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未验证 提交 5cfe1645 编写于 作者: S Sławomir Siwek 提交者： GitHub
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Replace matmul(v2) with fused_matmul during oneDNN fuse passes (#49515) 

* replace matmul with matmul_v2 in fuse passes

* Remove fusion logic from matmul

* removing fusion methods

* add proper name

* adjust namespaces

* clean attrs in python tests

* delete checkpoint and restore matmul version

* remove unused code

* matmul and reshape/transpose fuses migrated

* split MatmulOneDNN headers

* fuse activation and eltwise_add

* add fuse_activation

* matmul_transpose_reshape/reshape_transpose_matmul

* matmul + elementwise_add (fused)

* activation temporary modifciation

* merge newest develop

* remove depedency from other PR

* revert pbtxt

* remove placeholders from matmul_v2

* add description in OPMaker

* remove matmul_v2_op.h and all depedencies

* remove dims changing in base op

* add possibility to fuse already fused_matmul

* restart broken CI

* Empty-Commit

* revert matmul_utils.h

* codestyle

* adjust imports

* add pbtxt file

* 100% matmul unit tests coverage

* trigger CI with minimal changes to develop

* adjust changes to develop

* add fused_matmul op

* inherit base ops

* add "v2"

* move OPMaker

* Gradually add fused_matmul files

* second batch of fused_matmul changes

* split infershapes of matmul_v2 and fused_matmul

* inherit fused_matmul from matmul_v2

* Update paddle/phi/backends/onednn/onednn_reuse.h
Co-authored-by: NTomasz Socha <tomasz.socha@intel.com>

* Update paddle/phi/kernels/fusion/onednn/fused_matmul_kernel.cc
Co-authored-by: NTomasz Socha <tomasz.socha@intel.com>

---------
Co-authored-by: NTomasz Socha <tomasz.socha@intel.com>
上级 aa8cef4a
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Showing with 1478 addition and 298 deletion
paddle/fluid/framework/ir/mkldnn/matmul_activation_mkldnn_fuse_pass.cc
浏览文件 @ 5cfe1645
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
......@@ -26,7 +26,7 @@ using string::PrettyLogDetail;
void MatmulActivationMkldnnFusePass::ApplyImpl(Graph* graph) const {
auto act_types = GetSupportedActivations();
auto matmul_types = {"matmul", "matmul_v2"};
auto matmul_types = {"fused_matmul", "matmul", "matmul_v2"};
for (const auto& matmul_type : matmul_types)
for (auto& act_type : act_types) {
......@@ -61,8 +61,17 @@ void MatmulActivationMkldnnFusePass::FuseMatmulAct(
GET_IR_NODE_FROM_SUBGRAPH(
activation_out, activation_out, matmul_act_pattern);
SetActivationAttrs(matmul->Op(), activation->Op(), act_type);
matmul->Op()->SetOutput("Out", {activation_out->Name()});
OpDesc* matmul_op = matmul->Op();
matmul_op->SetType("fused_matmul");
if (matmul_type == "matmul") {
matmul_op->SetAttr("trans_x", matmul_op->GetAttr("transpose_X"));
matmul_op->SetAttr("trans_y", matmul_op->GetAttr("transpose_Y"));
matmul_op->SetAttr("matmul_alpha", matmul_op->GetAttr("alpha"));
}
SetActivationAttrs(matmul_op, activation->Op(), act_type);
matmul_op->SetOutput("Out", {activation_out->Name()});
IR_NODE_LINK_TO(matmul, activation_out);
GraphSafeRemoveNodes(graph, {activation, matmul_out});
......@@ -88,11 +97,6 @@ MatmulActivationMkldnnFusePass::MatmulActivationMkldnnFusePass() {
.AddInput("Y")
.IsTensor()
.End()
.AddInput(
"ResidualData") // Extra tensor used in matmul+elementwise_add fuse
.IsTensor()
.IsOptional()
.End()
.AddOutput("Out")
.IsTensor()
.End()
......@@ -113,8 +117,24 @@ MatmulActivationMkldnnFusePass::MatmulActivationMkldnnFusePass() {
.AddInput("Y")
.IsTensor()
.End()
.AddInput(
"ResidualData") // Extra tensor used in matmul+elementwise_add fuse
.AddOutput("Out")
.IsTensor()
.End()
.AddAttr("trans_x")
.IsType<bool>()
.End()
.AddAttr("trans_y")
.IsType<bool>()
.End();
AddOpCompat(OpCompat("fused_matmul"))
.AddInput("X")
.IsTensor()
.End()
.AddInput("Y")
.IsTensor()
.End()
.AddInput("ResidualData")
.IsTensor()
.IsOptional()
.End()
......@@ -126,6 +146,50 @@ MatmulActivationMkldnnFusePass::MatmulActivationMkldnnFusePass() {
.End()
.AddAttr("trans_y")
.IsType<bool>()
.End()
.AddAttr("matmul_alpha")
.IsType<float>()
.IsOptional()
.End()
.AddAttr("fuse_activation")
.IsType<std::string>()
.IsOptional()
.End()
.AddAttr("fuse_alpha")
.IsType<float>()
.IsOptional()
.End()
.AddAttr("fuse_beta")
.IsType<float>()
.IsOptional()
.End()
.AddAttr("fused_output_scale")
.IsType<float>()
.IsOptional()
.End()
.AddAttr("fused_reshape_X")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_transpose_X")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_reshape_Y")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_transpose_Y")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_reshape_Out")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_transpose_Out")
.IsType<std::vector<int>>()
.IsOptional()
.End();
AddOpCompat(OpCompat("abs"))
......@@ -279,6 +343,7 @@ REGISTER_PASS(matmul_activation_mkldnn_fuse_pass,
REGISTER_PASS_CAPABILITY(matmul_activation_mkldnn_fuse_pass)
.AddCombination(
paddle::framework::compatible::OpVersionComparatorCombination()
.EQ("fused_matmul", 0)
.LE("matmul", 1)
.EQ("matmul_v2", 0)
.EQ("abs", 0)
......
paddle/fluid/framework/ir/mkldnn/matmul_elementwise_add_mkldnn_fuse_pass.cc
浏览文件 @ 5cfe1645
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
......@@ -25,7 +25,7 @@ namespace ir {
using string::PrettyLogDetail;
void MatmulElementwiseAddMKLDNNFusePass::ApplyImpl(Graph* graph) const {
auto matmul_types = {"matmul", "matmul_v2"};
auto matmul_types = {"fused_matmul", "matmul", "matmul_v2"};
auto matmul_as_x = {true, false};
for (const auto& matmul_type : matmul_types)
......@@ -65,6 +65,12 @@ void MatmulElementwiseAddMKLDNNFusePass::FuseMatmulElementwiseAdd(
return;
}
matmul->Op()->SetType("fused_matmul");
if (matmul_type == "matmul") {
matmul->Op()->SetAttr("trans_x", matmul->Op()->GetAttr("transpose_X"));
matmul->Op()->SetAttr("trans_y", matmul->Op()->GetAttr("transpose_Y"));
matmul->Op()->SetAttr("matmul_alpha", matmul->Op()->GetAttr("alpha"));
}
matmul->Op()->SetInput("ResidualData", {elementwise_addend->Name()});
matmul->Op()->SetOutput("Out", {elementwise_add_out->Name()});
......@@ -125,6 +131,71 @@ MatmulElementwiseAddMKLDNNFusePass::MatmulElementwiseAddMKLDNNFusePass() {
.IsType<bool>()
.End();
AddOpCompat(OpCompat("fused_matmul"))
.AddInput("X")
.IsTensor()
.End()
.AddInput("Y")
.IsTensor()
.End()
.AddInput("ResidualData")
.IsTensor()
.IsOptional()
.End()
.AddOutput("Out")
.IsTensor()
.End()
.AddAttr("trans_x")
.IsType<bool>()
.End()
.AddAttr("trans_y")
.IsType<bool>()
.End()
.AddAttr("matmul_alpha")
.IsType<float>()
.IsOptional()
.End()
.AddAttr("fuse_activation")
.IsType<std::string>()
.IsOptional()
.End()
.AddAttr("fuse_alpha")
.IsType<float>()
.IsOptional()
.End()
.AddAttr("fuse_beta")
.IsType<float>()
.IsOptional()
.End()
.AddAttr("fused_output_scale")
.IsType<float>()
.IsOptional()
.End()
.AddAttr("fused_reshape_X")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_transpose_X")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_reshape_Y")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_transpose_Y")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_reshape_Out")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_transpose_Out")
.IsType<std::vector<int>>()
.IsOptional()
.End();
AddOpCompat(OpCompat("elementwise_add"))
.AddInput("X")
.IsTensor()
......@@ -149,6 +220,7 @@ REGISTER_PASS(matmul_elementwise_add_mkldnn_fuse_pass,
REGISTER_PASS_CAPABILITY(matmul_elementwise_add_mkldnn_fuse_pass)
.AddCombination(
paddle::framework::compatible::OpVersionComparatorCombination()
.EQ("fused_matmul", 0)
.LE("matmul", 1)
.EQ("matmul_v2", 0)
.LE("elementwise_add", 1));
paddle/fluid/framework/ir/mkldnn/matmul_transpose_reshape_mkldnn_fuse_pass.cc
浏览文件 @ 5cfe1645
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
......@@ -24,7 +24,7 @@ namespace ir {
using string::PrettyLogDetail;
void MatmulTransposeReshapeMKLDNNPass::ApplyImpl(Graph *graph) const {
auto matmul_types = {"matmul", "matmul_v2"};
auto matmul_types = {"fused_matmul", "matmul", "matmul_v2"};
for (const auto &matmul_type : matmul_types) {
Fuse(graph, matmul_type);
......@@ -84,6 +84,12 @@ void MatmulTransposeReshapeMKLDNNPass::Fuse(
}
OpDesc *matmul_desc = matmul_op->Op();
matmul_desc->SetType("fused_matmul");
if (matmul_type == "matmul") {
matmul_desc->SetAttr("trans_x", matmul_desc->GetAttr("transpose_X"));
matmul_desc->SetAttr("trans_y", matmul_desc->GetAttr("transpose_Y"));
matmul_desc->SetAttr("matmul_alpha", matmul_desc->GetAttr("alpha"));
}
matmul_desc->SetOutput("Out", {reshape_out->Name()});
matmul_desc->SetAttr("fused_reshape_Out", reshape_shape);
matmul_desc->SetAttr("fused_transpose_Out", transpose_axis);
......@@ -149,6 +155,71 @@ MatmulTransposeReshapeMKLDNNPass::MatmulTransposeReshapeMKLDNNPass() {
.IsType<bool>()
.End();
AddOpCompat(OpCompat("fused_matmul"))
.AddInput("X")
.IsTensor()
.End()
.AddInput("Y")
.IsTensor()
.End()
.AddInput("ResidualData")
.IsTensor()
.IsOptional()
.End()
.AddOutput("Out")
.IsTensor()
.End()
.AddAttr("trans_x")
.IsType<bool>()
.End()
.AddAttr("trans_y")
.IsType<bool>()
.End()
.AddAttr("matmul_alpha")
.IsType<float>()
.IsOptional()
.End()
.AddAttr("fuse_activation")
.IsType<std::string>()
.IsOptional()
.End()
.AddAttr("fuse_alpha")
.IsType<float>()
.IsOptional()
.End()
.AddAttr("fuse_beta")
.IsType<float>()
.IsOptional()
.End()
.AddAttr("fused_output_scale")
.IsType<float>()
.IsOptional()
.End()
.AddAttr("fused_reshape_X")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_transpose_X")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_reshape_Y")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_transpose_Y")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_reshape_Out")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_transpose_Out")
.IsType<std::vector<int>>()
.IsOptional()
.End();
AddOpCompat(OpCompat("transpose2"))
.AddInput("X")
.IsTensor()
......@@ -189,6 +260,7 @@ REGISTER_PASS(matmul_transpose_reshape_mkldnn_fuse_pass,
REGISTER_PASS_CAPABILITY(matmul_transpose_reshape_mkldnn_fuse_pass)
.AddCombination(
paddle::framework::compatible::OpVersionComparatorCombination()
.EQ("fused_matmul", 0)
.LE("matmul", 1)
.EQ("matmul_v2", 0)
.EQ("transpose2", 0)
......
paddle/fluid/framework/ir/mkldnn/operator_scale_onednn_fuse_pass.cc
浏览文件 @ 5cfe1645
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
......@@ -27,6 +27,7 @@ using string::PrettyLogDetail;
void FuseOperatorScaleOneDNNPass::ApplyImpl(Graph *graph) const {
const std::vector<std::string> fusable_ops{
"fc",
"fused_matmul",
"matmul",
"matmul_v2",
"elementwise_add",
......@@ -85,6 +86,19 @@ void FuseOperatorScaleOneDNNPass::FuseScale(Graph *graph,
scale = *(scale_tensor->data<float>());
}
if (op_type == "matmul") {
operator_op->Op()->SetType("fused_matmul");
operator_op->Op()->SetAttr("trans_x",
operator_op->Op()->GetAttr("transpose_X"));
operator_op->Op()->SetAttr("trans_y",
operator_op->Op()->GetAttr("transpose_Y"));
operator_op->Op()->SetAttr("matmul_alpha",
operator_op->Op()->GetAttr("alpha"));
}
if (op_type == "matmul_v2") {
operator_op->Op()->SetType("fused_matmul");
}
operator_op->Op()->SetAttr("fused_output_scale", scale);
operator_op->Op()->SetOutput("Out", {scale_out->Name()});
......@@ -111,6 +125,7 @@ REGISTER_PASS_CAPABILITY(operator_scale_onednn_fuse_pass)
.AddCombination(
paddle::framework::compatible::OpVersionComparatorCombination()
.EQ("fc", 0)
.EQ("fused_matmul", 0)
.LE("matmul", 1)
.EQ("matmul_v2", 0)
.LE("elementwise_add", 1)
......
paddle/fluid/framework/ir/mkldnn/reshape_transpose_matmul_mkldnn_fuse_pass.cc
浏览文件 @ 5cfe1645
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
......@@ -22,7 +22,7 @@ namespace framework {
namespace ir {
void ReshapeTransposeMatmulMkldnnFusePass::ApplyImpl(Graph *graph) const {
auto matmul_types = {"matmul", "matmul_v2"};
auto matmul_types = {"matmul", "matmul_v2", "fused_matmul"};
for (const auto &matmul_type : matmul_types) {
Fuse(graph,
......@@ -102,6 +102,25 @@ void ReshapeTransposeMatmulMkldnnFusePass::Fuse(
matmul_type + " encountered.");
}
// Return if input of fused_matmul is already fused
if (matmul_type == "fused_matmul") {
auto is_already_fused_X =
matmul_desc->HasAttr("fused_reshape_X")
? !(PADDLE_GET_CONST(std::vector<int>,
matmul_desc->GetAttr("fused_reshape_X"))
.empty())
: false;
if (is_already_fused_X && matmul_input_name == "X") return;
auto is_already_fused_Y =
matmul_desc->HasAttr("fused_reshape_Y")
? !(PADDLE_GET_CONST(std::vector<int>,
matmul_desc->GetAttr("fused_reshape_Y"))
.empty())
: false;
if (is_already_fused_Y && matmul_input_name == "Y") return;
}
auto reshape_shape =
paddle::get<std::vector<int>>(reshape_op->Op()->GetAttr("shape"));
auto transpose_axis =
......@@ -123,6 +142,12 @@ void ReshapeTransposeMatmulMkldnnFusePass::Fuse(
return;
}
matmul_desc->SetType("fused_matmul");
if (matmul_type == "matmul") {
matmul_desc->SetAttr("trans_x", matmul_desc->GetAttr("transpose_X"));
matmul_desc->SetAttr("trans_y", matmul_desc->GetAttr("transpose_Y"));
matmul_desc->SetAttr("matmul_alpha", matmul_desc->GetAttr("alpha"));
}
matmul_desc->SetInput(matmul_input_name, {(reshape_in)->Name()});
matmul_desc->SetAttr("fused_reshape_" + matmul_input_name, reshape_shape);
matmul_desc->SetAttr("fused_transpose_" + matmul_input_name,
......@@ -220,6 +245,71 @@ ReshapeTransposeMatmulMkldnnFusePass::ReshapeTransposeMatmulMkldnnFusePass() {
.AddAttr("trans_y")
.IsType<bool>()
.End();
AddOpCompat(OpCompat("fused_matmul"))
.AddInput("X")
.IsTensor()
.End()
.AddInput("Y")
.IsTensor()
.End()
.AddInput("ResidualData")
.IsTensor()
.IsOptional()
.End()
.AddOutput("Out")
.IsTensor()
.End()
.AddAttr("trans_x")
.IsType<bool>()
.End()
.AddAttr("trans_y")
.IsType<bool>()
.End()
.AddAttr("matmul_alpha")
.IsType<float>()
.IsOptional()
.End()
.AddAttr("fuse_activation")
.IsType<std::string>()
.IsOptional()
.End()
.AddAttr("fuse_alpha")
.IsType<float>()
.IsOptional()
.End()
.AddAttr("fuse_beta")
.IsType<float>()
.IsOptional()
.End()
.AddAttr("fused_output_scale")
.IsType<float>()
.IsOptional()
.End()
.AddAttr("fused_reshape_X")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_transpose_X")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_reshape_Y")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_transpose_Y")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_reshape_Out")
.IsType<std::vector<int>>()
.IsOptional()
.End()
.AddAttr("fused_transpose_Out")
.IsType<std::vector<int>>()
.IsOptional()
.End();
}
} // namespace ir
......@@ -234,5 +324,6 @@ REGISTER_PASS_CAPABILITY(reshape_transpose_matmul_mkldnn_fuse_pass)
paddle::framework::compatible::OpVersionComparatorCombination()
.EQ("reshape2", 0)
.EQ("transpose2", 0)
.EQ("fused_matmul", 0)
.EQ("matmul", 1)
.EQ("matmul_v2", 0));
paddle/fluid/operators/compat/fused_matmul.pbtxt 0 → 100644
浏览文件 @ 5cfe1645
type: "fused_matmul"
def {
inputs {
name: "X"
}
inputs {
name: "Y"
}
inputs {
name: "ResidualData"
}
outputs {
name: "Out"
}
attrs {
name: "trans_x"
type: BOOLEAN
}
attrs {
name: "trans_y"
type: BOOLEAN
}
}
extra {
attrs {
name: "matmul_alpha"
type: FLOAT
}
attrs {
name: "fuse_activation"
type: STRING
}
attrs {
name: "fuse_alpha"
type: FLOAT
}
attrs {
name: "fuse_beta"
type: FLOAT
}
attrs {
name: "fused_output_scale"
type: FLOAT
}
attrs {
name: "fused_reshape_X"
type: INTS
}
attrs {
name: "fused_transpose_X"
type: INTS
}
attrs {
name: "fused_reshape_Y"
type: INTS
}
attrs {
name: "fused_transpose_Y"
type: INTS
}
attrs {
name: "fused_reshape_Out"
type: INTS
}
attrs {
name: "fused_transpose_Out"
type: INTS
}
attrs {
name: "mkldnn_data_type"
type: STRING
}
attrs {
name: "Scale_x"
type: FLOAT
}
attrs {
name: "Scale_y"
type: FLOAT
}
attrs {
name: "Scale_in_eltwise"
type: FLOAT
}
attrs {
name: "Scale_out"
type: FLOAT
}
attrs {
name: "force_fp32_output"
type: BOOLEAN
}
}
paddle/fluid/operators/compat/matmul_v2.pbtxt
浏览文件 @ 5cfe1645
......@@ -39,28 +39,4 @@ extra {
name: "op_device"
type: STRING
}
attrs {
name: "fused_reshape_X"
type: INTS
}
attrs {
name: "fused_reshape_Y"
type: INTS
}
attrs {
name: "fused_transpose_X"
type: INTS
}
attrs {
name: "fused_transpose_Y"
type: INTS
}
attrs {
name: "fused_reshape_Out"
type: INTS
}
attrs {
name: "fused_transpose_Out"
type: INTS
}
}
paddle/fluid/operators/fused/fused_matmul_op.cc 0 → 100644
浏览文件 @ 5cfe1645
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/fluid/operators/matmul_v2_op.h"
namespace paddle {
namespace operators {
static std::vector<int64_t> GetInputShape(phi::DDim dim,
std::vector<int> shape,
std::vector<int> axis) {
PADDLE_ENFORCE_GT(dim.size(),
0,
phi::errors::InvalidArgument(
"The Input(%s) has not been initialized properly. The "
"shape of Input(%s) = [%s].",
dim));
auto is_input_fused = (!shape.empty() && !axis.empty());
if (is_input_fused) {
dim = dim.reshape(shape).transpose(axis);
}
return phi::vectorize(dim);
}
class FusedMatmulOp : public MatMulV2Op {
public:
using MatMulV2Op::MatMulV2Op;
void InferShape(framework::InferShapeContext* ctx) const override {
OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "fused_matmul");
OP_INOUT_CHECK(ctx->HasInput("Y"), "Input", "Y", "fused_matmul");
OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "fused_matmul");
bool trans_x = ctx->Attrs().Get<bool>("trans_x");
bool trans_y = ctx->Attrs().Get<bool>("trans_y");
std::vector<int64_t> dims_x =
GetInputShape(ctx->GetInputDim("X"),
ctx->Attrs().Get<std::vector<int>>("fused_reshape_X"),
ctx->Attrs().Get<std::vector<int>>("fused_transpose_X"));
std::vector<int64_t> dims_y =
GetInputShape(ctx->GetInputDim("Y"),
ctx->Attrs().Get<std::vector<int>>("fused_reshape_Y"),
ctx->Attrs().Get<std::vector<int>>("fused_transpose_Y"));
auto ndims_x = dims_x.size();
auto ndims_y = dims_y.size();
PADDLE_ENFORCE_GT(ndims_x,
0,
phi::errors::InvalidArgument(
"The Input(X) dims size must be greater than 0,"
" but received dims size is 0. "));
PADDLE_ENFORCE_GT(ndims_y,
0,
phi::errors::InvalidArgument(
"The Input(Y) dims size must be greater than 0,"
" but received dims size is 0. "));
bool x_broadcasted = false;
bool y_broadcasted = false;
if (ndims_x == 1) {
dims_x.insert(dims_x.begin(), 1);
ndims_x = 2;
x_broadcasted = true;
}
if (ndims_y == 1) {
dims_y.push_back(1);
ndims_y = 2;
y_broadcasted = true;
}
size_t M, N;
if (trans_x) {
M = dims_x[ndims_x - 1];
} else {
M = dims_x[ndims_x - 2];
}
if (trans_y) {
N = dims_y[ndims_y - 2];
} else {
N = dims_y[ndims_y - 1];
}
std::vector<int64_t> new_dims;
if (ndims_x > ndims_y) {
new_dims.assign(dims_x.begin(), dims_x.end() - 2);
} else if (ndims_x < ndims_y) {
new_dims.assign(dims_y.begin(), dims_y.end() - 2);
} else {
new_dims.reserve(ndims_x);
for (size_t i = 0; i < ndims_x - 2; ++i) {
new_dims.push_back(std::max(dims_x[i], dims_y[i]));
}
}
if (!x_broadcasted) {
new_dims.push_back(M);
}
if (!y_broadcasted) {
new_dims.push_back(N);
}
if (x_broadcasted && y_broadcasted) {
new_dims.push_back(1);
}
auto ddim_out = phi::make_ddim(new_dims);
auto shape = ctx->Attrs().Get<std::vector<int>>("fused_reshape_Out");
auto axis = ctx->Attrs().Get<std::vector<int>>("fused_transpose_Out");
auto is_output_fused = (!shape.empty() && !axis.empty());
if (is_output_fused) {
ddim_out = ddim_out.transpose(axis).reshape(shape);
}
ctx->SetOutputDim("Out", ddim_out);
ctx->ShareLoD("X", "Out");
}
};
class FusedMatmulOpMaker : public MatMulV2OpMaker {
protected:
void Apply() override {
AddInput("ResidualData",
"Extra input from matmul_elementwise_add_mkldnn_fuse_pass")
.AsDispensable()
.AsExtra();
AddAttr<float>("matmul_alpha", "Output scale used in matmul_v1")
.SetDefault(1.0f);
AddAttr<std::string>(
"fuse_activation",
"Activation type from matmul_activation_mkldnn_fuse_pass")
.SetDefault("");
AddAttr<float>("fuse_alpha",
"Activation alpha from matmul_activation_mkldnn_fuse_pass")
.SetDefault(0.0f);
AddAttr<float>("fuse_beta",
"Activation beta from matmul_activation_mkldnn_fuse_pass")
.SetDefault(0.0f);
AddAttr<float>("fused_output_scale",
"Output scale from operator_scale_onednn_fuse_pass")
.SetDefault(1.0f);
AddAttr<std::vector<int>>("fused_reshape_X",
"Reshape's shape attribute from "
"reshape_transpose_matmul_mkldnn_fuse_pass")
.SetDefault({});
AddAttr<std::vector<int>>("fused_transpose_X",
"Transpose's axis attribute from "
"reshape_transpose_matmul_mkldnn_fuse_pass")
.SetDefault({});
AddAttr<std::vector<int>>("fused_reshape_Y",
"Reshape's shape attribute from "
"reshape_transpose_matmul_mkldnn_fuse_pass")
.SetDefault({});
AddAttr<std::vector<int>>("fused_transpose_Y",
"Transpose's axis attribute from "
"reshape_transpose_matmul_mkldnn_fuse_pass")
.SetDefault({});
AddAttr<std::vector<int>>("fused_reshape_Out",
"Reshape's shape attribute from "
"matmul_transpose_reshape_mkldnn_fuse_pass")
.SetDefault({});
AddAttr<std::vector<int>>("fused_transpose_Out",
"Transpose's axis attribute from "
"matmul_transpose_reshape_mkldnn_fuse_pass")
.SetDefault({});
AddAttr<std::string>("mkldnn_data_type", "oneDNN operator data type")
.SetDefault("float32")
.InEnum({"float32", "int8", "bfloat16"});
AddAttr<float>("Scale_x", "Matmul X input quantization scale")
.SetDefault(1.0f);
AddAttr<float>("Scale_y", "Matmul Y input quantization scale")
.SetDefault(1.0f);
AddAttr<float>("Scale_in_eltwise", "Matmul ResidualData quantization scale")
.SetDefault(0.0f);
AddAttr<float>("Scale_out", "Matmul output quantization scale")
.SetDefault(1.0f);
AddAttr<bool>("force_fp32_output",
"Flag determining if output should be converted to FP32")
.SetDefault(false);
AddComment(
R"DOC(Matrix multiplication extended with oneDNN-specific fusion logic.)DOC");
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(
fused_matmul,
ops::FusedMatmulOp,
ops::FusedMatmulOpMaker,
paddle::framework::EmptyGradOpMaker<paddle::framework::OpDesc>,
paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>);
paddle/fluid/operators/matmul_v2_op.cc
浏览文件 @ 5cfe1645
// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
......@@ -24,52 +24,31 @@
namespace paddle {
namespace operators {
static framework::DDim GetDimForInput(const framework::InferShapeContext& ctx,
const std::string input_name) {
auto shape = ctx.Attrs().Get<std::vector<int>>("fused_reshape_" + input_name);
auto axis =
ctx.Attrs().Get<std::vector<int>>("fused_transpose_" + input_name);
auto dim = ctx.GetInputDim(input_name);
PADDLE_ENFORCE_GT(dim.size(),
0,
platform::errors::InvalidArgument(
"The Input(%s) has not been initialized properly. The "
"shape of Input(%s) = [%s].",
dim));
if (!shape.empty() && !axis.empty()) {
dim = dim.reshape(shape).transpose(axis);
}
return dim;
}
class MatMulV2Op : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override {
void MatMulV2Op::InferShape(framework::InferShapeContext* ctx) const {
OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "matmul_v2");
OP_INOUT_CHECK(ctx->HasInput("Y"), "Input", "Y", "matmul_v2");
OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "matmul_v2");
bool trans_x = ctx->Attrs().Get<bool>("trans_x");
bool trans_y = ctx->Attrs().Get<bool>("trans_y");
std::vector<int64_t> dims_x = phi::vectorize(GetDimForInput(*ctx, "X"));
std::vector<int64_t> dims_y = phi::vectorize(GetDimForInput(*ctx, "Y"));
std::vector<int64_t> dims_x = phi::vectorize(ctx->GetInputDim("X"));
std::vector<int64_t> dims_y = phi::vectorize(ctx->GetInputDim("Y"));
auto ndims_x = dims_x.size();
auto ndims_y = dims_y.size();
PADDLE_ENFORCE_GT(ndims_x,
0,
platform::errors::InvalidArgument(
phi::errors::InvalidArgument(
"The Input(X) dims size must be greater than 0,"
" but received dims size is 0. "));
PADDLE_ENFORCE_GT(ndims_y,
0,
platform::errors::InvalidArgument(
phi::errors::InvalidArgument(
"The Input(Y) dims size must be greater than 0,"
" but received dims size is 0. "));
bool x_broadcasted = false, y_broadcasted = false;
bool x_broadcasted = false;
bool y_broadcasted = false;
if (ndims_x == 1) {
dims_x.insert(dims_x.begin(), 1);
ndims_x = 2;
......@@ -115,33 +94,21 @@ class MatMulV2Op : public framework::OperatorWithKernel {
new_dims.push_back(1);
}
auto ddim_out = phi::make_ddim(new_dims);
#ifdef PADDLE_WITH_MKLDNN
auto shape = ctx->Attrs().Get<std::vector<int>>("fused_reshape_Out");
auto axis = ctx->Attrs().Get<std::vector<int>>("fused_transpose_Out");
if (!shape.empty() && !axis.empty()) {
ddim_out = ddim_out.transpose(axis).reshape(shape);
}
#endif
ctx->SetOutputDim("Out", ddim_out);
ctx->SetOutputDim("Out", phi::make_ddim(new_dims));
ctx->ShareLoD("X", "Out");
}
}
protected:
phi::KernelKey GetExpectedKernelType(
const framework::ExecutionContext& ctx) const override {
phi::KernelKey MatMulV2Op::GetExpectedKernelType(
const framework::ExecutionContext& ctx) const {
auto input_data_type =
OperatorWithKernel::IndicateOrPromoteVarDataTypes(ctx, "X", "Y");
return phi::KernelKey(input_data_type, ctx.GetPlace());
}
}
phi::KernelKey GetKernelTypeForVar(
phi::KernelKey MatMulV2Op::GetKernelTypeForVar(
const std::string& var_name,
const phi::DenseTensor& tensor,
const phi::KernelKey& expected_kernel_type) const override {
const phi::KernelKey& expected_kernel_type) const {
if (framework::IsComplexType(expected_kernel_type.dtype())) {
// only promote inputs’s types when contains complex input
return phi::KernelKey(tensor.place(), tensor.layout(), tensor.dtype());
......@@ -153,20 +120,16 @@ class MatMulV2Op : public framework::OperatorWithKernel {
(tensor.layout() != phi::DataLayout::ONEDNN) &&
phi::OneDNNContext::tls().get_cur_paddle_data_layout() ==
phi::DataLayout::kNHWC) {
return phi::KernelKey(tensor.place(),
phi::DataLayout::kNHWC,
expected_kernel_type.dtype());
return phi::KernelKey(
tensor.place(), phi::DataLayout::kNHWC, expected_kernel_type.dtype());
}
#endif
return phi::KernelKey(
tensor.place(), tensor.layout(), expected_kernel_type.dtype());
}
}
};
}
class MatMulV2OpMaker : public framework::OpProtoAndCheckerMaker {
public:
void Make() override {
void MatMulV2OpMaker::Make() {
AddInput("X", "tensor of shape (d0, d1 ... M, K)");
AddInput("Y", "tensor of shape (d0, d1 ... K, N)");
AddOutput("Out", "tensor of shape (d0, d1 ... M, N)");
......@@ -184,8 +147,8 @@ class MatMulV2OpMaker : public framework::OpProtoAndCheckerMaker {
In addition, it also follows the broadcast rule which is similar as
numpy.matmul.
)DOC");
}
};
Apply();
}
class MatMulV2OpGrad : public framework::OperatorWithKernel {
public:
......
paddle/fluid/operators/matmul_v2_op.h
浏览文件 @ 5cfe1645
/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
/* Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
......@@ -37,6 +37,29 @@ limitations under the License. */
namespace paddle {
namespace operators {
class MatMulV2Op : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override;
protected:
phi::KernelKey GetExpectedKernelType(
const framework::ExecutionContext& ctx) const override;
phi::KernelKey GetKernelTypeForVar(
const std::string& var_name,
const phi::DenseTensor& tensor,
const phi::KernelKey& expected_kernel_type) const override;
};
class MatMulV2OpMaker : public framework::OpProtoAndCheckerMaker {
public:
void Make() final;
protected:
virtual void Apply() {}
};
// Reshape a rank-3 tensor from P x M x N to (P * M) x N.
// Identity op if the tensor is not of rank 3.
static phi::DenseTensor FoldInitDims(const phi::DenseTensor& input) {
......
paddle/fluid/operators/ops_extra_info.h
浏览文件 @ 5cfe1645
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
......@@ -102,12 +102,6 @@ const std::unordered_map<std::string, ExtraAttrPropertySet>
{"fused_output_scale", ExtraAttrProperty::ONEDNN},
{"fuse_residual_connection", ExtraAttrProperty::ONEDNN},
{"fuse_with_relu", ExtraAttrProperty::ONEDNN},
{"fused_reshape_Out", ExtraAttrProperty::ONEDNN},
{"fused_transpose_Out", ExtraAttrProperty::ONEDNN},
{"fused_reshape_X", ExtraAttrProperty::ONEDNN},
{"fused_reshape_Y", ExtraAttrProperty::ONEDNN},
{"fused_transpose_X", ExtraAttrProperty::ONEDNN},
{"fused_transpose_Y", ExtraAttrProperty::ONEDNN},
{"mkldnn_data_type", ExtraAttrProperty::ONEDNN},
{"scale_x", ExtraAttrProperty::ONEDNN},
{"scale_y", ExtraAttrProperty::ONEDNN},
......@@ -226,8 +220,7 @@ class ExtraInfoUtils {
std::unordered_map<std::string, std::vector<std::string>>
g_extra_input_names_map_ = {{"conv2d", {"Bias", "ResidualData"}},
{"conv2d_transpose", {"Bias"}},
{"conv2d_grad", {"Bias"}},
{"matmul_v2", {"ResidualData"}}};
{"conv2d_grad", {"Bias"}}};
std::vector<std::string> empty_extra_input_names_;
};
......
paddle/phi/backends/onednn/onednn_reuse.h
浏览文件 @ 5cfe1645
/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
/* Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
......@@ -53,26 +53,31 @@ constexpr bool is_bfloat16() {
static void AppendActivation(const OneDNNContext& dev_ctx,
dnnl::post_ops& post_ops, // NOLINT
float activation_scale = 1.0f) {
float activation_scale = 1.0f,
std::string fuse_activation = "",
float fuse_alpha = 0.0f,
float fuse_beta = 0.0f) {
if (fuse_activation == "") {
const auto invalid_attribute =
dev_ctx.HasDnnAttr("fuse_activation")
? PADDLE_GET_CONST(std::string, dev_ctx.GetDnnAttr("fuse_activation"))
? PADDLE_GET_CONST(std::string,
dev_ctx.GetDnnAttr("fuse_activation"))
.empty()
: true;
if (invalid_attribute) return;
const auto fuse_activation =
fuse_activation =
dev_ctx.HasDnnAttr("fuse_activation")
? PADDLE_GET_CONST(std::string, dev_ctx.GetDnnAttr("fuse_activation"))
? PADDLE_GET_CONST(std::string,
dev_ctx.GetDnnAttr("fuse_activation"))
: "";
const auto fuse_alpha =
dev_ctx.HasDnnAttr("fuse_alpha")
fuse_alpha = dev_ctx.HasDnnAttr("fuse_alpha")
? PADDLE_GET_CONST(float, dev_ctx.GetDnnAttr("fuse_alpha"))
: 0.0f;
const auto fuse_beta =
dev_ctx.HasDnnAttr("fuse_beta")
fuse_beta = dev_ctx.HasDnnAttr("fuse_beta")
? PADDLE_GET_CONST(float, dev_ctx.GetDnnAttr("fuse_beta"))
: 0.0f;
}
if (fuse_activation == "hard_sigmoid") {
post_ops.append_eltwise(activation_scale,
......
paddle/phi/kernels/fusion/onednn/fused_matmul_kernel.cc 0 → 100644
浏览文件 @ 5cfe1645
此差异已折叠。
paddle/phi/kernels/onednn/matmul_kernel.cc
浏览文件 @ 5cfe1645
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
......@@ -51,8 +51,7 @@ void CalculateMatrixDims(const std::vector<int64_t> &x_dims,
const std::vector<int64_t> &y_dims,
std::vector<int64_t> *x_bd_dims,
std::vector<int64_t> *y_bd_dims,
DenseTensor *out,
const bool is_output_fused) {
DenseTensor *out) {
if (x_dims.size() == 1) {
(*x_bd_dims)[(*x_bd_dims).size() - 1] = x_dims[0];
} else if (x_dims.size() == 2) {
......@@ -74,7 +73,7 @@ void CalculateMatrixDims(const std::vector<int64_t> &x_dims,
}
}
if (!is_output_fused && x_dims.size() > 2 && y_dims.size() > 2) {
if (x_dims.size() > 2 && y_dims.size() > 2) {
auto out_dims = vectorize(out->dims());
for (size_t i = 0; i < (*x_bd_dims).size() - 2; ++i) {
PADDLE_ENFORCE_EQ(
......@@ -121,15 +120,6 @@ void MatmulKernel(const Context &dev_ctx,
? PADDLE_GET_CONST(bool, dev_ctx.GetDnnAttr("force_fp32_output"))
: false;
bool fuse_relu = false;
if (dev_ctx.HasDnnAttr("fuse_activation")) {
auto act_type =
PADDLE_GET_CONST(std::string, dev_ctx.GetDnnAttr("fuse_activation"));
if (act_type == "relu" || act_type == "relu6") {
fuse_relu = true;
}
}
auto x_dims = vectorize(GetDimsForInput(dev_ctx, x.dims(), "X"));
auto y_dims = vectorize(GetDimsForInput(dev_ctx, y.dims(), "Y"));
......@@ -139,12 +129,7 @@ void MatmulKernel(const Context &dev_ctx,
std::vector<int64_t> x_bd_dims(ndims, 1);
std::vector<int64_t> y_bd_dims(ndims, 1);
CalculateMatrixDims(x_dims,
y_dims,
&x_bd_dims,
&y_bd_dims,
out,
funcs::IsOutputFused(dev_ctx));
CalculateMatrixDims(x_dims, y_dims, &x_bd_dims, &y_bd_dims, out);
if (force_fp32_output || ((!is_int8) && (!is_bfloat16))) {
funcs::ExecuteMatmul<T, float>(
......@@ -152,9 +137,6 @@ void MatmulKernel(const Context &dev_ctx,
} else if (is_bfloat16) {
funcs::ExecuteMatmul<T, paddle::platform::bfloat16>(
dev_ctx, x, y, x_bd_dims, y_bd_dims, transpose_x, transpose_y, out);
} else if (fuse_relu) {
funcs::ExecuteMatmul<T, uint8_t>(
dev_ctx, x, y, x_bd_dims, y_bd_dims, transpose_x, transpose_y, out);
} else {
funcs::ExecuteMatmul<T, int8_t>(
dev_ctx, x, y, x_bd_dims, y_bd_dims, transpose_x, transpose_y, out);
......
paddle/phi/ops/compat/fused_matmul_sig.cc 0 → 100644
浏览文件 @ 5cfe1645
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/phi/core/compat/op_utils.h"
namespace phi {
KernelSignature FusedMatmulOpArgumentMapping(
const ArgumentMappingContext& ctx) {
return KernelSignature("fused_matmul",
{"X", "Y", "ResidualData"},
{"trans_x",
"trans_y",
"matmul_alpha",
"fuse_activation",
"fuse_alpha",
"fuse_beta",
"fused_output_scale",
"fused_reshape_X",
"fused_transpose_X",
"fused_reshape_Y",
"fused_transpose_Y",
"fused_reshape_Out",
"fused_transpose_Out",
"mkldnn_data_type",
"Scale_x",
"Scale_y",
"Scale_in_eltwise",
"Scale_out",
"force_fp32_output"},
{"Out"});
}
} // namespace phi
PD_REGISTER_ARG_MAPPING_FN(fused_matmul, phi::FusedMatmulOpArgumentMapping);
python/paddle/fluid/tests/unittests/ir/inference/test_map_matmul_v2_to_matmul_pass.py
浏览文件 @ 5cfe1645
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
......@@ -103,12 +103,6 @@ class TestMapMatmulToMulPass(PassAutoScanTest):
alpha=alpha,
trans_x=transpose_X,
trans_y=transpose_Y,
fused_reshape_Out=[],
fused_transpose_Out=[],
fused_reshape_X=[],
fused_reshape_Y=[],
fused_transpose_X=[],
fused_transpose_Y=[],
)
ops = [
......
python/paddle/fluid/tests/unittests/ir/inference/test_map_matmul_v2_to_mul_pass.py
浏览文件 @ 5cfe1645
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
......@@ -92,12 +92,6 @@ class TestMapMatmulToMulPass(PassAutoScanTest):
alpha=alpha,
trans_x=transpose_X,
trans_y=transpose_Y,
fused_reshape_Out=[],
fused_transpose_Out=[],
fused_reshape_X=[],
fused_reshape_Y=[],
fused_transpose_X=[],
fused_transpose_Y=[],
)
ops = [
......
python/paddle/fluid/tests/unittests/ir/inference/test_matmul_v2_scale_fuse_pass.py
浏览文件 @ 5cfe1645
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
......@@ -76,12 +76,6 @@ class TestMatmulV2ScaleFusePass(PassAutoScanTest):
outputs={"Out": ["matmul_out"]},
trans_x=transpose_X,
trans_y=transpose_Y,
fused_reshape_X=[],
fused_reshape_Y=[],
fused_transpose_X=[],
fused_transpose_Y=[],
fused_reshape_Out=[],
fused_transpose_Out=[],
)
is_scale_tensor = draw(st.booleans())
if is_scale_tensor:
......
python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_matmul_activation_fuse_pass.py
浏览文件 @ 5cfe1645
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the 'License');
# you may not use this file except in compliance with the License.
......@@ -146,7 +146,7 @@ class TestMatmulActivationMkldnnFusePass(PassAutoScanTest):
'operator_scale_onednn_fuse_pass',
],
)
yield config, ['matmul'], (1e-5, 1e-5)
yield config, ['fused_matmul'], (1e-5, 1e-5)
def test(self):
self.run_and_statis(
......
python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_matmul_elementwise_add_activation_fuse_pass.py
浏览文件 @ 5cfe1645
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the 'License');
# you may not use this file except in compliance with the License.
......@@ -137,7 +137,7 @@ class TestMatmulElementwiseAddActivationMkldnnFusePass(PassAutoScanTest):
'matmul_activation_mkldnn_fuse_pass',
],
)
yield config, ['matmul'], (1e-5, 1e-5)
yield config, ['fused_matmul'], (1e-5, 1e-5)
def test(self):
self.run_and_statis(
......
python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_matmul_elementwise_add_fuse_pass.py
浏览文件 @ 5cfe1645
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the 'License');
# you may not use this file except in compliance with the License.
......@@ -76,7 +76,7 @@ class TestMatmulElementwiseAddMkldnnFusePass(PassAutoScanTest):
config = self.create_inference_config(
use_mkldnn=True, passes=['matmul_elementwise_add_mkldnn_fuse_pass']
)
yield config, ['matmul'], (1e-5, 1e-5)
yield config, ['fused_matmul'], (1e-5, 1e-5)
def test(self):
self.run_and_statis(
......
python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_matmul_v2_activation_fuse_pass.py
浏览文件 @ 5cfe1645
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
......@@ -150,7 +150,7 @@ class TestMatmulv2ActivationMkldnnFusePass(PassAutoScanTest):
'operator_scale_onednn_fuse_pass',
],
)
yield config, ['matmul_v2'], (1e-5, 1e-5)
yield config, ['fused_matmul'], (1e-5, 1e-5)
def test(self):
self.run_and_statis(
......
python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_matmul_v2_elementwise_add_fuse_pass.py
浏览文件 @ 5cfe1645
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the 'License');
# you may not use this file except in compliance with the License.
......@@ -87,7 +87,7 @@ class TestMatmulV2ElementwiseAddMkldnnFusePass(PassAutoScanTest):
def sample_predictor_configs(self, program_config):
config = self.create_inference_config(use_mkldnn=True)
yield config, ['matmul_v2'], (1e-5, 1e-5)
yield config, ['fused_matmul'], (1e-5, 1e-5)
def test(self):
self.run_and_statis(
......
python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_matmul_v2_transpose_reshape_fuse_pass.py
浏览文件 @ 5cfe1645
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
......@@ -90,12 +90,6 @@ class TestMatmulv2TransposeReshapeMkldnnFusePass(PassAutoScanTest):
attrs={
"trans_x": transpose_X,
"trans_y": transpose_Y,
"fused_reshape_X": [],
"fused_reshape_Y": [],
"fused_transpose_X": [],
"fused_transpose_Y": [],
"fused_reshape_Out": [],
"fused_transpose_Out": [],
},
)
......@@ -135,17 +129,8 @@ class TestMatmulv2TransposeReshapeMkldnnFusePass(PassAutoScanTest):
return program_config
def sample_predictor_configs(self, program_config):
# gpu_cpu_map_matmul_v2_to_matmul_pass will affect the type of final fused op
fused_op = "matmul_v2"
input1_dim1 = program_config.inputs["input_data1"].shape[0]
input2_dim1 = program_config.inputs["input_data2"].shape[0]
input1_dim2 = program_config.inputs["input_data1"].shape[1]
input2_dim2 = program_config.inputs["input_data2"].shape[1]
if input1_dim1 == input2_dim1 and input1_dim2 == input2_dim2:
fused_op = "matmul"
config = self.create_inference_config(use_mkldnn=True)
yield config, [fused_op], (1e-5, 1e-5)
yield config, ['fused_matmul'], (1e-5, 1e-5)
def test(self):
self.run_and_statis(
......
python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_matmulv2_op.py
浏览文件 @ 5cfe1645
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
......@@ -93,12 +93,6 @@ class TestMkldnnMatmulv2Op(MkldnnAutoScanTest):
attrs={
"trans_x": kwargs["transpose_X"],
"trans_y": kwargs["transpose_Y"],
"fused_reshape_X": [],
"fused_reshape_Y": [],
"fused_transpose_X": [],
"fused_transpose_Y": [],
"fused_reshape_Out": [],
"fused_transpose_Out": [],
},
)
......
python/paddle/fluid/tests/unittests/ir/inference/test_onednn_matmul_transpose_reshape_fuse_pass.py
浏览文件 @ 5cfe1645
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
......@@ -116,7 +116,7 @@ class TestOneDNNMatmulTransposeReshapeFusePass(PassAutoScanTest):
def sample_predictor_configs(self, program_config):
config = self.create_inference_config(use_mkldnn=True)
yield config, ['matmul'], (1e-5, 1e-5)
yield config, ['fused_matmul'], (1e-5, 1e-5)
def test(self):
self.run_and_statis(
......
python/paddle/fluid/tests/unittests/ir/inference/test_onednn_reshape_transpose_matmul_fuse_pass.py
浏览文件 @ 5cfe1645
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
......@@ -154,7 +154,7 @@ class TestOneDNNReshapeTransposeMatmulFusePass(PassAutoScanTest):
def sample_predictor_configs(self, program_config):
config = self.create_inference_config(use_mkldnn=True)
yield config, ['matmul'], (1e-5, 1e-5)
yield config, ['fused_matmul'], (1e-5, 1e-5)
def test(self):
self.run_and_statis(
......
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