| /external/tensorflow/tensorflow/contrib/linear_optimizer/python/kernel_tests/ |
| sdca_ops_test.py | 220 train_op = lr.minimize()
222 train_op.run()
223 lr.update_weights(train_op).run()
271 train_op = lr.minimize()
276 train_op.run()
285 lr.update_weights(train_op).run()
332 train_op = lr.minimize()
334 train_op.run()
335 lr.update_weights(train_op).run()
388 train_op = lr.minimize(
[all...] |
| /external/tensorflow/tensorflow/python/training/ |
| basic_session_run_hooks_test.py | 236 train_op = constant_op.constant(3)
244 mon_sess.run(train_op)
254 train_op = constant_op.constant(3)
260 mon_sess.run(train_op)
265 mon_sess.run(train_op)
268 mon_sess.run(train_op)
273 mon_sess.run(train_op)
301 train_op = constant_op.constant(3)
307 mon_sess.run(train_op)
314 train_op = constant_op.constant(3
[all...] |
| /external/tensorflow/tensorflow/contrib/model_pruning/python/ |
| learning.py | 33 # Create the train_op
34 train_op = slim.learning.create_train_op(total_loss, optimizer)
43 learning.train(train_op,
58 def train(train_op,
90 train_op: A `Tensor` that, when executed, will apply the gradients and
98 session, the `train_op` `Tensor`, a global step `Tensor` and a dictionary.
149 ValueError: if `train_op` is empty or if `startup_delay_steps` is
155 def train_step_with_pruning_fn(sess, train_op, global_step,
157 total_loss, should_stop = train_step_fn(sess, train_op, global_step,
163 train_op,
[all...] |
| /external/tensorflow/tensorflow/python/grappler/ |
| model_analyzer_test.py | 37 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP)
38 train_op.append(d)
57 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP)
58 train_op.append(c)
|
| datasets_test.py | 53 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP)
54 train_op.append(get_next)
78 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP)
79 train_op.append(get_next)
114 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP)
115 train_op.append(get_next)
127 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP
[all...] |
| cluster_test.py | 39 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP)
40 train_op.append(c)
56 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP)
57 train_op.append(c)
74 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP)
75 train_op.append(c)
93 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP
[all...] |
| item_test.py | 54 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP)
55 train_op.append(c)
67 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP)
68 train_op.append(c)
89 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP)
90 train_op.append(c)
116 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP
[all...] |
| tf_optimizer_test.py | 38 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP)
39 # Being a train_op will make 'd' to be added as a fetch node.
40 train_op.append(d)
|
| memory_optimizer_test.py | 48 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP)
49 train_op.append(d)
69 train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP)
70 train_op.append(d)
123 train_op = optimizer.minimize(loss)
126 return (metagraph, init_op.name, train_op.name, loss.name)
192 train_op = graph.get_operation_by_name(train_op_name)
196 sess.run(train_op)
[all...] |
| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| model_fn.py | 64 'predictions', 'loss', 'train_op', 'eval_metric_ops',
74 train_op=None,
103 train_op: Op for the training step.
130 get_graph_from_inputs((predictions, loss, train_op))
132 # Validate train_op.
133 if train_op is None:
135 raise ValueError('Missing train_op.')
136 elif not isinstance(train_op, ops.Operation):
138 train_op = ops.convert_to_tensor(train_op).o
[all...] |
| logistic_regressor.py | 38 `(features, labels, mode) -> (predictions, loss, train_op)`.
49 predictions, loss, train_op = model_fn(features, labels, mode)
61 train_op=train_op,
100 `(features, labels, mode) -> (predictions, loss, train_op)`.
|
| /external/tensorflow/tensorflow/contrib/training/python/training/ |
| training_test.py | 100 train_op = training.create_train_op(loss, optimizer)
103 self.assertTrue(train_op in ops.get_collection(ops.GraphKeys.TRAIN_OP))
118 train_op = training.create_train_op(loss, optimizer)
133 session.run(train_op)
151 train_op = training.create_train_op(loss, optimizer, update_ops=[])
166 session.run(train_op)
184 train_op = training.create_train_op(loss, optimizer)
193 session.run(train_op)
207 train_op = training.create_train_op(loss, optimizer, global_step=None
[all...] |
| /external/tensorflow/tensorflow/contrib/slim/python/slim/ |
| learning_test.py | 254 train_op = learning.create_train_op(total_loss, optimizer)
257 train_op, logdir, number_of_steps=300, log_every_n_steps=10)
289 train_op = learning.create_train_op(total_loss, optimizer)
304 sess.run([train_op])
323 train_op = learning.create_train_op(total_loss, optimizer, update_ops=[])
338 sess.run([train_op])
356 train_op = learning.create_train_op(total_loss, optimizer)
365 sess.run([train_op])
381 train_op = learning.create_train_op(
391 sess.run([train_op])
[all...] |
| /external/tensorflow/tensorflow/contrib/learn/python/learn/ |
| graph_actions_test.py | 472 train_op = constant_op.constant(1.0)
476 g, output_dir=None, train_op=train_op, loss_op=loss_op)
481 train_op=constant_op.constant(1.0),
483 with self.assertRaisesRegexp(ValueError, 'train_op'):
485 g, output_dir=self._output_dir, train_op=None, loss_op=loss_op)
490 train_op=constant_op.constant(1.0),
496 train_op=constant_op.constant(1.0),
507 train_op = state_ops.assign_add(variables_lib.get_global_step(), 1)
513 train_op=train_op
[all...] |
| /external/tensorflow/tensorflow/contrib/eager/python/examples/mnist/ |
| mnist_graph_test.py | 55 train_op = optimizer.minimize(loss)
61 sess.run(train_op)
|
| /external/tensorflow/tensorflow/python/estimator/ |
| model_fn.py | 60 'mode', 'predictions', 'loss', 'train_op', 'eval_metric_ops',
73 train_op=None,
85 * For `mode == ModeKeys.TRAIN`: required fields are `loss` and `train_op`.
90 arguments will be ignored by an `Estimator`. E.g. `train_op` will be
97 train_op = ...
102 train_op=train_op)
116 train_op = ...
118 train_op = None
128 train_op=train_op
[all...] |
| /external/tensorflow/tensorflow/core/grappler/inputs/ |
| file_input_yielder.cc | 86 if (metagraph.collection_def().count("train_op") == 0 ||
87 !metagraph.collection_def().at("train_op").has_node_list() ||
88 metagraph.collection_def().at("train_op").node_list().value_size() == 0) {
96 metagraph.collection_def().at("train_op").node_list().value()) {
106 for (const auto& train_op : train_ops) {
107 if (train_ops_found.find(train_op) != train_ops_found.end()) {
108 LOG(ERROR) << "Non existent train op specified: " << train_op;
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/rnn_ptb/ |
| rnn_ptb_graph_test.py | 48 train_op = optimizer.apply_gradients(grads)
52 sess.run(train_op, feed_dict={inputs_ph: inputs, labels_ph: labels})
54 [train_op, loss], feed_dict={
133 train_op = optimizer.apply_gradients(grads)
138 sess.run(train_op)
142 sess.run(train_op)
|
| /external/tensorflow/tensorflow/contrib/boosted_trees/python/training/functions/ |
| gbdt_batch_test.py | 189 train_op = gbdt_model.train(
199 train_op.run()
213 train_op.run()
293 train_op = gbdt_model.train(
303 train_op.run()
317 train_op.run()
396 train_op = gbdt_model.train(
405 train_op.run()
466 train_op = gbdt_model.train(
477 train_op.run(
[all...] |
| /external/tensorflow/tensorflow/contrib/eager/python/examples/resnet50/ |
| resnet50_graph_test.py | 85 train_op = optimizer.minimize(loss)
95 sess.run([train_op, tf.contrib.summary.all_summary_ops()],
148 train_op = optimizer.minimize(loss)
155 sess.run(train_op)
158 sess.run(train_op)
|
| /external/tensorflow/tensorflow/contrib/kfac/examples/ |
| mlp.py | 131 train_op = optimizer.minimize(loss, global_step=global_step)
137 # - train_op: Update the weights with the minibatch's gradient.
145 [global_step, loss, accuracy, train_op, optimizer.cov_update_op])
307 train_op = optimizer.minimize(loss, global_step=global_step)
318 mode=mode, loss=loss, train_op=train_op, training_hooks=hooks)
|
| /external/tensorflow/tensorflow/contrib/opt/python/training/ |
| moving_average_optimizer.py | 93 train_op = self._optimizer.apply_gradients(
98 with ops.control_dependencies([train_op]):
107 return control_flow_ops.group(train_op, ma_op, name='train_with_avg')
|
| /external/tensorflow/tensorflow/examples/get_started/regression/ |
| custom_regression.py | 62 train_op = optimizer.minimize(
66 mode=mode, loss=total_loss, train_op=train_op)
|
| /external/tensorflow/tensorflow/examples/learn/ |
| iris_custom_decay_dnn.py | 59 train_op = optimizer.minimize(loss, global_step=global_step)
60 return tf.estimator.EstimatorSpec(mode, loss=loss, train_op=train_op)
|
| iris_custom_model.py | 56 train_op = optimizer.minimize(loss, global_step=tf.train.get_global_step())
57 return tf.estimator.EstimatorSpec(mode, loss=loss, train_op=train_op)
|
