fix(cleancode): AICPU算子告警整改（第三批）-ops-nn-AtomGit

Mactivation/log_softmax_v2/op_kernel_aicpu/log_softmax_v2_aicpu.cpp+2-2

	@@ -190,7 +190,7 @@ uint32_t LogSoftmaxV2CpuKernel::Compute(CpuKernelContext& ctx)
190	return result;	190	return result;
191	}	191	}
192		192
193	-KernelStatus LogSoftmaxV2CpuKernel::LogSoftmaxV2Check(const CpuKernelContext& ctx)	193	+KernelStatus LogSoftmaxV2CpuKernel::LogSoftmaxV2Check(const CpuKernelContext& ctx) const
194	{	194	{
195	KERNEL_CHECK_NULLPTR(ctx.Input(0)->GetData(), KERNEL_STATUS_PARAM_INVALID, "get input failed.");	195	KERNEL_CHECK_NULLPTR(ctx.Input(0)->GetData(), KERNEL_STATUS_PARAM_INVALID, "get input failed.");
196	KERNEL_CHECK_NULLPTR(ctx.Input(0)->GetTensorShape(), KERNEL_STATUS_PARAM_INVALID, "Get input tensor shape failed.");	196	KERNEL_CHECK_NULLPTR(ctx.Input(0)->GetTensorShape(), KERNEL_STATUS_PARAM_INVALID, "Get input tensor shape failed.");
	@@ -213,7 +213,7 @@ KernelStatus LogSoftmaxV2CpuKernel::LogSoftmaxV2Check(const CpuKernelContext& ct
213	}	213	}
214		214
215	template <typename T>	215	template <typename T>
216	-KernelStatus LogSoftmaxV2CpuKernel::LogSoftmaxV2Compute(const CpuKernelContext& ctx)	216	+KernelStatus LogSoftmaxV2CpuKernel::LogSoftmaxV2Compute(const CpuKernelContext& ctx) const
217	{	217	{
218	auto input = static_cast<T*>(ctx.Input(0)->GetData());	218	auto input = static_cast<T*>(ctx.Input(0)->GetData());
219	auto output = static_cast<T*>(ctx.Output(0)->GetData());	219	auto output = static_cast<T*>(ctx.Output(0)->GetData());

Mactivation/log_softmax_v2/op_kernel_aicpu/log_softmax_v2_aicpu.h+2-2

	@@ -24,10 +24,10 @@ public:
24	uint32_t Compute(CpuKernelContext& ctx) override;	24	uint32_t Compute(CpuKernelContext& ctx) override;
25		25
26	private:	26	private:
27	- KernelStatus LogSoftmaxV2Check(const CpuKernelContext& ctx);	27	+ KernelStatus LogSoftmaxV2Check(const CpuKernelContext& ctx) const;
28		28
29	template <typename T>	29	template <typename T>
30	- KernelStatus LogSoftmaxV2Compute(const CpuKernelContext& ctx);	30	+ KernelStatus LogSoftmaxV2Compute(const CpuKernelContext& ctx) const;
31	};	31	};
32	} // namespace aicpu	32	} // namespace aicpu
33		33

Mactivation/softmax_v2/op_kernel_aicpu/softmax_v2_aicpu.cpp+5-3

	@@ -354,8 +354,9 @@ KernelStatus SoftmaxV2ExtraCheck(const CpuKernelContext& ctx)
354		354
355	uint32_t SoftmaxV2Check(CpuKernelContext& ctx)	355	uint32_t SoftmaxV2Check(CpuKernelContext& ctx)
356	{	356	{
357	- return NormalCheck(ctx, kSoftmaxV2InputNum, kSoftmaxV2OutputNum, kSoftmaxV2Attr) ? KERNEL_STATUS_PARAM_INVALID :	357	+ return NormalCheck(ctx, kSoftmaxV2InputNum, kSoftmaxV2OutputNum, kSoftmaxV2Attr) != KERNEL_STATUS_OK ?
358	- SoftmaxV2ExtraCheck(ctx);	358	+ KERNEL_STATUS_PARAM_INVALID :
		359	+ SoftmaxV2ExtraCheck(ctx);
359	}	360	}
360		361
361	// DT_FLOAT16, DT_FLOAT, DT_DOUBLE	362	// DT_FLOAT16, DT_FLOAT, DT_DOUBLE
	@@ -385,7 +386,8 @@ uint32_t SoftmaxV2Compute(const CpuKernelContext& ctx)
385		386
386	uint32_t SoftmaxV2CpuKernel::Compute(CpuKernelContext& ctx)	387	uint32_t SoftmaxV2CpuKernel::Compute(CpuKernelContext& ctx)
387	{	388	{
388	- return detail::SoftmaxV2Check(ctx) ? KERNEL_STATUS_PARAM_INVALID : detail::SoftmaxV2Compute(ctx);	389	+ return detail::SoftmaxV2Check(ctx) != KERNEL_STATUS_OK ? KERNEL_STATUS_PARAM_INVALID :
		390	+ detail::SoftmaxV2Compute(ctx);
389	}	391	}
390		392
391	OPS_NN_REGISTER_CPU_KERNELV2(kSoftmaxV2, SoftmaxV2CpuKernel);	393	OPS_NN_REGISTER_CPU_KERNELV2(kSoftmaxV2, SoftmaxV2CpuKernel);

Mindex/reverse_sequence/op_kernel_aicpu/reverse_sequence_aicpu.cpp+1-1

	@@ -88,7 +88,7 @@ KernelStatus CalReverseSequence(const std::vector<void*>& ioAddrs, std::vector<i
88	output[i * seqStep + offset] = input[((reverseNum - i) - 1) * seqStep + offset];	88	output[i * seqStep + offset] = input[((reverseNum - i) - 1) * seqStep + offset];
89	output[((reverseNum - i) - 1) * seqStep + offset] = input[i * seqStep + offset];	89	output[((reverseNum - i) - 1) * seqStep + offset] = input[i * seqStep + offset];
90	}	90	}
91	- if ((i >= reverseNum) \|\| (i == reverseNum / kEven && reverseNum % kEven)) {	91	+ if ((i >= reverseNum) \|\| (i == reverseNum / kEven && (reverseNum % kEven) != 0)) {
92	output[i * seqStep + offset] = input[i * seqStep + offset];	92	output[i * seqStep + offset] = input[i * seqStep + offset];
93	}	93	}
94	}	94	}

Mindex/scatter_elements/op_kernel_aicpu/scatter_elements_aicpu.cpp+3-3

Mindex/scatter_elements/op_kernel_aicpu/scatter_elements_aicpu.h+3-3

	@@ -25,13 +25,13 @@ public:
25		25
26	private:	26	private:
27	template <typename TI>	27	template <typename TI>
28	- uint32_t DispatchByDataType(CpuKernelContext& ctx);	28	+ uint32_t DispatchByDataType(CpuKernelContext& ctx) const;
29		29
30	template <typename T>	30	template <typename T>
31	- uint32_t UpdateOutput(const CpuKernelContext& ctx, int64_t total_value_num);	31	+ uint32_t UpdateOutput(const CpuKernelContext& ctx, int64_t total_value_num) const;
32		32
33	template <typename T, typename TI>	33	template <typename T, typename TI>
34	- uint32_t DoCompute(const CpuKernelContext& ctx);	34	+ uint32_t DoCompute(const CpuKernelContext& ctx) const;
35	};	35	};
36	} // namespace aicpu	36	} // namespace aicpu
37		37

Mindex/sparse_segment_mean/op_kernel_aicpu/sparse_segment_mean_aicpu.cpp+2-2

	@@ -84,7 +84,7 @@ uint32_t SparseSegmentMeanCpuKernel::Compute(CpuKernelContext& ctx)
84	}	84	}
85		85
86	template <typename T, typename T1, typename T2>	86	template <typename T, typename T1, typename T2>
87	-KernelStatus SparseSegmentMeanCpuKernel::ComputeKernelWithType(const CpuKernelContext& ctx)	87	+KernelStatus SparseSegmentMeanCpuKernel::ComputeKernelWithType(const CpuKernelContext& ctx) const
88	{	88	{
89	auto xShape = ctx.Input(0)->GetTensorShape();	89	auto xShape = ctx.Input(0)->GetTensorShape();
90	T1 xDim0 = static_cast<T1>(xShape->GetDimSize(0));	90	T1 xDim0 = static_cast<T1>(xShape->GetDimSize(0));
	@@ -173,7 +173,7 @@ KernelStatus SparseSegmentMeanCpuKernel::ComputeKernelWithType(const CpuKernelCo
173	}	173	}
174		174
175	template <typename T>	175	template <typename T>
176	-KernelStatus SparseSegmentMeanCpuKernel::ComputeKernel(const CpuKernelContext& ctx)	176	+KernelStatus SparseSegmentMeanCpuKernel::ComputeKernel(const CpuKernelContext& ctx) const
177	{	177	{
178	auto indicesDataType = ctx.Input(1)->GetDataType();	178	auto indicesDataType = ctx.Input(1)->GetDataType();
179	auto segmentIdsDtype = ctx.Input(2)->GetDataType();	179	auto segmentIdsDtype = ctx.Input(2)->GetDataType();

Mindex/sparse_segment_mean/op_kernel_aicpu/sparse_segment_mean_aicpu.h+2-2

	@@ -25,10 +25,10 @@ private:
25	KernelStatus SparseSegmentCheck(const CpuKernelContext& ctx) const;	25	KernelStatus SparseSegmentCheck(const CpuKernelContext& ctx) const;
26		26
27	template <typename T>	27	template <typename T>
28	- KernelStatus ComputeKernel(const CpuKernelContext& ctx);	28	+ KernelStatus ComputeKernel(const CpuKernelContext& ctx) const;
29		29
30	template <typename T, typename T1, typename T2>	30	template <typename T, typename T1, typename T2>
31	- KernelStatus ComputeKernelWithType(const CpuKernelContext& ctx);	31	+ KernelStatus ComputeKernelWithType(const CpuKernelContext& ctx) const;
32	};	32	};
33	} // namespace aicpu	33	} // namespace aicpu
34	#endif // OPS_BUILT_IN_OP_KERNEL_AICPU_SPARSE_SEGMENT_MEAN_AICPU_H_	34	#endif // OPS_BUILT_IN_OP_KERNEL_AICPU_SPARSE_SEGMENT_MEAN_AICPU_H_

Mindex/sparse_segment_sum/op_kernel_aicpu/sparse_segment_sum_aicpu.cpp+2-2

	@@ -173,7 +173,7 @@ uint32_t SparseSegmentSumCpuKernel::Compute(CpuKernelContext& ctx)
173	}	173	}
174		174
175	template <typename T, typename T1, typename T2>	175	template <typename T, typename T1, typename T2>
176	-KernelStatus SparseSegmentSumCpuKernel::ComputeKernelWithType(const CpuKernelContext& ctx)	176	+KernelStatus SparseSegmentSumCpuKernel::ComputeKernelWithType(const CpuKernelContext& ctx) const
177	{	177	{
178	size_t n = ctx.Input(0)->GetTensorShape()->NumElements() / ctx.Input(0)->GetTensorShape()->GetDimSize(0);	178	size_t n = ctx.Input(0)->GetTensorShape()->NumElements() / ctx.Input(0)->GetTensorShape()->GetDimSize(0);
179	size_t num_indices = ctx.Input(2)->GetTensorShape()->NumElements();	179	size_t num_indices = ctx.Input(2)->GetTensorShape()->NumElements();
	@@ -232,7 +232,7 @@ KernelStatus SparseSegmentSumCpuKernel::ComputeKernelWithType(const CpuKernelCon
232	return KERNEL_STATUS_OK;	232	return KERNEL_STATUS_OK;
233	};	233	};
234	template <typename T>	234	template <typename T>
235	-KernelStatus SparseSegmentSumCpuKernel::ComputeKernel(const CpuKernelContext& ctx)	235	+KernelStatus SparseSegmentSumCpuKernel::ComputeKernel(const CpuKernelContext& ctx) const
236	{	236	{
237	auto indices_data_type = ctx.Input(1)->GetDataType();	237	auto indices_data_type = ctx.Input(1)->GetDataType();
238	auto segment_ids_dtype = ctx.Input(2)->GetDataType();	238	auto segment_ids_dtype = ctx.Input(2)->GetDataType();

Mindex/sparse_segment_sum/op_kernel_aicpu/sparse_segment_sum_aicpu.h+2-2

	@@ -30,10 +30,10 @@ private:
30	KernelStatus ComputeWithType(const CpuKernelContext& ctx);	30	KernelStatus ComputeWithType(const CpuKernelContext& ctx);
31		31
32	template <typename T>	32	template <typename T>
33	- KernelStatus ComputeKernel(const CpuKernelContext& ctx);	33	+ KernelStatus ComputeKernel(const CpuKernelContext& ctx) const;
34		34
35	template <typename T, typename T1, typename T2>	35	template <typename T, typename T1, typename T2>
36	- KernelStatus ComputeKernelWithType(const CpuKernelContext& ctx);	36	+ KernelStatus ComputeKernelWithType(const CpuKernelContext& ctx) const;
37	};	37	};
38	} // namespace aicpu	38	} // namespace aicpu
39	#endif	39	#endif

Mindex/sparse_to_dense/op_kernel_aicpu/sparse_to_dense_aicpu.cpp+2-2

	@@ -419,7 +419,7 @@ uint32_t SparseToDense(const CpuKernelContext& ctx, SparseTensor& st, const Tens
419	}	419	}
420	}	420	}
421		421
422	-KernelStatus SparseToDenseCpuKernel::ValidParam(const CpuKernelContext& ctx)	422	+KernelStatus SparseToDenseCpuKernel::ValidParam(const CpuKernelContext& ctx) const
423	{	423	{
424	KERNEL_LOG_INFO("Start to execute ValidParam");	424	KERNEL_LOG_INFO("Start to execute ValidParam");
425	Tensor* indicesTensor = ctx.Input(0);	425	Tensor* indicesTensor = ctx.Input(0);
	@@ -497,7 +497,7 @@ KernelStatus SparseToDenseCpuKernel::ValidParam(const CpuKernelContext& ctx)
497	}	497	}
498		498
499	uint32_t SparseToDenseCpuKernel::ParallelSetDefaultValue(const CpuKernelContext& ctx, const Tensor* defaultValueTensor,	499	uint32_t SparseToDenseCpuKernel::ParallelSetDefaultValue(const CpuKernelContext& ctx, const Tensor* defaultValueTensor,
500	- const Tensor* outputTensor, int64_t outputSize)	500	+ const Tensor* outputTensor, int64_t outputSize) const
501	{	501	{
502	auto typeSize = GetSizeByDataType(static_cast<DataType>(outputTensor->GetDataType()));	502	auto typeSize = GetSizeByDataType(static_cast<DataType>(outputTensor->GetDataType()));
503	char* defaultValueAddr = PtrToPtr<void, char>(defaultValueTensor->GetData());	503	char* defaultValueAddr = PtrToPtr<void, char>(defaultValueTensor->GetData());

Mindex/sparse_to_dense/op_kernel_aicpu/sparse_to_dense_aicpu.h+2-2

	@@ -21,9 +21,9 @@ public:
21	uint32_t Compute(CpuKernelContext& ctx) override;	21	uint32_t Compute(CpuKernelContext& ctx) override;
22		22
23	protected:	23	protected:
24	- KernelStatus ValidParam(const CpuKernelContext& ctx);	24	+ KernelStatus ValidParam(const CpuKernelContext& ctx) const;
25	uint32_t ParallelSetDefaultValue(const CpuKernelContext& ctx, const Tensor* defaultValueTensor,	25	uint32_t ParallelSetDefaultValue(const CpuKernelContext& ctx, const Tensor* defaultValueTensor,
26	- const Tensor* outputTensor, int64_t outputSize);	26	+ const Tensor* outputTensor, int64_t outputSize) const;
27	uint32_t SetDefaultValue(const CpuKernelContext& ctx, const Tensor* defaultValueTensor, const Tensor* outputTensor,	27	uint32_t SetDefaultValue(const CpuKernelContext& ctx, const Tensor* defaultValueTensor, const Tensor* outputTensor,
28	int64_t outputSize);	28	int64_t outputSize);
29	};	29	};

Mindex/tensor_scatter_update/op_kernel_aicpu/tensor_scatter_update_aicpu.cpp+2-2

	@@ -62,7 +62,7 @@ inline void GetOuterShape(const CpuKernelContextInfo& info, uint64_t* x_outer_sh
62	}	62	}
63	}	63	}
64		64
65	-inline void GetBatchStrides(uint64_t* outer_shape, uint64_t index_depth, uint64_t* batch_strides)	65	+inline void GetBatchStrides(const uint64_t* outer_shape, uint64_t index_depth, uint64_t* batch_strides)
66	{	66	{
67	batch_strides[index_depth - 1] = 1;	67	batch_strides[index_depth - 1] = 1;
68	for (int64_t i = static_cast<int64_t>(index_depth) - 2; i >= 0; --i) {	68	for (int64_t i = static_cast<int64_t>(index_depth) - 2; i >= 0; --i) {
	@@ -297,7 +297,7 @@ uint32_t IndicesCompute(const CpuKernelContextInfo& info)
297	}	297	}
298	}	298	}
299		299
300	-uint32_t TensorScatterUpdateCpukernel::GetInputAndCheck(const CpuKernelContextInfo& info)	300	+uint32_t TensorScatterUpdateCpukernel::GetInputAndCheck(const CpuKernelContextInfo& info) const
301	{	301	{
302	KERNEL_CHECK_FALSE((info.indices_dims >= kMinIndicesDims), KERNEL_STATUS_PARAM_INVALID,	302	KERNEL_CHECK_FALSE((info.indices_dims >= kMinIndicesDims), KERNEL_STATUS_PARAM_INVALID,
303	"indices must be at least rank %u but is rank %lu", kMinIndicesDims, info.indices_dims);	303	"indices must be at least rank %u but is rank %lu", kMinIndicesDims, info.indices_dims);

Mindex/tensor_scatter_update/op_kernel_aicpu/tensor_scatter_update_aicpu.h+1-1

	@@ -50,7 +50,7 @@ public:
50	uint32_t Compute(CpuKernelContext& ctx) override;	50	uint32_t Compute(CpuKernelContext& ctx) override;
51		51
52	private:	52	private:
53	- uint32_t GetInputAndCheck(const CpuKernelContextInfo& info);	53	+ uint32_t GetInputAndCheck(const CpuKernelContextInfo& info) const;
54	};	54	};
55	} // namespace aicpu	55	} // namespace aicpu
56		56

	@@ -234,7 +234,7 @@ uint32_t ScatterElementsCpuKernel::Compute(CpuKernelContext& ctx)
234	}	234	}
235		235
236	template <typename T>	236	template <typename T>
237	-uint32_t ScatterElementsCpuKernel::UpdateOutput(const CpuKernelContext& ctx, int64_t total_value_num)	237	+uint32_t ScatterElementsCpuKernel::UpdateOutput(const CpuKernelContext& ctx, int64_t total_value_num) const
238	{	238	{
239	auto* input_data = PtrToPtr<void, T>(ctx.Input(0)->GetData());	239	auto* input_data = PtrToPtr<void, T>(ctx.Input(0)->GetData());
240	auto* output_data = PtrToPtr<void, T>(ctx.Output(0)->GetData());	240	auto* output_data = PtrToPtr<void, T>(ctx.Output(0)->GetData());
	@@ -275,7 +275,7 @@ uint32_t ScatterElementsCpuKernel::UpdateOutput(const CpuKernelContext& ctx, int
275	}	275	}
276		276
277	template <typename TI>	277	template <typename TI>
278	-uint32_t ScatterElementsCpuKernel::DispatchByDataType(CpuKernelContext& ctx)	278	+uint32_t ScatterElementsCpuKernel::DispatchByDataType(CpuKernelContext& ctx) const
279	{	279	{
280	switch (ctx.Input(0)->GetDataType()) {	280	switch (ctx.Input(0)->GetDataType()) {
281	case DT_FLOAT16:	281	case DT_FLOAT16:
	@@ -315,7 +315,7 @@ uint32_t ScatterElementsCpuKernel::DispatchByDataType(CpuKernelContext& ctx)
315	}	315	}
316		316
317	template <typename T, typename TI>	317	template <typename T, typename TI>
318	-uint32_t ScatterElementsCpuKernel::DoCompute(const CpuKernelContext& ctx)	318	+uint32_t ScatterElementsCpuKernel::DoCompute(const CpuKernelContext& ctx) const
319	{	319	{
320	ScatterElementsComputeInfo info;	320	ScatterElementsComputeInfo info;
321	auto ret = InitScatterElementsInfo(ctx, info);	321	auto ret = InitScatterElementsInfo(ctx, info);