!3820 support tensor attr shape and dtype in graph mode

Merge pull request !3820 from zhangbuxue/support_dtype_and_shape_as_attr_in_graph_mode

mindspore/_extends/parse/standard_method.py

@@ -28,7 +28,8 @@ from ...ops.composite.base import _append
 __all__ = ['MultitypeFuncGraph', 'env_get', 'hyper_add', 'zeros_like', 'ones_like']
 
 trans = P.Transpose()
-
+shape_ = P.Shape()
+dtype_ = P.DType()
 
 def transpose(x):
     """Implementation of `transpose`."""

mindspore/ccsrc/frontend/operator/ops.h

@@ -93,7 +93,6 @@ inline const PrimitivePtr kPrimArrayToScalar = std::make_shared<Primitive>("arra
 inline const PrimitivePtr kPrimBroadcastShape = std::make_shared<Primitive>("broadcast_shape");
 inline const PrimitivePtr kPrimArrayMap = std::make_shared<Primitive>("array_map");
 inline const PrimitivePtr kPrimArrayReduce = std::make_shared<Primitive>("array_reduce");
-inline const PrimitivePtr kPrimShape = std::make_shared<Primitive>("Shape");
 inline const PrimitivePtr kPrimCast = std::make_shared<Primitive>("Cast");
 inline const PrimitivePtr kPrimConcat = std::make_shared<Primitive>("Concat");
 inline const PrimitivePtr kPrimSqueeze = std::make_shared<Primitive>("Squeeze");

mindspore/ccsrc/frontend/operator/prim_arrays.cc

@@ -15,7 +15,6 @@
  */
 
 #include "pipeline/jit/static_analysis/prim.h"
-#include "frontend/operator/ops.h"
 #include "abstract/utils.h"
 #include "frontend/operator/cc_implementations.h"
 #include "abstract/param_validator.h"
@@ -80,23 +79,6 @@ AbstractBasePtr InferImplBroadCastShape(const AnalysisEnginePtr &, const Primiti
   return std::make_shared<AbstractTuple>(elems);
 }
 
-AbstractBasePtr InferImplShape(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
-                               const AbstractBasePtrList &args_spec_list) {
-  // Inputs: a tensor.
-  const std::string op_name = primitive->name();
-  CheckArgsSize(op_name, args_spec_list, 1);
-  AbstractTensorPtr arg = CheckArg<AbstractTensor>(op_name, args_spec_list, 0);
-  MS_LOG(DEBUG) << "InferImplShape:" << arg->ToString();
-
-  AbstractBasePtrList values;
-  auto shp = arg->shape();
-  for (int entry : shp->shape()) {
-    auto entry_v = MakeValue(entry);
-    values.push_back(std::make_shared<AbstractScalar>(entry_v, entry_v->type()));
-  }
-  return std::make_shared<AbstractTuple>(values);
-}
-
 AbstractBasePtr InferImplTile(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
                               const AbstractBasePtrList &args_spec_list) {
   // Inputs: a tensor and a tuple.

mindspore/ccsrc/pipeline/jit/pipeline.cc

@@ -985,6 +985,7 @@ void ClearResAtexit() {
   abstract::ClearPrimEvaluatorMap();
   compile::ClearConvertCache();
   pipeline::GetMethodMap().clear();
+  pipeline::GetAttrMap().clear();
   pipeline::ExecutorPy::ClearRes();
   pipeline::ReclaimOptimizer();
   pynative::PynativeExecutor::GetInstance()->ClearRes();

mindspore/ccsrc/pipeline/jit/resource.cc

@@ -17,23 +17,20 @@
  */
 
 #include "pipeline/jit/resource.h"
-#include "pipeline/jit/pipeline.h"
 #include "pipeline/jit/static_analysis/static_analysis.h"
-#include "debug/draw.h"
 #include "debug/trace.h"
 #include "ir/dtype.h"
 #include "pipeline/jit/parse/data_converter.h"
 #include "frontend/operator/ops.h"
 #include "ir/graph_utils.h"
 #include "frontend/optimizer/ad/dfunctor.h"
-#include "vm/segment_runner.h"
 
 namespace mindspore {
 // namespace to support opmap definition
 namespace pipeline {
 
-MethodMap &GetMethodMap() {
-  static MethodMap method_map = {
+BuiltInTypeMap &GetMethodMap() {
+  static BuiltInTypeMap method_map = {
     {kObjectTypeString,
      {
        {"__bool__", std::string("str_bool")}  // C.str_bool
@@ -191,6 +188,15 @@ MethodMap &GetMethodMap() {
   return method_map;
 }
 
+BuiltInTypeMap &GetAttrMap() {
+  static BuiltInTypeMap attr_map = {{kObjectTypeTensorType,
+                                     {
+                                       {"shape", std::string("shape_")},  // C.shape_
+                                       {"dtype", std::string("dtype_")},  // C.dtype_
+                                     }}};
+  return attr_map;
+}
+
 Resource::Resource(const py::object &obj)
     : engine_(std::make_shared<abstract::AnalysisEngine>(abstract::GetPrimEvaluatorConstructors(), manager_)),
       input_(obj),
@@ -218,31 +224,42 @@ Resource::~Resource() {
   }
 }
 
-bool Resource::IsTypeInMethodMap(const TypeId &type) {
-  TypeId type_id = NormalizeTypeId(type);
-  const MethodMap &method_map = GetMethodMap();
-  auto iter = method_map.find(static_cast<int>(type_id));
-  if (iter != method_map.end()) {
-    return true;
+Any GetMethodOrAttr(const string &name, const TypeId &type_id, const BuiltInTypeMap &method_map) {
+  auto type_method_map = method_map.find(static_cast<int>(type_id));
+  if (type_method_map == method_map.end()) {
+    return Any();
   }
-  return false;
+  auto method = type_method_map->second.find(name);
+  if (method == type_method_map->second.end()) {
+    return Any();
+  }
+  return method->second;
 }
 
-Any Resource::GetMethodPtr(const TypeId &type, const std::string &name) {
+bool Resource::IsTypeInBuiltInMap(const TypeId &type) {
   TypeId type_id = NormalizeTypeId(type);
-  const MethodMap &method_map = GetMethodMap();
+  const BuiltInTypeMap &method_map = GetMethodMap();
   auto iter = method_map.find(static_cast<int>(type_id));
   if (iter == method_map.end()) {
-    MS_LOG(WARNING) << "Object type: " << type_id << " not in the method_map";
-    return Any();
+    const BuiltInTypeMap &attr_map = GetAttrMap();
+    iter = attr_map.find(static_cast<int>(type_id));
+    if (iter == attr_map.end()) {
+      return false;
+    }
   }
+  return true;
+}
 
-  auto iter_map = iter->second.find(name);
-  if (iter_map == iter->second.end()) {
-    MS_LOG(WARNING) << "Object type: " << type_id << " have no method: " << name;
-    return Any();
-  }
-  return iter_map->second;
+Any Resource::GetMethodPtr(const TypeId &type, const std::string &name) {
+  TypeId type_id = NormalizeTypeId(type);
+  const BuiltInTypeMap &method_map = GetMethodMap();
+  return GetMethodOrAttr(name, type_id, method_map);
+}
+
+Any Resource::GetAttrPtr(const TypeId &type, const std::string &name) {
+  TypeId type_id = NormalizeTypeId(type);
+  const BuiltInTypeMap &attr_map = GetAttrMap();
+  return GetMethodOrAttr(name, type_id, attr_map);
 }
 
 void Resource::Clean() {

mindspore/ccsrc/pipeline/jit/resource.h

@@ -44,9 +44,11 @@ const char kOutput[] = "output";
 
 class InferenceResource;
 
-using MethodMap = std::unordered_map<int, std::unordered_map<std::string, Any>>;
+using BuiltInTypeMap = std::unordered_map<int, std::unordered_map<std::string, Any>>;
 
-MethodMap &GetMethodMap();
+BuiltInTypeMap &GetMethodMap();
+
+BuiltInTypeMap &GetAttrMap();
 
 class ResourceBase {
  public:
@@ -87,10 +89,12 @@ class Resource : public ResourceBase {
 
   abstract::AnalysisEnginePtr engine() { return engine_; }
 
-  static bool IsTypeInMethodMap(const TypeId &type);
+  static bool IsTypeInBuiltInMap(const TypeId &type);
 
   static Any GetMethodPtr(const TypeId &type, const std::string &name);
 
+  static Any GetAttrPtr(const TypeId &type, const std::string &name);
+
   const py::object &input() const { return input_; }
 
   FuncGraphPtr func_graph() const { return func_graph_; }

mindspore/ccsrc/pipeline/jit/static_analysis/prim.cc

@@ -21,7 +21,6 @@
 #include <algorithm>
 #include <limits>
 #include <mutex>
-#include <set>
 #include <string>
 #include <utility>
 
@@ -31,10 +30,8 @@
 #include "frontend/operator/prim_to_function.h"
 #include "abstract/utils.h"
 #include "utils/symbolic.h"
-#include "./common.h"
 #include "pipeline/jit/resource.h"
 #include "pipeline/jit/parse/resolve.h"
-#include "ir/tensor.h"
 #include "utils/convert_utils.h"
 #include "utils/context/ms_context.h"
 #include "pipeline/jit/parse/data_converter.h"
@@ -64,7 +61,6 @@ PrimitiveEvalImplMap &GetPrimitiveToEvalImplMap() {
     {prim::kPrimScalarToArray, {InferImplScalarToArray, true}},
     {prim::kPrimArrayToScalar, {InferImplArrayToScalar, true}},
     {prim::kPrimBroadcastShape, {InferImplBroadCastShape, true}},
-    {prim::kPrimShape, {InferImplShape, true}},
     {prim::kPrimPack, {InferImplPack, true}},
     // Structure
     {prim::kPrimMakeTuple, {InferImplMakeTuple, true}},
@@ -634,7 +630,7 @@ EvaluatorPtr InitUniformPrimEvaluator(const PrimitivePtr &primitive, PrimitiveIm
 }
 
 const int kResolveCaseUserDefineClass = 1;
-const int kResolveCaseBuildinTypeMethod = 2;
+const int kResolveCaseBuiltInType = 2;
 const int kResolveCaseFunction = 3;
 int GetResolveCase(const TypePtr &data_type) {
   MS_EXCEPTION_IF_NULL(data_type);
@@ -643,8 +639,8 @@ int GetResolveCase(const TypePtr &data_type) {
   }
 
   // try method map, if not in method map, the data_type should be External type.
-  if (pipeline::Resource::IsTypeInMethodMap(data_type->type_id())) {
-    return kResolveCaseBuildinTypeMethod;
+  if (pipeline::Resource::IsTypeInBuiltInMap(data_type->type_id())) {
+    return kResolveCaseBuiltInType;
   }
 
   return kResolveCaseFunction;
@@ -674,8 +670,10 @@ inline void AddToManager(const AnalysisEnginePtr &engine, const FuncGraphPtr fun
   manager->AddFuncGraph(func_graph);
 }
 
-EvalResultPtr StaticGetterInferred(const ValuePtr &value, const ConfigPtr &data_conf,
-                                   const AnfNodeConfigPtr &old_conf) {
+enum REQUIRE_TYPE { ATTR, METHOD };
+
+EvalResultPtr StaticGetterInferred(const ValuePtr &value, const ConfigPtr &data_conf, const AnfNodeConfigPtr &old_conf,
+                                   REQUIRE_TYPE require_type = REQUIRE_TYPE::METHOD) {
   MS_EXCEPTION_IF_NULL(old_conf);
 
   AbstractBasePtr abs_ptr = ToAbstract(value, AnalysisContext::DummyContext(), old_conf);
@@ -701,6 +699,9 @@ EvalResultPtr StaticGetterInferred(const ValuePtr &value, const ConfigPtr &data_
   MS_EXCEPTION_IF_NULL(old_conf);
   FuncGraphPtr func_graph = old_conf->node()->func_graph();
   CNodePtr new_cnode = func_graph->NewCNode(input);
+  if (require_type == REQUIRE_TYPE::ATTR) {
+    new_cnode = func_graph->NewCNode({new_cnode});
+  }
   AnalysisEnginePtr eng = old_conf->engine();
   AnfNodeConfigPtr fn_conf = eng->MakeConfig(new_cnode, old_conf->context());
   return eng->ForwardConfig(old_conf, fn_conf);
@@ -781,9 +782,9 @@ EvalResultPtr GetEvaluatedValueForClassAttrOrMethod(const AnalysisEnginePtr &eng
   return StaticGetterInferred(converted_v, data_conf, out_conf);
 }
 
-EvalResultPtr GetEvaluatedValueForBuiltinTypeMethod(const AnalysisEnginePtr &engine, const ValuePtr &item_v,
-                                                    const TypePtr &data_type, const ConfigPtr &data_conf,
-                                                    const AnfNodeConfigPtr &out_conf) {
+EvalResultPtr GetEvaluatedValueForBuiltinTypeAttrOrMethod(const AnalysisEnginePtr &engine, const ValuePtr &item_v,
+                                                          const TypePtr &data_type, const ConfigPtr &data_conf,
+                                                          const AnfNodeConfigPtr &out_conf) {
   MS_EXCEPTION_IF_NULL(item_v);
   MS_EXCEPTION_IF_NULL(data_type);
   // The method maybe a Primitive or Composite
@@ -792,22 +793,29 @@ EvalResultPtr GetEvaluatedValueForBuiltinTypeMethod(const AnalysisEnginePtr &eng
   }
 
   std::string item_name = item_v->cast<StringImmPtr>()->value();
-  Any method = pipeline::Resource::GetMethodPtr(data_type->type_id(), item_name);
-  if (method.empty()) {
-    MS_LOG(EXCEPTION) << "Object type: " << data_type->ToString() << " has no method: " << item_name;
+  REQUIRE_TYPE require_type = REQUIRE_TYPE::METHOD;
+  Any require = pipeline::Resource::GetMethodPtr(data_type->type_id(), item_name);
+  if (require.empty()) {
+    require = pipeline::Resource::GetAttrPtr(data_type->type_id(), item_name);
+    if (require.empty()) {
+      MS_LOG(EXCEPTION) << "The object of type: " << data_type->ToString() << " has no method or attr: " << item_name;
+    }
+    require_type = REQUIRE_TYPE::ATTR;
   }
 
   ValuePtr converted_v = nullptr;
-  if (method.is<std::string>()) {
+  if (require.is<std::string>()) {
     // composite registered in standard_method_map go to this branch
-    converted_v = prim::GetPythonOps(method.cast<std::string>());
-    AddToManager(engine, converted_v->cast<FuncGraphPtr>());
-  } else if (method.is<PrimitivePtr>()) {
-    converted_v = method.cast<PrimitivePtr>();
+    converted_v = prim::GetPythonOps(require.cast<std::string>());
+    if (!converted_v->isa<Primitive>()) {
+      AddToManager(engine, converted_v->cast<FuncGraphPtr>());
+    }
+  } else if (require.is<PrimitivePtr>()) {
+    converted_v = require.cast<PrimitivePtr>();
   } else {
-    MS_LOG(EXCEPTION) << "Expect to get string or PrimitivePtr from method map, but got " << method.ToString();
+    MS_LOG(EXCEPTION) << "Expect to get string or PrimitivePtr from attr or method map, but got " << require.ToString();
   }
-  return StaticGetterInferred(converted_v, data_conf, out_conf);
+  return StaticGetterInferred(converted_v, data_conf, out_conf, require_type);
 }
 
 EvalResultPtr StaticGetter(const AnalysisEnginePtr &engine, const AbstractBasePtrList &args_spec_list,
@@ -831,8 +839,8 @@ EvalResultPtr StaticGetter(const AnalysisEnginePtr &engine, const AbstractBasePt
   int case_v = GetResolveCase(data_type);
   if (case_v == kResolveCaseUserDefineClass) {
     return GetEvaluatedValueForClassAttrOrMethod(engine, args_spec_list, item_value, data_conf, out_conf);
-  } else if (case_v == kResolveCaseBuildinTypeMethod) {
-    return GetEvaluatedValueForBuiltinTypeMethod(engine, item_value, data_type, data_conf, out_conf);
+  } else if (case_v == kResolveCaseBuiltInType) {
+    return GetEvaluatedValueForBuiltinTypeAttrOrMethod(engine, item_value, data_type, data_conf, out_conf);
   } else {
     return GetEvaluatedValueForNameSpaceString(engine, args_spec_list, out_conf);
   }

mindspore/ccsrc/pipeline/jit/static_analysis/prim.h

@@ -218,10 +218,6 @@ AbstractBasePtr InferImplConv2DBackpropFilter(const AnalysisEnginePtr &, const P
                                               const AbstractBasePtrList &args_spec_list);
 AbstractBasePtr InferImplBiasAddGrad(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
                                      const AbstractBasePtrList &args_spec_list);
-AbstractBasePtr InferImplGelu(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
-                              const AbstractBasePtrList &args_spec_list);
-AbstractBasePtr InferImplGeluGrad(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
-                                  const AbstractBasePtrList &args_spec_list);
 AbstractBasePtr InferImplRelu(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
                               const AbstractBasePtrList &args_spec_list);
 AbstractBasePtr InferImplFakeBprop(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
@@ -246,8 +242,6 @@ AbstractBasePtr InferImplArrayToScalar(const AnalysisEnginePtr &, const Primitiv
                                        const AbstractBasePtrList &args_spec_list);
 AbstractBasePtr InferImplBroadCastShape(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
                                         const AbstractBasePtrList &args_spec_list);
-AbstractBasePtr InferImplShape(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
-                               const AbstractBasePtrList &args_spec_list);
 AbstractBasePtr InferImplPack(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
                               const AbstractBasePtrList &args_spec_list);
 

mindspore/ops/operations/array_ops.py

@@ -22,20 +22,21 @@ import copy
 import functools
 import itertools
 import numbers
+
 import numpy as np
 
-from ..._checkparam import Validator as validator
-from ..._checkparam import Rel
-from ...common import dtype as mstype
-from ...common.tensor import Tensor
-from ...common.parameter import Parameter
-from ..operations.math_ops import _infer_shape_reduce
 from .._utils import get_concat_offset
-from ..primitive import Primitive, PrimitiveWithInfer, prim_attr_register, _run_op
-from ..._c_expression import signature_rw as sig_rw
-from ..._c_expression import signature_kind as sig_kind
+from ..operations.math_ops import _infer_shape_reduce
+from ..primitive import PrimitiveWithInfer, prim_attr_register, _run_op
 from ..._c_expression import signature_dtype as sig_dtype
+from ..._c_expression import signature_kind as sig_kind
+from ..._c_expression import signature_rw as sig_rw
 from ..._c_expression import typing
+from ..._checkparam import Rel
+from ..._checkparam import Validator as validator
+from ...common import dtype as mstype
+from ...common.parameter import Parameter
+from ...common.tensor import Tensor
 
 
 class _ScatterOp(PrimitiveWithInfer):
@@ -415,7 +416,7 @@ class Reshape(PrimitiveWithInfer):
         return out
 
 
-class Shape(Primitive):
+class Shape(PrimitiveWithInfer):
     """
     Returns the shape of input tensor.
 
@@ -436,6 +437,13 @@ class Shape(Primitive):
     def __init__(self):
         """init Shape"""
 
+    def __infer__(self, x):
+        validator.check_subclass("input_x", x['dtype'], mstype.tensor, self.name)
+        out = {'shape': (),
+               'dtype': mstype.tuple_,
+               'value': tuple(x['shape'])}
+        return out
+
 
 class Squeeze(PrimitiveWithInfer):
     """

tests/ut/cpp/operator/ops_test.cc

@@ -267,11 +267,6 @@ TEST_F(TestOps, BroadCastShapeTest) {
   ASSERT_EQ(prim->name(), kPrimBroadcastShape->name());
 }
 
-TEST_F(TestOps, ShapeTest) {
-  auto prim = std::make_shared<Primitive>("Shape");
-  ASSERT_EQ(prim->name(), kPrimShape->name());
-}
-
 TEST_F(TestOps, ArrayMapTest) {
   auto prim = std::make_shared<Primitive>("array_map");
   ASSERT_EQ(prim->name(), kPrimArrayMap->name());

tests/ut/cpp/pipeline/resource_test.cc

@@ -36,23 +36,23 @@ class TestResource : public UT::Common {
   void TearDown() {}
 };
 
-TEST_F(TestResource, test_standard_method_map) {
-  ASSERT_TRUE(true == Resource::IsTypeInMethodMap(kNumberTypeInt));
-  ASSERT_TRUE(true == Resource::IsTypeInMethodMap(kNumberTypeInt8));
-  ASSERT_TRUE(true == Resource::IsTypeInMethodMap(kNumberTypeInt16));
-  ASSERT_TRUE(true == Resource::IsTypeInMethodMap(kNumberTypeInt32));
-  ASSERT_TRUE(true == Resource::IsTypeInMethodMap(kNumberTypeInt64));
+TEST_F(TestResource, test_built_in_type_map) {
+  ASSERT_TRUE(true == Resource::IsTypeInBuiltInMap(kNumberTypeInt));
+  ASSERT_TRUE(true == Resource::IsTypeInBuiltInMap(kNumberTypeInt8));
+  ASSERT_TRUE(true == Resource::IsTypeInBuiltInMap(kNumberTypeInt16));
+  ASSERT_TRUE(true == Resource::IsTypeInBuiltInMap(kNumberTypeInt32));
+  ASSERT_TRUE(true == Resource::IsTypeInBuiltInMap(kNumberTypeInt64));
 
-  ASSERT_TRUE(true == Resource::IsTypeInMethodMap(kNumberTypeFloat));
-  ASSERT_TRUE(true == Resource::IsTypeInMethodMap(kNumberTypeFloat16));
-  ASSERT_TRUE(true == Resource::IsTypeInMethodMap(kNumberTypeFloat32));
-  ASSERT_TRUE(true == Resource::IsTypeInMethodMap(kNumberTypeFloat64));
+  ASSERT_TRUE(true == Resource::IsTypeInBuiltInMap(kNumberTypeFloat));
+  ASSERT_TRUE(true == Resource::IsTypeInBuiltInMap(kNumberTypeFloat16));
+  ASSERT_TRUE(true == Resource::IsTypeInBuiltInMap(kNumberTypeFloat32));
+  ASSERT_TRUE(true == Resource::IsTypeInBuiltInMap(kNumberTypeFloat64));
 
-  ASSERT_TRUE(true == Resource::IsTypeInMethodMap(kNumberTypeBool));
-  ASSERT_TRUE(true == Resource::IsTypeInMethodMap(kNumberTypeUInt));
-  ASSERT_TRUE(true == Resource::IsTypeInMethodMap(kObjectTypeTuple));
-  ASSERT_TRUE(true == Resource::IsTypeInMethodMap(kObjectTypeList));
-  ASSERT_TRUE(true == Resource::IsTypeInMethodMap(kObjectTypeTensorType));
+  ASSERT_TRUE(true == Resource::IsTypeInBuiltInMap(kNumberTypeBool));
+  ASSERT_TRUE(true == Resource::IsTypeInBuiltInMap(kNumberTypeUInt));
+  ASSERT_TRUE(true == Resource::IsTypeInBuiltInMap(kObjectTypeTuple));
+  ASSERT_TRUE(true == Resource::IsTypeInBuiltInMap(kObjectTypeList));
+  ASSERT_TRUE(true == Resource::IsTypeInBuiltInMap(kObjectTypeTensorType));
 
   MethodMap& map = GetMethodMap();
   for (auto& iter : map) {

tests/ut/cpp/pipeline/static_analysis/prim_test.cc

@@ -467,24 +467,6 @@ TEST_F(TestPrim, test_env_add) {
   ASSERT_TRUE(*res == *exp);
 }
 
-TEST_F(TestPrim, test_shape) {
-  PrimitivePtr shap = std::make_shared<Primitive>("Shape");
-  FuncGraphPtr func_graph = MakeFuncGraph(shap, 1);
-
-  auto a = UTPrimUtils::ArrayFloat64Of({2, 3});
-
-  AbstractBasePtrList args_spec_list = {a};
-
-  AbstractTuplePtr res = dyn_cast<AbstractTuple>(engine_->Run(func_graph, args_spec_list).inferred->abstract());
-  auto ret = res->BuildValue()->cast<ValueTuplePtr>()->value();
-
-  std::vector<ValuePtr> element_list = {MakeValue(2), MakeValue(3)};
-  ASSERT_TRUE(ret.size() == element_list.size());
-  for (int i = 0; i < element_list.size(); i++) {
-    ASSERT_TRUE(*ret[i] == *element_list[i]);
-  }
-}
-
 TEST_F(TestPrim, test_relu) {
   PrimitivePtr relu = prim::kPrimRelu;
   relu->AddAttr("T", MakeValue(static_cast<int>(kNumberTypeFloat64)));

tests/ut/python/pipeline/parse/test_dtype_and_shape_as_attr.py

@@ -0,0 +1,96 @@
+# Copyright 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.
+# ============================================================================
+""" test dtype and shape as attr"""
+import numpy as np
+import pytest
+
+import mindspore.nn as nn
+from mindspore import Tensor
+from mindspore import context
+from mindspore import dtype as mstype
+from mindspore.ops import operations as P
+
+context.set_context(mode=context.GRAPH_MODE)
+
+
+def test_dtype_and_shape_as_attr():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def construct(self, x):
+            shape = x.shape
+            dtype = x.dtype
+            return shape, dtype
+
+
+    net = Net()
+    x = Tensor(np.ones([1, 2, 3], np.int32))
+    ret = net(x)
+    assert ret == ((1, 2, 3), mstype.int32)
+
+
+def test_dtype_and_shape_as_attr_to_new_tensor():
+    class Net(nn.Cell):
+        def __init__(self, value):
+            super(Net, self).__init__()
+            self.fill = P.Fill()
+            self.value = value
+
+        def construct(self, x):
+            dtype = x.dtype
+            shape = x.shape
+            y = self.fill(dtype, shape, self.value)
+            return y
+
+
+    net = Net(2.2)
+    x = Tensor(np.ones([1, 2, 3], np.float32))
+    ret = net(x)
+    assert (ret.asnumpy() == (np.zeros([1, 2, 3], np.float32) + 2.2)).all()
+
+
+def test_type_not_have_the_attr():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def construct(self, x):
+            shape = x.shapes
+            return shape
+
+
+    net = Net()
+    x = Tensor(np.ones([1, 2, 3], np.int32))
+    with pytest.raises(RuntimeError) as ex:
+        net(x)
+    assert "The object of type: Tensor[Int32] has no method or attr: shapes" in str(ex.value)
+
+
+def test_type_not_have_the_method():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def construct(self, x):
+            shape = x.dtypes()
+            return shape
+
+
+    net = Net()
+    x = Tensor(np.ones([1, 2, 3], np.int32))
+    with pytest.raises(RuntimeError) as ex:
+        net(x)
+    assert "The object of type: Tensor[Int32] has no method or attr: dtypes" in str(ex.value)

tests/ut/python/pipeline/parse/test_super.py

@@ -20,7 +20,7 @@ import mindspore.nn as nn
 from mindspore import Tensor
 from mindspore import context
 
-context.set_context(mode=context.GRAPH_MODE, save_graphs=True)
+context.set_context(mode=context.GRAPH_MODE)
 
 
 class FatherNet(nn.Cell):
@@ -92,7 +92,6 @@ class Net(nn.Cell):
 
 def test_single_super():
     single_net = SingleSubNet(2, 3)
-    context.set_context(mode=context.GRAPH_MODE)
     x = Tensor(np.ones([1, 2, 3], np.int32))
     y = Tensor(np.ones([1, 2, 3], np.int32))
     single_net(x, y)
@@ -100,7 +99,6 @@ def test_single_super():
 
 def test_mul_super():
     mul_net = MulSubNet(2, 3, 4)
-    context.set_context(mode=context.GRAPH_MODE)
     x = Tensor(np.ones([1, 2, 3], np.int32))
     y = Tensor(np.ones([1, 2, 3], np.int32))
     mul_net(x, y)
@@ -108,7 +106,6 @@ def test_mul_super():
 
 def test_super_cell():
     net = Net(2)
-    context.set_context(mode=context.GRAPH_MODE)
     x = Tensor(np.ones([1, 2, 3], np.int32))
     y = Tensor(np.ones([1, 2, 3], np.int32))
     with pytest.raises(RuntimeError) as er:
@@ -142,7 +139,6 @@ def test_single_super_in():
             return ret_father_construct, ret_father_test, ret_father_x, ret_sub_z
 
     single_net_in = SingleSubNetIN(2, 3)
-    context.set_context(mode=context.GRAPH_MODE, save_graphs=True)
     x = Tensor(np.ones([1, 2, 3], np.int32))
     y = Tensor(np.ones([1, 2, 3], np.int32))
     single_net_in(x, y)