You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
117 lines
3.9 KiB
117 lines
3.9 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. */
|
|
|
|
#pragma once
|
|
#include <vector>
|
|
#include "paddle/fluid/framework/op_registry.h"
|
|
#include "paddle/fluid/operators/math/blas.h"
|
|
#include "paddle/fluid/operators/math/math_function.h"
|
|
#include "paddle/fluid/operators/math/pooling.h"
|
|
#include "paddle/fluid/platform/device_context.h"
|
|
|
|
namespace paddle {
|
|
namespace operators {
|
|
|
|
template <typename DeviceContext, typename T>
|
|
class FlattenKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext &context) const override {
|
|
auto *in = context.Input<framework::LoDTensor>("X");
|
|
auto *out = context.Output<framework::LoDTensor>("Out");
|
|
|
|
auto &axes = context.Attr<int>("axis");
|
|
auto x_dims = in->dims();
|
|
auto out_dims = framework::make_ddim(GetOutputShape(axes, x_dims));
|
|
|
|
out->mutable_data(context.GetPlace(), in->type());
|
|
framework::TensorCopy(
|
|
*in, context.GetPlace(),
|
|
context.template device_context<platform::DeviceContext>(), out);
|
|
out->Resize(out_dims);
|
|
}
|
|
|
|
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;
|
|
}
|
|
};
|
|
|
|
template <typename DeviceContext, typename T>
|
|
class FlattenGradKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext &ctx) const override {
|
|
auto *d_x = ctx.Output<framework::LoDTensor>(framework::GradVarName("X"));
|
|
auto *d_out =
|
|
ctx.Input<framework::LoDTensor>(framework::GradVarName("Out"));
|
|
auto in_dims = ctx.Input<framework::LoDTensor>("X")->dims();
|
|
|
|
d_x->mutable_data(ctx.GetPlace(), d_out->type());
|
|
framework::TensorCopySync(*d_out, ctx.GetPlace(), d_x);
|
|
d_x->Resize(in_dims);
|
|
}
|
|
};
|
|
|
|
template <typename DeviceContext, typename T>
|
|
class Flatten2Kernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext &context) const override {
|
|
auto &axes = context.Attr<int>("axis");
|
|
|
|
auto *in = context.Input<framework::LoDTensor>("X");
|
|
auto x_dims = in->dims();
|
|
|
|
auto *out = context.Output<framework::LoDTensor>("Out");
|
|
|
|
auto out_dims = framework::make_ddim(
|
|
FlattenKernel<DeviceContext, T>::GetOutputShape(axes, x_dims));
|
|
|
|
out->mutable_data(context.GetPlace(), in->type());
|
|
framework::TensorCopy(
|
|
*in, context.GetPlace(),
|
|
context.template device_context<platform::DeviceContext>(), out);
|
|
out->Resize(out_dims);
|
|
}
|
|
};
|
|
|
|
template <typename DeviceContext, typename T>
|
|
class Flatten2GradKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext &ctx) const override {
|
|
auto *d_x = ctx.Output<framework::LoDTensor>(framework::GradVarName("X"));
|
|
auto *d_out =
|
|
ctx.Input<framework::LoDTensor>(framework::GradVarName("Out"));
|
|
|
|
auto xshape_dims = ctx.Input<framework::LoDTensor>("XShape")->dims();
|
|
auto x_dims = framework::slice_ddim(xshape_dims, 1, xshape_dims.size());
|
|
|
|
d_x->mutable_data(ctx.GetPlace(), d_out->type());
|
|
framework::TensorCopySync(*d_out, ctx.GetPlace(), d_x);
|
|
d_x->Resize(x_dims);
|
|
}
|
|
};
|
|
|
|
} // namespace operators
|
|
} // namespace paddle
|