/** * Copyright 2020 Huawei Technologies Co., Ltd * * 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 "kernel/cpu/slice_cpu_kernel.h" #include "device/cpu/cpu_device_address.h" namespace mindspore { namespace kernel { void SliceCPUKernel::InitKernel(const CNodePtr &kernel_node) { CheckParam(kernel_node); input_shape_ = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0); output_shape_ = AnfAlgo::GetOutputInferShape(kernel_node, 0); begin_ = AnfAlgo::GetNodeAttr>(kernel_node, BEGIN); for (size_t i = 0; i < begin_.size(); i++) { if (begin_[i] < 0) { begin_[i] = begin_[i] + input_shape_[i]; } } auto prim = AnfAlgo::GetCNodePrimitive(kernel_node); MS_EXCEPTION_IF_NULL(prim); auto strides = prim->GetAttr(STRIDES); if (strides != nullptr) { strides_ = AnfAlgo::GetNodeAttr>(kernel_node, STRIDES); end_ = AnfAlgo::GetNodeAttr>(kernel_node, END); if (strides_.size() != end_.size() || strides_.size() != input_shape_.size()) { MS_LOG(EXCEPTION) << "stride|end|input size must be equal"; } for (size_t i = 0; i < strides_.size(); ++i) { if (strides_[i] < 0) { strides_[i] = (strides_[i] + input_shape_[i]) > 0 ? (strides_[i] + input_shape_[i]) : 0; } if (end_[i] < 0) { end_[i] = (end_[i] + input_shape_[i]) > 0 ? (end_[i] + input_shape_[i]) : 0; } } } else { auto sizes = AnfAlgo::GetNodeAttr>(kernel_node, SIZE); if (sizes.size() != input_shape_.size() || begin_.size() != input_shape_.size()) { MS_LOG(EXCEPTION) << "begin|size|input size must be equal"; } for (size_t i = 0; i < sizes.size(); ++i) { if (sizes[i] < 0) { sizes[i] = (sizes[i] + input_shape_[i]) > 0 ? (sizes[i] + input_shape_[i]) : 0; } strides_.emplace_back(1); end_.emplace_back(begin_[i] + sizes[i]); } } ExpandAllMemberDims(); CPUKernelUtils::GetElementNumEveryDim(input_shape_, &input_element_num_); CPUKernelUtils::GetElementNumEveryDim(output_shape_, &output_element_num_); } void SliceCPUKernel::ExpandAllMemberDims() { CPUKernelUtils::ExpandDimsTo4(&output_shape_); auto input_len = input_shape_.size(); if (input_len < 4) { for (size_t i = 0; i < 4 - input_len; ++i) { input_shape_.insert(input_shape_.begin(), 1); begin_.insert(begin_.begin(), 0); strides_.insert(strides_.begin(), 1); end_.insert(end_.begin(), 1); } } } bool SliceCPUKernel::Launch(const std::vector &inputs, const std::vector & /*workspace*/, const std::vector &outputs) { auto input_addr = reinterpret_cast(inputs[0]->addr); auto output_addr = reinterpret_cast(outputs[0]->addr); bool can_copy_memory[3] = {CanCopyMemoryOnAxis(0), CanCopyMemoryOnAxis(1), CanCopyMemoryOnAxis(2)}; size_t in_start_offset[3] = {begin_[0] * input_element_num_[0], begin_[1] * input_element_num_[1], begin_[2] * input_element_num_[2]}; size_t in_step_size[3] = {strides_[0] * input_element_num_[0], strides_[1] * input_element_num_[1], strides_[2] * input_element_num_[2]}; auto in_n_offset = in_start_offset[0]; auto out_n_offset = 0; for (int i = begin_[0]; i < end_[0]; i += strides_[0], in_n_offset += in_step_size[0], out_n_offset += output_element_num_[0]) { if (can_copy_memory[0]) { CopyDataToOutput(inputs, in_n_offset, outputs, out_n_offset, input_element_num_[0]); continue; } auto in_c_offset = in_start_offset[1]; auto out_c_offset = 0; for (int j = begin_[1]; j < end_[1]; j += strides_[1], in_c_offset += in_step_size[1], out_c_offset += output_element_num_[1]) { if (can_copy_memory[1]) { CopyDataToOutput(inputs, in_n_offset + in_c_offset, outputs, out_n_offset + out_c_offset, input_element_num_[1]); continue; } auto in_h_offset = in_start_offset[2]; auto out_h_offset = 0; for (int k = begin_[2]; k < end_[2]; k += strides_[2], in_h_offset += in_step_size[2], out_h_offset += output_element_num_[2]) { if (can_copy_memory[2]) { CopyDataToOutput(inputs, in_n_offset + in_c_offset + in_h_offset, outputs, out_n_offset + out_c_offset + out_h_offset, input_element_num_[2]); continue; } for (int m = begin_[3]; m < end_[3]; m += strides_[3]) { *output_addr++ = input_addr[in_n_offset + in_c_offset + in_h_offset + m]; } } } } return true; } bool SliceCPUKernel::CanCopyMemoryOnAxis(size_t dim) const { for (size_t i = dim + 1; i < 4; ++i) { if (begin_[i] != 0 || end_[i] != SizeToInt(input_shape_[i]) || strides_[i] != 1) { return false; } } return true; } void SliceCPUKernel::CopyDataToOutput(const std::vector &inputs, size_t in_offset, const std::vector &outputs, size_t out_offset, size_t copy_num) const { auto input_addr = reinterpret_cast(inputs[0]->addr); auto in_buff_size = inputs[0]->size; auto output_addr = reinterpret_cast(outputs[0]->addr); auto out_buff_size = outputs[0]->size; if ((in_offset + copy_num) * sizeof(float) > in_buff_size) { MS_LOG(EXCEPTION) << "input memory out of bounds."; } if ((out_offset + copy_num) * sizeof(float) > out_buff_size) { MS_LOG(EXCEPTION) << "output memory out of bounds."; } auto ret = memcpy_s(output_addr + out_offset, out_buff_size - out_offset * sizeof(float), input_addr + in_offset, copy_num * sizeof(float)); if (ret != EOK) { MS_LOG(EXCEPTION) << "memcpy failed. ret:" << ret; } } void SliceCPUKernel::CheckParam(const CNodePtr &kernel_node) const { size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node); if (input_num != 1) { MS_LOG(EXCEPTION) << "Input number is " << input_num << ", but SliceCPUKernel needs 1 inputs."; } size_t output_num = AnfAlgo::GetOutputTensorNum(kernel_node); if (output_num != 1) { MS_LOG(EXCEPTION) << "Output number is " << output_num << ", but SliceCPUKernel needs 1 output."; } auto input_shape = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0); if (input_shape.size() > 4) { MS_LOG(EXCEPTION) << "Input dims is " << input_shape.size() << ", but SliceCPUKernel olny support 4d or lower."; } if (input_shape.size() == 0) { MS_LOG(EXCEPTION) << "Input dims is " << input_shape.size() << ", scalar is not supported."; } } } // namespace kernel } // namespace mindspore