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Results 101 - 110 of 156 for mat_mul (0.15 sec)
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tensorflow/cc/gradients/math_grad.cc
std::vector<Output>* grad_outputs) { if (is_batch == false) { auto dx = MatMul(scope, x0, x1, MatMul::TransposeA(adj_x0).TransposeB(adj_x1)); grad_outputs->push_back(dx); auto dy = MatMul(scope, y0, y1, MatMul::TransposeA(adj_y0).TransposeB(adj_y1)); grad_outputs->push_back(dy); } else { auto dx = BatchMatMulV3(scope, x0, x1, x_data_type,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Aug 25 18:20:20 UTC 2023 - 50.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantized_function_library.mlir
} : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32> %6 = "tf.Cast"(%5) : (tensor<*xf32>) -> tensor<*xi32> func.return %6 : tensor<*xi32> } // Matmul with int32 accumulation. func.func private @internal_matmul_fn( %input : tensor<*xi8>, %weight : tensor<*xi8>, %input_scale : tensor<*xf32>, %input_zp : tensor<*xi32>,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Jan 08 01:16:10 UTC 2024 - 30.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v2/legalize_tf_test.cc
// May have been filtered so check for lack of failure instead of success. EXPECT_EQ(compilation_status.Delta(kMlirWithFallbackModeFailure), 0); } TEST(LegalizeTFTest, MatMul) { static constexpr char kMatMulModuleStr[] = R"( module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 268 : i32}} { func.func @main() -> (tensor<5x11xf32>) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 13 23:59:33 UTC 2024 - 16.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/resources/decomposition_lib.mlir
// "complex64, complex128, string}") tfr.func @tf__add_(!tfr.tensor<T>, !tfr.tensor<T>) -> !tfr.tensor<T> attributes{T} // Translated from: // // REGISTER_OP("MatMul") // .Input("a: T") // .Input("b: T") // .Output("product: T") // .Attr("transpose_a: bool = false") // .Attr("transpose_b: bool = false")
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Oct 13 16:33:28 UTC 2021 - 4.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/legalize-tf-while.mlir
%4 = "tf.Sub"(%3, %cst_2) : (tensor<?xi32>, tensor<i32>) -> tensor<?xi32> %5 = "tf.Transpose"(%arg3, %4) : (tensor<*xf32>, tensor<?xi32>) -> tensor<*xf32> %6 = "tf.MatMul"(%1, %5) {transpose_a = false, transpose_b = true} : (tensor<?x?xf32>, tensor<*xf32>) -> tensor<?x?xf32> %7 = "tf.AddV2"(%arg4, %6) {T = f32, device = ""} : (tensor<*xf32>, tensor<?x?xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/lift_quantizable_spots_as_functions.cc
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 16.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/ops/tf_op_quant_spec.cc
if (function_name.contains("with_bias")) { spec->biases_params[2] = {{0, 1}, quant::GetUniformQuantizedTypeForBias}; } } else if (function_name.contains("matmul")) { spec->coeff_op_quant_dim[1] = -1; if (function_name.contains("with_bias") || function_name.contains("and_bias")) { spec->biases_params[2] = {{0, 1},
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 6.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/insert_custom_aggregation_ops.mlir
func.func private @composite_matmul_with_bias_fn_1(%arg0: tensor<1x4xf32>, %arg1: tensor<4x3xf32>, %arg2: tensor<3xf32>) -> tensor<1x3xf32> attributes {tf_quant.composite_function} { %0 = "tf.MatMul"(%arg0, %arg1) <{grad_a = false, grad_b = false, transpose_a = false, transpose_b = false}> {attr_map = "0:transpose_a,1:transpose_b", device = ""} : (tensor<1x4xf32>, tensor<4x3xf32>) -> tensor<1x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 32.1K bytes - Viewed (0) -
tensorflow/cc/gradients/math_grad_test.cc
void TestMatMulGrad(const bool t_x, const bool t_y) { TestMatMulGradHelper<T>( /*is_x_batch=*/false, /*is_y_batch=*/false, t_x, t_y, [&](Output x, Output y) { return MatMul(root_, x, y, MatMul::TransposeA(t_x).TransposeB(t_y)); }); } template <typename T> void TestBatchMatMulGrad(const bool t_x, const bool t_y) { TestMatMulGradHelper<T>(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Aug 25 18:20:20 UTC 2023 - 36K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_composite_functions_tf.cc
return func_.emitWarning() << "Invalid number of arguments in the embedding " "matmul composite function"; } if (func_.getFunctionType().getNumResults() != 1) { return func_.emitWarning() << "Invalid number of results in the " "embedding matmul composite function"; } return success(); } private: func::FuncOp func_; };
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 17.6K bytes - Viewed (0)