| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | batch_matmul_op_test.py | 34 def _npBatchMatmul(self, x, y, adjoint_a, adjoint_b): argument
37 d2 = y.shape[-1] if not adjoint_b else y.shape[-2]
49 if adjoint_b:
80 def _compare(self, x_in, y_in, adjoint_a, adjoint_b, static_shape=True): argument
84 y = y_in if not adjoint_b else y_in.reshape(y_t_shape)
89 z0 = math_ops.matmul(x, y, adjoint_a=adjoint_a, adjoint_b=adjoint_b)
95 x_ph, y_ph, adjoint_a=adjoint_a, adjoint_b=adjoint_b)
97 z1 = self._npBatchMatmul(x, y, adjoint_a, adjoint_b)
107 def _testNonEmpty(self, dtype, adjoint_a, adjoint_b, use_static_shape): argument
112 self._rand(b_shape, dtype), adjoint_a, adjoint_b, use_static_shape)
[all …]
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| D | sparse_tensor_dense_matmul_op_test.py | 54 adjoint_b=False, argument
60 if adjoint_b:
73 sp_x_value, y, adjoint_a=adjoint_a, adjoint_b=adjoint_b)
78 adjoint_b=adjoint_b)
225 self._testMatmul(x, y, adjoint_a=False, adjoint_b=False)
226 self._testMatmul(x.transpose(), y, adjoint_a=True, adjoint_b=False)
227 self._testMatmul(x, y.transpose(), adjoint_a=False, adjoint_b=True)
229 x.transpose(), y.transpose(), adjoint_a=True, adjoint_b=True)
243 for adjoint_b in [True, False]:
250 y = y.transpose() if adjoint_b else y
[all …]
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| D | sparse_tensor_dense_matmul_grad_test.py | 62 def _testGradients(self, adjoint_a, adjoint_b, name, values_dtype, argument
71 dense_t = self._randomTensor([k, m], values_dtype, adjoint=adjoint_b)
74 sp_t, dense_t, adjoint_a=adjoint_a, adjoint_b=adjoint_b, name=name)
77 dense_t_shape = [m, k] if adjoint_b else [k, m]
87 for adjoint_b in [True, False]:
89 adjoint_a, adjoint_b, values_dtype.__name__, indices_dtype.__name__)
90 self._testGradients(adjoint_a, adjoint_b, name, values_dtype,
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| D | matmul_op_test.py | 250 for adjoint_b, transpose_b in trans_options:
253 transpose_a, adjoint_b, transpose_b)
261 adjoint_b=adjoint_b,
270 adjoint_b=adjoint_b,
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| /external/tensorflow/tensorflow/python/ops/ |
| D | linalg_grad.py | 43 ainv, math_ops.matmul(grad, ainv, adjoint_b=True), adjoint_a=True)
175 rdr = math_ops.matmul(r, dr, adjoint_b=True)
198 grad_a = -math_ops.matmul(c, grad_b, adjoint_b=True)
200 grad_a = -math_ops.matmul(grad_b, c, adjoint_b=True)
233 xzt = math_ops.matmul(x, z, adjoint_b=True)
235 grad_a = -math_ops.matmul(a, zx_sym) + math_ops.matmul(b, z, adjoint_b=True)
261 a2 = math_ops.matmul(tmp, a2, adjoint_b=True)
293 grad_a = -math_ops.matmul(c, grad_b, adjoint_b=True)
295 grad_a = -math_ops.matmul(grad_b, c, adjoint_b=True)
329 adjoint_b=True))
[all …]
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| D | math_grad.py | 1254 grad_x = math_ops.matmul(grad, y, adjoint_a=False, adjoint_b=True)
1255 grad_y = math_ops.matmul(x, grad, adjoint_a=True, adjoint_b=False)
1257 grad_x = math_ops.matmul(grad, y, adjoint_a=False, adjoint_b=False)
1258 grad_y = math_ops.matmul(grad, x, adjoint_a=True, adjoint_b=False)
1261 grad_x = math_ops.matmul(y, grad, adjoint_a=False, adjoint_b=True)
1262 grad_y = math_ops.matmul(x, grad, adjoint_a=False, adjoint_b=False)
1264 grad_x = math_ops.matmul(y, grad, adjoint_a=True, adjoint_b=True)
1265 grad_y = math_ops.matmul(grad, x, adjoint_a=True, adjoint_b=True)
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | sparse_tensor_dense_matmul_op_test.cc | 28 bool adjoint_b) { in SparseTensorDenseMatMulNode() argument
37 .Attr("adjoint_b", adjoint_b) in SparseTensorDenseMatMulNode()
43 bool adjoint_a, bool adjoint_b) { in SparseTensorDenseMatmul() argument
61 Tensor b(DT_FLOAT, adjoint_b ? TensorShape({n, k}) : TensorShape({k, n})); in SparseTensorDenseMatmul()
67 test::graph::Constant(g, b), adjoint_a, adjoint_b); in SparseTensorDenseMatmul()
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| D | batch_matmul_op_test.cc | 25 bool adjoint_b, DataType type) { in BatchMatmul() argument
29 Tensor in1(type, adjoint_b ? TensorShape({b, n, k}) : TensorShape({b, k, n})); in BatchMatmul()
32 test::graph::Constant(g, in1), adjoint_a, adjoint_b); in BatchMatmul()
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| /external/tensorflow/tensorflow/python/ops/linalg/ |
| D | linear_operator_util.py | 232 adjoint_b=False, argument
324 adjoint_b=adjoint_b)
335 adjoint_b=adjoint_b and still_need_to_transpose,
417 adjoint_b=False): argument
456 b_eq_sz_ = b.shape[-2 if adjoint_b or transpose_b else -1]
472 if adjoint_b:
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| D | linear_operator_full_matrix.py | 180 self._matrix, x, adjoint_a=adjoint, adjoint_b=adjoint_arg)
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| D | linear_operator_low_rank_update.py | 358 u, x, adjoint_a=True, adjoint_b=adjoint_arg)
365 v, x, adjoint_a=True, adjoint_b=adjoint_arg)
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| D | linear_operator_lower_triangular.py | 195 self._tril, x, adjoint_a=adjoint, adjoint_b=adjoint_arg)
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| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/state_space_models/ |
| D | kalman_filter.py | 209 adjoint_b=True)
243 observation_model, prior_state_var, adjoint_b=True)
282 identity_minus_factor, left_multiplied_state_var, adjoint_b=True)
333 adjoint_b=True),
338 adjoint_b=True)
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| D | test_utils.py | 82 adjoint_b=True)
91 adjoint_b=True).eval()
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| D | level_trend.py | 110 adjoint_b=True)
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| /external/tensorflow/tensorflow/python/kernel_tests/linalg/ |
| D | linear_operator_low_rank_update_test.py | 135 u, math_ops.matmul(diag_update_mat, v, adjoint_b=True))
139 matrix = base_diag_mat + math_ops.matmul(u, v, adjoint_b=True)
144 u, math_ops.matmul(diag_update_mat, u, adjoint_b=True))
148 matrix = base_diag_mat + math_ops.matmul(u, u, adjoint_b=True)
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| /external/tensorflow/tensorflow/contrib/solvers/python/kernel_tests/ |
| D | lanczos_test.py | 64 ub = lanczos.bidiag_matmul(lbd.u, lbd.alpha, lbd.beta, adjoint_b=False)
66 vbt = lanczos.bidiag_matmul(lbd.v, lbd.alpha, lbd.beta, adjoint_b=True)
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| /external/tensorflow/tensorflow/contrib/image/python/ops/ |
| D | interpolate_spline.py | 48 x_y_transpose = math_ops.matmul(x, y, adjoint_b=True)
69 x_x_transpose = math_ops.matmul(x, x, adjoint_b=True)
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| /external/tensorflow/tensorflow/contrib/solvers/python/ops/ |
| D | lanczos.py | 200 def bidiag_matmul(matrix, alpha, beta, adjoint_b=False, name="bidiag_matmul"): argument
227 if adjoint_b is False:
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| /external/tensorflow/tensorflow/core/ops/ |
| D | sparse_ops_test.cc | 186 auto set_adjoints = [&op](bool adjoint_a, bool adjoint_b) { in TEST() argument
193 .Attr("adjoint_b", adjoint_b) in TEST()
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| D | sparse_ops.cc | 107 bool adjoint_b; in __anona7ffb82a0402() local
109 TF_RETURN_IF_ERROR(c->GetAttr("adjoint_b", &adjoint_b)); in __anona7ffb82a0402()
111 DimensionHandle output_right = c->Dim(b, adjoint_b ? 0 : 1); in __anona7ffb82a0402()
114 DimensionHandle inner_right = c->Dim(b, adjoint_b ? 1 : 0); in __anona7ffb82a0402()
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.sparse.pbtxt | 45 …argspec: "args=[\'sp_a\', \'b\', \'adjoint_a\', \'adjoint_b\', \'name\'], varargs=None, keywords=N…
117 …argspec: "args=[\'sp_a\', \'b\', \'adjoint_a\', \'adjoint_b\', \'name\'], varargs=None, keywords=N…
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_SparseTensorDenseMatMul.pbtxt | 35 name: "adjoint_b"
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| /external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/ |
| D | cholesky_outer_product.py | 104 return math_ops.matmul(x, x, adjoint_b=True)
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| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| D | factorization_ops_test_utils.py | 131 gathered_row_factors, gathered_col_factors, adjoint_b=True))
|