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| /****************************************************************************** | ||
| * Copyright (c) 2022 Huawei Technologies Co., Ltd | ||
| * All rights reserved. | ||
| * | ||
| * Licensed under the BSD 3-Clause License (the "License"); | ||
| * you may not use this file except in compliance with the License. | ||
| * You may obtain a copy of the License at | ||
| * | ||
| * https://opensource.org/licenses/BSD-3-Clause | ||
| * | ||
| * 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. | ||
| ******************************************************************************/ | ||
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| #ifndef PYTORCH_NPU_HELPER_HPP_ | ||
| #define PYTORCH_NPU_HELPER_HPP_ | ||
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| #include <torch_npu/csrc/aten/NPUNativeFunctions.h> | ||
| #include <torch_npu/csrc/framework/utils/CalcuOpUtil.h> | ||
| #include <torch_npu/csrc/framework/utils/OpAdapter.h> | ||
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| #include "pytorch_cpp_helper.hpp" | ||
| #include "pytorch_device_registry.hpp" | ||
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| #define NPU_NAME_SPACE at_npu::native | ||
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| #define REGISTER_NPU_IMPL(key, value) REGISTER_DEVICE_IMPL(key, XLA, value) | ||
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| #define CHECK_NPU(x) \ | ||
| TORCH_CHECK(x.device().type() == at::kXLA, #x " must be a NPU tensor") | ||
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| #endif // PYTORCH_NPU_HELPER_HPP_ |
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| #include "pytorch_npu_helper.hpp" | ||
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| using namespace NPU_NAME_SPACE; | ||
| using namespace std; | ||
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| void deform_roi_pool_forward_impl(Tensor input, Tensor rois, Tensor offset, | ||
| Tensor output, int pooled_height, | ||
| int pooled_width, float spatial_scale, | ||
| int sampling_ratio, float gamma); | ||
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| void deform_roi_pool_backward_impl(Tensor grad_output, Tensor input, | ||
| Tensor rois, Tensor offset, | ||
| Tensor grad_input, Tensor grad_offset, | ||
| int pooled_height, int pooled_width, | ||
| float spatial_scale, int sampling_ratio, | ||
| float gamma); | ||
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| void deform_roi_pool_forward_npu(Tensor input, Tensor rois, Tensor offset, | ||
| Tensor output, int pooled_height, | ||
| int pooled_width, float spatial_scale, | ||
| int sampling_ratio, float gamma) { | ||
| c10::SmallVector<int64_t, 2> output_sizes = {pooled_height, pooled_width}; | ||
| at::IntArrayRef output_size = at::IntArrayRef(output_sizes); | ||
| int64_t sampling_ratio_ = (int64_t)sampling_ratio; | ||
| OpCommand cmd; | ||
| cmd.Name("DeformableRoiPool") | ||
| .Input(input) | ||
| .Input(rois) | ||
| .Input(offset) | ||
| .Output(output) | ||
| .Attr("spatial_scale", spatial_scale) | ||
| .Attr("output_size", output_size) | ||
| .Attr("sampling_ratio", sampling_ratio_) | ||
| .Attr("gamma", gamma) | ||
| .Run(); | ||
| } | ||
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| void deform_roi_pool_backward_npu(Tensor grad_output, Tensor input, Tensor rois, | ||
| Tensor offset, Tensor grad_input, | ||
| Tensor grad_offset, int pooled_height, | ||
| int pooled_width, float spatial_scale, | ||
| int sampling_ratio, float gamma) { | ||
| c10::SmallVector<int64_t, 2> output_sizes = {pooled_height, pooled_width}; | ||
| at::IntArrayRef output_size = at::IntArrayRef(output_sizes); | ||
| int64_t sampling_ratio_ = (int64_t)sampling_ratio; | ||
| OpCommand cmd; | ||
| cmd.Name("DeformableRoiPoolGrad") | ||
| .Input(grad_input) | ||
| .Input(input) | ||
| .Input(rois) | ||
| .Input(offset) | ||
| .Output(grad_output) | ||
| .Output(grad_offset) | ||
| .Attr("output_size", output_size) | ||
| .Attr("spatial_scale", spatial_scale) | ||
| .Attr("sample_ratio", sampling_ratio_) | ||
| .Attr("gamma", gamma) | ||
| .Run(); | ||
| } | ||
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| REGISTER_NPU_IMPL(deform_roi_pool_forward_impl, deform_roi_pool_forward_npu); | ||
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| REGISTER_NPU_IMPL(deform_roi_pool_backward_impl, deform_roi_pool_backward_npu); |
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