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Results 11 - 20 of 163 for matmult (0.19 sec)
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tensorflow/compiler/mlir/tensorflow/transforms/fused_kernel_matcher.cc
if ((matmul->hasAttr("grad_a") && mlir::cast<BoolAttr>(matmul->getAttr("grad_a")).getValue()) || (matmul->hasAttr("grad_b") && mlir::cast<BoolAttr>(matmul->getAttr("grad_b")).getValue())) { (void)rewriter.notifyMatchFailure(matmul, [&](Diagnostic &diag) { diag << "FusedMatMul kernel does not support grad_a/grad_b attrs"; }); return false; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 14.9K bytes - Viewed (0) -
tensorflow/cc/framework/gradients_test.cc
auto dv = Const(scope, {{1.0, 1.0}, {1.0, 1.0}}); auto dt = MatMul(scope, dv, u, MatMul::TransposeB(true)); auto du = MatMul(scope, t, dv, MatMul::TransposeA(true)); auto dz = Const(scope, {{1.0, 1.0}, {1.0, 1.0}}); auto dx = MatMul(scope, dz, y, MatMul::TransposeB(true)); auto dy = MatMul(scope, x, dz, MatMul::TransposeA(true)); } else { // Call AddSymbolicGradients.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 15 15:13:38 UTC 2023 - 25K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/matmul.mlir
Christian Sigg <******@****.***> 1714640622 -0700
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 1.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/include_variables_in_init_v1.py
# CHECK-NEXT: %[[READ_VAR_0:.*]] = "tf.ReadVariableOp"(%[[ARG_2]]) {{{.*}}} : (tensor<!tf_type.resource<tensor<1x3xf32>>>) -> tensor<1x3xf32> # CHECK-NEXT: %[[MATMUL_0:.*]] = "tf.MatMul"(%[[ARG_1]], %[[READ_VAR_0]]) <{{{.*}}}> {{{.*}}} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32> # CHECK-NEXT: return %[[MATMUL_0]] : tensor<3x3xf32> def Test(): x = tf.constant([[1.0], [1.0], [1.0]]) y = tf.compat.v1.get_variable( name='y',
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 31 08:49:35 UTC 2023 - 3.7K bytes - Viewed (0) -
tensorflow/c/eager/c_api_remote_test_util.cc
TFE_OpAddInput(matmul, h0_task0, status); ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status); TFE_OpAddInput(matmul, has_packed_input ? packed_handle : h1_task2, status); ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status); } else { // Handles are on task0 (local), and task2, but op is on task1. matmul = MatMulOp(ctx, h0_task0, h1_task2); } if (remote) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Dec 11 22:56:03 UTC 2020 - 9.1K bytes - Viewed (0) -
tensorflow/c/eager/c_api_remote_test.cc
ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); TFE_Op* matmul = MatMulOp(ctx, h0_task1, h1_task1); TFE_OpSetDevice(matmul, remote_device_name, status); EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); TFE_TensorHandle* retvals[1]; int num_retvals = 1; TFE_Execute(matmul, &retvals[0], &num_retvals, status); EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Aug 12 00:14:22 UTC 2020 - 5.4K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_activity_listener_test.cc
"/job:localhost/replica:0/task:0/device:CPU:0"); Output a = ops::Placeholder(root.WithOpName("A"), DT_FLOAT); for (int i = 0; i < 5; i++) { a = ops::MatMul(root.WithOpName(absl::StrCat("matmul_", i)), a, a); a = ops::Add(root.WithOpName(absl::StrCat("add_", i)), a, a); } GraphDef graph_def; root.graph()->ToGraphDef(&graph_def); return graph_def; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 08:47:20 UTC 2024 - 5.9K bytes - Viewed (0) -
tensorflow/c/c_api_test.cc
"gradients/MatMul", false, true); TF_Operation* matmul2 = MatMul(expected_graph_, s_, const0, const3, "gradients/MatMul_1", true, false); expected_grad_outputs[0] = {matmul1, 0}; expected_grad_outputs[1] = {matmul2, 0}; } TF_Tensor* FloatTensor2x2(const float* values) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 15 03:35:10 UTC 2024 - 96.9K bytes - Viewed (0) -
tensorflow/compiler/aot/tests/tfcompile_test.cc
matmul.arg0(1, 0) = 4; matmul.arg0(1, 1) = 5; matmul.arg0(1, 2) = 6; matmul.arg1(0, 0) = 7; matmul.arg1(0, 1) = 8; matmul.arg1(1, 0) = 9; matmul.arg1(1, 1) = 10; matmul.arg1(2, 0) = 11; matmul.arg1(2, 1) = 12; EXPECT_TRUE(matmul.Run()); EXPECT_EQ(matmul.error_msg(), ""); const float results[4] = {58, 64, 139, 154}; for (int i = 0; i < 4; ++i) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Sep 06 19:12:29 UTC 2023 - 26.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/device_copy.mlir
func.func @fold_identity_n_test(%arg0: tensor<2x2xf32>, %arg1: tensor<2x2xf32>) -> (tensor<2x2xf32>, tensor<2x2xf32>) { // CHECK: tf.MatMul %outputs = "tf.MatMul"(%arg0, %arg1) {device = "TPU", transpose_a = false, transpose_b = false} : (tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32> %outputs_0 = "tf.MatMul"(%arg0, %arg1) {device = "TPU", transpose_a = false, transpose_b = false} : (tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 28 12:06:33 UTC 2022 - 5.2K bytes - Viewed (0)