| /external/tensorflow/tensorflow/core/kernels/ |
| parameterized_truncated_normal_op_test.cc | 27 static Graph* PTruncatedNormal(int num_batches, int samples_per_batch) {
30 shape_t.flat<int32>().setValues({num_batches, samples_per_batch});
33 Tensor means_t(DT_FLOAT, TensorShape({num_batches}));
35 Tensor stdevs_t(DT_FLOAT, TensorShape({num_batches}));
38 Tensor minvals_t(DT_FLOAT, TensorShape({num_batches}));
40 Tensor maxvals_t(DT_FLOAT, TensorShape({num_batches}));
56 static Graph* PTruncatedNormal2SD(int num_batches, int samples_per_batch) {
59 shape_t.flat<int32>().setValues({num_batches, samples_per_batch});
61 Tensor means_t(DT_FLOAT, TensorShape({num_batches}));
63 Tensor stdevs_t(DT_FLOAT, TensorShape({num_batches}));
[all...] |
| eigen_pooling_test.cc | 32 const int num_batches = 13; local
38 Tensor<float, 4> input(depth, input_rows, input_cols, num_batches);
39 Tensor<float, 4> result(depth, output_rows, output_cols, num_batches);
52 EXPECT_EQ(result.dimension(3), num_batches);
54 for (int b = 0; b < num_batches; ++b) {
80 const int num_batches = 13; local
86 Tensor<float, 4, RowMajor> input(num_batches, input_cols, input_rows, depth);
87 Tensor<float, 4, RowMajor> result(num_batches, output_cols, output_rows,
101 EXPECT_EQ(result.dimension(0), num_batches);
103 for (int b = 0; b < num_batches; ++b)
130 const int num_batches = 13; local
190 const int num_batches = 13; local
250 const int num_batches = 13; local
312 const int num_batches = 13; local
374 const int num_batches = 13; local
452 const int num_batches = 13; local
529 const int num_batches = 13; local
577 const int num_batches = 13; local
627 const int num_batches = 13; local
687 const int num_batches = 13; local
[all...] |
| eigen_backward_spatial_convolutions_test.cc | 500 const int num_batches = 13; local
511 num_batches);
514 num_batches);
526 EXPECT_EQ(input_backward.dimension(3), num_batches);
528 for (int b = 0; b < num_batches; ++b) {
555 const int num_batches = 13; local
565 Tensor<float, 4, RowMajor> input_backward(num_batches, input_cols, input_rows,
569 Tensor<float, 4, RowMajor> output_backward(num_batches, output_cols,
579 EXPECT_EQ(input_backward.dimension(0), num_batches);
584 for (int b = 0; b < num_batches; ++b)
611 const int num_batches = 13; local
678 const int num_batches = 13; local
801 int num_batches = 1; local
878 int num_batches = 1; local
999 const int num_batches = 11; local
1046 const int num_batches = 11; local
1096 const int num_batches = 11; local
1144 const int num_batches = 11; local
1191 const int num_batches = 11; local
1366 const int num_batches = 13; local
1421 const int num_batches = 13; local
1477 const int num_batches = 13; local
1540 const int num_batches = 13; local
1607 const int num_batches = 13; local
1674 const int num_batches = 13; local
1734 const int num_batches = 13; local
1795 const int num_batches = 13; local
1874 const int num_batches = 13; local
1953 const int num_batches = 13; local
2030 const int num_batches = 13; local
[all...] |
| parameterized_truncated_normal_op.h | 37 void operator()(OpKernelContext* ctx, const Device& d, int64 num_batches,
|
| parameterized_truncated_normal_op.cc | 52 void operator()(OpKernelContext* ctx, const CPUDevice& d, int64 num_batches,
85 // with length num_batches, but the scalar becomes an array of length 1.
91 // The last batch can be short, if we adjusted num_batches and
232 Shard(worker_threads.num_threads, worker_threads.workers, num_batches,
264 int32 num_batches = shape_tensor.flat<int32>()(0); variable
271 const int32 num_elements = num_batches * samples_per_batch;
273 // Allocate the output before fudging num_batches and samples_per_batch.
305 int32 size = num_batches * samples_per_batch;
309 num_batches = adjusted_batches;
312 // Parameters must be broadcastable to the shape [num_batches]
[all...] |
| eigen_spatial_convolutions_test.cc | 195 const int num_batches = 13; local
202 Tensor<float, 4> input(input_depth, input_rows, input_cols, num_batches);
204 Tensor<float, 4> result(output_depth, output_rows, output_cols, num_batches);
217 EXPECT_EQ(result.dimension(3), num_batches);
219 for (int b = 0; b < num_batches; ++b) {
247 const int num_batches = 13; local
257 Tensor<float, 4> input(input_depth, input_rows, input_cols, num_batches);
259 Tensor<float, 4> result(output_depth, output_rows, output_cols, num_batches);
272 EXPECT_EQ(result.dimension(3), num_batches);
275 for (int b = 0; b < num_batches; ++b)
305 const int num_batches = 13; local
361 const int num_batches = 13; local
409 const int num_batches = 5; local
457 const int num_batches = 13; local
508 const int num_batches = 13; local
559 const int num_batches = 13; local
613 const int num_batches = 13; local
[all...] |
| parameterized_truncated_normal_op_gpu.cu.cc | 51 TruncatedNormalKernel(random::PhiloxRandom gen, T* data, int64 num_batches,
195 void operator()(OpKernelContext* ctx, const GPUDevice& d, int64 num_batches,
207 gen, output.data(), num_batches, samples_per_batch, num_elements,
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/linear_regression/ |
| linear_regression_graph_test.py | 30 num_batches = 200
38 num_batches=num_batches)
75 examples_per_sec = num_epochs * num_batches * batch_size / wall_time
79 iters=num_epochs * num_batches,
|
| linear_regression_test.py | 51 num_batches = 2
54 batch_size, num_batches)
72 true_w, true_b, noise_level=0., batch_size=64, num_batches=40)
87 num_batches = 200
94 num_batches=num_batches)
110 examples_per_sec = num_epochs * num_batches * batch_size / wall_time
114 iters=num_epochs * num_batches,
|
| linear_regression.py | 106 def synthetic_dataset(w, b, noise_level, batch_size, num_batches):
110 num_batches)
114 num_batches):
126 return tf.data.Dataset.range(num_batches).map(batch)
|
| /external/tensorflow/tensorflow/contrib/slim/python/slim/data/ |
| prefetch_queue_test.py | 43 num_batches = 5
48 counter = examples.count_up_to(num_batches * batch_size)
62 for i in range(num_batches):
80 num_batches = 5
85 counter = examples.count_up_to(num_batches * batch_size)
100 for _ in range(num_batches):
109 np.arange(0, num_batches * batch_size))
120 num_batches = 4
125 counter = examples.count_up_to(num_batches * batch_size)
141 for _ in range(int(num_batches / 2))
[all...] |
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| fractional_max_pool_op_test.py | 204 num_batches = 5
210 tensor_shape = (num_batches, num_rows, num_cols, num_channels)
220 num_batches = 5
226 tensor_shape = (num_batches, num_rows, num_cols, num_channels)
239 for num_batches in [1, 3]:
243 tensor_shape = (num_batches, num_rows, num_cols, num_channels)
255 num_batches = 3
259 tensor_shape = (num_batches, num_rows, num_cols, num_channels)
276 num_batches = 3
280 tensor_shape = (num_batches, num_rows, num_cols, num_channels
[all...] |
| fractional_avg_pool_op_test.py | 202 num_batches = 5
208 tensor_shape = (num_batches, num_rows, num_cols, num_channels)
268 for num_batches in [1, 3]:
272 tensor_shape = (num_batches, num_rows, num_cols, num_channels)
284 num_batches = 3
288 tensor_shape = (num_batches, num_rows, num_cols, num_channels)
305 num_batches = 3
309 tensor_shape = (num_batches, num_rows, num_cols, num_channels)
385 for num_batches in [1, 3]:
391 input_shape = (num_batches, num_rows, num_cols, num_channels
[all...] |
| self_adjoint_eig_op_test.py | 109 num_batches = int(np.prod(x_e.shape[:-1]))
111 x_e = np.reshape(x_e, [num_batches] + [n])
112 x_v = np.reshape(x_v, [num_batches] + [n, n])
113 y_e = np.reshape(y_e, [num_batches] + [n])
114 y_v = np.reshape(y_v, [num_batches] + [n, n])
115 for i in range(num_batches):
|
| /external/tensorflow/tensorflow/contrib/lite/kernels/ |
| svdf_test.cc | 183 int num_batches() { return batches_; } function in class:tflite::__anon39280::SVDFOpModel
221 const int svdf_num_batches = svdf.num_batches();
281 const int svdf_num_batches = svdf.num_batches();
|
| basic_rnn_test.cc | 174 int num_batches() { return batches_; } function in class:tflite::__anon39244::RNNOpModel
239 (rnn.input_size() * rnn.num_batches());
|
| fully_connected_test.cc | 157 int num_batches() { return batches_; } function in class:tflite::__anon39254::BaseFullyConnectedOpModel
348 (m.input_size() * m.num_batches());
|
| /external/tensorflow/tensorflow/python/training/ |
| input_test.py | 445 num_batches = 3
448 counter = examples.count_up_to(num_batches * batch_size)
472 for i in range(num_batches):
503 num_batches = 3
506 counter = examples.count_up_to(num_batches * batch_size)
515 for i in range(num_batches):
533 num_batches = 3
536 counter = examples.count_up_to(num_batches * batch_size)
547 for i in range(num_batches):
568 num_batches =
[all...] |
| /external/tensorflow/tensorflow/contrib/gan/python/eval/python/ |
| classifier_metrics_impl.py | 305 def classifier_score(images, classifier_fn, num_batches=1):
327 num_batches: Number of batches to split `generated_images` in to in order to
335 images, num_or_size_splits=num_batches)
445 num_batches=1):
480 num_batches: Number of batches to split images in to in order to
489 real_images, num_or_size_splits=num_batches)
491 generated_images, num_or_size_splits=num_batches)
505 real_a, gen_a = array_ops.split(activations, [num_batches, num_batches], 0)
|
| /external/libxkbcommon/xkbcommon/src/x11/ |
| util.c | 162 const size_t num_batches = ROUNDUP(count, SIZE) / SIZE; local
165 for (size_t batch = 0; batch < num_batches; batch++) {
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/spinn/ |
| data_test.py | 254 self.assertEqual(4, train_data.num_batches(1))
255 self.assertEqual(2, train_data.num_batches(2))
256 self.assertEqual(2, train_data.num_batches(3))
257 self.assertEqual(1, train_data.num_batches(4))
|
| /frameworks/ml/nn/common/operations/ |
| SVDFTest.cpp | 319 int num_batches() const { return batches_; } function in class:android::nn::wrapper::SVDFOpModel
361 const int svdf_num_batches = svdf.num_batches();
423 const int svdf_num_batches = svdf.num_batches();
|
| RNNTest.cpp | 213 uint32_t num_batches() const { return batches_; } function in class:android::nn::wrapper::BasicRNNOpModel
315 (rnn.input_size() * rnn.num_batches());
|
| /external/tensorflow/tensorflow/contrib/data/python/kernel_tests/ |
| batch_dataset_op_test.py | 209 num_batches = 7 // test_batch_size
210 for i in range(num_batches):
264 num_batches = 7 // test_batch_size
265 for i in range(num_batches):
345 num_batches = (28 * 7) // 14
346 for i in range(num_batches):
359 # We expect (num_batches - 1) full-sized batches.
360 num_batches = int(math.ceil((14 * 7) / 8))
361 for i in range(num_batches - 1):
370 self.assertAllEqual(component[((num_batches - 1) * 8 + j) % 7]**2
[all...] |
| /external/tensorflow/tensorflow/python/data/kernel_tests/ |
| batch_dataset_op_test.py | 67 num_batches = (28 * 7) // 14
68 for i in range(num_batches):
81 # We expect (num_batches - 1) full-sized batches.
82 num_batches = int(math.ceil((14 * 7) / 8))
83 for i in range(num_batches - 1):
92 self.assertAllEqual(component[((num_batches - 1) * 8 + j) % 7]**2,
|
