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fc1e1b77
编写于
8月 29, 2023
作者:
张
张春乔
提交者:
GitHub
8月 29, 2023
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[xdoctest] reformat example code with google style in No. 240 (#56474)
* 240 * fix bugs * fix bugs
上级
daac3829
变更
1
显示空白变更内容
内联
并排
Showing
1 changed file
with
142 addition
and
117 deletion
+142
-117
python/paddle/incubate/asp/utils.py
python/paddle/incubate/asp/utils.py
+142
-117
未找到文件。
python/paddle/incubate/asp/utils.py
浏览文件 @
fc1e1b77
...
@@ -57,17 +57,14 @@ class CheckMethod(Enum):
...
@@ -57,17 +57,14 @@ class CheckMethod(Enum):
Examples:
Examples:
.. code-block:: python
.. code-block:: python
import numpy as np
>>> import numpy as np
from paddle.incubate.asp import CheckMethod, MaskAlgo
>>> from paddle.incubate.asp import CheckMethod, MaskAlgo
>>> print(CheckMethod.get_checking_method(MaskAlgo.MASK_1D))
CheckMethod.get_checking_method(MaskAlgo.MASK_1D)
CheckMethod.CHECK_1D
# CheckMethod.CHECK_1D
>>> print(CheckMethod.get_checking_method(MaskAlgo.MASK_2D_GREEDY))
CheckMethod.CHECK_2D
CheckMethod.get_checking_method(MaskAlgo.MASK_2D_GREEDY)
>>> print(CheckMethod.get_checking_method(MaskAlgo.MASK_2D_BEST))
# CheckMethod.CHECK_2D
CheckMethod.CHECK_2D
CheckMethod.get_checking_method(MaskAlgo.MASK_2D_BEST)
# CheckMethod.CHECK_2D
"""
"""
assert
isinstance
(
assert
isinstance
(
mask_algo
,
MaskAlgo
mask_algo
,
MaskAlgo
...
@@ -92,12 +89,14 @@ def calculate_density(x):
...
@@ -92,12 +89,14 @@ def calculate_density(x):
Examples:
Examples:
.. code-block:: python
.. code-block:: python
import paddle
>>>
import paddle
import numpy as np
>>>
import numpy as np
x = np.array([[0, 1, 3, 0],
>>> x = np.array([[0, 1, 3, 0],
[1, 1, 0, 1]])
... [1, 1, 0, 1]])
paddle.incubate.asp.calculate_density(x) # 0.625
>>> out = paddle.incubate.asp.calculate_density(x)
>>> print(out)
0.625
"""
"""
x_flattened
=
x
.
flatten
()
x_flattened
=
x
.
flatten
()
...
@@ -149,21 +148,27 @@ def check_mask_1d(mat, n, m):
...
@@ -149,21 +148,27 @@ def check_mask_1d(mat, n, m):
Examples:
Examples:
.. code-block:: python
.. code-block:: python
import numpy as np
>>> import numpy as np
import paddle.incubate.asp as sparsity
>>> import paddle.incubate.asp as sparsity
x = np.array([[0, 1, 3, 0],
>>> x = np.array([[0, 1, 3, 0],
[1, 0, 0, 1]])
... [1, 0, 0, 1]])
sparsity.check_mask_1d(x, 2, 4) # True
>>> y = sparsity.check_mask_1d(x, 2, 4)
>>> print(y)
x = np.array([[0, 1, 5, 4],
True
[1, 0, 0, 1]])
sparsity.check_mask_1d(x, 2, 4) # False
>>> x = np.array([[0, 1, 5, 4],
... [1, 0, 0, 1]])
# x would be padded to shape (2, 8)
>>> y = sparsity.check_mask_1d(x, 2, 4)
x = np.array([[0, 1, 0, 4, 6],
>>> print(y)
[1, 0, 0, 1, 7]])
False
sparsity.check_mask_1d(x, 2, 4) # True
>>> # x would be padded to shape (2, 8)
>>> x = np.array([[0, 1, 0, 4, 6],
... [1, 0, 0, 1, 7]])
>>> y = sparsity.check_mask_1d(x, 2, 4)
>>> print(y)
True
"""
"""
if
len
(
mat
.
shape
)
<=
1
:
if
len
(
mat
.
shape
)
<=
1
:
mat_flattern
,
shape
=
_reshape_1d
(
mat
.
reshape
(
1
,
mat
.
shape
[
0
]),
m
)
mat_flattern
,
shape
=
_reshape_1d
(
mat
.
reshape
(
1
,
mat
.
shape
[
0
]),
m
)
...
@@ -193,15 +198,17 @@ def get_mask_1d(mat, n, m):
...
@@ -193,15 +198,17 @@ def get_mask_1d(mat, n, m):
Examples:
Examples:
.. code-block:: python
.. code-block:: python
import numpy as np
>>> import numpy as np
import paddle.incubate.asp as sparsity
>>> import paddle.incubate.asp as sparsity
>>> mat = np.array([[0, 1, 5, 4],
mat = np.array([[0, 1, 5, 4],
... [2, 7, 3, 6]])
[2, 7, 3, 6]])
>>> mask = sparsity.get_mask_1d(mat, 2, 4)
mask = sparsity.get_mask_1d(mat, 2, 4)
>>> print(mask)
# nparray([[0, 0, 1, 1],
[[0 0 1 1]
# [0, 1, 0, 1]])
[0 1 0 1]]
sparsity.check_mask_1d(mask, 2, 4) # True
>>> y = sparsity.check_mask_1d(mask, 2, 4)
>>> print(y)
True
"""
"""
mat_flattern
,
shape
=
_reshape_1d
(
mat
,
m
)
mat_flattern
,
shape
=
_reshape_1d
(
mat
,
m
)
...
@@ -277,28 +284,34 @@ def check_mask_2d(mat, n, m):
...
@@ -277,28 +284,34 @@ def check_mask_2d(mat, n, m):
Examples:
Examples:
.. code-block:: python
.. code-block:: python
import numpy as np
>>> import numpy as np
import paddle.incubate.asp as sparsity
>>> import paddle.incubate.asp as sparsity
x = np.array([[0, 8, 9, 0],
>>> x = np.array([[0, 8, 9, 0],
[9, 0, 0, 10],
... [9, 0, 0, 10],
[5, 0, 0, 6],
... [5, 0, 0, 6],
[0, 4, 6, 0]])
... [0, 4, 6, 0]])
sparsity.check_mask_2d(x, 2, 4) # True
>>> y = sparsity.check_mask_2d(x, 2, 4)
>>> print(y)
x = np.array([[0, 8, 0, 9],
True
[9, 0, 0, 10],
[0, 5, 0, 6],
>>> x = np.array([[0, 8, 0, 9],
[0, 4, 6, 0]])
... [9, 0, 0, 10],
sparsity.check_mask_2d(x, 2, 4) # False
... [0, 5, 0, 6],
... [0, 4, 6, 0]])
# x would be padded to shape (8, 8)
>>> y = sparsity.check_mask_2d(x, 2, 4)
x = np.array([[0, 8, 0, 9],
>>> print(y)
[9, 0, 7, 0],
True
[0, 5, 0, 6],
[3, 0, 6, 0],
>>> # x would be padded to shape (8, 8)
[1, 1, 0, 1]])
>>> x = np.array([[0, 8, 0, 9],
sparsity.check_mask_2d(x, 2, 4) # True
... [9, 0, 7, 0],
... [0, 5, 0, 6],
... [3, 0, 6, 0],
... [1, 1, 0, 1]])
>>> y = sparsity.check_mask_2d(x, 2, 4)
>>> print(y)
True
"""
"""
mat_padded
,
shape
=
_reshape_2d
(
mat
,
m
)
mat_padded
,
shape
=
_reshape_2d
(
mat
,
m
)
for
sub_mat
in
mat_padded
:
for
sub_mat
in
mat_padded
:
...
@@ -328,19 +341,22 @@ def get_mask_2d_greedy(mat, n, m):
...
@@ -328,19 +341,22 @@ def get_mask_2d_greedy(mat, n, m):
Examples:
Examples:
.. code-block:: python
.. code-block:: python
import numpy as np
>>> import numpy as np
import paddle.incubate.asp as sparsity
>>> import paddle.incubate.asp as sparsity
mat = np.array([[9, 8, 3, 7],
>>> mat = np.array([[9, 8, 3, 7],
[9, 2, 1, 10],
... [9, 2, 1, 10],
[5, 1, 3, 6],
... [5, 1, 3, 6],
[2, 4, 6, 1]])
... [2, 4, 6, 1]])
mask = sparsity.get_mask_2d_greedy(mat, 2, 4)
>>> mask = sparsity.get_mask_2d_greedy(mat, 2, 4)
# nparray([[1. 1. 0. 0.]
>>> print(mask)
# [1. 0. 0. 1.]
[[1. 1. 0. 0.]
# [0. 0. 1. 1.]
[1. 0. 0. 1.]
# [0. 1. 1. 0.]])
[0. 0. 1. 1.]
sparsity.check_mask_2d(mask, 2, 4) # True
[0. 1. 1. 0.]]
>>> y = sparsity.check_mask_2d(mask, 2, 4)
>>> print(y)
True
"""
"""
mat_padded
,
shape
=
_reshape_2d
(
mat
,
m
)
mat_padded
,
shape
=
_reshape_2d
(
mat
,
m
)
mask_padded
=
np
.
zeros_like
(
mat_padded
).
reshape
(
-
1
,
m
,
m
)
mask_padded
=
np
.
zeros_like
(
mat_padded
).
reshape
(
-
1
,
m
,
m
)
...
@@ -443,17 +459,19 @@ def get_mask_2d_best(mat, n, m):
...
@@ -443,17 +459,19 @@ def get_mask_2d_best(mat, n, m):
Examples:
Examples:
.. code-block:: python
.. code-block:: python
import numpy as np
>>> import numpy as np
import paddle.incubate.asp as sparsity
>>> import paddle.incubate.asp as sparsity
mat = np.array([[2, 8, 9, 9],
>>> mat = np.array([[2, 8, 9, 9],
[9, 1, 3, 9],
... [9, 1, 3, 9],
[5, 6, 3, 9],
... [5, 6, 3, 9],
[2, 4, 6, 9]])
... [2, 4, 6, 9]])
mask_greedy = sparsity.get_mask_2d_greedy(mat, 2, 4)
>>> mask_greedy = sparsity.get_mask_2d_greedy(mat, 2, 4)
mask_best = sparsity.get_mask_2d_best(mat, 2, 4)
>>> mask_best = sparsity.get_mask_2d_best(mat, 2, 4)
print("L1 norm of `greedy` sparse matrix", np.multiply(mat, mask_greedy).sum()) # 56
>>> print("L1 norm of `greedy` sparse matrix", np.multiply(mat, mask_greedy).sum())
print("L1 norm of `best` sparse matrix", np.multiply(mat, mask_best).sum()) # 61
L1 norm of `greedy` sparse matrix 56.0
>>> print("L1 norm of `best` sparse matrix", np.multiply(mat, mask_best).sum())
L1 norm of `best` sparse matrix 61.0
"""
"""
patterns
=
_compute_valid_2d_patterns
(
n
,
m
)
patterns
=
_compute_valid_2d_patterns
(
n
,
m
)
...
@@ -492,23 +510,25 @@ def create_mask(tensor, func_name=MaskAlgo.MASK_1D, n=2, m=4):
...
@@ -492,23 +510,25 @@ def create_mask(tensor, func_name=MaskAlgo.MASK_1D, n=2, m=4):
Examples:
Examples:
.. code-block:: python
.. code-block:: python
import numpy as np
>>> import numpy as np
import paddle.incubate.asp as sparsity
>>> import paddle.incubate.asp as sparsity
tensor = np.array([[2, 8, 9, 9],
>>> tensor = np.array([[2, 8, 9, 9],
[9, 1, 3, 9],
... [9, 1, 3, 9],
[5, 6, 3, 9],
... [5, 6, 3, 9],
[2, 4, 6, 9]])
... [2, 4, 6, 9]])
mask_1d = sparsity.create_mask(tensor, func_name=sparsity.MaskAlgo.MASK_1D)
>>> mask_1d = sparsity.create_mask(tensor, func_name=sparsity.MaskAlgo.MASK_1D)
# nparray([[0 0 1 1],
>>> print(mask_1d)
# [1 0 0 1],
[[0 0 1 1]
# [0 1 0 1],
[1 0 0 1]
# [0 0 1 1]])
[0 1 0 1]
mask_2d = sparsity.create_mask(tensor, func_name=sparsity.MaskAlgo.MASK_2D_BEST)
[0 0 1 1]]
# nparray([[0 1 1 0],
>>> mask_2d = sparsity.create_mask(tensor, func_name=sparsity.MaskAlgo.MASK_2D_BEST)
# [1 0 0 1],
>>> print(mask_2d)
# [1 1 0 0],
[[0 1 1 0]
# [0 0 1 1]])
[1 0 0 1]
[1 1 0 0]
[0 0 1 1]]
"""
"""
shape
=
tensor
.
shape
shape
=
tensor
.
shape
dtype
=
tensor
.
dtype
dtype
=
tensor
.
dtype
...
@@ -561,20 +581,25 @@ def check_sparsity(tensor, func_name=CheckMethod.CHECK_1D, n=2, m=4):
...
@@ -561,20 +581,25 @@ def check_sparsity(tensor, func_name=CheckMethod.CHECK_1D, n=2, m=4):
Examples:
Examples:
.. code-block:: python
.. code-block:: python
import numpy as np
>>> import numpy as np
import paddle.incubate.asp as sparsity
>>> import paddle.incubate.asp as sparsity
tensor = np.array([[2, 8, 9, 9],
>>> tensor = np.array([[2, 8, 9, 9],
[9, 1, 3, 9],
... [9, 1, 3, 9],
[5, 6, 3, 9],
... [5, 6, 3, 9],
[2, 4, 6, 9]])
... [2, 4, 6, 9]])
mask_1d = sparsity.create_mask(tensor, func_name=sparsity.MaskAlgo.MASK_1D)
>>> mask_1d = sparsity.create_mask(tensor, func_name=sparsity.MaskAlgo.MASK_1D)
# nparray([[0 0 1 1],
>>> print(mask_1d)
# [1 0 0 1],
[[0 0 1 1]
# [0 1 0 1],
[1 0 0 1]
# [0 0 1 1]])
[0 1 0 1]
sparsity.check_sparsity(mask_1d, func_name=sparsity.CheckMethod.CHECK_1D) # True
[0 0 1 1]]
sparsity.check_sparsity(mask_1d, func_name=sparsity.CheckMethod.CHECK_2D) # False
>>> y = sparsity.check_sparsity(mask_1d, func_name=sparsity.CheckMethod.CHECK_1D)
>>> print(y)
True
>>> y = sparsity.check_sparsity(mask_1d, func_name=sparsity.CheckMethod.CHECK_2D)
>>> print(y)
True
"""
"""
shape
=
tensor
.
shape
shape
=
tensor
.
shape
t
=
tensor
.
astype
(
float
)
t
=
tensor
.
astype
(
float
)
...
...
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