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!17515 cpu ops pclint clean 

From: @caojian05
Reviewed-by: @wuxuejian,@c_34
Signed-off-by: @wuxuejian,@c_34
This commit is contained in:
mindspore-ci-bot 2021-06-02 14:18:59 +08:00 committed by Gitee
parent 038121aae1 eb1c28c2cf
commit 97756065a1
4 changed files with 16 additions and 19 deletions
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2
mindspore/ccsrc/backend/kernel_compiler/cpu/gathernd_cpu_kernel.cc
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@ -53,7 +53,7 @@ void GatherNdCPUKernel<T>::InitKernel(const CNodePtr &kernel_node) {
for (size_t i = dim_indices_last - 1; i > 0; --i) { for (size_t i = dim_indices_last - 1; i > 0; --i) {
batch_strides_[i - 1] = input_shapes_[i - 1]; batch_strides_[i - 1] = input_shapes_[i - 1];
batch_indices_[i - 1] = batch_indices_[i] * input_shapes_[i]; batch_indices_[i - 1] = batch_indices_[i] * SizeToInt(input_shapes_[i]);
} }
} }

18
mindspore/ccsrc/backend/kernel_compiler/cpu/range_cpu_kernel.cc
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@ -21,22 +21,14 @@ namespace kernel {
void RangeCPUKernel::InitKernel(const CNodePtr &kernel_node) { void RangeCPUKernel::InitKernel(const CNodePtr &kernel_node) {
MS_EXCEPTION_IF_NULL(kernel_node); MS_EXCEPTION_IF_NULL(kernel_node);
dtype_ = AnfAlgo::GetInputDeviceDataType(kernel_node, 0); dtype_ = AnfAlgo::GetInputDeviceDataType(kernel_node, 0);
start_ = AnfAlgo::GetNodeAttr<float>(kernel_node, START);
limit_ = AnfAlgo::GetNodeAttr<float>(kernel_node, LIMIT);
delta_ = AnfAlgo::GetNodeAttr<float>(kernel_node, DELTA);
} }
bool RangeCPUKernel::Launch(const std::vector<kernel::AddressPtr> &inputs, const std::vector<kernel::AddressPtr> &, bool RangeCPUKernel::Launch(const std::vector<kernel::AddressPtr> &inputs, const std::vector<kernel::AddressPtr> &,
const std::vector<kernel::AddressPtr> &outputs) { const std::vector<kernel::AddressPtr> &outputs) {
if (dtype_ == kNumberTypeInt32) { if (dtype_ == kNumberTypeInt32) {
return LaunchKernel<int32_t>(inputs, outputs); return LaunchKernel<int32_t>(inputs, outputs);
} else if (dtype_ == kNumberTypeInt64) {
return LaunchKernel<int64_t>(inputs, outputs);
} else if (dtype_ == kNumberTypeFloat32) { } else if (dtype_ == kNumberTypeFloat32) {
return LaunchKernel<float>(inputs, outputs); return LaunchKernel<float>(inputs, outputs);
} else if (dtype_ == kNumberTypeFloat64) {
return LaunchKernel<double>(inputs, outputs);
} else { } else {
MS_LOG(EXCEPTION) << "Only support int, float, but actual data type is " << TypeIdLabel(dtype_); MS_LOG(EXCEPTION) << "Only support int, float, but actual data type is " << TypeIdLabel(dtype_);
} }
@ -44,10 +36,18 @@ bool RangeCPUKernel::Launch(const std::vector<kernel::AddressPtr> &inputs, const
template <typename T> template <typename T>
bool RangeCPUKernel::LaunchKernel(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &outputs) { bool RangeCPUKernel::LaunchKernel(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &outputs) {
T start_ = reinterpret_cast<T *>(inputs[0]->addr)[0];
T limit_ = reinterpret_cast<T *>(inputs[1]->addr)[0];
T delta_ = reinterpret_cast<T *>(inputs[2]->addr)[0];
auto output_addr = reinterpret_cast<T *>(outputs[0]->addr); auto output_addr = reinterpret_cast<T *>(outputs[0]->addr);
size_t elem_num = outputs[0]->size / sizeof(T); size_t elem_num = outputs[0]->size / sizeof(T);
for (size_t i = 0; i < elem_num; i++) { for (size_t i = 0; i < elem_num; i++) {
output_addr[i] = start_ + i * delta_; T val_ = start_ + i * delta_;
if (val_ > limit_) {
break;
}
output_addr[i] = val_;
} }
return true; return true;
} }

3
mindspore/ccsrc/backend/kernel_compiler/cpu/range_cpu_kernel.h
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@ -36,9 +36,6 @@ class RangeCPUKernel : public CPUKernel {
private: private:
TypeId dtype_{kTypeUnknown}; TypeId dtype_{kTypeUnknown};
int64_t start_;
int64_t limit_;
int64_t delta_;
}; };
MS_REG_CPU_KERNEL(Range, KernelAttr(), RangeCPUKernel); MS_REG_CPU_KERNEL(Range, KernelAttr(), RangeCPUKernel);

12
mindspore/ops/_op_impl/cpu/range.py
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@ -17,12 +17,12 @@
from mindspore.ops.op_info_register import op_info_register, CpuRegOp, DataType from mindspore.ops.op_info_register import op_info_register, CpuRegOp, DataType
range_op_info = CpuRegOp("Range") \ range_op_info = CpuRegOp("Range") \
.input(0, "x", "required") \ .input(0, "start", "required") \
.output(0, "y", "required") \ .input(1, "limit") \
.dtype_format(DataType.I32_Default, DataType.I32_Default) \ .input(2, "delta") \
.dtype_format(DataType.I64_Default, DataType.I64_Default) \ .output(0, "output", "required") \
.dtype_format(DataType.F32_Default, DataType.F32_Default) \ .dtype_format(DataType.I32_Default, DataType.I32_Default, DataType.I32_Default, DataType.I32_Default) \
.dtype_format(DataType.F64_Default, DataType.F64_Default) \ .dtype_format(DataType.F32_Default, DataType.F32_Default, DataType.F32_Default, DataType.F32_Default) \
.get_op_info() .get_op_info()