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// Copyright 2019 Yan Yan
//
// 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 "pytorch_cpp_helper.hpp"
#include "pytorch_device_registry.hpp"
template <unsigned NDim>
std::vector<torch::Tensor> GetIndicePairsForwardCUDAKernelLauncher(
torch::Tensor indices, int64_t batchSize,
std::vector<int64_t> outSpatialShape, std::vector<int64_t> spatialShape,
std::vector<int64_t> kernelSize, std::vector<int64_t> stride,
std::vector<int64_t> padding, std::vector<int64_t> dilation,
std::vector<int64_t> outPadding, int64_t _subM, int64_t _transpose);
template <unsigned NDim>
std::vector<torch::Tensor> get_indice_pairs_forward_cuda(
torch::Tensor indices, int64_t batchSize,
std::vector<int64_t> outSpatialShape, std::vector<int64_t> spatialShape,
std::vector<int64_t> kernelSize, std::vector<int64_t> stride,
std::vector<int64_t> padding, std::vector<int64_t> dilation,
std::vector<int64_t> outPadding, int64_t _subM, int64_t _transpose) {
return GetIndicePairsForwardCUDAKernelLauncher<NDim>(
indices, batchSize, outSpatialShape, spatialShape, kernelSize, stride,
padding, dilation, outPadding, _subM, _transpose);
};
template <unsigned NDim>
std::vector<torch::Tensor> GetIndicePairsForwardMLUKernelLauncher(
torch::Tensor indices, int64_t batchSize,
std::vector<int64_t> outSpatialShape, std::vector<int64_t> spatialShape,
std::vector<int64_t> kernelSize, std::vector<int64_t> stride,
std::vector<int64_t> padding, std::vector<int64_t> dilation,
std::vector<int64_t> outPadding, int64_t _subM, int64_t _transpose);
template <unsigned NDim>
std::vector<torch::Tensor> get_indice_pairs_forward_mlu(
torch::Tensor indices, int64_t batchSize,
std::vector<int64_t> outSpatialShape, std::vector<int64_t> spatialShape,
std::vector<int64_t> kernelSize, std::vector<int64_t> stride,
std::vector<int64_t> padding, std::vector<int64_t> dilation,
std::vector<int64_t> outPadding, int64_t _subM, int64_t _transpose) {
return GetIndicePairsForwardMLUKernelLauncher<NDim>(
indices, batchSize, outSpatialShape, spatialShape, kernelSize, stride,
padding, dilation, outPadding, _subM, _transpose);
}
template <unsigned NDim>
std::vector<torch::Tensor> GetIndicePairsBackwardCUDAKernelLauncher(
torch::Tensor indices, torch::Tensor gridOut, int64_t batchSize,
std::vector<int64_t> outSpatialShape, std::vector<int64_t> spatialShape,
std::vector<int64_t> kernelSize, std::vector<int64_t> stride,
std::vector<int64_t> padding, std::vector<int64_t> dilation,
std::vector<int64_t> outPadding, int64_t _subM, int64_t _transpose);
template <unsigned NDim>
std::vector<torch::Tensor> get_indice_pairs_backward_cuda(
torch::Tensor indices, torch::Tensor gridOut, int64_t batchSize,
std::vector<int64_t> outSpatialShape, std::vector<int64_t> spatialShape,
std::vector<int64_t> kernelSize, std::vector<int64_t> stride,
std::vector<int64_t> padding, std::vector<int64_t> dilation,
std::vector<int64_t> outPadding, int64_t _subM, int64_t _transpose) {
return GetIndicePairsBackwardCUDAKernelLauncher<NDim>(
indices, gridOut, batchSize, outSpatialShape, spatialShape, kernelSize,
stride, padding, dilation, outPadding, _subM, _transpose);
};
template <unsigned NDim>
std::vector<torch::Tensor> get_indice_pairs_forward(
torch::Tensor indices, int64_t batchSize,
std::vector<int64_t> outSpatialShape, std::vector<int64_t> spatialShape,
std::vector<int64_t> kernelSize, std::vector<int64_t> stride,
std::vector<int64_t> padding, std::vector<int64_t> dilation,
std::vector<int64_t> outPadding, int64_t _subM, int64_t _transpose) {
if (indices.device().is_cuda()) {
#ifdef MMCV_WITH_CUDA
CHECK_CUDA_INPUT(indices);
return get_indice_pairs_forward_cuda<NDim>(
indices, batchSize, outSpatialShape, spatialShape, kernelSize, stride,
padding, dilation, outPadding, _subM, _transpose);
#else
AT_ERROR("get_indice_pairs is not compiled with GPU support");
#endif
#ifdef MMCV_WITH_MLU
} else if (indices.device().type() == at::kMLU) {
return get_indice_pairs_forward_mlu<NDim>(
indices, batchSize, outSpatialShape, spatialShape, kernelSize, stride,
padding, dilation, outPadding, _subM, _transpose);
#endif
} else {
AT_ERROR("get_indice_pairs is not implemented on CPU");
}
}
template <unsigned NDim>
std::vector<torch::Tensor> get_indice_pairs_backward(
torch::Tensor indices, torch::Tensor gridOut, int64_t batchSize,
std::vector<int64_t> outSpatialShape, std::vector<int64_t> spatialShape,
std::vector<int64_t> kernelSize, std::vector<int64_t> stride,
std::vector<int64_t> padding, std::vector<int64_t> dilation,
std::vector<int64_t> outPadding, int64_t _subM, int64_t _transpose) {
if (indices.device().is_cuda()) {
#ifdef MMCV_WITH_CUDA
CHECK_CUDA_INPUT(indices);
CHECK_CUDA_INPUT(gridOut);
return get_indice_pairs_backward_cuda<NDim>(
indices, gridOut, batchSize, outSpatialShape, spatialShape, kernelSize,
stride, padding, dilation, outPadding, _subM, _transpose);
#else
AT_ERROR("get_indice_pairs is not compiled with GPU support");
#endif
} else {
AT_ERROR("get_indice_pairs is not implemented on CPU");
}
}
torch::Tensor indice_conv_forward_impl(torch::Tensor features,
torch::Tensor filters,
torch::Tensor indicePairs,
torch::Tensor indiceNum,
int64_t numActOut, int64_t _inverse,
int64_t _subM) {
return DISPATCH_DEVICE_IMPL(indice_conv_forward_impl, features, filters,
indicePairs, indiceNum, numActOut, _inverse,
_subM);
}
torch::Tensor indice_conv_forward(torch::Tensor features, torch::Tensor filters,
torch::Tensor indicePairs,
torch::Tensor indiceNum, int64_t numActOut,
int64_t _inverse, int64_t _subM) {
return indice_conv_forward_impl(features, filters, indicePairs, indiceNum,
numActOut, _inverse, _subM);
}
std::vector<torch::Tensor> indice_conv_backward_impl(
torch::Tensor features, torch::Tensor filters, torch::Tensor outGrad,
torch::Tensor indicePairs, torch::Tensor indiceNum, int64_t _inverse,
int64_t _subM) {
return DISPATCH_DEVICE_IMPL(indice_conv_backward_impl, features, filters,
outGrad, indicePairs, indiceNum, _inverse, _subM);
}
std::vector<torch::Tensor> indice_conv_backward(
torch::Tensor features, torch::Tensor filters, torch::Tensor outGrad,
torch::Tensor indicePairs, torch::Tensor indiceNum, int64_t _inverse,
int64_t _subM) {
return indice_conv_backward_impl(features, filters, outGrad, indicePairs,
indiceNum, _inverse, _subM);
}
template std::vector<torch::Tensor> get_indice_pairs_forward<2>(
torch::Tensor indices, int64_t batchSize,
std::vector<int64_t> outSpatialShape, std::vector<int64_t> spatialShape,
std::vector<int64_t> kernelSize, std::vector<int64_t> stride,
std::vector<int64_t> padding, std::vector<int64_t> dilation,
std::vector<int64_t> outPadding, int64_t _subM, int64_t _transpose);
template std::vector<torch::Tensor> get_indice_pairs_forward<3>(
torch::Tensor indices, int64_t batchSize,
std::vector<int64_t> outSpatialShape, std::vector<int64_t> spatialShape,
std::vector<int64_t> kernelSize, std::vector<int64_t> stride,
std::vector<int64_t> padding, std::vector<int64_t> dilation,
std::vector<int64_t> outPadding, int64_t _subM, int64_t _transpose);
template std::vector<torch::Tensor> get_indice_pairs_forward<4>(
torch::Tensor indices, int64_t batchSize,
std::vector<int64_t> outSpatialShape, std::vector<int64_t> spatialShape,
std::vector<int64_t> kernelSize, std::vector<int64_t> stride,
std::vector<int64_t> padding, std::vector<int64_t> dilation,
std::vector<int64_t> outPadding, int64_t _subM, int64_t _transpose);
template std::vector<torch::Tensor> get_indice_pairs_backward<2>(
torch::Tensor indices, torch::Tensor gridOut, int64_t batchSize,
std::vector<int64_t> outSpatialShape, std::vector<int64_t> spatialShape,
std::vector<int64_t> kernelSize, std::vector<int64_t> stride,
std::vector<int64_t> padding, std::vector<int64_t> dilation,
std::vector<int64_t> outPadding, int64_t _subM, int64_t _transpose);
template std::vector<torch::Tensor> get_indice_pairs_backward<3>(
torch::Tensor indices, torch::Tensor gridOut, int64_t batchSize,
std::vector<int64_t> outSpatialShape, std::vector<int64_t> spatialShape,
std::vector<int64_t> kernelSize, std::vector<int64_t> stride,
std::vector<int64_t> padding, std::vector<int64_t> dilation,
std::vector<int64_t> outPadding, int64_t _subM, int64_t _transpose);