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a6c50a6c
编写于
7月 29, 2022
作者:
T
thunder95
提交者:
GitHub
7月 29, 2022
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电子邮件补丁
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【PaddlePaddle Hackathon 3 No.15】为 Paddle 新增 count_nonzero (#44169)
* add count_nonzero api * remove grad test
上级
05515662
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
156 addition
and
0 deletion
+156
-0
python/paddle/__init__.py
python/paddle/__init__.py
+2
-0
python/paddle/fluid/tests/unittests/test_count_nonzero_api.py
...on/paddle/fluid/tests/unittests/test_count_nonzero_api.py
+86
-0
python/paddle/tensor/__init__.py
python/paddle/tensor/__init__.py
+2
-0
python/paddle/tensor/math.py
python/paddle/tensor/math.py
+66
-0
未找到文件。
python/paddle/__init__.py
浏览文件 @
a6c50a6c
...
...
@@ -220,6 +220,7 @@ from .tensor.math import stanh # noqa: F401
from
.tensor.math
import
sum
# noqa: F401
from
.tensor.math
import
nansum
# noqa: F401
from
.tensor.math
import
nanmean
# noqa: F401
from
.tensor.math
import
count_nonzero
# noqa: F401
from
.tensor.math
import
tanh
# noqa: F401
from
.tensor.math
import
tanh_
# noqa: F401
from
.tensor.math
import
add_n
# noqa: F401
...
...
@@ -560,6 +561,7 @@ __all__ = [ # noqa
'sum'
,
'nansum'
,
'nanmean'
,
'count_nonzero'
,
'tile'
,
'greater_equal'
,
'isfinite'
,
...
...
python/paddle/fluid/tests/unittests/test_count_nonzero_api.py
0 → 100644
浏览文件 @
a6c50a6c
# 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.
# 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.
from
__future__
import
print_function
import
unittest
import
numpy
as
np
import
paddle
import
paddle.fluid
as
fluid
import
paddle.fluid.core
as
core
from
paddle.fluid
import
Program
,
program_guard
np
.
random
.
seed
(
10
)
class
TestCountNonzeroAPI
(
unittest
.
TestCase
):
# test paddle.tensor.math.count_nonzero
def
setUp
(
self
):
self
.
x_shape
=
[
2
,
3
,
4
,
5
]
self
.
x
=
np
.
random
.
uniform
(
-
1
,
1
,
self
.
x_shape
).
astype
(
np
.
float32
)
self
.
place
=
paddle
.
CUDAPlace
(
0
)
if
core
.
is_compiled_with_cuda
()
\
else
paddle
.
CPUPlace
()
def
test_api_static
(
self
):
paddle
.
enable_static
()
with
paddle
.
static
.
program_guard
(
paddle
.
static
.
Program
()):
x
=
paddle
.
fluid
.
data
(
'X'
,
self
.
x_shape
)
out1
=
paddle
.
count_nonzero
(
x
)
out2
=
paddle
.
tensor
.
count_nonzero
(
x
)
out3
=
paddle
.
tensor
.
math
.
count_nonzero
(
x
)
axis
=
np
.
arange
(
len
(
self
.
x_shape
)).
tolist
()
out4
=
paddle
.
count_nonzero
(
x
,
axis
)
out5
=
paddle
.
count_nonzero
(
x
,
tuple
(
axis
))
exe
=
paddle
.
static
.
Executor
(
self
.
place
)
res
=
exe
.
run
(
feed
=
{
'X'
:
self
.
x
},
fetch_list
=
[
out1
,
out2
,
out3
,
out4
,
out5
])
out_ref
=
np
.
count_nonzero
(
self
.
x
)
for
out
in
res
:
self
.
assertEqual
(
np
.
allclose
(
out
,
out_ref
),
True
)
def
test_api_dygraph
(
self
):
paddle
.
disable_static
(
self
.
place
)
def
test_case
(
x
,
axis
=
None
,
keepdim
=
False
):
x_tensor
=
paddle
.
to_tensor
(
x
)
out
=
paddle
.
count_nonzero
(
x_tensor
,
axis
=
axis
,
keepdim
=
keepdim
)
if
isinstance
(
axis
,
list
):
axis
=
tuple
(
axis
)
if
len
(
axis
)
==
0
:
axis
=
None
out_ref
=
np
.
count_nonzero
(
x
,
axis
,
keepdims
=
keepdim
)
self
.
assertEqual
(
np
.
allclose
(
out
.
numpy
(),
out_ref
),
True
)
test_case
(
self
.
x
)
test_case
(
self
.
x
,
None
)
test_case
(
self
.
x
,
-
1
)
test_case
(
self
.
x
,
keepdim
=
True
)
test_case
(
self
.
x
,
2
,
keepdim
=
True
)
test_case
(
self
.
x
,
[
0
,
2
])
test_case
(
self
.
x
,
(
0
,
2
))
test_case
(
self
.
x
,
(
0
,
1
,
3
))
test_case
(
self
.
x
,
[
0
,
1
,
2
,
3
])
paddle
.
enable_static
()
def
test_errors
(
self
):
paddle
.
enable_static
()
with
paddle
.
static
.
program_guard
(
paddle
.
static
.
Program
()):
x
=
paddle
.
fluid
.
data
(
'X'
,
[
10
,
12
],
'int32'
)
self
.
assertRaises
(
ValueError
,
paddle
.
count_nonzero
,
x
,
axis
=
10
)
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/tensor/__init__.py
浏览文件 @
a6c50a6c
...
...
@@ -168,6 +168,7 @@ from .math import stanh # noqa: F401
from
.math
import
sum
# noqa: F401
from
.math
import
nansum
# noqa: F401
from
.math
import
nanmean
# noqa: F401
from
.math
import
count_nonzero
# noqa: F401
from
.math
import
tanh
# noqa: F401
from
.math
import
tanh_
# noqa: F401
from
.math
import
add_n
# noqa: F401
...
...
@@ -343,6 +344,7 @@ tensor_method_func = [ #noqa
'sum'
,
'nansum'
,
'nanmean'
,
'count_nonzero'
,
'tanh'
,
'tanh_'
,
'add_n'
,
...
...
python/paddle/tensor/math.py
浏览文件 @
a6c50a6c
...
...
@@ -1315,6 +1315,72 @@ def nanmean(x, axis=None, keepdim=False, name=None):
return
paddle
.
divide
(
paddle
.
nansum
(
x
,
axis
=
axis
,
keepdim
=
keepdim
,
name
=
name
),
cnt
.
astype
(
x
.
dtype
))
def
count_nonzero
(
x
,
axis
=
None
,
keepdim
=
False
,
name
=
None
):
r
"""
Counts the number of non-zero values in the tensor x along the specified axis.
Args:
x (Tensor): An N-D Tensor, the data type is bool, float16, float32, float64, int32 or int64.
axis (int|list|tuple, optional): The dimensions along which the sum is performed. If
:attr:`None`, sum all elements of :attr:`x` and return a
Tensor with a single element, otherwise must be in the
range :math:`[-rank(x), rank(x))`. If :math:`axis[i] < 0`,
the dimension to reduce is :math:`rank + axis[i]`.
keepdim (bool, optional): Whether to reserve the reduced dimension in the
output Tensor. The result Tensor will have one fewer dimension
than the :attr:`x` unless :attr:`keepdim` is true, default
value is False.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
Tensor: Results of count operation on the specified axis of input Tensor `x`, it's data type is `'int64'`.
Examples:
.. code-block:: python
:name: count_nonzero-example
import paddle
# x is a 2-D Tensor:
x = paddle.to_tensor([[0., 1.1, 1.2], [0., 0., 1.3], [0., 0., 0.]])
out1 = paddle.count_nonzero(x)
# [3]
out2 = paddle.count_nonzero(x, axis=0)
# [0, 1, 2]
out3 = paddle.count_nonzero(x, axis=0, keepdim=True)
# [[0, 1, 2]]
out4 = paddle.count_nonzero(x, axis=1)
# [2, 1, 0]
out5 = paddle.count_nonzero(x, axis=1, keepdim=True)
#[[2],
# [1],
# [0]]
# y is a 3-D Tensor:
y = paddle.to_tensor([[[0., 1.1, 1.2], [0., 0., 1.3], [0., 0., 0.]],
[[0., 2.5, 2.6], [0., 0., 2.4], [2.1, 2.2, 2.3]]])
out6 = paddle.count_nonzero(y, axis=[1, 2])
# [3, 6]
out7 = paddle.count_nonzero(y, axis=[0, 1])
# [1, 3, 5]
"""
if
axis
is
not
None
:
if
isinstance
(
axis
,
int
):
axis
=
[
axis
]
dims
=
len
(
x
.
shape
)
for
i
in
range
(
len
(
axis
)):
if
not
isinstance
(
axis
[
i
],
int
)
or
not
(
axis
[
i
]
<
dims
and
axis
[
i
]
>=
-
dims
):
raise
ValueError
(
"Axis should be None, int, or a list, element should in range [-rank(x), rank(x))."
)
bool_tensor
=
paddle
.
cast
(
x
,
'bool'
)
int_tensor
=
paddle
.
cast
(
bool_tensor
,
'int64'
)
return
paddle
.
sum
(
int_tensor
,
axis
=
axis
,
keepdim
=
keepdim
,
name
=
name
)
@
templatedoc
(
op_type
=
"sum"
)
def
add_n
(
inputs
,
name
=
None
):
"""
...
...
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