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data_layout_transform.cc
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// Copyright (c) 2018 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/framework/data_layout_transform.h"
#include "paddle/phi/core/utils/data_type.h"
#include "paddle/phi/kernels/funcs/math_function.h"
namespace paddle {
namespace framework {
std::vector<int> GetAxis(const DataLayout& from, const DataLayout& to) {
PADDLE_ENFORCE_NE(
from,
to,
platform::errors::InvalidArgument(
"Layout transform should transform between different layout."));
if (from == DataLayout::kNCHW && to == DataLayout::kNHWC) {
return {0, 2, 3, 1};
} else if (from == DataLayout::kNHWC && to == DataLayout::kNCHW) {
return {0, 3, 1, 2};
} else {
PADDLE_THROW(
platform::errors::InvalidArgument("Unsupported layout transform."));
}
}
template <typename T>
void CastDataLayout::apply() {
auto place = ctx_->GetPlace();
if (platform::is_cpu_place(place)) {
phi::funcs::Transpose<phi::CPUContext, T, 4> trans4;
auto* context = static_cast<const phi::CPUContext*>(ctx_);
trans4(*context, in_, out_, axis_);
} else {
PADDLE_THROW(platform::errors::PreconditionNotMet(
"Unsupported data layout cast from CPU to GPU."));
}
}
void TransDataLayout(const phi::KernelKey& kernel_type_for_var,
const phi::KernelKey& expected_kernel_type,
const phi::DenseTensor& in,
phi::DenseTensor* out,
const phi::Place& place) {
PADDLE_ENFORCE(
backends_are_same_class(kernel_type_for_var.backend(),
expected_kernel_type.backend()),
platform::errors::PreconditionNotMet(
"TransDataLayout only support DataLayout transform on same place."));
TransDataLayout(kernel_type_for_var.layout(),
expected_kernel_type.layout(),
place,
in,
out);
}
void TransDataLayout(DataLayout from_layout,
DataLayout to_layout,
phi::Place place,
const phi::DenseTensor& in,
phi::DenseTensor* out) {
PADDLE_ENFORCE_EQ(
arity(in.dims()),
4,
platform::errors::InvalidArgument(
"Input dimension arity only can be 4, the input dimension is %s.",
in.dims()));
auto& pool = platform::DeviceContextPool::Instance();
auto src_dim = in.dims();
std::vector<int64_t> dst_dim;
auto axis = GetAxis(from_layout, to_layout);
dst_dim.resize(axis.size());
for (size_t i = 0; i < axis.size(); i++) {
dst_dim[i] = src_dim[axis[i]];
}
out->Resize(phi::make_ddim(dst_dim));
out->mutable_data(place, in.dtype());
framework::VisitDataType(
static_cast<proto::VarType::Type>(phi::TransToProtoVarType(in.dtype())),
CastDataLayout(pool.Get(place), axis, in, out));
out->set_layout(to_layout);
}
} // namespace framework
} // namespace paddle