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11de384c
编写于
12月 25, 2020
作者:
L
LielinJiang
提交者:
GitHub
12月 25, 2020
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差异文件
Split callbacks unittest (#29914)
* split callback unittest * rm test_callback from timeout list
上级
01950ceb
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
208 addition
and
104 deletion
+208
-104
python/paddle/tests/CMakeLists.txt
python/paddle/tests/CMakeLists.txt
+0
-1
python/paddle/tests/test_callback_early_stop.py
python/paddle/tests/test_callback_early_stop.py
+131
-0
python/paddle/tests/test_callback_visualdl.py
python/paddle/tests/test_callback_visualdl.py
+75
-0
python/paddle/tests/test_callbacks.py
python/paddle/tests/test_callbacks.py
+2
-102
tools/windows/run_unittests.sh
tools/windows/run_unittests.sh
+0
-1
未找到文件。
python/paddle/tests/CMakeLists.txt
浏览文件 @
11de384c
...
...
@@ -48,5 +48,4 @@ set_tests_properties(test_dataset_wmt PROPERTIES TIMEOUT 120)
set_tests_properties
(
test_vision_models PROPERTIES TIMEOUT 120
)
set_tests_properties
(
test_dataset_uci_housing PROPERTIES TIMEOUT 120
)
set_tests_properties
(
test_dataset_imdb PROPERTIES TIMEOUT 150
)
set_tests_properties
(
test_callbacks PROPERTIES TIMEOUT 120
)
set_tests_properties
(
test_pretrained_model PROPERTIES TIMEOUT 600
)
python/paddle/tests/test_callback_early_stop.py
0 → 100644
浏览文件 @
11de384c
# 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
time
import
random
import
tempfile
import
shutil
import
numpy
as
np
import
paddle
from
paddle
import
Model
from
paddle.static
import
InputSpec
from
paddle.vision.models
import
LeNet
from
paddle.hapi.callbacks
import
config_callbacks
from
paddle.vision.datasets
import
MNIST
from
paddle.metric
import
Accuracy
from
paddle.nn.layer.loss
import
CrossEntropyLoss
class
MnistDataset
(
MNIST
):
def
__init__
(
self
,
mode
,
return_label
=
True
,
sample_num
=
None
):
super
(
MnistDataset
,
self
).
__init__
(
mode
=
mode
)
self
.
return_label
=
return_label
if
sample_num
:
self
.
images
=
self
.
images
[:
sample_num
]
self
.
labels
=
self
.
labels
[:
sample_num
]
def
__getitem__
(
self
,
idx
):
img
,
label
=
self
.
images
[
idx
],
self
.
labels
[
idx
]
img
=
np
.
reshape
(
img
,
[
1
,
28
,
28
])
if
self
.
return_label
:
return
img
,
np
.
array
(
self
.
labels
[
idx
]).
astype
(
'int64'
)
return
img
,
def
__len__
(
self
):
return
len
(
self
.
images
)
class
TestCallbacks
(
unittest
.
TestCase
):
def
setUp
(
self
):
self
.
save_dir
=
tempfile
.
mkdtemp
()
def
tearDown
(
self
):
shutil
.
rmtree
(
self
.
save_dir
)
def
test_earlystopping
(
self
):
paddle
.
seed
(
2020
)
for
dynamic
in
[
True
,
False
]:
paddle
.
enable_static
if
not
dynamic
else
None
device
=
paddle
.
set_device
(
'cpu'
)
sample_num
=
100
train_dataset
=
MnistDataset
(
mode
=
'train'
,
sample_num
=
sample_num
)
val_dataset
=
MnistDataset
(
mode
=
'test'
,
sample_num
=
sample_num
)
net
=
LeNet
()
optim
=
paddle
.
optimizer
.
Adam
(
learning_rate
=
0.001
,
parameters
=
net
.
parameters
())
inputs
=
[
InputSpec
([
None
,
1
,
28
,
28
],
'float32'
,
'x'
)]
labels
=
[
InputSpec
([
None
,
1
],
'int64'
,
'label'
)]
model
=
Model
(
net
,
inputs
=
inputs
,
labels
=
labels
)
model
.
prepare
(
optim
,
loss
=
CrossEntropyLoss
(
reduction
=
"sum"
),
metrics
=
[
Accuracy
()])
callbacks_0
=
paddle
.
callbacks
.
EarlyStopping
(
'loss'
,
mode
=
'min'
,
patience
=
1
,
verbose
=
1
,
min_delta
=
0
,
baseline
=
None
,
save_best_model
=
True
)
callbacks_1
=
paddle
.
callbacks
.
EarlyStopping
(
'acc'
,
mode
=
'auto'
,
patience
=
1
,
verbose
=
1
,
min_delta
=
0
,
baseline
=
0
,
save_best_model
=
True
)
callbacks_2
=
paddle
.
callbacks
.
EarlyStopping
(
'loss'
,
mode
=
'auto_'
,
patience
=
1
,
verbose
=
1
,
min_delta
=
0
,
baseline
=
None
,
save_best_model
=
True
)
callbacks_3
=
paddle
.
callbacks
.
EarlyStopping
(
'acc_'
,
mode
=
'max'
,
patience
=
1
,
verbose
=
1
,
min_delta
=
0
,
baseline
=
0
,
save_best_model
=
True
)
model
.
fit
(
train_dataset
,
val_dataset
,
batch_size
=
64
,
save_freq
=
10
,
save_dir
=
self
.
save_dir
,
epochs
=
10
,
verbose
=
0
,
callbacks
=
[
callbacks_0
,
callbacks_1
,
callbacks_2
,
callbacks_3
])
# Test for no val_loader
model
.
fit
(
train_dataset
,
batch_size
=
64
,
save_freq
=
10
,
save_dir
=
self
.
save_dir
,
epochs
=
10
,
verbose
=
0
,
callbacks
=
[
callbacks_0
])
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/tests/test_callback_visualdl.py
0 → 100644
浏览文件 @
11de384c
# 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
sys
import
unittest
import
time
import
random
import
tempfile
import
shutil
import
numpy
as
np
import
paddle
from
paddle
import
Model
from
paddle.static
import
InputSpec
from
paddle.vision.models
import
LeNet
from
paddle.hapi.callbacks
import
config_callbacks
import
paddle.vision.transforms
as
T
from
paddle.vision.datasets
import
MNIST
from
paddle.metric
import
Accuracy
from
paddle.nn.layer.loss
import
CrossEntropyLoss
class
MnistDataset
(
MNIST
):
def
__len__
(
self
):
return
512
class
TestCallbacks
(
unittest
.
TestCase
):
def
setUp
(
self
):
self
.
save_dir
=
tempfile
.
mkdtemp
()
def
tearDown
(
self
):
shutil
.
rmtree
(
self
.
save_dir
)
def
test_visualdl_callback
(
self
):
# visualdl not support python2
if
sys
.
version_info
<
(
3
,
):
return
inputs
=
[
InputSpec
([
-
1
,
1
,
28
,
28
],
'float32'
,
'image'
)]
labels
=
[
InputSpec
([
None
,
1
],
'int64'
,
'label'
)]
transform
=
T
.
Compose
([
T
.
Transpose
(),
T
.
Normalize
([
127.5
],
[
127.5
])])
train_dataset
=
MnistDataset
(
mode
=
'train'
,
transform
=
transform
)
eval_dataset
=
MnistDataset
(
mode
=
'test'
,
transform
=
transform
)
net
=
paddle
.
vision
.
LeNet
()
model
=
paddle
.
Model
(
net
,
inputs
,
labels
)
optim
=
paddle
.
optimizer
.
Adam
(
0.001
,
parameters
=
net
.
parameters
())
model
.
prepare
(
optimizer
=
optim
,
loss
=
paddle
.
nn
.
CrossEntropyLoss
(),
metrics
=
paddle
.
metric
.
Accuracy
())
callback
=
paddle
.
callbacks
.
VisualDL
(
log_dir
=
'visualdl_log_dir'
)
model
.
fit
(
train_dataset
,
eval_dataset
,
batch_size
=
64
,
callbacks
=
callback
)
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/tests/test_callbacks.py
浏览文件 @
11de384c
...
...
@@ -59,9 +59,9 @@ class TestCallbacks(unittest.TestCase):
def
run_callback
(
self
):
epochs
=
2
steps
=
5
0
steps
=
5
freq
=
2
eval_steps
=
2
0
eval_steps
=
2
inputs
=
[
InputSpec
([
None
,
1
,
28
,
28
],
'float32'
,
'image'
)]
lenet
=
Model
(
LeNet
(),
inputs
)
...
...
@@ -132,106 +132,6 @@ class TestCallbacks(unittest.TestCase):
self
.
verbose
=
3
self
.
run_callback
()
def
test_visualdl_callback
(
self
):
# visualdl not support python2
if
sys
.
version_info
<
(
3
,
):
return
inputs
=
[
InputSpec
([
-
1
,
1
,
28
,
28
],
'float32'
,
'image'
)]
labels
=
[
InputSpec
([
None
,
1
],
'int64'
,
'label'
)]
transform
=
T
.
Compose
([
T
.
Transpose
(),
T
.
Normalize
([
127.5
],
[
127.5
])])
train_dataset
=
paddle
.
vision
.
datasets
.
MNIST
(
mode
=
'train'
,
transform
=
transform
)
eval_dataset
=
paddle
.
vision
.
datasets
.
MNIST
(
mode
=
'test'
,
transform
=
transform
)
net
=
paddle
.
vision
.
LeNet
()
model
=
paddle
.
Model
(
net
,
inputs
,
labels
)
optim
=
paddle
.
optimizer
.
Adam
(
0.001
,
parameters
=
net
.
parameters
())
model
.
prepare
(
optimizer
=
optim
,
loss
=
paddle
.
nn
.
CrossEntropyLoss
(),
metrics
=
paddle
.
metric
.
Accuracy
())
callback
=
paddle
.
callbacks
.
VisualDL
(
log_dir
=
'visualdl_log_dir'
)
model
.
fit
(
train_dataset
,
eval_dataset
,
batch_size
=
64
,
callbacks
=
callback
)
def
test_earlystopping
(
self
):
paddle
.
seed
(
2020
)
for
dynamic
in
[
True
,
False
]:
paddle
.
enable_static
if
not
dynamic
else
None
device
=
paddle
.
set_device
(
'cpu'
)
sample_num
=
100
train_dataset
=
MnistDataset
(
mode
=
'train'
,
sample_num
=
sample_num
)
val_dataset
=
MnistDataset
(
mode
=
'test'
,
sample_num
=
sample_num
)
net
=
LeNet
()
optim
=
paddle
.
optimizer
.
Adam
(
learning_rate
=
0.001
,
parameters
=
net
.
parameters
())
inputs
=
[
InputSpec
([
None
,
1
,
28
,
28
],
'float32'
,
'x'
)]
labels
=
[
InputSpec
([
None
,
1
],
'int64'
,
'label'
)]
model
=
Model
(
net
,
inputs
=
inputs
,
labels
=
labels
)
model
.
prepare
(
optim
,
loss
=
CrossEntropyLoss
(
reduction
=
"sum"
),
metrics
=
[
Accuracy
()])
callbacks_0
=
paddle
.
callbacks
.
EarlyStopping
(
'loss'
,
mode
=
'min'
,
patience
=
1
,
verbose
=
1
,
min_delta
=
0
,
baseline
=
None
,
save_best_model
=
True
)
callbacks_1
=
paddle
.
callbacks
.
EarlyStopping
(
'acc'
,
mode
=
'auto'
,
patience
=
1
,
verbose
=
1
,
min_delta
=
0
,
baseline
=
0
,
save_best_model
=
True
)
callbacks_2
=
paddle
.
callbacks
.
EarlyStopping
(
'loss'
,
mode
=
'auto_'
,
patience
=
1
,
verbose
=
1
,
min_delta
=
0
,
baseline
=
None
,
save_best_model
=
True
)
callbacks_3
=
paddle
.
callbacks
.
EarlyStopping
(
'acc_'
,
mode
=
'max'
,
patience
=
1
,
verbose
=
1
,
min_delta
=
0
,
baseline
=
0
,
save_best_model
=
True
)
model
.
fit
(
train_dataset
,
val_dataset
,
batch_size
=
64
,
save_freq
=
10
,
save_dir
=
self
.
save_dir
,
epochs
=
10
,
verbose
=
0
,
callbacks
=
[
callbacks_0
,
callbacks_1
,
callbacks_2
,
callbacks_3
])
# Test for no val_loader
model
.
fit
(
train_dataset
,
batch_size
=
64
,
save_freq
=
10
,
save_dir
=
self
.
save_dir
,
epochs
=
10
,
verbose
=
0
,
callbacks
=
[
callbacks_0
])
if
__name__
==
'__main__'
:
unittest
.
main
()
tools/windows/run_unittests.sh
浏览文件 @
11de384c
...
...
@@ -100,7 +100,6 @@ diable_wingpu_test="^test_analysis_predictor$|\
^test_weight_decay
$|
\
^test_conv2d_int8_mkldnn_op
$|
\
^test_crypto
$|
\
^test_callbacks
$|
\
^test_program_prune_backward
$|
\
^test_imperative_ocr_attention_model
$|
\
^test_sentiment
$|
\
...
...
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