In [25]:
# https://www.tensorflow.org/extend/estimators
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
# tensorflow
import tensorflow as tf
import tensorflow.contrib.rnn as rnn
import tensorflow.contrib.learn as tflearn
import tensorflow.contrib.layers as tflayers
# keras
from tensorflow.contrib.keras.python.keras.layers import Dense, LSTM, GRU, Activation
from tensorflow.contrib.keras.python.keras.utils.data_utils import get_file
# input data
from tensorflow.examples.tutorials.mnist import input_data
# estimators
from tensorflow.contrib import learn
# estimator "builder"
from tensorflow.contrib.learn.python.learn.estimators import model_fn as model_fn_lib
# helpers
import numpy as np
import random
import sys
# enable logs
tf.logging.set_verbosity(tf.logging.INFO)
def sample(preds, temperature=1.0):
#print(preds)
return np.argmax(preds)
# THE MODEL
def model_fn(features, targets, mode, params):
"""Model function for Estimator."""
# 1. Configure the model via TensorFlow operations
# First, build all the model, a good idea is using Keras or tf.layers
# since these are high-level API's
#lstm = GRU(128, input_shape=(params["maxlen"], params["vocab_size"]))(features)
#preds = Dense(params["vocab_size"], activation='sigmoid')(lstm)
# 0. Reformat input shape to become a sequence
lstm1 = GRU(128, input_shape=(params["maxlen"], params["vocab_size"]),
return_sequences=True)(features)
lstm2 = GRU(128)(lstm1)
preds = Dense(params["vocab_size"])(lstm2)
preds_softmax = Activation("softmax")(preds)
# 2. Define the loss function for training/evaluation
loss = None
train_op = None
# Calculate Loss (for both TRAIN and EVAL modes)
if mode != learn.ModeKeys.PREDICT:
loss = tf.losses.softmax_cross_entropy(
onehot_labels=targets, logits=preds)
# 3. Define the training operation/optimizer
# Configure the Training Op (for TRAIN mode)
if mode == learn.ModeKeys.TRAIN:
train_op = tf.contrib.layers.optimize_loss(
loss=loss,
global_step=tf.contrib.framework.get_global_step(),
learning_rate=params["learning_rate"],
optimizer="RMSProp"
)
# 4. Generate predictions
predictions_dict = {
"preds": preds_softmax
}
# 5. Define how you want to evaluate the model
metrics = {
"accuracy": tf.metrics.accuracy(tf.argmax(input=preds_softmax, axis=1), tf.argmax(input=targets, axis=1))
}
# 6. Return predictions/loss/train_op/eval_metric_ops in ModelFnOps object
return model_fn_lib.ModelFnOps(
mode=mode,
predictions=predictions_dict,
loss=loss,
train_op=train_op,
eval_metric_ops=metrics)
In [2]:
print('Getting data')
#path = get_file('nietzsche.txt', origin='https://s3.amazonaws.com/text-datasets/nietzsche.txt')
path = 'shakespeare.txt'
text = open(path).read().lower()
print('corpus length:', len(text))
chars = sorted(list(set(text)))
print('total chars:', len(chars))
char_indices = dict((c, i) for i, c in enumerate(chars))
indices_char = dict((i, c) for i, c in enumerate(chars))
# cut the text in semi-redundant sequences of maxlen characters
maxlen = 40
step = 1
sentences = []
next_chars = []
for i in range(0, len(text) - maxlen, step):
sentences.append(text[i: i + maxlen])
next_chars.append(text[i + maxlen])
print('nb sequences:', len(sentences))
print('Vectorization...')
X = np.zeros((len(sentences), maxlen, len(chars)), dtype=np.float32)
y = np.zeros((len(sentences), len(chars)), dtype=np.float32)
for i, sentence in enumerate(sentences):
for t, char in enumerate(sentence):
X[i, t, char_indices[char]] = 1
y[i, char_indices[next_chars[i]]] = 1
print(X[0])
Getting data
corpus length: 1115394
total chars: 39
nb sequences: 1115354
Vectorization...
[[ 0. 0. 0. ..., 0. 0. 0.]
[ 0. 0. 0. ..., 0. 0. 0.]
[ 0. 0. 0. ..., 0. 0. 0.]
...,
[ 0. 0. 0. ..., 0. 0. 0.]
[ 0. 0. 0. ..., 0. 0. 0.]
[ 0. 0. 0. ..., 0. 0. 0.]]
In [28]:
# PARAMETERS
LEARNING_RATE = 0.01
BATCH_SIZE = 128
STEPS = 10000
NUM_OUTPUTS_PRED = 40
# Set model params
model_params = {"learning_rate": LEARNING_RATE, "vocab_size": len(chars), "maxlen": maxlen}
# Instantiate Estimator
nn = tf.contrib.learn.Estimator(model_fn=model_fn, params=model_params)
# Score accuracy
for iteration in range(1, 600):
print()
print('-' * 50)
print('Iteration', iteration)
# Fit
print('-' * 40)
print("Training")
print('-' * 40)
nn.fit(x=X, y=y, steps=STEPS, batch_size=BATCH_SIZE)
INFO:tensorflow:Using default config.
INFO:tensorflow:Using config: {'_tf_config': gpu_options {
per_process_gpu_memory_fraction: 1
}
, '_task_type': None, '_save_checkpoints_steps': None, '_model_dir': None, '_tf_random_seed': None, '_is_chief': True, '_task_id': 0, '_master': '', '_environment': 'local', '_save_checkpoints_secs': 600, '_keep_checkpoint_max': 5, '_num_worker_replicas': 0, '_evaluation_master': '', '_save_summary_steps': 100, '_keep_checkpoint_every_n_hours': 10000, '_num_ps_replicas': 0, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f6341474588>}
WARNING:tensorflow:Using temporary folder as model directory: /tmp/tmpb3eyyydg
--------------------------------------------------
Iteration 1
----------------------------------------
Training
----------------------------------------
WARNING:tensorflow:From <ipython-input-28-c9008343d737>:24: 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-28-c9008343d737>:24: 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(...))
WARNING:tensorflow:From <ipython-input-28-c9008343d737>:24: 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(...))
/usr/local/lib/python3.4/dist-packages/tensorflow/python/util/deprecation.py:248: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.
equality = a == b
INFO:tensorflow:Create CheckpointSaverHook.
INFO:tensorflow:Saving checkpoints for 1 into /tmp/tmpb3eyyydg/model.ckpt.
INFO:tensorflow:loss = 3.66463, step = 1
INFO:tensorflow:global_step/sec: 6.73345
INFO:tensorflow:loss = 3.11169, step = 101 (14.851 sec)
INFO:tensorflow:global_step/sec: 6.73881
INFO:tensorflow:loss = 2.57609, step = 201 (14.839 sec)
INFO:tensorflow:global_step/sec: 6.63066
INFO:tensorflow:loss = 2.2082, step = 301 (15.081 sec)
INFO:tensorflow:global_step/sec: 6.5516
INFO:tensorflow:loss = 2.36044, step = 401 (15.263 sec)
INFO:tensorflow:global_step/sec: 6.67613
INFO:tensorflow:loss = 2.12642, step = 501 (14.979 sec)
INFO:tensorflow:global_step/sec: 6.61581
INFO:tensorflow:loss = 2.0016, step = 601 (15.115 sec)
INFO:tensorflow:global_step/sec: 6.3953
INFO:tensorflow:loss = 1.99158, step = 701 (15.636 sec)
INFO:tensorflow:global_step/sec: 6.60731
INFO:tensorflow:loss = 2.09668, step = 801 (15.135 sec)
INFO:tensorflow:global_step/sec: 6.46653
INFO:tensorflow:loss = 1.94819, step = 901 (15.464 sec)
INFO:tensorflow:global_step/sec: 6.69827
INFO:tensorflow:loss = 1.98563, step = 1001 (14.929 sec)
INFO:tensorflow:global_step/sec: 6.62779
INFO:tensorflow:loss = 2.14272, step = 1101 (15.088 sec)
INFO:tensorflow:global_step/sec: 6.73226
INFO:tensorflow:loss = 1.71009, step = 1201 (14.854 sec)
INFO:tensorflow:global_step/sec: 6.78307
INFO:tensorflow:loss = 1.94125, step = 1301 (14.743 sec)
INFO:tensorflow:global_step/sec: 6.63439
INFO:tensorflow:loss = 1.77978, step = 1401 (15.073 sec)
INFO:tensorflow:global_step/sec: 6.70101
INFO:tensorflow:loss = 1.88542, step = 1501 (14.923 sec)
INFO:tensorflow:global_step/sec: 6.74343
INFO:tensorflow:loss = 1.82332, step = 1601 (14.829 sec)
INFO:tensorflow:global_step/sec: 6.81863
INFO:tensorflow:loss = 2.14602, step = 1701 (14.666 sec)
INFO:tensorflow:global_step/sec: 6.84734
INFO:tensorflow:loss = 1.97756, step = 1801 (14.604 sec)
INFO:tensorflow:global_step/sec: 6.69331
INFO:tensorflow:loss = 1.82729, step = 1901 (14.940 sec)
INFO:tensorflow:global_step/sec: 6.83327
INFO:tensorflow:loss = 1.91847, step = 2001 (14.634 sec)
INFO:tensorflow:global_step/sec: 6.83907
INFO:tensorflow:loss = 1.71896, step = 2101 (14.622 sec)
INFO:tensorflow:global_step/sec: 6.80297
INFO:tensorflow:loss = 1.77582, step = 2201 (14.699 sec)
INFO:tensorflow:global_step/sec: 6.85883
INFO:tensorflow:loss = 2.14473, step = 2301 (14.580 sec)
INFO:tensorflow:global_step/sec: 6.90686
INFO:tensorflow:loss = 2.07307, step = 2401 (14.478 sec)
INFO:tensorflow:global_step/sec: 6.92135
INFO:tensorflow:loss = 1.93684, step = 2501 (14.448 sec)
INFO:tensorflow:global_step/sec: 6.9415
INFO:tensorflow:loss = 2.08349, step = 2601 (14.406 sec)
INFO:tensorflow:global_step/sec: 6.70055
INFO:tensorflow:loss = 1.68604, step = 2701 (14.924 sec)
INFO:tensorflow:global_step/sec: 6.85602
INFO:tensorflow:loss = 1.89287, step = 2801 (14.586 sec)
INFO:tensorflow:global_step/sec: 6.89494
INFO:tensorflow:loss = 1.84995, step = 2901 (14.503 sec)
INFO:tensorflow:global_step/sec: 6.77646
INFO:tensorflow:loss = 1.76912, step = 3001 (14.757 sec)
INFO:tensorflow:global_step/sec: 6.68529
INFO:tensorflow:loss = 1.89526, step = 3101 (14.958 sec)
INFO:tensorflow:global_step/sec: 6.57561
INFO:tensorflow:loss = 1.6698, step = 3201 (15.208 sec)
INFO:tensorflow:global_step/sec: 6.38189
INFO:tensorflow:loss = 1.72777, step = 3301 (15.669 sec)
INFO:tensorflow:global_step/sec: 6.38287
INFO:tensorflow:loss = 1.87946, step = 3401 (15.667 sec)
INFO:tensorflow:global_step/sec: 6.88148
INFO:tensorflow:loss = 1.90305, step = 3501 (14.532 sec)
INFO:tensorflow:global_step/sec: 6.69948
INFO:tensorflow:loss = 1.68267, step = 3601 (14.926 sec)
INFO:tensorflow:global_step/sec: 6.84833
INFO:tensorflow:loss = 2.0533, step = 3701 (14.602 sec)
INFO:tensorflow:global_step/sec: 6.5583
INFO:tensorflow:loss = 1.77252, step = 3801 (15.248 sec)
INFO:tensorflow:global_step/sec: 6.52343
INFO:tensorflow:loss = 1.85812, step = 3901 (15.329 sec)
INFO:tensorflow:global_step/sec: 6.89939
INFO:tensorflow:loss = 1.55516, step = 4001 (14.494 sec)
INFO:tensorflow:Saving checkpoints for 4019 into /tmp/tmpb3eyyydg/model.ckpt.
INFO:tensorflow:global_step/sec: 6.42768
INFO:tensorflow:loss = 1.93629, step = 4101 (15.558 sec)
INFO:tensorflow:global_step/sec: 6.83746
INFO:tensorflow:loss = 1.92823, step = 4201 (14.625 sec)
INFO:tensorflow:global_step/sec: 6.66711
INFO:tensorflow:loss = 1.81239, step = 4301 (14.999 sec)
INFO:tensorflow:global_step/sec: 6.53779
INFO:tensorflow:loss = 1.70003, step = 4401 (15.296 sec)
INFO:tensorflow:global_step/sec: 6.64906
INFO:tensorflow:loss = 1.96269, step = 4501 (15.040 sec)
INFO:tensorflow:global_step/sec: 6.7806
INFO:tensorflow:loss = 1.88445, step = 4601 (14.748 sec)
INFO:tensorflow:global_step/sec: 6.46409
INFO:tensorflow:loss = 1.83989, step = 4701 (15.470 sec)
INFO:tensorflow:global_step/sec: 6.57378
INFO:tensorflow:loss = 2.01499, step = 4801 (15.213 sec)
INFO:tensorflow:global_step/sec: 6.61291
INFO:tensorflow:loss = 1.79146, step = 4901 (15.121 sec)
INFO:tensorflow:global_step/sec: 6.70305
INFO:tensorflow:loss = 1.9002, step = 5001 (14.919 sec)
INFO:tensorflow:global_step/sec: 6.43195
INFO:tensorflow:loss = 1.67045, step = 5101 (15.547 sec)
INFO:tensorflow:global_step/sec: 6.45031
INFO:tensorflow:loss = 1.9173, step = 5201 (15.503 sec)
INFO:tensorflow:global_step/sec: 6.42163
INFO:tensorflow:loss = 1.77776, step = 5301 (15.572 sec)
INFO:tensorflow:global_step/sec: 6.43873
INFO:tensorflow:loss = 1.81222, step = 5401 (15.531 sec)
INFO:tensorflow:global_step/sec: 6.44515
INFO:tensorflow:loss = 2.11882, step = 5501 (15.516 sec)
INFO:tensorflow:global_step/sec: 6.36898
INFO:tensorflow:loss = 1.63466, step = 5601 (15.701 sec)
INFO:tensorflow:global_step/sec: 6.35928
INFO:tensorflow:loss = 1.85063, step = 5701 (15.725 sec)
INFO:tensorflow:global_step/sec: 6.39468
INFO:tensorflow:loss = 1.65461, step = 5801 (15.638 sec)
INFO:tensorflow:global_step/sec: 6.40248
INFO:tensorflow:loss = 1.7843, step = 5901 (15.619 sec)
INFO:tensorflow:global_step/sec: 6.57913
INFO:tensorflow:loss = 1.78454, step = 6001 (15.200 sec)
INFO:tensorflow:global_step/sec: 6.51546
INFO:tensorflow:loss = 1.84334, step = 6101 (15.348 sec)
INFO:tensorflow:global_step/sec: 6.46745
INFO:tensorflow:loss = 1.80359, step = 6201 (15.462 sec)
INFO:tensorflow:global_step/sec: 6.48594
INFO:tensorflow:loss = 1.55682, step = 6301 (15.418 sec)
INFO:tensorflow:global_step/sec: 6.49107
INFO:tensorflow:loss = 2.02087, step = 6401 (15.406 sec)
INFO:tensorflow:global_step/sec: 6.46097
INFO:tensorflow:loss = 1.67637, step = 6501 (15.477 sec)
INFO:tensorflow:global_step/sec: 6.53119
INFO:tensorflow:loss = 1.66554, step = 6601 (15.311 sec)
INFO:tensorflow:global_step/sec: 6.44324
INFO:tensorflow:loss = 1.889, step = 6701 (15.520 sec)
INFO:tensorflow:global_step/sec: 6.49192
INFO:tensorflow:loss = 1.78155, step = 6801 (15.404 sec)
INFO:tensorflow:global_step/sec: 6.52685
INFO:tensorflow:loss = 1.62006, step = 6901 (15.321 sec)
INFO:tensorflow:global_step/sec: 6.37616
INFO:tensorflow:loss = 1.76569, step = 7001 (15.683 sec)
INFO:tensorflow:global_step/sec: 6.59445
INFO:tensorflow:loss = 1.76614, step = 7101 (15.164 sec)
INFO:tensorflow:global_step/sec: 6.58087
INFO:tensorflow:loss = 1.71921, step = 7201 (15.196 sec)
INFO:tensorflow:global_step/sec: 6.59366
INFO:tensorflow:loss = 1.65369, step = 7301 (15.166 sec)
INFO:tensorflow:global_step/sec: 6.59498
INFO:tensorflow:loss = 1.86757, step = 7401 (15.163 sec)
INFO:tensorflow:global_step/sec: 6.70763
INFO:tensorflow:loss = 1.69586, step = 7501 (14.908 sec)
INFO:tensorflow:global_step/sec: 6.67181
INFO:tensorflow:loss = 1.65873, step = 7601 (14.988 sec)
INFO:tensorflow:global_step/sec: 6.55402
INFO:tensorflow:loss = 1.7183, step = 7701 (15.258 sec)
INFO:tensorflow:global_step/sec: 6.6686
INFO:tensorflow:loss = 1.90489, step = 7801 (14.996 sec)
INFO:tensorflow:global_step/sec: 6.67061
INFO:tensorflow:loss = 1.61757, step = 7901 (14.991 sec)
INFO:tensorflow:Saving checkpoints for 7939 into /tmp/tmpb3eyyydg/model.ckpt.
INFO:tensorflow:global_step/sec: 6.09731
INFO:tensorflow:loss = 1.96585, step = 8001 (16.401 sec)
INFO:tensorflow:global_step/sec: 6.68294
INFO:tensorflow:loss = 1.54977, step = 8101 (14.963 sec)
INFO:tensorflow:global_step/sec: 6.60993
INFO:tensorflow:loss = 1.64236, step = 8201 (15.129 sec)
INFO:tensorflow:global_step/sec: 6.61586
INFO:tensorflow:loss = 1.56314, step = 8301 (15.115 sec)
INFO:tensorflow:global_step/sec: 6.67163
INFO:tensorflow:loss = 1.74221, step = 8401 (14.989 sec)
INFO:tensorflow:global_step/sec: 6.78086
INFO:tensorflow:loss = 1.74049, step = 8501 (14.747 sec)
INFO:tensorflow:global_step/sec: 6.71027
INFO:tensorflow:loss = 1.59981, step = 8601 (14.903 sec)
INFO:tensorflow:global_step/sec: 6.68742
INFO:tensorflow:loss = 1.89076, step = 8701 (14.953 sec)
INFO:tensorflow:global_step/sec: 6.73103
INFO:tensorflow:loss = 1.49434, step = 8801 (14.857 sec)
INFO:tensorflow:global_step/sec: 6.89386
INFO:tensorflow:loss = 1.71345, step = 8901 (14.506 sec)
INFO:tensorflow:global_step/sec: 6.87358
INFO:tensorflow:loss = 2.07762, step = 9001 (14.548 sec)
INFO:tensorflow:global_step/sec: 6.88136
INFO:tensorflow:loss = 2.14198, step = 9101 (14.532 sec)
INFO:tensorflow:global_step/sec: 6.68367
INFO:tensorflow:loss = 3.31467, step = 9201 (14.962 sec)
INFO:tensorflow:global_step/sec: 6.54802
INFO:tensorflow:loss = 3.09743, step = 9301 (15.272 sec)
INFO:tensorflow:global_step/sec: 6.80104
INFO:tensorflow:loss = 3.22471, step = 9401 (14.704 sec)
INFO:tensorflow:global_step/sec: 6.95361
INFO:tensorflow:loss = 3.13789, step = 9501 (14.381 sec)
INFO:tensorflow:global_step/sec: 6.91033
INFO:tensorflow:loss = 3.20369, step = 9601 (14.471 sec)
INFO:tensorflow:global_step/sec: 6.92991
INFO:tensorflow:loss = 3.36464, step = 9701 (14.430 sec)
INFO:tensorflow:global_step/sec: 6.76151
INFO:tensorflow:loss = 3.16024, step = 9801 (14.790 sec)
INFO:tensorflow:global_step/sec: 6.66131
INFO:tensorflow:loss = 3.08757, step = 9901 (15.012 sec)
INFO:tensorflow:Saving checkpoints for 10000 into /tmp/tmpb3eyyydg/model.ckpt.
INFO:tensorflow:Loss for final step: 3.14102.
--------------------------------------------------
Iteration 2
----------------------------------------
Training
----------------------------------------
WARNING:tensorflow:From <ipython-input-28-c9008343d737>:24: 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-28-c9008343d737>:24: 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(...))
WARNING:tensorflow:From <ipython-input-28-c9008343d737>:24: 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(...))
INFO:tensorflow:Create CheckpointSaverHook.
INFO:tensorflow:Restoring parameters from /tmp/tmpb3eyyydg/model.ckpt-10000
INFO:tensorflow:Saving checkpoints for 10001 into /tmp/tmpb3eyyydg/model.ckpt.
INFO:tensorflow:loss = 3.02254, step = 10001
INFO:tensorflow:global_step/sec: 6.87455
INFO:tensorflow:loss = 3.13725, step = 10101 (14.547 sec)
INFO:tensorflow:global_step/sec: 6.94521
INFO:tensorflow:loss = 3.20994, step = 10201 (14.398 sec)
INFO:tensorflow:global_step/sec: 6.97284
INFO:tensorflow:loss = 3.22871, step = 10301 (14.341 sec)
INFO:tensorflow:global_step/sec: 6.88516
INFO:tensorflow:loss = 3.22394, step = 10401 (14.524 sec)
INFO:tensorflow:global_step/sec: 6.79148
INFO:tensorflow:loss = 3.12883, step = 10501 (14.724 sec)
INFO:tensorflow:global_step/sec: 6.46741
INFO:tensorflow:loss = 3.04938, step = 10601 (15.462 sec)
INFO:tensorflow:global_step/sec: 6.75263
INFO:tensorflow:loss = 3.06904, step = 10701 (14.809 sec)
INFO:tensorflow:global_step/sec: 6.83355
INFO:tensorflow:loss = 3.09266, step = 10801 (14.634 sec)
INFO:tensorflow:global_step/sec: 6.80697
INFO:tensorflow:loss = 2.99133, step = 10901 (14.691 sec)
INFO:tensorflow:global_step/sec: 6.82539
INFO:tensorflow:loss = 3.12591, step = 11001 (14.651 sec)
INFO:tensorflow:global_step/sec: 6.84007
INFO:tensorflow:loss = 3.30762, step = 11101 (14.620 sec)
INFO:tensorflow:global_step/sec: 6.65386
INFO:tensorflow:loss = 3.07087, step = 11201 (15.029 sec)
INFO:tensorflow:global_step/sec: 6.76419
INFO:tensorflow:loss = 3.07753, step = 11301 (14.784 sec)
INFO:tensorflow:global_step/sec: 6.84286
INFO:tensorflow:loss = 3.01707, step = 11401 (14.614 sec)
INFO:tensorflow:global_step/sec: 6.84529
INFO:tensorflow:loss = 3.06243, step = 11501 (14.609 sec)
INFO:tensorflow:global_step/sec: 6.83676
INFO:tensorflow:loss = 3.08152, step = 11601 (14.627 sec)
INFO:tensorflow:global_step/sec: 6.71521
INFO:tensorflow:loss = 3.1759, step = 11701 (14.892 sec)
INFO:tensorflow:global_step/sec: 6.80408
INFO:tensorflow:loss = 3.08926, step = 11801 (14.697 sec)
INFO:tensorflow:global_step/sec: 6.7007
INFO:tensorflow:loss = 3.14384, step = 11901 (14.924 sec)
INFO:tensorflow:global_step/sec: 6.82601
INFO:tensorflow:loss = 3.0604, step = 12001 (14.650 sec)
INFO:tensorflow:global_step/sec: 6.89824
INFO:tensorflow:loss = 3.07297, step = 12101 (14.496 sec)
INFO:tensorflow:global_step/sec: 6.8611
INFO:tensorflow:loss = 3.183, step = 12201 (14.575 sec)
INFO:tensorflow:global_step/sec: 6.8568
INFO:tensorflow:loss = 3.2714, step = 12301 (14.584 sec)
INFO:tensorflow:global_step/sec: 6.88843
INFO:tensorflow:loss = 3.1505, step = 12401 (14.517 sec)
INFO:tensorflow:global_step/sec: 6.67464
INFO:tensorflow:loss = 3.18656, step = 12501 (14.982 sec)
INFO:tensorflow:global_step/sec: 6.69162
INFO:tensorflow:loss = 3.25563, step = 12601 (14.944 sec)
INFO:tensorflow:global_step/sec: 6.71095
INFO:tensorflow:loss = 3.10958, step = 12701 (14.901 sec)
INFO:tensorflow:global_step/sec: 6.62488
INFO:tensorflow:loss = 3.06234, step = 12801 (15.095 sec)
---------------------------------------------------------------------------
KeyboardInterrupt Traceback (most recent call last)
<ipython-input-28-c9008343d737> in <module>()
22 print("Training")
23 print('-' * 40)
---> 24 nn.fit(x=X, y=y, steps=STEPS, batch_size=BATCH_SIZE)
/usr/local/lib/python3.4/dist-packages/tensorflow/python/util/deprecation.py in new_func(*args, **kwargs)
279 _call_location(), decorator_utils.get_qualified_name(func),
280 func.__module__, arg_name, date, instructions)
--> 281 return func(*args, **kwargs)
282 new_func.__doc__ = _add_deprecated_arg_notice_to_docstring(
283 func.__doc__, date, instructions)
/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py in fit(self, x, y, input_fn, steps, batch_size, monitors, max_steps)
412 _verify_input_args(x, y, input_fn, None, batch_size)
413 if x is not None:
--> 414 SKCompat(self).fit(x, y, batch_size, steps, max_steps, monitors)
415 return self
416
/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py in fit(self, x, y, batch_size, steps, max_steps, monitors)
1315 steps=steps,
1316 max_steps=max_steps,
-> 1317 monitors=all_monitors)
1318 return self
1319
/usr/local/lib/python3.4/dist-packages/tensorflow/python/util/deprecation.py in new_func(*args, **kwargs)
279 _call_location(), decorator_utils.get_qualified_name(func),
280 func.__module__, arg_name, date, instructions)
--> 281 return func(*args, **kwargs)
282 new_func.__doc__ = _add_deprecated_arg_notice_to_docstring(
283 func.__doc__, date, instructions)
/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py in fit(self, x, y, input_fn, steps, batch_size, monitors, max_steps)
428 hooks.append(basic_session_run_hooks.StopAtStepHook(steps, max_steps))
429
--> 430 loss = self._train_model(input_fn=input_fn, hooks=hooks)
431 logging.info('Loss for final step: %s.', loss)
432 return self
/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py in _train_model(self, input_fn, hooks)
976 loss = None
977 while not mon_sess.should_stop():
--> 978 _, loss = mon_sess.run([model_fn_ops.train_op, model_fn_ops.loss])
979 summary_io.SummaryWriterCache.clear()
980 return loss
/usr/local/lib/python3.4/dist-packages/tensorflow/python/training/monitored_session.py in run(self, fetches, feed_dict, options, run_metadata)
482 feed_dict=feed_dict,
483 options=options,
--> 484 run_metadata=run_metadata)
485
486 def should_stop(self):
/usr/local/lib/python3.4/dist-packages/tensorflow/python/training/monitored_session.py in run(self, fetches, feed_dict, options, run_metadata)
818 feed_dict=feed_dict,
819 options=options,
--> 820 run_metadata=run_metadata)
821 except _PREEMPTION_ERRORS as e:
822 logging.info('An error was raised. This may be due to a preemption in '
/usr/local/lib/python3.4/dist-packages/tensorflow/python/training/monitored_session.py in run(self, *args, **kwargs)
774
775 def run(self, *args, **kwargs):
--> 776 return self._sess.run(*args, **kwargs)
777
778
/usr/local/lib/python3.4/dist-packages/tensorflow/python/training/monitored_session.py in run(self, fetches, feed_dict, options, run_metadata)
928 feed_dict=feed_dict,
929 options=options,
--> 930 run_metadata=run_metadata)
931
932 for hook in self._hooks:
/usr/local/lib/python3.4/dist-packages/tensorflow/python/training/monitored_session.py in run(self, *args, **kwargs)
774
775 def run(self, *args, **kwargs):
--> 776 return self._sess.run(*args, **kwargs)
777
778
/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
776 try:
777 result = self._run(None, fetches, feed_dict, options_ptr,
--> 778 run_metadata_ptr)
779 if run_metadata:
780 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
980 if final_fetches or final_targets:
981 results = self._do_run(handle, final_targets, final_fetches,
--> 982 feed_dict_string, options, run_metadata)
983 else:
984 results = []
/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1030 if handle is None:
1031 return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
-> 1032 target_list, options, run_metadata)
1033 else:
1034 return self._do_call(_prun_fn, self._session, handle, feed_dict,
/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1037 def _do_call(self, fn, *args):
1038 try:
-> 1039 return fn(*args)
1040 except errors.OpError as e:
1041 message = compat.as_text(e.message)
/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
1019 return tf_session.TF_Run(session, options,
1020 feed_dict, fetch_list, target_list,
-> 1021 status, run_metadata)
1022
1023 def _prun_fn(session, handle, feed_dict, fetch_list):
KeyboardInterrupt:
In [4]:
# choose a random sentence
start_index = random.randint(0, len(text) - maxlen - 1)
sentence = text[start_index: start_index + maxlen]
# generate output using the RNN model
original_sentence = sentence
generated = sentence
for i in range(NUM_OUTPUTS_PRED):
x = np.zeros((1, maxlen, len(chars)), dtype=np.float32)
for t, char in enumerate(sentence):
x[0, t, char_indices[char]] = 1.
p = None
for e in nn.predict(x):
if p is None: p = e["preds"]
next_index = sample(p)
next_char = indices_char[next_index]
generated += next_char
sentence = sentence[1:] + next_char
print('\n' * 10, '-' * 100)
print('HERE')
print(generated)
print(original_sentence)
print('-' * 100, '\n' * 10)
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
/usr/local/lib/python3.4/dist-packages/tensorflow/python/util/deprecation.py:248: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.
equality = a == b
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
WARNING:tensorflow:From <ipython-input-4-0037bc4a75f1>:15: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
----------------------------------------------------------------------------------------------------
HERE
r wine: 'a health!' quoth he, as if
he he weall our whit hemer, shallll with thi
r wine: 'a health!' quoth he, as if
he h
----------------------------------------------------------------------------------------------------
In [10]:
# generate output using the RNN model
original_sentence = "time"
sentence = original_sentence
generated = sentence
for i in range(10):
x = np.zeros((1, maxlen, len(chars)), dtype=np.float32)
for t, char in enumerate(sentence):
x[0, t, char_indices[char]] = 1.
p = None
for e in nn.predict(x):
if p is None: p = e["preds"]
print(p)
next_index = sample(p)
next_char = indices_char[next_index]
generated += next_char
sentence = sentence[1:] + next_char
print('\n' * 10, '-' * 100)
print('HERE')
print(generated)
print(original_sentence)
print('-' * 100, '\n' * 10)
WARNING:tensorflow:From <ipython-input-10-13d54bdcc739>:11: 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(...))
/usr/local/lib/python3.4/dist-packages/tensorflow/python/util/deprecation.py:248: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.
equality = a == b
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
[ 5.10431186e-04 9.98117208e-01 5.90219262e-11 2.03930277e-08
2.06349871e-08 2.60475685e-09 2.82078217e-05 3.51113055e-10
3.47168294e-09 1.67235417e-08 3.75141553e-07 7.82775580e-12
3.99932887e-09 9.54997086e-06 3.24845595e-09 8.95351988e-08
7.73334730e-11 5.15784544e-04 1.12831700e-08 2.41030378e-08
1.61963342e-07 1.10379597e-05 4.23501363e-14 3.85896364e-08
6.51927166e-07 1.49332386e-08 2.17957226e-08 9.30234746e-05
3.41106809e-12 5.81926339e-14 6.43336443e-06 1.41718772e-06
4.23773326e-06 6.97380048e-04 1.07524281e-10 3.80223630e-09
2.50599356e-16 3.96385121e-06 5.61318136e-13]
WARNING:tensorflow:From <ipython-input-10-13d54bdcc739>:11: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
[ 1.88392296e-04 9.96701300e-01 6.89299243e-11 3.92704997e-08
4.77182098e-08 5.60397133e-08 4.24981044e-05 1.64318018e-10
1.09672254e-08 3.59650869e-08 1.43609498e-07 2.67432743e-10
3.16079674e-09 1.19942524e-05 2.33558284e-09 2.75647551e-07
5.22546877e-08 2.56213383e-03 3.94488708e-08 4.85427254e-09
2.35454873e-08 2.10934639e-04 4.33996328e-12 1.73394454e-08
5.62093874e-06 1.34468117e-08 4.37477667e-07 7.28232699e-05
2.27405629e-11 3.02551635e-15 6.19593993e-05 7.95270182e-07
3.77228243e-05 8.50870711e-05 1.35057118e-10 9.39591427e-09
3.50112895e-15 1.75344121e-05 2.22621205e-12]
WARNING:tensorflow:From <ipython-input-10-13d54bdcc739>:11: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
[ 2.21534428e-04 9.93981183e-01 6.34928915e-11 7.94155213e-08
1.02674534e-07 4.81933107e-08 2.57556494e-05 3.74810669e-11
1.71956902e-08 7.91303520e-08 1.40207007e-07 5.19399579e-10
4.17961310e-09 3.55434872e-06 1.65757132e-08 8.26823452e-07
1.42910736e-07 3.92076746e-03 1.12817972e-07 4.10614298e-09
2.48197640e-08 1.39814988e-03 1.36355163e-11 1.95387866e-08
9.93353206e-06 9.34284685e-08 5.01213606e-07 1.35778726e-04
1.06468523e-11 1.60335925e-15 8.48395721e-05 5.26855729e-07
7.00378150e-05 1.39485695e-04 2.30429412e-10 7.22889339e-08
1.80896117e-14 6.05607647e-06 1.06008136e-11]
WARNING:tensorflow:From <ipython-input-10-13d54bdcc739>:11: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
[ 1.65209058e-04 9.89926696e-01 6.18273141e-11 1.74439037e-07
2.30940842e-07 9.38005869e-08 3.08850613e-05 5.62107201e-11
4.53494806e-08 1.72504471e-07 1.14165807e-07 1.51943380e-09
1.79230639e-08 4.25997041e-06 2.80067649e-08 1.27280111e-06
1.62253434e-06 5.83881326e-03 2.19799020e-07 2.01575068e-09
2.57136925e-08 3.34290345e-03 6.28930102e-11 1.89438918e-08
1.06596972e-05 4.22973642e-07 8.11774441e-07 7.87006720e-05
2.20400781e-11 9.51636434e-16 3.09886964e-04 9.64305855e-07
4.87182951e-05 2.32426857e-04 2.98119945e-10 1.03419843e-07
2.37176967e-14 4.51864707e-06 1.65346070e-11]
WARNING:tensorflow:From <ipython-input-10-13d54bdcc739>:11: 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(...))
INFO:tensorflow:Restoring parameters from /tmp/tmpceqk5qg1/model.ckpt-19101
[ 1.35492446e-04 9.88932848e-01 7.68679426e-11 2.17841517e-07
2.85031859e-07 3.32639729e-07 3.20755244e-05 3.45229470e-11
7.17388815e-08 2.19147609e-07 8.44852224e-08 6.79385925e-09
1.38642582e-08 2.98846044e-06 2.17521290e-08 1.20390803e-06
5.98514907e-06 5.55688282e-03 3.79682234e-07 2.08742468e-09
1.99904431e-08 4.11566952e-03 1.80283843e-10 1.79023711e-08
1.27436588e-05 6.51291828e-07 7.31034902e-07 9.08361544e-05
1.09732475e-11 4.26314223e-16 9.04713641e-04 9.94703328e-07
4.82707001e-05 1.51811502e-04 2.02012337e-10 1.48147834e-07
1.67475049e-14 4.25541339e-06 4.91029509e-11]
WARNING:tensorflow:From <ipython-input-10-13d54bdcc739>:11: 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(...))
---------------------------------------------------------------------------
KeyboardInterrupt Traceback (most recent call last)
<ipython-input-10-13d54bdcc739> in <module>()
9
10 p = None
---> 11 for e in nn.predict(x):
12 if p is None: p = e["preds"]
13
/usr/local/lib/python3.4/dist-packages/tensorflow/python/util/deprecation.py in new_func(*args, **kwargs)
279 _call_location(), decorator_utils.get_qualified_name(func),
280 func.__module__, arg_name, date, instructions)
--> 281 return func(*args, **kwargs)
282 new_func.__doc__ = _add_deprecated_arg_notice_to_docstring(
283 func.__doc__, date, instructions)
/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py in predict(self, x, input_fn, batch_size, outputs, as_iterable)
563 feed_fn=feed_fn,
564 outputs=outputs,
--> 565 as_iterable=as_iterable)
566
567 def get_variable_value(self, name):
/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py in _infer_model(self, input_fn, feed_fn, outputs, as_iterable, iterate_batches)
855 contrib_framework.create_global_step(g)
856 features = self._get_features_from_input_fn(input_fn)
--> 857 infer_ops = self._get_predict_ops(features)
858 predictions = self._filter_predictions(infer_ops.predictions, outputs)
859 mon_sess = monitored_session.MonitoredSession(
/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py in _get_predict_ops(self, features)
1186 labels = tensor_signature.create_placeholders_from_signatures(
1187 self._labels_info)
-> 1188 return self._call_model_fn(features, labels, model_fn_lib.ModeKeys.INFER)
1189
1190 def export_savedmodel(
/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py in _call_model_fn(self, features, labels, mode)
1101 if 'model_dir' in model_fn_args:
1102 kwargs['model_dir'] = self.model_dir
-> 1103 model_fn_results = self._model_fn(features, labels, **kwargs)
1104
1105 if isinstance(model_fn_results, model_fn_lib.ModelFnOps):
<ipython-input-1-576f94d3a7c0> in model_fn(features, targets, mode, params)
47 # 0. Reformat input shape to become a sequence
48 lstm1 = GRU(128, input_shape=(params["maxlen"], params["vocab_size"]),
---> 49 return_sequences=False)(features)
50 #lstm2 = GRU(128)(lstm1)
51 preds = Dense(params["vocab_size"])(lstm1)
/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/keras/python/keras/layers/recurrent.py in __call__(self, inputs, initial_state, **kwargs)
277 else:
278 kwargs['initial_state'] = initial_state
--> 279 return super(Recurrent, self).__call__(inputs, **kwargs)
280
281 def call(self, inputs, mask=None, initial_state=None, training=None):
/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/keras/python/keras/engine/topology.py in __call__(self, inputs, **kwargs)
576
577 # Actually call the layer, collecting output(s), mask(s), and shape(s).
--> 578 output = self.call(inputs, **kwargs)
579 output_mask = self.compute_mask(inputs, previous_mask)
580
/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/keras/python/keras/layers/recurrent.py in call(self, inputs, mask, initial_state, training)
322 mask=mask,
323 constants=constants,
--> 324 unroll=self.unroll)
325 if self.stateful:
326 updates = []
/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/keras/python/keras/backend.py in rnn(step_function, inputs, initial_states, go_backwards, mask, constants, unroll)
2513 loop_vars=(time, output_ta) + states,
2514 parallel_iterations=32,
-> 2515 swap_memory=True)
2516 last_time = final_outputs[0]
2517 output_ta = final_outputs[1]
/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/control_flow_ops.py in while_loop(cond, body, loop_vars, shape_invariants, parallel_iterations, back_prop, swap_memory, name)
2621 context = WhileContext(parallel_iterations, back_prop, swap_memory, name)
2622 ops.add_to_collection(ops.GraphKeys.WHILE_CONTEXT, context)
-> 2623 result = context.BuildLoop(cond, body, loop_vars, shape_invariants)
2624 return result
2625
/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/control_flow_ops.py in BuildLoop(self, pred, body, loop_vars, shape_invariants)
2454 self.Enter()
2455 original_body_result, exit_vars = self._BuildLoop(
-> 2456 pred, body, original_loop_vars, loop_vars, shape_invariants)
2457 finally:
2458 self.Exit()
/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/control_flow_ops.py in _BuildLoop(self, pred, body, original_loop_vars, loop_vars, shape_invariants)
2404 structure=original_loop_vars,
2405 flat_sequence=vars_for_body_with_tensor_arrays)
-> 2406 body_result = body(*packed_vars_for_body)
2407 if not nest.is_sequence(body_result):
2408 body_result = [body_result]
/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/keras/python/keras/backend.py in _step(time, output_ta_t, *states)
2502 current_input = input_ta.read(time)
2503 output, new_states = step_function(current_input,
-> 2504 tuple(states) + tuple(constants))
2505 for state, new_state in zip(states, new_states):
2506 new_state.set_shape(state.get_shape())
/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/keras/python/keras/layers/recurrent.py in step(self, inputs, states)
868 self.recurrent_kernel_z))
869 r = self.recurrent_activation(x_r + K.dot(h_tm1 * rec_dp_mask[1],
--> 870 self.recurrent_kernel_r))
871
872 hh = self.activation(x_h + K.dot(r * h_tm1 * rec_dp_mask[2],
/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/keras/python/keras/activations.py in hard_sigmoid(x)
64
65 def hard_sigmoid(x):
---> 66 return K.hard_sigmoid(x)
67
68
/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/keras/python/keras/backend.py in hard_sigmoid(x)
2817 zero = _to_tensor(0., x.dtype.base_dtype)
2818 one = _to_tensor(1., x.dtype.base_dtype)
-> 2819 x = clip_ops.clip_by_value(x, zero, one)
2820 return x
2821
/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/clip_ops.py in clip_by_value(t, clip_value_min, clip_value_max, name)
56
57 # Go through list of tensors, for each value in each tensor clip
---> 58 t_min = math_ops.minimum(t, clip_value_max)
59 t_max = math_ops.maximum(t_min, clip_value_min, name=name)
60
/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/gen_math_ops.py in minimum(x, y, name)
1390 A `Tensor`. Has the same type as `x`.
1391 """
-> 1392 result = _op_def_lib.apply_op("Minimum", x=x, y=y, name=name)
1393 return result
1394
/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/op_def_library.py in apply_op(self, op_type_name, name, **keywords)
766 op = g.create_op(op_type_name, inputs, output_types, name=scope,
767 input_types=input_types, attrs=attr_protos,
--> 768 op_def=op_def)
769 if output_structure:
770 outputs = op.outputs
/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/ops.py in create_op(self, op_type, inputs, dtypes, input_types, name, attrs, op_def, compute_shapes, compute_device)
2334 ret = Operation(node_def, self, inputs=inputs, output_types=dtypes,
2335 control_inputs=control_inputs, input_types=input_types,
-> 2336 original_op=self._default_original_op, op_def=op_def)
2337 if compute_shapes:
2338 set_shapes_for_outputs(ret)
/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/ops.py in __init__(self, node_def, g, inputs, output_types, control_inputs, input_types, original_op, op_def)
1237 # created.
1238 self._id_value = self._graph._next_id() # pylint: disable=protected-access
-> 1239 self._recompute_node_def()
1240
1241 def colocation_groups(self):
/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/ops.py in _recompute_node_def(self)
1400 # Methods below are used when building the NodeDef and Graph proto.
1401 def _recompute_node_def(self):
-> 1402 del self._node_def.input[:]
1403 self._node_def.input.extend([t._as_node_def_input() for t in self._inputs])
1404 if self._control_inputs:
/usr/local/lib/python3.4/dist-packages/google/protobuf/internal/containers.py in __delitem__(self, key)
318 self._message_listener.Modified()
319
--> 320 def __delitem__(self, key):
321 """Deletes the item at the specified position."""
322 del self._values[key]
KeyboardInterrupt:
In [ ]:
Content source: mari-linhares/tensorflow-workshop
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