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体验新版 GitCode,发现更多精彩内容 >>
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52a34649
编写于
11月 03, 2022
作者:
J
JYChen
提交者:
GitHub
11月 03, 2022
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差异文件
remove paddle.fluid.layers.reduce_prod (#47525)
上级
30c7758f
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
2 addition
and
98 deletion
+2
-98
python/paddle/fluid/layers/distributions.py
python/paddle/fluid/layers/distributions.py
+2
-1
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+0
-92
python/paddle/fluid/tests/unittests/ipu/test_reduce_x_op_ipu.py
.../paddle/fluid/tests/unittests/ipu/test_reduce_x_op_ipu.py
+0
-5
未找到文件。
python/paddle/fluid/layers/distributions.py
浏览文件 @
52a34649
...
@@ -19,6 +19,7 @@ from . import nn
...
@@ -19,6 +19,7 @@ from . import nn
import
math
import
math
import
numpy
as
np
import
numpy
as
np
import
warnings
import
warnings
import
paddle
from
..data_feeder
import
(
from
..data_feeder
import
(
convert_dtype
,
convert_dtype
,
...
@@ -660,7 +661,7 @@ class MultivariateNormalDiag(Distribution):
...
@@ -660,7 +661,7 @@ class MultivariateNormalDiag(Distribution):
one_diag
=
tensor
.
diag
(
one_diag
=
tensor
.
diag
(
tensor
.
ones
(
shape
=
[
batch_shape
[
0
]],
dtype
=
self
.
loc
.
dtype
)
tensor
.
ones
(
shape
=
[
batch_shape
[
0
]],
dtype
=
self
.
loc
.
dtype
)
)
)
det_diag
=
nn
.
reduce_
prod
(
value
+
one_all
-
one_diag
)
det_diag
=
paddle
.
prod
(
value
+
one_all
-
one_diag
)
return
det_diag
return
det_diag
...
...
python/paddle/fluid/layers/nn.py
100755 → 100644
浏览文件 @
52a34649
...
@@ -86,7 +86,6 @@ __all__ = [
...
@@ -86,7 +86,6 @@ __all__ = [
'reduce_mean',
'reduce_mean',
'reduce_max',
'reduce_max',
'reduce_min',
'reduce_min',
'reduce_prod',
'reduce_all',
'reduce_all',
'reduce_any',
'reduce_any',
'dropout',
'dropout',
...
@@ -5323,97 +5322,6 @@ def reduce_min(input, dim=None, keep_dim=False, name=None):
...
@@ -5323,97 +5322,6 @@ def reduce_min(input, dim=None, keep_dim=False, name=None):
return out
return out
def reduce_prod(input, dim=None, keep_dim=False, name=None):
"""
Computes the product of tensor elements over the given dimension.
Args:
input (Variable): The input variable which is a Tensor, the data type is float32,
float64, int32, int64.
dim (int|list|tuple, optional): The dimensions along which the product is performed. If
:attr:`None`, multiply all elements of :attr:`input` and return a
Tensor variable with a single element, otherwise must be in the
range :math:`[-rank(input), rank(input))`. If :math:`dim[i] < 0`,
the dimension to reduce is :math:`rank + dim[i]`.
keep_dim (bool, optional): Whether to reserve the reduced dimension in the
output Tensor. The result tensor will have one fewer dimension
than the :attr:`input` unless :attr:`keep_dim` is true, default
value is False.
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`
Returns:
Variable: Tensor, result of product on the specified dim of input tensor,
it's data type is the same as input's Tensor.
Examples:
.. code-block:: python
import paddle.fluid as fluid
import paddle
paddle.enable_static()
# x is a Tensor variable with following elements:
# [[0.2, 0.3, 0.5, 0.9]
# [0.1, 0.2, 0.6, 0.7]]
# Each example is followed by the corresponding output tensor.
x = fluid.data(name='x', shape=[2, 4], dtype='float32')
fluid.layers.reduce_prod(x) # [0.0002268]
fluid.layers.reduce_prod(x, dim=0) # [0.02, 0.06, 0.3, 0.63]
fluid.layers.reduce_prod(x, dim=-1) # [0.027, 0.0084]
fluid.layers.reduce_prod(x, dim=1,
keep_dim=True) # [[0.027], [0.0084]]
# y is a Tensor variable with shape [2, 2, 2] and elements as below:
# [[[1.0, 2.0], [3.0, 4.0]],
# [[5.0, 6.0], [7.0, 8.0]]]
# Each example is followed by the corresponding output tensor.
y = fluid.data(name='y', shape=[2, 2, 2], dtype='float32')
fluid.layers.reduce_prod(y, dim=[1, 2]) # [24.0, 1680.0]
fluid.layers.reduce_prod(y, dim=[0, 1]) # [105.0, 384.0]
"""
if dim is not None and not isinstance(dim, list):
if isinstance(dim, tuple):
dim = list(dim)
elif isinstance(dim, int):
dim = [dim]
else:
raise TypeError(
"The type of axis must be int, list or tuple, but received {}".format(
type(dim)
)
)
if in_dygraph_mode():
return _C_ops.prod(
input,
dim if dim is not None and dim != [] else [0],
keep_dim,
True
if dim is None or dim == [] or len(dim) == len(input.shape)
else False,
)
helper = LayerHelper('reduce_prod', **locals())
check_variable_and_dtype(
input, 'input', ['float32', 'float64', 'int32', 'int64'], 'reduce_prod'
)
out = helper.create_variable_for_type_inference(dtype=helper.input_dtype())
helper.append_op(
type='reduce_prod',
inputs={'X': input},
outputs={'Out': out},
attrs={
'dim': dim if dim is not None and dim != [] else [0],
'keep_dim': keep_dim,
'reduce_all': True
if dim is None or dim == [] or len(dim) == len(input.shape)
else False,
},
)
return out
def reduce_all(input, dim=None, keep_dim=False, name=None):
def reduce_all(input, dim=None, keep_dim=False, name=None):
"""
"""
...
...
python/paddle/fluid/tests/unittests/ipu/test_reduce_x_op_ipu.py
浏览文件 @
52a34649
...
@@ -131,11 +131,6 @@ class TestMin(TestMean):
...
@@ -131,11 +131,6 @@ class TestMin(TestMean):
self
.
op
=
paddle
.
fluid
.
layers
.
reduce_min
self
.
op
=
paddle
.
fluid
.
layers
.
reduce_min
class
TestProd
(
TestMean
):
def
set_test_op
(
self
):
self
.
op
=
paddle
.
fluid
.
layers
.
reduce_prod
class
TestSum
(
TestMean
):
class
TestSum
(
TestMean
):
def
set_test_op
(
self
):
def
set_test_op
(
self
):
self
.
op
=
paddle
.
fluid
.
layers
.
reduce_sum
self
.
op
=
paddle
.
fluid
.
layers
.
reduce_sum
...
...
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