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1595
已合并
fix: 修复Remainder/Greater/Equal/IsIn报错dtype支持列表双层中括号 #5512
hahaha22创建于 9月9日
fix: 修复Remainder/Greater/Equal/IsIn报错dtype支持列表双层中括号 #5512
已合并
hahaha22创建于 9月9日
从hahaha22/ops-mathe-class-log-fix合入到cann/ops-mathmaster
共 5 个文件变更+64-78
Mmath/equal/op_api/aclnn_eq_scalar.cpp+10-14
@@ -46,7 +46,7 @@ static const std::initializer_list<op::DataType> REGBASE_DTYPE_SUPPORT_LIST = {
46 op::DataType::DT_DOUBLE, op::DataType::DT_COMPLEX64, op::DataType::DT_COMPLEX128, op::DataType::DT_BF16,46 op::DataType::DT_DOUBLE, op::DataType::DT_COMPLEX64, op::DataType::DT_COMPLEX128, op::DataType::DT_BF16,
47 op::DataType::DT_UINT64};47 op::DataType::DT_UINT64};
48 48 
49-//其他output支持的类型49+// 其他output支持的类型
50static const std::initializer_list<op::DataType> OUT_DTYPE_SUPPORT_910_LIST = {50static const std::initializer_list<op::DataType> OUT_DTYPE_SUPPORT_910_LIST = {
51 op::DataType::DT_FLOAT, op::DataType::DT_INT32, op::DataType::DT_INT64, op::DataType::DT_FLOAT16,51 op::DataType::DT_FLOAT, op::DataType::DT_INT32, op::DataType::DT_INT64, op::DataType::DT_FLOAT16,
52 op::DataType::DT_INT16, op::DataType::DT_INT8, op::DataType::DT_UINT8, op::DataType::DT_UINT64,52 op::DataType::DT_INT16, op::DataType::DT_INT8, op::DataType::DT_UINT8, op::DataType::DT_UINT64,
@@ -236,9 +236,7 @@ static bool CheckDtypeValid(const aclTensor* self, const aclScalar* other, const
236 OP_CHECK_DTYPE_NOT_SUPPORT(other, dtypeSupportList, return false);236 OP_CHECK_DTYPE_NOT_SUPPORT(other, dtypeSupportList, return false);
237 237 
238 auto npuArch = op::GetCurrentPlatformInfo().GetCurNpuArch();238 auto npuArch = op::GetCurrentPlatformInfo().GetCurNpuArch();
239- auto outSuportList = IsRegBase(npuArch) ?239+ auto outSuportList = IsRegBase(npuArch) ? GetOutputDtypeSupportList() : dtypeSupportList;
H
Hhahaha229月9日

outSuportList 少了个 p，应该是 outSupportList，这次正好重排到这一行，建议顺手把拼写改掉，le_scalar 里也有同名的这个变量。

likedislike
240- GetOutputDtypeSupportList() :
241- dtypeSupportList;
242 // 检查out的数据类型240 // 检查out的数据类型
243 OP_CHECK_DTYPE_NOT_SUPPORT(out, outSuportList, return false);241 OP_CHECK_DTYPE_NOT_SUPPORT(out, outSuportList, return false);
244 242 
@@ -255,18 +253,16 @@ static bool CheckPromoteType(const aclTensor* self, const aclScalar* other, cons
255 auto inputSupportList = GetInputDtypeSupportList();253 auto inputSupportList = GetInputDtypeSupportList();
256 // 检查self的数据类型是否在Equal算子的支持列表内254 // 检查self的数据类型是否在Equal算子的支持列表内
257 if (!CheckType(promoteType, inputSupportList)) {255 if (!CheckType(promoteType, inputSupportList)) {
258- OP_LOGE(256+ OP_LOGE(ACLNN_ERR_PARAM_INVALID, "promote dtype %s should be in dtype support list %s.",
259- ACLNN_ERR_PARAM_INVALID, "promote dtype %s should be in dtype support list [%s].",257+ op::ToString(promoteType).GetString(), op::ToString(inputSupportList).GetString());
260- op::ToString(promoteType).GetString(), op::ToString(inputSupportList).GetString());
261 return false;258 return false;
262 }259 }
263 } else {260 } else {
264 promoteType = op::PromoteType(self->GetDataType(), other->GetDataType());261 promoteType = op::PromoteType(self->GetDataType(), other->GetDataType());
265 }262 }
266 if (promoteType == DataType::DT_UNDEFINED) {263 if (promoteType == DataType::DT_UNDEFINED) {
267- OP_LOGE(264+ OP_LOGE(ACLNN_ERR_PARAM_INVALID, "Self dtype %s and other dtype %s can not promote dtype.",
268- ACLNN_ERR_PARAM_INVALID, "Self dtype %s and other dtype %s can not promote dtype.",265+ op::ToString(self->GetDataType()).GetString(), op::ToString(other->GetDataType()).GetString());
269- op::ToString(self->GetDataType()).GetString(), op::ToString(other->GetDataType()).GetString());
270 return false;266 return false;
271 }267 }
272 268 
@@ -308,8 +304,8 @@ static aclnnStatus CheckParams(const aclTensor* self, const aclScalar* other, co
308 return ACLNN_SUCCESS;304 return ACLNN_SUCCESS;
309}305}
310 306 
311-aclnnStatus aclnnEqScalarGetWorkspaceSize(307+aclnnStatus aclnnEqScalarGetWorkspaceSize(const aclTensor* self, const aclScalar* other, aclTensor* out,
312- const aclTensor* self, const aclScalar* other, aclTensor* out, uint64_t* workspaceSize, aclOpExecutor** executor)308+ uint64_t* workspaceSize, aclOpExecutor** executor)
313{309{
314 L2_DFX_PHASE_1(aclnnEqScalar, DFX_IN(self, other), DFX_OUT(out));310 L2_DFX_PHASE_1(aclnnEqScalar, DFX_IN(self, other), DFX_OUT(out));
315 // 固定写法，创建OpExecutor311 // 固定写法，创建OpExecutor
@@ -357,8 +353,8 @@ aclnnStatus aclnnEqScalarGetWorkspaceSize(
357 return ACLNN_SUCCESS;353 return ACLNN_SUCCESS;
358}354}
359 355 
360-aclnnStatus aclnnInplaceEqScalarGetWorkspaceSize(356+aclnnStatus aclnnInplaceEqScalarGetWorkspaceSize(const aclTensor* selfRef, const aclScalar* other,
361- const aclTensor* selfRef, const aclScalar* other, uint64_t* workspaceSize, aclOpExecutor** executor)357+ uint64_t* workspaceSize, aclOpExecutor** executor)
362{358{
363 auto out = const_cast<aclTensor*>(selfRef);359 auto out = const_cast<aclTensor*>(selfRef);
364 return aclnnEqScalarGetWorkspaceSize(selfRef, other, out, workspaceSize, executor);360 return aclnnEqScalarGetWorkspaceSize(selfRef, other, out, workspaceSize, executor);
Mmath/equal/op_api/aclnn_eq_tensor.cpp+21-27
@@ -161,20 +161,18 @@ static bool CheckDtypeValid(const aclTensor* self, const aclTensor* other, const
161 promoteType = op::PromoteType(self->GetDataType(), other->GetDataType());161 promoteType = op::PromoteType(self->GetDataType(), other->GetDataType());
162 }162 }
163 if (promoteType == DataType::DT_UNDEFINED) {163 if (promoteType == DataType::DT_UNDEFINED) {
164- OP_LOGE(164+ OP_LOGE(ACLNN_ERR_PARAM_INVALID, "Self dtype %s and other dtype %s can not promote dtype.",
165- ACLNN_ERR_PARAM_INVALID, "Self dtype %s and other dtype %s can not promote dtype.",165+ op::ToString(self->GetDataType()).GetString(), op::ToString(other->GetDataType()).GetString());
166- op::ToString(self->GetDataType()).GetString(), op::ToString(other->GetDataType()).GetString());
167 return false;166 return false;
168 }167 }
169 168 
170 // 检查promoteType的数据类型是否在equal算子的支持列表内169 // 检查promoteType的数据类型是否在equal算子的支持列表内
171 if (!CheckType(promoteType, inputSupportList)) {170 if (!CheckType(promoteType, inputSupportList)) {
172- OP_LOGE(171+ OP_LOGE(ACLNN_ERR_PARAM_INVALID,
173- ACLNN_ERR_PARAM_INVALID,172+ "Self dtype %s and other dtype %s get promoteType dtype %s should be in "
174- "Self dtype %s and other dtype %s get promoteType dtype %s should be in "173+ "dtype support list %s.",
175- "dtype support list [%s].",174+ op::ToString(self->GetDataType()).GetString(), op::ToString(other->GetDataType()).GetString(),
176- op::ToString(self->GetDataType()).GetString(), op::ToString(other->GetDataType()).GetString(),175+ op::ToString(promoteType).GetString(), op::ToString(inputSupportList).GetString());
177- op::ToString(promoteType).GetString(), op::ToString(inputSupportList).GetString());
178 return false;176 return false;
179 }177 }
180 178 
@@ -194,16 +192,15 @@ static bool CheckShape(const aclTensor* self, const aclTensor* other, const aclT
194 OP_CHECK_BROADCAST_AND_INFER_SHAPE(self, other, outShape, return false);192 OP_CHECK_BROADCAST_AND_INFER_SHAPE(self, other, outShape, return false);
195 193 
196 if (outShape != out->GetViewShape()) {194 if (outShape != out->GetViewShape()) {
197- OP_LOGE(195+ OP_LOGE(ACLNN_ERR_PARAM_INVALID, "BroadcastShape %s is not equal out's shape %s.",
198- ACLNN_ERR_PARAM_INVALID, "BroadcastShape %s is not equal out's shape %s.",196+ op::ToString(outShape).GetString(), op::ToString(out->GetViewShape()).GetString());
199- op::ToString(outShape).GetString(), op::ToString(out->GetViewShape()).GetString());
200 return false;197 return false;
201 }198 }
202 return true;199 return true;
203}200}
204 201 
205-static aclnnStatus CheckParams(202+static aclnnStatus CheckParams(const aclTensor* self, const aclTensor* other, const aclTensor* out,
206- const aclTensor* self, const aclTensor* other, const aclTensor* out, DataType& promoteType)203+ DataType& promoteType)
207{204{
208 // 1. 检查输入的数据类型是否在API支持的数据类型范围之内，需要根据api定义校验205 // 1. 检查输入的数据类型是否在API支持的数据类型范围之内，需要根据api定义校验
209 CHECK_RET(CheckDtypeValid(self, other, out, promoteType), ACLNN_ERR_PARAM_INVALID);206 CHECK_RET(CheckDtypeValid(self, other, out, promoteType), ACLNN_ERR_PARAM_INVALID);
@@ -214,8 +211,8 @@ static aclnnStatus CheckParams(
214 return ACLNN_SUCCESS;211 return ACLNN_SUCCESS;
215}212}
216 213 
217-aclnnStatus aclnnEqTensorGetWorkspaceSize(214+aclnnStatus aclnnEqTensorGetWorkspaceSize(const aclTensor* self, const aclTensor* other, aclTensor* out,
218- const aclTensor* self, const aclTensor* other, aclTensor* out, uint64_t* workspaceSize, aclOpExecutor** executor)215+ uint64_t* workspaceSize, aclOpExecutor** executor)
219{216{
220 L2_DFX_PHASE_1(aclnnEqTensor, DFX_IN(self, other), DFX_OUT(out));217 L2_DFX_PHASE_1(aclnnEqTensor, DFX_IN(self, other), DFX_OUT(out));
221 218 
@@ -280,21 +277,18 @@ static inline aclnnStatus CheckInplace(const aclTensor* selfRef, const aclTensor
280 op::Shape broadcastShape;277 op::Shape broadcastShape;
281 OP_CHECK(278 OP_CHECK(
282 BroadcastInferShape(selfRef->GetViewShape(), other->GetViewShape(), broadcastShape),279 BroadcastInferShape(selfRef->GetViewShape(), other->GetViewShape(), broadcastShape),
283- OP_LOGE(280+ OP_LOGE(ACLNN_ERR_PARAM_INVALID, "Shape of selfRef and other can't broadcast, got %s, %s.",
284- ACLNN_ERR_PARAM_INVALID, "Shape of selfRef and other can't broadcast, got %s, %s.",281+ op::ToString(selfRef->GetViewShape()).GetString(), op::ToString(other->GetViewShape()).GetString()),
285- op::ToString(selfRef->GetViewShape()).GetString(), op::ToString(other->GetViewShape()).GetString()),
286- return ACLNN_ERR_PARAM_INVALID);
287- OP_CHECK(
288- selfRef->GetViewShape() == broadcastShape,
289- OP_LOGE(
290- ACLNN_ERR_PARAM_NULLPTR, "Expected shape of selfRef should be %s, but got %s.",
291- op::ToString(broadcastShape).GetString(), op::ToString(selfRef->GetViewShape()).GetString()),
292 return ACLNN_ERR_PARAM_INVALID);282 return ACLNN_ERR_PARAM_INVALID);
283+ OP_CHECK(selfRef->GetViewShape() == broadcastShape,
284+ OP_LOGE(ACLNN_ERR_PARAM_NULLPTR, "Expected shape of selfRef should be %s, but got %s.",
285+ op::ToString(broadcastShape).GetString(), op::ToString(selfRef->GetViewShape()).GetString()),
286+ return ACLNN_ERR_PARAM_INVALID);
293 return ACLNN_SUCCESS;287 return ACLNN_SUCCESS;
294}288}
295 289 
296-aclnnStatus aclnnInplaceEqTensorGetWorkspaceSize(290+aclnnStatus aclnnInplaceEqTensorGetWorkspaceSize(const aclTensor* selfRef, const aclTensor* other,
297- const aclTensor* selfRef, const aclTensor* other, uint64_t* workspaceSize, aclOpExecutor** executor)291+ uint64_t* workspaceSize, aclOpExecutor** executor)
298{292{
299 auto ret = CheckInplace(selfRef, other);293 auto ret = CheckInplace(selfRef, other);
300 CHECK_RET(ret == ACLNN_SUCCESS, ret);294 CHECK_RET(ret == ACLNN_SUCCESS, ret);
Mmath/equal/op_api/aclnn_isin_tensor_scalar.cpp+10-12
@@ -148,20 +148,18 @@ static bool CheckDtypeValid(const aclTensor* element, const aclScalar* testEleme
148 // 检查element和testElement能否做数据类型推导148 // 检查element和testElement能否做数据类型推导
149 op::DataType promoteType = PromoteTypeScalar(element, testElement);149 op::DataType promoteType = PromoteTypeScalar(element, testElement);
150 if (promoteType == DataType::DT_UNDEFINED) {150 if (promoteType == DataType::DT_UNDEFINED) {
151- OP_LOGE(151+ OP_LOGE(ACLNN_ERR_PARAM_INVALID, "element dtype %s and testElement dtype %s can not promote dtype.",
152- ACLNN_ERR_PARAM_INVALID, "element dtype %s and testElement dtype %s can not promote dtype.",152+ op::ToString(element->GetDataType()).GetString(), op::ToString(testElement->GetDataType()).GetString());
153- op::ToString(element->GetDataType()).GetString(), op::ToString(testElement->GetDataType()).GetString());
154 return false;153 return false;
155 }154 }
156 155 
157 // 检查promoteType的数据类型是否在equal算子的支持列表内156 // 检查promoteType的数据类型是否在equal算子的支持列表内
158 if (!CheckType(promoteType, supportList)) {157 if (!CheckType(promoteType, supportList)) {
159- OP_LOGE(158+ OP_LOGE(ACLNN_ERR_PARAM_INVALID,
160- ACLNN_ERR_PARAM_INVALID,159+ "element dtype %s and testElement dtype %s get promoteType dtype %s should be in "
161- "element dtype %s and testElement dtype %s get promoteType dtype %s should be in "160+ "dtype support list %s.",
162- "dtype support list [%s].",161+ op::ToString(element->GetDataType()).GetString(), op::ToString(testElement->GetDataType()).GetString(),
163- op::ToString(element->GetDataType()).GetString(), op::ToString(testElement->GetDataType()).GetString(),162+ op::ToString(promoteType).GetString(), op::ToString(supportList).GetString());
164- op::ToString(promoteType).GetString(), op::ToString(supportList).GetString());
165 return false;163 return false;
166 }164 }
167 165 
@@ -190,9 +188,9 @@ static aclnnStatus CheckParams(const aclTensor* element, const aclScalar* testEl
190 return ACLNN_SUCCESS;188 return ACLNN_SUCCESS;
191}189}
192 190 
193-aclnnStatus aclnnIsInTensorScalarGetWorkspaceSize(191+aclnnStatus aclnnIsInTensorScalarGetWorkspaceSize(const aclTensor* element, const aclScalar* testElement,
194- const aclTensor* element, const aclScalar* testElement, [[maybe_unused]] bool assumeUnique, bool invert,192+ [[maybe_unused]] bool assumeUnique, bool invert, aclTensor* out,
195- aclTensor* out, uint64_t* workspaceSize, aclOpExecutor** executor)193+ uint64_t* workspaceSize, aclOpExecutor** executor)
196{194{
197 L2_DFX_PHASE_1(aclnnIsInTensorScalar, DFX_IN(element, testElement), DFX_OUT(out));195 L2_DFX_PHASE_1(aclnnIsInTensorScalar, DFX_IN(element, testElement), DFX_OUT(out));
198 196 
Mmath/floor_mod/op_api/aclnn_remainder.cpp+3-3
@@ -190,7 +190,7 @@ static bool CheckPromoteType(const op::DataType selfDtype, const op::DataType ot
190 return false;190 return false;
191 }191 }
192 if (!CheckType(promoteType, DTYPE_SUPPORT_LIST)) {192 if (!CheckType(promoteType, DTYPE_SUPPORT_LIST)) {
193- OP_LOGE(ACLNN_ERR_PARAM_INVALID, "Promote type %s should be in dtype support list [%s].",193+ OP_LOGE(ACLNN_ERR_PARAM_INVALID, "Promote type %s should be in dtype support list %s.",
194 op::ToString(promoteType).GetString(), op::ToString(DTYPE_SUPPORT_LIST).GetString());194 op::ToString(promoteType).GetString(), op::ToString(DTYPE_SUPPORT_LIST).GetString());
195 return false;195 return false;
196 }196 }
@@ -220,7 +220,7 @@ static bool CheckPromoteTypeTensorScalar(const op::DataType selfDtype, const op:
220 return false;220 return false;
221 }221 }
222 if (!CheckType(castDtype, DTYPE_SUPPORT_LIST)) {222 if (!CheckType(castDtype, DTYPE_SUPPORT_LIST)) {
223- OP_LOGE(ACLNN_ERR_PARAM_INVALID, "expected dtype %s should be in dtype support list [%s].",223+ OP_LOGE(ACLNN_ERR_PARAM_INVALID, "expected dtype %s should be in dtype support list %s.",
224 op::ToString(castDtype).GetString(), op::ToString(DTYPE_SUPPORT_LIST).GetString());224 op::ToString(castDtype).GetString(), op::ToString(DTYPE_SUPPORT_LIST).GetString());
225 return false;225 return false;
226 }226 }
@@ -252,7 +252,7 @@ static bool CheckPromoteTypeScalarTensor(const op::DataType selfDtype, const op:
252 return false;252 return false;
253 }253 }
254 if (!CheckType(outDtype, DTYPE_SUPPORT_LIST)) {254 if (!CheckType(outDtype, DTYPE_SUPPORT_LIST)) {
255- OP_LOGE(ACLNN_ERR_PARAM_INVALID, "out dtype %s should be in dtype support list [%s].",255+ OP_LOGE(ACLNN_ERR_PARAM_INVALID, "out dtype %s should be in dtype support list %s.",
256 op::ToString(outDtype).GetString(), op::ToString(DTYPE_SUPPORT_LIST).GetString());256 op::ToString(outDtype).GetString(), op::ToString(DTYPE_SUPPORT_LIST).GetString());
257 return false;257 return false;
258 }258 }
Mmath/greater/op_api/aclnn_gt_tensor.cpp+20-22
@@ -90,10 +90,11 @@ static bool CheckDtypeValid(const aclTensor* self, const aclTensor* other, const
90{90{
91 auto npuArch = op::GetCurrentPlatformInfo().GetCurNpuArch();91 auto npuArch = op::GetCurrentPlatformInfo().GetCurNpuArch();
92 bool is910bSocVersion = (npuArch == NpuArch::DAV_2201 || IsRegBase(npuArch));92 bool is910bSocVersion = (npuArch == NpuArch::DAV_2201 || IsRegBase(npuArch));
93- const std::initializer_list<op::DataType> CURRENT_DTYPE_SUPPORT_LIST =93+ const std::initializer_list<op::DataType> CURRENT_DTYPE_SUPPORT_LIST = is910bSocVersion ? DTYPE_SUPPORT_910B_LIST :
94- is910bSocVersion ? DTYPE_SUPPORT_910B_LIST : DTYPE_SUPPORT_910_LIST;94+ DTYPE_SUPPORT_910_LIST;
95- const std::initializer_list<op::DataType> CURRENT_OUT_DTYPE_SUPPORT_LIST =95+ const std::initializer_list<op::DataType> CURRENT_OUT_DTYPE_SUPPORT_LIST = is910bSocVersion ?
96- is910bSocVersion ? OUT_DTYPE_SUPPORT_910B_LIST : OUT_DTYPE_SUPPORT_910_LIST;96+ OUT_DTYPE_SUPPORT_910B_LIST :
97+ OUT_DTYPE_SUPPORT_910_LIST;
97 98 
98 // 检查out的数据类型是否在Greater算子的支持列表内99 // 检查out的数据类型是否在Greater算子的支持列表内
99 OP_CHECK_DTYPE_NOT_SUPPORT(out, CURRENT_OUT_DTYPE_SUPPORT_LIST, return false);100 OP_CHECK_DTYPE_NOT_SUPPORT(out, CURRENT_OUT_DTYPE_SUPPORT_LIST, return false);
@@ -117,20 +118,18 @@ static bool CheckDtypeValid(const aclTensor* self, const aclTensor* other, const
117 }118 }
118 119 
119 if (promoteType == DataType::DT_UNDEFINED) {120 if (promoteType == DataType::DT_UNDEFINED) {
120- OP_LOGE(121+ OP_LOGE(ACLNN_ERR_PARAM_INVALID, "Self dtype %s and other dtype %s can not promote dtype.",
121- ACLNN_ERR_PARAM_INVALID, "Self dtype %s and other dtype %s can not promote dtype.",122+ op::ToString(self->GetDataType()).GetString(), op::ToString(other->GetDataType()).GetString());
122- op::ToString(self->GetDataType()).GetString(), op::ToString(other->GetDataType()).GetString());
123 return false;123 return false;
124 }124 }
125 125 
126 // 检查promoteType的数据类型是否在Greater算子的支持列表内126 // 检查promoteType的数据类型是否在Greater算子的支持列表内
127 if (!CheckType(promoteType, CURRENT_DTYPE_SUPPORT_LIST)) {127 if (!CheckType(promoteType, CURRENT_DTYPE_SUPPORT_LIST)) {
128- OP_LOGE(128+ OP_LOGE(ACLNN_ERR_PARAM_INVALID,
129- ACLNN_ERR_PARAM_INVALID,129+ "Self dtype %s and other dtype %s get promoteType dtype %s should be in "
H
Hhahaha229月9日

这次修了 5 个文件，但仓里同样写法 dtype support list [%s] 的还有 12 个文件没修，包括 le_scalar、le_tensor、ne_scalar、ne_tensor、tensor_equal/aclnn_equal、add_n、axpy_v2、one_hot、searchsorted、reduce_sum、reduce_mean、reduce_nansum，其中 le_scalar 和 aclnn_equal 同时也被 #5467 改到。这类报错格式问题建议排个跟进 PR 一次性清完，不然修一半容易出现两批 PR 互相踩。

likedislike
130- "Self dtype %s and other dtype %s get promoteType dtype %s should be in "130+ "dtype support list %s.",
131- "dtype support list [%s].",131+ op::ToString(self->GetDataType()).GetString(), op::ToString(other->GetDataType()).GetString(),
132- op::ToString(self->GetDataType()).GetString(), op::ToString(other->GetDataType()).GetString(),132+ op::ToString(promoteType).GetString(), op::ToString(CURRENT_DTYPE_SUPPORT_LIST).GetString());
133- op::ToString(promoteType).GetString(), op::ToString(CURRENT_DTYPE_SUPPORT_LIST).GetString());
134 return false;133 return false;
135 }134 }
136 if (IsRegBase(npuArch)) {135 if (IsRegBase(npuArch)) {
@@ -155,16 +154,15 @@ static bool CheckShape(const aclTensor* self, const aclTensor* other, const aclT
155 OP_CHECK_BROADCAST_AND_INFER_SHAPE(self, other, outShape, return false);154 OP_CHECK_BROADCAST_AND_INFER_SHAPE(self, other, outShape, return false);
156 155 
157 if (outShape != out->GetViewShape()) {156 if (outShape != out->GetViewShape()) {
158- OP_LOGE(157+ OP_LOGE(ACLNN_ERR_PARAM_INVALID, "BroadcastShape %s is not equal out's shape %s.",
159- ACLNN_ERR_PARAM_INVALID, "BroadcastShape %s is not equal out's shape %s.",158+ op::ToString(outShape).GetString(), op::ToString(out->GetViewShape()).GetString());
160- op::ToString(outShape).GetString(), op::ToString(out->GetViewShape()).GetString());
161 return false;159 return false;
162 }160 }
163 return true;161 return true;
164}162}
165 163 
166-static aclnnStatus CheckParams4Gt(164+static aclnnStatus CheckParams4Gt(const aclTensor* self, const aclTensor* other, const aclTensor* out,
167- const aclTensor* self, const aclTensor* other, const aclTensor* out, DataType& promoteType)165+ DataType& promoteType)
168{166{
169 // 1. 检查输入的数据类型是否在API支持的数据类型范围之内，需要根据api定义校验167 // 1. 检查输入的数据类型是否在API支持的数据类型范围之内，需要根据api定义校验
170 CHECK_RET(CheckDtypeValid(self, other, out, promoteType), ACLNN_ERR_PARAM_INVALID);168 CHECK_RET(CheckDtypeValid(self, other, out, promoteType), ACLNN_ERR_PARAM_INVALID);
@@ -175,8 +173,8 @@ static aclnnStatus CheckParams4Gt(
175 return ACLNN_SUCCESS;173 return ACLNN_SUCCESS;
176}174}
177 175 
178-aclnnStatus aclnnGtTensorGetWorkspaceSize(176+aclnnStatus aclnnGtTensorGetWorkspaceSize(const aclTensor* self, const aclTensor* other, aclTensor* out,
179- const aclTensor* self, const aclTensor* other, aclTensor* out, uint64_t* workspaceSize, aclOpExecutor** executor)177+ uint64_t* workspaceSize, aclOpExecutor** executor)
180{178{
181 L2_DFX_PHASE_1(aclnnGtTensor, DFX_IN(self, other), DFX_OUT(out));179 L2_DFX_PHASE_1(aclnnGtTensor, DFX_IN(self, other), DFX_OUT(out));
182 // 固定写法，创建OpExecutor180 // 固定写法，创建OpExecutor
@@ -239,8 +237,8 @@ aclnnStatus aclnnGtTensor(void* workspace, uint64_t workspaceSize, aclOpExecutor
239 return CommonOpExecutorRun(workspace, workspaceSize, executor, stream);237 return CommonOpExecutorRun(workspace, workspaceSize, executor, stream);
240}238}
241 239 
242-aclnnStatus aclnnInplaceGtTensorGetWorkspaceSize(240+aclnnStatus aclnnInplaceGtTensorGetWorkspaceSize(const aclTensor* selfRef, const aclTensor* other,
243- const aclTensor* selfRef, const aclTensor* other, uint64_t* workspaceSize, aclOpExecutor** executor)241+ uint64_t* workspaceSize, aclOpExecutor** executor)
244{242{
245 auto out = const_cast<aclTensor*>(selfRef);243 auto out = const_cast<aclTensor*>(selfRef);
246 return aclnnGtTensorGetWorkspaceSize(selfRef, other, out, workspaceSize, executor);244 return aclnnGtTensorGetWorkspaceSize(selfRef, other, out, workspaceSize, executor);