/external/tensorflow/tensorflow/compiler/tests/ |
D | matrix_triangular_solve_op_test.py | 81 a = np.tril(rng.randn(5, 5)) 82 b = rng.randn(5, 7) 88 a = rng.randn(5, 5) # the `a` matrix is not lower-triangular 89 b = rng.randn(5, 7) 101 a = np.tril(rng.randn(5, 5) + rng.randn(5, 5) * 1j) 102 b = rng.randn(5, 7) + rng.randn(5, 7) * 1j 114 b = rng.randn(*b_shape) 126 b = rng.randn(*b_shape) 134 b = rng.randn(n, n) 142 a = rng.randn(3, 4).astype(dtype) [all …]
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/external/tensorflow/tensorflow/python/compiler/tensorrt/test/ |
D | concatenation_test.py | 38 a = constant_op.constant(np.random.randn(3, 1, 1), dtype=dtype) 40 a = constant_op.constant(np.random.randn(3, 1, 1), dtype=dtype) 42 a = constant_op.constant(np.random.randn(1, 3, 1), dtype=dtype) 44 a = constant_op.constant(np.random.randn(1, 3, 1), dtype=dtype) 46 a = constant_op.constant(np.random.randn(3, 1, 1), dtype=dtype) 48 a = constant_op.constant(np.random.randn(3, 1, 1), dtype=dtype) 50 a = constant_op.constant(np.random.randn(3, 1), dtype=dtype) 52 a = constant_op.constant(np.random.randn(3, 1), dtype=dtype) 54 a = constant_op.constant(np.random.randn(3, 1, 1), dtype=dtype) 56 a = constant_op.constant(np.random.randn(3, 1), dtype=dtype) [all …]
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D | memory_alignment_test.py | 37 np.random.randn(1, 1, 3, 5), name="kernel_1", dtype=dtype) 39 np.random.randn(1, 1, 5, 10), name="kernel_2", dtype=dtype)
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D | vgg_block_nchw_test.py | 47 np.random.randn(1, 1, 2, 6), name="weights", dtype=dtype) 55 b = constant_op.constant(np.random.randn(6), name="bias", dtype=dtype)
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D | vgg_block_test.py | 46 np.random.randn(1, 1, 2, 6), name="weights", dtype=dtype) 49 b = constant_op.constant(np.random.randn(6), name="bias", dtype=dtype)
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D | dynamic_input_shapes_test.py | 37 bias1 = constant_op.constant(np.random.randn(8), dtype=dtypes.float32) 48 bias2 = constant_op.constant(np.random.randn(1), dtype=dtypes.float32)
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D | batch_matmul_test.py | 81 np.random.randn(1, 5, 7), dtype=dtype, name="kernel") 99 b = constant_op.constant(np.random.randn(5, 7), dtype=dtype, name="kernel")
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/external/tensorflow/tensorflow/python/kernel_tests/ |
D | einsum_op_test.py | 48 arr = np.array(r.randn(*shape)).astype(dtype) 50 arr += 1j * np.array(r.randn(*shape)).astype(dtype) 167 arr = np.array(r.randn(*shape)).astype(dtype) 169 arr += 1j * np.array(r.randn(*shape)).astype(dtype) 195 ('ij,jk->ik', r.randn(1, 2, 3), r.randn(3, 4)), 196 ('...ij,jk->ik', r.randn(3), r.randn(3, 4)), 198 ('ij,jk->ik', r.randn(2, 3), r.randn(4, 4)), 200 ('...ij,...jk->...ik', r.randn(5, 2, 3), r.randn(7, 3, 4)), 203 ('...ij,...jk->ik', r.randn(2, 2, 3), r.randn(3, 4)), 226 input_np = np.array(r.randn(*actual_shape)) [all …]
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D | betainc_op_test.py | 118 a_s = np.abs(np.random.randn(10, 10) * 30) # in (0, infty) 119 b_s = np.abs(np.random.randn(10, 10) * 30) # in (0, infty) 125 a_s = np.abs(np.random.randn(10, 10) * 30) # in (0, infty) 126 b_s = np.abs(np.random.randn(10, 10) * 30) # in (0, infty) 132 a_s = np.abs(np.random.randn(10, 10) * 1e15) # in (0, infty) 133 b_s = np.abs(np.random.randn(10, 10) * 1e15) # in (0, infty) 140 a_s = np.abs(np.random.randn(10, 10) * 1e-16) # in (0, infty) 141 b_s = np.abs(np.random.randn(10, 10) * 1e-16) # in (0, infty) 148 a_s = np.abs(np.random.randn(10, 10) * 1e-8) # in (0, infty) 149 b_s = np.abs(np.random.randn(10, 10) * 1e-8) # in (0, infty) [all …]
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D | sparse_add_op_test.py | 55 x = np.random.randn(n, m).astype(np_dtype) 164 rand_vals_np = np.random.randn(n, m).astype(dtype) 165 dense_np = np.random.randn(n, m).astype(dtype) 184 rand_vals_np = np.random.randn(n, m).astype(np.float32) 185 dense_np = np.random.randn(n, m).astype(np.float32)
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D | bias_op_base.py | 289 self._testAll(np.random.randn(*shape), np.random.randn(shape[-1])) 295 np.random.randn(*shape), np.random.randn(shape[-1]), dtypes.float64, 302 np.random.randn(*shape), np.random.randn(shape[-1]), dtypes.float64,
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D | where_op_test.py | 97 x = np.random.randn(*shape) + 1j * np.random.randn(*shape) 98 x = (np.random.randn(*shape) > 0).astype(dtype) 253 x = np.random.randn(3, 4) 254 y = np.random.randn(3, 4)
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/external/tensorflow/tensorflow/python/kernel_tests/linalg/sparse/ |
D | csr_sparse_matrix_test.py | 67 a_mats = sparsify(np.random.randn(*dense_shape)).astype(np.float32) 87 a_mats = np.random.randn(*dense_shape).astype(np.float32) 111 (np.random.randn(*dense_shape) + 1.j * np.random.randn(*dense_shape)) 128 a_mats = sparsify((np.random.randn(*dense_shape) + 129 1.j * np.random.randn(*dense_shape))).astype( 159 a_mats = sparsify((np.random.randn(*dense_shape_a) + 160 1.j * np.random.randn(*dense_shape_a))).astype(dtype) 161 b_mats = sparsify((np.random.randn(*dense_shape_b) + 162 1.j * np.random.randn(*dense_shape_b))).astype(dtype) 200 a_mats = sparsify((np.random.randn(*dense_shape_a) + [all …]
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D | csr_sparse_matrix_grad_test.py | 66 mats_val = sparsify(np.random.randn(*dense_shape)) 72 grad_vals = np.random.randn(*dense_shape).astype(np.float32) 92 a_mats_val = sparsify(np.random.randn(*dense_shape)) 93 b_mats_val = sparsify(np.random.randn(*dense_shape)) 96 grad_vals = np.random.randn(*dense_shape).astype(np.float32)
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D | csr_sparse_matrix_ops_test.py | 185 a_mats = sparsify(np.random.randn(*dense_shape)).astype(np.float32) 256 sparsify(np.random.randn(*dense_shape)).astype(np.float32) 387 sparsify(np.random.randn(*dense_shape)).astype(np.float32) 480 a_mats = sparsify(np.random.randn(*dense_shape)).astype(np.float32) 481 b_mats = sparsify(np.random.randn(*dense_shape)).astype(np.float32) 509 b = np.random.randn(*shapes[1]).astype(np.float32) 529 b = np.random.randn(*shapes[1]).astype(np.complex64) 561 (np.random.randn(*a_dense_shape) + 562 1.j * np.random.randn(*a_dense_shape))).astype(dtype) 563 b_mats = (np.random.randn(*b_dense_shape) + [all …]
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D | csr_sparse_matrix_dense_mat_mul_grad_test.py | 69 np.random.randn(3, 5, 11) + 70 1.j * np.random.randn(3, 5, 11)).astype(datatype) 75 b_mats_val = (np.random.randn(3, 11, 13) + 76 1.j * np.random.randn(3, 11, 13)).astype(datatype)
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D | csr_sparse_matrix_sparse_mat_mul_grad_test.py | 69 np.random.randn(3, 5, 11) + 70 1.j * np.random.randn(3, 5, 11)).astype(datatype) 76 np.random.randn(3, 11, 13) + 77 1.j * np.random.randn(3, 11, 13)).astype(datatype)
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/external/tensorflow/tensorflow/python/ops/ |
D | special_math_ops_test.py | 647 arr = np.array(r.randn(*shape)).astype(dtype) 649 arr += 1j * np.array(r.randn(*shape)).astype(dtype) 658 a = array_ops.placeholder_with_default(r.randn(2, 3), shape=(2, 3)) 659 b = array_ops.placeholder_with_default(r.randn(3, 4), shape=(3, 4)) 793 input_np = np.array(r.randn(*actual_shape)) 815 x = r.randn(1, 2, 3) 816 y = r.randn(1, 2, 4) 817 z = r.randn(1, 3, 4) 901 ('a0->a', r.randn(5, 3)), 902 ('a->a,a', r.randn(5)), [all …]
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/external/tensorflow/tensorflow/python/kernel_tests/array_ops/ |
D | stack_op_test.py | 45 def randn(self, shape, dtype): member in StackOpTest 46 data = np.random.randn(*shape) 60 data = self.randn(shape, dtype) 74 data = self.randn(shape, np.float32) 85 data = self.randn(shape, np.float32) 103 data = self.randn(shape, dtype) 124 data = self.randn(shape, np.float32) 130 data = self.randn(shape, np.float32) 141 data = self.randn(shape, np.float32) 147 data = self.randn(shape, np.float32) [all …]
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D | unstack_op_test.py | 43 def randn(self, shape, dtype): member in UnstackOpTest 44 data = np.random.randn(*shape) 74 data = self.randn(shape, dtype) 100 data = self.randn(shape, dtype) 115 data = np.random.randn(*shape) 129 data = np.random.randn(*shape) 214 data = np.random.randn(*shape).astype(dtype)
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/external/tensorflow/tensorflow/python/kernel_tests/linalg/ |
D | linear_operator_adjoint_test.py | 122 matrix1 = np.random.randn(4, 4) 123 matrix2 = np.random.randn(4, 4) 144 matrix1 = np.random.randn(4, 4) + 1j * np.random.randn(4, 4) 145 matrix2 = np.random.randn(4, 4) + 1j * np.random.randn(4, 4) 176 matrix2 = np.random.randn(4, 4) 209 matrix2 = np.random.randn(4, 4) + 1j * np.random.randn(4, 4)
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/external/tensorflow/tensorflow/python/ops/numpy_ops/ |
D | np_random_test.py | 69 self.np_func = np.random.randn 70 self.onp_func = onp.random.randn 189 outputs = [np_random.randn(*args) for _ in range(num_samples)] 210 np_random.randn(*args).tolist() for _ in range(num_samples) 217 np_random.randn(*args).tolist() for _ in range(num_samples)
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/external/tensorflow/tensorflow/python/data/benchmarks/ |
D | from_tensor_slices_benchmark.py | 70 input_data = np.random.randn(input_size) 88 input_data = np.random.randn(input_size) 137 input_data = np.random.randn(input_size)
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/external/tensorflow/tensorflow/core/kernels/ |
D | parameterized_truncated_normal_op_gpu.cu.cc | 139 const auto randn = normal_dist(&gen); in TruncatedNormalKernel() local 142 if ((randn[i] >= normMin) && randn[i] <= normMax) { in TruncatedNormalKernel() 143 data[offset] = randn[i] * stddev + mean; in TruncatedNormalKernel()
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/external/tensorflow/tensorflow/python/lib/core/ |
D | bfloat16_test.py | 360 x = rng.randn(3, 7, 10).astype(bfloat16) 370 x = rng.randn(3, 7, 10).astype(bfloat16) 371 y = rng.randn(4, 1, 7, 10).astype(bfloat16) 383 x = rng.randn(3, 7).astype(bfloat16) 384 y = rng.randn(4, 1, 7).astype(bfloat16) 398 vals = rng.randn(*shape) 407 x = rng.randn(3, 7).astype(bfloat16) 408 y = rng.randn(4, 1, 7).astype(bfloat16) 416 x = rng.randn(3, 7).astype(bfloat16) 424 x = rng.randn(3, 7).astype(bfloat16) [all …]
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