improve interface '__bool__' for tensor

mindspore/_extends/parse/standard_method.py

@@ -17,7 +17,6 @@
 """standard_method"""
 from dataclasses import dataclass
 from mindspore.common import dtype as mstype
-from mindspore.common._register_for_tensor import tensor_operator_registry
 from ...ops import functional as F
 from ...ops import operations as P
 from ...ops.primitive import constexpr
@@ -206,13 +205,11 @@ def const_tensor_to_bool(x):
     if x is None:
         raise ValueError("Only constant tensor bool can be converted to bool")
     x = x.asnumpy()
-    if x.shape not in ((), (1,)):
-        raise ValueError("The truth value of an array with several elements is ambiguous.")
     if x.shape == ():
-        value = bool(x)
-    else:
-        value = bool(x[0])
-    return value
+        return bool(x)
+    if x.shape == (1,):
+        return bool(x[0])
+    raise ValueError("The truth value of an array with several elements is ambiguous.")
 
 
 def tensor_bool(x):
@@ -349,6 +346,3 @@ def list_append(self_, item):
 def to_array(x):
     """Implementation of `to_array`."""
     return x.__ms_to_array__()
-
-
-tensor_operator_registry.register('__bool__', tensor_bool)

mindspore/ccsrc/pipeline/jit/parse/data_converter.cc

@@ -73,7 +73,7 @@ FuncGraphPtr ConvertToBpropCut(const py::object &obj) {
 namespace {
 bool ConvertTuple(const py::object &obj, ValuePtr *const data, bool use_signature) {
   MS_LOG(DEBUG) << "Converting python tuple";
-  py::tuple tuple = obj.cast<py::tuple>();
+  auto tuple = obj.cast<py::tuple>();
   std::vector<ValuePtr> value_list;
   for (size_t it = 0; it < tuple.size(); ++it) {
     ValuePtr out = nullptr;
@@ -91,7 +91,7 @@ bool ConvertTuple(const py::object &obj, ValuePtr *const data, bool use_signatur
 bool ConvertList(const py::object &obj, ValuePtr *const data, bool use_signature) {
   MS_LOG(DEBUG) << "Converting python list";
 
-  py::list list = obj.cast<py::list>();
+  auto list = obj.cast<py::list>();
   std::vector<ValuePtr> value_list;
   for (size_t it = 0; it < list.size(); ++it) {
     ValuePtr out = nullptr;
@@ -124,7 +124,7 @@ bool ConvertCellList(const py::object &obj, ValuePtr *const data, bool use_signa
 bool ConvertDict(const py::object &obj, ValuePtr *data, bool use_signature) {
   MS_LOG(DEBUG) << "Converting python dict";
 
-  py::dict dict_values = obj.cast<py::dict>();
+  auto dict_values = obj.cast<py::dict>();
   std::vector<std::pair<std::string, ValuePtr>> key_values;
   for (auto item : dict_values) {
     if (!py::isinstance<py::str>(item.first)) {
@@ -208,7 +208,7 @@ bool ConvertMetaFuncGraph(const py::object &obj, ValuePtr *const data, bool use_
 bool ConvertSlice(const py::object &obj, ValuePtr *const data) {
   MS_LOG(DEBUG) << "Converting slice object";
 
-  py::slice slice_obj = obj.cast<py::slice>();
+  auto slice_obj = obj.cast<py::slice>();
   auto convert_func = [obj](std::string attr) -> ValuePtr {
     auto py_attr = py::getattr(obj, attr.c_str());
     if (py::isinstance<py::none>(py_attr)) {
@@ -335,7 +335,7 @@ bool ConvertData(const py::object &obj, ValuePtr *const data, bool use_signature
   } else if (py::isinstance<MetaTensor>(obj)) {
     converted = obj.cast<MetaTensorPtr>();
   } else if (py::isinstance<EnvInstance>(obj)) {
-    std::shared_ptr<EnvInstance> env = obj.cast<std::shared_ptr<EnvInstance>>();
+    auto env = obj.cast<std::shared_ptr<EnvInstance>>();
     converted = env;
   } else if (py::hasattr(obj, PYTHON_CLASS_MEMBER_NAMESPACE)) {
     converted = std::make_shared<NameSpace>(RESOLVE_NAMESPACE_NAME_CLASS_MEMBER, obj);
@@ -374,7 +374,7 @@ FuncGraphPtr ConvertToFuncGraph(const py::object &obj, const std::string &python
 
   data_converter::MakeProperNameToFuncGraph(func_graph, obj_id);
   data_converter::CacheObjectValue(obj_id, func_graph);
-  if (obj_key != "") {
+  if (!obj_key.empty()) {
     MS_LOG(DEBUG) << "Add graph:" << obj_key << ", func_graph:" << func_graph->ToString();
     data_converter::SetObjGraphValue(obj_key, func_graph);
   }
@@ -440,7 +440,7 @@ bool IsCellInstance(const py::object &obj) {
 py::object CreatePythonObject(const py::object &type, const py::tuple &params) {
   py::module mod = python_adapter::GetPyModule(PYTHON_MOD_PARSE_MODULE);
   py::object obj;
-  if (params.size() == 0) {
+  if (params.empty()) {
     obj = python_adapter::CallPyModFn(mod, PYTHON_MOD_CREATE_OBJ_INSTANCE, type);
   } else {
     obj = python_adapter::CallPyModFn(mod, PYTHON_MOD_CREATE_OBJ_INSTANCE, type, params);
@@ -499,7 +499,7 @@ ClassPtr ParseDataClass(const py::object &cls_obj) {
   ClassAttrVector attributes;
   py::dict names = python_adapter::CallPyModFn(mod, PYTHON_MOD_GET_DATACLASS_ATTRS, cls_obj);
   for (auto &item : names) {
-    TypePtr type_value = item.second.cast<TypePtr>();
+    auto type_value = item.second.cast<TypePtr>();
     MS_EXCEPTION_IF_NULL(type_value);
     MS_LOG(DEBUG) << "(Name: " << py::cast<std::string>(item.first) << ", type: " << type_value->ToString() << ")";
     attributes.push_back(std::make_pair(py::cast<std::string>(item.first), type_value));
@@ -508,8 +508,8 @@ ClassPtr ParseDataClass(const py::object &cls_obj) {
   std::unordered_map<std::string, ValuePtr> methods_map;
   py::dict methods = python_adapter::CallPyModFn(mod, PYTHON_MOD_GET_DATACLASS_METHODS, cls_obj);
   for (auto &item : methods) {
-    std::string fun_name = item.first.cast<std::string>();
-    py::object obj = py::cast<py::object>(item.second);
+    auto fun_name = item.first.cast<std::string>();
+    auto obj = py::cast<py::object>(item.second);
     std::shared_ptr<PyObjectWrapper> method_obj = std::make_shared<PyObjectWrapper>(obj, fun_name);
     methods_map[fun_name] = method_obj;
   }

mindspore/common/tensor.py

@@ -108,8 +108,12 @@ class Tensor(Tensor_):
         return out
 
     def __bool__(self):
-        out = tensor_operator_registry.get('__bool__')(self)
-        return out
+        data = self.asnumpy()
+        if data.shape == ():
+            return bool(data)
+        if data.shape == (1,):
+            return bool(data[0])
+        raise ValueError("The truth value of an array with several elements is ambiguous.")
 
     def __pos__(self):
         return self

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

@@ -35,7 +35,6 @@ def test_dtype_and_shape_as_attr():
             dtype = x.dtype
             return shape, dtype
 
-
     net = Net()
     x = Tensor(np.ones([1, 2, 3], np.int32))
     ret = net(x)
@@ -55,7 +54,6 @@ def test_dtype_and_shape_as_attr_to_new_tensor():
             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)
@@ -71,7 +69,6 @@ def test_type_not_have_the_attr():
             shape = x.shapes
             return shape
 
-
     net = Net()
     x = Tensor(np.ones([1, 2, 3], np.int32))
     with pytest.raises(RuntimeError) as ex:
@@ -88,7 +85,6 @@ def test_type_not_have_the_method():
             shape = x.dtypes()
             return shape
 
-
     net = Net()
     x = Tensor(np.ones([1, 2, 3], np.int32))
     with pytest.raises(RuntimeError) as ex: