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310f4320
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310f4320
编写于
12月 01, 2022
作者:
2
201716010711
提交者:
GitHub
12月 01, 2022
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差异文件
clean fluid task: delete sum api (#48438)
上级
47e7b7a5
变更
11
显示空白变更内容
内联
并排
Showing
11 changed file
with
127 addition
and
91 deletion
+127
-91
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+0
-73
python/paddle/fluid/optimizer.py
python/paddle/fluid/optimizer.py
+2
-2
python/paddle/fluid/tests/unittests/ipu/test_sum_op_ipu.py
python/paddle/fluid/tests/unittests/ipu/test_sum_op_ipu.py
+2
-2
python/paddle/fluid/tests/unittests/ir/test_ir_fusion_group_pass.py
...dle/fluid/tests/unittests/ir/test_ir_fusion_group_pass.py
+2
-2
python/paddle/fluid/tests/unittests/test_layers.py
python/paddle/fluid/tests/unittests/test_layers.py
+1
-1
python/paddle/fluid/tests/unittests/test_optimizer_grad.py
python/paddle/fluid/tests/unittests/test_optimizer_grad.py
+1
-1
python/paddle/fluid/tests/unittests/test_paddle_fluid_modelaverage.py
...e/fluid/tests/unittests/test_paddle_fluid_modelaverage.py
+109
-0
python/paddle/fluid/tests/unittests/test_sum_op.py
python/paddle/fluid/tests/unittests/test_sum_op.py
+3
-3
python/paddle/fluid/tests/unittests/xpu/test_sum_op_xpu.py
python/paddle/fluid/tests/unittests/xpu/test_sum_op_xpu.py
+3
-3
python/paddle/hapi/model.py
python/paddle/hapi/model.py
+2
-2
python/paddle/incubate/optimizer/modelaverage.py
python/paddle/incubate/optimizer/modelaverage.py
+2
-2
未找到文件。
python/paddle/fluid/layers/nn.py
浏览文件 @
310f4320
...
...
@@ -104,7 +104,6 @@ __all__ = [
'elementwise_mul'
,
'gaussian_random'
,
'sampling_id'
,
'sum'
,
'shape'
,
'clip'
,
'clip_by_norm'
,
...
...
@@ -5439,78 +5438,6 @@ def sampling_id(x, min=0.0, max=1.0, seed=0, dtype='float32'):
return
out
@
templatedoc
()
def
sum
(
x
):
"""
${comment}
Case 1:
::
Input:
Input. Shape = [2, 3]
Input = [[1, 2, 3],
[4, 5, 6]]
Output:
The output. Shape = [2, 3]
Output = [[1, 2, 3],
[4, 5, 6]]
Case 2:
::
Input:
First input:
Input1. Shape = [2, 3]
Input1 = [[1, 2, 3],
[4, 5, 6]]
The second input:
Input2. Shape = [2, 3]
Input2 = [[7, 8, 9],
[10, 11, 12]]
Output:
The output. Shape = [2, 3]
Output = [[8, 10, 12],
[14, 16, 18]]
Args:
x (Variable|list(Variable)): ${x_comment}
Returns:
Variable: ${out_comment}
Examples:
.. code-block:: python
import paddle.fluid as fluid
input0 = fluid.layers.fill_constant(shape=[2, 3], dtype='int64', value=5)
input1 = fluid.layers.fill_constant(shape=[2, 3], dtype='int64', value=3)
sum = fluid.layers.sum([input0, input1])
# You can print out 'sum' via executor.
out = fluid.layers.Print(sum, message="the sum of input0 and input1: ")
exe = fluid.Executor(fluid.CPUPlace())
exe.run(fluid.default_main_program())
# The printed result is:
# 1570701754 the sum of input0 and input1: The place is:CPUPlace
# Tensor[sum_0.tmp_0]
# shape: [2,3,]
# dtype: l
# data: 8,8,8,8,8,8,
# the sum of input0 and input1 is 2-D Tensor with shape [2,3].
# dtype is the corresponding C++ data type, which may vary in different environments.
# Eg: if the data type of tensor is int64, then the corresponding C++ data type is int64_t,
# so the dtype value is typeid(int64_t).Name(), which is 'x' on MacOS, 'l' on Linux,
# and '__int64' on Windows. They both represent 64-bit integer variables.
"""
return
paddle
.
add_n
(
x
)
def
shape
(
input
):
"""
:alias_main: paddle.shape
...
...
python/paddle/fluid/optimizer.py
浏览文件 @
310f4320
...
...
@@ -3980,8 +3980,8 @@ class ModelAverage(Optimizer):
# backup param value to grad
layers
.
assign
(
input
=
param
,
output
=
grad
)
# param = (sum_1 + sum_2 + sum_3) / (num_accumulates + old_num_accumulates)
tmp
=
layers
.
sum
(
x
=
[
num_accumulates
,
old_num_accumulates
])
sum
=
layers
.
sum
(
x
=
[
sum_1
,
sum_2
,
sum_3
])
tmp
=
paddle
.
add_n
(
[
num_accumulates
,
old_num_accumulates
])
sum
=
paddle
.
add_n
(
[
sum_1
,
sum_2
,
sum_3
])
tmp
=
layers
.
cast
(
x
=
tmp
,
dtype
=
'float32'
if
self
.
_dtype
is
None
else
self
.
_dtype
)
...
...
python/paddle/fluid/tests/unittests/ipu/test_sum_op_ipu.py
浏览文件 @
310f4320
...
...
@@ -51,7 +51,7 @@ class TestBase(IPUOpTest):
y
=
paddle
.
static
.
data
(
name
=
self
.
feed_list
[
1
],
shape
=
self
.
feed_shape
[
1
],
dtype
=
'float32'
)
out
=
paddle
.
fluid
.
layers
.
sum
([
x
,
y
],
**
self
.
attrs
)
out
=
paddle
.
add_n
([
x
,
y
],
**
self
.
attrs
)
self
.
fetch_list
=
[
out
.
name
]
def
run_model
(
self
,
exec_mode
):
...
...
@@ -92,7 +92,7 @@ class TestCase1(TestBase):
z
=
paddle
.
static
.
data
(
name
=
self
.
feed_list
[
2
],
shape
=
self
.
feed_shape
[
2
],
dtype
=
'float32'
)
out
=
paddle
.
fluid
.
layers
.
sum
([
x
,
y
,
z
],
**
self
.
attrs
)
out
=
paddle
.
add_n
([
x
,
y
,
z
],
**
self
.
attrs
)
self
.
fetch_list
=
[
out
.
name
]
...
...
python/paddle/fluid/tests/unittests/ir/test_ir_fusion_group_pass.py
浏览文件 @
310f4320
...
...
@@ -165,13 +165,13 @@ class FusionGroupPassSumTest(FusionGroupPassTest):
)
# subgraph with 2 op nodes
tmp_0
=
layers
.
sum
(
tmp_0
=
paddle
.
add_n
(
[
self
.
feed_vars
[
0
],
self
.
feed_vars
[
1
],
self
.
feed_vars
[
2
]]
)
tmp_1
=
paddle
.
sqrt
(
tmp_0
)
tmp_2
=
layers
.
mul
(
tmp_0
,
self
.
feed_vars
[
3
])
# subgraph with 2 op nodes
tmp_3
=
paddle
.
square
(
layers
.
sum
([
tmp_1
,
tmp_2
]))
tmp_3
=
paddle
.
square
(
paddle
.
add_n
([
tmp_1
,
tmp_2
]))
self
.
append_gradients
(
tmp_3
)
...
...
python/paddle/fluid/tests/unittests/test_layers.py
浏览文件 @
310f4320
...
...
@@ -3534,7 +3534,7 @@ class TestBook(LayerTest):
name
=
"input"
,
shape
=
[
13
,
11
],
dtype
=
'float32'
)
out
=
layers
.
sum
(
input
)
out
=
paddle
.
add_n
(
input
)
return
out
def
make_slice
(
self
):
...
...
python/paddle/fluid/tests/unittests/test_optimizer_grad.py
浏览文件 @
310f4320
...
...
@@ -122,7 +122,7 @@ class SimpleNetWithCond:
cond_i
=
fluid
.
layers
.
assign
(
np
.
array
([
cond_i
],
dtype
=
'float32'
))
sum_cond
=
fluid
.
layers
.
cond
(
cond_i
>
1.0
,
cond_true
,
cond_false
)
sum_all
=
fluid
.
layers
.
sum
([
sum_xy
,
sub_yz
,
sum_cond
])
sum_all
=
paddle
.
add_n
([
sum_xy
,
sub_yz
,
sum_cond
])
mean_out
=
paddle
.
mean
(
sum_all
)
if
use_bf16
:
import
paddle.static.amp
as
amp
...
...
python/paddle/fluid/tests/unittests/test_paddle_fluid_modelaverage.py
0 → 100644
浏览文件 @
310f4320
# Copyright (c) 2020 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.
import
unittest
import
numpy
as
np
import
paddle.fluid
as
fluid
import
paddle
class
TestModelAverage
(
unittest
.
TestCase
):
def
test_model_average_static
(
self
):
paddle
.
enable_static
()
place
=
fluid
.
CPUPlace
()
shape
=
[
2
,
3
,
8
,
8
]
exe
=
fluid
.
Executor
(
place
)
train_program
=
fluid
.
Program
()
startup
=
fluid
.
Program
()
test_program
=
fluid
.
Program
()
with
fluid
.
program_guard
(
train_program
,
startup
):
with
fluid
.
unique_name
.
guard
():
data
=
fluid
.
data
(
name
=
'X'
,
shape
=
[
None
,
1
],
dtype
=
'float32'
)
hidden
=
fluid
.
layers
.
fc
(
input
=
data
,
size
=
10
)
loss
=
paddle
.
mean
(
hidden
)
test_program
=
train_program
.
clone
()
optimizer
=
paddle
.
optimizer
.
Momentum
(
learning_rate
=
0.2
,
momentum
=
0.1
)
optimizer
.
minimize
(
loss
)
# build ModelAverage optimizer
model_average
=
paddle
.
fluid
.
optimizer
.
ModelAverage
(
0.15
,
min_average_window
=
2
,
max_average_window
=
10
)
exe
.
run
(
startup
)
for
i
in
range
(
10
):
x
=
np
.
random
.
random
(
size
=
(
10
,
1
)).
astype
(
'float32'
)
(
latest_b
,
sum_1
,
sum_2
,
sum_3
,
num_accumulates
,
old_num_accumulates
,
num_updates
,
)
=
exe
.
run
(
program
=
train_program
,
feed
=
{
'X'
:
x
},
fetch_list
=
[
'fc_0.b_0'
,
'fc_0.b_0_sum_1_0'
,
'fc_0.b_0_sum_2_0'
,
'fc_0.b_0_sum_3_0'
,
'fc_0.b_0_num_accumulates_0'
,
'fc_0.b_0_old_num_accumulates_0'
,
'fc_0.b_0_num_updates_0'
,
],
)
self
.
assertTrue
(
np
.
equal
(
sum_1
,
np
.
zeros
(
shape
=
[
10
],
dtype
=
'float32'
)).
all
()
)
self
.
assertTrue
(
np
.
equal
(
sum_2
,
np
.
zeros
(
shape
=
[
10
],
dtype
=
'float32'
)).
all
()
)
self
.
assertTrue
(
np
.
equal
(
num_accumulates
,
np
.
array
([
0
],
dtype
=
'int64'
)).
all
()
)
self
.
assertTrue
(
np
.
equal
(
old_num_accumulates
,
np
.
array
([
2
],
dtype
=
'int64'
)).
all
()
)
self
.
assertTrue
(
np
.
equal
(
num_updates
,
np
.
array
([
10
],
dtype
=
'int64'
)).
all
()
)
average_b
=
(
sum_1
+
sum_2
+
sum_3
)
/
(
num_accumulates
+
old_num_accumulates
)
# apply ModelAverage
with
model_average
.
apply
(
exe
):
x
=
np
.
random
.
random
(
size
=
(
10
,
1
)).
astype
(
'float32'
)
outs
,
b
=
exe
.
run
(
program
=
test_program
,
feed
=
{
'X'
:
x
},
fetch_list
=
[
loss
.
name
,
'fc_0.b_0'
],
)
self
.
assertAlmostEqual
(
np
.
mean
(
average_b
),
np
.
mean
(
b
))
x
=
np
.
random
.
random
(
size
=
(
10
,
1
)).
astype
(
'float32'
)
outs
,
b
=
exe
.
run
(
program
=
test_program
,
feed
=
{
'X'
:
x
},
fetch_list
=
[
loss
.
name
,
'fc_0.b_0'
],
)
self
.
assertAlmostEqual
(
np
.
mean
(
latest_b
),
np
.
mean
(
b
))
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/test_sum_op.py
浏览文件 @
310f4320
...
...
@@ -426,20 +426,20 @@ class API_Test_Add_n(unittest.TestCase):
class
TestRaiseSumError
(
unittest
.
TestCase
):
def
test_errors
(
self
):
def
test_type
():
fluid
.
layers
.
sum
([
11
,
22
])
paddle
.
add_n
([
11
,
22
])
self
.
assertRaises
(
TypeError
,
test_type
)
def
test_dtype
():
data1
=
fluid
.
data
(
name
=
"input1"
,
shape
=
[
10
],
dtype
=
"int8"
)
data2
=
fluid
.
data
(
name
=
"input2"
,
shape
=
[
10
],
dtype
=
"int8"
)
fluid
.
layers
.
sum
([
data1
,
data2
])
paddle
.
add_n
([
data1
,
data2
])
self
.
assertRaises
(
TypeError
,
test_dtype
)
def
test_dtype1
():
data1
=
fluid
.
data
(
name
=
"input1"
,
shape
=
[
10
],
dtype
=
"int8"
)
fluid
.
layers
.
sum
(
data1
)
paddle
.
add_n
(
data1
)
self
.
assertRaises
(
TypeError
,
test_dtype1
)
...
...
python/paddle/fluid/tests/unittests/xpu/test_sum_op_xpu.py
浏览文件 @
310f4320
...
...
@@ -130,20 +130,20 @@ class API_Test_Add_n(unittest.TestCase):
class
TestRaiseSumError
(
unittest
.
TestCase
):
def
test_errors
(
self
):
def
test_type
():
fluid
.
layers
.
sum
([
11
,
22
])
paddle
.
add_n
([
11
,
22
])
self
.
assertRaises
(
TypeError
,
test_type
)
def
test_dtype
():
data1
=
fluid
.
data
(
name
=
"input1"
,
shape
=
[
10
],
dtype
=
"int8"
)
data2
=
fluid
.
data
(
name
=
"input2"
,
shape
=
[
10
],
dtype
=
"int8"
)
fluid
.
layers
.
sum
([
data1
,
data2
])
paddle
.
add_n
([
data1
,
data2
])
self
.
assertRaises
(
TypeError
,
test_dtype
)
def
test_dtype1
():
data1
=
fluid
.
data
(
name
=
"input1"
,
shape
=
[
10
],
dtype
=
"int8"
)
fluid
.
layers
.
sum
(
data1
)
paddle
.
add_n
(
data1
)
self
.
assertRaises
(
TypeError
,
test_dtype1
)
...
...
python/paddle/hapi/model.py
浏览文件 @
310f4320
...
...
@@ -637,7 +637,7 @@ class StaticGraphAdapter:
metrics
.
append
(
to_list
(
metric
.
compute
(
*
(
outputs
+
labels
))))
if
mode
==
'train'
and
self
.
model
.
_optimizer
:
self
.
_loss_endpoint
=
fluid
.
layers
.
sum
(
losses
)
self
.
_loss_endpoint
=
paddle
.
add_n
(
losses
)
if
self
.
_nranks
>
1
:
role
=
role_maker
.
PaddleCloudRoleMaker
(
is_collective
=
True
)
fleet
.
init
(
role
)
...
...
@@ -795,7 +795,7 @@ class DynamicGraphAdapter:
losses
=
self
.
model
.
_loss
(
*
(
to_list
(
outputs
)
+
labels
))
losses
=
to_list
(
losses
)
final_loss
=
fluid
.
layers
.
sum
(
losses
)
final_loss
=
paddle
.
add_n
(
losses
)
if
self
.
_amp_level
!=
"O0"
:
scaled
=
self
.
model
.
_scaler
.
scale
(
final_loss
)
...
...
python/paddle/incubate/optimizer/modelaverage.py
浏览文件 @
310f4320
...
...
@@ -548,8 +548,8 @@ class ModelAverage(Optimizer):
# backup param value to grad
layers
.
assign
(
input
=
param
,
output
=
grad
)
# param = (sum_1 + sum_2 + sum_3) / (num_accumulates + old_num_accumulates)
tmp
=
layers
.
sum
(
x
=
[
num_accumulates
,
old_num_accumulates
])
sum
=
layers
.
sum
(
x
=
[
sum_1
,
sum_2
,
sum_3
])
tmp
=
paddle
.
add_n
(
[
num_accumulates
,
old_num_accumulates
])
sum
=
paddle
.
add_n
(
[
sum_1
,
sum_2
,
sum_3
])
tmp
=
layers
.
cast
(
x
=
tmp
,
dtype
=
'float32'
if
self
.
_dtype
is
None
else
self
.
_dtype
)
...
...
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