wehub-resource-sync
141 lines
5.2 KiB
C++
141 lines
5.2 KiB
C++
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/phi/kernels/strided_slice_kernel.h"
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#include "glog/logging.h"
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#include "paddle/phi/kernels/funcs/slice_utils.h"
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#include "paddle/common/flags.h"
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#include "paddle/phi/backends/all_context.h"
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#include "paddle/phi/core/kernel_registry.h"
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COMMON_DECLARE_bool(use_stride_kernel);
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namespace phi {
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template <typename Context>
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void StridedSliceRawStridedKernel(const Context& dev_ctx,
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const DenseTensor& input,
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const std::vector<int>& axes,
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const IntArray& starts_arr,
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const IntArray& ends_arr,
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const IntArray& strides_arr,
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const std::vector<int>& infer_flags,
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const std::vector<int>& decrease_axis,
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DenseTensor* out) {
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if (!FLAGS_use_stride_kernel) {
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PADDLE_THROW(common::errors::Fatal(
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"FLAGS_use_stride_kernel is closed. Strided kernel "
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"be called, something wrong has happened!"));
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}
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std::vector<int64_t> starts = starts_arr.GetData();
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std::vector<int64_t> ends = ends_arr.GetData();
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std::vector<int64_t> strides = strides_arr.GetData();
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std::vector<int64_t> output_dims = vectorize<int64_t>(input.dims());
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std::vector<int64_t> output_stride = vectorize<int64_t>(input.strides());
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int64_t output_offset = static_cast<int64_t>(input.offset());
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for (size_t i = 0; i < axes.size(); ++i) {
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int64_t axis_size = input.dims()[axes[i]];
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if (axis_size < 0) {
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continue;
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}
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bool dummy_zero_dim_out = false;
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funcs::normalize_interval(starts[i],
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ends[i],
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strides[i],
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axis_size,
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&starts[i],
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&ends[i],
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&dummy_zero_dim_out);
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if (ends[i] == -axis_size - 1) {
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ends[i] = -1;
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}
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int64_t step_size = std::abs(strides[i]);
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auto out_dim = (std::abs(ends[i] - starts[i]) + step_size - 1) / step_size;
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output_offset += starts[i] * output_stride[axes[i]] * SizeOf(out->dtype());
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output_dims[axes[i]] = out_dim;
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output_stride[axes[i]] *= strides[i];
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}
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// generate new shape
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if (!decrease_axis.empty()) {
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std::vector<int64_t> new_out_shape;
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std::vector<int64_t> new_out_stride;
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for (auto de_axis : decrease_axis) {
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output_dims[de_axis] = 0;
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}
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for (size_t i = 0; i < output_dims.size(); ++i) {
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if (output_dims[i] != 0) {
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new_out_shape.push_back(output_dims[i]);
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new_out_stride.push_back(output_stride[i]);
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}
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}
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output_dims = new_out_shape;
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output_stride = new_out_stride;
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}
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auto meta = out->meta();
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meta.offset = output_offset;
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auto tmp_dim = DDim(output_dims.data(), static_cast<int>(output_dims.size()));
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// if (product(meta.dims) > 0 && meta.dims != tmp_dim) {
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// PADDLE_THROW(
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// common::errors::Fatal("strided_slice kernel stride compute diff,
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// infer "
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// "shape is %s, but compute is %s.",
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// meta.dims,
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// tmp_dim));
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// }
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meta.dims = tmp_dim;
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meta.strides =
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DDim(output_stride.data(), static_cast<int>(output_stride.size()));
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out->set_meta(meta);
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out->ResetHolder(input.Holder());
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out->ShareInplaceVersionCounterWith(input);
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}
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template <typename Context>
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void StridedSliceStridedKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const std::vector<int>& axes,
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const IntArray& starts,
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const IntArray& ends,
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const IntArray& strides,
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DenseTensor* out) {
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if (!FLAGS_use_stride_kernel) {
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PADDLE_THROW(common::errors::Fatal(
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"FLAGS_use_stride_kernel is closed. Strided kernel "
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"be called, something wrong has happened!"));
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}
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std::vector<int> infer_flags(axes.size(), 1);
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std::vector<int> decrease_axis;
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StridedSliceRawStridedKernel<Context>(
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dev_ctx, x, axes, starts, ends, strides, infer_flags, decrease_axis, out);
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}
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} // namespace phi
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PD_REGISTER_KERNEL_FOR_ALL_BACKEND_DTYPE(strided_slice_raw,
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STRIDED,
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phi::StridedSliceRawStridedKernel) {}
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PD_REGISTER_KERNEL_FOR_ALL_BACKEND_DTYPE(strided_slice,
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STRIDED,
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phi::StridedSliceStridedKernel) {}
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