forked from huawei/mindspore2022
114 lines
4.3 KiB
C++
114 lines
4.3 KiB
C++
/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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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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*/
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#include "kernel/cpu/slice_cpu_kernel.h"
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#include "device/cpu/cpu_device_address.h"
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#include "ir/primitive.h"
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namespace mindspore {
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namespace kernel {
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void SliceCPUKernel::InitKernel(const CNodePtr &kernel_node) {
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CheckParam(kernel_node);
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input_shape_ = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0);
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output_shape_ = AnfAlgo::GetOutputInferShape(kernel_node, 0);
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CPUKernelUtils::ExpandDimsTo4(&output_shape_);
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begin_ = AnfAlgo::GetNodeAttr<std::vector<int>>(kernel_node, BEGIN);
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for (size_t i = 0; i < begin_.size(); i++) {
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if (begin_[i] < 0) {
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begin_[i] = begin_[i] + input_shape_[i];
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}
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}
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auto prim = AnfAlgo::GetCNodePrimitive(kernel_node);
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MS_EXCEPTION_IF_NULL(prim);
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auto strides = prim->GetAttr(STRIDES);
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if (strides != nullptr) {
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strides_ = AnfAlgo::GetNodeAttr<std::vector<int>>(kernel_node, STRIDES);
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end_ = AnfAlgo::GetNodeAttr<std::vector<int>>(kernel_node, END);
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if (strides_.size() != end_.size() || strides_.size() != input_shape_.size()) {
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MS_LOG(EXCEPTION) << "stride|end|input size must be equal";
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}
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for (size_t i = 0; i < strides_.size(); ++i) {
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if (strides_[i] < 0) {
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strides_[i] = (strides_[i] + input_shape_[i]) > 0 ? (strides_[i] + input_shape_[i]) : 0;
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}
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if (end_[i] < 0) {
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end_[i] = (end_[i] + input_shape_[i]) > 0 ? (end_[i] + input_shape_[i]) : 0;
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}
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}
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} else {
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auto sizes = AnfAlgo::GetNodeAttr<std::vector<int>>(kernel_node, SIZE);
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if (sizes.size() != input_shape_.size() || begin_.size() != input_shape_.size()) {
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MS_LOG(EXCEPTION) << "begin|size|input size must be equal";
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}
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for (size_t i = 0; i < sizes.size(); ++i) {
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if (sizes[i] < 0) {
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sizes[i] = (sizes[i] + input_shape_[i]) > 0 ? (sizes[i] + input_shape_[i]) : 0;
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}
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strides_.emplace_back(1);
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end_.emplace_back(begin_[i] + sizes[i]);
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}
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}
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auto input_len = input_shape_.size();
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if (input_len < 4) {
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for (size_t i = 0; i < 4 - input_len; ++i) {
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input_shape_.insert(input_shape_.begin(), 1);
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begin_.insert(begin_.begin(), 0);
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strides_.insert(strides_.begin(), 1);
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end_.insert(end_.begin(), 1);
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}
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}
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}
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bool SliceCPUKernel::Launch(const std::vector<kernel::AddressPtr> &inputs,
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const std::vector<kernel::AddressPtr> & /*workspace*/,
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const std::vector<kernel::AddressPtr> &outputs) {
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auto input_addr = reinterpret_cast<float *>(inputs[0]->addr);
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auto output_addr = reinterpret_cast<float *>(outputs[0]->addr);
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for (int i = begin_[0]; i < end_[0]; i += strides_[0]) {
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for (int j = begin_[1]; j < end_[1]; j += strides_[1]) {
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for (int k = begin_[2]; k < end_[2]; k += strides_[2]) {
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for (int m = begin_[3]; m < end_[3]; m += strides_[3]) {
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auto offset = CPUKernelUtils::CalcOffset(input_shape_, i, j, k, m);
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*output_addr++ = input_addr[offset];
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}
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}
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}
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}
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return true;
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}
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void SliceCPUKernel::CheckParam(const CNodePtr &kernel_node) {
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size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
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if (input_num != 1) {
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MS_LOG(EXCEPTION) << "Input number is " << input_num << ", but SliceCPUKernel needs 1 inputs.";
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}
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size_t output_num = AnfAlgo::GetOutputTensorNum(kernel_node);
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if (output_num != 1) {
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MS_LOG(EXCEPTION) << "Output number is " << output_num << ", but SliceCPUKernel needs 1 output.";
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}
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auto input_shape = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0);
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if (input_shape.size() > 4) {
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MS_LOG(EXCEPTION) << "Input dims is " << input_shape.size() << ", but SliceCPUKernel olny support 4d or lower.";
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}
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if (input_shape.size() == 0) {
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MS_LOG(EXCEPTION) << "Input dims is " << input_shape.size() << ", scalar is not supported.";
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}
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}
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} // namespace kernel
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} // namespace mindspore
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