| /external/skia/infra/bots/ |
| Makefile | 4 train:
5 python infra_tests.py --train
|
| infra_tests.py | 28 def python_unit_tests(train):
29 if train:
36 def recipe_test(train):
39 if train:
40 cmd.append('train')
46 def gen_tasks_test(train):
48 if not train:
64 train = False
65 if '--train' in sys.argv:
66 train = Tru
[all...] |
| /external/skqp/infra/bots/ |
| Makefile | 4 train:
5 python infra_tests.py --train
|
| infra_tests.py | 28 def python_unit_tests(train):
29 if train:
36 def recipe_test(train):
39 if train:
40 cmd.append('train')
46 def gen_tasks_test(train):
48 if not train:
64 train = False
65 if '--train' in sys.argv:
66 train = Tru
[all...] |
| /external/tensorflow/tensorflow/examples/speech_commands/ |
| train_test.py | 26 from tensorflow.examples.speech_commands import train
90 'train_dir': os.path.join(self.get_temp_dir(), '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'))
[all...] |
| /external/tensorflow/tensorflow/examples/get_started/regression/ |
| dnn_regression.py | 32 (train, test) = imports85.dataset()
38 train = train.map(normalize_price)
46 train.shuffle(1000).batch(128)
84 # Train the model.
85 model.train(input_fn=input_train, steps=STEPS)
|
| linear_regression_categorical.py | 32 (train, test) = imports85.dataset()
38 train = train.map(normalize_price)
46 train.shuffle(1000).batch(128)
88 # Train the model.
90 model.train(input_fn=input_train, steps=STEPS)
|
| custom_regression.py | 59 if mode == tf.estimator.ModeKeys.TRAIN:
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,
145 # Train the model.
146 model.train(input_fn=input_train, steps=STEPS
[all...] |
| /external/toolchain-utils/bestflags/examples/omnetpp/ |
| test_omnetpp | 6 (time ./omnetpp$1 ../../data/train/input/omnetpp.ini) 1>log-file 2>time.txt
11 diff ../../data/train/output/omnetpp.sca.result omnetpp.sca
|
| /external/tensorflow/tensorflow/examples/how_tos/reading_data/ |
| 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/contrib/model_pruning/examples/cifar10/ |
| 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
56 """Train CIFAR-10 for a number of steps."""
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)
[all...] |
| cifar10_eval.py | 28 data set, compile the program and train the model.
60 ckpt = tf.train.get_checkpoint_state(FLAGS.checkpoint_dir)
73 coord = tf.train.Coordinator()
119 variable_averages = tf.train.ExponentialMovingAverage(
122 saver = tf.train.Saver(variables_to_restore)
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/linear_regression/ |
| 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)
|
| /external/tensorflow/tensorflow/contrib/gan/ |
| __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/core/kernels/ |
| 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...] |
| 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);
|
| /external/tensorflow/tensorflow/contrib/gan/python/ |
| train_test.py | 15 """Tests for gan.python.train."""
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
[all...] |
| /external/tensorflow/tensorflow/contrib/eager/python/examples/revnet/ |
| cifar_tfrecords.py | 17 Generates tf.train.Example protos and writes them to TFRecord files from the
56 return tf.train.Feature(int64_list=tf.train.Int64List(value=[value]))
60 return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))
69 file_names['train'] = ['data_batch_%d' % i for i in range(1, 5)]
74 file_names['train_all'] = ['train']
77 file_names['train'] = ['train']
78 file_names['validation'] = ['train']
[all...] |
| /external/tensorflow/tensorflow/examples/tutorials/layers/ |
| cnn_mnist.py | 82 inputs=dense, rate=0.4, training=mode == tf.estimator.ModeKeys.TRAIN)
99 # Calculate Loss (for both TRAIN and EVAL modes)
102 # Configure the Training Op (for TRAIN mode)
103 if mode == tf.estimator.ModeKeys.TRAIN:
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(
136 # Train the mode
[all...] |
| /external/tensorflow/tensorflow/contrib/learn/python/learn/datasets/ |
| text_datasets.py | 42 train_path = os.path.join(data_dir, 'dbpedia_csv/train.csv')
58 train_path = os.path.join(data_dir, 'dbpedia_csv', 'train.csv')
65 train_path = train_path.replace('train.csv', 'train_small.csv')
72 train = base.load_csv_without_header(
77 return base.Datasets(train=train, validation=None, test=test)
|
| /external/tensorflow/tensorflow/examples/saved_model/integration_tests/ |
| use_model_in_sequential_keras.py | 33 def train(fine_tuning): function
34 """Build a Keras model and train with mock data."""
63 train(fine_tuning=False)
64 train(fine_tuning=True)
|
| /external/tensorflow/tensorflow/contrib/data/python/ops/ |
| interleave_ops.py | 47 filenames = tf.data.Dataset.list_files("/path/to/data/train*.tfrecords")
106 filenames = tf.data.Dataset.list_files("/path/to/data/train*.tfrecords")
|
| /external/tensorflow/tensorflow/python/data/experimental/kernel_tests/serialization/ |
| checkpoint_input_pipeline_hook_test.py | 53 mode='train',
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/contrib/layers/python/layers/ |
| 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}
[all...] |
| /external/tensorflow/tensorflow/contrib/distribute/python/examples/ |
| simple_estimator_example.py | 32 optimizer = tf.train.GradientDescentOptimizer(0.2)
55 assert mode == tf.estimator.ModeKeys.TRAIN
57 global_step = tf.train.get_global_step()
79 estimator.train(input_fn=train_input_fn, steps=steps)
|
