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Searched refs:num_examples (Results 1 – 24 of 24) sorted by relevance

/external/tensorflow/tensorflow/core/kernels/
Dsdca_ops_test.cc88 const int num_examples) { in SparseExampleIndices() argument
89 const int x_size = num_examples * 4; in SparseExampleIndices()
96 const int num_examples) { in SparseFeatureIndices() argument
97 const int x_size = num_examples * 4; in SparseFeatureIndices()
122 void GetGraphs(const int32 num_examples, const int32 num_sparse_feature_groups, in GetGraphs() argument
179 SparseExampleIndices(g, sparse_features_per_group, num_examples))); in GetGraphs()
184 SparseFeatureIndices(g, sparse_features_per_group, num_examples))); in GetGraphs()
189 NodeBuilder::NodeOut(RandomZeroOrOne(g, num_examples * 4))); in GetGraphs()
196 RandomZeroOrOneMatrix(g, num_examples, dense_features_per_group))); in GetGraphs()
199 Node* const weights = Ones(g, num_examples); in GetGraphs()
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Dsdca_internal.cc247 for (int example_id = 0; example_id < num_examples(); ++example_id) { in SampleAdaptiveProbabilities()
270 auto local_gen = generator.ReserveSamples32(num_examples()); in SampleAdaptiveProbabilities()
284 while (id < num_examples() && num_retries < num_examples()) { in SampleAdaptiveProbabilities()
295 examples_not_seen.reserve(num_examples()); in SampleAdaptiveProbabilities()
296 for (int i = 0; i < num_examples(); ++i) { in SampleAdaptiveProbabilities()
305 for (int i = id; i < num_examples(); ++i) { in SampleAdaptiveProbabilities()
350 const int num_examples = static_cast<int>(example_weights.size()); in Initialize() local
360 examples_.resize(num_examples); in Initialize()
361 probabilities_.resize(num_examples); in Initialize()
362 sampled_index_.resize(num_examples); in Initialize()
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Dsdca_internal.h337 int num_examples() const { return examples_.size(); } in num_examples() function
352 const DeviceBase::CpuWorkerThreads& worker_threads, int num_examples,
363 const DeviceBase::CpuWorkerThreads& worker_threads, int num_examples,
371 const DeviceBase::CpuWorkerThreads& worker_threads, int num_examples,
Dsdca_ops.cc144 TensorShape expected_example_state_shape({examples.num_examples(), 4}); in DoCompute()
228 examples.num_examples(), kCostPerUnit, train_step); in DoCompute()
/external/tensorflow/tensorflow/tools/gcs_test/python/
Dgcs_smoke.py39 def create_examples(num_examples, input_mean): argument
41 ids = np.arange(num_examples).reshape([num_examples, 1])
42 inputs = np.random.randn(num_examples, 1) + input_mean
45 for row in range(num_examples):
208 example_data = create_examples(FLAGS.num_examples, 5)
223 if read_count != FLAGS.num_examples:
226 FLAGS.num_examples))
241 for _ in range(FLAGS.num_examples):
/external/tensorflow/tensorflow/python/debug/examples/
Ddebug_keras.py32 num_examples = 8
36 xs = np.zeros([num_examples, input_dims])
37 ys = np.zeros([num_examples, output_dims])
39 (xs, ys)).repeat(num_examples).batch(int(num_examples / steps_per_epoch))
/external/tensorflow/tensorflow/examples/how_tos/reading_data/
Dconvert_to_records.py44 num_examples = data_set.num_examples
46 if images.shape[0] != num_examples:
48 (images.shape[0], num_examples))
56 for index in range(num_examples):
/external/tensorflow/tensorflow/contrib/crf/
DREADME.md15 num_examples = 10
21 x = np.random.rand(num_examples, num_words, num_features).astype(np.float32)
24 y = np.random.randint(num_tags, size=[num_examples, num_words]).astype(np.int32)
27 sequence_lengths = np.full(num_examples, num_words - 1, dtype=np.int32)
42 [num_examples, num_words, num_tags])
/external/tensorflow/tensorflow/contrib/linear_optimizer/python/
Dsdca_estimator_test.py519 num_examples = 40
522 constant_op.constant([str(x + 1) for x in range(num_examples)]),
526 constant_op.constant([[0.0]] * num_examples),
528 for i in range(num_examples)])
563 num_examples = 200
564 half = int(num_examples / 2)
567 constant_op.constant([str(x + 1) for x in range(num_examples)]),
616 num_examples = 200
617 half = int(num_examples / 2)
620 constant_op.constant([str(x + 1) for x in range(num_examples)]),
/external/tensorflow/tensorflow/contrib/factorization/examples/
Dmnist.py106 batch_size = min(FLAGS.batch_size, data_set.num_examples)
107 steps_per_epoch = data_set.num_examples // batch_size
108 num_examples = steps_per_epoch * batch_size
115 precision = true_count / num_examples
117 (num_examples, true_count, precision))
/external/tensorflow/tensorflow/examples/tutorials/mnist/
Dfully_connected_feed.py104 steps_per_epoch = data_set.num_examples // FLAGS.batch_size
105 num_examples = steps_per_epoch * FLAGS.batch_size
111 precision = float(true_count) / num_examples
113 (num_examples, true_count, precision))
/external/tensorflow/tensorflow/contrib/factorization/python/ops/
Dgmm_ops_test.py39 self.num_examples = 1000
44 self.data, self.true_assignments = self.make_data(self.num_examples)
48 self.num_examples, self.centers)
136 self.assertEqual((self.num_examples, 1), scores.shape)
Dgmm_ops.py405 num_examples = math_ops.cast(math_ops.reduce_sum(final_points_in_k),
408 (num_examples + MEPS))
/external/tensorflow/tensorflow/core/ops/
Dparsing_ops.cc173 shape_inference::DimensionHandle num_examples = c->Dim(input, 0); in __anon952516500402() local
197 TF_RETURN_IF_ERROR(c->Concatenate(c->Vector(num_examples), s, &s)); in __anon952516500402()
219 c->Concatenate(c->Matrix(num_examples, c->UnknownDim()), s, &s)); in __anon952516500402()
225 c->set_output(output_idx++, c->Vector(num_examples)); in __anon952516500402()
/external/tensorflow/tensorflow/contrib/linear_optimizer/python/kernel_tests/
Dsdca_ops_test.py113 def make_random_examples_and_variables_dicts(num_examples, dim, num_non_zero): argument
118 [i for i in range(num_examples) for _ in range(num_non_zero)], [
119 i for _ in range(num_examples)
122 [num_non_zero**(-0.5) for _ in range(num_examples * num_non_zero)])
127 example_weights=[random.random() for _ in range(num_examples)],
129 1. if random.random() > 0.5 else 0. for _ in range(num_examples)
131 example_ids=[str(i) for i in range(num_examples)])
395 num_examples = 1000
401 num_examples, dim, non_zeros)
/external/tensorflow/tensorflow/contrib/gan/python/features/python/
Dvirtual_batchnorm_test.py130 num_examples = 4
132 range(num_examples)]
138 for i in range(num_examples):
/external/tensorflow/tensorflow/core/util/
Dexample_proto_fast_parsing.cc1763 int num_examples = serialized.size(); in FastParseSequenceExample() local
1774 if (!example_names.empty() && example_names.size() != num_examples) { in FastParseSequenceExample()
1826 all_context_features(num_examples); in FastParseSequenceExample()
1828 all_sequence_features(num_examples); in FastParseSequenceExample()
1830 for (int d = 0; d < num_examples; d++) { in FastParseSequenceExample()
2013 dense_shape.AddDim(num_examples); in FastParseSequenceExample()
2041 for (int e = 0; e < num_examples; e++) { in FastParseSequenceExample()
2154 for (int e = 0; e < num_examples; e++) { in FastParseSequenceExample()
2192 out_shape(0) = num_examples; in FastParseSequenceExample()
2196 TensorShape dense_length_shape({num_examples}); in FastParseSequenceExample()
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/external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/
Dlinear_test.py1739 num_examples = 40
1742 constant_op.constant([str(x + 1) for x in range(num_examples)]),
1746 constant_op.constant([[0.0]] * num_examples),
1748 [[1 if i % 4 == 0 else 0] for i in range(num_examples)])
1785 num_examples = 200
1786 half = int(num_examples / 2)
1789 constant_op.constant([str(x + 1) for x in range(num_examples)]),
1839 num_examples = 200
1840 half = int(num_examples / 2)
1843 constant_op.constant([str(x + 1) for x in range(num_examples)]),
/external/tensorflow/tensorflow/contrib/model_pruning/examples/cifar10/
Dcifar10_eval.py80 num_iter = int(math.ceil(FLAGS.num_examples / 128))
/external/tensorflow/tensorflow/contrib/eager/python/examples/nmt_with_attention/
Dnmt_with_attention.ipynb175 "def create_dataset(path, num_examples):\n",
178 … word_pairs = [[preprocess_sentence(w) for w in l.split('\\t')] for l in lines[:num_examples]]\n",
232 "def load_dataset(path, num_examples):\n",
234 " pairs = create_dataset(path, num_examples)\n",
287 "num_examples = 30000\n",
288 …r, inp_lang, targ_lang, max_length_inp, max_length_targ = load_dataset(path_to_file, num_examples)"
/external/tensorflow/tensorflow/tools/docker/notebooks/
D2_getting_started.ipynb158 "num_examples = 50\n",
159 "X = np.array([np.linspace(-2, 4, num_examples), np.linspace(-6, 6, num_examples)])\n",
160 "X += np.random.randn(2, num_examples)\n",
286 "num_examples = 50\n",
287 "X = np.array([np.linspace(-2, 4, num_examples), np.linspace(-6, 6, num_examples)])\n",
350 "X += np.random.randn(2, num_examples)\n",
579 "num_examples = 50\n",
580 "X = np.array([np.linspace(-2, 4, num_examples), np.linspace(-6, 6, num_examples)])\n",
582 "X += np.random.randn(2, num_examples)\n",
/external/tensorflow/tensorflow/lite/kernels/
Dbidirectional_sequence_rnn_test.cc1027 const int num_examples = 64; in TEST() local
1028 for (int k = 0; k < num_examples; k++) { in TEST()
/external/tensorflow/tensorflow/contrib/learn/python/learn/datasets/
Dmnist.py176 def num_examples(self): member in DataSet
/external/tensorflow/tensorflow/contrib/slim/
DREADME.md890 num_examples = 10000
892 num_batches = math.ceil(num_examples / float(batch_size))