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6ea8bfc6
编写于
11月 23, 2022
作者:
H
heyanru
提交者:
GitHub
11月 23, 2022
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差异文件
[Fluid Clean] Remove paddle.fluid.layers.nn.reduce_max/min (#48236)
上级
baa1f663
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
13 addition
and
159 deletion
+13
-159
python/paddle/fluid/layers/distributions.py
python/paddle/fluid/layers/distributions.py
+4
-4
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+1
-147
python/paddle/fluid/tests/unittests/dygraph_to_static/test_sentiment.py
...fluid/tests/unittests/dygraph_to_static/test_sentiment.py
+3
-3
python/paddle/fluid/tests/unittests/dygraph_to_static/test_tsm.py
...addle/fluid/tests/unittests/dygraph_to_static/test_tsm.py
+1
-1
python/paddle/fluid/tests/unittests/ipu/test_reduce_x_op_ipu.py
.../paddle/fluid/tests/unittests/ipu/test_reduce_x_op_ipu.py
+2
-2
python/paddle/fluid/tests/unittests/test_assert_op.py
python/paddle/fluid/tests/unittests/test_assert_op.py
+2
-2
未找到文件。
python/paddle/fluid/layers/distributions.py
浏览文件 @
6ea8bfc6
...
...
@@ -530,9 +530,9 @@ class Categorical(Distribution):
"""
check_type
(
other
,
'other'
,
Categorical
,
'kl_divergence'
)
logits
=
self
.
logits
-
nn
.
reduce_max
(
self
.
logits
,
dim
=-
1
,
keep_
dim
=
True
)
other_logits
=
other
.
logits
-
nn
.
reduce_
max
(
other
.
logits
,
dim
=-
1
,
keep_
dim
=
True
logits
=
self
.
logits
-
paddle
.
max
(
self
.
logits
,
axis
=-
1
,
keep
dim
=
True
)
other_logits
=
other
.
logits
-
paddle
.
max
(
other
.
logits
,
axis
=-
1
,
keep
dim
=
True
)
e_logits
=
paddle
.
exp
(
logits
)
other_e_logits
=
paddle
.
exp
(
other_logits
)
...
...
@@ -554,7 +554,7 @@ class Categorical(Distribution):
Variable: Shannon entropy of Categorical distribution. The data type is float32.
"""
logits
=
self
.
logits
-
nn
.
reduce_max
(
self
.
logits
,
dim
=-
1
,
keep_
dim
=
True
)
logits
=
self
.
logits
-
paddle
.
max
(
self
.
logits
,
axis
=-
1
,
keep
dim
=
True
)
e_logits
=
paddle
.
exp
(
logits
)
z
=
nn
.
reduce_sum
(
e_logits
,
dim
=-
1
,
keep_dim
=
True
)
prob
=
e_logits
/
z
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
6ea8bfc6
...
...
@@ -79,8 +79,6 @@ __all__ = [
'data_norm'
,
'reduce_sum'
,
'reduce_mean'
,
'reduce_max'
,
'reduce_min'
,
'reduce_all'
,
'reduce_any'
,
'dropout'
,
...
...
@@ -190,7 +188,7 @@ OP_NAMEMAPPING = {
def
_get_reduce_dim
(
dim
,
input
):
"""
Internal function for reduce_sum, reduce_mean, reduce_
max, reduce_min, reduce_
prod.
Internal function for reduce_sum, reduce_mean, reduce_prod.
It computes the attribute reduce_all value based on axis.
"""
if
dim
is
not
None
and
not
isinstance
(
dim
,
list
):
...
...
@@ -3938,150 +3936,6 @@ def reduce_mean(input, dim=None, keep_dim=False, name=None):
return
paddle
.
mean
(
x
=
input
,
axis
=
dim
,
keepdim
=
keep_dim
,
name
=
name
)
def
reduce_max
(
input
,
dim
=
None
,
keep_dim
=
False
,
name
=
None
):
"""
Computes the maximum 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 (list|int, optional): The dimension along which the maximum is computed.
If :attr:`None`, compute the maximum over 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, results of maximum 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_max(x) # [0.9]
fluid.layers.reduce_max(x, dim=0) # [0.2, 0.3, 0.6, 0.9]
fluid.layers.reduce_max(x, dim=-1) # [0.9, 0.7]
fluid.layers.reduce_max(x, dim=1, keep_dim=True) # [[0.9], [0.7]]
# 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_max(y, dim=[1, 2]) # [4.0, 8.0]
fluid.layers.reduce_max(y, dim=[0, 1]) # [7.0, 8.0]
"""
helper
=
LayerHelper
(
'reduce_max'
,
**
locals
())
out
=
helper
.
create_variable_for_type_inference
(
dtype
=
helper
.
input_dtype
())
if
dim
is
not
None
and
not
isinstance
(
dim
,
list
):
dim
=
[
dim
]
if
in_dygraph_mode
():
return
_C_ops
.
max
(
input
,
dim
if
dim
is
not
None
else
[],
keep_dim
)
helper
.
append_op
(
type
=
'reduce_max'
,
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_min
(
input
,
dim
=
None
,
keep_dim
=
False
,
name
=
None
):
"""
Computes the minimum 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 (list|int, optional): The dimensions along which the minimum is computed.
If :attr:`None`, compute the minimum over 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 minimum 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_min(x) # [0.1]
fluid.layers.reduce_min(x, dim=0) # [0.1, 0.2, 0.5, 0.7]
fluid.layers.reduce_min(x, dim=-1) # [0.2, 0.1]
fluid.layers.reduce_min(x, dim=1, keep_dim=True) # [[0.2], [0.1]]
# 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_min(y, dim=[1, 2]) # [1.0, 5.0]
fluid.layers.reduce_min(y, dim=[0, 1]) # [1.0, 2.0]
"""
helper
=
LayerHelper
(
'reduce_min'
,
**
locals
())
out
=
helper
.
create_variable_for_type_inference
(
dtype
=
helper
.
input_dtype
())
if
dim
is
not
None
and
not
isinstance
(
dim
,
list
):
dim
=
[
dim
]
if
in_dygraph_mode
():
return
_C_ops
.
min
(
input
,
dim
if
dim
is
not
None
else
[],
keep_dim
)
helper
.
append_op
(
type
=
'reduce_min'
,
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
):
"""
...
...
python/paddle/fluid/tests/unittests/dygraph_to_static/test_sentiment.py
浏览文件 @
6ea8bfc6
...
...
@@ -52,7 +52,7 @@ class SimpleConvPool(fluid.dygraph.Layer):
def
forward
(
self
,
inputs
):
x
=
paddle
.
tanh
(
self
.
_conv2d
(
inputs
))
x
=
fluid
.
layers
.
reduce_max
(
x
,
dim
=-
1
)
x
=
paddle
.
max
(
x
,
axis
=-
1
)
x
=
paddle
.
reshape
(
x
,
shape
=
[
self
.
batch_size
,
-
1
])
return
x
...
...
@@ -194,7 +194,7 @@ class GRU(fluid.dygraph.Layer):
emb
=
paddle
.
reshape
(
emb
,
shape
=
[
self
.
batch_size
,
-
1
,
self
.
hid_dim
])
fc_1
=
self
.
_fc1
(
emb
)
gru_hidden
=
self
.
_gru
(
fc_1
)
gru_hidden
=
fluid
.
layers
.
reduce_max
(
gru_hidden
,
dim
=
1
)
gru_hidden
=
paddle
.
max
(
gru_hidden
,
axis
=
1
)
tanh_1
=
paddle
.
tanh
(
gru_hidden
)
fc_2
=
self
.
_fc2
(
tanh_1
)
prediction
=
self
.
_fc_prediction
(
fc_2
)
...
...
@@ -254,7 +254,7 @@ class BiGRU(fluid.dygraph.Layer):
encoded_vector
=
fluid
.
layers
.
concat
(
input
=
[
gru_forward_tanh
,
gru_backward_tanh
],
axis
=
2
)
encoded_vector
=
fluid
.
layers
.
reduce_max
(
encoded_vector
,
dim
=
1
)
encoded_vector
=
paddle
.
max
(
encoded_vector
,
axis
=
1
)
fc_2
=
self
.
_fc2
(
encoded_vector
)
prediction
=
self
.
_fc_prediction
(
fc_2
)
# TODO(Aurelius84): Uncomment the following codes when we support return variable-length vars.
...
...
python/paddle/fluid/tests/unittests/dygraph_to_static/test_tsm.py
浏览文件 @
6ea8bfc6
...
...
@@ -208,7 +208,7 @@ class TSM_ResNet(fluid.dygraph.Layer):
y
=
self
.
pool2d_avg
(
y
)
y
=
fluid
.
layers
.
dropout
(
y
,
dropout_prob
=
0.5
)
y
=
paddle
.
reshape
(
y
,
[
-
1
,
self
.
seg_num
,
y
.
shape
[
1
]])
y
=
fluid
.
layers
.
reduce_mean
(
y
,
dim
=
1
)
y
=
paddle
.
mean
(
y
,
axis
=
1
)
y
=
paddle
.
reshape
(
y
,
shape
=
[
-
1
,
2048
])
y
=
self
.
out
(
y
)
return
y
...
...
python/paddle/fluid/tests/unittests/ipu/test_reduce_x_op_ipu.py
浏览文件 @
6ea8bfc6
...
...
@@ -123,12 +123,12 @@ class TestMean(IPUOpTest):
class
TestMax
(
TestMean
):
def
set_test_op
(
self
):
self
.
op
=
paddle
.
fluid
.
layers
.
reduce_
max
self
.
op
=
paddle
.
max
class
TestMin
(
TestMean
):
def
set_test_op
(
self
):
self
.
op
=
paddle
.
fluid
.
layers
.
reduce_
min
self
.
op
=
paddle
.
min
class
TestSum
(
TestMean
):
...
...
python/paddle/fluid/tests/unittests/test_assert_op.py
浏览文件 @
6ea8bfc6
...
...
@@ -70,7 +70,7 @@ class TestAssertOp(unittest.TestCase):
def
test_assert_summary
(
self
):
def
net_func
():
x
=
layers
.
fill_constant
(
shape
=
[
10
],
dtype
=
'float32'
,
value
=
2.0
)
condition
=
layers
.
reduce_
max
(
x
)
<
1.0
condition
=
paddle
.
max
(
x
)
<
1.0
layers
.
Assert
(
condition
,
(
x
,),
5
)
print
(
"test_assert_summary"
)
...
...
@@ -80,7 +80,7 @@ class TestAssertOp(unittest.TestCase):
def
test_assert_summary_greater_than_size
(
self
):
def
net_func
():
x
=
layers
.
fill_constant
(
shape
=
[
2
,
3
],
dtype
=
'float32'
,
value
=
2.0
)
condition
=
layers
.
reduce_
max
(
x
)
<
1.0
condition
=
paddle
.
max
(
x
)
<
1.0
layers
.
Assert
(
condition
,
[
x
],
10
,
name
=
"test"
)
print
(
"test_assert_summary_greater_than_size"
)
...
...
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