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体验新版 GitCode,发现更多精彩内容 >>
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92ab6148
编写于
2月 13, 2017
作者:
Y
Yi Wang
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Add Event Handler
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doc/design/api.md
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...
...
@@ -163,7 +163,7 @@ There are some open questions here:
feed a topology with more data layers?
**
##
#
Training
## Training
The recommended way to training a model is to call
`paddle.train`
,
which simply calls
`paddle.trainer.Default`
, a global variable of
...
...
@@ -171,15 +171,42 @@ type `paddle.trainer.SGD`. Equivalently, we can do
```
python
opt
=
paddle
.
trainer
.
SGD
(...,
paddle
.
updater
.
Adam
(...))
opt
.
train
(
model
,
reader
=
read
,
...)
opt
.
train
(
topology
,
parameters
,
reader
=
read
,
...)
```
### Updater
Please be aware that a trainer requires an updater as its data
member. This is to make it easier to customize trainers, as
discussed
[
here
](
https://github.com/PaddlePaddle/Paddle/issues/1319
)
.
### Event Handler
`paddle.train`
and
`paddle.trainer.XXX.train`
take an optional
parameter
`event_handler`
, which should be either
`None`
or a function
that handle some events:
1.
BeginTraining
1.
EndTraining
1.
BeginMinibatch
1.
EndMinibatch
1.
BeginPass
1.
EndPass
where EndPass is sent if and only if the reader yields
`end_pass=True`
.
An example as follows:
```
python
def
event_handler
(
event
):
if
ininstance
(
event
,
paddle
.
event
.
EndMinibatch
):
print
paddle
.
test
(...)
paddle
.
train
(
topology
,
parameters
,
reader
,
event_handler
)
```
###
#
Distributed Training
### Distributed Training
If users want to do distributed training on a cluster, s/he should
call
`paddle.dist_train`
and provides access tokens to the cluster as
...
...
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