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PaddleRec
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eb04c187
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体验新版 GitCode,发现更多精彩内容 >>
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eb04c187
编写于
4月 14, 2020
作者:
T
tangwei
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
add infer net define
上级
ac45ce07
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
32 addition
and
30 deletion
+32
-30
fleetrec/examples/user_define_trainer.py
fleetrec/examples/user_define_trainer.py
+0
-1
fleetrec/models/base.py
fleetrec/models/base.py
+12
-6
fleetrec/models/ctr_dnn/model.py
fleetrec/models/ctr_dnn/model.py
+16
-12
fleetrec/trainer/cluster_trainer.py
fleetrec/trainer/cluster_trainer.py
+2
-6
fleetrec/trainer/single_trainer.py
fleetrec/trainer/single_trainer.py
+2
-5
未找到文件。
fleetrec/examples/user_define_trainer.py
浏览文件 @
eb04c187
...
...
@@ -28,7 +28,6 @@ class UserDefineTrainer(TranspileTrainer):
self
.
regist_context_processor
(
'train_pass'
,
self
.
train
)
def
init
(
self
,
context
):
self
.
model
.
input
()
self
.
model
.
net
()
self
.
model
.
metrics
()
self
.
model
.
avg_loss
()
...
...
fleetrec/models/base.py
浏览文件 @
eb04c187
...
...
@@ -63,11 +63,11 @@ def create(config):
model
=
None
if
config
[
'mode'
]
==
'fluid'
:
model
=
YamlModel
(
config
)
model
.
net
()
model
.
train_
net
()
return
model
class
Model
(
object
):
class
Model
Base
(
object
):
"""R
"""
__metaclass__
=
abc
.
ABCMeta
...
...
@@ -80,6 +80,9 @@ class Model(object):
self
.
_data_var
=
[]
self
.
_fetch_interval
=
20
def
get_input
(
self
):
return
self
.
_data_var
def
get_cost_op
(
self
):
"""R
"""
...
...
@@ -94,20 +97,23 @@ class Model(object):
return
self
.
_fetch_interval
@
abc
.
abstractmethod
def
net
(
self
):
def
train_
net
(
self
):
"""R
"""
pass
def
infer_net
(
self
):
pass
class
YamlModel
(
Model
):
class
YamlModel
(
Model
Base
):
"""R
"""
def
__init__
(
self
,
config
):
"""R
"""
Model
.
__init__
(
self
,
config
)
Model
Base
.
__init__
(
self
,
config
)
self
.
_config
=
config
self
.
_name
=
config
[
'name'
]
f
=
open
(
config
[
'layer_file'
],
'r'
)
...
...
@@ -116,7 +122,7 @@ class YamlModel(Model):
self
.
_build_param
=
{
'layer'
:
{},
'inner_layer'
:
{},
'layer_extend'
:
{},
'model'
:
{}}
self
.
_inference_meta
=
{
'dependency'
:
{},
'params'
:
{}}
def
net
(
self
):
def
train_
net
(
self
):
"""R
build a fluid model with config
Return:
...
...
fleetrec/models/ctr_dnn/model.py
浏览文件 @
eb04c187
...
...
@@ -16,12 +16,12 @@ import math
import
paddle.fluid
as
fluid
from
fleetrec.utils
import
envs
from
fleetrec.models.base
import
Model
from
fleetrec.models.base
import
Model
Base
class
TrainModel
(
Model
):
class
Model
(
ModelBase
):
def
__init__
(
self
,
config
):
Model
.
__init__
(
self
,
config
)
Model
Base
.
__init__
(
self
,
config
)
self
.
namespace
=
"train.model"
def
input
(
self
):
...
...
@@ -52,8 +52,10 @@ class TrainModel(Model):
self
.
dense_input
=
dense_input
()
self
.
label_input
=
label_input
()
def
inputs
(
self
):
return
[
self
.
dense_input
]
+
self
.
sparse_inputs
+
[
self
.
label_input
]
for
input
in
self
.
sparse_inputs
:
self
.
_data_var
.
append
(
input
)
self
.
_data_var
.
append
(
self
.
dense_input
)
self
.
_data_var
.
append
(
self
.
label_input
)
def
net
(
self
):
def
embedding_layer
(
input
):
...
...
@@ -112,15 +114,17 @@ class TrainModel(Model):
self
.
_metrics
[
"AUC"
]
=
auc
self
.
_metrics
[
"BATCH_AUC"
]
=
batch_auc
def
train_net
(
self
):
self
.
input
()
self
.
net
()
self
.
avg_loss
()
self
.
metrics
()
def
optimizer
(
self
):
learning_rate
=
envs
.
get_global_env
(
"hyper_parameters.learning_rate"
,
None
,
self
.
namespace
)
optimizer
=
fluid
.
optimizer
.
Adam
(
learning_rate
,
lazy_mode
=
True
)
return
optimizer
class
EvaluateModel
(
object
):
def
input
(
self
):
pass
def
net
(
self
):
pass
def
infer_net
(
self
):
self
.
input
()
self
.
net
()
fleetrec/trainer/cluster_trainer.py
浏览文件 @
eb04c187
...
...
@@ -66,15 +66,11 @@ class ClusterTrainer(TranspileTrainer):
return
strategy
def
init
(
self
,
context
):
self
.
model
.
input
()
self
.
model
.
net
()
self
.
model
.
metrics
()
self
.
model
.
avg_loss
()
self
.
model
.
train_net
()
optimizer
=
self
.
model
.
optimizer
()
strategy
=
self
.
build_strategy
()
optimizer
=
fleet
.
distributed_optimizer
(
optimizer
,
strategy
)
optimizer
.
minimize
(
self
.
model
.
_cost
)
optimizer
.
minimize
(
self
.
model
.
get_cost_op
()
)
if
fleet
.
is_server
():
context
[
'status'
]
=
'server_pass'
...
...
fleetrec/trainer/single_trainer.py
浏览文件 @
eb04c187
...
...
@@ -37,12 +37,9 @@ class SingleTrainer(TranspileTrainer):
self
.
regist_context_processor
(
'terminal_pass'
,
self
.
terminal
)
def
init
(
self
,
context
):
self
.
model
.
input
()
self
.
model
.
net
()
self
.
model
.
metrics
()
self
.
model
.
avg_loss
()
self
.
model
.
train_net
()
optimizer
=
self
.
model
.
optimizer
()
optimizer
.
minimize
(
self
.
model
.
_cost
)
optimizer
.
minimize
(
(
self
.
model
.
get_cost_op
())
)
self
.
fetch_vars
=
[]
self
.
fetch_alias
=
[]
...
...
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