forked from mindspore-Ecosystem/mindspore
!39105 [CodeCheck]Fix code check problem of Op SpaceToBatchND
Merge pull request !39105 from zichun_ye/op_dev
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649ae3f83c
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@ -79,7 +79,7 @@ bool SpaceToBatchNDCpuKernelMod::LaunchKernel(const std::vector<kernel::AddressP
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const auto *input = reinterpret_cast<T *>(inputs[0]->addr);
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auto *output = reinterpret_cast<T *>(outputs[0]->addr);
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int ret = memset_s(output, outputs[0]->size, 0, sizeof(T) * output_size_);
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int ret = memset_s(output, outputs[0]->size, 0, sizeof(T) * static_cast<size_t>(output_size_));
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if (ret != 0) {
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MS_LOG(EXCEPTION) << "For '" << kernel_name_ << "', memset_s error. Error no: " << ret;
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}
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@ -88,8 +88,8 @@ bool SpaceToBatchNDCpuKernelMod::LaunchKernel(const std::vector<kernel::AddressP
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std::vector<int64_t> input_index(input_shape_.size(), 0);
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int64_t cur_pos = pos;
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for (int rev_i = input_shape_.size() - 1; rev_i >= 0; rev_i -= 1) {
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input_index[rev_i] = cur_pos % input_shape_[rev_i];
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cur_pos = cur_pos / input_shape_[rev_i];
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input_index[rev_i] = cur_pos % input_shape_[IntToSize(rev_i)];
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cur_pos = cur_pos / input_shape_[IntToSize(rev_i)];
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}
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std::vector<int64_t> output_index(input_index);
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@ -142,9 +142,9 @@ bool SpaceToBatchNDCpuKernelMod::Init(const BaseOperatorPtr &base_operator, cons
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int SpaceToBatchNDCpuKernelMod::Resize(const BaseOperatorPtr &base_operator, const std::vector<KernelTensorPtr> &inputs,
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const std::vector<KernelTensorPtr> &outputs,
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const std::map<uint32_t, tensor::TensorPtr> &inputsOnHost) {
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if (KernelMod::Resize(base_operator, inputs, outputs, inputsOnHost) == KRET_RESIZE_FAILED) {
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if (KernelMod::Resize(base_operator, inputs, outputs, inputsOnHost) == static_cast<int>(KRET_RESIZE_FAILED)) {
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MS_LOG(WARNING) << kernel_name_ << " reinit failed.";
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return KRET_RESIZE_FAILED;
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return static_cast<int>(KRET_RESIZE_FAILED);
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}
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// get input_shape
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input_shape_ = inputs.at(kIndex0)->GetShapeVector();
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@ -153,15 +153,15 @@ int SpaceToBatchNDCpuKernelMod::Resize(const BaseOperatorPtr &base_operator, con
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input_size_ = 1;
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output_size_ = 1;
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for (size_t i = 0; i < input_shape_.size(); ++i) {
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input_size_ = input_shape_[i] * input_size_;
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input_size_ *= input_shape_[i];
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}
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for (size_t i = 0; i < output_shape_.size(); ++i) {
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output_size_ = output_shape_[i] * output_size_;
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output_size_ *= output_shape_[i];
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}
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off_set_ = input_shape_.size() - block_size_.size();
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return KRET_OK;
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return static_cast<int>(KRET_OK);
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}
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const std::vector<std::pair<KernelAttr, KernelRunFunc>> &SpaceToBatchNDCpuKernelMod::GetFuncList() const {
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@ -91,7 +91,7 @@ abstract::ShapePtr SpaceToBatchNDInferShape(const PrimitivePtr &primitive,
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for (const auto &item : input_args) {
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MS_EXCEPTION_IF_NULL(item);
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}
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auto input_shape_ptr = CheckAndConvertUtils::GetTensorInputShape(prim_name, input_args, kInputIndex0);
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auto input_shape_ptr = CheckAndConvertUtils::GetTensorInputShape(prim_name, input_args, 0);
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auto paddings_value_ptr = primitive->GetAttr(kPaddings);
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MS_EXCEPTION_IF_NULL(paddings_value_ptr);
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@ -115,7 +115,7 @@ TypePtr SpaceToBatchNDInferType(const PrimitivePtr &prim, const std::vector<Abst
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}
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const std::set<TypePtr> valid_types = {kInt8, kInt16, kInt32, kInt64, kUInt8, kUInt16,
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kUInt32, kUInt64, kFloat16, kFloat32, kFloat64};
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auto var_type = input_args[kInputIndex0]->BuildType();
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auto var_type = input_args[0]->BuildType();
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return CheckAndConvertUtils::CheckTensorTypeValid("input type", var_type, valid_types, prim->name());
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}
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