In [1]:
%pylab inline
pylab.rcParams['figure.figsize'] = (10, 6)
from tensorflow.contrib import learn
from sklearn.metrics import mean_squared_error
from lstm import lstm_model, load_csvdata
from datetime import datetime
import Predictors as predictors
import stock_tools as st
import matplotlib.pyplot as plt
import pandas as pd
Populating the interactive namespace from numpy and matplotlib
This is a test of a LSTM memory deep learning model to predict the SPY. It is written using tensorflow and is the process of being updated to tensrflow 1.0 The memory modules and the number of nodes have not be tuned, so predictions can be made better. At the moment only a small subset of the data is used due to the computational constraints.
In the future more predictors should be introduced as this will aid precission.
In [2]:
# Create a template with the available variables
interest = 'SPY'
start_date = datetime.strptime('2000-01-01', '%Y-%m-%d')
end_date = datetime.strptime('2010-12-31', '%Y-%m-%d')
# Get the data and correct for fluctuations
data = st.get_data(start_date, end_date, from_file=True)
corr_data = st.ohlc_adj(data)
# Create a predictors class which we will base our decisions from
pred = predictors.Predictors(corr_data)
# The data is far too noisy to make accurate predictions.
# We apply a 5 day exponential rolling filter. This should preserve
# shape and reduce noise.
pred.e_filter(5)
In [6]:
# Setup the default vairables
LOG_DIR = '.opt_logs/lstm_stock'
TIMESTEPS = 20
RNN_LAYERS = [{'num_units': 5}]
DENSE_LAYERS = [10, 10]
TRAINING_STEPS = 100000
BATCH_SIZE = 100
PRINT_STEPS = TRAINING_STEPS / 100
LEARNING_RATE= 0.01
# We want to predict the Closing price. Not too much data
close = pred.data.Close.ix[(len(pred.props)-252*2):]
# Split the data into test and train
X, y = load_csvdata(close, TIMESTEPS, seperate=False)
In [7]:
# Create an regression model based on LSTM architecture
regressor = learn.Estimator(model_fn=lstm_model(TIMESTEPS, RNN_LAYERS, DENSE_LAYERS,
learning_rate=LEARNING_RATE, optimizer="Adagrad"),
model_dir=LOG_DIR)
# create a lstm instance and validation monitor
validation_monitor = learn.monitors.ValidationMonitor(X['val'], y['val'],
every_n_steps=PRINT_STEPS,
early_stopping_rounds=1000)
# Fit the data to the models
regressor.fit(X['train'], y['train'],
monitors=[validation_monitor],
batch_size=BATCH_SIZE,
steps=TRAINING_STEPS)
INFO:tensorflow:Using default config.
INFO:tensorflow:Using config: {'_task_type': None, '_save_checkpoints_secs': 600, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x10369ad30>, '_tf_config': gpu_options {
per_process_gpu_memory_fraction: 1
}
, '_environment': 'local', '_keep_checkpoint_max': 5, '_save_summary_steps': 100, '_num_ps_replicas': 0, '_is_chief': True, '_task_id': 0, '_tf_random_seed': None, '_evaluation_master': '', '_save_checkpoints_steps': None, '_keep_checkpoint_every_n_hours': 10000, '_master': ''}
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:322: BaseMonitor.__init__ (from tensorflow.contrib.learn.python.learn.monitors) is deprecated and will be removed after 2016-12-05.
Instructions for updating:
Monitors are deprecated. Please use tf.train.SessionRunHook.
WARNING:tensorflow:From <ipython-input-7-5632e25cd73d>:14: calling BaseEstimator.fit (from tensorflow.contrib.learn.python.learn.estimators.estimator) with y is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From <ipython-input-7-5632e25cd73d>:14: calling BaseEstimator.fit (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From <ipython-input-7-5632e25cd73d>:14: calling BaseEstimator.fit (from tensorflow.contrib.learn.python.learn.estimators.estimator) with batch_size is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
est = Estimator(...) -> est = SKCompat(Estimator(...))
/anaconda/lib/python3.5/site-packages/tensorflow/python/util/deprecation.py:247: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.
equality = a == b
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/models.py:107: mean_squared_error_regressor (from tensorflow.contrib.learn.python.learn.ops.losses_ops) is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Use `tf.contrib.losses.mean_squared_error` and explicit logits computation.
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/ops/losses_ops.py:39: mean_squared_error (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.
Instructions for updating:
Use tf.losses.mean_squared_error instead.
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/losses/python/losses/loss_ops.py:530: compute_weighted_loss (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.
Instructions for updating:
Use tf.losses.compute_weighted_loss instead.
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/losses/python/losses/loss_ops.py:151: add_loss (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.
Instructions for updating:
Use tf.losses.add_loss instead.
INFO:tensorflow:Create CheckpointSaverHook.
INFO:tensorflow:Saving checkpoints for 339006 into .opt_logs/lstm_stock/model.ckpt.
INFO:tensorflow:step = 339006, loss = 0.806717
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with y is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/models.py:107: mean_squared_error_regressor (from tensorflow.contrib.learn.python.learn.ops.losses_ops) is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Use `tf.contrib.losses.mean_squared_error` and explicit logits computation.
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/ops/losses_ops.py:39: mean_squared_error (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.
Instructions for updating:
Use tf.losses.mean_squared_error instead.
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/losses/python/losses/loss_ops.py:530: compute_weighted_loss (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.
Instructions for updating:
Use tf.losses.compute_weighted_loss instead.
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/losses/python/losses/loss_ops.py:151: add_loss (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.
Instructions for updating:
Use tf.losses.add_loss instead.
INFO:tensorflow:Starting evaluation at 2017-04-09-09:21:17
INFO:tensorflow:Finished evaluation at 2017-04-09-09:21:20
INFO:tensorflow:Saving dict for global step 339006: global_step = 339006, loss = 0.25423
WARNING:tensorflow:Skipping summary for global_step, must be a float or np.float32.
INFO:tensorflow:Validation (step 339006): loss = 0.25423, global_step = 339006
INFO:tensorflow:global_step/sec: 5.17287
INFO:tensorflow:step = 339106, loss = 0.582741
INFO:tensorflow:global_step/sec: 106.13
INFO:tensorflow:step = 339206, loss = 0.528766
INFO:tensorflow:global_step/sec: 91.9155
INFO:tensorflow:step = 339306, loss = 0.273415
INFO:tensorflow:global_step/sec: 102.148
INFO:tensorflow:step = 339406, loss = 0.919193
INFO:tensorflow:global_step/sec: 115.209
INFO:tensorflow:step = 339506, loss = 0.513935
INFO:tensorflow:global_step/sec: 114.399
INFO:tensorflow:step = 339606, loss = 0.670143
INFO:tensorflow:global_step/sec: 114.766
INFO:tensorflow:step = 339706, loss = 0.435021
INFO:tensorflow:global_step/sec: 113.334
INFO:tensorflow:step = 339806, loss = 0.454065
INFO:tensorflow:global_step/sec: 111.879
INFO:tensorflow:step = 339906, loss = 0.580047
INFO:tensorflow:global_step/sec: 102.983
INFO:tensorflow:step = 340006, loss = 0.546571
INFO:tensorflow:global_step/sec: 113.181
INFO:tensorflow:step = 340106, loss = 0.614448
INFO:tensorflow:global_step/sec: 115.903
INFO:tensorflow:step = 340206, loss = 0.560771
INFO:tensorflow:global_step/sec: 111.747
INFO:tensorflow:step = 340306, loss = 0.629022
INFO:tensorflow:global_step/sec: 116.741
INFO:tensorflow:step = 340406, loss = 0.44038
INFO:tensorflow:global_step/sec: 115.986
INFO:tensorflow:step = 340506, loss = 0.408515
INFO:tensorflow:global_step/sec: 112.924
INFO:tensorflow:step = 340606, loss = 0.662987
INFO:tensorflow:global_step/sec: 116.818
INFO:tensorflow:step = 340706, loss = 0.531829
INFO:tensorflow:global_step/sec: 117.568
INFO:tensorflow:step = 340806, loss = 0.438657
INFO:tensorflow:global_step/sec: 117.674
INFO:tensorflow:step = 340906, loss = 0.620047
INFO:tensorflow:global_step/sec: 117.091
INFO:tensorflow:step = 341006, loss = 0.349382
INFO:tensorflow:global_step/sec: 99.7272
INFO:tensorflow:step = 341106, loss = 0.439398
INFO:tensorflow:global_step/sec: 78.0838
INFO:tensorflow:step = 341206, loss = 0.596738
INFO:tensorflow:global_step/sec: 75.8052
INFO:tensorflow:step = 341306, loss = 0.470497
INFO:tensorflow:global_step/sec: 106.383
INFO:tensorflow:step = 341406, loss = 0.601673
INFO:tensorflow:global_step/sec: 117.009
INFO:tensorflow:step = 341506, loss = 0.532679
INFO:tensorflow:global_step/sec: 111.718
INFO:tensorflow:step = 341606, loss = 0.556467
INFO:tensorflow:global_step/sec: 115.078
INFO:tensorflow:step = 341706, loss = 0.391023
INFO:tensorflow:global_step/sec: 116.364
INFO:tensorflow:step = 341806, loss = 0.460295
INFO:tensorflow:global_step/sec: 113.886
INFO:tensorflow:step = 341906, loss = 0.548109
INFO:tensorflow:global_step/sec: 116.403
INFO:tensorflow:step = 342006, loss = 0.524565
INFO:tensorflow:global_step/sec: 116.934
INFO:tensorflow:step = 342106, loss = 0.511981
INFO:tensorflow:global_step/sec: 114.017
INFO:tensorflow:step = 342206, loss = 0.398324
INFO:tensorflow:global_step/sec: 115.184
INFO:tensorflow:step = 342306, loss = 0.281603
INFO:tensorflow:global_step/sec: 114.725
INFO:tensorflow:step = 342406, loss = 0.39462
INFO:tensorflow:global_step/sec: 118.718
INFO:tensorflow:step = 342506, loss = 0.480679
INFO:tensorflow:global_step/sec: 111.672
INFO:tensorflow:step = 342606, loss = 0.57041
INFO:tensorflow:global_step/sec: 114.754
INFO:tensorflow:step = 342706, loss = 0.411844
INFO:tensorflow:global_step/sec: 116.828
INFO:tensorflow:step = 342806, loss = 0.533774
INFO:tensorflow:global_step/sec: 114.179
INFO:tensorflow:step = 342906, loss = 0.455098
INFO:tensorflow:global_step/sec: 117.01
INFO:tensorflow:step = 343006, loss = 0.42254
INFO:tensorflow:global_step/sec: 115.726
INFO:tensorflow:step = 343106, loss = 0.510424
INFO:tensorflow:global_step/sec: 116.358
INFO:tensorflow:step = 343206, loss = 0.500688
INFO:tensorflow:global_step/sec: 108.862
INFO:tensorflow:step = 343306, loss = 0.46724
INFO:tensorflow:global_step/sec: 105.158
INFO:tensorflow:step = 343406, loss = 0.66938
INFO:tensorflow:global_step/sec: 115.92
INFO:tensorflow:step = 343506, loss = 0.387522
INFO:tensorflow:global_step/sec: 117.361
INFO:tensorflow:step = 343606, loss = 0.364447
INFO:tensorflow:global_step/sec: 114.268
INFO:tensorflow:step = 343706, loss = 0.514702
INFO:tensorflow:global_step/sec: 113.073
INFO:tensorflow:step = 343806, loss = 0.469244
INFO:tensorflow:global_step/sec: 116.972
INFO:tensorflow:step = 343906, loss = 0.534099
INFO:tensorflow:global_step/sec: 116.398
INFO:tensorflow:step = 344006, loss = 0.409695
INFO:tensorflow:global_step/sec: 116.199
INFO:tensorflow:step = 344106, loss = 0.54489
INFO:tensorflow:global_step/sec: 110.191
INFO:tensorflow:step = 344206, loss = 0.609699
INFO:tensorflow:global_step/sec: 117.537
INFO:tensorflow:step = 344306, loss = 0.647423
INFO:tensorflow:global_step/sec: 112.543
INFO:tensorflow:step = 344406, loss = 0.620821
INFO:tensorflow:global_step/sec: 98.5311
INFO:tensorflow:step = 344506, loss = 0.453426
INFO:tensorflow:global_step/sec: 103.522
INFO:tensorflow:step = 344606, loss = 0.499177
INFO:tensorflow:global_step/sec: 110.217
INFO:tensorflow:step = 344706, loss = 0.411452
INFO:tensorflow:global_step/sec: 108.275
INFO:tensorflow:step = 344806, loss = 0.425225
INFO:tensorflow:global_step/sec: 108.11
INFO:tensorflow:step = 344906, loss = 0.390474
INFO:tensorflow:global_step/sec: 113.261
INFO:tensorflow:step = 345006, loss = 0.313468
INFO:tensorflow:global_step/sec: 108.572
INFO:tensorflow:step = 345106, loss = 0.434078
INFO:tensorflow:global_step/sec: 104.522
INFO:tensorflow:step = 345206, loss = 0.512227
INFO:tensorflow:global_step/sec: 81.0007
INFO:tensorflow:step = 345306, loss = 0.351638
INFO:tensorflow:global_step/sec: 116.67
INFO:tensorflow:step = 345406, loss = 0.472098
INFO:tensorflow:global_step/sec: 117.19
INFO:tensorflow:step = 345506, loss = 0.347732
INFO:tensorflow:global_step/sec: 117.762
INFO:tensorflow:step = 345606, loss = 0.558673
INFO:tensorflow:global_step/sec: 112.362
INFO:tensorflow:step = 345706, loss = 0.49848
INFO:tensorflow:global_step/sec: 117.734
INFO:tensorflow:step = 345806, loss = 0.425987
INFO:tensorflow:global_step/sec: 113.684
INFO:tensorflow:step = 345906, loss = 0.543236
INFO:tensorflow:global_step/sec: 111.97
INFO:tensorflow:step = 346006, loss = 0.401278
INFO:tensorflow:global_step/sec: 117.85
INFO:tensorflow:step = 346106, loss = 0.411407
INFO:tensorflow:global_step/sec: 94.3647
INFO:tensorflow:step = 346206, loss = 0.49146
INFO:tensorflow:global_step/sec: 72.0722
INFO:tensorflow:step = 346306, loss = 0.719834
INFO:tensorflow:global_step/sec: 113.715
INFO:tensorflow:step = 346406, loss = 0.387193
INFO:tensorflow:global_step/sec: 113.196
INFO:tensorflow:step = 346506, loss = 0.415186
INFO:tensorflow:global_step/sec: 108.784
INFO:tensorflow:step = 346606, loss = 0.435098
INFO:tensorflow:global_step/sec: 96.7805
INFO:tensorflow:step = 346706, loss = 0.515897
INFO:tensorflow:global_step/sec: 117.198
INFO:tensorflow:step = 346806, loss = 0.488466
INFO:tensorflow:global_step/sec: 115.551
INFO:tensorflow:step = 346906, loss = 0.57207
INFO:tensorflow:global_step/sec: 114.11
INFO:tensorflow:step = 347006, loss = 0.494605
INFO:tensorflow:global_step/sec: 115.721
INFO:tensorflow:step = 347106, loss = 0.612438
INFO:tensorflow:global_step/sec: 116.584
INFO:tensorflow:step = 347206, loss = 0.489791
INFO:tensorflow:global_step/sec: 107.971
INFO:tensorflow:step = 347306, loss = 0.468933
INFO:tensorflow:global_step/sec: 112.272
INFO:tensorflow:step = 347406, loss = 0.496476
INFO:tensorflow:global_step/sec: 114.758
INFO:tensorflow:step = 347506, loss = 0.506092
INFO:tensorflow:global_step/sec: 117.463
INFO:tensorflow:step = 347606, loss = 0.489552
INFO:tensorflow:global_step/sec: 116.831
INFO:tensorflow:step = 347706, loss = 0.603145
INFO:tensorflow:global_step/sec: 100.971
INFO:tensorflow:step = 347806, loss = 0.551206
INFO:tensorflow:global_step/sec: 75.9792
INFO:tensorflow:step = 347906, loss = 0.303643
INFO:tensorflow:global_step/sec: 74.6989
INFO:tensorflow:step = 348006, loss = 0.37927
INFO:tensorflow:global_step/sec: 92.6601
INFO:tensorflow:step = 348106, loss = 0.920131
INFO:tensorflow:global_step/sec: 116.881
INFO:tensorflow:step = 348206, loss = 0.413982
INFO:tensorflow:global_step/sec: 114.421
INFO:tensorflow:step = 348306, loss = 0.498875
INFO:tensorflow:global_step/sec: 112.332
INFO:tensorflow:step = 348406, loss = 0.452476
INFO:tensorflow:global_step/sec: 118.374
INFO:tensorflow:step = 348506, loss = 0.452039
INFO:tensorflow:global_step/sec: 117.065
INFO:tensorflow:step = 348606, loss = 0.477456
INFO:tensorflow:global_step/sec: 116.62
INFO:tensorflow:step = 348706, loss = 0.398244
INFO:tensorflow:global_step/sec: 117.225
INFO:tensorflow:step = 348806, loss = 0.952247
INFO:tensorflow:global_step/sec: 115.254
INFO:tensorflow:step = 348906, loss = 0.431787
INFO:tensorflow:global_step/sec: 116.098
INFO:tensorflow:step = 349006, loss = 0.662923
INFO:tensorflow:global_step/sec: 114.305
INFO:tensorflow:step = 349106, loss = 0.498748
INFO:tensorflow:global_step/sec: 114.518
INFO:tensorflow:step = 349206, loss = 0.602874
INFO:tensorflow:global_step/sec: 117.794
INFO:tensorflow:step = 349306, loss = 0.647044
INFO:tensorflow:global_step/sec: 113.615
INFO:tensorflow:step = 349406, loss = 0.560512
INFO:tensorflow:global_step/sec: 113.496
INFO:tensorflow:step = 349506, loss = 0.461952
INFO:tensorflow:global_step/sec: 115.568
INFO:tensorflow:step = 349606, loss = 0.597699
INFO:tensorflow:global_step/sec: 115.952
INFO:tensorflow:step = 349706, loss = 0.742347
INFO:tensorflow:global_step/sec: 116.308
INFO:tensorflow:step = 349806, loss = 0.486255
INFO:tensorflow:global_step/sec: 117.033
INFO:tensorflow:step = 349906, loss = 0.374514
INFO:tensorflow:global_step/sec: 105.601
INFO:tensorflow:step = 350006, loss = 0.473089
INFO:tensorflow:global_step/sec: 115.441
INFO:tensorflow:step = 350106, loss = 0.498085
INFO:tensorflow:global_step/sec: 117.259
INFO:tensorflow:step = 350206, loss = 0.513201
INFO:tensorflow:global_step/sec: 116.014
INFO:tensorflow:step = 350306, loss = 0.443927
INFO:tensorflow:global_step/sec: 113.88
INFO:tensorflow:step = 350406, loss = 0.452892
INFO:tensorflow:global_step/sec: 115.601
INFO:tensorflow:step = 350506, loss = 0.436417
INFO:tensorflow:global_step/sec: 116.503
INFO:tensorflow:step = 350606, loss = 0.420372
INFO:tensorflow:global_step/sec: 118.287
INFO:tensorflow:step = 350706, loss = 0.36123
INFO:tensorflow:global_step/sec: 115.155
INFO:tensorflow:step = 350806, loss = 0.537954
INFO:tensorflow:global_step/sec: 115.585
INFO:tensorflow:step = 350906, loss = 0.480799
INFO:tensorflow:global_step/sec: 112.515
INFO:tensorflow:step = 351006, loss = 0.492548
INFO:tensorflow:global_step/sec: 109.685
INFO:tensorflow:step = 351106, loss = 0.551821
INFO:tensorflow:global_step/sec: 91.4695
INFO:tensorflow:step = 351206, loss = 0.567941
INFO:tensorflow:global_step/sec: 107.787
INFO:tensorflow:step = 351306, loss = 0.747511
INFO:tensorflow:global_step/sec: 117.029
INFO:tensorflow:step = 351406, loss = 0.369468
INFO:tensorflow:global_step/sec: 114.139
INFO:tensorflow:step = 351506, loss = 0.695197
INFO:tensorflow:global_step/sec: 114.321
INFO:tensorflow:step = 351606, loss = 0.461856
INFO:tensorflow:global_step/sec: 111.252
INFO:tensorflow:step = 351706, loss = 0.47705
INFO:tensorflow:global_step/sec: 93.3355
INFO:tensorflow:step = 351806, loss = 0.507072
INFO:tensorflow:global_step/sec: 86.4301
INFO:tensorflow:step = 351906, loss = 0.620717
INFO:tensorflow:global_step/sec: 116.494
INFO:tensorflow:step = 352006, loss = 0.72283
INFO:tensorflow:global_step/sec: 115.707
INFO:tensorflow:step = 352106, loss = 0.328128
INFO:tensorflow:global_step/sec: 116.606
INFO:tensorflow:step = 352206, loss = 0.434188
INFO:tensorflow:global_step/sec: 114.608
INFO:tensorflow:step = 352306, loss = 0.782123
INFO:tensorflow:global_step/sec: 111.28
INFO:tensorflow:step = 352406, loss = 0.588399
INFO:tensorflow:global_step/sec: 115.001
INFO:tensorflow:step = 352506, loss = 0.543554
INFO:tensorflow:global_step/sec: 116.058
INFO:tensorflow:step = 352606, loss = 0.430322
INFO:tensorflow:global_step/sec: 114.072
INFO:tensorflow:step = 352706, loss = 0.579322
INFO:tensorflow:global_step/sec: 115.354
INFO:tensorflow:step = 352806, loss = 0.84962
INFO:tensorflow:global_step/sec: 117.043
INFO:tensorflow:step = 352906, loss = 0.865846
INFO:tensorflow:global_step/sec: 115.53
INFO:tensorflow:step = 353006, loss = 0.631429
INFO:tensorflow:global_step/sec: 116.876
INFO:tensorflow:step = 353106, loss = 0.338776
INFO:tensorflow:global_step/sec: 114.599
INFO:tensorflow:step = 353206, loss = 0.561563
INFO:tensorflow:global_step/sec: 110.706
INFO:tensorflow:step = 353306, loss = 0.312941
INFO:tensorflow:global_step/sec: 104.683
INFO:tensorflow:step = 353406, loss = 0.54279
INFO:tensorflow:global_step/sec: 109.309
INFO:tensorflow:step = 353506, loss = 0.540346
INFO:tensorflow:global_step/sec: 117.541
INFO:tensorflow:step = 353606, loss = 0.322703
INFO:tensorflow:global_step/sec: 110.23
INFO:tensorflow:step = 353706, loss = 0.51748
INFO:tensorflow:global_step/sec: 110.669
INFO:tensorflow:step = 353806, loss = 0.490543
INFO:tensorflow:global_step/sec: 115.189
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INFO:tensorflow:step = 365906, loss = 0.501001
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INFO:tensorflow:global_step/sec: 114.114
INFO:tensorflow:step = 367406, loss = 0.563856
INFO:tensorflow:global_step/sec: 100.19
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INFO:tensorflow:global_step/sec: 108.707
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INFO:tensorflow:global_step/sec: 100.644
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INFO:tensorflow:global_step/sec: 111.62
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INFO:tensorflow:global_step/sec: 103.236
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INFO:tensorflow:global_step/sec: 114.948
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INFO:tensorflow:step = 368506, loss = 0.406165
INFO:tensorflow:global_step/sec: 110.701
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INFO:tensorflow:step = 368906, loss = 1.11554
INFO:tensorflow:global_step/sec: 18.2088
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INFO:tensorflow:step = 369606, loss = 0.555678
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INFO:tensorflow:step = 377006, loss = 0.626471
INFO:tensorflow:global_step/sec: 114.395
INFO:tensorflow:step = 377106, loss = 0.327142
INFO:tensorflow:global_step/sec: 116.406
INFO:tensorflow:step = 377206, loss = 0.775088
INFO:tensorflow:global_step/sec: 118.156
INFO:tensorflow:step = 377306, loss = 0.597418
INFO:tensorflow:global_step/sec: 118.713
INFO:tensorflow:step = 377406, loss = 0.576139
INFO:tensorflow:global_step/sec: 119.591
INFO:tensorflow:step = 377506, loss = 0.378929
INFO:tensorflow:global_step/sec: 100.406
INFO:tensorflow:step = 377606, loss = 0.414595
INFO:tensorflow:global_step/sec: 88.6105
INFO:tensorflow:step = 377706, loss = 0.484988
INFO:tensorflow:global_step/sec: 77.5634
INFO:tensorflow:step = 377806, loss = 0.331551
INFO:tensorflow:global_step/sec: 117.024
INFO:tensorflow:step = 377906, loss = 0.389457
INFO:tensorflow:global_step/sec: 120.076
INFO:tensorflow:step = 378006, loss = 0.536181
INFO:tensorflow:global_step/sec: 116.956
INFO:tensorflow:step = 378106, loss = 0.537166
INFO:tensorflow:global_step/sec: 112.007
INFO:tensorflow:step = 378206, loss = 0.524786
INFO:tensorflow:global_step/sec: 119
INFO:tensorflow:step = 378306, loss = 0.528516
INFO:tensorflow:global_step/sec: 119.695
INFO:tensorflow:step = 378406, loss = 0.435281
INFO:tensorflow:global_step/sec: 119.095
INFO:tensorflow:step = 378506, loss = 0.565628
INFO:tensorflow:global_step/sec: 118.008
INFO:tensorflow:step = 378606, loss = 0.437732
INFO:tensorflow:global_step/sec: 119.066
INFO:tensorflow:step = 378706, loss = 0.476584
INFO:tensorflow:global_step/sec: 112.978
INFO:tensorflow:step = 378806, loss = 0.45328
INFO:tensorflow:global_step/sec: 118.528
INFO:tensorflow:step = 378906, loss = 0.720383
INFO:tensorflow:global_step/sec: 120.037
INFO:tensorflow:step = 379006, loss = 0.490189
INFO:tensorflow:global_step/sec: 119.595
INFO:tensorflow:step = 379106, loss = 0.406839
INFO:tensorflow:global_step/sec: 117.278
INFO:tensorflow:step = 379206, loss = 0.501699
INFO:tensorflow:global_step/sec: 102.947
INFO:tensorflow:step = 379306, loss = 0.331875
INFO:tensorflow:global_step/sec: 118.932
INFO:tensorflow:step = 379406, loss = 0.478926
INFO:tensorflow:global_step/sec: 116.891
INFO:tensorflow:step = 379506, loss = 0.467781
INFO:tensorflow:global_step/sec: 118.21
INFO:tensorflow:step = 379606, loss = 0.33497
INFO:tensorflow:global_step/sec: 118.543
INFO:tensorflow:step = 379706, loss = 0.38063
INFO:tensorflow:global_step/sec: 118.242
INFO:tensorflow:step = 379806, loss = 0.456673
INFO:tensorflow:global_step/sec: 105.957
INFO:tensorflow:step = 379906, loss = 0.646754
INFO:tensorflow:global_step/sec: 109.42
INFO:tensorflow:step = 380006, loss = 0.591002
INFO:tensorflow:global_step/sec: 118.723
INFO:tensorflow:step = 380106, loss = 0.334872
INFO:tensorflow:global_step/sec: 118.712
INFO:tensorflow:step = 380206, loss = 0.490124
INFO:tensorflow:global_step/sec: 116.117
INFO:tensorflow:step = 380306, loss = 0.408442
INFO:tensorflow:global_step/sec: 119.599
INFO:tensorflow:step = 380406, loss = 0.498566
INFO:tensorflow:global_step/sec: 119.957
INFO:tensorflow:step = 380506, loss = 0.392774
INFO:tensorflow:global_step/sec: 119.551
INFO:tensorflow:step = 380606, loss = 0.529818
INFO:tensorflow:global_step/sec: 119.674
INFO:tensorflow:step = 380706, loss = 0.562171
INFO:tensorflow:global_step/sec: 119.484
INFO:tensorflow:step = 380806, loss = 0.43141
INFO:tensorflow:global_step/sec: 117.855
INFO:tensorflow:step = 380906, loss = 0.45203
INFO:tensorflow:global_step/sec: 101.306
INFO:tensorflow:step = 381006, loss = 0.448674
INFO:tensorflow:global_step/sec: 72.1571
INFO:tensorflow:step = 381106, loss = 0.659196
INFO:tensorflow:global_step/sec: 87.1296
INFO:tensorflow:step = 381206, loss = 0.351614
INFO:tensorflow:global_step/sec: 101.185
INFO:tensorflow:step = 381306, loss = 0.381443
INFO:tensorflow:global_step/sec: 119.168
INFO:tensorflow:step = 381406, loss = 0.499513
INFO:tensorflow:global_step/sec: 119.037
INFO:tensorflow:step = 381506, loss = 0.485337
INFO:tensorflow:global_step/sec: 115.165
INFO:tensorflow:step = 381606, loss = 0.47329
INFO:tensorflow:global_step/sec: 118.653
INFO:tensorflow:step = 381706, loss = 0.564508
INFO:tensorflow:global_step/sec: 119.22
INFO:tensorflow:step = 381806, loss = 0.468723
INFO:tensorflow:global_step/sec: 119.308
INFO:tensorflow:step = 381906, loss = 0.516377
INFO:tensorflow:global_step/sec: 118.739
INFO:tensorflow:step = 382006, loss = 0.42499
INFO:tensorflow:global_step/sec: 118.937
INFO:tensorflow:step = 382106, loss = 0.457166
INFO:tensorflow:global_step/sec: 118.223
INFO:tensorflow:step = 382206, loss = 0.579174
INFO:tensorflow:global_step/sec: 104.848
INFO:tensorflow:step = 382306, loss = 0.686682
INFO:tensorflow:global_step/sec: 105.143
INFO:tensorflow:step = 382406, loss = 0.515517
INFO:tensorflow:global_step/sec: 100.643
INFO:tensorflow:step = 382506, loss = 0.389967
INFO:tensorflow:global_step/sec: 109.42
INFO:tensorflow:step = 382606, loss = 0.412178
INFO:tensorflow:global_step/sec: 95.8852
INFO:tensorflow:step = 382706, loss = 0.44355
INFO:tensorflow:global_step/sec: 96.0917
INFO:tensorflow:step = 382806, loss = 0.534399
INFO:tensorflow:global_step/sec: 107.697
INFO:tensorflow:step = 382906, loss = 0.554399
INFO:tensorflow:global_step/sec: 107.913
INFO:tensorflow:step = 383006, loss = 0.490167
INFO:tensorflow:global_step/sec: 89.6477
INFO:tensorflow:step = 383106, loss = 0.484643
INFO:tensorflow:global_step/sec: 65.8837
INFO:tensorflow:step = 383206, loss = 0.383646
INFO:tensorflow:global_step/sec: 47.9689
INFO:tensorflow:step = 383306, loss = 0.328062
INFO:tensorflow:global_step/sec: 54.4778
INFO:tensorflow:step = 383406, loss = 0.472838
INFO:tensorflow:global_step/sec: 34.3446
INFO:tensorflow:step = 383506, loss = 0.514248
INFO:tensorflow:global_step/sec: 57.7484
INFO:tensorflow:step = 383606, loss = 0.590927
INFO:tensorflow:global_step/sec: 29.4674
INFO:tensorflow:step = 383706, loss = 0.523987
INFO:tensorflow:global_step/sec: 49.6168
INFO:tensorflow:step = 383806, loss = 0.574431
INFO:tensorflow:global_step/sec: 55.3299
INFO:tensorflow:step = 383906, loss = 0.315646
INFO:tensorflow:global_step/sec: 54.5231
INFO:tensorflow:step = 384006, loss = 0.400056
INFO:tensorflow:global_step/sec: 50.338
INFO:tensorflow:step = 384106, loss = 0.515504
INFO:tensorflow:global_step/sec: 78.161
INFO:tensorflow:step = 384206, loss = 0.491597
INFO:tensorflow:global_step/sec: 80.2718
INFO:tensorflow:step = 384306, loss = 0.377297
INFO:tensorflow:global_step/sec: 82.4471
INFO:tensorflow:step = 384406, loss = 0.343897
INFO:tensorflow:global_step/sec: 87.8854
INFO:tensorflow:step = 384506, loss = 0.393786
INFO:tensorflow:global_step/sec: 82.6583
INFO:tensorflow:step = 384606, loss = 0.485856
INFO:tensorflow:global_step/sec: 111.961
INFO:tensorflow:step = 384706, loss = 0.461298
INFO:tensorflow:global_step/sec: 78.4229
INFO:tensorflow:step = 384806, loss = 0.407846
INFO:tensorflow:global_step/sec: 99.1838
INFO:tensorflow:step = 384906, loss = 0.541162
INFO:tensorflow:global_step/sec: 98.9235
INFO:tensorflow:step = 385006, loss = 0.41547
INFO:tensorflow:global_step/sec: 59.2678
INFO:tensorflow:step = 385106, loss = 0.424858
INFO:tensorflow:global_step/sec: 99.9649
INFO:tensorflow:step = 385206, loss = 0.596552
INFO:tensorflow:global_step/sec: 97.0856
INFO:tensorflow:step = 385306, loss = 0.567831
INFO:tensorflow:global_step/sec: 117.444
INFO:tensorflow:step = 385406, loss = 0.364882
INFO:tensorflow:global_step/sec: 108.632
INFO:tensorflow:step = 385506, loss = 0.481766
INFO:tensorflow:global_step/sec: 116.346
INFO:tensorflow:step = 385606, loss = 0.475818
INFO:tensorflow:global_step/sec: 116.285
INFO:tensorflow:step = 385706, loss = 0.423154
INFO:tensorflow:global_step/sec: 116.912
INFO:tensorflow:step = 385806, loss = 0.567895
INFO:tensorflow:global_step/sec: 108.971
INFO:tensorflow:step = 385906, loss = 0.732621
INFO:tensorflow:global_step/sec: 58.6307
INFO:tensorflow:step = 386006, loss = 0.398121
INFO:tensorflow:global_step/sec: 36.1394
INFO:tensorflow:step = 386106, loss = 0.372611
INFO:tensorflow:global_step/sec: 56.7783
INFO:tensorflow:step = 386206, loss = 0.412003
INFO:tensorflow:global_step/sec: 93.2437
INFO:tensorflow:step = 386306, loss = 0.555516
INFO:tensorflow:global_step/sec: 93.0212
INFO:tensorflow:step = 386406, loss = 0.482065
INFO:tensorflow:global_step/sec: 85.7707
INFO:tensorflow:step = 386506, loss = 0.469064
INFO:tensorflow:global_step/sec: 44.7564
INFO:tensorflow:step = 386606, loss = 0.481325
INFO:tensorflow:global_step/sec: 107.685
INFO:tensorflow:step = 386706, loss = 0.400064
INFO:tensorflow:global_step/sec: 117.671
INFO:tensorflow:step = 386806, loss = 0.730189
INFO:tensorflow:global_step/sec: 98.0446
INFO:tensorflow:step = 386906, loss = 0.472098
INFO:tensorflow:global_step/sec: 109.901
INFO:tensorflow:step = 387006, loss = 0.45731
INFO:tensorflow:global_step/sec: 109.564
INFO:tensorflow:step = 387106, loss = 0.528994
INFO:tensorflow:global_step/sec: 116.445
INFO:tensorflow:step = 387206, loss = 0.499117
INFO:tensorflow:global_step/sec: 89.8502
INFO:tensorflow:step = 387306, loss = 0.324342
INFO:tensorflow:global_step/sec: 84.1684
INFO:tensorflow:step = 387406, loss = 0.694533
INFO:tensorflow:global_step/sec: 81.6077
INFO:tensorflow:step = 387506, loss = 0.388515
INFO:tensorflow:global_step/sec: 78.8264
INFO:tensorflow:step = 387606, loss = 0.465186
INFO:tensorflow:global_step/sec: 53.7486
INFO:tensorflow:step = 387706, loss = 0.525449
INFO:tensorflow:global_step/sec: 50.5706
INFO:tensorflow:step = 387806, loss = 0.384899
INFO:tensorflow:global_step/sec: 58.9592
INFO:tensorflow:step = 387906, loss = 0.364296
INFO:tensorflow:global_step/sec: 68.8129
INFO:tensorflow:step = 388006, loss = 0.441541
INFO:tensorflow:global_step/sec: 57.4465
INFO:tensorflow:step = 388106, loss = 0.500398
INFO:tensorflow:global_step/sec: 46.4508
INFO:tensorflow:step = 388206, loss = 0.398707
INFO:tensorflow:global_step/sec: 75.4235
INFO:tensorflow:step = 388306, loss = 0.605762
INFO:tensorflow:global_step/sec: 52.463
INFO:tensorflow:step = 388406, loss = 0.478451
INFO:tensorflow:global_step/sec: 55.3954
INFO:tensorflow:step = 388506, loss = 0.382462
INFO:tensorflow:global_step/sec: 38.8498
INFO:tensorflow:step = 388606, loss = 0.595269
INFO:tensorflow:global_step/sec: 75.6649
INFO:tensorflow:step = 388706, loss = 0.257353
INFO:tensorflow:global_step/sec: 85.5813
INFO:tensorflow:step = 388806, loss = 0.393585
INFO:tensorflow:global_step/sec: 81.0885
INFO:tensorflow:step = 388906, loss = 0.412343
INFO:tensorflow:global_step/sec: 68.8203
INFO:tensorflow:step = 389006, loss = 0.503414
INFO:tensorflow:global_step/sec: 76.7401
INFO:tensorflow:step = 389106, loss = 0.489611
INFO:tensorflow:global_step/sec: 116.1
INFO:tensorflow:step = 389206, loss = 0.399781
INFO:tensorflow:global_step/sec: 110.076
INFO:tensorflow:step = 389306, loss = 0.461814
INFO:tensorflow:global_step/sec: 70.7897
INFO:tensorflow:step = 389406, loss = 0.504079
INFO:tensorflow:global_step/sec: 70.274
INFO:tensorflow:step = 389506, loss = 0.451159
INFO:tensorflow:global_step/sec: 66.6445
INFO:tensorflow:step = 389606, loss = 0.572699
INFO:tensorflow:global_step/sec: 76.5977
INFO:tensorflow:step = 389706, loss = 0.486634
INFO:tensorflow:global_step/sec: 91.7861
INFO:tensorflow:step = 389806, loss = 0.439432
INFO:tensorflow:global_step/sec: 94.7557
INFO:tensorflow:step = 389906, loss = 0.417397
INFO:tensorflow:global_step/sec: 110.992
INFO:tensorflow:step = 390006, loss = 0.378733
INFO:tensorflow:global_step/sec: 103.646
INFO:tensorflow:step = 390106, loss = 0.5153
INFO:tensorflow:global_step/sec: 117.597
INFO:tensorflow:step = 390206, loss = 0.456069
INFO:tensorflow:global_step/sec: 106.083
INFO:tensorflow:step = 390306, loss = 0.447019
INFO:tensorflow:global_step/sec: 110.825
INFO:tensorflow:step = 390406, loss = 0.521564
INFO:tensorflow:global_step/sec: 110.191
INFO:tensorflow:step = 390506, loss = 0.524356
INFO:tensorflow:global_step/sec: 85.4958
INFO:tensorflow:step = 390606, loss = 0.322122
INFO:tensorflow:global_step/sec: 66.4122
INFO:tensorflow:step = 390706, loss = 0.400309
INFO:tensorflow:global_step/sec: 59.075
INFO:tensorflow:step = 390806, loss = 0.487829
INFO:tensorflow:global_step/sec: 76.3594
INFO:tensorflow:step = 390906, loss = 0.703757
INFO:tensorflow:global_step/sec: 92.3058
INFO:tensorflow:step = 391006, loss = 0.382804
INFO:tensorflow:global_step/sec: 92.6568
INFO:tensorflow:step = 391106, loss = 0.566826
INFO:tensorflow:Saving checkpoints for 391144 into .opt_logs/lstm_stock/model.ckpt.
INFO:tensorflow:global_step/sec: 7.98702
INFO:tensorflow:step = 391206, loss = 0.434566
INFO:tensorflow:global_step/sec: 66.808
INFO:tensorflow:step = 391306, loss = 0.536504
INFO:tensorflow:global_step/sec: 62.853
INFO:tensorflow:step = 391406, loss = 0.364899
INFO:tensorflow:global_step/sec: 58.5329
INFO:tensorflow:step = 391506, loss = 0.470208
INFO:tensorflow:global_step/sec: 95.6628
INFO:tensorflow:step = 391606, loss = 0.332662
INFO:tensorflow:global_step/sec: 111.603
INFO:tensorflow:step = 391706, loss = 0.49798
INFO:tensorflow:global_step/sec: 110.665
INFO:tensorflow:step = 391806, loss = 0.498388
INFO:tensorflow:global_step/sec: 114.772
INFO:tensorflow:step = 391906, loss = 0.436898
INFO:tensorflow:global_step/sec: 114.465
INFO:tensorflow:step = 392006, loss = 0.673943
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with y is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/models.py:107: mean_squared_error_regressor (from tensorflow.contrib.learn.python.learn.ops.losses_ops) is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Use `tf.contrib.losses.mean_squared_error` and explicit logits computation.
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/ops/losses_ops.py:39: mean_squared_error (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.
Instructions for updating:
Use tf.losses.mean_squared_error instead.
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/losses/python/losses/loss_ops.py:530: compute_weighted_loss (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.
Instructions for updating:
Use tf.losses.compute_weighted_loss instead.
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/losses/python/losses/loss_ops.py:151: add_loss (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.
Instructions for updating:
Use tf.losses.add_loss instead.
INFO:tensorflow:Starting evaluation at 2017-04-09-09:31:35
INFO:tensorflow:Finished evaluation at 2017-04-09-09:31:39
INFO:tensorflow:Saving dict for global step 391144: global_step = 391144, loss = 0.208015
WARNING:tensorflow:Skipping summary for global_step, must be a float or np.float32.
INFO:tensorflow:Validation (step 392006): loss = 0.208015, global_step = 391144
INFO:tensorflow:global_step/sec: 7.39509
INFO:tensorflow:step = 392106, loss = 0.335708
INFO:tensorflow:global_step/sec: 116.441
INFO:tensorflow:step = 392206, loss = 0.382963
INFO:tensorflow:global_step/sec: 115.807
INFO:tensorflow:step = 392306, loss = 0.537882
INFO:tensorflow:global_step/sec: 115.245
INFO:tensorflow:step = 392406, loss = 0.625242
INFO:tensorflow:global_step/sec: 117.556
INFO:tensorflow:step = 392506, loss = 0.366225
INFO:tensorflow:global_step/sec: 105.651
INFO:tensorflow:step = 392606, loss = 0.344535
INFO:tensorflow:global_step/sec: 96.672
INFO:tensorflow:step = 392706, loss = 0.490773
INFO:tensorflow:global_step/sec: 74.9781
INFO:tensorflow:step = 392806, loss = 0.611885
INFO:tensorflow:global_step/sec: 43.7497
INFO:tensorflow:step = 392906, loss = 0.436357
INFO:tensorflow:global_step/sec: 79.2152
INFO:tensorflow:step = 393006, loss = 0.482824
INFO:tensorflow:global_step/sec: 116.383
INFO:tensorflow:step = 393106, loss = 0.486694
INFO:tensorflow:global_step/sec: 108.878
INFO:tensorflow:step = 393206, loss = 0.627389
INFO:tensorflow:global_step/sec: 98.1852
INFO:tensorflow:step = 393306, loss = 0.591142
INFO:tensorflow:global_step/sec: 117.282
INFO:tensorflow:step = 393406, loss = 0.429641
INFO:tensorflow:global_step/sec: 115.905
INFO:tensorflow:step = 393506, loss = 0.485474
INFO:tensorflow:global_step/sec: 103.198
INFO:tensorflow:step = 393606, loss = 0.415822
INFO:tensorflow:global_step/sec: 111.503
INFO:tensorflow:step = 393706, loss = 0.504345
INFO:tensorflow:global_step/sec: 64.8767
INFO:tensorflow:step = 393806, loss = 0.743686
INFO:tensorflow:global_step/sec: 49.6055
INFO:tensorflow:step = 393906, loss = 0.453747
INFO:tensorflow:global_step/sec: 50.937
INFO:tensorflow:step = 394006, loss = 0.683122
INFO:tensorflow:global_step/sec: 53.9478
INFO:tensorflow:step = 394106, loss = 0.418972
INFO:tensorflow:global_step/sec: 39.0643
INFO:tensorflow:step = 394206, loss = 0.492652
INFO:tensorflow:global_step/sec: 48.5584
INFO:tensorflow:step = 394306, loss = 0.467116
INFO:tensorflow:global_step/sec: 73.1647
INFO:tensorflow:step = 394406, loss = 0.550699
INFO:tensorflow:global_step/sec: 67.8354
INFO:tensorflow:step = 394506, loss = 0.534082
INFO:tensorflow:global_step/sec: 99.4983
INFO:tensorflow:step = 394606, loss = 0.370517
INFO:tensorflow:global_step/sec: 83.7151
INFO:tensorflow:step = 394706, loss = 0.300084
INFO:tensorflow:global_step/sec: 105.824
INFO:tensorflow:step = 394806, loss = 0.473405
INFO:tensorflow:global_step/sec: 50.1923
INFO:tensorflow:step = 394906, loss = 0.32583
INFO:tensorflow:global_step/sec: 110.751
INFO:tensorflow:step = 395006, loss = 0.559909
INFO:tensorflow:global_step/sec: 111.81
INFO:tensorflow:step = 395106, loss = 0.560547
INFO:tensorflow:global_step/sec: 94.0539
INFO:tensorflow:step = 395206, loss = 0.310815
INFO:tensorflow:global_step/sec: 84.3184
INFO:tensorflow:step = 395306, loss = 0.438703
INFO:tensorflow:global_step/sec: 105.287
INFO:tensorflow:step = 395406, loss = 0.60348
INFO:tensorflow:global_step/sec: 95.8173
INFO:tensorflow:step = 395506, loss = 0.5214
INFO:tensorflow:global_step/sec: 96.7383
INFO:tensorflow:step = 395606, loss = 0.428374
INFO:tensorflow:global_step/sec: 95.5123
INFO:tensorflow:step = 395706, loss = 0.403604
INFO:tensorflow:global_step/sec: 108.802
INFO:tensorflow:step = 395806, loss = 0.480228
INFO:tensorflow:global_step/sec: 61.61
INFO:tensorflow:step = 395906, loss = 0.578693
INFO:tensorflow:global_step/sec: 51.7796
INFO:tensorflow:step = 396006, loss = 0.445174
INFO:tensorflow:global_step/sec: 42.6104
INFO:tensorflow:step = 396106, loss = 0.52254
INFO:tensorflow:global_step/sec: 54.1196
INFO:tensorflow:step = 396206, loss = 0.893658
INFO:tensorflow:global_step/sec: 70.1982
INFO:tensorflow:step = 396306, loss = 0.538302
INFO:tensorflow:global_step/sec: 85.9776
INFO:tensorflow:step = 396406, loss = 0.449723
INFO:tensorflow:global_step/sec: 48.8699
INFO:tensorflow:step = 396506, loss = 0.643234
INFO:tensorflow:global_step/sec: 61.8005
INFO:tensorflow:step = 396606, loss = 0.293744
INFO:tensorflow:global_step/sec: 69.8891
INFO:tensorflow:step = 396706, loss = 0.4705
INFO:tensorflow:global_step/sec: 88.0424
INFO:tensorflow:step = 396806, loss = 0.507166
INFO:tensorflow:global_step/sec: 110.043
INFO:tensorflow:step = 396906, loss = 0.395285
INFO:tensorflow:global_step/sec: 113.784
INFO:tensorflow:step = 397006, loss = 0.417568
INFO:tensorflow:global_step/sec: 117.253
INFO:tensorflow:step = 397106, loss = 0.485271
INFO:tensorflow:global_step/sec: 68.3422
INFO:tensorflow:step = 397206, loss = 0.531123
INFO:tensorflow:global_step/sec: 55.926
INFO:tensorflow:step = 397306, loss = 0.370861
INFO:tensorflow:global_step/sec: 95.0851
INFO:tensorflow:step = 397406, loss = 0.486647
INFO:tensorflow:global_step/sec: 92.3384
INFO:tensorflow:step = 397506, loss = 0.5503
INFO:tensorflow:global_step/sec: 98.4269
INFO:tensorflow:step = 397606, loss = 0.555602
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INFO:tensorflow:global_step/sec: 108.316
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INFO:tensorflow:step = 413706, loss = 0.474991
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INFO:tensorflow:step = 420806, loss = 0.453726
INFO:tensorflow:global_step/sec: 28.7167
INFO:tensorflow:step = 420906, loss = 0.638019
INFO:tensorflow:global_step/sec: 52.7535
INFO:tensorflow:step = 421006, loss = 0.573441
INFO:tensorflow:global_step/sec: 54.8315
INFO:tensorflow:step = 421106, loss = 0.461695
INFO:tensorflow:global_step/sec: 54.3166
INFO:tensorflow:step = 421206, loss = 0.437009
INFO:tensorflow:global_step/sec: 23.3161
INFO:tensorflow:step = 421306, loss = 0.49744
INFO:tensorflow:global_step/sec: 26.5325
INFO:tensorflow:step = 421406, loss = 0.525337
INFO:tensorflow:global_step/sec: 49.163
INFO:tensorflow:step = 421506, loss = 0.573535
INFO:tensorflow:global_step/sec: 64.0805
INFO:tensorflow:step = 421606, loss = 0.484636
INFO:tensorflow:global_step/sec: 56.3936
INFO:tensorflow:step = 421706, loss = 0.292208
INFO:tensorflow:global_step/sec: 33.761
INFO:tensorflow:step = 421806, loss = 0.510519
INFO:tensorflow:global_step/sec: 20.6473
INFO:tensorflow:step = 421906, loss = 0.529513
INFO:tensorflow:global_step/sec: 59.4794
INFO:tensorflow:step = 422006, loss = 0.471067
INFO:tensorflow:global_step/sec: 75.2916
INFO:tensorflow:step = 422106, loss = 0.370604
INFO:tensorflow:global_step/sec: 58.8928
INFO:tensorflow:step = 422206, loss = 0.594427
INFO:tensorflow:global_step/sec: 87.5781
INFO:tensorflow:step = 422306, loss = 0.490108
INFO:tensorflow:global_step/sec: 92.6497
INFO:tensorflow:step = 422406, loss = 0.409757
INFO:tensorflow:global_step/sec: 107.943
INFO:tensorflow:step = 422506, loss = 0.455557
INFO:tensorflow:global_step/sec: 106.529
INFO:tensorflow:step = 422606, loss = 0.64797
INFO:tensorflow:global_step/sec: 114.23
INFO:tensorflow:step = 422706, loss = 0.498126
INFO:tensorflow:global_step/sec: 114.123
INFO:tensorflow:step = 422806, loss = 0.503534
INFO:tensorflow:global_step/sec: 115.884
INFO:tensorflow:step = 422906, loss = 0.340305
INFO:tensorflow:global_step/sec: 117.842
INFO:tensorflow:step = 423006, loss = 0.459481
INFO:tensorflow:global_step/sec: 110.014
INFO:tensorflow:step = 423106, loss = 0.47673
INFO:tensorflow:global_step/sec: 106.219
INFO:tensorflow:step = 423206, loss = 0.582803
INFO:tensorflow:global_step/sec: 112.108
INFO:tensorflow:step = 423306, loss = 0.470261
INFO:tensorflow:global_step/sec: 110.477
INFO:tensorflow:step = 423406, loss = 0.327331
INFO:tensorflow:global_step/sec: 115.742
INFO:tensorflow:step = 423506, loss = 0.373291
INFO:tensorflow:global_step/sec: 118.416
INFO:tensorflow:step = 423606, loss = 0.630655
INFO:tensorflow:global_step/sec: 118.046
INFO:tensorflow:step = 423706, loss = 0.411714
INFO:tensorflow:global_step/sec: 118.874
INFO:tensorflow:step = 423806, loss = 0.310494
INFO:tensorflow:global_step/sec: 117.859
INFO:tensorflow:step = 423906, loss = 0.367473
INFO:tensorflow:global_step/sec: 117.833
INFO:tensorflow:step = 424006, loss = 0.320105
INFO:tensorflow:global_step/sec: 118.003
INFO:tensorflow:step = 424106, loss = 0.494732
INFO:tensorflow:global_step/sec: 116.882
INFO:tensorflow:step = 424206, loss = 0.32872
INFO:tensorflow:global_step/sec: 104.324
INFO:tensorflow:step = 424306, loss = 0.566186
INFO:tensorflow:global_step/sec: 92.6228
INFO:tensorflow:step = 424406, loss = 0.558004
INFO:tensorflow:global_step/sec: 95.7526
INFO:tensorflow:step = 424506, loss = 0.46077
INFO:tensorflow:global_step/sec: 106.357
INFO:tensorflow:step = 424606, loss = 0.35891
INFO:tensorflow:global_step/sec: 106.978
INFO:tensorflow:step = 424706, loss = 0.398465
INFO:tensorflow:global_step/sec: 97.3041
INFO:tensorflow:step = 424806, loss = 0.312876
INFO:tensorflow:global_step/sec: 73.6504
INFO:tensorflow:step = 424906, loss = 0.797811
INFO:tensorflow:global_step/sec: 77.21
INFO:tensorflow:step = 425006, loss = 0.429547
INFO:tensorflow:global_step/sec: 112.121
INFO:tensorflow:step = 425106, loss = 0.539678
INFO:tensorflow:global_step/sec: 111.162
INFO:tensorflow:step = 425206, loss = 0.451492
INFO:tensorflow:global_step/sec: 117.87
INFO:tensorflow:step = 425306, loss = 0.302857
INFO:tensorflow:global_step/sec: 104.866
INFO:tensorflow:step = 425406, loss = 0.412508
INFO:tensorflow:global_step/sec: 107.019
INFO:tensorflow:step = 425506, loss = 0.324712
INFO:tensorflow:global_step/sec: 111.079
INFO:tensorflow:step = 425606, loss = 0.338704
INFO:tensorflow:global_step/sec: 95.8107
INFO:tensorflow:step = 425706, loss = 0.357042
INFO:tensorflow:global_step/sec: 45.6431
INFO:tensorflow:step = 425806, loss = 0.533395
INFO:tensorflow:global_step/sec: 61.0767
INFO:tensorflow:step = 425906, loss = 0.634868
INFO:tensorflow:global_step/sec: 118.922
INFO:tensorflow:step = 426006, loss = 0.364024
INFO:tensorflow:global_step/sec: 118.658
INFO:tensorflow:step = 426106, loss = 0.70469
INFO:tensorflow:global_step/sec: 83.6482
INFO:tensorflow:step = 426206, loss = 0.596489
INFO:tensorflow:global_step/sec: 118.636
INFO:tensorflow:step = 426306, loss = 0.621488
INFO:tensorflow:global_step/sec: 114.693
INFO:tensorflow:step = 426406, loss = 0.385896
INFO:tensorflow:global_step/sec: 90.7509
INFO:tensorflow:step = 426506, loss = 0.449903
INFO:tensorflow:global_step/sec: 100.92
INFO:tensorflow:step = 426606, loss = 0.585428
INFO:tensorflow:global_step/sec: 91.7549
INFO:tensorflow:step = 426706, loss = 0.379231
INFO:tensorflow:global_step/sec: 102.073
INFO:tensorflow:step = 426806, loss = 0.305658
INFO:tensorflow:global_step/sec: 86.8891
INFO:tensorflow:step = 426906, loss = 0.486742
INFO:tensorflow:global_step/sec: 116.115
INFO:tensorflow:step = 427006, loss = 0.448885
INFO:tensorflow:global_step/sec: 113.674
INFO:tensorflow:step = 427106, loss = 0.497082
INFO:tensorflow:global_step/sec: 76.3542
INFO:tensorflow:step = 427206, loss = 0.561545
INFO:tensorflow:global_step/sec: 40.7942
INFO:tensorflow:step = 427306, loss = 0.401827
INFO:tensorflow:global_step/sec: 55.3136
INFO:tensorflow:step = 427406, loss = 0.365532
INFO:tensorflow:global_step/sec: 81.5264
INFO:tensorflow:step = 427506, loss = 0.400427
INFO:tensorflow:global_step/sec: 73.1214
INFO:tensorflow:step = 427606, loss = 0.475435
INFO:tensorflow:global_step/sec: 85.4748
INFO:tensorflow:step = 427706, loss = 0.442511
INFO:tensorflow:global_step/sec: 98.347
INFO:tensorflow:step = 427806, loss = 0.554806
INFO:tensorflow:global_step/sec: 100.024
INFO:tensorflow:step = 427906, loss = 0.415691
INFO:tensorflow:global_step/sec: 117.088
INFO:tensorflow:step = 428006, loss = 0.397549
INFO:tensorflow:global_step/sec: 118.519
INFO:tensorflow:step = 428106, loss = 0.394291
INFO:tensorflow:global_step/sec: 119.371
INFO:tensorflow:step = 428206, loss = 0.423157
INFO:tensorflow:global_step/sec: 103.546
INFO:tensorflow:step = 428306, loss = 0.55074
INFO:tensorflow:global_step/sec: 116.016
INFO:tensorflow:step = 428406, loss = 0.425674
INFO:tensorflow:global_step/sec: 116.804
INFO:tensorflow:step = 428506, loss = 0.402643
INFO:tensorflow:global_step/sec: 113.162
INFO:tensorflow:step = 428606, loss = 0.534744
INFO:tensorflow:global_step/sec: 105.82
INFO:tensorflow:step = 428706, loss = 0.354176
INFO:tensorflow:global_step/sec: 115.101
INFO:tensorflow:step = 428806, loss = 0.685939
INFO:tensorflow:global_step/sec: 111.404
INFO:tensorflow:step = 428906, loss = 0.487807
INFO:tensorflow:global_step/sec: 85.874
INFO:tensorflow:step = 429006, loss = 0.366385
INFO:tensorflow:global_step/sec: 106.414
INFO:tensorflow:step = 429106, loss = 0.580176
INFO:tensorflow:global_step/sec: 82.3936
INFO:tensorflow:step = 429206, loss = 0.529077
INFO:tensorflow:global_step/sec: 102.036
INFO:tensorflow:step = 429306, loss = 0.482415
INFO:tensorflow:global_step/sec: 109.876
INFO:tensorflow:step = 429406, loss = 0.406685
INFO:tensorflow:global_step/sec: 119.543
INFO:tensorflow:step = 429506, loss = 0.56468
INFO:tensorflow:global_step/sec: 111.397
INFO:tensorflow:step = 429606, loss = 0.436728
INFO:tensorflow:global_step/sec: 109.839
INFO:tensorflow:step = 429706, loss = 0.487103
INFO:tensorflow:global_step/sec: 105.931
INFO:tensorflow:step = 429806, loss = 0.482126
INFO:tensorflow:global_step/sec: 117.545
INFO:tensorflow:step = 429906, loss = 0.470042
INFO:tensorflow:global_step/sec: 119.026
INFO:tensorflow:step = 430006, loss = 0.512768
INFO:tensorflow:global_step/sec: 106.063
INFO:tensorflow:step = 430106, loss = 0.65634
INFO:tensorflow:global_step/sec: 94.0685
INFO:tensorflow:step = 430206, loss = 0.462901
INFO:tensorflow:global_step/sec: 92.7027
INFO:tensorflow:step = 430306, loss = 0.360102
INFO:tensorflow:global_step/sec: 95.9051
INFO:tensorflow:step = 430406, loss = 0.421326
INFO:tensorflow:global_step/sec: 103.234
INFO:tensorflow:step = 430506, loss = 0.496619
INFO:tensorflow:global_step/sec: 95.0533
INFO:tensorflow:step = 430606, loss = 0.551563
INFO:tensorflow:global_step/sec: 92.0804
INFO:tensorflow:step = 430706, loss = 0.429046
INFO:tensorflow:global_step/sec: 119.763
INFO:tensorflow:step = 430806, loss = 0.370887
INFO:tensorflow:global_step/sec: 93.3423
INFO:tensorflow:step = 430906, loss = 0.384966
INFO:tensorflow:global_step/sec: 111.896
INFO:tensorflow:step = 431006, loss = 0.450823
INFO:tensorflow:global_step/sec: 117.256
INFO:tensorflow:step = 431106, loss = 0.467991
INFO:tensorflow:global_step/sec: 118.708
INFO:tensorflow:step = 431206, loss = 0.492158
INFO:tensorflow:global_step/sec: 114.346
INFO:tensorflow:step = 431306, loss = 0.369902
INFO:tensorflow:global_step/sec: 118.309
INFO:tensorflow:step = 431406, loss = 0.52271
INFO:tensorflow:global_step/sec: 117.736
INFO:tensorflow:step = 431506, loss = 0.565111
INFO:tensorflow:global_step/sec: 102.908
INFO:tensorflow:step = 431606, loss = 0.451215
INFO:tensorflow:global_step/sec: 106.906
INFO:tensorflow:step = 431706, loss = 0.525432
INFO:tensorflow:global_step/sec: 112.931
INFO:tensorflow:step = 431806, loss = 0.482871
INFO:tensorflow:global_step/sec: 112.481
INFO:tensorflow:step = 431906, loss = 0.365422
INFO:tensorflow:global_step/sec: 110.639
INFO:tensorflow:step = 432006, loss = 0.538592
INFO:tensorflow:global_step/sec: 112.068
INFO:tensorflow:step = 432106, loss = 0.306204
INFO:tensorflow:global_step/sec: 112.721
INFO:tensorflow:step = 432206, loss = 0.334636
INFO:tensorflow:global_step/sec: 94.1291
INFO:tensorflow:step = 432306, loss = 0.415131
INFO:tensorflow:global_step/sec: 108.886
INFO:tensorflow:step = 432406, loss = 0.458054
INFO:tensorflow:global_step/sec: 109.498
INFO:tensorflow:step = 432506, loss = 0.513917
INFO:tensorflow:global_step/sec: 108.601
INFO:tensorflow:step = 432606, loss = 0.512376
INFO:tensorflow:global_step/sec: 111.294
INFO:tensorflow:step = 432706, loss = 0.317374
INFO:tensorflow:global_step/sec: 111.756
INFO:tensorflow:step = 432806, loss = 0.299387
INFO:tensorflow:global_step/sec: 110.081
INFO:tensorflow:step = 432906, loss = 0.510377
INFO:tensorflow:global_step/sec: 113.748
INFO:tensorflow:step = 433006, loss = 0.251561
INFO:tensorflow:global_step/sec: 112.519
INFO:tensorflow:step = 433106, loss = 0.531615
INFO:tensorflow:global_step/sec: 113.012
INFO:tensorflow:step = 433206, loss = 0.516377
INFO:tensorflow:global_step/sec: 111.531
INFO:tensorflow:step = 433306, loss = 0.498984
INFO:tensorflow:global_step/sec: 89.0442
INFO:tensorflow:step = 433406, loss = 0.416305
INFO:tensorflow:global_step/sec: 81.585
INFO:tensorflow:step = 433506, loss = 0.393011
INFO:tensorflow:global_step/sec: 75.6112
INFO:tensorflow:step = 433606, loss = 0.397339
INFO:tensorflow:global_step/sec: 98.3975
INFO:tensorflow:step = 433706, loss = 0.430039
INFO:tensorflow:global_step/sec: 110.766
INFO:tensorflow:step = 433806, loss = 0.417845
INFO:tensorflow:global_step/sec: 108.742
INFO:tensorflow:step = 433906, loss = 0.528167
INFO:tensorflow:global_step/sec: 106.831
INFO:tensorflow:step = 434006, loss = 0.490619
INFO:tensorflow:global_step/sec: 99.6313
INFO:tensorflow:step = 434106, loss = 0.49169
INFO:tensorflow:global_step/sec: 107.99
INFO:tensorflow:step = 434206, loss = 0.448148
INFO:tensorflow:global_step/sec: 94.5385
INFO:tensorflow:step = 434306, loss = 0.342449
INFO:tensorflow:global_step/sec: 97.6068
INFO:tensorflow:step = 434406, loss = 0.392912
INFO:tensorflow:global_step/sec: 85.9497
INFO:tensorflow:step = 434506, loss = 0.416774
INFO:tensorflow:global_step/sec: 104.088
INFO:tensorflow:step = 434606, loss = 0.43352
INFO:tensorflow:global_step/sec: 105.132
INFO:tensorflow:step = 434706, loss = 0.424444
INFO:tensorflow:global_step/sec: 103.279
INFO:tensorflow:step = 434806, loss = 0.395388
INFO:tensorflow:global_step/sec: 44.0608
INFO:tensorflow:step = 434906, loss = 0.513787
INFO:tensorflow:global_step/sec: 55.7899
INFO:tensorflow:step = 435006, loss = 0.525513
INFO:tensorflow:global_step/sec: 49.0053
INFO:tensorflow:step = 435106, loss = 0.495579
INFO:tensorflow:global_step/sec: 112.45
INFO:tensorflow:step = 435206, loss = 0.351461
INFO:tensorflow:global_step/sec: 62.0605
INFO:tensorflow:step = 435306, loss = 0.39851
INFO:tensorflow:global_step/sec: 72.2697
INFO:tensorflow:step = 435406, loss = 0.376165
INFO:tensorflow:global_step/sec: 83.5916
INFO:tensorflow:step = 435506, loss = 0.354302
INFO:tensorflow:global_step/sec: 44.0844
INFO:tensorflow:step = 435606, loss = 0.337326
INFO:tensorflow:global_step/sec: 59.8255
INFO:tensorflow:step = 435706, loss = 0.322885
INFO:tensorflow:global_step/sec: 41.313
INFO:tensorflow:step = 435806, loss = 0.382056
INFO:tensorflow:global_step/sec: 39.553
INFO:tensorflow:step = 435906, loss = 0.432241
INFO:tensorflow:global_step/sec: 53.5287
INFO:tensorflow:step = 436006, loss = 0.451678
INFO:tensorflow:global_step/sec: 46.9819
INFO:tensorflow:step = 436106, loss = 0.385194
INFO:tensorflow:global_step/sec: 53.2343
INFO:tensorflow:step = 436206, loss = 0.532502
INFO:tensorflow:global_step/sec: 45.8845
INFO:tensorflow:step = 436306, loss = 0.420789
INFO:tensorflow:global_step/sec: 39.4492
INFO:tensorflow:step = 436406, loss = 0.452752
INFO:tensorflow:global_step/sec: 75.1014
INFO:tensorflow:step = 436506, loss = 0.43155
INFO:tensorflow:global_step/sec: 38.4569
INFO:tensorflow:step = 436606, loss = 0.38609
INFO:tensorflow:global_step/sec: 60.0908
INFO:tensorflow:step = 436706, loss = 0.548012
INFO:tensorflow:global_step/sec: 41.2633
INFO:tensorflow:step = 436806, loss = 0.419649
INFO:tensorflow:global_step/sec: 60.0169
INFO:tensorflow:step = 436906, loss = 0.466492
INFO:tensorflow:global_step/sec: 64.1797
INFO:tensorflow:step = 437006, loss = 0.366808
INFO:tensorflow:global_step/sec: 88.9339
INFO:tensorflow:step = 437106, loss = 0.498089
INFO:tensorflow:global_step/sec: 92.7881
INFO:tensorflow:step = 437206, loss = 0.382282
INFO:tensorflow:global_step/sec: 84.775
INFO:tensorflow:step = 437306, loss = 0.505018
INFO:tensorflow:global_step/sec: 105.173
INFO:tensorflow:step = 437406, loss = 0.507503
INFO:tensorflow:global_step/sec: 68.7711
INFO:tensorflow:step = 437506, loss = 0.529242
INFO:tensorflow:global_step/sec: 41.5779
INFO:tensorflow:step = 437606, loss = 0.552276
INFO:tensorflow:global_step/sec: 53.8395
INFO:tensorflow:step = 437706, loss = 0.447926
INFO:tensorflow:global_step/sec: 55.9332
INFO:tensorflow:step = 437806, loss = 0.362302
INFO:tensorflow:global_step/sec: 74.2658
INFO:tensorflow:step = 437906, loss = 0.463032
INFO:tensorflow:global_step/sec: 43.4752
INFO:tensorflow:step = 438006, loss = 0.436154
INFO:tensorflow:global_step/sec: 46.2918
INFO:tensorflow:step = 438106, loss = 0.412675
INFO:tensorflow:global_step/sec: 50.3416
INFO:tensorflow:step = 438206, loss = 0.373837
INFO:tensorflow:global_step/sec: 31.7823
INFO:tensorflow:step = 438306, loss = 0.36443
INFO:tensorflow:global_step/sec: 67.9552
INFO:tensorflow:step = 438406, loss = 0.581339
INFO:tensorflow:global_step/sec: 44.9161
INFO:tensorflow:step = 438506, loss = 0.351752
INFO:tensorflow:Saving checkpoints for 438596 into .opt_logs/lstm_stock/model.ckpt.
INFO:tensorflow:global_step/sec: 7.02513
INFO:tensorflow:step = 438606, loss = 0.574096
INFO:tensorflow:global_step/sec: 35.0276
INFO:tensorflow:step = 438706, loss = 0.368276
INFO:tensorflow:global_step/sec: 40.3259
INFO:tensorflow:step = 438806, loss = 0.377791
INFO:tensorflow:global_step/sec: 75.692
INFO:tensorflow:step = 438906, loss = 0.418554
INFO:tensorflow:Saving checkpoints for 439005 into .opt_logs/lstm_stock/model.ckpt.
INFO:tensorflow:Loss for final step: 0.258574.
Out[7]:
Estimator(params=None)
In [8]:
# Make the prediction
predicted = list(regressor.predict(X['test']))
# Calculate the error
score = mean_squared_error(predicted, y['test'])
print ("MSE: %f" % score)
WARNING:tensorflow:From <ipython-input-8-d096f593ed28>:2: calling BaseEstimator.predict (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
est = Estimator(...) -> est = SKCompat(Estimator(...))
/anaconda/lib/python3.5/site-packages/tensorflow/python/util/deprecation.py:247: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.
equality = a == b
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/models.py:107: mean_squared_error_regressor (from tensorflow.contrib.learn.python.learn.ops.losses_ops) is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Use `tf.contrib.losses.mean_squared_error` and explicit logits computation.
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/ops/losses_ops.py:39: mean_squared_error (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.
Instructions for updating:
Use tf.losses.mean_squared_error instead.
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/losses/python/losses/loss_ops.py:530: compute_weighted_loss (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.
Instructions for updating:
Use tf.losses.compute_weighted_loss instead.
WARNING:tensorflow:From /anaconda/lib/python3.5/site-packages/tensorflow/contrib/losses/python/losses/loss_ops.py:151: add_loss (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.
Instructions for updating:
Use tf.losses.add_loss instead.
MSE: 0.157704
In [9]:
# plot the data
actual = close.ix[len(close)-len(predicted):]
predicted = pd.Series(predicted, index=actual.index)
comp = pd.DataFrame({"Actual": actual,"Pred":predicted})
plot_predicted = pred.props.price.ix[len(pred.props.price)-len(predicted):].plot(label='SPY', legend=True)
plot_test = comp.Pred.plot(label='Predicted SPY', legend=True)
plt.ylabel("Share Price [$]")
plt.show()
We can see that the preciction is the shape of the real data, however there is a delay. This is probably due to using the delayed exponential mean.
I have not made trading predictions using this model as the computation time is too long. But the trading model is presented in DL_BuySell.py
In [ ]:
Content source: simonward86/MySJcLqwwx
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