未验证 提交 34f07045 编写于 作者: L Ligoml 提交者: GitHub

update docs dtype(core.VarDesc.VarType)test=document_fix (#40947)

* update docs dtype(core.VarDesc.VarType)

* fix code style, test=document_fix

fix code style, test=document_fix
Co-authored-by: NChen Long <1300851984@qq.com>
上级 324b6b71
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
......@@ -11,20 +11,6 @@
# 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.
# Copyright(c) 2019 PaddlePaddle Authors.All Rights Reserved.
#
# 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.
"""
Contrib layers just related to the neural network.
"""
......@@ -1050,7 +1036,7 @@ def sparse_embedding(input,
vectors can be loaded with the :attr:`param_attr` parameter. The local word vector needs
to be transformed into numpy format, and the shape of local word vector should be consistent
with :attr:`size` .
dtype(str|core.VarDesc.VarType): It refers to the data type of output Tensor. It must be float32 or
dtype(str): It refers to the data type of output Tensor. It must be float32 or
float64. Default: float32.
Returns:
......
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
......@@ -214,7 +214,7 @@ def embedding(input,
user-defined or pre-trained word vectors can be loaded with the :attr:`param_attr` parameter.
The local word vector needs to be transformed into numpy format, and the shape of local word
vector should be consistent with :attr:`size` .
dtype(str|core.VarDesc.VarType): It refers to the data type of output Tensor.
dtype(str): It refers to the data type of output Tensor.
It must be float32 or float64. Default: float32.
Returns:
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
......@@ -229,7 +229,7 @@ def cast(x, dtype):
Args:
x(Tensor): An input N-D Tensor with data type bool, float16,
float32, float64, int32, int64, uint8.
dtype(np.dtype|core.VarDesc.VarType|str): Data type of the output:
dtype(np.dtype|str): Data type of the output:
bool, float16, float32, float64, int8, int32, int64, uint8.
Returns:
......
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
......@@ -512,7 +512,7 @@ def arange(start=0, end=None, step=1, dtype=None, name=None):
it is the istance between two adjacent values, out[i+1] - out[i].
If ``step`` is a Tensor, it is a 1-D Tensor with shape [1], with
data type int32, int64, float32, float64. Default is 1.
dtype(str|np.dtype|core.VarDesc.VarType, optional): The data type of the
dtype(str|np.dtype, optional): The data type of the
output tensor. Supported data types: int32, int64, float32, float64.
If ``dytpe`` is None, the data type is float32. Default is None.
name(str, optional): The default value is None. Normally there is no
......
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