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fix doc of data,matmul,dot,cholesky,scatter,divide,remainder,inverse,sign (#28665)

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musl/disable_test_yolov3_temporarily
ShenLiang 5 years ago committed by GitHub
parent 29b5050726
commit bb5f8e3575
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GPG Key ID: 4AEE18F83AFDEB23
5 changed files with 16 additions and 22 deletions
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3
python/paddle/fluid/layers/nn.py
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@ -8545,7 +8545,8 @@ def scatter_nd_add(ref, index, updates, name=None):
.. code-block:: python
import paddle.fluid as fluid
import paddle
paddle.enable_static()
ref = fluid.data(name='ref', shape=[3, 5, 9, 10], dtype='float32')
index = fluid.data(name='index', shape=[3, 2], dtype='int32')
updates = fluid.data(name='update', shape=[3, 9, 10], dtype='float32')

1
python/paddle/static/input.py
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@ -57,6 +57,7 @@ def data(name, shape, dtype=None, lod_level=0):
import numpy as np
import paddle
paddle.enable_static()
# Creates a variable with fixed size [3, 2, 1]
# User can only feed data of the same shape to x

13
python/paddle/tensor/linalg.py
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@ -96,7 +96,6 @@ def matmul(x, y, transpose_x=False, transpose_y=False, name=None):
import paddle
import numpy as np
paddle.disable_static()
# vector * vector
x_data = np.random.random([10]).astype(np.float32)
y_data = np.random.random([10]).astype(np.float32)
@ -563,7 +562,7 @@ def dot(x, y, name=None):
name(str, optional): Name of the output. Default is None. It's used to print debug info for developers. Details: :ref:`api_guide_Name`
Returns:
Variable: the calculated result Tensor.
Tensor: the calculated result Tensor.
Examples:
@ -572,13 +571,12 @@ def dot(x, y, name=None):
import paddle
import numpy as np
paddle.disable_static()
x_data = np.random.uniform(0.1, 1, [10]).astype(np.float32)
y_data = np.random.uniform(1, 3, [10]).astype(np.float32)
x = paddle.to_tensor(x_data)
y = paddle.to_tensor(y_data)
z = paddle.dot(x, y)
print(z.numpy())
print(z)
"""
op_type = 'dot'
@ -750,7 +748,7 @@ def cholesky(x, upper=False, name=None):
:math:`L` is lower-triangular.
Args:
x (Variable): The input tensor. Its shape should be `[*, M, M]`,
x (Tensor): The input tensor. Its shape should be `[*, M, M]`,
where * is zero or more batch dimensions, and matrices on the
inner-most 2 dimensions all should be symmetric positive-definite.
Its data type should be float32 or float64.
@ -758,7 +756,7 @@ def cholesky(x, upper=False, name=None):
triangular matrices. Default: False.
Returns:
Variable: A Tensor with same shape and data type as `x`. It represents \
Tensor: A Tensor with same shape and data type as `x`. It represents \
triangular matrices generated by Cholesky decomposition.
Examples:
@ -767,13 +765,12 @@ def cholesky(x, upper=False, name=None):
import paddle
import numpy as np
paddle.disable_static()
a = np.random.rand(3, 3)
a_t = np.transpose(a, [1, 0])
x_data = np.matmul(a, a_t) + 1e-03
x = paddle.to_tensor(x_data)
out = paddle.cholesky(x, upper=False)
print(out.numpy())
print(out)
# [[1.190523 0. 0. ]
# [0.9906703 0.27676893 0. ]
# [1.25450498 0.05600871 0.06400121]]

2
python/paddle/tensor/manipulation.py
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@ -862,6 +862,7 @@ def scatter(x, index, updates, overwrite=True, name=None):
Output is obtained by updating the input on selected indices based on updates.
.. code-block:: python
import numpy as np
#input:
x = np.array([[1, 1], [2, 2], [3, 3]])
@ -902,7 +903,6 @@ def scatter(x, index, updates, overwrite=True, name=None):
.. code-block:: python
import paddle
paddle.disable_static()
x = paddle.to_tensor([[1, 1], [2, 2], [3, 3]], dtype='float32')
index = paddle.to_tensor([2, 1, 0, 1], dtype='int64')

19
python/paddle/tensor/math.py
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@ -312,12 +312,10 @@ def divide(x, y, name=None):
import paddle
paddle.disable_static()
x = paddle.to_tensor([2, 3, 4], dtype='float64')
y = paddle.to_tensor([1, 5, 2], dtype='float64')
z = paddle.divide(x, y)
print(z.numpy()) # [2., 0.6, 2.]
print(z) # [2., 0.6, 2.]
"""
op_type = 'elementwise_div'
@ -354,12 +352,10 @@ def floor_divide(x, y, name=None):
import paddle
paddle.disable_static()
x = paddle.to_tensor([2, 3, 8, 7])
y = paddle.to_tensor([1, 5, 3, 3])
z = paddle.floor_divide(x, y)
print(z.numpy()) # [2, 0, 2, 2]
print(z) # [2, 0, 2, 2]
"""
op_type = 'elementwise_floordiv'
@ -376,10 +372,11 @@ def remainder(x, y, name=None):
Mod two tensors element-wise. The equation is:
.. math::
out = x \% y
**Note**:
``paddle.mod`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
``paddle.remainder`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
Args:
x (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
@ -397,7 +394,7 @@ def remainder(x, y, name=None):
x = paddle.to_tensor([2, 3, 8, 7])
y = paddle.to_tensor([1, 5, 3, 3])
z = paddle.mod(x, y)
z = paddle.remainder(x, y)
print(z) # [0, 3, 2, 1]
"""
@ -1037,7 +1034,7 @@ def inverse(x, name=None):
(2-D Tensor) or batches of square matrices.
Args:
x (Variable): The input tensor. The last two
x (Tensor): The input tensor. The last two
dimensions should be equal. When the number of dimensions is
greater than 2, it is treated as batches of square matrix. The data
type can be float32 and float64.
@ -1046,14 +1043,13 @@ def inverse(x, name=None):
please refer to :ref:`api_guide_Name`
Returns:
Variable: A Tensor holds the inverse of x. The shape and data type
Tensor: A Tensor holds the inverse of x. The shape and data type
is the same as x.
Examples:
.. code-block:: python
import paddle
paddle.disable_static()
mat = paddle.to_tensor([[2, 0], [0, 2]], dtype='float32')
inv = paddle.inverse(mat)
@ -1915,7 +1911,6 @@ def sign(x, name=None):
import paddle
paddle.disable_static()
x = paddle.to_tensor([3.0, 0.0, -2.0, 1.7], dtype='float32')
out = paddle.sign(x=x)
print(out) # [1.0, 0.0, -1.0, 1.0]

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