/external/tensorflow/tensorflow/lite/testing/op_tests/ |
D | strided_slice_np_style.py | 37 [tf.newaxis, 38 slice(3, 7, 1), tf.newaxis, 45 "spec": [[slice(3, 7, 2)], [tf.newaxis, slice(None)]], 96 "spec": [[tf.newaxis, # new_axis before ellipsis 99 [tf.newaxis, # new_axis after (and before) ellipsis 101 slice(None), Ellipsis, tf.newaxis]],
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/external/tensorflow/tensorflow/python/ops/distributions/ |
D | multinomial.py | 207 self._mean_val = self._total_count[..., array_ops.newaxis] * self._probs 254 n_draws[..., array_ops.newaxis], dtype=self.logits.dtype) * self.logits 263 x = random_ops.multinomial(logits[array_ops.newaxis, ...], n_draw, 296 self.total_count)[..., array_ops.newaxis] 298 -math_ops.matmul(self._mean_val[..., array_ops.newaxis], 299 p[..., array_ops.newaxis, :]), # outer product 304 self.total_count)[..., array_ops.newaxis]
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D | dirichlet.py | 268 return self.concentration / self.total_concentration[..., array_ops.newaxis] 273 -math_ops.matmul(x[..., array_ops.newaxis], 274 x[..., array_ops.newaxis, :]), # outer prod 284 return math_ops.rsqrt(1. + self.total_concentration[..., array_ops.newaxis]) 294 self.total_concentration[..., array_ops.newaxis] - k)
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D | dirichlet_multinomial.py | 295 self.total_concentration[..., array_ops.newaxis]) 318 -math_ops.matmul(x[..., array_ops.newaxis], 319 x[..., array_ops.newaxis, :]), # outer prod 331 c0 = self.total_concentration[..., array_ops.newaxis]
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/external/tensorflow/tensorflow/python/ops/linalg/ |
D | linear_operator_kronecker.py | 344 output = output[array_ops.newaxis, ...] 461 output = output[array_ops.newaxis, ...] 518 diag_part = diag_part[..., :, array_ops.newaxis] 519 op_diag_part = operator.diag_part()[..., array_ops.newaxis, :] 538 ..., :, array_ops.newaxis, :, array_ops.newaxis] 541 ..., array_ops.newaxis, :, array_ops.newaxis, :] 564 product = product[..., array_ops.newaxis] 566 product = product * eigval[..., array_ops.newaxis, :]
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D | linear_operator_householder.py | 214 mat = normalized_axis[..., array_ops.newaxis] 245 mat = normalized_axis[..., array_ops.newaxis]
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D | linear_operator_block_diag.py | 420 x_mat = [block[..., array_ops.newaxis] for block in x] 429 x_mat = x[..., array_ops.newaxis] 616 diag_list += [operator.diag_part()[..., array_ops.newaxis]] 670 eig_list += [operator.eigvals()[..., array_ops.newaxis]]
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D | linear_operator_block_lower_triangular.py | 560 x_mat = [block[..., array_ops.newaxis] for block in x] 569 x_mat = x[..., array_ops.newaxis] 829 diag_list.append(op.diag_part()[..., array_ops.newaxis]) 872 eig_list.append(op.eigvals()[..., array_ops.newaxis])
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/external/tensorflow/tensorflow/compiler/tests/ |
D | image_ops_test.py | 425 out = sess.run(resized, {image: image_np[np.newaxis, :, :, np.newaxis]}) 428 expected[np.newaxis, :, :, np.newaxis], out, rtol=2e-4, atol=2e-4) 430 self.assertAllClose(expected[np.newaxis, :, :, np.newaxis], out) 564 out = sess.run(resized, {image: image_np[np.newaxis, :, :, np.newaxis]}) 567 expected[np.newaxis, :, :, np.newaxis], out, rtol=0.1, atol=0.01) 569 self.assertAllClose(expected[np.newaxis, :, :, np.newaxis], out) 648 out = sess.run(resized, {grads: grads_np[np.newaxis, :, :, np.newaxis]}) 651 expected[np.newaxis, :, :, np.newaxis], out, rtol=0.1, atol=0.01) 654 expected[np.newaxis, :, :, np.newaxis], out) 725 out = sess.run(resized, {image: image_np[np.newaxis, :, :, np.newaxis]}) [all …]
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D | gather_nd_op_test.py | 114 np.vstack((params[np.newaxis, :], params[np.newaxis, :])),
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/external/tensorflow/tensorflow/python/ops/linalg/sparse/ |
D | conjugate_gradient.py | 91 x[..., array_ops.newaxis], 97 x = state.x + alpha[..., array_ops.newaxis] * state.p 98 r = state.r - alpha[..., array_ops.newaxis] * z 105 p = q + beta[..., array_ops.newaxis] * state.p
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/external/tensorflow/tensorflow/python/ops/ragged/ |
D | ragged_getitem_test.py | 219 (SLICE_BUILDER[array_ops.newaxis, :], [EXAMPLE_RAGGED_TENSOR_2D]), 220 (SLICE_BUILDER[:, array_ops.newaxis], 355 (SLICE_BUILDER[array_ops.newaxis, :], [EXAMPLE_RAGGED_TENSOR_4D]), 356 (SLICE_BUILDER[:, array_ops.newaxis], 484 rt_newaxis0 = rt[array_ops.newaxis] 485 rt_newaxis1 = rt[:, array_ops.newaxis] 486 rt_newaxis2 = rt[:, :, array_ops.newaxis] 487 rt_newaxis3 = rt[:, :, :, array_ops.newaxis] 488 rt_newaxis4 = rt[:, :, :, :, array_ops.newaxis]
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D | ragged_getitem.py | 135 if row_key is array_ops.newaxis: 258 if column_key is array_ops.newaxis: 383 num_indices = sum(1 for idx in key_list if idx is not array_ops.newaxis)
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/external/tensorflow/tensorflow/python/kernel_tests/linalg/ |
D | linear_operator_kronecker_test.py | 42 product = product[..., array_ops.newaxis, :, array_ops.newaxis] 43 factor_to_mul = factor[..., array_ops.newaxis, :, array_ops.newaxis, :]
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/external/tensorflow/tensorflow/python/kernel_tests/ |
D | ctc_decoder_ops_test.py | 144 ], np.float32)[:, np.newaxis] 198 input_prob_matrix_0[t, :][np.newaxis, :] for t in range(seq_len_0) 212 np.float32)[np.newaxis, :]
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D | array_ops_test.py | 755 ones[array_ops.newaxis, :, 795 _ = checker[np.newaxis] 797 _ = checker[..., np.newaxis] 799 _ = checker[..., np.newaxis, :] 800 _ = checker[:, ..., np.newaxis, :, :] 802 _ = checker[:, :, np.newaxis, :, 2::-1] 804 _ = checker[np.newaxis, ..., np.newaxis] 825 _ = checker[np.newaxis, ..., np.newaxis] 829 _ = checker[np.newaxis, 1:] 896 self.tensorShapeEqual(a[3:5, :, array_ops.newaxis, 50:3,], [all …]
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/external/tensorflow/tensorflow/python/kernel_tests/signal/ |
D | reconstruction_ops_test.py | 47 powers = np.power(self.bases[:, np.newaxis], exponents[np.newaxis, :]) 152 input_matrix = input_matrix[np.newaxis, :, :].astype(float)
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/external/tensorflow/tensorflow/python/keras/applications/ |
D | imagenet_utils_test.py | 116 self.assertEqual(model.predict(x[np.newaxis])[0].shape, x.shape) 123 out1 = model1.predict(x[np.newaxis])[0] 131 out2 = model2.predict(x2[np.newaxis])[0]
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/external/tensorflow/tensorflow/python/data/experimental/kernel_tests/serialization/ |
D | parallel_map_dataset_serialization_test.py | 48 np.arange(self._tensor_slice_len)[:, np.newaxis], 59 np.arange(self._tensor_slice_len)[:, np.newaxis],
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D | unbatch_dataset_serialization_test.py | 37 np.array([[1, 2, 3]]) * np.arange(tensor_slice_len)[:, np.newaxis],
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D | batch_dataset_serialization_test.py | 40 np.array([[1, 2, 3]]) * np.arange(tensor_slice_len)[:, np.newaxis],
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/external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
D | multinomial_test.py | 269 theta /= np.sum(theta, 1)[..., array_ops.newaxis] 276 x_centered = x - sample_mean[array_ops.newaxis, ...] 278 x_centered[..., array_ops.newaxis], 279 x_centered[..., array_ops.newaxis, :]), 0)
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D | dirichlet_multinomial_test.py | 241 x_centered = x - sample_mean[array_ops.newaxis, ...] 243 x_centered[..., array_ops.newaxis], 244 x_centered[..., array_ops.newaxis, :]), 0) 339 ns * (ns + alpha_0) / (1 + alpha_0))[..., array_ops.newaxis]
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/external/tensorflow/tensorflow/python/ops/numpy_ops/ |
D | __init__.py | 172 from tensorflow.python.ops.array_ops import newaxis
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/external/tensorflow/tensorflow/python/data/benchmarks/ |
D | batch_benchmark.py | 38 indices=np.arange(non_zeros_per_row, dtype=np.int64)[:, np.newaxis],
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