forked from mindspore-Ecosystem/mindspore
!6912 generalize CPU Slice op
Merge pull request !6912 from baihuawei/fixslice
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commit
d8cfba8ba6
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@ -22,28 +22,20 @@ 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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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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TransArg();
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for (size_t i = 0; i < begin_.size(); i++) {
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while (begin_[i] < 0) {
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begin_[i] = begin_[i] + input_shape_[i];
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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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if (begin_[i] > SizeToInt(input_shape_[i])) {
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begin_[i] = input_shape_[i];
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}
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}
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} else {
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@ -51,23 +43,34 @@ void SliceCPUKernel::InitKernel(const CNodePtr &kernel_node) {
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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 < begin_.size(); i++) {
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while (begin_[i] < 0) {
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begin_[i] = begin_[i] + input_shape_[i];
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}
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if (begin_[i] > SizeToInt(input_shape_[i])) {
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begin_[i] = input_shape_[i];
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}
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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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while (sizes[i] < 0) {
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sizes[i] = sizes[i] + input_shape_[i];
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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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ExpandAllMemberDims();
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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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void SliceCPUKernel::ExpandAllMemberDims() {
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CPUKernelUtils::ExpandDimsTo4(&output_shape_);
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auto output_len = output_shape_.size();
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if (output_len < 4) {
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for (size_t i = 0; i < 4 - output_len; ++i) {
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output_shape_.push_back(1);
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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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@ -86,6 +89,7 @@ bool SliceCPUKernel::Launch(const std::vector<kernel::AddressPtr> &inputs,
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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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int signstride[4] = {SignOfStride(0), SignOfStride(1), SignOfStride(2), SignOfStride(3)};
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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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@ -93,31 +97,31 @@ bool SliceCPUKernel::Launch(const std::vector<kernel::AddressPtr> &inputs,
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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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for (int i = begin_[0]; signstride[0] * i < signstride[0] * 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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CopyDataToOutput(inputs, in_n_offset, outputs, out_n_offset, input_element_num_[0], 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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for (int j = begin_[1]; signstride[1] * j < signstride[1] * 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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CopyDataToOutput(inputs, in_n_offset + in_c_offset, outputs, out_n_offset + out_c_offset, input_element_num_[1],
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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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for (int k = begin_[2]; signstride[2] * k < signstride[2] * 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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out_n_offset + out_c_offset + out_h_offset, input_element_num_[2], 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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for (int m = begin_[3]; signstride[3] * m < signstride[3] * 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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@ -136,9 +140,15 @@ bool SliceCPUKernel::CanCopyMemoryOnAxis(size_t dim) const {
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return true;
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}
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int SliceCPUKernel::SignOfStride(size_t axis) const {
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if (strides_[axis] > 0) {
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return 1;
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}
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return -1;
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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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size_t copy_num, int id) 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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@ -148,7 +158,7 @@ void SliceCPUKernel::CopyDataToOutput(const std::vector<kernel::AddressPtr> &inp
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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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MS_LOG(EXCEPTION) << id << " 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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@ -158,6 +168,26 @@ void SliceCPUKernel::CopyDataToOutput(const std::vector<kernel::AddressPtr> &inp
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}
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}
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void SliceCPUKernel::TransArg() {
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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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MS_LOG(EXCEPTION) << "slice stride cannot be zero";
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}
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if (end_[i] == 0 && begin_[i] < 0) {
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end_[i] = end_[i] + input_shape_[i];
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}
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while (end_[i] < 0) {
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end_[i] = end_[i] + input_shape_[i];
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}
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if (end_[i] > SizeToInt(input_shape_[i])) {
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end_[i] = input_shape_[i];
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}
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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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@ -35,9 +35,12 @@ class SliceCPUKernel : public CPUKernel {
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private:
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void ExpandAllMemberDims();
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bool CanCopyMemoryOnAxis(size_t dim) const;
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int SignOfStride(size_t axis) const;
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void 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, size_t copy_num) const;
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const std::vector<kernel::AddressPtr> &outputs, size_t out_offset, size_t copy_num,
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int id) const;
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void CheckParam(const CNodePtr &kernel_node) const;
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void TransArg();
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std::vector<int> begin_;
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std::vector<int> end_;
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std::vector<int> strides_;
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@ -72,6 +72,51 @@ def test_slice2():
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assert (output.asnumpy() == expect).all()
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class Slice3(nn.Cell):
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def __init__(self):
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super(Slice3, self).__init__()
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self.relu = nn.ReLU()
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def construct(self, x):
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return (x[..., -1], x[..., 2:1:-1], x[1:3:1, 0, ...], x[-1, 0, ...])
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_slice3():
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inputx = np.random.rand(4, 4, 4, 4).astype(np.float32)
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x = Tensor(inputx)
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slice_op = Slice3()
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output = slice_op(x)
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assert (output[0].asnumpy() == inputx[..., -1]).all()
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assert (output[1].asnumpy() == inputx[..., 2:1:-1]).all()
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assert (output[2].asnumpy() == inputx[1:3:1, 0, ...]).all()
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assert (output[3].asnumpy() == inputx[-1, 0, ...]).all()
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class Slice4(nn.Cell):
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def __init__(self):
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super(Slice4, self).__init__()
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self.relu = nn.ReLU()
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def construct(self, x):
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return x[:10:1, :, 2:3:1]
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_slice4():
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inputx = np.random.rand(4, 4, 4).astype(np.float32)
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x = Tensor(inputx)
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slice_op = Slice4()
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output = slice_op(x)
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assert (output.asnumpy() == inputx[:10:1, :, 2:3:1]).all()
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if __name__ == '__main__':
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test_slice()
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test_slice2()
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test_slice3()
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test_slice4()
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