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PaddleRec
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e5af9cad
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体验新版 GitCode,发现更多精彩内容 >>
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e5af9cad
编写于
5月 21, 2020
作者:
D
Dong Daxiang
提交者:
GitHub
5月 21, 2020
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差异文件
Merge pull request #13 from seiriosPlus/delete_unused_trainer
Delete unused trainer
上级
633ecc2c
780ccefa
变更
3
展开全部
隐藏空白更改
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并排
Showing
3 changed file
with
1 addition
and
676 deletion
+1
-676
core/reader.py
core/reader.py
+1
-0
core/trainers/ctr_coding_trainer.py
core/trainers/ctr_coding_trainer.py
+0
-142
core/trainers/ctr_modul_trainer.py
core/trainers/ctr_modul_trainer.py
+0
-534
未找到文件。
core/reader.py
浏览文件 @
e5af9cad
...
@@ -40,6 +40,7 @@ class Reader(dg.MultiSlotDataGenerator):
...
@@ -40,6 +40,7 @@ class Reader(dg.MultiSlotDataGenerator):
@
abc
.
abstractmethod
@
abc
.
abstractmethod
def
init
(
self
):
def
init
(
self
):
"""init"""
pass
pass
@
abc
.
abstractmethod
@
abc
.
abstractmethod
...
...
core/trainers/ctr_coding_trainer.py
已删除
100755 → 0
浏览文件 @
633ecc2c
# 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
os
import
numpy
as
np
import
paddle.fluid
as
fluid
from
paddle.fluid.incubate.fleet.parameter_server.pslib
import
fleet
from
paddle.fluid.incubate.fleet.base.role_maker
import
MPISymetricRoleMaker
from
paddlerec.core.utils
import
envs
from
paddlerec.core.trainer
import
Trainer
class
CtrTrainer
(
Trainer
):
"""R
"""
def
__init__
(
self
,
config
):
"""R
"""
Trainer
.
__init__
(
self
,
config
)
self
.
global_config
=
config
self
.
_metrics
=
{}
self
.
processor_register
()
def
processor_register
(
self
):
role
=
MPISymetricRoleMaker
()
fleet
.
init
(
role
)
if
fleet
.
is_server
():
self
.
regist_context_processor
(
'uninit'
,
self
.
instance
)
self
.
regist_context_processor
(
'init_pass'
,
self
.
init
)
self
.
regist_context_processor
(
'server_pass'
,
self
.
server
)
else
:
self
.
regist_context_processor
(
'uninit'
,
self
.
instance
)
self
.
regist_context_processor
(
'init_pass'
,
self
.
init
)
self
.
regist_context_processor
(
'train_pass'
,
self
.
train
)
self
.
regist_context_processor
(
'terminal_pass'
,
self
.
terminal
)
def
_get_dataset
(
self
):
namespace
=
"train.reader"
inputs
=
self
.
model
.
get_inputs
()
threads
=
envs
.
get_global_env
(
"train.threads"
,
None
)
batch_size
=
envs
.
get_global_env
(
"batch_size"
,
None
,
namespace
)
reader_class
=
envs
.
get_global_env
(
"class"
,
None
,
namespace
)
abs_dir
=
os
.
path
.
dirname
(
os
.
path
.
abspath
(
__file__
))
reader
=
os
.
path
.
join
(
abs_dir
,
'../utils'
,
'dataset_instance.py'
)
pipe_cmd
=
"python {} {} {} {}"
.
format
(
reader
,
reader_class
,
"TRAIN"
,
self
.
_config_yaml
)
train_data_path
=
envs
.
get_global_env
(
"train_data_path"
,
None
,
namespace
)
dataset
=
fluid
.
DatasetFactory
().
create_dataset
()
dataset
.
set_use_var
(
inputs
)
dataset
.
set_pipe_command
(
pipe_cmd
)
dataset
.
set_batch_size
(
batch_size
)
dataset
.
set_thread
(
threads
)
file_list
=
[
os
.
path
.
join
(
train_data_path
,
x
)
for
x
in
os
.
listdir
(
train_data_path
)
]
dataset
.
set_filelist
(
file_list
)
return
dataset
def
instance
(
self
,
context
):
models
=
envs
.
get_global_env
(
"train.model.models"
)
model_class
=
envs
.
lazy_instance_by_fliename
(
models
,
"Model"
)
self
.
model
=
model_class
(
None
)
context
[
'status'
]
=
'init_pass'
def
init
(
self
,
context
):
"""R
"""
self
.
model
.
train_net
()
optimizer
=
self
.
model
.
optimizer
()
optimizer
=
fleet
.
distributed_optimizer
(
optimizer
,
strategy
=
{
"use_cvm"
:
False
})
optimizer
.
minimize
(
self
.
model
.
get_avg_cost
())
if
fleet
.
is_server
():
context
[
'status'
]
=
'server_pass'
else
:
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
server
(
self
,
context
):
fleet
.
run_server
()
fleet
.
stop_worker
()
context
[
'is_exit'
]
=
True
def
train
(
self
,
context
):
self
.
_exe
.
run
(
fluid
.
default_startup_program
())
fleet
.
init_worker
()
dataset
=
self
.
_get_dataset
()
shuf
=
np
.
array
([
fleet
.
worker_index
()])
gs
=
shuf
*
0
fleet
.
_role_maker
.
_node_type_comm
.
Allreduce
(
shuf
,
gs
)
print
(
"trainer id: {}, trainers: {}, gs: {}"
.
format
(
fleet
.
worker_index
(
),
fleet
.
worker_num
(),
gs
))
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
[
'status'
]
=
'terminal_pass'
fleet
.
stop_worker
()
def
terminal
(
self
,
context
):
print
(
"terminal ended."
)
context
[
'is_exit'
]
=
True
core/trainers/ctr_modul_trainer.py
已删除
100755 → 0
浏览文件 @
633ecc2c
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