forked from huawei/mindspore2022
175 lines
7.1 KiB
C++
175 lines
7.1 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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CPUKernelUtils::GetElementNumEveryDim(input_shape_, &input_element_num_);
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CPUKernelUtils::GetElementNumEveryDim(output_shape_, &output_element_num_);
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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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bool can_copy_memory[3] = {CanCopyMemoryOnAxis(0), CanCopyMemoryOnAxis(1), CanCopyMemoryOnAxis(2)};
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size_t in_start_offset[3] = {begin_[0] * input_element_num_[0], begin_[1] * input_element_num_[1],
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begin_[2] * input_element_num_[2]};
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size_t in_step_size[3] = {strides_[0] * input_element_num_[0], strides_[1] * input_element_num_[1],
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strides_[2] * input_element_num_[2]};
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auto in_n_offset = in_start_offset[0];
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auto out_n_offset = 0;
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for (int i = begin_[0]; i < end_[0];
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i += strides_[0], in_n_offset += in_step_size[0], out_n_offset += output_element_num_[0]) {
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if (can_copy_memory[0]) {
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CopyDataToOutput(inputs, in_n_offset, outputs, out_n_offset, input_element_num_[0]);
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continue;
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}
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auto in_c_offset = in_start_offset[1];
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auto out_c_offset = 0;
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for (int j = begin_[1]; j < end_[1];
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j += strides_[1], in_c_offset += in_step_size[1], out_c_offset += output_element_num_[1]) {
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if (can_copy_memory[1]) {
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CopyDataToOutput(inputs, in_n_offset + in_c_offset, outputs, out_n_offset + out_c_offset,
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input_element_num_[1]);
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continue;
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}
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auto in_h_offset = in_start_offset[2];
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auto out_h_offset = 0;
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for (int k = begin_[2]; k < end_[2];
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k += strides_[2], in_h_offset += in_step_size[2], out_h_offset += output_element_num_[2]) {
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if (can_copy_memory[2]) {
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CopyDataToOutput(inputs, in_n_offset + in_c_offset + in_h_offset, outputs,
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out_n_offset + out_c_offset + out_h_offset, input_element_num_[2]);
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continue;
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}
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for (int m = begin_[3]; m < end_[3]; m += strides_[3]) {
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*output_addr++ = input_addr[in_n_offset + in_c_offset + in_h_offset + m];
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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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bool SliceCPUKernel::CanCopyMemoryOnAxis(size_t dim) const {
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for (size_t i = dim + 1; i < 4; ++i) {
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if (begin_[i] != 0 || end_[i] != SizeToInt(input_shape_[i]) || strides_[i] != 1) {
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return false;
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}
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}
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return true;
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}
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void SliceCPUKernel::CopyDataToOutput(const std::vector<kernel::AddressPtr> &inputs, size_t in_offset,
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const std::vector<kernel::AddressPtr> &outputs, size_t out_offset,
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size_t copy_num) const {
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auto input_addr = reinterpret_cast<float *>(inputs[0]->addr);
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auto in_buff_size = inputs[0]->size;
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auto output_addr = reinterpret_cast<float *>(outputs[0]->addr);
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auto out_buff_size = outputs[0]->size;
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if ((in_offset + copy_num) * sizeof(float) > in_buff_size) {
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MS_LOG(EXCEPTION) << "input memory out of bounds.";
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}
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if ((out_offset + copy_num) * sizeof(float) > out_buff_size) {
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MS_LOG(EXCEPTION) << "output memory out of bounds.";
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}
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auto ret = memcpy_s(output_addr + out_offset, out_buff_size - out_offset * sizeof(float), input_addr + in_offset,
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copy_num * sizeof(float));
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if (ret != EOK) {
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MS_LOG(EXCEPTION) << "memcpy failed. ret:" << ret;
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}
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}
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void SliceCPUKernel::CheckParam(const CNodePtr &kernel_node) const {
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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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