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Paddle/paddle/fluid/operators/flatten_op.cc

295 lines
11 KiB

/* Copyright (c) 2019 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/flatten_op.h"
#include <memory>
#include <string>
#include <unordered_map>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
namespace paddle {
namespace operators {
using Tensor = framework::Tensor;
class FlattenOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext *ctx) const override {
OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "Flatten");
OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "Flatten");
const auto &axis = ctx->Attrs().Get<int>("axis");
const auto &in_dims = ctx->GetInputDim("X");
PADDLE_ENFORCE_GE(axis, 0,
platform::errors::InvalidArgument(
"The axis should be greater than or equal to 0."));
PADDLE_ENFORCE_LE(
axis, in_dims.size(),
platform::errors::InvalidArgument(
"The axis should be less than or equal to input tensor's rank."));
const auto &out_dims = GetOutputShape(axis, in_dims);
ctx->SetOutputDim("Out", framework::make_ddim(out_dims));
if (in_dims[0] == out_dims[0]) {
// Only pass LoD when the first dimension of output and Input(X)
// are the same.
ctx->ShareLoD("X", "Out");
}
}
static std::vector<int32_t> GetOutputShape(const int axis,
const framework::DDim &in_dims) {
int64_t outer = 1, inner = 1;
for (int i = 0; i < in_dims.size(); ++i) {
if (i < axis) {
outer *= in_dims[i];
} else {
inner *= in_dims[i];
}
}
std::vector<int32_t> out_shape(2);
out_shape[0] = outer;
out_shape[1] = inner;
return out_shape;
}
protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext &ctx) const override {
return framework::OpKernelType(
OperatorWithKernel::IndicateVarDataType(ctx, "X"),
ctx.device_context());
}
};
class FlattenOpMaker : public framework::OpProtoAndCheckerMaker {
public:
void Make() override {
AddInput("X", "(Tensor) A tensor of rank >= axis.");
AddOutput("Out",
"A 2D tensor is reshaped input tensor. The input dimensions"
"up to axis are flattened to the outer dimension of the output"
"and the remaining input dimensions are flattened into the inner"
"dimension of the output.");
AddAttr<int>("axis",
"(int)"
"Indicate up to which input dimensions (exclusive) should be"
"flattened to the outer dimension of the output. The value"
"for axis must be in the range [0, R], where R is the rank of"
"the input tensor. When axis = 0, the shape of the output"
"tensor is (1, (d_0 X d_1 ... d_n), where the shape of the"
"input tensor is (d_0, d_1, ... d_n).")
.SetDefault(1);
AddComment(R"DOC(
Flatten Operator
Flattens the input tensor into a 2D matrix.
Examples:
Case 1:
Given
X.shape = (3, 100, 100, 4)
and
axis = 2
We get:
Out.shape = (3 * 100, 4 * 100)
Case 2:
Given
X.shape = (3, 100, 100, 4)
and
axis = 0
We get:
Out.shape = (1, 3 * 100 * 100 * 4)
)DOC");
}
};
class FlattenGradOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext *context) const override {
context->SetOutputDim(framework::GradVarName("X"),
context->GetInputDim("X"));
context->ShareLoD("X", framework::GradVarName("X"));
}
protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext &ctx) const override {
return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType(
ctx, framework::GradVarName("Out")),
ctx.device_context());
}
};
template <typename T>
class FlattenGradOpMaker : public framework::SingleGradOpMaker<T> {
public:
using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
void Apply(GradOpPtr<T> grad_op) const override {
grad_op->SetType("flatten_grad");
grad_op->SetInput("X", this->Input("X"));
grad_op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
grad_op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
grad_op->SetAttrMap(this->Attrs());
}
};
// FIXME(zcd): flatten2 adds an intermediate output(XShape) based on flatten,
// the XShape is used to carry the shape and lod of X which will be used in
// flatten_grad, in this way, the framework can reuse the memory of X
// immediately the flatten2_op is finished.
// Considering compatibility issues, we could not fix flatten2_op
class Flatten2Op : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext *ctx) const override {
OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "Flatten2");
OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "Flatten2");
const auto &axis = ctx->Attrs().Get<int>("axis");
const auto &in_dims = ctx->GetInputDim("X");
PADDLE_ENFORCE_GE(axis, 0,
platform::errors::InvalidArgument(
"The axis should be greater than or equal to 0."));
PADDLE_ENFORCE_LE(
axis, in_dims.size(),
platform::errors::InvalidArgument(
"The axis should be less than or equal to input tensor's rank"));
const auto &out_dims = FlattenOp::GetOutputShape(axis, in_dims);
ctx->SetOutputDim("Out", framework::make_ddim(out_dims));
if (in_dims[0] == out_dims[0]) {
// Only pass LoD when the first dimension of output and Input(X)
// are the same.
ctx->ShareLoD("X", "Out");
}
OP_INOUT_CHECK(ctx->HasOutput("XShape"), "Output", "XShape", "Flatten2");
std::vector<int64_t> xshape_dims(in_dims.size() + 1);
xshape_dims[0] = 0;
for (int i = 0; i < in_dims.size(); ++i) {
xshape_dims[i + 1] = in_dims[i];
}
ctx->SetOutputDim("XShape", framework::make_ddim(xshape_dims));
ctx->ShareLoD("X", "XShape");
}
};
class Flatten2OpMaker : public FlattenOpMaker {
public:
void Make() override {
FlattenOpMaker::Make();
AddOutput("XShape",
"XShape is just used to store the shape and lod of X, which will "
"be used in FlattenGradOp.")
.AsIntermediate();
}
};
GradMaker for dygraph (#19706) * refactor dygraph,test=develop * fix failed unittest,test=develop * polish code,test=develop * check windows ci error,test=develop try to fix windows ci error by np.allclose,test=develop * polish vlog and profiler, test=develop * try to fix preceding ops order,test=develop * test transformer in windows ci, test=develop * use python c-api to speed up tracer.trace,test=develop * test=develop, fix docker with paddle nccl problem * test=develop, add ut for debug string and gradient_accumulator * test=develop, add tests for layer/gradient_accumulator/prepared_op * test=develop, fix complie error for test_prepared_op * test=develop, add more ut for dygraph * test=develop, create API.spec for dygraph api change * optimize grad maker; test=develop * optimize grad maker * test * grad make optim; test=develop * fix unittest bugs; test=develop * add dygraph grad op maker and split_op * grad op maker refactor; test=develop * add dygraph grad maker; test=develop * fix op deformable_conv_v1_op bug; test=develop * fix deformable_conv prroi pool bugs; * fix new op grad op maker bug; test=develop * fix split by ref bug; test=develop * fix dygraph auto prune bug; test=develop * fix test_trace bug; test=develop * fix fused emb seq pool bug; test=develop * remove useless code in op_desc file; test=develop * remove useless code, StrVarBaseNode; test=develop * fix review issues; test=develop * fix rank_loss grad maker; test=develop * remove flag in VarBase; test=develop * fix distributed_notify_op compile bug ; test=develop * fix reshape op double grad; test=develop * fix expand as op; test=develop * add impertive type_defs.h for demo_train; test=develop * fix inference lib cmake; test=develop * fix inference lib; test=develop * fix infernce_lib; test=develop * fix inference cmake; test=develop * fix inference lib; test=develop * fix inference lib; test=develop * remove condition dygraph grad maker, modify local name; test=develop * fix split grad maker bug; test=develop * fix pyramid_op bug; test=develop * change travis time out limit; test=develop * restore travis; test=develop * change timeout limit; test=develop
5 years ago
template <typename T>
class Flatten2GradOpMaker : public framework::SingleGradOpMaker<T> {
public:
GradMaker for dygraph (#19706) * refactor dygraph,test=develop * fix failed unittest,test=develop * polish code,test=develop * check windows ci error,test=develop try to fix windows ci error by np.allclose,test=develop * polish vlog and profiler, test=develop * try to fix preceding ops order,test=develop * test transformer in windows ci, test=develop * use python c-api to speed up tracer.trace,test=develop * test=develop, fix docker with paddle nccl problem * test=develop, add ut for debug string and gradient_accumulator * test=develop, add tests for layer/gradient_accumulator/prepared_op * test=develop, fix complie error for test_prepared_op * test=develop, add more ut for dygraph * test=develop, create API.spec for dygraph api change * optimize grad maker; test=develop * optimize grad maker * test * grad make optim; test=develop * fix unittest bugs; test=develop * add dygraph grad op maker and split_op * grad op maker refactor; test=develop * add dygraph grad maker; test=develop * fix op deformable_conv_v1_op bug; test=develop * fix deformable_conv prroi pool bugs; * fix new op grad op maker bug; test=develop * fix split by ref bug; test=develop * fix dygraph auto prune bug; test=develop * fix test_trace bug; test=develop * fix fused emb seq pool bug; test=develop * remove useless code in op_desc file; test=develop * remove useless code, StrVarBaseNode; test=develop * fix review issues; test=develop * fix rank_loss grad maker; test=develop * remove flag in VarBase; test=develop * fix distributed_notify_op compile bug ; test=develop * fix reshape op double grad; test=develop * fix expand as op; test=develop * add impertive type_defs.h for demo_train; test=develop * fix inference lib cmake; test=develop * fix inference lib; test=develop * fix infernce_lib; test=develop * fix inference cmake; test=develop * fix inference lib; test=develop * fix inference lib; test=develop * remove condition dygraph grad maker, modify local name; test=develop * fix split grad maker bug; test=develop * fix pyramid_op bug; test=develop * change travis time out limit; test=develop * restore travis; test=develop * change timeout limit; test=develop
5 years ago
using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
void Apply(GradOpPtr<T> grad_op) const override {
grad_op->SetType("flatten2_grad");
GradMaker for dygraph (#19706) * refactor dygraph,test=develop * fix failed unittest,test=develop * polish code,test=develop * check windows ci error,test=develop try to fix windows ci error by np.allclose,test=develop * polish vlog and profiler, test=develop * try to fix preceding ops order,test=develop * test transformer in windows ci, test=develop * use python c-api to speed up tracer.trace,test=develop * test=develop, fix docker with paddle nccl problem * test=develop, add ut for debug string and gradient_accumulator * test=develop, add tests for layer/gradient_accumulator/prepared_op * test=develop, fix complie error for test_prepared_op * test=develop, add more ut for dygraph * test=develop, create API.spec for dygraph api change * optimize grad maker; test=develop * optimize grad maker * test * grad make optim; test=develop * fix unittest bugs; test=develop * add dygraph grad op maker and split_op * grad op maker refactor; test=develop * add dygraph grad maker; test=develop * fix op deformable_conv_v1_op bug; test=develop * fix deformable_conv prroi pool bugs; * fix new op grad op maker bug; test=develop * fix split by ref bug; test=develop * fix dygraph auto prune bug; test=develop * fix test_trace bug; test=develop * fix fused emb seq pool bug; test=develop * remove useless code in op_desc file; test=develop * remove useless code, StrVarBaseNode; test=develop * fix review issues; test=develop * fix rank_loss grad maker; test=develop * remove flag in VarBase; test=develop * fix distributed_notify_op compile bug ; test=develop * fix reshape op double grad; test=develop * fix expand as op; test=develop * add impertive type_defs.h for demo_train; test=develop * fix inference lib cmake; test=develop * fix inference lib; test=develop * fix infernce_lib; test=develop * fix inference cmake; test=develop * fix inference lib; test=develop * fix inference lib; test=develop * remove condition dygraph grad maker, modify local name; test=develop * fix split grad maker bug; test=develop * fix pyramid_op bug; test=develop * change travis time out limit; test=develop * restore travis; test=develop * change timeout limit; test=develop
5 years ago
grad_op->SetInput("XShape", this->Output("XShape"));
grad_op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
grad_op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
grad_op->SetAttrMap(this->Attrs());
}
};
class Flatten2GradOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext *context) const override {
OP_INOUT_CHECK(context->HasInput("XShape"), "Input", "XShape",
"Flatten2Grad");
OP_INOUT_CHECK(context->HasInput(framework::GradVarName("Out")), "Input",
framework::GradVarName("Out"), "Flatten2Grad");
auto xshape_dims = context->GetInputDim("XShape");
auto x_dims = framework::slice_ddim(xshape_dims, 1, xshape_dims.size());
context->SetOutputDim(framework::GradVarName("X"), x_dims);
context->ShareLoD("XShape", framework::GradVarName("X"));
}
protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext &ctx) const override {
return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType(
ctx, framework::GradVarName("Out")),
ctx.device_context());
}
};
DECLARE_INPLACE_OP_INFERER(FlattenOpInplaceInferer, {"X", "Out"});
DECLARE_INPLACE_OP_INFERER(FlattenGradInplaceInferer,
{framework::GradVarName("Out"),
framework::GradVarName("X")});
DECLARE_NO_NEED_BUFFER_VARS_INFERER(FlattenGradNoNeedBufferVarsInferer, "X");
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(flatten, ops::FlattenOp, ops::FlattenOpMaker,
ops::FlattenGradOpMaker<paddle::framework::OpDesc>,
ops::FlattenGradOpMaker<paddle::imperative::OpBase>,
ops::FlattenOpInplaceInferer);
REGISTER_OPERATOR(flatten_grad, ops::FlattenGradOp,
ops::FlattenGradInplaceInferer,
ops::FlattenGradNoNeedBufferVarsInferer);
REGISTER_OPERATOR(flatten2, ops::Flatten2Op, ops::Flatten2OpMaker,
GradMaker for dygraph (#19706) * refactor dygraph,test=develop * fix failed unittest,test=develop * polish code,test=develop * check windows ci error,test=develop try to fix windows ci error by np.allclose,test=develop * polish vlog and profiler, test=develop * try to fix preceding ops order,test=develop * test transformer in windows ci, test=develop * use python c-api to speed up tracer.trace,test=develop * test=develop, fix docker with paddle nccl problem * test=develop, add ut for debug string and gradient_accumulator * test=develop, add tests for layer/gradient_accumulator/prepared_op * test=develop, fix complie error for test_prepared_op * test=develop, add more ut for dygraph * test=develop, create API.spec for dygraph api change * optimize grad maker; test=develop * optimize grad maker * test * grad make optim; test=develop * fix unittest bugs; test=develop * add dygraph grad op maker and split_op * grad op maker refactor; test=develop * add dygraph grad maker; test=develop * fix op deformable_conv_v1_op bug; test=develop * fix deformable_conv prroi pool bugs; * fix new op grad op maker bug; test=develop * fix split by ref bug; test=develop * fix dygraph auto prune bug; test=develop * fix test_trace bug; test=develop * fix fused emb seq pool bug; test=develop * remove useless code in op_desc file; test=develop * remove useless code, StrVarBaseNode; test=develop * fix review issues; test=develop * fix rank_loss grad maker; test=develop * remove flag in VarBase; test=develop * fix distributed_notify_op compile bug ; test=develop * fix reshape op double grad; test=develop * fix expand as op; test=develop * add impertive type_defs.h for demo_train; test=develop * fix inference lib cmake; test=develop * fix inference lib; test=develop * fix infernce_lib; test=develop * fix inference cmake; test=develop * fix inference lib; test=develop * fix inference lib; test=develop * remove condition dygraph grad maker, modify local name; test=develop * fix split grad maker bug; test=develop * fix pyramid_op bug; test=develop * change travis time out limit; test=develop * restore travis; test=develop * change timeout limit; test=develop
5 years ago
ops::Flatten2GradOpMaker<paddle::framework::OpDesc>,
ops::Flatten2GradOpMaker<paddle::imperative::OpBase>,
ops::FlattenOpInplaceInferer);
REGISTER_OPERATOR(flatten2_grad, ops::Flatten2GradOp,
ops::FlattenGradInplaceInferer);
REGISTER_OP_CPU_KERNEL(
flatten, ops::FlattenKernel<paddle::platform::CPUDeviceContext, float>,
ops::FlattenKernel<paddle::platform::CPUDeviceContext, double>,
ops::FlattenKernel<paddle::platform::CPUDeviceContext, int>,
ops::FlattenKernel<paddle::platform::CPUDeviceContext, int8_t>,
ops::FlattenKernel<paddle::platform::CPUDeviceContext, int64_t>);
REGISTER_OP_CPU_KERNEL(
flatten_grad,
ops::FlattenGradKernel<paddle::platform::CPUDeviceContext, float>,
ops::FlattenGradKernel<paddle::platform::CPUDeviceContext, double>,
ops::FlattenGradKernel<paddle::platform::CPUDeviceContext, int>,
ops::FlattenGradKernel<paddle::platform::CPUDeviceContext, int8_t>,
ops::FlattenGradKernel<paddle::platform::CPUDeviceContext, int64_t>);
REGISTER_OP_CPU_KERNEL(
flatten2, ops::Flatten2Kernel<paddle::platform::CPUDeviceContext, float>,
ops::Flatten2Kernel<paddle::platform::CPUDeviceContext, double>,
ops::Flatten2Kernel<paddle::platform::CPUDeviceContext, int>,
ops::Flatten2Kernel<paddle::platform::CPUDeviceContext, int8_t>,
ops::Flatten2Kernel<paddle::platform::CPUDeviceContext, int64_t>);
REGISTER_OP_CPU_KERNEL(
flatten2_grad,
ops::Flatten2GradKernel<paddle::platform::CPUDeviceContext, float>,
ops::Flatten2GradKernel<paddle::platform::CPUDeviceContext, double>,
ops::Flatten2GradKernel<paddle::platform::CPUDeviceContext, int>,
ops::Flatten2GradKernel<paddle::platform::CPUDeviceContext, int8_t>,
ops::Flatten2GradKernel<paddle::platform::CPUDeviceContext, int64_t>);