upgrade Ascend package 24 Feb 22

inc/external/acl/OWNERS

@@ -1,10 +0,0 @@
-approvers:
-- ji_chen
-- wqtshg
-- zhangfan_hq
-reviewers:
-- justin_zhao
-- zhangyongfeng88
-- w00267184
-options:
-  no_parent_owners: true

inc/external/acl/acl.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/acl/acl_base.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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.
@@ -164,6 +164,7 @@ typedef enum {
   ACL_FORMAT_NC1HWC0 = 3,
   ACL_FORMAT_FRACTAL_Z = 4,
   ACL_FORMAT_NC1HWC0_C04 = 12,
+  ACL_FORMAT_HWCN = 16,
   ACL_FORMAT_NDHWC = 27,
   ACL_FORMAT_FRACTAL_NZ = 29,
   ACL_FORMAT_NCDHW = 30,

inc/external/acl/acl_mdl.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/acl/acl_op.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/acl/acl_op_compiler.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/acl/acl_prof.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/acl/acl_rt.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/acl/acl_tdt.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/acl/acl_tdt_queue.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/acl/error_codes/ge_error_codes.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/acl/error_codes/rt_error_codes.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/acl/ops/acl_cblas.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/acl/ops/acl_dvpp.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/acl/ops/acl_fv.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/ge/ge_api.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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.
@@ -72,7 +72,7 @@ class GE_FUNC_VISIBILITY Session {
   /// @return Status result of function
   ///
   ATTRIBUTED_DEPRECATED(Status AddGraph(uint32_t, const Graph &, const std::map<AscendString, AscendString> &))
-  Status AddGraph(uint32_t graphId, const Graph &graph, const std::map<std::string, std::string> &options);
+  Status AddGraph(uint32_t graph_id, const Graph &graph, const std::map<std::string, std::string> &options);
 
   ///
   /// @ingroup client
@@ -82,7 +82,7 @@ class GE_FUNC_VISIBILITY Session {
   /// @param [in] options graph options
   /// @return Status result of function
   ///
-  Status AddGraph(uint32_t graphId, const Graph &graph, const std::map<AscendString, AscendString> &options);
+  Status AddGraph(uint32_t graph_id, const Graph &graph, const std::map<AscendString, AscendString> &options);
 
   ///
   /// @ingroup client
@@ -119,7 +119,7 @@ class GE_FUNC_VISIBILITY Session {
   /// @param [out] outputs output data
   /// @return Status result of function
   ///
-  Status RunGraph(uint32_t graphId, const std::vector<Tensor> &inputs, std::vector<Tensor> &outputs);
+  Status RunGraph(uint32_t graph_id, const std::vector<Tensor> &inputs, std::vector<Tensor> &outputs);
 
   ///
   /// @ingroup ge_graph
@@ -140,9 +140,9 @@ class GE_FUNC_VISIBILITY Session {
   /// @param [in] inputs: input data
   /// @return Status result of function
   ///
-  Status BuildGraph(uint32_t graphId, const std::vector<InputTensorInfo> &inputs);
+  Status BuildGraph(uint32_t graph_id, const std::vector<InputTensorInfo> &inputs);
 
-  Status BuildGraph(uint32_t graphId, const std::vector<ge::Tensor> &inputs); /*lint !e148*/
+  Status BuildGraph(uint32_t graph_id, const std::vector<ge::Tensor> &inputs); /*lint !e148*/
 
   ///
   /// @ingroup ge_graph
@@ -154,7 +154,7 @@ class GE_FUNC_VISIBILITY Session {
   ///                        Please ensure that the implementation of the function is trusted.
   /// @return Status result of function
   ///
-  Status RunGraphAsync(uint32_t graphId, const std::vector<ge::Tensor> &inputs, RunAsyncCallback callback);
+  Status RunGraphAsync(uint32_t graph_id, const std::vector<ge::Tensor> &inputs, RunAsyncCallback callback);
 
   ///
   /// @ingroup ge_graph

inc/external/ge/ge_api_error_codes.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/ge/ge_api_types.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/ge/ge_error_codes.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/ge/ge_ir_build.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/hccl/hccl.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/hccl/hccl_types.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/external/runtime/rt_error_codes.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ * Copyright 2019-2022 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/file_constant_util.h

@@ -23,7 +23,6 @@
 #include "ge/ge_api_error_codes.h"
 #include "nlohmann/json.hpp"
 #include "graph/op_desc.h"
-#include "graph/types.h"
 #include "graph/ge_tensor.h"
 
 namespace ge {

inc/framework/common/helper/model_helper.h

@@ -20,7 +20,6 @@
 #include <memory>
 #include <string>
 
-#include "framework/common/fmk_types.h"
 #include "framework/common/helper/om_file_helper.h"
 #include "common/model/ge_model.h"
 #include "common/model/ge_root_model.h"

inc/framework/common/op/attr_value_util.h

@@ -34,7 +34,6 @@
 #include <google/protobuf/map.h>
 #include <unordered_map>
 #include <string>
-#include "external/graph/types.h"
 #include "graph/debug/ge_attr_define.h"
 #include "proto/om.pb.h"
 

inc/framework/common/op/ge_op_utils.h

@@ -21,8 +21,6 @@
 #include <vector>
 
 #include "framework/common/op/attr_value_util.h"
-#include "register/register_types.h"
-#include "register/register_error_codes.h"
 #include "framework/common/util.h"
 #include "graph/attr_value.h"
 #include "graph/ge_tensor.h"

inc/framework/common/profiling_definitions.h

@@ -52,6 +52,21 @@ enum {
   kOpExecute,
   kAllocMem,
   kCopyH2D,
+  kPrepareNode,
+  kWaitForPrepareDone,
+  kPropgateOutputs,
+  kOnNodeDoneCallback,
+  kValidateInputTensor,
+  kAfterExecuted,
+  kRtEventSychronize,
+  kInferShapeWaitDependShape,
+  kInferShapeWaitInputTensor,
+  kInferShapeCallInferFunc,
+  kInferShapePropgate,
+  // v2 control node
+  kSelectBranch,
+  kExecuteSubGraph,
+  kInitSubGraphExecutor,
 
   // Add new definitions here
   kProfilingIndexEnd

inc/framework/common/scope_guard.h

@@ -18,7 +18,6 @@
 #define INC_FRAMEWORK_COMMON_SCOPE_GUARD_H_
 
 #include <functional>
-#include <iostream>
 
 /// Usage:
 /// Acquire Resource 1

inc/framework/common/util.h

@@ -17,11 +17,9 @@
 #ifndef AIR_INC_FRAMEWORK_COMMON_UTIL_H_
 #define AIR_INC_FRAMEWORK_COMMON_UTIL_H_
 
-#include <climits>
 #include <cmath>
 #include <sstream>
 #include <string>
-#include <vector>
 
 #include <google/protobuf/text_format.h>
 #include "external/graph/types.h"

inc/framework/executor/ge_executor.h

@@ -315,6 +315,10 @@ class GE_FUNC_VISIBILITY GeExecutor {
   static Status LoadDynamicSingleOpV2(const std::string &model_name, const ModelData &model_data, void *const stream,
                                       DynamicSingleOp **const single_op, const uint64_t model_id);
 
+  static Status UnloadSingleOp(const uint64_t op_id);
+
+  static Status UnloadDynamicSingleOp(const uint64_t op_id);
+
   static Status ExecuteAsync(DynamicSingleOp *const executor, const std::vector<GeTensorDesc> &input_desc,
                              const std::vector<DataBuffer> &inputs, std::vector<GeTensorDesc> &output_desc,
                              std::vector<DataBuffer> &outputs);

inc/framework/omg/parser/op_parser.h

@@ -21,8 +21,6 @@
 #include "framework/omg/parser/parser_types.h"
 #include "framework/omg/omg_inner_types.h"
 #include "proto/om.pb.h"
-#include "graph/ge_tensor.h"
-#include "graph/op_desc.h"
 #include "graph/utils/op_desc_utils.h"
 
 using google::protobuf::Message;

inc/framework/omg/version.h

@@ -18,7 +18,6 @@
 #define INC_FRAMEWORK_OMG_VERSION_H_
 
 #include <memory>
-#include <set>
 
 #include "framework/common/debug/log.h"
 #include "framework/common/string_util.h"

metadef

@@ -1 +1 @@
-Subproject commit 0a2335712484f85cd44a0f2402eac6932b22b40a
+Subproject commit ab3207e99f94aabf036e1c8b068de0df15ff2d01

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

@@ -62,6 +62,7 @@ static const int32_t ACL_ERROR_RT_OVER_LIMIT                 = 207012; // over l
 static const int32_t ACL_ERROR_RT_QUEUE_EMPTY                = 207013; // queue is empty
 static const int32_t ACL_ERROR_RT_QUEUE_FULL                 = 207014; // queue is full
 static const int32_t ACL_ERROR_RT_REPEATED_INIT              = 207015; // repeated init
+static const int32_t ACL_ERROR_RT_AIVEC_OVER_FLOW            = 207016; // aivec over flow
 
 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

third_party/fwkacllib/inc/ops/array_ops.h

@@ -1496,17 +1496,23 @@ REG_OP(QueueData)
 /**
 * @brief Ensures that the tensor's shape matches the expected shape. \n
 * @par Inputs:
-* x: A Tensor. \n
+* input: A Tensor. that need to be checked with desired shape 
+*        Must be one of the following types:
+*        int8, uint8, int16, uint16, int32, int64, float16, float
+*        double, complex64 complex128 \n
 * @par Attributes:
-* shape:  The shape that needs to be checked \n
+* shape: required, a desired tensor shape. type: list int \n
 * @par Outputs:
-* y: A tensor. \n
+* output: A tensor. has the same type and contents as input 
+*        Must be one of the following types:
+*        int8, uint8, int16, uint16, int32, int64, float16, float
+*        double, complex64 complex128 \n
 */
 REG_OP(EnsureShape)
-    .INPUT(input, TensorType({DT_INT8,DT_UINT8,DT_INT16,DT_UINT16,DT_INT32,DT_INT64,DT_FLOAT16, \
-                            DT_FLOAT,DT_DOUBLE}))
-    .OUTPUT(output, TensorType({DT_INT8,DT_UINT8,DT_INT16,DT_UINT16,DT_INT32,DT_INT64,DT_FLOAT16, \
-                            DT_FLOAT,DT_DOUBLE}))
+    .INPUT(input, TensorType({DT_INT8,DT_UINT8, DT_INT16, DT_UINT16, DT_INT32, DT_INT64, DT_FLOAT16, \
+                            DT_FLOAT, DT_DOUBLE, DT_COMPLEX64, DT_COMPLEX128}))
+    .OUTPUT(output, TensorType({DT_INT8, DT_UINT8, DT_INT16, DT_UINT16, DT_INT32, DT_INT64, DT_FLOAT16, \
+                            DT_FLOAT,DT_DOUBLE, DT_COMPLEX64, DT_COMPLEX128}))
     .REQUIRED_ATTR(shape, ListInt)
     .OP_END_FACTORY_REG(EnsureShape)
 }  // namespace ge

third_party/fwkacllib/inc/ops/ctc_ops.h

@@ -156,16 +156,15 @@ REG_OP(CTCBeamSearchDecoder)
 *@li log_alpha: The probability of possible trace of input to target.
 
 *@par Attributes:
-*@li blank : Blank label. Default 0.
+*@li blank: Blank label. Default 0.
 *@li reduction: Specifies the reduction to apply to the output. Default: 'mean'.
-*@li zero_infinity : Whether to zero infinite losses and the associated gradients.
-*@li label_max : The max length of targets.
+*@li zero_infinity: Whether to zero infinite losses and the associated gradients.
 
-*@par Third-party framework compatibility
+* @par Third-party framework compatibility:
 * Compatible with Pytorch CTCLoss operator.
 
 *@attention Constraints:
-*The limit of Label’s length is 1K.
+* The limit of Label’s length is 1K.
 */
 REG_OP(CTCLossV2)
     .INPUT(log_probs, TensorType({DT_FLOAT, DT_DOUBLE}))
@@ -177,38 +176,36 @@ REG_OP(CTCLossV2)
     .ATTR(blank, Int, 0)
     .ATTR(reduction, String, "mean")
     .ATTR(zero_infinity, Bool, false)
-    .ATTR(label_max, Int, 0)
     .OP_END_FACTORY_REG(CTCLossV2)
 
 /**
 *@brief The Connectionist Temporal Classification loss grad.
 
-*@par Inputs:
+* @par Inputs:
 *@li grad_out: Gradient renewal coefficient. Tensor of size (N), where N = batch size.
-*@li log_probs: Tensor of size (T, N, C), where T =input length, N =batch size,
+* @li log_probs: Tensor of size (T, N, C), where T =input length, N =batch size,
                 and C = number of classes (including blank).
                 It represent the logarithmized probabilities of the outputs.
 *@li targets: Tensor of size (N, S) or sum(target_lengths), where S = max target length.
              It represent the target sequences.
-*@li input_lengths: Tuple or tensor of size (N). It represent the lengths of the inputs.
+* @li input_lengths: Tuple or tensor of size (N). It represent the lengths of the inputs.
 *@li target_lengths: Tuple or tensor of size (N). It represent lengths of the targets.
-*@li neg_log_likelihood: A loss value which is differentiable with respect to each input node.
-*@li log_alpha: The probability of possible trace of input to target.
+* @li neg_log_likelihood: A loss value which is differentiable with respect to each input node.
+* @li log_alpha: The probability of possible trace of input to target.
 
-*@par Outputs:
+* @par Outputs:
 *@li grad: Tensor of size (T, N, C), The grad of Connectionist Temporal Classification loss.
 
-*@par Attributes:
-*@li blank : Blank label. Default 0.
-*@li reduction: Specifies the reduction to apply to the output. Default: 'mean'.
-*@li zero_infinity : Whether to zero infinite losses and the associated gradients.
-*@li label_max : The max length of targets.
+* @par Attributes:
+*@li blank: Blank label. Default 0.
+* @li reduction: Specifies the reduction to apply to the output. Default: 'mean'.
+* @li zero_infinity: Whether to zero infinite losses and the associated gradients.
 
-*@par Third-party framework compatibility
+* @par Third-party framework compatibility:
 * Compatible with Pytorch CTCLoss operator.
 
-*@attention Constraints:
-*The limit of Label’s length is 1K.
+* @attention Constraints:
+* The limit of Label’s length is 1K.
 */
 REG_OP(CTCLossV2Grad)
     .INPUT(grad_out, TensorType({DT_FLOAT, DT_DOUBLE}))
@@ -222,7 +219,6 @@ REG_OP(CTCLossV2Grad)
     .ATTR(blank, Int, 0)
     .ATTR(reduction, String, "mean")
     .ATTR(zero_infinity, Bool, false)
-    .ATTR(label_max, Int, 0)
     .OP_END_FACTORY_REG(CTCLossV2Grad)
 }  // namespace ge
 

third_party/fwkacllib/inc/ops/image_ops.h

@@ -349,6 +349,7 @@ REG_OP(ExtractGlimpse)
 *y:images converted to RGB . \n
 
 *@attention Constraints:
+*Input images currently supports DT_FLOAT, DT_DOUBLE .
 *Last dimension of input x must be size 3 . \n
 
 *@par Third-party framework compatibility
@@ -2307,5 +2308,52 @@ REG_OP(UpsampleNearest1dGrad)
     .REQUIRED_ATTR(output_size, ListInt)
     .ATTR(scales, ListFloat, {})
     .OP_END_FACTORY_REG(UpsampleNearest1dGrad)
+
+/**
+* @brief JPEG encode input image with provided compression quality. \n
+
+* @par Inputs:
+* @li images: image is a 3-D uint8 tensor of shape [height, width, channels]. 
+* @li quality: int32 jpeg compression quality value between 0 and 100, 0-D tensor.
+
+* @par Outputs: JPEG-encoded image
+* contents: an output string. \n
+
+* @par Third-party framework compatibility.
+* Compatible with tensorflow EncodeJpegVariableQuality operator.
+*/
+
+REG_OP(EncodeJpegVariableQuality)
+    .INPUT(images, TensorType({DT_UINT8}))
+    .INPUT(quality, TensorType({DT_INT32}))
+    .OUTPUT(contents, TensorType({DT_STRING}))
+    .OP_END_FACTORY_REG(EncodeJpegVariableQuality)
+
+/**
+* @brief image to transforms. \n
+
+* @par Inputs:
+* @li images: [batch, height, width, channels], 4-D tensor. 
+* @li transforms: [batch, 8] or [1, 8] matrix, 2-D tensor.
+* @li outout_shape: [new_height, new_width], 1-D tensor.
+
+* @par Attributes:
+* @li interpolation: Interpolation method, "NEAREST" or "BILINEAR", 0-D tensor.
+* @li fill_mode: Defaults to "CONSTANT". Fill mode, "REFLECT", "WRAP", or "CONSTANT", 0-D tensor.
+
+* @par Outputs
+* transformed_images: has the same type as iamges, 4-D tensor with shape[batch, new_height, new_width, channels]. \n
+
+* @par Third-party framework compatibility.
+* Compatible with tensorflow ImageProjectiveTransform operator.
+*/
+REG_OP(ImageProjectiveTransform)
+    .INPUT(images, TensorType({DT_UINT8, DT_INT32, DT_INT64, DT_FLOAT16, DT_FLOAT, DT_DOUBLE}))
+    .INPUT(transforms, TensorType({DT_FLOAT}))
+    .INPUT(output_shape, TensorType({DT_INT32}))
+    .REQUIRED_ATTR(interpolation, String)
+    .ATTR(fill_mode, String, "CONSTANT")
+    .OUTPUT(transformed_images, TensorType({DT_UINT8, DT_INT32, DT_INT64, DT_FLOAT16, DT_FLOAT, DT_DOUBLE}))
+    .OP_END_FACTORY_REG(ImageProjectiveTransform)
 }  // namespace ge
 #endif  // OPS_BUILT_IN_OP_PROTO_INC_IMAGE_OPS_H_

third_party/fwkacllib/inc/ops/nn_norm_ops.h

@@ -1700,6 +1700,45 @@ REG_OP(GroupNormRelu)
     .REQUIRED_ATTR(num_groups, Int)
     .ATTR(eps, Float, 0.00001)
     .OP_END_FACTORY_REG(GroupNormRelu)
-}  // namespace ge
 
+/**
+* @brief Function dropout with softmaxgrad and muls
+
+* @par Inputs:
+* Two inputs, including:
+* @li y_grad: A mutable Tensor. The type only support float16.
+* @li mask: A mutable Tensor. Must met all of the following rules:
+*     shape of mask should be 1D.
+*     dtype of mask should be uint8.
+*     value of shape should met the following algorithm:
+*     value = (size(x) + 128 - 1) // 128 * 128
+* @li softmax_output: A mutable Tensor. Must met all of the following rules:
+*     shape of softmax_output should be NZ.
+*     dtype of softmax_output should be float16.
+*     it is the output of softmax
+
+* @par Attributes:
+* @li input_keep_prob:A attribute used to judge which units should be keep.
+*     Has the same type as "x" . \n
+* @li alpha: A attribute used to scale tensor.
+*     Has the same type as "x" . \n
+* @li axes: A list of int. The dimension softmax would be performed on. Defaults
+*     to "[-1]" . \n
+
+* @par Outputs:
+* x_grad: A mutable Tensor. Has the same type as "x". \n
+
+* @par Restrictions:
+* Warning: THIS FUNCTION IS EXPERIMENTAL. Please do not use.
+*/
+REG_OP(DropoutWithMulsAndSoftmaxGrad)
+    .INPUT(y_grad, TensorType({ DT_FLOAT16 }))
+    .INPUT(mask, TensorType({ DT_UINT8 }))
+    .INPUT(softmax_output, TensorType({ DT_FLOAT16 }))
+    .OUTPUT(x_grad, TensorType({ DT_FLOAT16 }))
+    .REQUIRED_ATTR(input_keep_prob, Float)
+    .REQUIRED_ATTR(alpha, Float)
+    .ATTR(axes, ListInt, { -1 })
+    .OP_END_FACTORY_REG(DropoutWithMulsAndSoftmaxGrad)
+}  // namespace ge
 #endif  // OPS_BUILT_IN_OP_PROTO_INC_NN_NORM_OPS_H_

third_party/fwkacllib/inc/ops/quantize_ops.h

@@ -241,6 +241,29 @@ REG_OP(AscendRequantS16)
   .ATTR(dual_output, Bool, false)
   .ATTR(relu_flag, Bool, false)
   .OP_END_FACTORY_REG(AscendRequantS16)
+
+/**
+* @brief Quantizes the input of int8 . \n
+
+* @par Inputs:
+* @li x: An FRACTAL_Z tensor of type int8, specifying the input.
+* @li offset: An FRACTAL_Z tensor of type int8.
+
+* @par Attributes:
+* @li dst_type: A optional int from: DT_INT8, DT_INT4. Defaults to DT_INT8.
+
+* @par Outputs:
+* @li y: output tensor of type int4 or int8 and with format FRACTAL_Z.
+
+* @par Third-party framework compatibility
+* It is a custom operator. It has no corresponding operator in Caffe, Onnx, Tensorflow or Pythorch.
+*/
+REG_OP(AscendWeightQuant)
+  .INPUT(x, TensorType({DT_INT8}))
+  .INPUT(offset, TensorType({DT_INT8}))
+  .OUTPUT(y, TensorType({DT_INT8, DT_INT4}))
+  .ATTR(dst_type, Int, DT_INT8)
+  .OP_END_FACTORY_REG(AscendWeightQuant)
 } // namespace ge
 
 #endif  // OPS_BUILT_IN_OP_PROTO_INC_QUANTIZE_OPS_H_

third_party/fwkacllib/inc/runtime/dev.h

@@ -82,6 +82,12 @@ typedef enum tagRtDeviceModuleType {
     RT_MODULE_TYPE_VECTOR_CORE, /**< VECTOR CORE info*/
 } rtDeviceModuleType_t;
 
+typedef enum tagRtMemRequestFeature {
+    MEM_REQUEST_FEATURE_DEFAULT = 0,
+    MEM_REQUEST_FEATURE_OPP,
+    MEM_REQUEST_FEATURE_RESERVED
+} rtMemRequestFeature_t;
+
 // used for rtGetDevMsg callback function
 typedef void (*rtGetMsgCallback)(const char_t *msg, uint32_t len);
 
@@ -418,6 +424,15 @@ RTS_API rtError_t rtDeviceResetWithoutTsd(int32_t devId);
  * @return RT_ERROR_INVALID_VALUE for error input
  */
 RTS_API rtError_t rtGetDevMsg(rtGetDevMsgType_t getMsgType, rtGetMsgCallback callback);
+
+/**
+ * @ingroup dvrt_dev
+ * @brief get ts mem type
+ * @param [in] rtMemRequestFeature_t mem request feature type
+ * @param [in] mem request size
+ * @return RT_MEMORY_TS, RT_MEMORY_HBM, RT_MEMORY_TS | RT_MEMORY_POLICY_HUGE_PAGE_ONLY
+ */
+RTS_API uint32_t rtGetTsMemType(rtMemRequestFeature_t featureType, uint32_t memSize);
 #if defined(__cplusplus)
 }
 #endif

third_party/fwkacllib/inc/runtime/kernel.h

@@ -217,6 +217,13 @@ typedef void (*rtCallback_t)(void *fnData);
 #define RT_NORMAL_KERNEL_MODE (0x01U)
 #define RT_ALL_KERNEL_MODE (0x02U)
 
+/**
+ * @ingroup rt_kernel
+ * @brief SHAPE kernel type
+**/
+#define RT_STATIC_SHAPE_KERNEL (0x00U)
+#define RT_DYNAMIC_SHAPE_KERNEL (0x01U)
+
 /**
  * @ingroup rt_kernel
  * @brief kernel L1 Fusion Dump bit flags
@@ -335,6 +342,21 @@ RTS_API rtError_t rtQueryFunctionRegistered(const char_t *stubName);
 RTS_API rtError_t rtKernelConfigDump(uint32_t kind, uint32_t dumpSizePerBlock, uint32_t blockDim, void **dumpBaseAddr,
                                      rtStream_t stm);
 
+/**
+* @ingroup rt_kernel
+* @brief get kernel address and prefetchCnt
+* @param [in] hdl           program for dynamic shape
+* @param [in] tilingKey     tilingKey for dynamic shape
+* @param [in] stubFunc      stubFunc for static shape
+* @param [in] flag          flag for distinguishing between dynamic shape and static shape
+* @param [out] addr         address of kernel function
+* @param [out] prefetchCnt  prefetchCnt of kernel function
+* @return RT_ERROR_NONE for ok
+* @return RT_ERROR_INVALID_VALUE for error input
+*/
+RTS_API rtError_t rtKernelGetAddrAndPrefCnt(void *hdl, const uint64_t tilingKey, const void * const stubFunc,
+                                            const uint32_t flag, void **addr, uint32_t *prefetchCnt);
+
 /**
  * @ingroup rt_kernel
  * @brief launch kernel to device

third_party/fwkacllib/inc/runtime/rt_model.h

@@ -336,6 +336,16 @@ RTS_API rtError_t rtSetTaskGenCallback(rtTaskGenCallback callback);
  */
 RTS_API rtError_t rtModelCreate(rtModel_t *mdl, uint32_t flag);
 
+/**
+ * @ingroup rt_model
+ * @brief set ge model id to aicpu
+ * @param [in]     model   aicpu model
+ * @param [in]     extid   ge model id
+ * @return RT_ERROR_NONE for ok
+ * @return RT_ERROR_INVALID_VALUE for error input
+ */
+rtError_t rtModelSetExtId(rtModel_t mdl, uint32_t extId);
+
 /**
  * @ingroup rt_model
  * @brief destroy model instance

third_party/fwkacllib/inc/tdt/tsd_client.h

@@ -34,6 +34,13 @@
 extern "C" {
 #endif  // __cplusplus
 
+struct InitFlowGwInfo {
+    const char_t *groupName;
+    uint64_t schedPolicy;
+    uint64_t reschedInterval;
+    char_t rsv[128];
+};
+
 /**
 * @ingroup Open
 * @brief Used for the Framework process to communicate with the TSDDaemon process,
@@ -101,6 +108,27 @@ TDT_LIB_EXPORT uint32_t TsdOpenEx(const uint32_t logicDeviceId, const uint32_t r
 */
 TDT_LIB_EXPORT uint32_t TsdInitQs(const uint32_t logicDeviceId, const char_t * const groupName = nullptr);
 
+/**
+* @ingroup InitFlowGw
+* @brief Used for the Framework process to communicate with the TSDDaemon process,
+* and notify TSD to complete the initialization of FlowGw processes
+*
+* @par Function
+* Used for the Framework process to communicate with the TSDDaemon process,
+* and notify TSD to complete the initialization of other processes
+*
+* @param logicDeviceId [IN] type #unsigned int. Logic device ID
+* @param initInfo [IN] type #InitFlowGwInfo pointer. Initialization parameters
+* @retval TDT_OK Success
+* @retval OtherValues Failure
+*
+* @par Dependency
+* @li libtsdclient.so: Library to which the interface belongs.
+* @li tsd_client.h: Header file where the interface declaration is located.
+* @li data_common.h: Header file where 'TDT_StatusT' defined
+*/
+TDT_LIB_EXPORT uint32_t TsdInitFlowGw(const uint32_t logicDeviceId, const InitFlowGwInfo * const initInfo);
+
 /**
 * @ingroup Close
 * @brief notify TSDClient close resource

third_party/fwkacllib/inc/toolchain/prof_reporter.h

@@ -14,8 +14,8 @@
  * limitations under the License.
  */
 
-#ifndef MSPROF_ENGINE_PROF_REPORTER_H_
-#define MSPROF_ENGINE_PROF_REPORTER_H_
+#ifndef MSPROF_ENGINE_PROF_REPORTER_H
+#define MSPROF_ENGINE_PROF_REPORTER_H
 
 #if (defined(_WIN32) || defined(_WIN64) || defined(_MSC_VER))
 #define MSVP_PROF_API __declspec(dllexport)