| /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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| D | Makefile | 4 train: target
5 python infra_tests.py --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:
59 train = False
61 train = True
70 err = t(train)
82 if train:
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| D | Makefile | 4 train: target
5 python infra_tests.py --train
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| /external/tensorflow/tensorflow/examples/speech_commands/ |
| D | train_test.py | 26 from tensorflow.examples.speech_commands import train
121 train.FLAGS = self._getDefaultFlags()
122 train.main('')
125 os.path.join(train.FLAGS.train_dir,
126 train.FLAGS.model_architecture + '.pbtxt')))
129 os.path.join(train.FLAGS.train_dir,
130 train.FLAGS.model_architecture + '_labels.txt')))
133 os.path.join(train.FLAGS.train_dir,
134 train.FLAGS.model_architecture + '.ckpt-1.meta')))
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | training_ops_test.cc | 111 Graph* train; in BM_SGD() local
112 SGD(params, &init, &train); in BM_SGD()
113 test::Benchmark("cpu", train, GetOptions(), init).Run(iters); in BM_SGD()
143 Graph* train; in BM_Adagrad() local
144 Adagrad(params, &init, &train); in BM_Adagrad()
145 test::Benchmark("cpu", train, GetOptions(), init).Run(iters); in BM_Adagrad()
177 Graph* train; in BM_SparseAdagrad() local
178 SparseAdagrad(m, n, &init, &train); in BM_SparseAdagrad()
179 test::Benchmark("cpu", train, GetMultiThreadedOptions(), init).Run(iters); in BM_SparseAdagrad()
216 Graph* train; in BM_Momentum() local
[all …]
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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()
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| /external/tensorflow/tensorflow/python/data/experimental/kernel_tests/serialization/ |
| D | checkpoint_input_pipeline_hook_test.py | 86 est.train(_input_fn, steps=2, hooks=[self._build_iterator_saver_hook(est)])
88 est.train(_input_fn, steps=2, hooks=[self._build_iterator_saver_hook(est)])
101 est.train(_input_fn, steps=2, hooks=[self._build_iterator_saver_hook(est)])
103 est.train(_input_fn, steps=2, hooks=[self._build_iterator_saver_hook(est)])
114 est.train(_input_fn, steps=2, hooks=[self._build_iterator_saver_hook(est)])
116 est.train(_input_fn, steps=2, hooks=[self._build_iterator_saver_hook(est)])
119 est.train(_input_fn, steps=2)
131 est.train(
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| /external/tensorflow/tensorflow/lite/micro/examples/magic_wand/train/ |
| D | train_magic_wand_model.ipynb | 35 …"This notebook demonstrates how to train a 20kb gesture recognition model for [TensorFlow Lite for…
41 …nsorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/magic_wand/train/train_magic_wand_m…
44 …nsorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/magic_wand/train/train_magic_wand_m…
105 "!cp -r tensorflow/tensorflow/lite/micro/examples/magic_wand/train train"
130 "# Download the data we will use to train the model\n",
132 "# Extract the data into the train directory\n",
133 "!tar xvzf data.tar.gz -C train 1>/dev/null"
156 "# The scripts must be run from within the train directory\n",
157 "%cd train\n",
213 "!python train.py --model CNN --person true"
[all …]
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| D | train_test.py | 27 from train import build_cnn
28 from train import build_lstm
29 from train import load_data
30 from train import reshape_function
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| D | README.md | 5 The scripts in this directory can be used to train a TensorFlow model that
9 The following document contains instructions on using the scripts to train a
31 notebook demonstrates how to train the model. It's the easiest way to get
36 …nsorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/magic_wand/train/train_magic_wand_m…
39 …nsorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/magic_wand/train/train_magic_wand_m…
53 There are two ways to train the model:
69 $ python train.py --model CNN --person false
82 $ python train.py --model CNN --person true
191 Finally, run the commands described earlier to train a new model.
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| /external/tensorflow/tensorflow/lite/experimental/examples/lstm/ |
| D | bidirectional_sequence_rnn_test.py | 164 opt = tf.train.AdamOptimizer(
171 batch_x, batch_y = self.mnist.train.next_batch(
218 saver = tf.train.Saver()
237 b1, _ = self.mnist.train.next_batch(batch_size=1, fake_data=True)
291 saver = tf.train.Saver()
313 saver = tf.train.Saver()
337 saver = tf.train.Saver()
364 saver = tf.train.Saver()
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| D | unidirectional_sequence_lstm_test.py | 132 opt = tf.train.AdamOptimizer(
139 batch_x, batch_y = self.mnist.train.next_batch(
174 saver = tf.train.Saver()
193 b1, _ = self.mnist.train.next_batch(batch_size=1, fake_data=True)
250 saver = tf.train.Saver()
269 saver = tf.train.Saver()
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| D | unidirectional_sequence_rnn_test.py | 128 opt = tf.train.AdamOptimizer(
134 batch_x, batch_y = self.mnist.train.next_batch(
169 saver = tf.train.Saver()
188 b1, _ = self.mnist.train.next_batch(batch_size=1, fake_data=True)
241 saver = tf.train.Saver()
260 saver = tf.train.Saver()
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| D | bidirectional_sequence_lstm_test.py | 143 opt = tf.train.AdamOptimizer(
150 batch_x, batch_y = self.mnist.train.next_batch(
190 saver = tf.train.Saver()
209 b1, _ = self.mnist.train.next_batch(batch_size=1, fake_data=True)
266 saver = tf.train.Saver()
285 saver = tf.train.Saver()
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| /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,
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| /external/tensorflow/tensorflow/examples/saved_model/integration_tests/ |
| D | use_model_in_sequential_keras.py | 35 def train(fine_tuning): function
70 train(fine_tuning=False)
71 train(fine_tuning=True)
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| /external/skqp/infra/bots/recipes/ |
| D | README.md | 14 When you change a recipe, you generally need to re-train the simulation test:
16 $ python infra/bots/recipes.py test train
20 $ cd infra/bots; make train
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| /external/skia/infra/bots/recipes/ |
| D | README.md | 14 When you change a recipe, you generally need to re-train the simulation test:
16 $ python infra/bots/recipes.py test train
20 $ cd infra/bots; make train
|
| /external/tensorflow/tensorflow/examples/tf2_showcase/ |
| D | mnist.py | 140 def train(model, optimizer, dataset, step_counter, log_interval=None, function
197 optimizer = tf.train.MomentumOptimizer(
211 step_counter = tf.train.get_or_create_global_step()
212 checkpoint = tf.train.Checkpoint(
215 checkpoint.restore(tf.train.latest_checkpoint(checkpoint_dir))
221 train(model, optimizer, train_ds, step_counter,
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| /external/tensorflow/tensorflow/examples/tutorials/mnist/ |
| D | mnist_with_summaries.py | 38 def train(): function
128 train_step = tf.compat.v1.train.AdamOptimizer(FLAGS.learning_rate).minimize(
151 def feed_dict(train): argument
153 if train or FLAGS.fake_data:
154 xs, ys = mnist.train.next_batch(100, fake_data=FLAGS.fake_data)
190 train()
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| D | input_data.py | 283 train = fake()
286 return _Datasets(train=train, validation=validation, test=test)
328 train = _DataSet(train_images, train_labels, **options)
332 return _Datasets(train=train, validation=validation, test=test)
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| /external/toolchain-utils/bestflags/examples/omnetpp/ |
| D | 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
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| /external/skqp/infra/bots/recipe_modules/ |
| D | README.md | 19 When you change a recipe module, you generally need to re-train the simulation
22 $ python infra/bots/recipes.py test run --train
26 $ cd infra/bots; make train
|
| /external/skia/infra/bots/recipe_modules/ |
| D | README.md | 19 When you change a recipe module, you generally need to re-train the simulation
22 $ python infra/bots/recipes.py test run --train
26 $ cd infra/bots; make train
|