!49135 算子ScalarToTensor针对bool类型的变量，动静行为不一致，问题修正

Merge pull request !49135 from tangdezhi_123/master

docs/api/api_python/ops/mindspore.ops.func_scalar_to_tensor.rst

@@ -6,11 +6,11 @@ mindspore.ops.scalar_to_tensor
     将Scalar转换为指定数据类型的Tensor。
 
     参数：
-        - **input_x** (Union[int, float]) - 输入是Scalar。只能是常量值。
+        - **input_x** (Union[bool, int, float]) - 输入是Scalar。只能是常量值。
         - **dtype** (mindspore.dtype) - 指定输出的数据类型。只能是常量值。默认值：mindspore.float32。
 
     返回：
         Tensor，零维Tensor，其值和输入一致。
 
     异常：
-        - **TypeError** - `input_x` 既不是int也不是float。
+        - **TypeError** - `input_x` 既不是bool, 也不是int，float。

mindspore/python/mindspore/ops/function/array_func.py

@@ -4702,7 +4702,7 @@ def scalar_to_tensor(input_x, dtype=mstype.float32):
     Converts a scalar to a `Tensor`, and converts the data type to the specified type.
 
     Args:
-        input_x (Union[int, float]): The input is a scalar. Only constant value is allowed.
+        input_x (Union[bool, int, float]): The input is a scalar. Only constant value is allowed.
         dtype (mindspore.dtype): The target data type. Default: mindspore.float32. Only
             constant value is allowed.
 
@@ -4710,7 +4710,7 @@ def scalar_to_tensor(input_x, dtype=mstype.float32):
         Tensor. 0-D Tensor and the content is the input.
 
     Raises:
-        TypeError: If `input_x` is neither int nor float.
+        TypeError: If `input_x` is neither bool nor int nor float.
 
     Supported Platforms:
         ``Ascend`` ``GPU`` ``CPU``

mindspore/python/mindspore/ops/operations/array_ops.py

@@ -1762,7 +1762,7 @@ class ScalarToTensor(PrimitiveWithInfer):
         self.init_prim_io_names(inputs=['input_scalar', 'dtype'], outputs=['output_data'])
 
     def __call__(self, x, dtype=mstype.float32):
-        validator.check_value_type("x", x, [int, float], self.name)
+        validator.check_value_type("x", x, [bool, int, float], self.name)
         validator.check_subclass("dtype", dtype, mstype.number, self.name)
         data_type = mstype.dtype_to_nptype(dtype)
         return Tensor(np.array(x, data_type))