| /external/tensorflow/tensorflow/python/ops/ |
| D | matmul_benchmark.py | 31 def build_graph(device, n, m, k, transpose_a, transpose_b, dtype): argument
47 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, argument
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(' ', ''),
114 def run_test_gpu(self, n, m, k, transpose_a, transpose_b, dtype, num_iters): argument
115 self.run_graph(test.gpu_device_name(), n, m, k, transpose_a, transpose_b,
121 for n, m, (transpose_a, transpose_b) in itertools.product(
[all …]
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| /external/tensorflow/tensorflow/python/kernel_tests/linalg/sparse/ |
| D | csr_sparse_matrix_test.py | 147 def _testSparseSparse(self, transpose_a, transpose_b, adjoint_a, adjoint_b): argument
151 dense_shape_a = [5, 13, 7] if transpose_a or adjoint_a else [5, 7, 13]
164 transpose_a=transpose_a,
171 transpose_a=transpose_a,
187 def _testSparseDense(self, transpose_a, transpose_b, adjoint_a, adjoint_b): argument
192 dense_shape_a = [5, 13, 7] if transpose_a or adjoint_a else [5, 7, 13]
204 transpose_a=transpose_a,
211 transpose_a=transpose_a,
225 def _testDenseSparse(self, transpose_a, transpose_b, adjoint_a, adjoint_b): argument
230 dense_shape_a = [5, 13, 7] if transpose_a or adjoint_a else [5, 7, 13]
[all …]
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| D | csr_sparse_matrix_sparse_mat_mul_grad_test.py | 58 def _testLargeBatchSparseMatrixSparseMatMulGrad(self, datatype, transpose_a, argument
68 if transpose_a or adjoint_a:
85 transpose_a=transpose_a,
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| D | csr_sparse_matrix_dense_mat_mul_grad_test.py | 53 transpose_a, argument
74 if transpose_a or adjoint_a:
92 transpose_a=transpose_a,
|
| /external/tensorflow/tensorflow/python/ops/linalg/sparse/ |
| D | sparse_csr_matrix_grad.py | 135 transpose_a=False, argument
163 transpose_a = transpose_a or adjoint_a
170 dense_shape = (a.shape[-1] if transpose_a else a.shape[-2],
184 a_rows = gather_op(transpose(a) if transpose_a else a, indices=rows)
246 grad_a = matmul(b, grad, transpose_a=t_b, transpose_b=True)
247 grad_b = sparse_matmul(a, grad, transpose_a=not t_a, transpose_output=t_b)
260 grad_a = matmul(b, grad, transpose_a=True, adjoint_b=True)
263 grad_a = matmul(b, grad, transpose_a=True, transpose_b=True)
272 grad_a = matmul(grad, b, transpose_a=True, transpose_b=not t_b)
274 grad_a = matmul(b, grad, transpose_a=t_b)
[all …]
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| D | sparse_csr_matrix_ops.py | 115 def matmul_shape_inference(a, b, c, transpose_a, transpose_b, adjoint_a, argument
124 transpose_a = transpose_a or adjoint_a
132 c_rows = a_shape.dim[rank - (1 if transpose_a else 2)].size
143 transpose_a=False, argument
179 transpose_a=transpose_a,
196 transpose_a=transpose_a,
205 c_handle = matmul_shape_inference(a_matrix, b_matrix, c, transpose_a,
213 transpose_a=transpose_a,
223 transpose_a=not transpose_b,
224 transpose_b=not transpose_a,
[all …]
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| /external/tensorflow/tensorflow/compiler/xla/service/gpu/ |
| D | triangular_solve_thunk.cc | 60 switch (options.transpose_a()) { in TriangularSolveThunk()
69 << options.transpose_a(); in TriangularSolveThunk()
90 se::blas::Transpose transpose_a, PrimitiveType type, in RunTriangulatSolve() argument
111 ->ThenBlasTrsm(side, uplo, transpose_a, unit_diagonal, m, n, in RunTriangulatSolve()
121 ->ThenBlasTrsm(side, uplo, transpose_a, unit_diagonal, m, n, in RunTriangulatSolve()
131 ->ThenBlasTrsm(side, uplo, transpose_a, unit_diagonal, m, n, in RunTriangulatSolve()
142 ->ThenBlasTrsm(side, uplo, transpose_a, unit_diagonal, m, n, in RunTriangulatSolve()
174 ->ThenBlasTrsmBatched(side, uplo, transpose_a, unit_diagonal, m, in RunTriangulatSolve()
185 ->ThenBlasTrsmBatched(side, uplo, transpose_a, unit_diagonal, m, in RunTriangulatSolve()
196 side, uplo, transpose_a, unit_diagonal, m, n, in RunTriangulatSolve()
[all …]
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| /external/tensorflow/tensorflow/compiler/xla/service/ |
| D | triangular_solve_expander.cc | 130 bool transpose_a, bool conjugate_a, in SolveWithInvertedDiagonalBlocks() argument
161 bool backward = left_side ^ lower ^ transpose_a; in SolveWithInvertedDiagonalBlocks()
199 if (!left_side ^ transpose_a) { in SolveWithInvertedDiagonalBlocks()
206 remainder = b_row - BatchDot(a_row, transpose_a, x, false, precision); in SolveWithInvertedDiagonalBlocks()
208 remainder = b_row - BatchDot(x, false, a_row, transpose_a, precision); in SolveWithInvertedDiagonalBlocks()
215 BatchDot(inv_block, transpose_a, remainder, false, precision); in SolveWithInvertedDiagonalBlocks()
218 BatchDot(remainder, false, inv_block, transpose_a, precision); in SolveWithInvertedDiagonalBlocks()
366 XlaOp a, XlaOp b, bool left_side, bool lower, bool transpose_a, in SolveByInvertingDiagonalBlocks() argument
397 lower, transpose_a, conjugate_a, in SolveByInvertingDiagonalBlocks()
410 XlaOp a, XlaOp b, bool left_side, bool lower, bool transpose_a, in SolveDirectly() argument
[all …]
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| D | triangular_solve_expander.h | 45 bool lower, bool transpose_a,
56 bool transpose_a, bool conjugate_a, bool unit_diagonal,
60 bool transpose_a, bool conjugate_a,
|
| /external/tensorflow/tensorflow/compiler/mlir/tensorflow/tests/ |
| D | unroll-batch-matmul.mlir | 35 …// CHECK: %[[MATMUL_1:.*]] = "tf.MatMul"(%[[LHS_1]], %[[RHS_1]]) {transpose_a = false, transpose_b…
36 …// CHECK: %[[MATMUL_2:.*]] = "tf.MatMul"(%[[LHS_2]], %[[RHS_2]]) {transpose_a = false, transpose_b…
37 …// CHECK: %[[MATMUL_3:.*]] = "tf.MatMul"(%[[LHS_3]], %[[RHS_3]]) {transpose_a = false, transpose_b…
38 …// CHECK: %[[MATMUL_4:.*]] = "tf.MatMul"(%[[LHS_4]], %[[RHS_4]]) {transpose_a = false, transpose_b…
39 …// CHECK: %[[MATMUL_5:.*]] = "tf.MatMul"(%[[LHS_5]], %[[RHS_5]]) {transpose_a = false, transpose_b…
40 …// CHECK: %[[MATMUL_6:.*]] = "tf.MatMul"(%[[LHS_6]], %[[RHS_6]]) {transpose_a = false, transpose_b…
79 …// CHECK: %[[MATMUL_1:.*]] = "tf.MatMul"(%[[LHS_1]], %[[RHS_1]]) {transpose_a = true, transpose_b …
80 …// CHECK: %[[MATMUL_2:.*]] = "tf.MatMul"(%[[LHS_2]], %[[RHS_2]]) {transpose_a = true, transpose_b …
81 …// CHECK: %[[MATMUL_3:.*]] = "tf.MatMul"(%[[LHS_3]], %[[RHS_3]]) {transpose_a = true, transpose_b …
82 …// CHECK: %[[MATMUL_4:.*]] = "tf.MatMul"(%[[LHS_4]], %[[RHS_4]]) {transpose_a = true, transpose_b …
[all …]
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| D | device_copy.mlir | 6 …%outputs = "tf.MatMul"(%arg0, %arg1) {device = "/device:CPU:0", transpose_a = false, transpose_b =…
15 …%outputs = "tf.MatMul"(%arg0, %arg1) {device = "", transpose_a = false, transpose_b = false} : (te…
24 …%outputs = "tf.MatMul"(%arg0, %arg1) {device = "/device:GPU:0", transpose_a = false, transpose_b =…
33 …%outputs = "tf.MatMul"(%arg0, %arg1) {device = "/device:GPU:0", transpose_a = false, transpose_b =…
42 …%outputs = "tf.MatMul"(%arg0, %arg1) {device = "", transpose_a = false, transpose_b = false} : (te…
51 …%outputs = "tf.MatMul"(%arg0, %arg1) {device = "TPU", transpose_a = false, transpose_b = false} : …
52 …%outputs_0 = "tf.MatMul"(%arg0, %arg1) {device = "TPU", transpose_a = false, transpose_b = false} …
61 …%outputs = "tf.MatMul"(%arg0, %arg1) {device = "TPU", transpose_a = false, transpose_b = false} : …
62 …%outputs_0 = "tf.MatMul"(%arg0, %arg1) {device = "TPU", transpose_a = false, transpose_b = false} …
|
| /external/tensorflow/tensorflow/core/kernels/ |
| D | quantized_matmul_op_test.cc | 90 const bool transpose_a = true; in TEST_F() local
104 .Attr("transpose_a", transpose_a) in TEST_F()
140 const bool transpose_a = true; in TEST_F() local
154 .Attr("transpose_a", transpose_a) in TEST_F()
179 const bool transpose_a = true; in TEST_F() local
193 .Attr("transpose_a", transpose_a) in TEST_F()
218 const bool transpose_a = true; in TEST_F() local
232 .Attr("transpose_a", transpose_a) in TEST_F()
311 const bool transpose_a = true; in TEST_F() local
321 .Attr("transpose_a", transpose_a) in TEST_F()
|
| D | matmul_op_test.cc | 101 const Tensor& bias_data, bool transpose_a, in RunMatMulWithBias() argument
110 ops::MatMul::Attrs().TransposeA(transpose_a).TransposeB(transpose_b)); in RunMatMulWithBias()
121 bool transpose_a, bool transpose_b, const string& activation_type, in RunMatMulWithBiasAndActivation() argument
129 ops::MatMul::Attrs().TransposeA(transpose_a).TransposeB(transpose_b)); in RunMatMulWithBiasAndActivation()
152 const std::vector<string>& fused_ops, bool transpose_a, in RunFusedMatMulOp() argument
180 .Attr("transpose_a", transpose_a) in RunFusedMatMulOp()
221 void VerifyMatMulWithBias(int m, int k, int n, bool transpose_a, in VerifyMatMulWithBias() argument
226 RunMatMulWithBias(input_data, filter_data, bias_data, transpose_a, in VerifyMatMulWithBias()
234 transpose_a, transpose_b, out, in VerifyMatMulWithBias()
243 void VerifyConv2DWithBiasAndActivation(int m, int k, int n, bool transpose_a, in VerifyConv2DWithBiasAndActivation() argument
[all …]
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| /external/tensorflow/tensorflow/compiler/mlir/quantization/tensorflow/passes/ |
| D | lift_quantizable_spots_as_functions.td | 65 (TF_MatMulOp:$res $a, $b, $transpose_a, $transpose_b),
70 (NamedAttr<"transpose_a"> $transpose_a),
111 (TF_MatMulOp $a, $b, $transpose_a, $transpose_b),
117 (NamedAttr<"transpose_a"> $transpose_a),
190 (TF_MatMulOp $a, $b, $transpose_a, $transpose_b)),
195 (NamedAttr<"transpose_a"> $transpose_a),
202 (TF_MatMulOp $a, $b, $transpose_a, $transpose_b),
208 (NamedAttr<"transpose_a"> $transpose_a),
|
| D | lift_quantizable_spots_as_functions_drq.td | 28 (TF_MatMulOp:$res $a, $b, $transpose_a, $transpose_b),
33 (NamedAttr<"transpose_a"> $transpose_a),
|
| /external/tensorflow/tensorflow/compiler/mlir/quantization/tensorflow/tests/ |
| D | prepare_quantize_drq.mlir | 26 …%0 = "tf.MatMul"(%arg0, %arg1) {attr_map = "0:transpose_a,1:transpose_a", device = "", transpose_a…
38 …CK: %0 = "tf.MatMul"(%arg0, %arg1) {attr_map = "0:transpose_a,1:transpose_a", device = "", transpo…
|
| /external/gemmlowp/eight_bit_int_gemm/ |
| D | eight_bit_int_gemm.cc | 68 template <bool transpose_a, bool transpose_b, bool transpose_c>
84 transpose_a ? MapOrder::RowMajor : MapOrder::ColMajor; in EightBitIntGemmImpl()
107 template <bool transpose_a, bool transpose_b, bool transpose_c>
119 transpose_a ? MapOrder::RowMajor : MapOrder::ColMajor; in EightBitIntGemmInt32Impl()
217 bool CanHandleMetaFastpath(bool transpose_a, bool transpose_b, bool transpose_c, in CanHandleMetaFastpath() argument
226 if (!IsRowMajorOrVector(transpose_a, lda, m, k)) { in CanHandleMetaFastpath()
301 void EightBitIntGemm(bool transpose_a, bool transpose_b, bool transpose_c, in EightBitIntGemm() argument
311 if (CanHandleMetaFastpath(transpose_a, transpose_b, transpose_c, m, n, k, lda, in EightBitIntGemm()
320 if (transpose_a == ta && transpose_b == tb && transpose_c == tc) { \ in EightBitIntGemm()
338 void EightBitIntGemm(bool transpose_a, bool transpose_b, bool transpose_c, in EightBitIntGemm() argument
[all …]
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| /external/tensorflow/tensorflow/compiler/mlir/tfrt/tests/jit/ |
| D | fission.mlir | 7 // CHECK-SAME: {transpose_a = false, transpose_b = false}
13 transpose_a = false,
24 // CHECK-SAME: {transpose_a = false, transpose_b = false}
31 transpose_a = false,
|
| /external/tensorflow/tensorflow/core/ops/ |
| D | sparse_csr_matrix_ops.cc | 245 bool transpose_a = false; in __anon6adce4610702() local
250 TF_RETURN_IF_ERROR(c->GetAttr("transpose_a", &transpose_a)); in __anon6adce4610702()
258 if (adjoint_a && transpose_a) { in __anon6adce4610702()
266 transpose_a = transpose_a || adjoint_a; in __anon6adce4610702()
269 auto output_rows = c->Dim(a_shape, transpose_a ? -1 : -2); in __anon6adce4610702()
286 TF_RETURN_IF_ERROR(c->Merge(c->Dim(a_shape, transpose_a ? -2 : -1), in __anon6adce4610702()
408 bool transpose_a = false; in __anon6adce4610a02() local
410 TF_RETURN_IF_ERROR(c->GetAttr("transpose_a", &transpose_a)); in __anon6adce4610a02()
416 if (adjoint_a && transpose_a) { in __anon6adce4610a02()
423 transpose_a = transpose_a || adjoint_a; in __anon6adce4610a02()
[all …]
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| /external/tensorflow/tensorflow/core/ops/compat/ops_history_v2/ |
| D | MatMul.pbtxt | 16 name: "transpose_a"
59 name: "transpose_a"
103 name: "transpose_a"
147 name: "transpose_a"
|
| /external/tensorflow/tensorflow/core/ops/compat/ops_history_v1/ |
| D | MatMul.pbtxt | 16 name: "transpose_a"
59 name: "transpose_a"
103 name: "transpose_a"
147 name: "transpose_a"
|
| /external/tensorflow/tensorflow/python/util/ |
| D | function_parameter_canonicalizer_test.py | 45 2, 3, transpose_a=True, name='my_matmul'),
62 transpose_a=True, transpose_b=True, adjoint_a=True)
82 self._matmul_func.canonicalize(2, 3, False, transpose_a=True)
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| /external/tensorflow/tensorflow/python/kernel_tests/math_ops/ |
| D | matmul_op_test.py | 198 math_ops.matmul(a, b, transpose_a=True)
286 for adjoint_a, transpose_a in trans_options:
290 transpose_a, adjoint_b, transpose_b)
297 transpose_a=transpose_a,
306 transpose_a=transpose_a,
|
| /external/tensorflow/tensorflow/core/graph/ |
| D | mkl_testlib.cc | 26 Node* oneDNNMatmul(Graph* g, Node* in0, Node* in1, bool transpose_a, in oneDNNMatmul() argument
32 .Attr("transpose_a", transpose_a) in oneDNNMatmul()
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| /external/tensorflow/tensorflow/security/advisory/ |
| D | tfsa-2022-107.md | 17 transpose_a = False
26 …a=min_a, max_a=max_a, min_b=min_b, max_b=max_b, Toutput=Toutput, transpose_a=transpose_a, transpos…
|