[bugfix] 修复opbase的log问题-opbase-AtomGit

Minclude/nnopbase/opdev/op_executor.h+2-2

	@@ -114,7 +114,7 @@ public:
114	allocatedTensorList_.push_back(tensor);	114	allocatedTensorList_.push_back(tensor);
115	return tensor;	115	return tensor;
116	} catch (...) {	116	} catch (...) {
117	- OP_LOGE(ACLNN_ERR_INNER, "aclOpExecutor::ConvertToTensor fail.");	117	+ OP_LOGE(ACLNN_ERR_INNER, "aclOpExecutor::ConvertToTensor failed.");
118	delete tensor;	118	delete tensor;
119	return nullptr;	119	return nullptr;
120	}	120	}
	@@ -181,7 +181,7 @@ public:
181	if (uniqueExecutor_.get() != nullptr) {	181	if (uniqueExecutor_.get() != nullptr) {
182	uniqueExecutor_.get()->DeleteCache();	182	uniqueExecutor_.get()->DeleteCache();
183	OP_LOGE_WITHOUT_REPORT(ACLNN_ERR_INNER_NOT_TRANS_EXECUTOR,	183	OP_LOGE_WITHOUT_REPORT(ACLNN_ERR_INNER_NOT_TRANS_EXECUTOR,
184	- "When %s do success, ReleaseTo(executor) should be called before return.",	184	+ "When %s succeeds, ReleaseTo(executor) should be called before return.",
185	funcName_);	185	funcName_);
186	}	186	}
187	}	187	}

Msrc/nnopbase/common/inc/block_pool.h+1-1

	@@ -376,7 +376,7 @@ private:
376	}	376	}
377		377
378	if (index < 0 \|\| index >= BlockPool::MAX_STORE) {	378	if (index < 0 \|\| index >= BlockPool::MAX_STORE) {
379	- OP_LOGE(ACLNN_ERR_INNER, "invalid cache to alloc, idx %d size %lu", index, size);	379	+ OP_LOGE(ACLNN_ERR_INNER, "invalid cache to alloc, idx %d size %lu B", index, size);
380	return nullptr;	380	return nullptr;
381	}	381	}
382		382

Msrc/nnopbase/common/inc/launch_arg_info.h+5-5

	@@ -274,7 +274,7 @@ private:
274	devArgNum_++;	274	devArgNum_++;
275	tensorNum_++;	275	tensorNum_++;
276	#ifdef DEBUG	276	#ifdef DEBUG
277	- OP_LOGD("Append Launch DEVICE aclTensor. dims: %zu, dtype: %d, aclTensor: %p, addr: %p, tensor size: %zu",	277	+ OP_LOGD("Append Launch DEVICE aclTensor. dims: %zu, dtype: %d, aclTensor: %p, addr: %p, tensor size: %zu B",
278	arg->GetStorageShape().GetDimNum(), arg->GetDataType(), arg, arg->GetData(),	278	arg->GetStorageShape().GetDimNum(), arg->GetDataType(), arg, arg->GetData(),
279	arg->GetTensor()->GetSize());	279	arg->GetTensor()->GetSize());
280	const auto& shape = arg->GetStorageShape();	280	const auto& shape = arg->GetStorageShape();
	@@ -288,7 +288,7 @@ private:
288	hostArgNum_++;	288	hostArgNum_++;
289	tensorNum_++;	289	tensorNum_++;
290	#ifdef DEBUG	290	#ifdef DEBUG
291	- OP_LOGD("Append Launch HOST aclTensor. dims: %zu, dtype: %d, %p, calc size: %zu, tensor size: %zu",	291	+ OP_LOGD("Append Launch HOST aclTensor. dims: %zu, dtype: %d, %p, calc size: %zu B, tensor size: %zu B",
292	arg->GetStorageShape().GetDimNum(), arg->GetDataType(), arg, size, arg->GetTensor()->GetSize());	292	arg->GetStorageShape().GetDimNum(), arg->GetDataType(), arg, size, arg->GetTensor()->GetSize());
293	const auto& shape = arg->GetStorageShape();	293	const auto& shape = arg->GetStorageShape();
294	for (size_t i = 0; i < shape.GetDimNum(); i++) {	294	for (size_t i = 0; i < shape.GetDimNum(); i++) {
	@@ -318,7 +318,7 @@ private:
318	tensorNum_ += arg->Size() + 1;	318	tensorNum_ += arg->Size() + 1;
319	dfxInfoDumpElemCount_++;	319	dfxInfoDumpElemCount_++;
320	#ifdef DEBUG	320	#ifdef DEBUG
321	- OP_LOGD("Append input DEVICE ptr: size %lu, dataSize %zu", arg->Size(), dataSize);	321	+ OP_LOGD("Append input DEVICE ptr: tensor num: %lu, dataSize: %zu B", arg->Size(), dataSize);
322	#endif	322	#endif
323	return;	323	return;
324	}	324	}
	@@ -347,7 +347,7 @@ private:
347	tensorNum_++;	347	tensorNum_++;
348	dfxInfoDumpElemCount_ += CalAdumpDFXInfoElemCount(arg);	348	dfxInfoDumpElemCount_ += CalAdumpDFXInfoElemCount(arg);
349	#ifdef DEBUG	349	#ifdef DEBUG
350	- OP_LOGD("Append Launch aclTensor. dims: %zu, dtype: %d, data:%p, tensor size: %zu",	350	+ OP_LOGD("Append Launch aclTensor. dims: %zu, dtype: %d, data:%p, tensor size: %zu B",
351	arg->GetStorageShape().GetDimNum(), arg->GetDataType(), arg->GetData(), arg->GetTensor()->GetSize());	351	arg->GetStorageShape().GetDimNum(), arg->GetDataType(), arg->GetData(), arg->GetTensor()->GetSize());
352	const auto& shape = arg->GetStorageShape();	352	const auto& shape = arg->GetStorageShape();
353	for (size_t i = 0; i < shape.GetDimNum(); i++) {	353	for (size_t i = 0; i < shape.GetDimNum(); i++) {
	@@ -374,7 +374,7 @@ private:
374	tensorNum_ += arg->Size() + 1;	374	tensorNum_ += arg->Size() + 1;
375	dfxInfoDumpElemCount_++;	375	dfxInfoDumpElemCount_++;
376	#ifdef DEBUG	376	#ifdef DEBUG
377	- OP_LOGD("Append output DEVICE ptr: size %ld, dataSize %ld", arg->Size(), dataSize);	377	+ OP_LOGD("Append output DEVICE ptr: tensor num: %lu, dataSize: %zu B", arg->Size(), dataSize);
378	#endif	378	#endif
379	return;	379	return;
380	}	380	}

Msrc/nnopbase/common/utils/op_cache.cpp+1-1

	@@ -993,7 +993,7 @@ void* OpExecCache::AddLaunchData(size_t dataLen)
993	// if cache buf not enough, abandon cache.	993	// if cache buf not enough, abandon cache.
994	if (cacheOffset_ + dataLen > cacheCap_) {	994	if (cacheOffset_ + dataLen > cacheCap_) {
995	MarkOpCacheInvalid();	995	MarkOpCacheInvalid();
996	- OP_LOGW("cache buf has full, abandon current cache.");	996	+ OP_LOGW("cache buf is full, abandon current cache.");
997	if (dataLen > cacheCap_) {	997	if (dataLen > cacheCap_) {
998	OP_LOGW("cache buf cap is not enough for once cache data!");	998	OP_LOGW("cache buf cap is not enough for once cache data!");
999	}	999	}

Msrc/nnopbase/common/utils/op_feature.cpp+1-1

	@@ -123,7 +123,7 @@ aclnnStatus InitPcieThroughInfo()
123	g_pcieThroughEnabled = false;	123	g_pcieThroughEnabled = false;
124	NpuArch npuArch = GetCurrentPlatformInfo().GetCurNpuArch();	124	NpuArch npuArch = GetCurrentPlatformInfo().GetCurNpuArch();
125	if (npuArch != NpuArch::DAV_3510 && npuArch != NpuArch::DAV_9201 && npuArch != NpuArch::DAV_9202) {	125	if (npuArch != NpuArch::DAV_3510 && npuArch != NpuArch::DAV_9201 && npuArch != NpuArch::DAV_9202) {
126	- OP_LOGI("Current NPU arch [%u] not support PCIe through.", static_cast<uint32_t>(npuArch));	126	+ OP_LOGI("Current NPU arch [%u] does not support PCIe through.", static_cast<uint32_t>(npuArch));
127	return;	127	return;
128	}	128	}
129		129

Msrc/nnopbase/composite_op/aclnn_engine/dsa_task.h+9-7

	@@ -43,7 +43,8 @@ protected:
43		43
44	aclnnStatus VisitOutputArgs(OpArgList& argList)	44	aclnnStatus VisitOutputArgs(OpArgList& argList)
45	{	45	{
46	- CHECK_COND(argList.count == DSA_TASK_OUTPUT_NUM, ACLNN_ERR_INNER, "output arg num must be 1.");	46	+ CHECK_COND(argList.count == DSA_TASK_OUTPUT_NUM, ACLNN_ERR_INNER, "output arg num must be 1, but got %zu.",
		47	+ argList.count);
47	return VisitOutputArg(reinterpret_cast<aclTensor*>(argList[0]->pointer));	48	return VisitOutputArg(reinterpret_cast<aclTensor*>(argList[0]->pointer));
48	}	49	}
49		50
	@@ -186,7 +187,7 @@ private:
186	} else if (idx == idxStd) {	187	} else if (idx == idxStd) {
187	const auto rc = memcpy_s(&workspaceHolder_[IDX_PARAM1], sizeof(uint64_t), arg->GetData(), arg->Size());	188	const auto rc = memcpy_s(&workspaceHolder_[IDX_PARAM1], sizeof(uint64_t), arg->GetData(), arg->Size());
188	if (rc != EOK) {	189	if (rc != EOK) {
189	- OP_LOGE(ACLNN_ERR_INNER, "memcpy first input arg fail.");	190	+ OP_LOGE(ACLNN_ERR_INNER, "memcpy second input arg (std) failed.");
190	return ACLNN_ERR_INNER;	191	return ACLNN_ERR_INNER;
191	}	192	}
192		193
	@@ -217,7 +218,7 @@ private:
217	aclnnStatus VisitInputArgs(OpArgList& argList)	218	aclnnStatus VisitInputArgs(OpArgList& argList)
218	{	219	{
219	CHECK_COND(argList.count == DSA_TASK_INPUT_NUM, ACLNN_ERR_INNER,	220	CHECK_COND(argList.count == DSA_TASK_INPUT_NUM, ACLNN_ERR_INNER,
220	- "DSARandomNormal or DSARandomTruncatedNormal input arg num must be 5.");	221	+ "DSARandomNormal or DSARandomTruncatedNormal input arg num must be 5, but got %zu.", argList.count);
221	return argList.VisitBy([this](size_t idx, OpArg& arg) -> aclnnStatus { return VisitInputArg(idx, arg); });	222	return argList.VisitBy([this](size_t idx, OpArg& arg) -> aclnnStatus { return VisitInputArg(idx, arg); });
222	}	223	}
223	};	224	};
	@@ -324,7 +325,7 @@ private:
324	} else if (idx == idxMax) {	325	} else if (idx == idxMax) {
325	const auto rc = memcpy_s(&workspaceHolder_[IDX_PARAM1], sizeof(uint64_t), arg->GetData(), arg->Size());	326	const auto rc = memcpy_s(&workspaceHolder_[IDX_PARAM1], sizeof(uint64_t), arg->GetData(), arg->Size());
326	if (rc != EOK) {	327	if (rc != EOK) {
327	- OP_LOGE(ACLNN_ERR_INNER, "memcpy first input arg fail.");	328	+ OP_LOGE(ACLNN_ERR_INNER, "memcpy second input arg (max) failed.");
328	return ACLNN_ERR_INNER;	329	return ACLNN_ERR_INNER;
329	}	330	}
330	memcpy_s(randomNumTaskInfo_.randomNumFuncParaInfo.paramInfo.uniformDisInfo.max.valueOrAddr, arg->Size(),	331	memcpy_s(randomNumTaskInfo_.randomNumFuncParaInfo.paramInfo.uniformDisInfo.max.valueOrAddr, arg->Size(),
	@@ -355,7 +356,7 @@ private:
355	aclnnStatus VisitInputArgs(OpArgList& argList)	356	aclnnStatus VisitInputArgs(OpArgList& argList)
356	{	357	{
357	CHECK_COND(argList.count == DSA_TASK_INPUT_NUM, ACLNN_ERR_INNER,	358	CHECK_COND(argList.count == DSA_TASK_INPUT_NUM, ACLNN_ERR_INNER,
358	- "DSARandomUniformTask input arg num must be 5.");	359	+ "DSARandomUniformTask input arg num must be 5, but got %zu.", argList.count);
359	return argList.VisitBy([this](size_t idx, OpArg& arg) -> aclnnStatus { return VisitInputArg(idx, arg); });	360	return argList.VisitBy([this](size_t idx, OpArg& arg) -> aclnnStatus { return VisitInputArg(idx, arg); });
360	}	361	}
361	};	362	};
	@@ -468,7 +469,7 @@ private:
468	aclnnStatus VisitInputArgs(OpArgList& argList)	469	aclnnStatus VisitInputArgs(OpArgList& argList)
469	{	470	{
470	CHECK_COND(argList.count == DSA_GENBIT_TASK_INPUT_NUM, ACLNN_ERR_INNER,	471	CHECK_COND(argList.count == DSA_GENBIT_TASK_INPUT_NUM, ACLNN_ERR_INNER,
471	- "DSARandomUniformTask input arg num must be 4.");	472	+ "DSAGenBitMaskTask input arg num must be 4, but got %zu.", argList.count);
472	return argList.VisitBy([this](size_t idx, OpArg& arg) -> aclnnStatus { return VisitInputArg(idx, arg); });	473	return argList.VisitBy([this](size_t idx, OpArg& arg) -> aclnnStatus { return VisitInputArg(idx, arg); });
473	}	474	}
474		475
	@@ -480,7 +481,8 @@ private:
480		481
481	aclnnStatus VisitOutputArgs(OpArgList& argList)	482	aclnnStatus VisitOutputArgs(OpArgList& argList)
482	{	483	{
483	- CHECK_COND(argList.count == DSA_TASK_OUTPUT_NUM, ACLNN_ERR_INNER, "output arg num must be 1.");	484	+ CHECK_COND(argList.count == DSA_TASK_OUTPUT_NUM, ACLNN_ERR_INNER, "output arg num must be 1, but got %zu.",
		485	+ argList.count);
484	return VisitOutputArg(reinterpret_cast<aclTensor*>(argList[0]->pointer));	486	return VisitOutputArg(reinterpret_cast<aclTensor*>(argList[0]->pointer));
485	}	487	}
486	};	488	};

Msrc/nnopbase/composite_op/aclnn_engine/kernel_context_holder.h+1-1

	@@ -52,7 +52,7 @@ public:
52	CHECK_RET_CODE(input.VisitBy([this](size_t idx, OpArg& arg) { return UpdateInputArg(idx, arg); }),	52	CHECK_RET_CODE(input.VisitBy([this](size_t idx, OpArg& arg) { return UpdateInputArg(idx, arg); }),
53	"UpdateInputArg failed.");	53	"UpdateInputArg failed.");
54	CHECK_RET_CODE(output.VisitBy([this](size_t idx, OpArg& arg) { return UpdateOutputArg(idx, arg); }),	54	CHECK_RET_CODE(output.VisitBy([this](size_t idx, OpArg& arg) { return UpdateOutputArg(idx, arg); }),
55	- "UpdateInputArg failed.");	55	+ "UpdateOutputArg failed.");
56	FinalizeComputeNodeInfo(attr.count);	56	FinalizeComputeNodeInfo(attr.count);
57	void* attrPtr = attrDataStart_;	57	void* attrPtr = attrDataStart_;
58	CHECK_RET_CODE(	58	CHECK_RET_CODE(

Msrc/nnopbase/composite_op/aclnn_engine/kernel_mgr.cpp+2-1

	@@ -99,7 +99,8 @@ aclnnStatus KernelMgr::LoadStaticBinJson()
99	staticBinAndJsonDir_.append(STATIC_BIN_AND_JSON_DIR_PATH);	99	staticBinAndJsonDir_.append(STATIC_BIN_AND_JSON_DIR_PATH);
100	std::string realConfigJsonPath = RealPath(configJsonPath);	100	std::string realConfigJsonPath = RealPath(configJsonPath);
101	OP_CHECK(!realConfigJsonPath.empty(),	101	OP_CHECK(!realConfigJsonPath.empty(),
102	- OP_LOGW("static kernel config json is not exist, path: %s", configJsonPath.c_str()), return ACLNN_SUCCESS);	102	+ OP_LOGW("static kernel config json does not exist, path: %s", configJsonPath.c_str()),
		103	+ return ACLNN_SUCCESS);
103	ifstream f(realConfigJsonPath);	104	ifstream f(realConfigJsonPath);
104	try {	105	try {
105	staticConfigJson_ = nlohmann::json::parse(f);	106	staticConfigJson_ = nlohmann::json::parse(f);

Msrc/nnopbase/composite_op/aclnn_engine/non_finite_check_op.h+4-4

	@@ -93,7 +93,7 @@ public:
93	OP_CHECK(ret == ACL_SUCCESS, OP_LOGW("failed to call aclrtMallocWithCfg, ret %d", ret), return ACLNN_ERR_INNER);	93	OP_CHECK(ret == ACL_SUCCESS, OP_LOGW("failed to call aclrtMallocWithCfg, ret %d", ret), return ACLNN_ERR_INNER);
94		94
95	workspaceTensor->SetStorageAddr(wsAddr);	95	workspaceTensor->SetStorageAddr(wsAddr);
96	- OP_LOGD("create non finite check op workspace size %zu", workspaceSize[0]);	96	+ OP_LOGD("create non finite check op workspace size %zu bytes", workspaceSize[0]);
97	return ACLNN_SUCCESS;	97	return ACLNN_SUCCESS;
98	}	98	}
99		99
	@@ -184,7 +184,7 @@ struct NonFiniteCheckTensorList {
184	OP_LOGD("tensor dimNum %zu", dimNum);	184	OP_LOGD("tensor dimNum %zu", dimNum);
185	size_ += sizeof(int64_t); // ptr	185	size_ += sizeof(int64_t); // ptr
186	}	186	}
187	- OP_LOGD("size %zu ptrOffset %zu", size_, ptrOffset_);	187	+ OP_LOGD("size %zu bytes, ptrOffset %zu bytes", size_, ptrOffset_);
188	}	188	}
189		189
190	aclnnStatus Init(std::vector<aclTensor*>& checkTensors)	190	aclnnStatus Init(std::vector<aclTensor*>& checkTensors)
	@@ -274,11 +274,11 @@ public:
274	return ret);	274	return ret);
275		275
276	auto rc = aclrtSynchronizeStream(nonFiniteCheckOpCtx.stream_);	276	auto rc = aclrtSynchronizeStream(nonFiniteCheckOpCtx.stream_);
277	- OP_CHECK(rc == ACL_SUCCESS, OP_LOGW("aclrtSynchronizeStream failed, ret %d", ret), return ACLNN_ERR_INNER);	277	+ OP_CHECK(rc == ACL_SUCCESS, OP_LOGW("aclrtSynchronizeStream failed, ret %d", rc), return ACLNN_ERR_INNER);
278		278
279	float status = 0;	279	float status = 0;
280	rc = aclrtMemcpy(&status, sizeof(float), outputAddr, sizeof(float), ACL_MEMCPY_DEVICE_TO_HOST);	280	rc = aclrtMemcpy(&status, sizeof(float), outputAddr, sizeof(float), ACL_MEMCPY_DEVICE_TO_HOST);
281	- OP_CHECK(rc == ACL_SUCCESS, OP_LOGW("aclrtMemcpy failed, ret %d", ret), return ACLNN_ERR_INNER);	281	+ OP_CHECK(rc == ACL_SUCCESS, OP_LOGW("aclrtMemcpy failed, ret %d", rc), return ACLNN_ERR_INNER);
282	OP_LOGD("non finite check status %f", status);	282	OP_LOGD("non finite check status %f", status);
283	if (static_cast<int>(status) == 1) {	283	if (static_cast<int>(status) == 1) {
284	dump = true;	284	dump = true;

Msrc/nnopbase/composite_op/aclnn_engine/op_dfx.cpp+1-1

	@@ -1185,7 +1185,7 @@ static bool IsSaturationOverflow(aclrtStream stream)
1185	CHECK_COND(ret == ACL_SUCCESS, false, "aclrtNpuGetFloatOverFlowStatus failed, ret %d", ret);	1185	CHECK_COND(ret == ACL_SUCCESS, false, "aclrtNpuGetFloatOverFlowStatus failed, ret %d", ret);
1186		1186
1187	auto rc = aclrtSynchronizeStream(stream);	1187	auto rc = aclrtSynchronizeStream(stream);
1188	- OP_CHECK(rc == ACL_SUCCESS, OP_LOGW("aclrtSynchronizeStream failed, ret %d", ret), return ACLNN_ERR_INNER);	1188	+ OP_CHECK(rc == ACL_SUCCESS, OP_LOGW("aclrtSynchronizeStream failed, ret %d", rc), return ACLNN_ERR_INNER);
1189		1189
1190	uint8_t status = 0;	1190	uint8_t status = 0;
1191	ret = aclrtMemcpy(&status, sizeof(uint8_t), ValueToPtr(realAddr), sizeof(uint8_t), ACL_MEMCPY_DEVICE_TO_HOST);	1191	ret = aclrtMemcpy(&status, sizeof(uint8_t), ValueToPtr(realAddr), sizeof(uint8_t), ACL_MEMCPY_DEVICE_TO_HOST);

Msrc/nnopbase/composite_op/aclnn_engine/op_executor.cpp+4-2

	@@ -703,7 +703,9 @@ aclTensor* aclOpExecutor::CreateView(const aclTensor* tensor, const op::Shape& o
703	}	703	}
704	int64_t actualShapeLen = storageSize - offset;	704	int64_t actualShapeLen = storageSize - offset;
705	OP_CHECK((actualShapeLen >= 0 && actualShapeLen <= storageSize),	705	OP_CHECK((actualShapeLen >= 0 && actualShapeLen <= storageSize),
706	- OP_LOGE(ACLNN_ERR_INNER, "The tensor's offset is invalid with the specified storageShape"),	706	+ OP_LOGE(ACLNN_ERR_INNER,
		707	+ "The tensor's offset %ld is invalid, storage size is %ld, offset must be in [0, %ld].",
		708	+ offset, storageSize, storageSize),
707	return nullptr;);	709	return nullptr;);
708	// 在非连续场景下，传入tiling的storageshape会被oom用来计算合法内存大小，aclnn在下发时会将gm地址加上offset偏移，此时算子合法内存大小应为原始内存大小减offset	710	// 在非连续场景下，传入tiling的storageshape会被oom用来计算合法内存大小，aclnn在下发时会将gm地址加上offset偏移，此时算子合法内存大小应为原始内存大小减offset
709	storageShapeCorrect.SetDim(0, actualShapeLen);	711	storageShapeCorrect.SetDim(0, actualShapeLen);
	@@ -892,7 +894,7 @@ uint64_t aclOpExecutor::GetMagicNumber() { return magicNumber_; }
892	UniqueExecutor::UniqueExecutor(const char* funcName) : funcName_(funcName), uniqueExecutor_(new aclOpExecutor())	894	UniqueExecutor::UniqueExecutor(const char* funcName) : funcName_(funcName), uniqueExecutor_(new aclOpExecutor())
893	{	895	{
894	OP_LOGI("Create executor: %p", uniqueExecutor_.get());	896	OP_LOGI("Create executor: %p", uniqueExecutor_.get());
895	- OP_CHECK(uniqueExecutor_ != nullptr, OP_LOGE(ACLNN_ERR_INNER, "executor constructed failed."),	897	+ OP_CHECK(uniqueExecutor_ != nullptr, OP_LOGE(ACLNN_ERR_INNER, "failed to construct executor."),
896	throw std::bad_alloc());	898	throw std::bad_alloc());
897	auto& threadLocalCtx = op::internal::GetThreadLocalContext();	899	auto& threadLocalCtx = op::internal::GetThreadLocalContext();
898	uniqueExecutor_->SetLogInfo(threadLocalCtx.logInfo_);	900	uniqueExecutor_->SetLogInfo(threadLocalCtx.logInfo_);

Msrc/nnopbase/composite_op/aclnn_engine/op_kernel.cpp+9-6

	@@ -1143,7 +1143,8 @@ aclnnStatus OpKernel::HashAndInsert(const string& binAndJsonDir, const string& b
1143	auto binsIter = bins_.find(hash);	1143	auto binsIter = bins_.find(hash);
1144	if (binsIter != bins_.end()) {	1144	if (binsIter != bins_.end()) {
1145	if (key.key != binsIter->second->GetKeyAndDetail().key) {	1145	if (key.key != binsIter->second->GetKeyAndDetail().key) {
1146	- OP_LOGE(ACLNN_ERR_INNER, "Two bin [%s & %s] has same hash but their integral key is diff[%s, %s].",	1146	+ OP_LOGE(ACLNN_ERR_INNER,
		1147	+ "Two bins [%s & %s] have the same hash but their integral keys differ [%s, %s].",
1147	binOrJsonPath.c_str(), binsIter->second->jsonPath_.c_str(),	1148	binOrJsonPath.c_str(), binsIter->second->jsonPath_.c_str(),
1148	GetReadableKey(key.key, keyParams.len).c_str(),	1149	GetReadableKey(key.key, keyParams.len).c_str(),
1149	GetReadableKey(binsIter->second->GetKeyAndDetail().key, keyParams.len).c_str());	1150	GetReadableKey(binsIter->second->GetKeyAndDetail().key, keyParams.len).c_str());
	@@ -1153,7 +1154,7 @@ aclnnStatus OpKernel::HashAndInsert(const string& binAndJsonDir, const string& b
1153	binsIter->second->SetJsonPath(jsonPath);	1154	binsIter->second->SetJsonPath(jsonPath);
1154	binsIter->second->SetBinPath(binPath);	1155	binsIter->second->SetBinPath(binPath);
1155	} else {	1156	} else {
1156	- OP_LOGW("Two different bin [%s & %s] has same integral key %s.", binOrJsonPath.c_str(),	1157	+ OP_LOGW("Two different bins [%s & %s] have the same integral key %s.", binOrJsonPath.c_str(),
1157	binsIter->second->jsonPath_.c_str(), GetReadableKey(key.key, keyParams.len).c_str());	1158	binsIter->second->jsonPath_.c_str(), GetReadableKey(key.key, keyParams.len).c_str());
1158	continue;	1159	continue;
1159	}	1160	}
	@@ -1220,7 +1221,7 @@ void HandleAttrValue(const nlohmann::json& value, AttrInfo& attrInfo)
1220	OP_LOGD("Float attr [%s] need to be compared.", attrInfo.attrName.c_str());	1221	OP_LOGD("Float attr [%s] need to be compared.", attrInfo.attrName.c_str());
1221	attrInfo.supportAll = false;	1222	attrInfo.supportAll = false;
1222	} else {	1223	} else {
1223	- OP_LOGD("Float attr [%s] currently do not need to be compared.", attrInfo.attrName.c_str());	1224	+ OP_LOGD("Float attr [%s] currently does not need to be compared.", attrInfo.attrName.c_str());
1224	}	1225	}
1225	} else if (value.is_number()) {	1226	} else if (value.is_number()) {
1226	int64_t valueInt64 = value.get<int64_t>();	1227	int64_t valueInt64 = value.get<int64_t>();
	@@ -1231,14 +1232,14 @@ void HandleAttrValue(const nlohmann::json& value, AttrInfo& attrInfo)
1231	OP_LOGD("Int64 attr [%s] need to be compared.", attrInfo.attrName.c_str());	1232	OP_LOGD("Int64 attr [%s] need to be compared.", attrInfo.attrName.c_str());
1232	attrInfo.supportAll = false;	1233	attrInfo.supportAll = false;
1233	} else {	1234	} else {
1234	- OP_LOGD("Int64 attr [%s] currently do not need to be compared.", attrInfo.attrName.c_str());	1235	+ OP_LOGD("Int64 attr [%s] currently does not need to be compared.", attrInfo.attrName.c_str());
1235	}	1236	}
1236	} else if (value.is_array()) {	1237	} else if (value.is_array()) {
1237	if (attrInfo.values[0] != value.size()) {	1238	if (attrInfo.values[0] != value.size()) {
1238	OP_LOGD("Int64 attr [%s] need to be compared.", attrInfo.attrName.c_str());	1239	OP_LOGD("Int64 attr [%s] need to be compared.", attrInfo.attrName.c_str());
1239	attrInfo.supportAll = false;	1240	attrInfo.supportAll = false;
1240	} else {	1241	} else {
1241	- OP_LOGD("Int64 attr [%s] currently do not need to be compared.", attrInfo.attrName.c_str());	1242	+ OP_LOGD("Int64 attr [%s] currently does not need to be compared.", attrInfo.attrName.c_str());
1242	}	1243	}
1243	}	1244	}
1244	return;	1245	return;
	@@ -1266,7 +1267,9 @@ aclnnStatus OpKernel::JudgeInputSupportAll(const nlohmann::json& binListJson)
1266	for (const auto& input : *inputsIter) {	1267	for (const auto& input : *inputsIter) {
1267	++inputsCnt;	1268	++inputsCnt;
1268	if (inputsCnt >= static_cast<int64_t>(inputInfos_.size())) {	1269	if (inputsCnt >= static_cast<int64_t>(inputInfos_.size())) {
1269	- OP_LOGE(ACLNN_ERR_INNER_INPUT_NUM_IN_JSON_TOO_LARGE, "%ld is too large", inputsCnt);	1270	+ OP_LOGE(ACLNN_ERR_INNER_INPUT_NUM_IN_JSON_TOO_LARGE,
		1271	+ "Input num %ld in json is too large, max supported input num is %zu.", inputsCnt,
		1272	+ inputInfos_.size());
1270	return ACLNN_ERR_INNER_INPUT_NUM_IN_JSON_TOO_LARGE;	1273	return ACLNN_ERR_INNER_INPUT_NUM_IN_JSON_TOO_LARGE;
1271	}	1274	}
1272	auto& inputInfo = inputInfos_[inputsCnt];	1275	auto& inputInfo = inputInfos_[inputsCnt];

Msrc/nnopbase/composite_op/aclnn_engine/z_framework_op.cpp+1-1

	@@ -192,7 +192,7 @@ aclnnStatus CopyNpuToNpu(const aclTensor* src, const aclTensor* dst, aclOpExecut
192	OP_LOGE(ACLNN_ERR_INNER, "Get input param's placement:%d when expect kOnDeviceHbm.", src->GetPlacement()),	192	OP_LOGE(ACLNN_ERR_INNER, "Get input param's placement:%d when expect kOnDeviceHbm.", src->GetPlacement()),
193	return ACLNN_ERR_INNER);	193	return ACLNN_ERR_INNER);
194	OP_CHECK(dst->GetPlacement() == op::TensorPlacement::kOnDeviceHbm,	194	OP_CHECK(dst->GetPlacement() == op::TensorPlacement::kOnDeviceHbm,
195	- OP_LOGE(ACLNN_ERR_INNER, "Get out param's placement:%d when expect kOnDeviceHbm.", src->GetPlacement()),	195	+ OP_LOGE(ACLNN_ERR_INNER, "Get out param's placement:%d when expect kOnDeviceHbm.", dst->GetPlacement()),
196	return ACLNN_ERR_INNER);	196	return ACLNN_ERR_INNER);
197		197
198	op::internal::ProfilingInfoId profilingInfoId;	198	op::internal::ProfilingInfoId profilingInfoId;

Msrc/nnopbase/composite_op/log/op_error_manager.cpp+1-1

	@@ -206,7 +206,7 @@ void ReportErrorMessageInner(const std::string& code, const char* fmt, ...)
206	va_start(argList, fmt);	206	va_start(argList, fmt);
207	auto ret = vsnprintf_s(buf.data(), LIMIT_PREDEFINED_MESSAGE, LIMIT_PREDEFINED_MESSAGE - 1U, fmt, argList);	207	auto ret = vsnprintf_s(buf.data(), LIMIT_PREDEFINED_MESSAGE, LIMIT_PREDEFINED_MESSAGE - 1U, fmt, argList);
208	if (ret == -1) {	208	if (ret == -1) {
209	- OP_LOGW("Construct report error message fail, maybe the length of error message exceeds limits: %zu",	209	+ OP_LOGW("Construct report error message failed, maybe the length of error message exceeds limits: %zu",
210	LIMIT_PREDEFINED_MESSAGE);	210	LIMIT_PREDEFINED_MESSAGE);
211	}	211	}
212	va_end(argList);	212	va_end(argList);

Msrc/nnopbase/composite_op/mem_mgr/memory_allocator.cpp+2-1

	@@ -41,7 +41,8 @@ void TensorBucket::UpdateOffset(const uint64_t offset)
41	for (const auto ref : refs_) {	41	for (const auto ref : refs_) {
42	ref->SetOffset(offset_);	42	ref->SetOffset(offset_);
43	OP_LOGI(	43	OP_LOGI(
44	- "MaxAllocator tensor index: %zu, offset: %lu, lifetime: [%ld, %ld], original size: %ld, align size: %lu.",	44	+ "MaxAllocator tensor index: %zu, offset: %lu B, lifetime: [%ld, %ld], original size: %ld B, "
		45	+ "align size: %lu B.",
45	ref->GetIndex(), offset_, ref->GetLifeTimeStart(), ref->GetLifeTimeEnd(), ref->GetSize(),	46	ref->GetIndex(), offset_, ref->GetLifeTimeStart(), ref->GetLifeTimeEnd(), ref->GetSize(),
46	Align(ref->GetSize()));	47	Align(ref->GetSize()));
47	}	48	}

Msrc/nnopbase/composite_op/utils/platform.cpp+1-1

	@@ -361,7 +361,7 @@ const PlatformInfo& PlatformThreadLocalCtx::GetPlatformInfo()
361	int32_t deviceId;	361	int32_t deviceId;
362	auto ret = aclrtGetDevice(&deviceId);	362	auto ret = aclrtGetDevice(&deviceId);
363	OP_CHECK(ret == ACL_SUCCESS,	363	OP_CHECK(ret == ACL_SUCCESS,
364	- OP_LOGE(ACLNN_ERR_RUNTIME_ERROR, "Get device id failed when do GetCurrentPlatformInfo."),	364	+ OP_LOGE(ACLNN_ERR_RUNTIME_ERROR, "Get device id failed when doing GetCurrentPlatformInfo."),
365	return invalidPlatform_);	365	return invalidPlatform_);
366	while (platformInfoList_.size() <= static_cast<size_t>(deviceId)) {	366	while (platformInfoList_.size() <= static_cast<size_t>(deviceId)) {
367	PlatformInfo* info = new PlatformInfo(platformInfoList_.size());	367	PlatformInfo* info = new PlatformInfo(platformInfoList_.size());

Msrc/nnopbase/stub/gen_stubapi.py+1-1

	@@ -456,7 +456,7 @@ class H2CC(object):
456	self.line_index += 1	456	self.line_index += 1
457	self.write_specified_template()	457	self.write_specified_template()
458	logging.info('Added %s functions', len(self.func_list_exist))	458	logging.info('Added %s functions', len(self.func_list_exist))
459	- logging.info('Successfully converted,please see ' + self.output_file)	459	+ logging.info('Successfully converted, please see ' + self.output_file)
460		460
461	def handle_func1(self, line, template_string=''):	461	def handle_func1(self, line, template_string=''):
462	"""	462	"""