/external/tensorflow/tensorflow/contrib/eager/python/examples/linear_regression/ |
H A D | linear_regression_graph_test.py | 53 optimization_step = tf.train.GradientDescentOptimizer( 59 def train(num_epochs): function in function:GraphLinearRegressionBenchmark.benchmarkGraphLinearRegression 69 train(1) 72 train(num_epochs)
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/external/tensorflow/tensorflow/contrib/model_pruning/python/ |
H A D | learning.py | 31 optimizer = tf.train.MomentumOptimizer(FLAGS.learning_rate, FLAGS.momentum) 43 learning.train(train_op, 58 def train(train_op, function 83 """Wrapper around tf-slim's train function. 136 sync_optimizer: an instance of tf.train.SyncReplicasOptimizer, or a list of 162 total_loss, _ = _slim.learning.train(
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/external/tensorflow/tensorflow/contrib/gan/ |
H A D | __init__.py | 33 from tensorflow.contrib.gan.python import train namespace 37 from tensorflow.contrib.gan.python.train import * 48 _allowed_symbols += train.__all__
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/external/tensorflow/tensorflow/examples/tutorials/mnist/ |
H A D | mnist_with_summaries.py | 38 def train(): function 127 with tf.name_scope('train'): 128 train_step = tf.train.AdamOptimizer(FLAGS.learning_rate).minimize( 141 train_writer = tf.summary.FileWriter(FLAGS.log_dir + '/train', sess.graph) 149 def feed_dict(train): 151 if train or FLAGS.fake_data: 152 xs, ys = mnist.train.next_batch(100, fake_data=FLAGS.fake_data) 164 else: # Record train set summaries, and train 186 train() [all...] |
/external/tensorflow/tensorflow/contrib/model_pruning/ |
H A D | __init__.py | 27 from tensorflow.contrib.model_pruning.python.learning import train namespace 42 'MaskedBasicLSTMCell', 'MaskedLSTMCell', 'train', 'apply_mask',
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/external/tensorflow/tensorflow/contrib/model_pruning/examples/cifar10/ |
H A D | cifar10_train.py | 15 """A binary to train pruned CIFAR-10 using a single GPU. 33 data set, compile the program and train the model. 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() [all...] |
H A D | cifar10_pruning.py | 30 train_op = train(loss, global_step) 153 eval_data: bool, indicating if one should use the train or eval data set. 309 loss_averages = tf.train.ExponentialMovingAverage(0.9, name='avg') 324 def train(total_loss, global_step): function 342 lr = tf.train.exponential_decay( 355 opt = tf.train.GradientDescentOptimizer(lr) 371 variable_averages = tf.train.ExponentialMovingAverage(MOVING_AVERAGE_DECAY, 376 train_op = tf.no_op(name='train')
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/external/tensorflow/tensorflow/contrib/training/ |
H A D | __init__.py | 65 from tensorflow.contrib.training.python.training.training import train namespace 78 'multiply_gradients', 'train']
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/external/tensorflow/tensorflow/contrib/framework/python/framework/ |
H A D | checkpoint_utils.py | 31 from tensorflow.python.training import training as train namespace 63 return train.NewCheckpointReader(filename)
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/external/tensorflow/tensorflow/contrib/learn/python/learn/ |
H A D | __init__.py | 41 from tensorflow.contrib.learn.python.learn.graph_actions import train namespace
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H A D | experiment.py | 119 """Experiment is a class containing all information needed to train a model. 176 means train forever. 200 Perform this many (integer) number of train steps for each 246 "Please call `TPUEstimator` train/evaluate directly. \n" 329 def train(self, delay_secs=None): member in class:Experiment 333 `delay_secs` seconds. If `self._train_steps` is `None`, train forever. 346 # to train. We might as well start as soon as we can. 503 # Exit if we have already reached number of steps to train. 658 self.train(delay_secs=0) 689 1. The procedure will have train an [all...] |
H A D | graph_actions.py | 61 'graph_actions.py will be deleted. Use tf.train.* utilities instead. ' 123 def train(graph, function 158 graph: A graph to train. It is expected that this graph is not in use 180 arg to tf.train.Saver constructor. 190 max_steps: Number of total steps for which to train model. If `None`, 191 train forever. Two calls fit(steps=100) means 200 training iterations. 251 """See train.""" 348 'Global step was not incremented by train op at step %s' 496 graph: A `Graph` to train. It is expected that this graph is not in use
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/external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/ |
H A D | estimators.py | 38 from tensorflow.python.training import training as train namespace 53 from tf.train.Optimizer. Defaults to Adam with step size 0.02. 62 optimizer = train.AdamOptimizer(0.02) 188 NORMAL_LIKELIHOOD_LOSS, we train the covariance term as well. For 203 from tf.train.Optimizer. Defaults to Adagrad with step size 0.1. 210 optimizer = train.AdagradOptimizer(0.1) 360 from tf.train.Optimizer. Defaults to Adam with step size 0.02.
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H A D | head_test.py | 36 from tensorflow.python.training import training as train namespace 96 optimizer=train.GradientDescentOptimizer(0.001)).create_estimator_spec 133 optimizer=train.AdamOptimizer(0.001)).create_estimator_spec
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H A D | state_management_test.py | 42 from tensorflow.python.training import training as train namespace 304 with train.MonitoredSession() as session:
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/external/tensorflow/tensorflow/contrib/training/python/training/ |
H A D | training.py | 36 optimizer = tf.train.MomentumOptimizer(FLAGS.learning_rate, FLAGS.momentum) 42 tf.contrib.training.train(train_op, my_log_dir) 48 In order to use the `train` function, one needs a train_op: an `Operation` that 144 tf.contrib.training.train(train_op, my_log_dir, scaffold=scaffold) 177 tf.contrib.training.train(train_op, my_log_dir, scaffold=scaffold) 208 tf.contrib.training.train(train_op, my_log_dir, scaffold=scaffold) 240 tf.contrib.training.train(train_op, my_log_dir, scaffold=scaffold) 267 'train', 393 variables_to_train: an optional list of variables to train. If None, it will 477 def train(train_o function [all...] |
/external/tensorflow/tensorflow/contrib/eager/python/examples/rnn_ptb/ |
H A D | rnn_ptb.py | 188 def train(model, optimizer, train_data, sequence_length, clip_ratio): function 225 self.train = self.tokenize(os.path.join(path, "ptb.train.txt")) 298 train_data = _divide_into_batches(corpus.train, FLAGS.batch_size) 305 tf.train.latest_checkpoint(FLAGS.logdir)): 314 optimizer = tf.train.GradientDescentOptimizer(learning_rate) 318 train(model, optimizer, train_data, FLAGS.seq_len, FLAGS.clip)
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/external/tensorflow/tensorflow/contrib/layers/python/layers/ |
H A D | optimizers.py | 38 from tensorflow.python.training import training as train namespace 41 "Adagrad": train.AdagradOptimizer, 42 "Adam": train.AdamOptimizer, 43 "Ftrl": train.FtrlOptimizer, 44 "Momentum": lambda lr: train.MomentumOptimizer(lr, momentum=0.9), 45 "RMSProp": train.RMSPropOptimizer, 46 "SGD": train.GradientDescentOptimizer, 80 optimizer=lambda lr: tf.train.MomentumOptimizer(lr, momentum=0.5))`. 83 optimizer=lambda: tf.train.MomentumOptimizer(0.5, momentum=0.5))`. 87 optimizer=tf.train [all...] |
/external/tensorflow/tensorflow/contrib/slim/python/slim/ |
H A D | learning.py | 22 tf.train.Supervisor and its managed_session in its implementation to ensure the 38 optimizer = tf.train.MomentumOptimizer(FLAGS.learning_rate, FLAGS.momentum) 44 slim.learning.train(train_op, my_log_dir) 50 In order to train, TF-Slim's train loop needs a train_op: an `Operation` that 143 slim.learning.train(train_op, my_log_dir, init_fn=InitAssignFn) 177 slim.learning.train(train_op, my_log_dir, init_fn=InitAssignFn) 210 slim.learning.train(train_op, my_log_dir, init_fn=InitAssignFn) 244 slim.learning.train(train_op, my_log_dir, init_fn=InitAssignFn) 276 'create_train_op', 'train_step', 'train' 531 def train(train_op, function [all...] |
/external/tensorflow/tensorflow/python/grappler/ |
H A D | memory_optimizer_test.py | 35 from tensorflow.python.training import training as train namespace 122 optimizer = train.AdamOptimizer(0.001) 125 metagraph = train.export_meta_graph() 190 train.import_meta_graph(metagraph) 243 optimizer = train.AdamOptimizer(0.001) 265 metagraph = train.export_meta_graph()
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/external/tensorflow/tensorflow/contrib/boosted_trees/python/training/functions/ |
H A D | gbdt_batch.py | 404 mode: Mode the graph is running in (train|predict|eval). 468 def train(self, loss, predictions_dict, labels): member in class:GradientBoostedDecisionTreeModel
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/external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
H A D | linear.py | 48 from tensorflow.python.training import training as train namespace 280 return train.FtrlOptimizer(learning_rate=learning_rate) 326 optimizer=tf.train.FtrlOptimizer( 418 optimizer: The optimizer used to train the model. If specified, it should 690 optimizer: An instance of `tf.Optimizer` used to train the model. If 927 optimizer: An instance of `tf.Optimizer` used to train the model. If
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/external/tensorflow/tensorflow/core/kernels/ |
H A D | sdca_ops_test.cc | 233 Graph* train = nullptr; local 236 20 /* dense features per group */, &init, &train); 238 test::Benchmark("cpu", train, GetSingleThreadedOptions(), init).Run(iters); 244 Graph* train = nullptr; local 247 200000 /* dense features per group */, &init, &train); 249 test::Benchmark("cpu", train, GetSingleThreadedOptions(), init).Run(iters); 255 Graph* train = nullptr; local 258 0 /* dense features per group */, &init, &train); 260 test::Benchmark("cpu", train, GetMultiThreadedOptions(), init).Run(iters);
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H A D | training_ops_test.cc | 82 Graph* train; local 83 SGD(params, &init, &train); 84 test::Benchmark("cpu", train, GetOptions(), init).Run(iters); 114 Graph* train; local 115 Adagrad(params, &init, &train); 116 test::Benchmark("cpu", train, GetOptions(), init).Run(iters); 148 Graph* train; local 149 Momentum(params, &init, &train); 150 test::Benchmark("cpu", train, GetOptions(), init).Run(iters); 191 Graph* train; local 231 Graph* train; local 268 Graph* train; local 305 Graph* train; local [all...] |
/external/opencv/ml/src/ |
H A D | mlknearest.cpp | 65 train( _train_data, _responses, _sample_idx, _is_regression, _max_k, false ); 92 bool CvKNearest::train( const CvMat* _train_data, const CvMat* _responses, function in class:CvKNearest 99 CV_FUNCNAME( "CvKNearest::train" ); 113 CV_CALL( cvPrepareTrainData( "CvKNearest::train", _train_data, CV_ROW_SAMPLE, 320 CV_ERROR( CV_StsError, "The search tree must be constructed first using train method" );
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