upgrad Ascend software package 15 Jul 22

inc/external/ge/ge_api_types.h

@@ -77,6 +77,8 @@ const char_t *const GRAPH_MEMORY_MAX_SIZE = "ge.graphMemoryMaxSize";
 const char_t *const VARIABLE_MEMORY_MAX_SIZE = "ge.variableMemoryMaxSize";
 const char_t *const OPTION_EXEC_REUSE_ZERO_COPY_MEMORY = "ge.exec.reuseZeroCopyMemory";
 
+const std::string ATOMIC_CLEAN_POLICY = "ge.exec.atomicCleanPolicy";
+
 const char_t *const OPTION_EXEC_LOGICAL_DEVICE_CLUSTER_DEPLOY_MODE = "ge.exec.logicalDeviceClusterDeployMode";
 const char_t *const OPTION_EXEC_LOGICAL_DEVICE_ID = "ge.exec.logicalDeviceId";
 

metadef

@@ -1 +1 @@
-Subproject commit 175dce710e744666c6204540857634f362aafd61
+Subproject commit e4d1efc47349f13af1bcdb53ba408118779fc27e

third_party/fwkacllib/inc/ops/array_ops.h

@@ -1160,27 +1160,27 @@ REG_OP(MirrorPadGrad)
     .OP_END_FACTORY_REG(MirrorPadGrad)
 
 /**
-*@brief Returns locations of nonzero / true values in a tensor. \n
+* @brief Returns locations of nonzero / true values in a tensor. \n
 
-*@par Inputs:
-*Including:
-*x: A Tensor. Must be one of the following types:
-DT_DOUBLE, DT_FLOAT, DT_FLOAT16, DT_INT8, DT_UINT8, DT_INT16,
-DT_UINT16, DT_INT32, DT_UINT32, DT_INT64, DT_UINT64, DT_BOOL. \n
+* @par Inputs:
+* Including:
+* @li x: A Tensor. Must be one of the following types:
+  DT_DOUBLE, DT_FLOAT, DT_FLOAT16, DT_INT8, DT_UINT8, DT_QINT8,
+  DT_QUINT8, DT_INT16, DT_UINT16, DT_INT32, DT_UINT32, DT_QINT32,
+  DT_INT64, DT_UINT64, DT_BOOL, DT_COMPLEX64, DT_COMPLEX128 \n
 
-*@par Outputs:
-*y: A Tensor of type DT_INT64. \n
+* @par Outputs:
+* @li y: A Tensor of type DT_INT64. \n
 
-*@attention Constraints:
-*Where runs on the Ascend AI CPU, which delivers poor performance.\n
+* @attention Constraints:
+* Where runs on the Ascend AI CPU, which delivers poor performance.\n
 
-*@par Third-party framework compatibility
-*Compatible with the TensorFlow operator Where.
+* @par Third-party framework compatibility
+* Compatible with the TensorFlow operator Where.
 */
 
 REG_OP(Where)
-    .INPUT(x, TensorType({DT_DOUBLE, DT_FLOAT, DT_FLOAT16, DT_INT8, DT_UINT8, DT_INT16, \
-              DT_UINT16, DT_INT32, DT_UINT32, DT_INT64, DT_UINT64, DT_BOOL}))
+    .INPUT(x, TensorType({BasicType(), DT_BOOL}))
     .OUTPUT(y, TensorType({DT_INT64}))
     .OP_END_FACTORY_REG(Where)
 

third_party/fwkacllib/inc/ops/matrix_calculation_ops.h

@@ -1815,6 +1815,60 @@ REG_OP(SwinAttentionScore)
     .ATTR(bmm_score_transpose_b, Bool, false)
     .ATTR(softmax_axes, ListInt, {})
     .OP_END_FACTORY_REG(SwinAttentionScore)
+
+/**
+* @brief Uses "updates" to update tensor "data" by "indices". \n
+
+* @par Inputs:
+* Three inputs, including:
+* @li var: A Tensor of type BasicType.
+* @li indices: An ND Tensor of type int32 or int64.
+* @li updates: An Tensor with the same dtype as 'var'. Same shape as indices. \n
+
+* @par Attributes:
+* @li use_locking: An optional bool. Defaults to "False". If "True",
+* the operation will be protected by a lock . \n
+
+* @par Outputs:
+* var: A Tensor. Has the same type and format as input "var" . \n
+
+* @par Third-party framework compatibility
+* Compatible with the TensorFlow operator ScatterNdMax.
+*/
+REG_OP(ScatterNdMax)
+    .INPUT(var, TensorType::BasicType())
+    .INPUT(indices, TensorType::IndexNumberType())
+    .INPUT(updates, TensorType::BasicType())
+    .OUTPUT(var,  TensorType::BasicType())
+    .ATTR(use_locking, Bool, false)
+    .OP_END_FACTORY_REG(ScatterNdMax)
+
+/**
+* @brief Uses "updates" to update tensor "data" by "indices". \n
+
+* @par Inputs:
+* Three inputs, including:
+* @li var: A Tensor of type BasicType.
+* @li indices: A ND Tensor of type int32 or int64.
+* @li updates: A Tensor with the same dtype as 'var'. Same shape as indices. \n 
+
+* @par Attributes:
+* use_locking: An optional bool. Defaults to "False". If "True",
+* the operation will be protected by a lock . \n
+
+* @par Outputs:
+* var: A Tensor. Has the same type and format as input "var" . \n
+
+* @par Third-party framework compatibility
+* Compatible with the TensorFlow operator ScatterNdMin.
+*/
+REG_OP(ScatterNdMin)
+    .INPUT(var, TensorType::BasicType())
+    .INPUT(indices, TensorType::IndexNumberType())
+    .INPUT(updates, TensorType::BasicType())
+    .OUTPUT(var,  TensorType::BasicType())
+    .ATTR(use_locking, Bool, false)
+    .OP_END_FACTORY_REG(ScatterNdMin)
 }  // namespace ge
 
 #endif  // OPS_BUILT_IN_OP_PROTO_INC_MATRIX_CALCULATION_OPS_H_

third_party/fwkacllib/inc/toolchain/prof_callback.h

@@ -170,7 +170,7 @@ MSVP_PROF_API int32_t MsprofInit(uint32_t moduleId, void *data, uint32_t dataLen
  * @param moduleId  [IN] module Id
  * @param handle    [IN] the pointer of callback
  */
-MSVP_PROF_API int32_t MsprofRegisterCallback(uint32_t moduleId, ProfCommandHandle handle);
+MSVP_PROF_API int32_t MsprofRegisterCallback(uint32_t moduleId, ProfCommandHandle callback);
 /*
  * @name profReportData
  * @brief start reporter/stop reporter/report date