| /external/tensorflow/tensorflow/compiler/tf2xla/lib/ |
| triangular_solve.h | 31 // depending on the value of the value of (left_side, transpose_a, conjugate_a)
53 // `transpose_a` is a boolean indicating whether the matrix `a` is transposed.
56 // transpose_a and conjugate_a are true the effect is a Hermitian adjoint.
62 xla::ComputationDataHandle b, bool left_side, bool lower, bool transpose_a,
67 const xla::ComputationDataHandle& b, bool transpose_a, bool conjugate_a);
|
| triangular_solve.cc | 34 xla::ComputationDataHandle b, bool left_side, bool lower, bool transpose_a,
136 b_param, transpose_a,
141 left_side, lower, transpose_a,
164 if (!left_side && lower == transpose_a) {
188 // a_slice_2 = T(a_slice_2) if transpose_a else a_slice_2
203 /*transpose_y=*/transpose_a,
214 } else if (left_side && lower != transpose_a) {
238 // a_slice_2 = T(a_slice_2) if transpose_a else a_slice_2
251 /*transpose_x=*/transpose_a,
262 } else if (!left_side && lower != transpose_a) {
[all...] |
| /external/tensorflow/tensorflow/python/ops/ |
| matmul_benchmark.py | 35 def build_graph(device, n, m, k, transpose_a, transpose_b, dtype):
43 transpose_a: boolean value to show if tensor A is transposed.
51 if not transpose_a:
60 z = math_ops.matmul(x, y, transpose_a=transpose_a, transpose_b=transpose_b)
67 def run_graph(self, device, n, m, k, transpose_a, transpose_b, num_iters,
76 transpose_a: boolean value to show if tensor A is transposed.
86 output = build_graph(device, n, m, k, transpose_a, transpose_b, dtype)
99 ',ta:' + str(transpose_a) + '.tb:' + str(transpose_b), num_iters,
109 str(transpose_a) + ',tb:' + str(transpose_b)).replace(' ', '')
[all...] |
| matmul_benchmark_test.py | 32 def BuildGraphTest(n, m, k, transpose_a, transpose_b, dtype):
37 (n, m, k, transpose_a, transpose_b))
40 (n, m, k, transpose_a, transpose_b))
41 self._VerifyBuildGraph(n, m, k, transpose_a, transpose_b, dtype)
46 def RunGraphTest(n, m, k, transpose_a, transpose_b, dtype):
51 (n, m, k, transpose_a, transpose_b))
54 (n, m, k, transpose_a, transpose_b))
55 self._VerifyRunGraph(n, m, k, transpose_a, transpose_b, dtype)
71 def _VerifyBuildGraph(self, n, m, k, transpose_a, transpose_b, dtype):
75 transpose_a, transpose_b, dtype
[all...] |
| math_grad.py | [all...] |
| /external/gemmlowp/eight_bit_int_gemm/ |
| eight_bit_int_gemm.h | 55 void EightBitIntGemm(bool transpose_a, bool transpose_b, bool transpose_c,
62 void EightBitIntGemm(bool transpose_a, bool transpose_b, bool transpose_c,
|
| eight_bit_int_gemm.cc | 71 template <bool transpose_a, bool transpose_b, bool transpose_c>
87 transpose_a ? MapOrder::RowMajor : MapOrder::ColMajor;
110 template <bool transpose_a, bool transpose_b, bool transpose_c>
122 transpose_a ? MapOrder::RowMajor : MapOrder::ColMajor;
220 bool CanHandleMetaFastpath(bool transpose_a, bool transpose_b, bool transpose_c,
229 if (!IsRowMajorOrVector(transpose_a, lda, m, k)) {
304 void EightBitIntGemm(bool transpose_a, bool transpose_b, bool transpose_c,
314 if (CanHandleMetaFastpath(transpose_a, transpose_b, transpose_c, m, n, k, lda,
323 if (transpose_a == ta && transpose_b == tb && transpose_c == tc) { \
341 void EightBitIntGemm(bool transpose_a, bool transpose_b, bool transpose_c
[all...] |
| /external/tensorflow/tensorflow/core/kernels/ |
| quantized_matmul_op_test.cc | 90 const bool transpose_a = true; local
104 .Attr("transpose_a", transpose_a)
113 // We have set the transpose_a flag to true, so the matrix is transposed, and
140 const bool transpose_a = true; local
154 .Attr("transpose_a", transpose_a)
180 const bool transpose_a = true; local
194 .Attr("transpose_a", transpose_a)
273 const bool transpose_a = true; local
[all...] |
| matmul_op_test.cc | 24 static Graph* Matmul(int m, int k, int n, bool transpose_a, bool transpose_b,
27 Tensor in0(type, transpose_a ? TensorShape({k, m}) : TensorShape({m, k}));
32 test::graph::Constant(g, in1), transpose_a, transpose_b);
|
| reference_gemm.h | 34 void ReferenceGemm(bool transpose_a, bool transpose_b, bool transpose_c,
40 if (transpose_a) {
|
| matmul_op.cc | 274 bool transpose_a = dim_pair[0].first == 0; local
276 auto blas_transpose_a = trans[transpose_a];
294 transpose_a, transpose_b, m, n, k, dtype, device_id,
317 transpose_b ? k : n, a_ptr, transpose_a ? m : k, beta,
335 transpose_b ? k : n, a_ptr, transpose_a ? m : k, 0.0,
348 LaunchBlasGemv<T>::Compute(ctx, stream, !transpose_a,
349 transpose_a ? m : k, transpose_a ? k : m,
376 transpose_b ? k : n, a_ptr, transpose_a ? m : k, beta,
409 LaunchBlasGemv<T>::Compute(ctx, stream, !transpose_a,
[all...] |
| meta_support.h | 66 // If transpose_a is false the lhs operand has row major layout, otherwise
70 void QuantizedGemm(OpKernelContext* context, bool transpose_a, bool transpose_b,
|
| mkl_matmul_op.cc | 42 OP_REQUIRES_OK(ctx, ctx->GetAttr("transpose_a", &transpose_a_));
89 bool transpose_a = dim_pair[0].first == 0; variable
96 MklBlasGemm(transpose_a, transpose_b, m, n, k, a_ptr, transpose_a ? m : k,
|
| sparse_matmul_op_test.cc | 51 Node* SparseMatMulNode(Graph* g, Node* in0, Node* in1, bool transpose_a,
57 .Attr("transpose_a", transpose_a)
68 bool transpose_a, bool transpose_b) {
72 auto left_shape = transpose_a ? TensorShape({d, m}) : TensorShape({m, d});
83 test::graph::Constant(g, right), transpose_a, transpose_b,
90 float sparsity_b, bool transpose_a,
94 transpose_a, transpose_b);
|
| quantized_conv_ops.cc | 376 const bool transpose_a = false; local
391 meta::QuantizedGemm(context, transpose_a, transpose_b, im2col_buffer,
413 !transpose_a ? gemmlowp::MapOrder::RowMajor
440 transpose_a, transpose_b, transpose_c, m, n, k, im2col_buffer,
|
| /external/tensorflow/tensorflow/contrib/factorization/python/kernel_tests/ |
| masked_matmul_benchmark.py | 63 transpose_a=False, transpose_b=False):
73 transpose_a: boolean, whether to transpose the a matrix.
83 a_shape = a_shape if not transpose_a else [a_shape[1], a_shape[0]]
92 a_ph, b_ph, mask_indices_ph, transpose_a, transpose_b)
116 tr_a=int(transpose_a),
133 for transpose_a in [False, True]:
139 self._run_graph(a_shape, b_shape, nnz, num_iters, sort, transpose_a,
|
| masked_matmul_ops_test.py | 60 def _runTestMaskedProduct(self, transpose_a, transpose_b):
62 a = self._a if not transpose_a else array_ops.transpose(self._a)
73 a, b, self._mask_ind, transpose_a, transpose_b)
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| matmul_op_test.py | 152 math_ops.matmul(a, b, transpose_a=True)
236 for adjoint_a, transpose_a in trans_options:
240 transpose_a, adjoint_b, transpose_b)
247 transpose_a=transpose_a,
256 transpose_a=transpose_a,
|
| sparse_matmul_op_test.py | 57 transpose_a=tr_a,
147 transpose_a=tr_a,
|
| /external/tensorflow/tensorflow/python/tools/ |
| print_selective_registration_header_test.py | 47 attr: { key: "transpose_a" value: { b: false } }
56 attr: { key: "transpose_a" value: { b: false } }
|
| /external/tensorflow/tensorflow/contrib/factorization/kernels/ |
| masked_matmul_ops.cc | 74 const Tensor& transpose_a = context->input(3); variable
83 OP_REQUIRES(context, TensorShapeUtils::IsScalar(transpose_a.shape()),
84 InvalidArgument("Input transpose_a should be a scalar."));
88 const bool adj_a = transpose_a.scalar<bool>()();
|
| /external/tensorflow/tensorflow/python/ops/linalg/ |
| linear_operator_util.py | 200 transpose_a=False,
251 transpose_a: If `True`, `a` is transposed before multiplication.
276 ValueError: If transpose_a and adjoint_a, or transpose_b and adjoint_b
284 transpose_a=transpose_a,
|
| /external/tensorflow/tensorflow/contrib/rnn/python/ops/ |
| gru_ops.py | 90 d_w_ru = math_ops.matmul(x_h_prev, d_r_bar_u_bar, transpose_a=True)
94 d_w_c = math_ops.matmul(x_h_prevr, d_c_bar, transpose_a=True)
|
| /external/tensorflow/tensorflow/core/grappler/costs/ |
| op_level_cost_estimator.cc | 559 bool transpose_a = false; local
567 if (item.first == "transpose_a" && item.second.b() == true)
568 transpose_a = true;
572 VLOG(1) << "transpose_a:" << transpose_a;
578 if (transpose_a) {
683 AttrValue transpose_a; local
684 transpose_a.set_b(false);
686 transpose_a.set_b(op_features.attr().at("adj_x").b());
688 (*matmul_op_features.mutable_attr())["transpose_a"] = transpose_a
[all...] |
| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| gmm_ops.py | 62 cov = math_ops.matmul(x, x, transpose_a=True) / (num_points - 1)
382 self._w[shard_id], array_ops.squeeze(shard, [0]), transpose_a=True),
428 square_mean = math_ops.matmul(mean, mean, transpose_a=True)
|
