!2076 update ascend software package 16 Aug 21

Merge pull request !2076 from yanghaoran/release

inc/external/acl/OWNERS

@@ -0,0 +1,9 @@
+approvers:
+- ji_chen
+- wqtshg
+- zhangfan_hq
+reviewers:
+- justin_zhao
+- zhangyongfeng88
+options:
+  no_parent_owners: true

inc/external/acl/acl_prof.h

@@ -40,20 +40,13 @@ typedef enum {
   ACL_AICORE_MEMORY_BANDWIDTH = 2,
   ACL_AICORE_L0B_AND_WIDTH = 3,
   ACL_AICORE_RESOURCE_CONFLICT_RATIO = 4,
-  ACL_AICORE_MEMORY_UB = 5,
   ACL_AICORE_NONE = 0xFF
 } aclprofAicoreMetrics;
 
-typedef enum {
-  ACL_STEP_START = 0,  // step  start
-  ACL_STEP_END = 1     // step  end
-} aclprofStepTag;
-
 typedef struct aclprofConfig aclprofConfig;
 typedef struct aclprofStopConfig aclprofStopConfig;
 typedef struct aclprofAicoreEvents aclprofAicoreEvents;
 typedef struct aclprofSubscribeConfig aclprofSubscribeConfig;
-typedef struct aclprofStepInfo aclprofStepInfo;
 
 /**
  * @ingroup AscendCL
@@ -329,36 +322,6 @@ ACL_FUNC_VISIBILITY uint64_t aclprofGetOpDuration(const void *opInfo, size_t opI
  */
 ACL_FUNC_VISIBILITY size_t aclprofGetModelId(const void *opInfo, size_t opInfoLen, uint32_t index);
 
-/**
- * @ingroup AscendCL
- * @brief
- *
- * @param  stepInfo [IN]     pointer to stepInfo data
- * @param  aclprofstepTag [IN] start or end flag
- * @param  stream [IN] steam info
- *
- * @retval 0 for failed
- */
-ACL_FUNC_VISIBILITY aclError aclprofGetStepTimestamp(aclprofStepInfo *stepInfo, aclprofStepTag tag, aclrtStream stream);
-
-/**
- * @ingroup AscendCL
- * @brief create pointer to aclprofStepInfo data
- *
- *
- * @retval aclprofStepInfo pointer
- */
-ACL_FUNC_VISIBILITY aclprofStepInfo *aclprofCreateStepInfo();
-
-/**
- * @ingroup AscendCL
- * @brief destroy aclprofStepInfo pointer
- *
- *
- * @retval void
- */
-ACL_FUNC_VISIBILITY void aclprofDestroyStepInfo(aclprofStepInfo *stepinfo);
-
 #ifdef __cplusplus
 }
 #endif

inc/external/acl/error_codes/rt_error_codes.h

@@ -44,7 +44,6 @@ static const int32_t ACL_ERROR_RT_STREAM_NO_CB_REG = 107015;          // callbac
 static const int32_t ACL_ERROR_RT_INVALID_MEMORY_TYPE = 107016;       // invalid memory type
 static const int32_t ACL_ERROR_RT_INVALID_HANDLE = 107017;            // invalid handle
 static const int32_t ACL_ERROR_RT_INVALID_MALLOC_TYPE = 107018;       // invalid malloc type
-static const int32_t ACL_ERROR_RT_WAIT_TIMEOUT = 107019;              // wait timeout
 
 static const int32_t ACL_ERROR_RT_FEATURE_NOT_SUPPORT = 207000;  // feature not support
 static const int32_t ACL_ERROR_RT_MEMORY_ALLOCATION = 207001;    // memory allocation error
@@ -57,7 +56,6 @@ static const int32_t ACL_ERROR_RT_NO_EVENT_RESOURCE = 207007;    // no event res
 static const int32_t ACL_ERROR_RT_NO_STREAM_RESOURCE = 207008;   // no stream resource
 static const int32_t ACL_ERROR_RT_NO_NOTIFY_RESOURCE = 207009;   // no notify resource
 static const int32_t ACL_ERROR_RT_NO_MODEL_RESOURCE = 207010;    // no model resource
-static const int32_t ACL_ERROR_RT_NO_CDQ_RESOURCE = 207011;      // no cdq resource
 
 static const int32_t ACL_ERROR_RT_INTERNAL_ERROR = 507000;              // runtime internal error
 static const int32_t ACL_ERROR_RT_TS_ERROR = 507001;                    // ts internel error
@@ -96,7 +94,6 @@ static const int32_t ACL_ERROR_RT_DEV_SETUP_ERROR = 507033;             // devic
 static const int32_t ACL_ERROR_RT_VECTOR_CORE_TIMEOUT = 507034;         // vector core timeout
 static const int32_t ACL_ERROR_RT_VECTOR_CORE_EXCEPTION = 507035;       // vector core exception
 static const int32_t ACL_ERROR_RT_VECTOR_CORE_TRAP_EXCEPTION = 507036;  // vector core trap exception
-static const int32_t ACL_ERROR_RT_CDQ_BATCH_ABNORMAL = 507037;          // cdq alloc batch abnormal
 
 static const int32_t ACL_ERROR_RT_DRV_INTERNAL_ERROR = 507899;    // drv internal error
 static const int32_t ACL_ERROR_RT_AICPU_INTERNAL_ERROR = 507900;  // aicpu internal error

inc/framework/common/fmk_error_codes.h

@@ -20,14 +20,18 @@
 #if defined(_MSC_VER)
 #ifdef FUNC_VISIBILITY
 #define GE_FUNC_VISIBILITY _declspec(dllexport)
+#define GE_OBJECT_VISIBILITY
 #else
 #define GE_FUNC_VISIBILITY
+#define GE_OBJECT_VISIBILITY
 #endif
 #else
 #ifdef FUNC_VISIBILITY
 #define GE_FUNC_VISIBILITY __attribute__((visibility("default")))
+#define GE_OBJECT_VISIBILITY
 #else
 #define GE_FUNC_VISIBILITY
+#define GE_OBJECT_VISIBILITY __attribute__((visibility("hidden")))
 #endif
 #endif
 
@@ -70,7 +74,9 @@ class GE_FUNC_VISIBILITY StatusFactory {
 
 class GE_FUNC_VISIBILITY ErrorNoRegisterar {
  public:
-  ErrorNoRegisterar(uint32_t err, const std::string &desc) { StatusFactory::Instance()->RegisterErrorNo(err, desc); }
+  ErrorNoRegisterar(uint32_t err, const std::string &desc) {
+    StatusFactory::Instance()->RegisterErrorNo(err, desc);
+  }
   ~ErrorNoRegisterar() {}
 };
 

inc/framework/common/ge_compiler_options.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

inc/framework/common/l2_cache_optimize.h

@@ -104,7 +104,7 @@ class GE_FUNC_VISIBILITY L2CacheOptimize {
 
   // maximum common divisor
   uint32_t Measure(uint32_t x, uint32_t y) {
-    if (x == 0 || y == 0) return RC_VALUE_DEFAULT;
+    if ((x == 0) || (y == 0)) return RC_VALUE_DEFAULT;
     uint32_t z = y;
     while (x % y != 0) {
       z = x % y;

inc/framework/common/profiling/ge_profiling.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

inc/framework/common/profiling/ge_runner_profiling.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

inc/framework/common/string_util.h

@@ -45,16 +45,16 @@ class GE_FUNC_VISIBILITY StringUtils {
  public:
   static std::string &Ltrim(std::string &s) {
 #if __cplusplus >= 201103L
-    (void)s.erase(s.begin(), std::find_if(s.begin(), s.end(), [](int c) { return !std::isspace(c); }));
+    (void)s.erase(s.begin(), std::find_if(s.begin(), s.end(), [](int c) { return std::isspace(c) == 0; }));
 #else
     (void)s.erase(s.begin(), std::find_if(s.begin(), s.end(), std::not1(std::ptr_fun<int, int>(std::isspace))));
 #endif
     return s;
   }
   // lint -esym(551,*)
-  static std::string &Rtrim(std::string &s) {  /*lint !e618*/
+  static std::string &Rtrim(std::string &s) { /*lint !e618*/
 #if __cplusplus >= 201103L
-    (void)s.erase(s.begin(), std::find_if(s.begin(), s.end(), [](int c) { return !std::isspace(c); }));
+    (void)s.erase(s.begin(), std::find_if(s.begin(), s.end(), [](int c) { return std::isspace(c) == 0; }));
 #else
     (void)s.erase(std::find_if(s.rbegin(), s.rend(), std::not1(std::ptr_fun<int, int>(std::isspace))).base(), s.end());
 #endif
@@ -67,7 +67,9 @@ class GE_FUNC_VISIBILITY StringUtils {
   ///  @param [in] string to be trimmed
   ///  @return string after trim
   ///
-  static std::string &Trim(std::string &s) { return Ltrim(Rtrim(s)); }
+  static std::string &Trim(std::string &s) {
+    return Ltrim(Rtrim(s));
+  }
 
   ///
   ///  @ingroup domi_common
@@ -92,7 +94,7 @@ class GE_FUNC_VISIBILITY StringUtils {
     }
 
     auto str_size = str.size();
-    if (str_size > 0 && str[str_size - 1] == delim) {
+    if ((str_size > 0) && (str[str_size - 1] == delim)) {
       elems.emplace_back("");
     }
 

inc/framework/common/taskdown_common.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

inc/framework/memory/memory_api.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

inc/framework/omg/ge_init.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

inc/framework/omg/omg.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

inc/framework/omg/parser/model_parser.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -36,7 +36,7 @@ using Status = domi::Status;
 
 namespace domi {
 using GetGraphCallback = std::function<std::unique_ptr<google::protobuf::Message>(
-  const google::protobuf::Message *root_proto, const std::string &graph)>;
+    const google::protobuf::Message *root_proto, const std::string &graph)>;
 
 using GetGraphCallbackV2 = std::function<std::string(const std::string &subgraph_name)>;
 
@@ -109,7 +109,9 @@ class GE_FUNC_VISIBILITY ModelParser {
    * @return SUCCESS
    * @return Others failed
    */
-  virtual Status ToJson(const char *model_file, const char *json_file) { return domi::SUCCESS; }
+  virtual Status ToJson(const char *model_file, const char *json_file) {
+    return domi::SUCCESS;
+  }
 
   /*
    * @ingroup domi_omg
@@ -129,7 +131,9 @@ class GE_FUNC_VISIBILITY ModelParser {
    * @return SUCCESS
    * @return Others failed
    */
-  virtual Status ParseProto(const std::string &serialized_proto, ge::ComputeGraphPtr &graph) { return UNSUPPORTED; }
+  virtual Status ParseProto(const std::string &serialized_proto, ge::ComputeGraphPtr &graph) {
+    return UNSUPPORTED;
+  }
 
   /**
    * @ingroup domi_omg

inc/framework/omg/parser/op_parser.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

inc/framework/omg/parser/parser_api.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -24,8 +24,8 @@
 
 namespace ge {
 // Initialize parser
-GE_FUNC_VISIBILITY Status ParserInitialize(const std::map<std::string, std::string>& options);
+GE_FUNC_VISIBILITY Status ParserInitialize(const std::map<std::string, std::string> &options);
 // Finalize parser, release all resources
 GE_FUNC_VISIBILITY Status ParserFinalize();
 }  // namespace ge
-#endif // INC_FRAMEWORK_OMG_PARSER_PARSER_API_H_
+#endif  // INC_FRAMEWORK_OMG_PARSER_PARSER_API_H_

inc/framework/omg/parser/parser_factory.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

inc/framework/omg/parser/weights_parser.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

metadef

@@ -1 +1 @@
-Subproject commit e7b48d87d861921299e7c0fe293aaeac61136900
+Subproject commit 51418f61f26599c85bee2b57328afbbf1c9927c7

third_party/fwkacllib/inc/aicpu/aicpu_schedule/aicpu_op_type_list.h

@@ -1,60 +1,60 @@
-/**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef AICPU_OP_TYPE_LIST_H_
-#define AICPU_OP_TYPE_LIST_H_
-
-enum OpKernelType {
-    TF_KERNEL,
-    CPU_KERNEL
-};
-
-enum ReturnCode {
-    OP_TYPE_NOT_SUPPORT,
-    FORMAT_NOT_SUPPORT,
-    DTYPE_NOT_SUPPORT
-};
-
-#pragma pack(push, 1)
-//One byte alignment
-struct SysOpInfo {
-    uint64_t opLen;
-    uint64_t opType;
-    OpKernelType kernelsType;
-};
-
-struct OpParamInfo {
-    uint64_t num;
-    uint64_t dtypeList;
-    uint64_t formatList;
-};
-
-struct SysOpCheckInfo {
-    uint64_t opListNum;
-    uint64_t offSetLen;
-    uint64_t sysOpInfoList;
-    uint64_t opParamInfoList;
-};
-
-struct SysOpCheckResp {
-    uint64_t opListNum;
-    bool isWithoutJson;
-    uint64_t returnCodeList;
-    uint64_t sysOpInfoList;
-    uint64_t opParamInfoList;
-};
-#pragma pack(pop)
-#endif  // AICPU_OP_TYPE_LIST_H_
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef AICPU_OP_TYPE_LIST_H_
+#define AICPU_OP_TYPE_LIST_H_
+
+enum OpKernelType {
+    TF_KERNEL,
+    CPU_KERNEL
+};
+
+enum ReturnCode {
+    OP_TYPE_NOT_SUPPORT,
+    FORMAT_NOT_SUPPORT,
+    DTYPE_NOT_SUPPORT
+};
+
+#pragma pack(push, 1)
+//One byte alignment
+struct SysOpInfo {
+    uint64_t opLen;
+    uint64_t opType;
+    OpKernelType kernelsType;
+};
+
+struct OpParamInfo {
+    uint64_t num;
+    uint64_t dtypeList;
+    uint64_t formatList;
+};
+
+struct SysOpCheckInfo {
+    uint64_t opListNum;
+    uint64_t offSetLen;
+    uint64_t sysOpInfoList;
+    uint64_t opParamInfoList;
+};
+
+struct SysOpCheckResp {
+    uint64_t opListNum;
+    bool isWithoutJson;
+    uint64_t returnCodeList;
+    uint64_t sysOpInfoList;
+    uint64_t opParamInfoList;
+};
+#pragma pack(pop)
+#endif  // AICPU_OP_TYPE_LIST_H_

third_party/fwkacllib/inc/cce/aicpu_engine.h

@@ -13,6 +13,7 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+
 #ifndef AICPU_ENGINE_H__
 #define AICPU_ENGINE_H__
 

third_party/fwkacllib/inc/external/runtime/rt_error_codes.h

@@ -1,103 +1,109 @@
-/**
-* @file rt_error_codes.h
-*
-* Copyright (C) Huawei Technologies Co., Ltd. 2019-2020. All Rights Reserved.
-*
-* This program is distributed in the hope that it will be useful,
-* but WITHOUT ANY WARRANTY; without even the implied warranty of
-* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
-*/
-
-#ifndef __INC_EXTERNEL_RT_ERROR_CODES_H__
-#define __INC_EXTERNEL_RT_ERROR_CODES_H__
-
-#include <stddef.h>
-
-#ifdef __cplusplus
-extern "C" {
-#endif
-
-static const int32_t ACL_RT_SUCCESS                          = 0; // success
-
-static const int32_t ACL_ERROR_RT_PARAM_INVALID              = 107000; // param invalid
-static const int32_t ACL_ERROR_RT_INVALID_DEVICEID           = 107001; // invalid device id
-static const int32_t ACL_ERROR_RT_CONTEXT_NULL               = 107002; // current context null
-static const int32_t ACL_ERROR_RT_STREAM_CONTEXT             = 107003; // stream not in current context
-static const int32_t ACL_ERROR_RT_MODEL_CONTEXT              = 107004; // model not in current context
-static const int32_t ACL_ERROR_RT_STREAM_MODEL               = 107005; // stream not in model
-static const int32_t ACL_ERROR_RT_EVENT_TIMESTAMP_INVALID    = 107006; // event timestamp invalid
-static const int32_t ACL_ERROR_RT_EVENT_TIMESTAMP_REVERSAL   = 107007; // event timestamp reversal
-static const int32_t ACL_ERROR_RT_ADDR_UNALIGNED             = 107008; // memory address unaligned
-static const int32_t ACL_ERROR_RT_FILE_OPEN                  = 107009; // open file failed
-static const int32_t ACL_ERROR_RT_FILE_WRITE                 = 107010; // write file failed
-static const int32_t ACL_ERROR_RT_STREAM_SUBSCRIBE           = 107011; // error subscribe stream
-static const int32_t ACL_ERROR_RT_THREAD_SUBSCRIBE           = 107012; // error subscribe thread
-static const int32_t ACL_ERROR_RT_GROUP_NOT_SET              = 107013; // group not set
-static const int32_t ACL_ERROR_RT_GROUP_NOT_CREATE           = 107014; // group not create
-static const int32_t ACL_ERROR_RT_STREAM_NO_CB_REG           = 107015; // callback not register to stream
-static const int32_t ACL_ERROR_RT_INVALID_MEMORY_TYPE        = 107016; // invalid memory type
-static const int32_t ACL_ERROR_RT_INVALID_HANDLE             = 107017; // invalid handle
-static const int32_t ACL_ERROR_RT_INVALID_MALLOC_TYPE        = 107018; // invalid malloc type
-static const int32_t ACL_ERROR_RT_WAIT_TIMEOUT               = 107019; // wait timeout
-
-static const int32_t ACL_ERROR_RT_FEATURE_NOT_SUPPORT        = 207000; // feature not support
-static const int32_t ACL_ERROR_RT_MEMORY_ALLOCATION          = 207001; // memory allocation error
-static const int32_t ACL_ERROR_RT_MEMORY_FREE                = 207002; // memory free error
-static const int32_t ACL_ERROR_RT_AICORE_OVER_FLOW           = 207003; // aicore over flow
-static const int32_t ACL_ERROR_RT_NO_DEVICE                  = 207004; // no device
-static const int32_t ACL_ERROR_RT_RESOURCE_ALLOC_FAIL        = 207005; // resource alloc fail
-static const int32_t ACL_ERROR_RT_NO_PERMISSION              = 207006; // no permission
-static const int32_t ACL_ERROR_RT_NO_EVENT_RESOURCE          = 207007; // no event resource
-static const int32_t ACL_ERROR_RT_NO_STREAM_RESOURCE         = 207008; // no stream resource
-static const int32_t ACL_ERROR_RT_NO_NOTIFY_RESOURCE         = 207009; // no notify resource
-static const int32_t ACL_ERROR_RT_NO_MODEL_RESOURCE          = 207010; // no model resource
-static const int32_t ACL_ERROR_RT_NO_CDQ_RESOURCE            = 207011; // no cdq resource
-
-static const int32_t ACL_ERROR_RT_INTERNAL_ERROR             = 507000; // runtime internal error
-static const int32_t ACL_ERROR_RT_TS_ERROR                   = 507001; // ts internel error
-static const int32_t ACL_ERROR_RT_STREAM_TASK_FULL           = 507002; // task full in stream
-static const int32_t ACL_ERROR_RT_STREAM_TASK_EMPTY          = 507003; // task empty in stream
-static const int32_t ACL_ERROR_RT_STREAM_NOT_COMPLETE        = 507004; // stream not complete
-static const int32_t ACL_ERROR_RT_END_OF_SEQUENCE            = 507005; // end of sequence
-static const int32_t ACL_ERROR_RT_EVENT_NOT_COMPLETE         = 507006; // event not complete
-static const int32_t ACL_ERROR_RT_CONTEXT_RELEASE_ERROR      = 507007; // context release error
-static const int32_t ACL_ERROR_RT_SOC_VERSION                = 507008; // soc version error
-static const int32_t ACL_ERROR_RT_TASK_TYPE_NOT_SUPPORT      = 507009; // task type not support
-static const int32_t ACL_ERROR_RT_LOST_HEARTBEAT             = 507010; // ts lost heartbeat
-static const int32_t ACL_ERROR_RT_MODEL_EXECUTE              = 507011; // model execute failed
-static const int32_t ACL_ERROR_RT_REPORT_TIMEOUT             = 507012; // report timeout
-static const int32_t ACL_ERROR_RT_SYS_DMA                    = 507013; // sys dma error
-static const int32_t ACL_ERROR_RT_AICORE_TIMEOUT             = 507014; // aicore timeout
-static const int32_t ACL_ERROR_RT_AICORE_EXCEPTION           = 507015; // aicore exception
-static const int32_t ACL_ERROR_RT_AICORE_TRAP_EXCEPTION      = 507016; // aicore trap exception
-static const int32_t ACL_ERROR_RT_AICPU_TIMEOUT              = 507017; // aicpu timeout
-static const int32_t ACL_ERROR_RT_AICPU_EXCEPTION            = 507018; // aicpu exception
-static const int32_t ACL_ERROR_RT_AICPU_DATADUMP_RSP_ERR     = 507019; // aicpu datadump response error
-static const int32_t ACL_ERROR_RT_AICPU_MODEL_RSP_ERR        = 507020; // aicpu model operate response error
-static const int32_t ACL_ERROR_RT_PROFILING_ERROR            = 507021; // profiling error
-static const int32_t ACL_ERROR_RT_IPC_ERROR                  = 507022; // ipc error
-static const int32_t ACL_ERROR_RT_MODEL_ABORT_NORMAL         = 507023; // model abort normal
-static const int32_t ACL_ERROR_RT_KERNEL_UNREGISTERING       = 507024; // kernel unregistering
-static const int32_t ACL_ERROR_RT_RINGBUFFER_NOT_INIT        = 507025; // ringbuffer not init
-static const int32_t ACL_ERROR_RT_RINGBUFFER_NO_DATA         = 507026; // ringbuffer no data
-static const int32_t ACL_ERROR_RT_KERNEL_LOOKUP              = 507027; // kernel lookup error
-static const int32_t ACL_ERROR_RT_KERNEL_DUPLICATE           = 507028; // kernel register duplicate
-static const int32_t ACL_ERROR_RT_DEBUG_REGISTER_FAIL        = 507029; // debug register failed
-static const int32_t ACL_ERROR_RT_DEBUG_UNREGISTER_FAIL      = 507030; // debug unregister failed
-static const int32_t ACL_ERROR_RT_LABEL_CONTEXT              = 507031; // label not in current context
-static const int32_t ACL_ERROR_RT_PROGRAM_USE_OUT            = 507032; // program register num use out
-static const int32_t ACL_ERROR_RT_DEV_SETUP_ERROR            = 507033; // device setup error
-static const int32_t ACL_ERROR_RT_VECTOR_CORE_TIMEOUT        = 507034; // vector core timeout
-static const int32_t ACL_ERROR_RT_VECTOR_CORE_EXCEPTION      = 507035; // vector core exception
-static const int32_t ACL_ERROR_RT_VECTOR_CORE_TRAP_EXCEPTION = 507036; // vector core trap exception
-static const int32_t ACL_ERROR_RT_CDQ_BATCH_ABNORMAL         = 507037; // cdq alloc batch abnormal
-
-static const int32_t ACL_ERROR_RT_DRV_INTERNAL_ERROR         = 507899; // drv internal error
-static const int32_t ACL_ERROR_RT_AICPU_INTERNAL_ERROR       = 507900; // aicpu internal error
-static const int32_t ACL_ERROR_RT_SOCKET_CLOSE               = 507901; // hdc disconnect
-
-#ifdef __cplusplus
-}
-#endif
-
-#endif // __INC_EXTERNEL_RT_ERROR_CODES_H__
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef __INC_EXTERNEL_RT_ERROR_CODES_H__
+#define __INC_EXTERNEL_RT_ERROR_CODES_H__
+
+#include <stddef.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+static const int32_t ACL_RT_SUCCESS                          = 0; // success
+
+static const int32_t ACL_ERROR_RT_PARAM_INVALID              = 107000; // param invalid
+static const int32_t ACL_ERROR_RT_INVALID_DEVICEID           = 107001; // invalid device id
+static const int32_t ACL_ERROR_RT_CONTEXT_NULL               = 107002; // current context null
+static const int32_t ACL_ERROR_RT_STREAM_CONTEXT             = 107003; // stream not in current context
+static const int32_t ACL_ERROR_RT_MODEL_CONTEXT              = 107004; // model not in current context
+static const int32_t ACL_ERROR_RT_STREAM_MODEL               = 107005; // stream not in model
+static const int32_t ACL_ERROR_RT_EVENT_TIMESTAMP_INVALID    = 107006; // event timestamp invalid
+static const int32_t ACL_ERROR_RT_EVENT_TIMESTAMP_REVERSAL   = 107007; // event timestamp reversal
+static const int32_t ACL_ERROR_RT_ADDR_UNALIGNED             = 107008; // memory address unaligned
+static const int32_t ACL_ERROR_RT_FILE_OPEN                  = 107009; // open file failed
+static const int32_t ACL_ERROR_RT_FILE_WRITE                 = 107010; // write file failed
+static const int32_t ACL_ERROR_RT_STREAM_SUBSCRIBE           = 107011; // error subscribe stream
+static const int32_t ACL_ERROR_RT_THREAD_SUBSCRIBE           = 107012; // error subscribe thread
+static const int32_t ACL_ERROR_RT_GROUP_NOT_SET              = 107013; // group not set
+static const int32_t ACL_ERROR_RT_GROUP_NOT_CREATE           = 107014; // group not create
+static const int32_t ACL_ERROR_RT_STREAM_NO_CB_REG           = 107015; // callback not register to stream
+static const int32_t ACL_ERROR_RT_INVALID_MEMORY_TYPE        = 107016; // invalid memory type
+static const int32_t ACL_ERROR_RT_INVALID_HANDLE             = 107017; // invalid handle
+static const int32_t ACL_ERROR_RT_INVALID_MALLOC_TYPE        = 107018; // invalid malloc type
+static const int32_t ACL_ERROR_RT_WAIT_TIMEOUT               = 107019; // wait timeout
+
+static const int32_t ACL_ERROR_RT_FEATURE_NOT_SUPPORT        = 207000; // feature not support
+static const int32_t ACL_ERROR_RT_MEMORY_ALLOCATION          = 207001; // memory allocation error
+static const int32_t ACL_ERROR_RT_MEMORY_FREE                = 207002; // memory free error
+static const int32_t ACL_ERROR_RT_AICORE_OVER_FLOW           = 207003; // aicore over flow
+static const int32_t ACL_ERROR_RT_NO_DEVICE                  = 207004; // no device
+static const int32_t ACL_ERROR_RT_RESOURCE_ALLOC_FAIL        = 207005; // resource alloc fail
+static const int32_t ACL_ERROR_RT_NO_PERMISSION              = 207006; // no permission
+static const int32_t ACL_ERROR_RT_NO_EVENT_RESOURCE          = 207007; // no event resource
+static const int32_t ACL_ERROR_RT_NO_STREAM_RESOURCE         = 207008; // no stream resource
+static const int32_t ACL_ERROR_RT_NO_NOTIFY_RESOURCE         = 207009; // no notify resource
+static const int32_t ACL_ERROR_RT_NO_MODEL_RESOURCE          = 207010; // no model resource
+static const int32_t ACL_ERROR_RT_NO_CDQ_RESOURCE            = 207011; // no cdq resource
+
+static const int32_t ACL_ERROR_RT_INTERNAL_ERROR             = 507000; // runtime internal error
+static const int32_t ACL_ERROR_RT_TS_ERROR                   = 507001; // ts internel error
+static const int32_t ACL_ERROR_RT_STREAM_TASK_FULL           = 507002; // task full in stream
+static const int32_t ACL_ERROR_RT_STREAM_TASK_EMPTY          = 507003; // task empty in stream
+static const int32_t ACL_ERROR_RT_STREAM_NOT_COMPLETE        = 507004; // stream not complete
+static const int32_t ACL_ERROR_RT_END_OF_SEQUENCE            = 507005; // end of sequence
+static const int32_t ACL_ERROR_RT_EVENT_NOT_COMPLETE         = 507006; // event not complete
+static const int32_t ACL_ERROR_RT_CONTEXT_RELEASE_ERROR      = 507007; // context release error
+static const int32_t ACL_ERROR_RT_SOC_VERSION                = 507008; // soc version error
+static const int32_t ACL_ERROR_RT_TASK_TYPE_NOT_SUPPORT      = 507009; // task type not support
+static const int32_t ACL_ERROR_RT_LOST_HEARTBEAT             = 507010; // ts lost heartbeat
+static const int32_t ACL_ERROR_RT_MODEL_EXECUTE              = 507011; // model execute failed
+static const int32_t ACL_ERROR_RT_REPORT_TIMEOUT             = 507012; // report timeout
+static const int32_t ACL_ERROR_RT_SYS_DMA                    = 507013; // sys dma error
+static const int32_t ACL_ERROR_RT_AICORE_TIMEOUT             = 507014; // aicore timeout
+static const int32_t ACL_ERROR_RT_AICORE_EXCEPTION           = 507015; // aicore exception
+static const int32_t ACL_ERROR_RT_AICORE_TRAP_EXCEPTION      = 507016; // aicore trap exception
+static const int32_t ACL_ERROR_RT_AICPU_TIMEOUT              = 507017; // aicpu timeout
+static const int32_t ACL_ERROR_RT_AICPU_EXCEPTION            = 507018; // aicpu exception
+static const int32_t ACL_ERROR_RT_AICPU_DATADUMP_RSP_ERR     = 507019; // aicpu datadump response error
+static const int32_t ACL_ERROR_RT_AICPU_MODEL_RSP_ERR        = 507020; // aicpu model operate response error
+static const int32_t ACL_ERROR_RT_PROFILING_ERROR            = 507021; // profiling error
+static const int32_t ACL_ERROR_RT_IPC_ERROR                  = 507022; // ipc error
+static const int32_t ACL_ERROR_RT_MODEL_ABORT_NORMAL         = 507023; // model abort normal
+static const int32_t ACL_ERROR_RT_KERNEL_UNREGISTERING       = 507024; // kernel unregistering
+static const int32_t ACL_ERROR_RT_RINGBUFFER_NOT_INIT        = 507025; // ringbuffer not init
+static const int32_t ACL_ERROR_RT_RINGBUFFER_NO_DATA         = 507026; // ringbuffer no data
+static const int32_t ACL_ERROR_RT_KERNEL_LOOKUP              = 507027; // kernel lookup error
+static const int32_t ACL_ERROR_RT_KERNEL_DUPLICATE           = 507028; // kernel register duplicate
+static const int32_t ACL_ERROR_RT_DEBUG_REGISTER_FAIL        = 507029; // debug register failed
+static const int32_t ACL_ERROR_RT_DEBUG_UNREGISTER_FAIL      = 507030; // debug unregister failed
+static const int32_t ACL_ERROR_RT_LABEL_CONTEXT              = 507031; // label not in current context
+static const int32_t ACL_ERROR_RT_PROGRAM_USE_OUT            = 507032; // program register num use out
+static const int32_t ACL_ERROR_RT_DEV_SETUP_ERROR            = 507033; // device setup error
+static const int32_t ACL_ERROR_RT_VECTOR_CORE_TIMEOUT        = 507034; // vector core timeout
+static const int32_t ACL_ERROR_RT_VECTOR_CORE_EXCEPTION      = 507035; // vector core exception
+static const int32_t ACL_ERROR_RT_VECTOR_CORE_TRAP_EXCEPTION = 507036; // vector core trap exception
+static const int32_t ACL_ERROR_RT_CDQ_BATCH_ABNORMAL         = 507037; // cdq alloc batch abnormal
+
+static const int32_t ACL_ERROR_RT_DRV_INTERNAL_ERROR         = 507899; // drv internal error
+static const int32_t ACL_ERROR_RT_AICPU_INTERNAL_ERROR       = 507900; // aicpu internal error
+static const int32_t ACL_ERROR_RT_SOCKET_CLOSE               = 507901; // hdc disconnect
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif // __INC_EXTERNEL_RT_ERROR_CODES_H__

third_party/fwkacllib/inc/mmpa/sub_inc/mmpa_typedef_win.h

@@ -1,83 +1,83 @@
-/**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef MMPA_TYPEDEF_WIN_H
-#define MMPA_TYPEDEF_WIN_H
-
-#ifdef __cplusplus
-#if __cplusplus
-extern "C" {
-#endif  // __cpluscplus
-#endif  // __cpluscplus
-
-#ifndef FALSE
-#define FALSE 0
-#endif
-
-#ifndef TRUE
-#define TRUE 1
-#endif
-
-#define EN_OK 0
-#define EN_ERR 1
-#define EN_ERROR (-1)
-#define EN_INVALID_PARAM (-2)
-#define EN_TIMEOUT (-3)
-
-#define HANDLE_INVALID_VALUE (-1)
-#define INVALID_SOCKET_HANDLE INVALID_SOCKET
-#define MMPA_MEM_MAX_LEN (0x7fffffff)
-#define MMPA_PROCESS_ERROR (0x7fffffff)
-
-#define MMPA_ONE_THOUSAND 1000
-#define MMPA_COMPUTER_BEGIN_YEAR 1900
-#define SUMMER_TIME_OR_NOT (-1)
-#define MMPA_ZERO 0
-#define MMPA_VALUE_ONE 1
-#define MMPA_SOCKET_MAIN_EDITION 2
-#define MMPA_SOCKET_SECOND_EDITION 0
-#define MMPA_PIPE_BUF_SIZE 1024
-#define MMPA_MAX_SCANDIR_COUNT 1024
-#define MAX_IOVEC_SIZE 32
-#define MMPA_PIPE_COUNT 2
-#define MMPA_THREADNAME_SIZE 16
-#define MMPA_MIN_OS_NAME_SIZE (MAX_COMPUTERNAME_LENGTH + 1)
-#define MMPA_MIN_OS_VERSION_SIZE 64
-
-#define MMPA_MAX_NI 19
-#define MMPA_MIDDLE_NI 5
-#define MMPA_LOW_NI (-5)
-#define MMPA_MIN_NI (-20)
-#define MMPA_MAX_FILE 128
-
-#define MMPA_MAX_THREAD_PIO 99
-#define MMPA_MIDDLE_THREAD_PIO 66
-#define MMPA_LOW_THREAD_PIO 33
-#define MMPA_MIN_THREAD_PIO 1
-
-#define MMPA_THREAD_SCHED_RR 0
-#define MMPA_THREAD_SCHED_FIFO 0
-#define MMPA_THREAD_SCHED_OTHER 0
-#define MMPA_THREAD_MIN_STACK_SIZE 0
-
-#define MM_MUTEX_INITIALIZER NULL
-
-#ifdef __cplusplus
-#if __cplusplus
-}
-#endif  // __cpluscplus
-#endif  // __cpluscplus
-#endif  // _MMPA_TYPEDEF_WIN_H_
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef MMPA_TYPEDEF_WIN_H
+#define MMPA_TYPEDEF_WIN_H
+
+#ifdef __cplusplus
+#if __cplusplus
+extern "C" {
+#endif  // __cpluscplus
+#endif  // __cpluscplus
+
+#ifndef FALSE
+#define FALSE 0
+#endif
+
+#ifndef TRUE
+#define TRUE 1
+#endif
+
+#define EN_OK 0
+#define EN_ERR 1
+#define EN_ERROR (-1)
+#define EN_INVALID_PARAM (-2)
+#define EN_TIMEOUT (-3)
+
+#define HANDLE_INVALID_VALUE (-1)
+#define INVALID_SOCKET_HANDLE INVALID_SOCKET
+#define MMPA_MEM_MAX_LEN (0x7fffffff)
+#define MMPA_PROCESS_ERROR (0x7fffffff)
+
+#define MMPA_ONE_THOUSAND 1000
+#define MMPA_COMPUTER_BEGIN_YEAR 1900
+#define SUMMER_TIME_OR_NOT (-1)
+#define MMPA_ZERO 0
+#define MMPA_VALUE_ONE 1
+#define MMPA_SOCKET_MAIN_EDITION 2
+#define MMPA_SOCKET_SECOND_EDITION 0
+#define MMPA_PIPE_BUF_SIZE 1024
+#define MMPA_MAX_SCANDIR_COUNT 1024
+#define MAX_IOVEC_SIZE 32
+#define MMPA_PIPE_COUNT 2
+#define MMPA_THREADNAME_SIZE 16
+#define MMPA_MIN_OS_NAME_SIZE (MAX_COMPUTERNAME_LENGTH + 1)
+#define MMPA_MIN_OS_VERSION_SIZE 64
+
+#define MMPA_MAX_NI 19
+#define MMPA_MIDDLE_NI 5
+#define MMPA_LOW_NI (-5)
+#define MMPA_MIN_NI (-20)
+#define MMPA_MAX_FILE 128
+
+#define MMPA_MAX_THREAD_PIO 99
+#define MMPA_MIDDLE_THREAD_PIO 66
+#define MMPA_LOW_THREAD_PIO 33
+#define MMPA_MIN_THREAD_PIO 1
+
+#define MMPA_THREAD_SCHED_RR 0
+#define MMPA_THREAD_SCHED_FIFO 0
+#define MMPA_THREAD_SCHED_OTHER 0
+#define MMPA_THREAD_MIN_STACK_SIZE 0
+
+#define MM_MUTEX_INITIALIZER NULL
+
+#ifdef __cplusplus
+#if __cplusplus
+}
+#endif  // __cpluscplus
+#endif  // __cpluscplus
+#endif  // _MMPA_TYPEDEF_WIN_H_

third_party/fwkacllib/inc/mmpa/sub_inc/mmpa_win.h

@@ -1,4 +1,4 @@
-/**
+/**
  * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");

third_party/fwkacllib/inc/ops/aipp.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/all_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/array_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -1249,38 +1249,6 @@ REG_OP(ExpandD)
     .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT, DT_INT32, DT_INT8, DT_UINT8}))
     .REQUIRED_ATTR(shape, ListInt)
     .OP_END_FACTORY_REG(ExpandD)
-
-/**
-*@brief Finds unique elements in a 1D tensor. \n
-
-*@par Inputs:
-*x: 1D tensor. Must be one of the following types:
-*     float16, float32, double, int64, int32, int16, uint16, int8 ,uint8. \n
-
-*@par Attributes:
-*@li return_inverse: Whether to also return the indices for where elements in the original 
-*                input ended up in the returned unique list.
-*@li return_inverse: Whether to also return the counts for each unique element.
-
-*@par Outputs:
-*@li y1: The output list of unique scalar elements. Has the same type as "x".
-*@li y2: Representing the indices for where elements in the original input map to in the output.
-*@li y3: Representing the number of occurrences for each unique value or tensor. \n
-
-* @par Third-party framework compatibility
-* Compatible with the troch operator _unique2.
-*/
-
-REG_OP(UniqueWithCountsAndSorting)
-    .INPUT(x, TensorType({ DT_INT8, DT_UINT8, DT_INT16, DT_UINT16, \
-           DT_INT32, DT_INT64, DT_FLOAT16, DT_FLOAT, DT_DOUBLE }))
-    .OUTPUT(y1, TensorType({ DT_INT8, DT_UINT8, DT_INT16, DT_UINT16, \
-           DT_INT32, DT_INT64, DT_FLOAT16, DT_FLOAT, DT_DOUBLE }))
-    .OUTPUT(y2, TensorType({ DT_INT32, DT_INT64 }))
-    .OUTPUT(y3, TensorType({ DT_INT32, DT_INT64 }))
-    .ATTR(return_inverse, Bool, false)
-    .ATTR(return_counts, Bool, false)
-    .OP_END_FACTORY_REG(UniqueWithCountsAndSorting)
 }  // namespace ge
 
 #endif  // OPS_BUILT_IN_OP_PROTO_INC_ARRAY_OPS_H_

third_party/fwkacllib/inc/ops/audio_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/avg_pool_1d_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/batch_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/bitwise_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/boosted_trees_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/candidate_sampling_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/case_condition_ops.h

@@ -0,0 +1,53 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/*!
+ * \file case_condition_ops.h
+ * \brief
+ */
+#ifndef OPS_BUILT_IN_OP_PROTO_INC_CASE_CONDITION_OPS_H_
+#define OPS_BUILT_IN_OP_PROTO_INC_CASE_CONDITION_OPS_H_
+
+#include "graph/operator_reg.h"
+
+namespace ge {
+/**
+*@brief x[0] is i, x[1] is j and x[2] is k when algorithm is LU,
+y = 0 when i >= k && j < k,
+y = 1 when i == k && j == k,
+y = 2 when i > k && j == k,
+y = 3 when i == k && j > k,
+y = 4 when i > k && j > k,
+default y = 5
+use for lu decomposition
+*@par Inputs:
+*x: A Tensor of type int32/int64/uint64. \n
+
+*@par Attributes:
+*algorithm: A string, only support LU now
+*@par Outputs:
+*y: A Tensor of type int32
+*/
+REG_OP(CaseCondition)
+    .INPUT(x, TensorType({DT_INT32, DT_INT64, DT_UINT64}))
+    .OUTPUT(y, TensorType({DT_INT32}))
+    .ATTR(algorithm, String, "LU")
+    .OP_END_FACTORY_REG(CaseCondition)
+
+} // namespace ge
+
+
+#endif  // OPS_BUILT_IN_OP_PROTO_INC_CASE_CONDITION_OPS_H_

third_party/fwkacllib/inc/ops/condtake_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/control_flow_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/coordinates_1d_to_2d_ops.h

@@ -0,0 +1,48 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/*!
+ * \file coordinates_1d_to_2d_ops.h
+ * \brief
+ */
+#ifndef OPS_BUILT_IN_OP_PROTO_INC_COORDINATES_1D_TO_2D_OPS_H_
+#define OPS_BUILT_IN_OP_PROTO_INC_COORDINATES_1D_TO_2D_OPS_H_
+
+#include "graph/operator_reg.h"
+
+namespace ge {
+/**
+*@brief Convert one-dimensional coordinates to two-dimensional coordinates.
+*@par Inputs:
+*@li x: A Tensor of type int32/int64/uint64. One-dimensional coordinates.
+*@li shape: A Tensor of type int32/int64/uint64. 4D tensor [N,C,H,W].
+*@par Outputs:
+*@li row: row of two-dimensional
+*@li col: col of two-dimensional
+*@li n: col number of two-dimensional
+*/
+REG_OP(Coordinates1DTo2D)
+    .INPUT(x, TensorType({DT_INT32, DT_INT64, DT_UINT64}))
+    .INPUT(shape, TensorType({DT_INT32, DT_INT64, DT_UINT64}))
+    .OUTPUT(row, TensorType({DT_INT32, DT_INT64, DT_UINT64}))
+    .OUTPUT(col, TensorType({DT_INT32, DT_INT64, DT_UINT64}))
+    .OUTPUT(n, TensorType({DT_INT32, DT_INT64, DT_UINT64}))
+    .OP_END_FACTORY_REG(Coordinates1DTo2D)
+
+} // namespace ge
+
+
+#endif  // OPS_BUILT_IN_OP_PROTO_INC_COORDINATES_1D_TO_2D_OPS_H_

third_party/fwkacllib/inc/ops/correlation.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/ctc_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -164,7 +164,7 @@ REG_OP(CTCBeamSearchDecoder)
 * Compatible with Pytorch CTCLoss operator.
 
 *@par Restrictions:
-*The length of Label should in [4, 1000].
+*The limit of Label’s length is 1K.
 */
 REG_OP(CTCLossV2)
     .INPUT(log_probs, TensorType({DT_FLOAT, DT_DOUBLE}))

third_party/fwkacllib/inc/ops/data_flow_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/elewise_calculation_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/functional_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/get_data_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/globalavgpool.h

@@ -1,49 +1,49 @@
-/**
- * Copyright 2019 Huawei Technologies Co., Ltd
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-/*!
- * \file globalavgpool.h
- * \brief
- */
-#ifndef OPS_BUILT_IN_OP_PROTO_INC_GLOBALAVERAGEPOOL_H_
-#define OPS_BUILT_IN_OP_PROTO_INC_GLOBALAVERAGEPOOL_H_
-
-#include "graph/operator_reg.h"
-
-namespace ge {
-/**
-*@brief GlobalAveragePool consumes an input tensor X and applies average pooling across the values in the same channel.
-This is equivalent to AveragePool with kernel size equal to the spatial dimension of input tensor \n
-
-*@par Inputs:
-*@li x: Input data tensor from the previous operator; dimensions for image case are (N x C x H x W),
-where N is the batch size, C is the number of channels, and H and W are the height and the width of the data.
-For non image case, the dimensions are in the form of (N x C x D1 x D2 ... Dn), where N is the batch size.
-
-*@par Outputs:
-*y: Output data tensor from pooling across the input tensor. The output tensor has the same rank as the input.
-The first two dimensions of output shape are the same as the input (N x C), while the other dimensions are all 1
-
-*@par Restrictions:
-*Warning: This operator can be integrated only by configuring INSERT_OP_FILE of aclgrphBuildModel. Please do not use it directly.
-*/
-REG_OP(GlobalAveragePool)
-    .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE}))
-    .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE}))
-    .OP_END_FACTORY_REG(GlobalAveragePool)
-} // namespace ge
-
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/*!
+ * \file globalavgpool.h
+ * \brief
+ */
+#ifndef OPS_BUILT_IN_OP_PROTO_INC_GLOBALAVERAGEPOOL_H_
+#define OPS_BUILT_IN_OP_PROTO_INC_GLOBALAVERAGEPOOL_H_
+
+#include "graph/operator_reg.h"
+
+namespace ge {
+/**
+*@brief GlobalAveragePool consumes an input tensor X and applies average pooling across the values in the same channel.
+This is equivalent to AveragePool with kernel size equal to the spatial dimension of input tensor \n
+
+*@par Inputs:
+*@li x: Input data tensor from the previous operator; dimensions for image case are (N x C x H x W),
+where N is the batch size, C is the number of channels, and H and W are the height and the width of the data.
+For non image case, the dimensions are in the form of (N x C x D1 x D2 ... Dn), where N is the batch size.
+
+*@par Outputs:
+*y: Output data tensor from pooling across the input tensor. The output tensor has the same rank as the input.
+The first two dimensions of output shape are the same as the input (N x C), while the other dimensions are all 1
+
+*@par Restrictions:
+*Warning: This operator can be integrated only by configuring INSERT_OP_FILE of aclgrphBuildModel. Please do not use it directly.
+*/
+REG_OP(GlobalAveragePool)
+    .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE}))
+    .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE}))
+    .OP_END_FACTORY_REG(GlobalAveragePool)
+} // namespace ge
+
 #endif  // OPS_BUILT_IN_OP_PROTO_INC_GLOBALAVGPOOL_H_

third_party/fwkacllib/inc/ops/hcom_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/hvd_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/image_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/index_to_addr_ops.h

@@ -0,0 +1,63 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/*!
+ * \file index_to_addr_ops.h
+ * \brief
+ */
+#ifndef OPS_BUILT_IN_OP_PROTO_INC_INDEX_TO_ADDR_OPS_H_
+#define OPS_BUILT_IN_OP_PROTO_INC_INDEX_TO_ADDR_OPS_H_
+
+#include "graph/operator_reg.h"
+
+namespace ge {
+
+/**
+*@brief get block tensor according to base addr tensor, for hccl remote read to use.
+*@par Inputs:
+*@li base_addr: A Tensor of type int64/uint64. \n
+*@li row:A Tensor of type int64/uint64. \n
+*@li col: A Tensor of type int64/uint64.
+
+*@par Outputs:
+*addr_table: list of [rank id, host addr, device addr, read size]
+
+*@par Attributes:
+*@li ori_shape: An required list int. Shape of base tensor.
+*@li block_size: An required list int. Shape of split block tensor.
+*@li ori_storage_mode: An optional string from: '"Matrix", "UT"'. Defaults to
+"Matrix". Currently only support Matrix storage
+*@li block_storage_mode: An optional string from: '"Matrix", "UT"'. Defaults to
+"Matrix". Currently only support Matrix storage
+*@li rank_id: An optional int of rank id. Defaults is 0
+*@li dtype: An optional Type of base tensor. Defaults is DT_FLOAT
+*/
+REG_OP(IndexToAddr)
+    .INPUT(base_addr, TensorType({DT_INT64, DT_UINT64}))
+    .INPUT(x, TensorType({DT_INT64, DT_UINT64}))
+    .OUTPUT(addrs_table, TensorType({DT_INT64, DT_UINT64}))
+    .REQUIRED_ATTR(ori_shape, ListInt)
+    .REQUIRED_ATTR(block_size, ListInt)
+    .ATTR(ori_storage_mode, String, "Matrix")
+    .ATTR(block_storage_mode, String, "Matrix")
+    .ATTR(rank_id, Int, 0)
+    .ATTR(dtype, Type, DT_FLOAT)
+    .OP_END_FACTORY_REG(IndexToAddr)
+
+} // namespace ge
+
+
+#endif  // OPS_BUILT_IN_OP_PROTO_INC_INDEX_TO_ADDR_OPS_H_

third_party/fwkacllib/inc/ops/internal_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/linalg_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/list_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/logging_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -111,6 +111,38 @@ REG_OP(PrintV2)
   .INPUT(x, TensorType({DT_STRING}))
   .ATTR(output_stream, String, "stderr")
   .OP_END_FACTORY_REG(PrintV2)
+
+/**
+*@brief Prints a list of tensors. \n
+
+*@par Inputs:
+*x: A tensor passwd through this op . \n
+*data: A list of tensors to print out when op is evaluated. \n
+
+*@par Attributes:
+*message: A string, prefix of the error message. \n
+*first_n: Only log first_n number of times. Negative numbers 
+*log always; this is the default. \n
+*summarize: Only print this many entries of each tensor. 
+*If None, then a maximum of 3 elements are printed per input tensor. \n
+
+*@par Third-party framework compatibility
+*Compatible with tensorflow Print operator . \n
+
+*@par Restrictions:
+*Warning: THIS FUNCTION IS EXPERIMENTAL. Please do not use.
+*/
+REG_OP(PrintV3)
+  .INPUT(x, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, DT_UINT16, DT_UINT8, DT_INT32,
+    DT_INT64, DT_UINT32, DT_UINT64, DT_DOUBLE, DT_STRING}))
+  .DYNAMIC_INPUT(data, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, DT_UINT16, DT_UINT8, DT_INT32,
+    DT_INT64, DT_UINT32, DT_UINT64, DT_DOUBLE, DT_STRING}))
+  .OUTPUT(y, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, DT_UINT16, DT_UINT8, DT_INT32,
+    DT_INT64, DT_UINT32, DT_UINT64, DT_DOUBLE, DT_STRING}))
+  .ATTR(message, String, "")
+  .ATTR(first_n, Int, -1)
+  .ATTR(summarize, Int, 3)
+  .OP_END_FACTORY_REG(PrintV3)
 }  // namespace ge
 
 #endif  // OPS_BUILT_IN_OP_PROTO_INC_LOGGING_OPS_H_

third_party/fwkacllib/inc/ops/lookup_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/math_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/matrix_calculation_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -88,11 +88,11 @@ REG_OP(MatMul)
 * Compatible with the TensorFlow operator BatchMatmul.
 */
 REG_OP(MatMulV2)
-    .INPUT(x1, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT32, DT_INT8}))
-    .INPUT(x2, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT32, DT_INT8}))
+    .INPUT(x1, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT32, DT_INT8, DT_INT4}))
+    .INPUT(x2, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT32, DT_INT8 DT_INT4}))
     .OPTIONAL_INPUT(bias, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT32}))
     .OUTPUT(y, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT32}))
-    .OPTIONAL_INPUT(offset_w, TensorType({DT_INT8}))
+    .OPTIONAL_INPUT(offset_w, TensorType({DT_INT8, DT_INT4}))
     .ATTR(transpose_x1, Bool, false)
     .ATTR(transpose_x2, Bool, false)
     .ATTR(offset_x, Int, 0)
@@ -180,12 +180,12 @@ REG_OP(MatMulV2Compress)
 */
 
 REG_OP(GEMM)
-    .INPUT(a, TensorType({DT_FLOAT16, DT_INT8}))
-    .INPUT(b, TensorType({DT_FLOAT16, DT_INT8}))
-    .INPUT(c, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT32}))
-    .INPUT(alpha, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT32}))
-    .INPUT(beta, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT32}))
-    .OUTPUT(y, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT32}))
+    .INPUT(a, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT32}))
+    .INPUT(b, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT32}))
+    .INPUT(c, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT32}))
+    .INPUT(alpha, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT32}))
+    .INPUT(beta, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT32}))
+    .OUTPUT(y, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT32}))
     .ATTR(transpose_a, Bool, false)
     .ATTR(transpose_b, Bool, false)
     .OP_END_FACTORY_REG(GEMM)
@@ -246,10 +246,10 @@ REG_OP(BatchMatMul)
 */
 
 REG_OP(BatchMatMulV2)
-    .INPUT(x1, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT32, DT_INT8}))
-    .INPUT(x2, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT32, DT_INT8}))
+    .INPUT(x1, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT32, DT_INT8, DT_INT4}))
+    .INPUT(x2, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT32, DT_INT8, DT_INT4}))
     .OPTIONAL_INPUT(bias, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT32}))
-    .OPTIONAL_INPUT(offset_w, TensorType({DT_INT8}))
+    .OPTIONAL_INPUT(offset_w, TensorType({DT_INT8, DT_INT4}))
     .OUTPUT(y, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT32}))
     .ATTR(adj_x1, Bool, false)
     .ATTR(adj_x2, Bool, false)
@@ -531,61 +531,6 @@ REG_OP(ScatterAdd)
     .ATTR(use_locking, Bool, false)
     .OP_END_FACTORY_REG(ScatterAdd)
 
-/**
-*@brief  Use a scalar to modify the tensor. \n
-
-*@par Inputs:
-*inputs, including:
-*@li index: An ND Tensor . \n
-
-*Must be one of the following types: float16, float32, int32, int8, uint8
-
-*@par Attributes:
-* dim : the axis along which to index .
-* value : the source element(s) to scatter . \n
-
-*@par Outputs:
-*y: A Tensor. Has the same type and format as input "index" . \n
-
-*@par Third-party framework compatibility
-* Compatible with the Pytorch operator ScatterScalar.
-*/
-REG_OP(ScatterScalar)
-    .INPUT(index, TensorType({DT_FLOAT16,DT_FLOAT,DT_INT32,DT_INT8,DT_UINT8}))
-    .OUTPUT(y, TensorType({DT_FLOAT16,DT_FLOAT,DT_INT32,DT_INT8,DT_UINT8}))
-    .REQUIRED_ATTR(dim, Int)
-    .REQUIRED_ATTR(value, Float)
-    .OP_END_FACTORY_REG(ScatterScalar)
-
-/**
-*@brief Use a tensor to modify the tensor . \n
-
-*@par Inputs:
-* Two inputs, including:
-*@li index: An ND Tensor . \n
-
-*Must be one of the following types: float16, float32, int32, int8, uint8
-
-*@li src: An ND Tensor . \n
-
-*Must be one of the following types: float16, float32, int32, int8, uint8
-
-*@par Attributes:
-* dim : the axis along which to index . \n
-
-*@par Outputs:
-*y: A Tensor. Has the same type and format as input "index" . \n
-
-*@par Third-party framework compatibility
-* Compatible with the Pytorch operator ScatterTensor.
-*/
-REG_OP(ScatterTensor)
-    .INPUT(index, TensorType({DT_FLOAT16,DT_FLOAT,DT_INT32,DT_INT8,DT_UINT8}))
-    .INPUT(src, TensorType({DT_FLOAT16,DT_FLOAT,DT_INT32,DT_INT8,DT_UINT8}))
-    .OUTPUT(y, TensorType({DT_FLOAT16,DT_FLOAT,DT_INT32,DT_INT8,DT_UINT8}))
-    .REQUIRED_ATTR(dim, Int)
-    .OP_END_FACTORY_REG(ScatterTensor)
-
 /**
 *@brief Divides a variable reference by sparse updates . \n
 
@@ -839,10 +784,10 @@ REG_OP(DiagPart)
 * Yes
 */
 REG_OP(FullyConnection)
-    .INPUT(x, TensorType({DT_FLOAT16, DT_INT8}))
-    .INPUT(w, TensorType({DT_FLOAT16, DT_INT8}))
+    .INPUT(x, TensorType({DT_FLOAT16, DT_INT8, DT_INT4}))
+    .INPUT(w, TensorType({DT_FLOAT16, DT_INT8, DT_INT4}))
     .OPTIONAL_INPUT(b, TensorType({DT_FLOAT16, DT_INT32,DT_FLOAT32}))
-    .OPTIONAL_INPUT(offset_w, TensorType({DT_INT8}))
+    .OPTIONAL_INPUT(offset_w, TensorType({DT_INT8, DT_INT4}))
     .OUTPUT(y, TensorType({DT_FLOAT16, DT_INT32,DT_FLOAT32}))
     .REQUIRED_ATTR(num_output, Int)
     .ATTR(transpose, Bool, false)
@@ -1197,10 +1142,12 @@ REG_OP(IndexAdd)
 
 * @par Inputs:
 * Three inputs, including:
-* @li x1: A Tensor. Must be one of the following types:
-*     float16, float32, int32, int8, uint8.
+* @li x1:  A Tensor. Must be one of the following types:
+*float16, float32, double, int32, uint8, int16, int8, complex64, int64,
+*qint8, quint8, qint32, uint16, complex128, uint32, uint64. \n
+
 * @li x2: A Tensor of the same type as "x1".
-* @li indices: A Tensor of the indices, type should be int32.
+* @li indices: A Tensor of the indices, 
 
 * @par Attributes:
 * @li accumulate: Does it support self accumulation.Defaults to 0.
@@ -1215,10 +1162,10 @@ REG_OP(IndexAdd)
 * Warning:THIS FUNCTION IS EXPERIMENTAL. Please do not use.
 */
 REG_OP(IndexPut)
-    .INPUT(x1, TensorType({DT_INT64, DT_INT32, DT_INT8, DT_UINT8, DT_FLOAT32, DT_FLOAT16}))
-    .INPUT(x2, TensorType({DT_INT64, DT_INT32, DT_INT8, DT_UINT8, DT_FLOAT32, DT_FLOAT16}))
-    .INPUT(indices, TensorType({DT_INT64, DT_INT32}))
-    .OUTPUT(y, TensorType({DT_INT64, DT_INT32, DT_INT8, DT_UINT8, DT_FLOAT32, DT_FLOAT16}))
+    .INPUT(x1, TensorType::BasicType())
+    .INPUT(x2, TensorType::BasicType())
+    .OUTPUT(y, TensorType::BasicType())
+    .REQUIRED_ATTR(indices, ListInt)
     .ATTR(accumulate, Int, 0)
     .OP_END_FACTORY_REG(IndexPut)
 

third_party/fwkacllib/inc/ops/nn_batch_norm_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/nn_calculation_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -869,59 +869,60 @@ REG_OP(Conv2D)
 /**
 *@brief Computes a 2D convolution given 4D "x" and "filter_compress" tensors.
 *@par Inputs:
-* @li x: A 4D tensor of input images.
-* @li filter_compress: A 4D tensor of compressed filters.
-* @li compress_index: A 1D Tensor dtype of int8.
-* @li bias: An optional 1D tensor.
-* @li offset_w: An optional 1D tensor for quantized convolution. Reserved.
+*@li x: A 4D tensor of input images.
+*@li filter_compress: A 4D tensor of compressed filter data blocks.
+*@li compress_index: A 1D tensor of index for decompression.
+*@li bias: An optional 1D tensor of additive biases to the filter outputs.
+* The data is stored in the order of: [out_channels].
+*@li offset_w: Reserved.
+*\n
+*\n
+* The following are the supported data types and data formats:
+*\n
+*\n
+| Tensor    | x       | filter_compress  | compress_index | bias    | y       |\n
+| :-------: | :-----: | :--------------: | :------------: | :-----: | :-----: |\n
+| Data Type |  int8   |       int8       |     int8       |  int32  |  int32  |\n
+| Format    |  NCHW   |       NCHW       |      ND        |  ND     |  NCHW   |\n
+|           |  NHWC   |       HWCN       |                |         |  NHWC   |\n
+*\n
+* For float32 type, the actual calculation on the chip is based on
+* float16.
+*\n
 *
-* The input and output tensor attributes are listed as follows:
-* @verbatim
-    |Tensor    | x       | filter_compress  | bias    | offset_w | y
-    -----------|---------|---------|---------|----------|--------
-    |Data Type | float16 | float16 | float16 | _        | float16
-    |          |---------|---------|---------|----------|--------
-    |          | float32 | float32 | float32 | _        | float32
-    |          |---------|---------|---------|----------|--------
-    |          | int8    | int8    | int32   | int8     | int32
-    -----------|---------|---------|---------|----------|--------
-    |Format    | NCHW    | NCHW    | ND      | ND       | NCHW
-    |          | NHWC    | NHWC    |         |          | NHWC
-    |          |         | HWCN    |         |          |
-@endverbatim
-* It should be noted that the data types must correspond to each other, but the
-* format does not need to . \n
-
 *@par Attributes:
-* @li strides: A list of 4 integers. Specifying the strides of the
-* convolution along the height and width. The dimension order is determined
-* by the data format of "x". By default the N and C dimensions are set to 1.
-* @li pads: A list of 4 integers. Specifying the top, bottom, left and right
-* padding.
-* @li dilations: A list of 4 integers. Specifying the dilation rate to use
-* for dilated convolution. Has the same dimension order and value as "strides".
-* @li groups: Number of blocked connections from input channels to output
-* channels. Input channels and output channels must both be divisible by
-* "groups".Type is int32.
-* @li offset_x: An optional integer for quantized convolution. Type is int32.
-* Defaults to "0".
-* @li data_format: An optional string from: "NHWC", "NCHW". Specifying the
-* data format of the input and output images. Type is string.
-* Defaults to "NHWC". Reserved . \n
-
+*@li strides: Required. A list of 4 integers. The stride of the sliding window
+* for each dimension of input. The dimension order is determined by the data
+* format of "x". The N and C dimensions must be set to 1.
+*@li pads: Required. A list of 4 integers. The number of pixels to add to each
+* (top, bottom, left, right) side of the input.
+*@li dilations: Optional. A list of 4 integers. The dilation factor for each
+* dimension of input. The dimension order is determined by the data format of
+* "x". The N and C dimensions must be set to 1. Defaults to [1, 1, 1, 1].
+*@li groups: Optional. An integer of type int32. The number of blocked
+* connections from input channels to output channels. In_channels and
+* out_channels must both be divisible by "groups". Only support 1.
+*@li offset_x: Optional. An integer of type int32. The negative offset added
+* to the input image for int8 type. Ensure that the output is within the
+* effective range. Defaults to 0.
+*@li data_format: Reserved.
+*
 *@par Outputs:
-* @li y: A 4D Tensor of output images . \n
-
+* y: A 4D Tensor of output feature map. Has the same type as "x". With the
+* format "NHWC", the data is stored in the order of: [batch, out_height,
+* out_width, out_channels].
+*\n
+*
 *@par Restrictions:
-*Warning: THIS FUNCTION IS DEPRECATED.
+*Warning: THIS FUNCTION IS EXPERIMENTAL.
 */
 REG_OP(Conv2DCompress)
-    .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT, DT_INT8}))
-    .INPUT(filter_compress, TensorType({DT_FLOAT16, DT_FLOAT, DT_INT8}))
+    .INPUT(x, TensorType({DT_INT8}))
+    .INPUT(filter_compress, TensorType({DT_INT8}))
     .INPUT(compress_index, TensorType({DT_INT8}))
-    .OPTIONAL_INPUT(bias, TensorType({DT_FLOAT16, DT_FLOAT, DT_INT32}))
+    .OPTIONAL_INPUT(bias, TensorType({DT_INT32}))
     .OPTIONAL_INPUT(offset_w, TensorType({DT_INT8}))
-    .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT, DT_INT32}))
+    .OUTPUT(y, TensorType({DT_INT32}))
     .REQUIRED_ATTR(strides, ListInt)
     .REQUIRED_ATTR(pads, ListInt)
     .ATTR(dilations, ListInt, {1, 1, 1, 1})

third_party/fwkacllib/inc/ops/nn_detect_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -1002,9 +1002,12 @@ REG_OP(SPP)
 *@par Inputs:
 * Three inputs, including:
 *@li x: An NC1HWC0 tensor of type float16 or float32, describing the feature
-* map.
+* map. The data of x must be greater than or equal to "0.0".
 *@li rois: A tensor of type float16 or float32, with 3D shape
-* [batch, 5, roi_max_num], describing the RIOs.
+* [batch, 5, roi_max_num], describing the RIOs. Each ROI consists of five
+* elements: "batch_id", "x1", "y1", "x2", and "y2", which "batch_id" indicates
+* the index of the input feature map, "x1", "y1", "x2", or "y2" must be
+* greater than or equal to "0.0".
 * roi_max_num must be less than or equal to 6000 and must be divided by 16.
 *@li roi_actual_num: A  optional tensor of type int32, with shape [batch, 8], specifying
 * the number of ROIs per batch . \n

third_party/fwkacllib/inc/ops/nn_norm_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/nn_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/nn_pooling_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -1402,6 +1402,7 @@ REG_OP(MaxPoolGradWithArgmaxV2)
 * @li pads:A required list of int8, int16, int32, or int64 values,
 * a data to caculate when padding_mode is "CALCULATED".
 * @li data_format: An optional string. Defaults to "NHWC" .
+* If data_format = "NC1HWC0", ori_format must be "NCHW".
 * @li global_pooling bool, Whether to use the global pooling.
 * If global_pooling = true, kernel size and paddings will be ignored.
 * Default False
@@ -1786,5 +1787,30 @@ REG_OP(SubSampleLabels)
     .REQUIRED_ATTR(positive_fraction, Float)
     .OP_END_FACTORY_REG(SubSampleLabels)
 
+/**
+*@brief Computes GlobalLpPool, GlobalLpPool consumes an input tensor X and applies lp pool pooling across the
+values in the same channel. \n
+
+*@par Inputs:
+* x: A Tensor of type float16 or float32 . \n
+
+*@par Attributes:
+*@li p: Optional. Must be one of the following types: float32. Defaults to 2.0. \n
+
+*@par Outputs:
+* y: A Tensor. Has the same type as "x", when shape of x is [N,C,H,W], shape of y is [N,C,1,1].
+*@par Third-party framework compatibility
+* Compatible with the onnx operator GlobalLpPool.
+*@par Restrictions:
+*Warning: THIS FUNCTION IS DEPRECATED.
+*Warning: THIS FUNCTION IS EXPERIMENTAL. Please do not use.
+*/
+
+REG_OP(GlobalLpPool)
+    .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT}))
+    .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT}))
+    .ATTR(p, Float, 2.0)
+    .OP_END_FACTORY_REG(GlobalLpPool);
+
 }  // namespace ge
 #endif  // OPS_BUILT_IN_OP_PROTO_INC_NN_POOLING_OPS_H

third_party/fwkacllib/inc/ops/nn_training_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/no_op.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/nonlinear_fuc_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -98,6 +98,22 @@ REG_OP(FastGeluGrad)
     .OUTPUT(z, TensorType({DT_FLOAT16, DT_FLOAT}))
     .OP_END_FACTORY_REG(FastGeluGrad)
 
+/**
+* @brief Compute hardswish of "x" element-wise . \n
+
+*@par Inputs:
+*One input, including:
+*x: A Tensor. Must be one of the following types: float16, float32
+
+*@par Outputs:
+*y: A Tensor. Has the same type as "x".
+*@par Third-party framework compatibility
+* Compatible with the Torch operator Hardswish.
+*/
+REG_OP(Hardswish)
+    .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT}))
+    .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT}))
+    .OP_END_FACTORY_REG(Hardswish)
 
 /**
 *@brief Computes the gradient for the tanh of "x" . \n

third_party/fwkacllib/inc/ops/npu_loss_scale_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/outfeed_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/pad_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/parsing_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/quantize_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -96,18 +96,19 @@ REG_OP(Quantize)
 *@li dst_type: A optional int32, specifying the output data type. Defaults to "DT_INT8" . \n
 
 *@par Outputs:
-*y: The quantized output tensor of type int8 and with format NC1HWC0 . \n
+*y: The quantized output tensor of type int8 or int4 and with format NC1HWC0 . \n
 
 *@par Third-party framework compatibility
 * It is a custom operator. It has no corresponding operator in Caffe.
 */
 REG_OP(AscendQuant)
     .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT32}))
-    .OUTPUT(y, TensorType({DT_INT8}))
+    .OUTPUT(y, TensorType({DT_INT8, DT_INT4}))
     .REQUIRED_ATTR(scale, Float)
     .REQUIRED_ATTR(offset, Float)
     .ATTR(sqrt_mode, Bool, false)
     .ATTR(round_mode, String, "Round")
+    .ATTR(dst_type, Int, DT_INT8)
     .OP_END_FACTORY_REG(AscendQuant)
 
 /**

third_party/fwkacllib/inc/ops/ragged_array_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/ragged_conversion_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/ragged_math_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/random_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/reduce_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/resource_variable_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/rnn.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -285,9 +285,9 @@ REG_OP(DynamicRNN)
 *@li num_proj:An integer identifying the num projection in the op. Default to 0.
 *@li time_major:An bool identifying the time major in the op. Default to true.
 *@li activation:An string identifying the type of activation function in the op. Default to "tanh".
-*Only tanh is currently supported.
+*Support "tanh" and "clip".
 *@li recurrent_activation:An string identifying the type of activation function in the op. Default to "sigmoid".
-*Supprot "sigmoid" and "hard_sigmoid". In general, set "hard_sigmoid" for TF Keras LSTM.
+*Support "sigmoid" and "hard_sigmoid". In general, set "hard_sigmoid" for TF Keras LSTM.
 *@li forget_bias:An float identifying the forget bias in the op. Default to 0.
 *@li gate_order:An string identifying the type of gate order in the op. Support "ijfo" and "ifco". Default to "ijfo".
 *Set "ijfo" for TF operator LSTM, Set "ifco" for TF Keras LSTM.

third_party/fwkacllib/inc/ops/rpn_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/save_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/sdca_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/selection_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -1895,6 +1895,33 @@ REG_OP(Cummin)
     .REQUIRED_ATTR(axis, Int)
     .OP_END_FACTORY_REG(Cummin)
 
+/**
+*@brief Returns a namedtuple (values, indices) where values is the cumulative 
+* the cumulative maximum of elements of input in the dimension dim. 
+* And indices is the index location of each maximum value found in the dimension dim. \n
+
+*@par Inputs:
+*One inputs, including:
+* x: A tensor . Must be one of the following types:
+*     float16, float32, int32, uint32, int8, uint8. \n
+
+*@par Attributes:
+* dim: Axis along which to cummax. \n
+
+*@par Outputs:
+* @li y: A Tensor with the same type and shape of x's.
+* @li indices: A Tensor with the int32/int64 type and the same shape of x's. \n
+
+*@par Third-party framework compatibility
+*Compatible with the Pytorch operator Cummax. \n
+*/
+REG_OP(Cummax)
+    .INPUT(x, TensorType::BasicType())
+    .OUTPUT(y, TensorType::BasicType())
+    .OUTPUT(indices, TensorType::BasicType())
+    .REQUIRED_ATTR(dim, Int)
+    .OP_END_FACTORY_REG(Cummax)
+
 /**
 *@brief Extends the input with copies of data along a specified dimension. For example:
 *(1) If x = [[[1, 2], [3, 4], [5, 6]], [[7, 8], [9, 10], [11, 12]]], with shape (2, 3, 2);
@@ -2129,24 +2156,6 @@ REG_OP(MaskedSelectV2)
     .INPUT(mask, TensorType({DT_BOOL}))
     .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT}))
     .OP_END_FACTORY_REG(MaskedSelectV2)
-    
-/**
-* @brief Choose the value of X with value according to mask.
-
-* @par Inputs:
-* two inputs, including:
-*  @li x: A Tensor of dtype is float16 or float32 or float64 or int64 or int32 or int16 or int8 or uint8.
-*  @li mask: A Tensor of dtype is bool. \n
-
-* @par Outputs:
-*  @li y: A tensor with the same type as x. \n
-
-*/
-REG_OP(MaskedSelect)
-    .INPUT(x, TensorType({DT_FLOAT, DT_FLOAT16, DT_DOUBLE, DT_UINT8,  DT_INT8, DT_INT16, DT_INT32, DT_INT64}))
-    .INPUT(mask, TensorType({DT_BOOL}))
-    .OUTPUT(y, TensorType({DT_FLOAT, DT_FLOAT16, DT_DOUBLE, DT_UINT8, DT_INT8, DT_INT16, DT_INT32, DT_INT64}))
-    .OP_END_FACTORY_REG(MaskedSelect)
 
 /**
 * @brief update the value of X with value according to mask.
@@ -2364,6 +2373,35 @@ REG_OP(InplaceTopKDistance)
     .INPUT(pq_ivf, TensorType({DT_INT32}))
     .ATTR(order, String, "asc")
     .OP_END_FACTORY_REG(InplaceTopKDistance)
+
+/**
+* @brief After a set of sorted data and a new set of data are re-sorted, get the first k data. \n
+*
+* @par Inputs:
+* @li sorted_distance: A sorted Tensor, Will be updated after calculation. Must be one of the following types: float16. 
+* @li pq_ivf: A Tensor of type int32, index corresponding to sorted_distance.
+* @li pq_index: A Tensor of type int32 , the bucket number corresponding to sorted_distance. \n
+*
+*@par Outputs:
+* @li topk_distance: A Tensor of type float16, the new data set will be reordered with sorted_distance and updated to topk_distance.
+* @li topk_ivf: A Tensor of type int32, index corresponding to topk_distance. 
+* @li topk_index: A scalar of type int32 , the bucket number corresponding to topk_distance. \n
+*
+* @par Attributes:
+* k: get the first k data of sorted_distance. \n
+*
+* @par Restrictions:
+* Warning: THIS FUNCTION IS EXPERIMENTAL.  Please do not use.
+*/
+REG_OP(TopKPQDistanceMerge)
+    .INPUT(sorted_distance, TensorType({DT_FLOAT16}))
+    .INPUT(pq_ivf, TensorType({DT_INT32}))
+    .INPUT(pq_index, TensorType({DT_INT32}))
+    .OUTPUT(topk_distance, TensorType({DT_FLOAT16}))
+    .OUTPUT(topk_ivf, TensorType({DT_INT32}))
+    .OUTPUT(topk_index, TensorType({DT_INT32}))
+    .REQUIRED_ATTR(k, Int)
+    .OP_END_FACTORY_REG(TopKPQDistanceMerge)
 } // namespace ge
 
 #endif  // OPS_BUILT_IN_OP_PROTO_INC_SELECTION_OPS_H_

third_party/fwkacllib/inc/ops/set_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/slice_write_ops.h

@@ -0,0 +1,50 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/*!
+ * \file slice_write_ops.h
+ * \brief
+ */
+#ifndef OPS_BUILT_IN_OP_PROTO_INC_SLICE_WRITE_OPS_H_
+#define OPS_BUILT_IN_OP_PROTO_INC_SLICE_WRITE_OPS_H_
+
+#include "graph/operator_reg.h"
+
+namespace ge {
+
+/**
+*@brief write tensor value to tensor x.
+*@par Inputs:
+*x: A Tensor of type float16/float/double/int32/int64. \n
+*begin:A Tensor of type int32/int64. \n
+*value: A Tensor of type float16/float/double/int32/int64.
+*@par Outputs:
+*x: same tensor with input x
+*/
+REG_OP(SliceWrite)
+    .INPUT(x, TensorType({DT_FLOAT, DT_FLOAT16, DT_DOUBLE, \
+        DT_INT32, DT_INT64}))
+    .INPUT(begin, TensorType({DT_INT32, DT_INT64}))
+    .INPUT(value, TensorType({DT_FLOAT, DT_FLOAT16, DT_DOUBLE, \
+        DT_INT32, DT_INT64}))
+    .OUTPUT(x, TensorType({DT_FLOAT, DT_FLOAT16, DT_DOUBLE, \
+        DT_INT32, DT_INT64}))
+    .OP_END_FACTORY_REG(SliceWrite)
+
+} // namespace ge
+
+
+#endif  // OPS_BUILT_IN_OP_PROTO_INC_SLICE_WRITE_OPS_H_

third_party/fwkacllib/inc/ops/sparse_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/spectral_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/split_combination_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/state_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/stateful_random_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/stateless_random_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/string_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/swap_co_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/target_crop_and_resize.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/ops/transformation_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -153,6 +153,32 @@ REG_OP(TransData)
     .ATTR(groups, Int, 1)
     .OP_END_FACTORY_REG(TransData)
 
+/**
+*@brief Do format transfer for various data format only 
+support "ND" to "ND_RNN_BIAS" and "ND" to "FRACTAL_ZN_RNN"
+
+*@par Inputs:
+*src: A Tensor. For all branches can be types: float16, float32, int32, int8, bool.
+* For branches without padding also can be types: int16, int64, uint8, uint16, uint32, uint64 . \n
+
+*@par Attributes:
+*@li src_format: A string source data format, can be "ND", "ND_RNN_BIAS", "FRACTAL_ZN_RNN" etc.
+*@li dst_format: A string target data format, can be "ND", "ND_RNN_BIAS", "FRACTAL_ZN_RNN" etc.
+*@li input_size: A mental int32.
+*@li hidden_size: A mental int32.
+
+*@par Outputs:
+*dst: A Tensor. Has the same type as "src".
+*/
+REG_OP(TransDataRNN)
+    .INPUT(src, TensorType::BasicType())
+    .OUTPUT(dst, TensorType::BasicType())
+    .REQUIRED_ATTR(src_format, String)
+    .REQUIRED_ATTR(dst_format, String)
+    .REQUIRED_ATTR(input_size, Int)
+    .REQUIRED_ATTR(hidden_size, Int)
+    .OP_END_FACTORY_REG(TransDataRNN)
+
 /**
 *@brief Permutes the dimensions according to order.
         The returned tensor's dimension i will correspond to the input dimension order[i] . \n

third_party/fwkacllib/inc/ops/warp_perspective_ops.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/opt_info/opt_info.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2021 Huawei Technologies Co., Ltd
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

third_party/fwkacllib/inc/runtime/base.h

@@ -1,18 +1,18 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
-
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
  * You may obtain a copy of the License at
-
+ *
  * http://www.apache.org/licenses/LICENSE-2.0
-
+ *
  * Unless required by applicable law or agreed to in writing, software
  * distributed under the License is distributed on an "AS IS" BASIS,
  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  * See the License for the specific language governing permissions and
  * limitations under the License.
-*/
+ */
 
 #ifndef __CCE_RUNTIME_BASE_H__
 #define __CCE_RUNTIME_BASE_H__
@@ -94,6 +94,14 @@ typedef void (*rtTaskFailCallback)(rtExceptionInfo *exceptionInfo);
 
 typedef void (*rtDeviceStateCallback)(uint32_t devId, bool isOpen);
 
+/**
+ * @ingroup profiling_base
+ * @brief dataType: rtProfCtrlType_t
+ * @brief data: data swtich or reporter function
+ * @brief dataLen: length of data
+ */
+typedef rtError_t (*rtProfCtrlHandle)(uint32_t dataType, void *data, uint32_t dataLen);
+
 /**
  * @ingroup dvrt_base
  * @brief stream handle.
@@ -118,6 +126,32 @@ typedef void *rtLabel_t;
  */
 typedef void *rtModel_t;
 
+#define RT_PROF_MAX_DEV_NUM 64
+
+/**
+ * @ingroup profiling_base
+ * @brief profiling command info
+ */
+typedef struct rtProfCommandHandle {
+    uint64_t profSwitch;
+    uint64_t profSwitchHi;
+    uint32_t devNums;
+    uint32_t devIdList[RT_PROF_MAX_DEV_NUM];
+    uint32_t modelId;
+    uint32_t type;
+} rtProfCommandHandle_t;
+
+/**
+ * @ingroup profiling_base
+ * @brief type of app register profiling switch or reporter callback
+ */
+typedef enum {
+    RT_PROF_CTRL_INVALID = 0,
+    RT_PROF_CTRL_SWITCH,
+    RT_PROF_CTRL_REPORTER,
+    RT_PROF_CTRL_BUTT
+} rtProfCtrlType_t;
+
 /**
  * @ingroup profiling_base
  * @brief runtime handle.
@@ -166,6 +200,57 @@ RTS_API rtError_t rtProfilerTraceEx(uint64_t id, uint64_t modelId, uint16_t tagI
  */
 RTS_API rtError_t rtSetMsprofReporterCallback(MsprofReporterCallback callback);
 
+/**
+ * @ingroup profiling_base
+ * @brief add the map of deviceId and GE model index, called by ge
+ * @param [in] geModelIdx  The index of GE model
+ * @param [in] deviceId    The id of device
+ * @return RT_ERROR_NONE for ok
+ * @return ACL_ERROR_RT_PARAM_INVALID for error input
+ */
+RTS_API rtError_t rtSetDeviceIdByGeModelIdx(uint32_t geModelIdx, uint32_t deviceId);
+
+/**
+ * @ingroup profiling_base
+ * @brief del the map of deviceId and GE model index, called by ge
+ * @param [in] geModelIdx  The index of GE model
+ * @param [in] deviceId    The id of device
+ * @return RT_ERROR_NONE for ok
+ * @return ACL_ERROR_RT_PARAM_INVALID for error input
+ */
+RTS_API rtError_t rtUnsetDeviceIdByGeModelIdx(uint32_t geModelIdx, uint32_t deviceId);
+
+/**
+ * @ingroup profiling_base
+ * @brief find deviceId by GE model index, called by profiling
+ * @param [in]  geModelIdx  The index of GE model
+ * @param [out] deviceId    The id of device
+ * @return RT_ERROR_NONE for ok
+ * @return ACL_ERROR_RT_PARAM_INVALID for error input
+ * @return ACL_ERROR_RT_INTERNAL_ERROR for can't find deviceId by geModelIdx
+ */
+RTS_API rtError_t rtGetDeviceIdByGeModelIdx(uint32_t geModelIdx, uint32_t *deviceId);
+
+/**
+ * @ingroup profiling_base
+ * @brief set profling switch, called by profiling
+ * @param [in]  data  rtProfCommandHandle
+ * @param [out] len   length of data
+ * @return RT_ERROR_NONE for ok
+ * @return ACL_ERROR_RT_PARAM_INVALID for error input
+ */
+RTS_API rtError_t rtProfSetProSwitch(void *data, uint32_t len);
+
+/**
+ * @ingroup profiling_base
+ * @brief register callback of upper app, called by ge or acl
+ * @param [in]  moduleId of APP
+ * @param [in]  callback function when switch or reporter change
+ * @return RT_ERROR_NONE for ok
+ * @return ACL_ERROR_RT_PARAM_INVALID for error input
+ */
+RTS_API rtError_t rtProfRegisterCtrlCallback(uint32_t moduleId, rtProfCtrlHandle callback);
+
 /**
  * @ingroup dvrt_base
  * @brief Returns the last error from a runtime call.
@@ -356,7 +441,6 @@ RTS_API rtError_t rtLabelCreateExV2(rtLabel_t *label, rtModel_t model, rtStream_
  * @return RT_ERROR_INVALID_VALUE for input null ptr
  */
 RTS_API rtError_t rtGetTaskIdAndStreamID(uint32_t *taskId, uint32_t *streamId);
-
 #if defined(__cplusplus)
 }
 #endif

third_party/fwkacllib/inc/runtime/config.h

@@ -1,18 +1,18 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
-
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
  * You may obtain a copy of the License at
-
+ *
  * http://www.apache.org/licenses/LICENSE-2.0
-
+ *
  * Unless required by applicable law or agreed to in writing, software
  * distributed under the License is distributed on an "AS IS" BASIS,
  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  * See the License for the specific language governing permissions and
  * limitations under the License.
-*/
+ */
 
 #ifndef __CCE_RUNTIME_CONFIG_H__
 #define __CCE_RUNTIME_CONFIG_H__

third_party/fwkacllib/inc/runtime/context.h

@@ -1,18 +1,18 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
-
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
  * You may obtain a copy of the License at
-
+ *
  * http://www.apache.org/licenses/LICENSE-2.0
-
+ *
  * Unless required by applicable law or agreed to in writing, software
  * distributed under the License is distributed on an "AS IS" BASIS,
  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  * See the License for the specific language governing permissions and
  * limitations under the License.
-*/
+ */
 
 #ifndef __CCE_RUNTIME_CONTEXT_H__
 #define __CCE_RUNTIME_CONTEXT_H__

third_party/fwkacllib/inc/runtime/dev.h

@@ -1,18 +1,18 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
-
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
  * You may obtain a copy of the License at
-
+ *
  * http://www.apache.org/licenses/LICENSE-2.0
-
+ *
  * Unless required by applicable law or agreed to in writing, software
  * distributed under the License is distributed on an "AS IS" BASIS,
  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  * See the License for the specific language governing permissions and
  * limitations under the License.
-*/
+ */
 
 #ifndef __CCE_RUNTIME_DEVICE_H__
 #define __CCE_RUNTIME_DEVICE_H__

third_party/fwkacllib/inc/runtime/dvfsprofile.h

@@ -1,18 +1,18 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
-
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
  * You may obtain a copy of the License at
-
+ *
  * http://www.apache.org/licenses/LICENSE-2.0
-
+ *
  * Unless required by applicable law or agreed to in writing, software
  * distributed under the License is distributed on an "AS IS" BASIS,
  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  * See the License for the specific language governing permissions and
  * limitations under the License.
-*/
+ */
 
 #ifndef __CCE_RUNTIME_DVFSPROFILE_H__
 #define __CCE_RUNTIME_DVFSPROFILE_H__

third_party/fwkacllib/inc/runtime/event.h

@@ -1,18 +1,18 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
-
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
  * You may obtain a copy of the License at
-
+ *
  * http://www.apache.org/licenses/LICENSE-2.0
-
+ *
  * Unless required by applicable law or agreed to in writing, software
  * distributed under the License is distributed on an "AS IS" BASIS,
  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  * See the License for the specific language governing permissions and
  * limitations under the License.
-*/
+ */
 
 #ifndef __CCE_RUNTIME_EVENT_H__
 #define __CCE_RUNTIME_EVENT_H__