!47993 fix api bug

Merge pull request !47993 from 于振华/fix_api_bug_230117

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

@@ -7,11 +7,14 @@ mindspore.ops.full
 
     参数：
         - **size** (Union(tuple[int], list[int])) - 指定输出Tensor的shape。
-        - **fill_value** (number.Number) - 用来填充输出Tensor的值。
-        - **dtype** (mindspore.dtype) - 指定输出Tensor的数据类型。数据类型只支持 `bool_ <https://www.mindspore.cn/docs/zh-CN/master/api_python/mindspore/mindspore.dtype.html#mindspore.dtype>`_ 和 `number <https://www.mindspore.cn/docs/zh-CN/master/api_python/mindspore/mindspore.dtype.html#mindspore.dtype>`_ 。
+        - **fill_value** (number.Number) - 用来填充输出Tensor的值。当前不支持复数类型。
+
+    关键字参数：
+        - **dtype** (mindspore.dtype) - 指定输出Tensor的数据类型。数据类型只支持 `bool_` 和 `number` ，更多细节详见 :class:`mindspore.dtype` 。默认值：None。
+
     返回：
         Tensor。
 
     异常：
         - **TypeError** - `size` 不是元组。
-        - **TypeError** - `size` 中包含小于0的成员。
+        - **ValueError** - `size` 中包含小于0的成员。

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

@@ -7,7 +7,7 @@ mindspore.ops.full_like
 
     参数：
         - **x** (Tensor) - `x` 的shape决定输出Tensor的shape。
-        - **fill_value** (number.Number) - 用来填充输出Tensor的值。
+        - **fill_value** (number.Number) - 用来填充输出Tensor的值。当前不支持复数类型。
 
     关键字参数：
         - **dtype** (mindspore.dtype, 可选) - 指定输出Tensor的数据类型。数据类型只支持 `bool_` 和 `number` ，更多细节详见 :class:`mindspore.dtype` 。默认值：None。

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

@@ -373,7 +373,7 @@ def hamming_window(window_length, periodic=True, alpha=0.54, beta=0.46, *, dtype
     if window_length <= 1:
         return Tensor(np.ones(window_length))
     if dtype is not None and dtype not in mstype.float_type:
-        raise TypeError(f"For array function 'hamming_window', 'dtype' must be floating pont dtypes, but got {dtype}.")
+        raise TypeError(f"For array function 'hamming_window', 'dtype' must be floating point dtypes, but got {dtype}.")
 
     if periodic:
         window_length += 1
@@ -638,7 +638,7 @@ def one_hot(indices, depth, on_value, off_value, axis=-1):
     return onehot(indices, depth, on_value, off_value)
 
 
-def fill(type, shape, value):
+def fill(type, shape, value):  # pylint: disable=redefined-outer-name
     """
     Create a Tensor of the specified shape and fill it with the specified value.
 
@@ -724,17 +724,18 @@ def full(size, fill_value, *, dtype=None): # pylint: disable=redefined-outer-nam
 
     Args:
         size (Union(tuple[int], list[int])): The specified shape of output tensor.
-        fill_value (number.Number): Value to fill the returned tensor.
-        dtype (mindspore.dtype): The specified type of output tensor. The data type only supports
-            `bool_ <https://www.mindspore.cn/docs/en/master/api_python/mindspore.html#mindspore.dtype>`_ and
-            `number <https://www.mindspore.cn/docs/en/master/api_python/mindspore.html#mindspore.dtype>`_ .
+        fill_value (number.Number): Value to fill the returned tensor. Complex numbers are not supported for now.
+
+    Keyword Args:
+        dtype (mindspore.dtype): The specified type of output tensor. `bool_` and `number` are supported, for details,
+            please refer to :class:`mindspore.dtype` . Default: None.
 
     Returns:
         Tensor.
 
     Raises:
         TypeError: If `size` is not a tuple or list.
-        TypeError: The element in `size` is less than 0.
+        ValueError: The element in `size` is less than 0.
 
     Supported Platforms:
         ``Ascend`` ``GPU`` ``CPU``
@@ -768,11 +769,11 @@ def full_like(x, fill_value, *, dtype=None):
 
     Args:
         x (Tensor): The shape of `x` will determine shape of the output Tensor.
-        fill_value (number.Number): Value to fill the returned Tensor.
+        fill_value (number.Number): Value to fill the returned Tensor. Complex numbers are not supported for now.
 
     Keyword Args:
-        dtype (mindspore.dtype, optional): The specified type of output tensor. The data type only supports
-            `bool_` and `number` , for details, please refer to :class:`mindspore.dtype` . Default: None.
+        dtype (mindspore.dtype, optional): The specified type of output tensor. `bool_` and `number` are supported,
+            for details, please refer to :class:`mindspore.dtype` . Default: None.
 
     Returns:
         Tensor.
@@ -860,8 +861,9 @@ def chunk(x, chunks, axis=0):
         size1 = _tuple_setitem(arr_shape, axis, length1)
         start2 = _tuple_setitem(start1, axis, length1)
         size2 = _tuple_setitem(arr_shape, axis, length2)
-        res = P.Split(axis, true_chunks)(tensor_slice(x, start1, size1)) + \
-              P.Split(axis, 1)(tensor_slice(x, start2, size2))
+        res = P.Split(axis, true_chunks)(tensor_slice(x, start1, size1))
+        if length2:
+            res += P.Split(axis, 1)(tensor_slice(x, start2, size2))
     return res
 
 

mindspore/python/mindspore/ops/function/nn_func.py

@@ -3599,8 +3599,6 @@ def cosine_embedding_loss(input1, input2, target, margin=0.0, reduction="mean"):
     if margin_f > 1.0 or margin_f < -1.0:
         raise ValueError(f"For ops.cosine_embedding_loss, the value of 'margin' should be in [-1, 1],"
                          f"but got {margin_f}.")
-    # if target > 0, 1-cosine(input1, input2)
-    # else, max(0, cosine(input1, input2)-margin)
     prod_sum = _get_cache_prim(P.ReduceSum)()(input1 * input2, (1,))
     square1 = _get_cache_prim(P.ReduceSum)()(ops.square(input1), (1,))
     square2 = _get_cache_prim(P.ReduceSum)()(ops.square(input2), (1,))