wehub-resource-sync
113 lines
3.5 KiB
C++
113 lines
3.5 KiB
C++
// Copyright (c) 2022 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 "paddle/phi/core/dense_tensor.h"
|
|
#include "paddle/phi/core/tensor_utils.h"
|
|
#include "paddle/phi/kernels/funcs/eigen/common.h"
|
|
#include "paddle/phi/kernels/funcs/eigen/eigen_function.h"
|
|
#include "paddle/phi/kernels/meshgrid_kernel.h"
|
|
|
|
namespace phi {
|
|
|
|
template <typename T, typename Context, int Rank>
|
|
void MeshgridForward(const Context& dev_ctx,
|
|
const std::vector<const DenseTensor*>& ins,
|
|
std::vector<DenseTensor*> outs) {
|
|
PADDLE_ENFORCE_GT(
|
|
ins.size(),
|
|
0,
|
|
common::errors::InvalidArgument(
|
|
"Expected at least 1 input tensors, but only received %d.",
|
|
ins.size()));
|
|
|
|
int64_t size = ins.size();
|
|
std::vector<int64_t> shape(size);
|
|
|
|
for (int64_t i = 0; i < size; i++) {
|
|
switch (ins[i]->dims().size()) {
|
|
case 0:
|
|
shape[i] = 1;
|
|
break;
|
|
case 1:
|
|
shape[i] = ins[i]->dims()[0];
|
|
break;
|
|
default:
|
|
PADDLE_THROW(common::errors::InvalidArgument(
|
|
"Expected scalar or 1D tensor in the tensor list but got tensor "
|
|
"%d: ",
|
|
i));
|
|
}
|
|
}
|
|
|
|
for (int64_t i = 0; i < size; i++) {
|
|
std::vector<int64_t> view_shape(size, 1);
|
|
view_shape[i] = shape[i];
|
|
|
|
DenseTensor reshape_ins_tensor;
|
|
Copy(dev_ctx, *ins[i], dev_ctx.GetPlace(), false, &reshape_ins_tensor);
|
|
DDim out_dims_reshape = make_ddim(view_shape);
|
|
reshape_ins_tensor.Resize(out_dims_reshape);
|
|
DDim out_dims = make_ddim(shape);
|
|
|
|
Eigen::DSizes<int64_t, Rank> bcast_dims;
|
|
for (int64_t j = 0; j < size; j++) {
|
|
bcast_dims[j] = shape[j];
|
|
}
|
|
bcast_dims[i] = 1;
|
|
|
|
outs[i]->Resize(out_dims);
|
|
auto x = EigenTensor<T, Rank>::From(
|
|
static_cast<const DenseTensor>(reshape_ins_tensor));
|
|
dev_ctx.template Alloc<T>(outs[i]);
|
|
auto y = EigenTensor<T, Rank>::From(*outs[i]);
|
|
auto& place = *dev_ctx.eigen_device();
|
|
funcs::EigenBroadcast<std::decay_t<decltype(place)>, T, Rank>::Eval(
|
|
place, y, x, bcast_dims);
|
|
}
|
|
}
|
|
|
|
template <typename T, typename Context>
|
|
void MeshgridKernel(const Context& dev_ctx,
|
|
const std::vector<const DenseTensor*>& inputs,
|
|
std::vector<DenseTensor*> outputs) {
|
|
int rank = inputs.size();
|
|
switch (rank) {
|
|
case 1:
|
|
MeshgridForward<T, Context, 1>(dev_ctx, inputs, outputs);
|
|
break;
|
|
case 2:
|
|
MeshgridForward<T, Context, 2>(dev_ctx, inputs, outputs);
|
|
break;
|
|
case 3:
|
|
MeshgridForward<T, Context, 3>(dev_ctx, inputs, outputs);
|
|
break;
|
|
case 4:
|
|
MeshgridForward<T, Context, 4>(dev_ctx, inputs, outputs);
|
|
break;
|
|
case 5:
|
|
MeshgridForward<T, Context, 5>(dev_ctx, inputs, outputs);
|
|
break;
|
|
case 6:
|
|
MeshgridForward<T, Context, 6>(dev_ctx, inputs, outputs);
|
|
break;
|
|
default:
|
|
PADDLE_THROW(common::errors::InvalidArgument(
|
|
"Excepted Tensor numbers between 1 and 6, but only received %d .",
|
|
rank));
|
|
}
|
|
}
|
|
} // namespace phi
|