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PaddleRec
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e0bab5f6
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PaddleRec
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e0bab5f6
编写于
5月 01, 2020
作者:
T
tangwei
浏览文件
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电子邮件补丁
差异文件
add log hint for local cluster training
上级
73d3502f
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
5 addition
and
115 deletion
+5
-115
demo/__init__.py
demo/__init__.py
+0
-0
demo/ctr-dnn_train.yaml
demo/ctr-dnn_train.yaml
+0
-47
demo/user_define_trainer.py
demo/user_define_trainer.py
+0
-61
readme.md
readme.md
+5
-7
未找到文件。
demo/__init__.py
已删除
100644 → 0
浏览文件 @
73d3502f
demo/ctr-dnn_train.yaml
已删除
100644 → 0
浏览文件 @
73d3502f
# 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.
train
:
trainer
:
# for cluster training
strategy
:
"
async"
epochs
:
10
workspace
:
"
fleetrec.models.rank.dnn"
reader
:
batch_size
:
2
class
:
"
{workspace}/../criteo_reader.py"
train_data_path
:
"
{workspace}/data/train"
model
:
models
:
"
{workspace}/model.py"
hyper_parameters
:
sparse_inputs_slots
:
27
sparse_feature_number
:
1000001
sparse_feature_dim
:
9
dense_input_dim
:
13
fc_sizes
:
[
512
,
256
,
128
,
32
]
learning_rate
:
0.001
optimizer
:
adam
save
:
increment
:
dirname
:
"
increment"
epoch_interval
:
2
save_last
:
True
inference
:
dirname
:
"
inference"
epoch_interval
:
4
save_last
:
True
demo/user_define_trainer.py
已删除
100644 → 0
浏览文件 @
73d3502f
# 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
paddle.fluid
as
fluid
from
fleetrec.core.trainers.transpiler_trainer
import
TranspileTrainer
from
fleetrec.core.utils
import
envs
class
UserDefineTrainer
(
TranspileTrainer
):
def
__init__
(
self
,
config
=
None
):
TranspileTrainer
.
__init__
(
self
,
config
)
print
(
"this is a demo about how to use user define trainer in fleet-rec"
)
def
processor_register
(
self
):
self
.
regist_context_processor
(
'uninit'
,
self
.
instance
)
self
.
regist_context_processor
(
'init_pass'
,
self
.
init
)
self
.
regist_context_processor
(
'train_pass'
,
self
.
train
)
def
init
(
self
,
context
):
self
.
model
.
train_net
()
optimizer
=
self
.
model
.
optimizer
()
optimizer
.
minimize
((
self
.
model
.
get_cost_op
()))
self
.
fetch_vars
=
[]
self
.
fetch_alias
=
[]
self
.
fetch_period
=
self
.
model
.
get_fetch_period
()
metrics
=
self
.
model
.
get_metrics
()
if
metrics
:
self
.
fetch_vars
=
metrics
.
values
()
self
.
fetch_alias
=
metrics
.
keys
()
context
[
'status'
]
=
'train_pass'
def
train
(
self
,
context
):
# run startup program at once
self
.
_exe
.
run
(
fluid
.
default_startup_program
())
dataset
=
self
.
_get_dataset
()
epochs
=
envs
.
get_global_env
(
"train.epochs"
)
for
i
in
range
(
epochs
):
self
.
_exe
.
train_from_dataset
(
program
=
fluid
.
default_main_program
(),
dataset
=
dataset
,
fetch_list
=
self
.
fetch_vars
,
fetch_info
=
self
.
fetch_alias
,
print_period
=
self
.
fetch_period
)
context
[
'is_exit'
]
=
True
readme.md
浏览文件 @
e0bab5f6
...
...
@@ -26,22 +26,20 @@ python setup.py install
## ctr-dnn示例使用
目前框架内置了ctr-dnn模型,后续会加入更多模型
示例代码位于FleetRec/demo/下, 当前支持单机训练和本地1
*
1模拟训练
目前框架内置了多个模型,简单的命令即可使用内置模型开始单机训练和本地1
*
1模拟训练
### 单机训练
```
bash
cd
FleetRec
python
-m
fleetrec.run
\
-m
demo/ctr-dnn_train.yaml
\
-m
fleetrec.models.rank.dnn
\
-d
cpu
\
-e
single
# 使用GPU资源进行训练
python
-m
fleetrec.run
\
-m
demo/ctr-dnn_train.yaml
\
-m
fleetrec.models.rank.dnn
\
-d
gpu
\
-e
single
```
...
...
@@ -52,7 +50,7 @@ python -m fleetrec.run \
cd
FleetRec
# 使用CPU资源进行训练
python
-m
fleetrec.run
\
-m
demo/ctr-dnn_train.yaml
\
-m
fleetrec.models.rank.dnn
\
-d
cpu
\
-e
local_cluster
```
...
...
@@ -63,7 +61,7 @@ python -m fleetrec.run \
cd
FleetRec
python
-m
fleetrec.run
\
-m
demo/ctr-dnn_train.yaml
\
-m
fleetrec.models.rank.dnn
\
-d
cpu
\
-e
cluster
```
...
...
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