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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/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/quantization/tensorflow/passes/prepare_lifting.cc
} return ConstantFoldOpIfPossible(value.getDefiningOp()).front(); } // Matches convolution op with "NHWC" data format or matmul op with false adj_y. // The list of supported ops in this function is: // - Conv2DOp // - Conv3DOp // - DepthwiseConv2dNativeOp // - MatMulOp // - BatchMatMulV2Op LogicalResult MatchSupportedAffineOp(Operation* op, Value& binding_output,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 13.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/fold_broadcast.cc
} const int x_row = matmul_op.getAdjX() ? shape_x.back() : *(shape_x.rbegin() + 1); const int x_col = !matmul_op.getAdjX() ? shape_x.back() : *(shape_x.rbegin() + 1); const int y_row = matmul_op.getAdjY() ? shape_y.back() : *(shape_y.rbegin() + 1); const int y_col = !matmul_op.getAdjY() ? shape_y.back() : *(shape_y.rbegin() + 1);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 7.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/replace_cast_hacks_with_tf_xla_ops.td
(IsInt8ElementType $weight), (IsConstTensor $weight), (IsInt32ElementType $matmul), (HasStaticShapeConstraint $weight)], [], (addBenefit 10)>; // Convert Matmul with hybrid inputs (f32 activation/int8 weight) to XlaDotV2 def ConvertTFMatMulToXLADotV2OpWeightOnly : Pat< (TF_MatMulOp:$matmul $input, (TF_MulOp (TF_CastOp (TF_IdentityOp $weight), $truncate1), $scale),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Dec 10 05:52:02 UTC 2023 - 21.1K bytes - Viewed (0) -
tensorflow/c/eager/c_api_distributed_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: Thu Feb 15 09:49:45 UTC 2024 - 23.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/unroll_batch_matmul_disabled.pbtxt
# RUN: tf_tfl_translate -unfold_batchmatmul=false -tf-input-arrays=Placeholder,Placeholder_1 -tf-input-shapes=2,5,3:3,7 -tf-input-data-types=DT_FLOAT,DT_FLOAT -tf-output-arrays=MatMul -output-mlir %s -o - 2>&1 | FileCheck %s node { name: "Placeholder" op: "Placeholder" attr { key: "dtype" value { type: DT_FLOAT } } attr { key: "shape" value { shape { dim { size: 2
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 1.5K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/math_grad.cc
std::string name_grad_B = "MatMul_Grad_B"; if (!t_a && !t_b) { TF_RETURN_IF_ERROR(MatMul(ctx, upstream_grad, B.get(), &matmul_A_output, /*transpose_a = */ false, /*transpose_b = */ true, name_grad_A.c_str())); TF_RETURN_IF_ERROR(MatMul(ctx, A.get(), upstream_grad, &matmul_B_output, /*transpose_a = */ true,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 28 13:53:47 UTC 2024 - 15.2K bytes - Viewed (0)