| /external/tensorflow/tensorflow/examples/speech_commands/ |
| D | train_test.py | 26 from tensorflow.examples.speech_commands import train
108 train.FLAGS = self._getDefaultFlags()
109 train.main('')
112 os.path.join(train.FLAGS.train_dir,
113 train.FLAGS.model_architecture + '.pbtxt')))
116 os.path.join(train.FLAGS.train_dir,
117 train.FLAGS.model_architecture + '_labels.txt')))
120 os.path.join(train.FLAGS.train_dir,
121 train.FLAGS.model_architecture + '.ckpt-1.meta')))
125 train.FLAGS = self._getDefaultFlags()
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| /external/skqp/infra/bots/ |
| D | infra_tests.py | 28 def python_unit_tests(train): argument
29 if train:
36 def recipe_test(train): argument
39 if train:
46 def gen_tasks_test(train): argument
48 if not train:
64 train = False
66 train = True
75 err = t(train)
87 if train:
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| /external/skia/infra/bots/ |
| D | infra_tests.py | 28 def python_unit_tests(train): argument
29 if train:
36 def recipe_test(train): argument
39 if train:
46 def gen_tasks_test(train): argument
48 if not train:
64 train = False
66 train = True
75 err = t(train)
87 if train:
|
| /external/tensorflow/tensorflow/contrib/gan/python/ |
| D | train_test.py | 27 from tensorflow.contrib.gan.python import train
172 return train.gan_model(
180 return train.gan_model(
204 return train.infogan_model(
213 return train.infogan_model(
238 return train.acgan_model(
247 return train.acgan_model(
272 return train.cyclegan_model(
280 return train.cyclegan_model(
319 return train.stargan_model(
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| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| D | optimizers_test.py | 71 train = optimizers_lib.optimize_loss(
74 session.run(train, feed_dict={x: 5})
87 train = optimizers_lib.optimize_loss(
90 session.run(train, feed_dict={x: 5})
170 train = optimizers_lib.optimize_loss(
177 session.run(train, feed_dict={x: 5})
187 train = optimizers_lib.optimize_loss(
195 session.run(train, feed_dict={x: 5})
203 train = optimizers_lib.optimize_loss(
210 session.run(train, feed_dict={x: 5})
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| D | optimizers.py | 37 from tensorflow.python.training import training as train unknown
40 "Adagrad": train.AdagradOptimizer,
41 "Adam": train.AdamOptimizer,
42 "Ftrl": train.FtrlOptimizer,
43 …"Momentum": lambda learning_rate: train.MomentumOptimizer(learning_rate, momentum=0.9), # pylint:…
44 "RMSProp": train.RMSPropOptimizer,
45 "SGD": train.GradientDescentOptimizer,
159 global_step = train.get_global_step()
161 train.assert_global_step(global_step)
|
| /external/tensorflow/tensorflow/core/kernels/ |
| D | training_ops_test.cc | 82 Graph* train; in BM_SGD() local
83 SGD(params, &init, &train); in BM_SGD()
84 test::Benchmark("cpu", train, GetOptions(), init).Run(iters); in BM_SGD()
114 Graph* train; in BM_Adagrad() local
115 Adagrad(params, &init, &train); in BM_Adagrad()
116 test::Benchmark("cpu", train, GetOptions(), init).Run(iters); in BM_Adagrad()
148 Graph* train; in BM_Momentum() local
149 Momentum(params, &init, &train); in BM_Momentum()
150 test::Benchmark("cpu", train, GetOptions(), init).Run(iters); in BM_Momentum()
191 Graph* train; in BM_Adam() local
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| D | sdca_ops_test.cc | 233 Graph* train = nullptr; in BM_SDCA() local
236 20 /* dense features per group */, &init, &train); in BM_SDCA()
238 test::Benchmark("cpu", train, GetSingleThreadedOptions(), init).Run(iters); in BM_SDCA()
244 Graph* train = nullptr; in BM_SDCA_LARGE_DENSE() local
247 200000 /* dense features per group */, &init, &train); in BM_SDCA_LARGE_DENSE()
249 test::Benchmark("cpu", train, GetSingleThreadedOptions(), init).Run(iters); in BM_SDCA_LARGE_DENSE()
255 Graph* train = nullptr; in BM_SDCA_LARGE_SPARSE() local
258 0 /* dense features per group */, &init, &train); in BM_SDCA_LARGE_SPARSE()
260 test::Benchmark("cpu", train, GetMultiThreadedOptions(), init).Run(iters); in BM_SDCA_LARGE_SPARSE()
|
| /external/tensorflow/tensorflow/examples/how_tos/reading_data/ |
| D | convert_to_records.py | 33 return tf.train.Feature(int64_list=tf.train.Int64List(value=[value]))
37 return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))
58 example = tf.train.Example(
59 features=tf.train.Features(
78 convert_to(data_sets.train, 'train')
|
| /external/tensorflow/tensorflow/examples/get_started/regression/ |
| D | custom_regression.py | 60 optimizer = params.get("optimizer", tf.train.AdamOptimizer)
63 loss=average_loss, global_step=tf.train.get_global_step())
87 (train, test) = imports85.dataset()
93 train = train.map(normalize_price)
101 train.shuffle(1000).batch(128)
141 "optimizer": tf.train.AdamOptimizer,
146 model.train(input_fn=input_train, steps=STEPS)
|
| D | linear_regression_categorical.py | 32 (train, test) = imports85.dataset()
38 train = train.map(normalize_price)
46 train.shuffle(1000).batch(128)
90 model.train(input_fn=input_train, steps=STEPS)
|
| D | dnn_regression.py | 32 (train, test) = imports85.dataset()
38 train = train.map(normalize_price)
46 train.shuffle(1000).batch(128)
85 model.train(input_fn=input_train, steps=STEPS)
|
| /external/tensorflow/tensorflow/contrib/model_pruning/examples/cifar10/ |
| D | cifar10_train.py | 55 def train(): function
72 train_op = cifar10.train(loss, global_step)
90 class _LoggerHook(tf.train.SessionRunHook):
99 return tf.train.SessionRunArgs(loss) # Asks for loss value.
114 with tf.train.MonitoredTrainingSession(
116 hooks=[tf.train.StopAtStepHook(last_step=FLAGS.max_steps),
117 tf.train.NanTensorHook(loss),
132 train()
|
| /external/tensorflow/tensorflow/python/data/experimental/kernel_tests/serialization/ |
| D | checkpoint_input_pipeline_hook_test.py | 79 est.train(_input_fn, steps=2, hooks=[self._build_iterator_saver_hook(est)])
81 est.train(_input_fn, steps=2, hooks=[self._build_iterator_saver_hook(est)])
93 est.train(_input_fn, steps=2, hooks=[self._build_iterator_saver_hook(est)])
95 est.train(_input_fn, steps=2, hooks=[self._build_iterator_saver_hook(est)])
105 est.train(_input_fn, steps=2, hooks=[self._build_iterator_saver_hook(est)])
107 est.train(_input_fn, steps=2, hooks=[self._build_iterator_saver_hook(est)])
110 est.train(_input_fn, steps=2)
121 est.train(
|
| /external/tensorflow/tensorflow/examples/tutorials/layers/ |
| D | cnn_mnist.py | 104 optimizer = tf.train.GradientDescentOptimizer(learning_rate=0.001)
107 global_step=tf.train.get_global_step())
121 train_data = mnist.train.images # Returns np.array
122 train_labels = np.asarray(mnist.train.labels, dtype=np.int32)
133 logging_hook = tf.train.LoggingTensorHook(
143 mnist_classifier.train(
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/revnet/ |
| D | cifar_tfrecords.py | 56 return tf.train.Feature(int64_list=tf.train.Int64List(value=[value]))
60 return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))
116 example = tf.train.Example(
117 features=tf.train.Features(
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/linear_regression/ |
| D | linear_regression_graph_test.py | 53 optimization_step = tf.train.GradientDescentOptimizer(
59 def train(num_epochs): function
69 train(1)
72 train(num_epochs)
|
| /external/tensorflow/tensorflow/contrib/tpu/ |
| D | tpu_estimator.md | 4 This document describes how to train a TensorFlow model on TPUs using the
19 * `Estimator.train()` - train a model on a given input for a fixed number of
58 learning_rate = tf.train.exponential_decay(
59 FLAGS.learning_rate, tf.train.get_global_step(), 100000, 0.96)
62 tf.train.GradientDescentOptimizer(learning_rate=learning_rate))
64 train_op = optimizer.minimize(loss, global_step=tf.train.get_global_step())
69 """Returns an `input_fn` for train and eval."""
116 estimator.train(input_fn=get_input_fn(FLAGS.train_file),
189 tf.train.GradientDescentOptimizer(learning_rate=learning_rate))
207 1. In order to amortize the TPU launch cost, the model train step is wrapped in
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| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| D | kmeans_test.py | 163 kmeans.train(input_fn=self.input_fn(), steps=1)
169 kmeans.train(input_fn=self.input_fn(), steps=1)
172 kmeans.train(input_fn=self.input_fn(), steps=steps)
191 kmeans.train(
223 kmeans.train(input_fn=self.input_fn(), max_steps=max_steps)
282 kmeans.train(
298 kmeans.train(
316 kmeans.train(
380 self.kmeans.train(input_fn=self.input_fn(), max_steps=max_steps)
387 self.kmeans.train(input_fn=self.input_fn(), steps=10)
[all …]
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| /external/tensorflow/tensorflow/contrib/gan/ |
| D | __init__.py | 33 from tensorflow.contrib.gan.python import train
37 from tensorflow.contrib.gan.python.train import *
48 _allowed_symbols += train.__all__
|
| /external/tensorflow/tensorflow/contrib/slim/python/slim/ |
| D | learning_test.py | 256 loss = learning.train(
443 loss = learning.train(
462 loss = learning.train(
482 loss = learning.train(
517 loss = learning.train(
543 loss = learning.train(
571 learning.train(
589 learning.train(
608 learning.train(
628 learning.train(train_op, logdir, init_op=None, number_of_steps=300)
[all …]
|
| /external/tensorflow/tensorflow/python/ops/ |
| D | batch_norm_benchmark.py | 68 def build_graph(device, input_shape, axes, num_layers, mode, scale, train): argument
98 if train:
111 if train:
127 train, num_iters): argument
146 train)
155 (device, len(input_shape), len(axes), num_layers, mode, scale, train,
169 train=train,
|
| /external/tensorflow/tensorflow/contrib/autograph/examples/benchmarks/ |
| D | cartpole_benchmark.py | 105 def train(self, cart_pole_env, optimizer, discount_rate, num_games, member in GraphPolicyNetwork
178 zip(grad_list, var_list), global_step=tf.train.get_global_step())
191 steps_per_game = policy_network.train(
313 def train(self, cart_pole_env, optimizer, discount_rate, num_games, member in EagerPolicyNetwork
360 zip(grad_list, var_list), global_step=tf.train.get_global_step())
370 steps_per_game = policy_network.train(
427 opt = tf.train.AdamOptimizer(0.05)
444 opt = tf.train.AdamOptimizer(0.05)
471 opt = tf.train.AdamOptimizer(0.05)
485 opt = tf.train.AdamOptimizer(0.05)
|
| /external/tensorflow/tensorflow/examples/tutorials/mnist/ |
| D | mnist_with_summaries.py | 38 def train(): function
128 train_step = tf.train.AdamOptimizer(FLAGS.learning_rate).minimize(
149 def feed_dict(train): argument
151 if train or FLAGS.fake_data:
152 xs, ys = mnist.train.next_batch(100, fake_data=FLAGS.fake_data)
187 train()
|
| /external/tensorflow/tensorflow/examples/learn/ |
| D | iris_custom_decay_dnn.py | 54 global_step = tf.train.get_global_step()
55 learning_rate = tf.train.exponential_decay(
58 optimizer = tf.train.AdagradOptimizer(learning_rate=learning_rate)
81 classifier.train(input_fn=train_input_fn, steps=1000)
|