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体验新版 GitCode,发现更多精彩内容 >>
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a0f1dba3
编写于
9月 30, 2020
作者:
L
LielinJiang
提交者:
GitHub
9月 30, 2020
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差异文件
Add visualdl callback function (#27565)
* add visualdl callback
上级
9b3ef597
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
140 addition
and
1 deletion
+140
-1
python/paddle/hapi/callbacks.py
python/paddle/hapi/callbacks.py
+111
-1
python/paddle/tests/test_callbacks.py
python/paddle/tests/test_callbacks.py
+28
-0
python/unittest_py/requirements.txt
python/unittest_py/requirements.txt
+1
-0
未找到文件。
python/paddle/hapi/callbacks.py
浏览文件 @
a0f1dba3
...
...
@@ -13,12 +13,14 @@
# limitations under the License.
import
os
import
numbers
from
paddle.fluid.dygraph.parallel
import
ParallelEnv
from
paddle.utils
import
try_import
from
.progressbar
import
ProgressBar
__all__
=
[
'Callback'
,
'ProgBarLogger'
,
'ModelCheckpoint'
]
__all__
=
[
'Callback'
,
'ProgBarLogger'
,
'ModelCheckpoint'
,
'VisualDL'
]
def
config_callbacks
(
callbacks
=
None
,
...
...
@@ -471,3 +473,111 @@ class ModelCheckpoint(Callback):
path
=
'{}/final'
.
format
(
self
.
save_dir
)
print
(
'save checkpoint at {}'
.
format
(
os
.
path
.
abspath
(
path
)))
self
.
model
.
save
(
path
)
class
VisualDL
(
Callback
):
"""VisualDL callback function
Args:
log_dir (str): The directory to save visualdl log file.
Examples:
.. code-block:: python
import paddle
from paddle.static import InputSpec
inputs = [InputSpec([-1, 1, 28, 28], 'float32', 'image')]
labels = [InputSpec([None, 1], 'int64', 'label')]
train_dataset = paddle.vision.datasets.MNIST(mode='train')
eval_dataset = paddle.vision.datasets.MNIST(mode='test')
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())
## uncomment following lines to fit model with visualdl callback function
# callback = paddle.callbacks.VisualDL(log_dir='visualdl_log_dir')
# model.fit(train_dataset, eval_dataset, batch_size=64, callbacks=callback)
"""
def
__init__
(
self
,
log_dir
):
self
.
log_dir
=
log_dir
self
.
epochs
=
None
self
.
steps
=
None
self
.
epoch
=
0
def
_is_write
(
self
):
return
ParallelEnv
().
local_rank
==
0
def
on_train_begin
(
self
,
logs
=
None
):
self
.
epochs
=
self
.
params
[
'epochs'
]
assert
self
.
epochs
self
.
train_metrics
=
self
.
params
[
'metrics'
]
assert
self
.
train_metrics
self
.
_is_fit
=
True
self
.
train_step
=
0
def
on_epoch_begin
(
self
,
epoch
=
None
,
logs
=
None
):
self
.
steps
=
self
.
params
[
'steps'
]
self
.
epoch
=
epoch
def
_updates
(
self
,
logs
,
mode
):
if
not
self
.
_is_write
():
return
if
not
hasattr
(
self
,
'writer'
):
visualdl
=
try_import
(
'visualdl'
)
self
.
writer
=
visualdl
.
LogWriter
(
self
.
log_dir
)
metrics
=
getattr
(
self
,
'%s_metrics'
%
(
mode
))
current_step
=
getattr
(
self
,
'%s_step'
%
(
mode
))
if
mode
==
'train'
:
total_step
=
current_step
else
:
total_step
=
self
.
epoch
for
k
in
metrics
:
if
k
in
logs
:
temp_tag
=
mode
+
'/'
+
k
if
isinstance
(
logs
[
k
],
(
list
,
tuple
)):
temp_value
=
logs
[
k
][
0
]
elif
isinstance
(
logs
[
k
],
numbers
.
Number
):
temp_value
=
logs
[
k
]
else
:
continue
self
.
writer
.
add_scalar
(
tag
=
temp_tag
,
step
=
total_step
,
value
=
temp_value
)
def
on_train_batch_end
(
self
,
step
,
logs
=
None
):
logs
=
logs
or
{}
self
.
train_step
+=
1
if
self
.
_is_write
():
self
.
_updates
(
logs
,
'train'
)
def
on_eval_begin
(
self
,
logs
=
None
):
self
.
eval_steps
=
logs
.
get
(
'steps'
,
None
)
self
.
eval_metrics
=
logs
.
get
(
'metrics'
,
[])
self
.
eval_step
=
0
self
.
evaled_samples
=
0
def
on_train_end
(
self
,
logs
=
None
):
if
hasattr
(
self
,
'writer'
):
self
.
writer
.
close
()
delattr
(
self
,
'writer'
)
def
on_eval_end
(
self
,
logs
=
None
):
if
self
.
_is_write
():
self
.
_updates
(
logs
,
'eval'
)
if
(
not
hasattr
(
self
,
'_is_fit'
))
and
hasattr
(
self
,
'writer'
):
self
.
writer
.
close
()
delattr
(
self
,
'writer'
)
python/paddle/tests/test_callbacks.py
浏览文件 @
a0f1dba3
...
...
@@ -12,11 +12,13 @@
# 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
paddle
from
paddle
import
Model
from
paddle.static
import
InputSpec
...
...
@@ -102,6 +104,32 @@ class TestCallbacks(unittest.TestCase):
self
.
verbose
=
2
self
.
run_callback
()
def
test_visualdl_callback
(
self
):
# visualdl not support python3
if
sys
.
version_info
<
(
3
,
):
return
inputs
=
[
InputSpec
([
-
1
,
1
,
28
,
28
],
'float32'
,
'image'
)]
labels
=
[
InputSpec
([
None
,
1
],
'int64'
,
'label'
)]
train_dataset
=
paddle
.
vision
.
datasets
.
MNIST
(
mode
=
'train'
)
eval_dataset
=
paddle
.
vision
.
datasets
.
MNIST
(
mode
=
'test'
)
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/unittest_py/requirements.txt
浏览文件 @
a0f1dba3
...
...
@@ -2,3 +2,4 @@ PyGithub
coverage
pycrypto ; platform_system != "Windows"
mock
visualdl ; python_version>="3.5"
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