From 30838aa698d6f3f3b0860b052f6a50ef53ac6784 Mon Sep 17 00:00:00 2001 From: David Nicolas <37790151+liyongchao911@users.noreply.github.com> Date: Tue, 26 Apr 2022 19:05:12 +0800 Subject: [PATCH] replace the numpy with paddle for the data generation in code; test=document_fix (#42259) * replace the numpy with paddle_tensor for the data generation in code example * Create manipulation.py replace name as: https://github.com/PaddlePaddle/docs/blob/develop/docs/templates/common_docs.py#L9 * for CI;test=document_fix * for CI;test=document_fix Co-authored-by: Chen Long <1300851984@qq.com> --- python/paddle/tensor/manipulation.py | 113 ++++++++++++--------------- python/paddle/tensor/math.py | 14 ++-- 2 files changed, 55 insertions(+), 72 deletions(-) diff --git a/python/paddle/tensor/manipulation.py b/python/paddle/tensor/manipulation.py index b0e0082c6d..127aa71137 100755 --- a/python/paddle/tensor/manipulation.py +++ b/python/paddle/tensor/manipulation.py @@ -45,9 +45,9 @@ def cast(x, dtype): equals the input dtype, but it's fine if you do so. Args: - x(Tensor): An input N-D Tensor with data type bool, float16, + x (Tensor): An input N-D Tensor with data type bool, float16, float32, float64, int32, int64, uint8. - dtype(np.dtype|str): Data type of the output: + dtype (np.dtype|str): Data type of the output: bool, float16, float32, float64, int8, int32, int64, uint8. Returns: @@ -601,8 +601,7 @@ def crop(x, shape=None, offsets=None, name=None): Tensor. When it is a list, each element can be an integer or a Tensor of shape: [1]. If Variable contained, it is suitable for the case that the offsets may be changed each iteration. Default: None, the offsets are 0 at each dimension. - name(str, optional): The default value is None. Normally there is no need for user to set - this property. For more information, please refer to :ref:`api_guide_Name` . + name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`. Returns: Tensor: The cropped Tensor has same data type with `x`. @@ -742,8 +741,8 @@ def fill_(x, value): This function fill the Tensor with value inplace. Args: - x(Tensor): ``x`` is the Tensor we want to filled data inplace - value(Scale): ``value`` is the value to be filled in x + x (Tensor): ``x`` is the Tensor we want to filled data inplace + value (Scale): ``value`` is the value to be filled in x Returns: x(Tensor): Tensor x filled with value inplace @@ -776,10 +775,10 @@ def zero_(x): This function fill the Tensor with zero inplace. Args: - x(Tensor): ``x`` is the Tensor we want to filled with zero inplace + x (Tensor): ``x`` is the Tensor we want to filled with zero inplace Returns: - x(Tensor): Tensor x filled with zero inplace + x (Tensor): Tensor x filled with zero inplace Examples: .. code-block:: python @@ -798,19 +797,21 @@ def zero_(x): @dygraph_only def fill_diagonal_(x, value, offset=0, wrap=False, name=None): """ - **Notes**: - **This API is ONLY available in Dygraph mode** + Note: + This API is ONLY available in Dygraph mode. + This function fill the value into the x Tensor's diagonal inplace. + Args: x(Tensor): ``x`` is the original Tensor value(Scale): ``value`` is the value to filled in x offset(int,optional): the offset to the main diagonal. Default: 0 (main diagonal). wrap(bool,optional): the diagonal 'wrapped' after N columns for tall matrices. name(str,optional): Name for the operation (optional, default is None) + Returns: Tensor: Tensor with diagonal filled with value. - Returns type: - dtype is same as x Tensor + Examples: .. code-block:: python import paddle @@ -874,25 +875,22 @@ def _fill_diagonal_tensor_impl(x, y, offset=0, dim1=0, dim2=1, inplace=False): def fill_diagonal_tensor_(x, y, offset=0, dim1=0, dim2=1, name=None): """ - **Notes**: - **This API is ONLY available in Dygraph mode** + Note: + This API is ONLY available in Dygraph mode. This function fill the source Tensor y into the x Tensor's diagonal inplace. Args: - x(Tensor): ``x`` is the original Tensor - y(Tensor): ``y`` is the Tensor to filled in x - dim1(int,optional): first dimension with respect to which to fill diagonal. Default: 0. - dim2(int,optional): second dimension with respect to which to fill diagonal. Default: 1. - offset(int,optional): the offset to the main diagonal. Default: 0 (main diagonal). - name(str,optional): Name for the operation (optional, default is None) + x (Tensor): ``x`` is the original Tensor + y (Tensor): ``y`` is the Tensor to filled in x + dim1 (int,optional): first dimension with respect to which to fill diagonal. Default: 0. + dim2 (int,optional): second dimension with respect to which to fill diagonal. Default: 1. + offset (int,optional): the offset to the main diagonal. Default: 0 (main diagonal). + name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`. Returns: Tensor: Tensor with diagonal filled with y. - Returns type: - list: dtype is same as x Tensor - Examples: .. code-block:: python @@ -913,19 +911,16 @@ def fill_diagonal_tensor(x, y, offset=0, dim1=0, dim2=1, name=None): This function fill the source Tensor y into the x Tensor's diagonal. Args: - x(Tensor): ``x`` is the original Tensor - y(Tensor): ``y`` is the Tensor to filled in x - dim1(int,optional): first dimension with respect to which to fill diagonal. Default: 0. - dim2(int,optional): second dimension with respect to which to fill diagonal. Default: 1. - offset(int,optional): the offset to the main diagonal. Default: 0 (main diagonal). - name(str,optional): Name for the operation (optional, default is None) + x (Tensor): ``x`` is the original Tensor + y (Tensor): ``y`` is the Tensor to filled in x + dim1 (int,optional): first dimension with respect to which to fill diagonal. Default: 0. + dim2 (int,optional): second dimension with respect to which to fill diagonal. Default: 1. + offset (int,optional): the offset to the main diagonal. Default: 0 (main diagonal). + name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`. Returns: Tensor: Tensor with diagonal filled with y. - Returns type: - list: dtype is same as x Tensor - Examples: .. code-block:: python @@ -944,19 +939,17 @@ def fill_diagonal_tensor(x, y, offset=0, dim1=0, dim2=1, name=None): @dygraph_only def tolist(x): """ - **Notes**: - **This API is ONLY available in Dygraph mode** + Note: + This API is ONLY available in Dygraph mode. This function translate the paddle.Tensor to python list. Args: - x(Tensor): ``x`` is the Tensor we want to translate to list + x (Tensor): ``x`` is the Tensor we want to translate to list. Returns: list: A list that contain the same value of current Tensor. - Returns type: - list: dtype is same as current Tensor Examples: .. code-block:: python @@ -980,15 +973,13 @@ def concat(x, axis=0, name=None): This OP concatenates the input along the axis. Args: - x(list|tuple): ``x`` is a Tensor list or Tensor tuple which is with data type bool, float16, + x (list|tuple): ``x`` is a Tensor list or Tensor tuple which is with data type bool, float16, float32, float64, int32, int64, uint8. All the Tensors in ``x`` must have same data type. - axis(int|Tensor, optional): Specify the axis to operate on the input Tensors. + axis (int|Tensor, optional): Specify the axis to operate on the input Tensors. It's a scalar with data type int or a Tensor with shape [1] and data type int32 or int64. The effective range is [-R, R), where R is Rank(x). When ``axis < 0``, it works the same way as ``axis+R``. Default is 0. - name (str, optional): The default value is None. Normally there is no - need for user to set this property. For more information, please - refer to :ref:`api_guide_Name`. + name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`. Returns: Tensor: A Tensor with the same data type as ``x``. @@ -1097,12 +1088,10 @@ def broadcast_tensors(input, name=None): If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting`. Args: - input(list|tuple): ``input`` is a Tensor list or Tensor tuple which is with data type bool, + input (list|tuple): ``input`` is a Tensor list or Tensor tuple which is with data type bool, float16, float32, float64, int32, int64. All the Tensors in ``input`` must have same data type. Currently we only support tensors with rank no greater than 5. - - name (str, optional): The default value is None. Normally there is no need for user to set this property. - For more information, please refer to :ref:`api_guide_Name`. + name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`. Returns: list(Tensor): The list of broadcasted tensors following the same order as ``input``. @@ -1192,8 +1181,7 @@ def flip(x, axis, name=None): x (Tensor): A Tensor(or LoDTensor) with shape :math:`[N_1, N_2,..., N_k]` . The data type of the input Tensor x should be float32, float64, int32, int64, bool. axis (list|tuple|int): The axis(axes) to flip on. Negative indices for indexing from the end are accepted. - name (str, optional): The default value is None. Normally there is no need for user to set this property. - For more information, please refer to :ref:`api_guide_Name` . + name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`. Returns: Tensor: Tensor or LoDTensor calculated by flip layer. The data type is same with input x. @@ -3143,20 +3131,19 @@ def reshape(x, shape, name=None): the corresponding dimension of x. Args: - x(Tensor): An N-D Tensor. The data type is ``float32``, ``float64``, ``int32``, ``int64`` or ``bool`` - shape(list|tuple|Tensor): Define the target shape. At most one dimension of the target shape can be -1. + x (Tensor): An N-D Tensor. The data type is ``float32``, ``float64``, ``int32``, ``int64`` or ``bool`` + shape (list|tuple|Tensor): Define the target shape. At most one dimension of the target shape can be -1. The data type is ``int32`` . If ``shape`` is a list or tuple, the elements of it should be integers or Tensors with shape [1]. If ``shape`` is an Tensor, it should be an 1-D Tensor . - name(str, optional): The default value is None. Normally there is no need for user to set this property. - For more information, please refer to :ref:`api_guide_Name` . + name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`. Returns: Tensor: A reshaped Tensor with the same data type as ``x``. Examples: .. code-block:: python + :name: code-example1 - import numpy as np import paddle x = paddle.rand([2, 4, 6], dtype="float32") @@ -3170,9 +3157,9 @@ def reshape(x, shape, name=None): print(out) # the shape of out_2 is [4, 12]. - shape_tensor = paddle.to_tensor(np.array([8, 6]).astype("int32")) + shape_tensor = paddle.to_tensor([8, 6], dtype=paddle.int32) out = paddle.reshape(x, shape=shape_tensor) - print(out) + print(out.shape) # the shape is [8, 6]. # out shares data with x in dygraph mode x[0, 0, 0] = 10. @@ -4113,14 +4100,12 @@ def take_along_axis(arr, indices, axis): Examples: .. code-block:: python + :name: code-example1 import paddle - import numpy as np - x_np = np.array([[1, 2, 3], [4, 5, 6], [7,8,9]]) - index_np = np.array([[0]]) - x = paddle.to_tensor(x_np) - index = paddle.to_tensor(index_np) + x = paddle.to_tensor([[1, 2, 3], [4, 5, 6], [7,8,9]]) + index = paddle.to_tensor([[0]]) axis = 0 result = paddle.take_along_axis(x, index, axis) print(result) @@ -4180,14 +4165,12 @@ def put_along_axis(arr, indices, values, axis, reduce='assign'): Examples: .. code-block:: python + :name: code-example1 import paddle - import numpy as np - x_np = np.array([[10, 30, 20], [60, 40, 50]]) - index_np = np.array([[0]]) - x = paddle.to_tensor(x_np) - index = paddle.to_tensor(index_np) + x = paddle.to_tensor([[10, 30, 20], [60, 40, 50]]) + index = paddle.to_tensor([[0]]) value = 99 axis = 0 result = paddle.put_along_axis(x, index, value, axis) diff --git a/python/paddle/tensor/math.py b/python/paddle/tensor/math.py index 59206eca81..b7b08af9e6 100644 --- a/python/paddle/tensor/math.py +++ b/python/paddle/tensor/math.py @@ -282,22 +282,22 @@ def multiplex(inputs, index, name=None): inputs (list): The input Tensor list. The list elements are N-D Tensors of data types float32, float64, int32, int64. All input Tensor shapes should be the same and rank must be at least 2. index (Tensor): Used to select some rows in the input Tensor to construct an index of the output Tensor. It is a 2-D Tensor with data type int32 or int64 and shape [M, 1], where M is the number of input Tensors. name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`. - + Returns: Tensor: Output of multiplex OP, with data type being float32, float64, int32, int64. Examples: .. code-block:: python + :name: code-example1 import paddle - import numpy as np - img1 = np.array([[1, 2], [3, 4]]).astype(np.float32) - img2 = np.array([[5, 6], [7, 8]]).astype(np.float32) - inputs = [paddle.to_tensor(img1), paddle.to_tensor(img2)] - index = paddle.to_tensor(np.array([[1], [0]]).astype(np.int32)) + img1 = paddle.to_tensor([[1, 2], [3, 4]], dtype=paddle.float32) + img2 = paddle.to_tensor([[5, 6], [7, 8]], dtype=paddle.float32) + inputs = [img1, img2] + index = paddle.to_tensor([[1], [0]], dtype=paddle.int32) res = paddle.multiplex(inputs, index) - print(res) # [array([[5., 6.], [3., 4.]], dtype=float32)] + print(res) # Tensor([[5., 6.], [3., 4.]], dtype=float32) """ if _non_static_mode(): -- GitLab