94      0.96      0.95      1000
          8       0.96      0.98      0.97      1000
          9       0.97      0.95      0.96      1000

avg / total       0.89      0.89      0.89     10000

In [27]:
# Fashion MNIST labels
fashion_mnist_labels = {0:'T-shirt/Top' , 1:'Trouser', 2:'Pullover', 3:'Dress', 4:'Coat' , 5:'Sandal', 6:'Shirt', 7: 'Sneaker', 8: 'Bag' ,9: 'Ankle Boot'}
In [28]:
X_test.shape
Out[28]:
(10000, 784)

Step-8: Plot Predicted Labels with Test Labels

In [29]:
# Select N random samples from Test Data to Plot
n = np.random.randint(0, X_test.shape[0], 32)
In [30]:
# Plot Final Predictions with Test Labels
fig = plt.figure(figsize=(20,8))

for i in range(len(n)):
    ax = fig.add_subplot(4, 8, i + 1, xticks=[], yticks=[])
    ax.imshow(np.squeeze(X_test[i].reshape(28,28)))
    pred_idx = final_preds[i]
    true_idx = y_test[i]
    ax.set_title("{} ({})".format(fashion_mnist_labels[pred_idx], fashion_mnist_labels[true_idx]), color=("green" if pred_idx == true_idx else "red"))