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一只大灰猫
PaddleRec
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65909976
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65909976
编写于
4月 29, 2020
作者:
T
tangwei
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差异文件
add windons/mac support
上级
5d92ae8f
变更
9
隐藏空白更改
内联
并排
Showing
9 changed file
with
140 addition
and
9 deletion
+140
-9
fleetrec/core/model.py
fleetrec/core/model.py
+1
-0
fleetrec/core/trainers/cluster_trainer.py
fleetrec/core/trainers/cluster_trainer.py
+9
-2
fleetrec/core/trainers/ctr_coding_trainer.py
fleetrec/core/trainers/ctr_coding_trainer.py
+1
-1
fleetrec/core/trainers/single_trainer.py
fleetrec/core/trainers/single_trainer.py
+49
-4
fleetrec/core/trainers/transpiler_trainer.py
fleetrec/core/trainers/transpiler_trainer.py
+17
-2
fleetrec/core/utils/dataloader_instance.py
fleetrec/core/utils/dataloader_instance.py
+53
-0
fleetrec/core/utils/dataset_instance.py
fleetrec/core/utils/dataset_instance.py
+0
-0
fleetrec/models/ctr/dnn/model.py
fleetrec/models/ctr/dnn/model.py
+2
-0
fleetrec/run.py
fleetrec/run.py
+8
-0
未找到文件。
fleetrec/core/model.py
浏览文件 @
65909976
...
...
@@ -12,6 +12,7 @@ class Model(object):
self
.
_cost
=
None
self
.
_metrics
=
{}
self
.
_data_var
=
[]
self
.
_data_loader
=
None
self
.
_fetch_interval
=
20
self
.
_namespace
=
"train.model"
...
...
fleetrec/core/trainers/cluster_trainer.py
浏览文件 @
65909976
...
...
@@ -39,7 +39,11 @@ class ClusterTrainer(TranspileTrainer):
else
:
self
.
regist_context_processor
(
'uninit'
,
self
.
instance
)
self
.
regist_context_processor
(
'init_pass'
,
self
.
init
)
self
.
regist_context_processor
(
'train_pass'
,
self
.
train
)
if
envs
.
get_platform
()
==
"LINUX"
:
self
.
regist_context_processor
(
'train_pass'
,
self
.
dataset_train
)
else
:
self
.
regist_context_processor
(
'train_pass'
,
self
.
dataloader_train
)
self
.
regist_context_processor
(
'terminal_pass'
,
self
.
terminal
)
def
build_strategy
(
self
):
...
...
@@ -87,7 +91,10 @@ class ClusterTrainer(TranspileTrainer):
fleet
.
run_server
()
context
[
'is_exit'
]
=
True
def
train
(
self
,
context
):
def
dataloader_train
(
self
,
context
):
pass
def
dataset_train
(
self
,
context
):
self
.
_exe
.
run
(
fleet
.
startup_program
)
fleet
.
init_worker
()
...
...
fleetrec/core/trainers/ctr_coding_trainer.py
浏览文件 @
65909976
...
...
@@ -57,7 +57,7 @@ class CtrPaddleTrainer(Trainer):
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'
,
'
reader
_instance.py'
)
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
)
...
...
fleetrec/core/trainers/single_trainer.py
浏览文件 @
65909976
...
...
@@ -22,6 +22,7 @@ import paddle.fluid as fluid
from
fleetrec.core.trainers.transpiler_trainer
import
TranspileTrainer
from
fleetrec.core.utils
import
envs
import
numpy
as
np
logging
.
basicConfig
(
format
=
"%(asctime)s - %(levelname)s - %(message)s"
)
logger
=
logging
.
getLogger
(
"fluid"
)
...
...
@@ -32,7 +33,12 @@ class SingleTrainer(TranspileTrainer):
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
)
if
envs
.
get_platform
()
==
"LINUX"
:
self
.
regist_context_processor
(
'train_pass'
,
self
.
dataset_train
)
else
:
self
.
regist_context_processor
(
'train_pass'
,
self
.
dataloader_train
)
self
.
regist_context_processor
(
'infer_pass'
,
self
.
infer
)
self
.
regist_context_processor
(
'terminal_pass'
,
self
.
terminal
)
...
...
@@ -51,12 +57,51 @@ class SingleTrainer(TranspileTrainer):
self
.
fetch_alias
=
metrics
.
keys
()
context
[
'status'
]
=
'train_pass'
def
train
(
self
,
context
):
# run startup program at once
def
dataloader_train
(
self
,
context
):
self
.
_exe
.
run
(
fluid
.
default_startup_program
())
reader
=
self
.
_get_dataloader
()
epochs
=
envs
.
get_global_env
(
"train.epochs"
)
dataset
=
self
.
_get_dataset
()
program
=
fluid
.
compiler
.
CompiledProgram
(
fluid
.
default_main_program
()).
with_data_parallel
(
loss_name
=
self
.
model
.
get_cost_op
.
name
)
metrics_varnames
=
[]
metrics_format
=
[]
metrics_format
.
append
(
"{}: {{}}"
.
format
(
"epoch"
))
metrics_format
.
append
(
"{}: {{}}"
.
format
(
"batch"
))
for
name
,
var
in
self
.
model
.
get_metrics
().
items
():
metrics_format
.
append
(
"{}: {{}}"
.
format
(
name
))
metrics_format
=
", "
.
join
(
metrics_format
)
for
epoch
in
range
(
epochs
):
reader
.
start
()
batch_id
=
0
try
:
while
True
:
metrics_rets
=
self
.
_exe
.
run
(
program
=
program
,
fetch_list
=
metrics_varnames
)
metrics_rets
=
np
.
mean
(
metrics_rets
,
axis
=
0
)
metrics
=
[
epoch
,
batch_id
]
metrics
.
extend
(
metrics_rets
.
tolist
())
if
batch_id
%
10
==
0
and
batch_id
!=
0
:
print
(
metrics_format
.
format
(
metrics
))
batch_id
+=
1
except
fluid
.
core
.
EOFException
:
reader
.
reset
()
context
[
'status'
]
=
'infer_pass'
def
dataset_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
):
...
...
fleetrec/core/trainers/transpiler_trainer.py
浏览文件 @
65909976
...
...
@@ -22,6 +22,7 @@ from paddle.fluid.incubate.fleet.parameter_server.distribute_transpiler import f
from
fleetrec.core.trainer
import
Trainer
from
fleetrec.core.utils
import
envs
from
fleetrec.core.utils
import
dataloader_instance
class
TranspileTrainer
(
Trainer
):
...
...
@@ -35,6 +36,16 @@ class TranspileTrainer(Trainer):
def
processor_register
(
self
):
print
(
"Need implement by trainer, `self.regist_context_processor('uninit', self.instance)` must be the first"
)
def
_get_dataloader
(
self
):
namespace
=
"train.reader"
dataloader
=
self
.
model
.
_data_loader
batch_size
=
envs
.
get_global_env
(
"batch_size"
,
None
,
namespace
)
reader_class
=
envs
.
get_global_env
(
"class"
,
None
,
namespace
)
reader
=
dataloader_instance
.
dataloader
(
reader_class
,
"TRAIN"
,
self
.
_config_yaml
)
dataloader
.
set_sample_generator
(
reader
,
batch_size
)
return
dataloader
def
_get_dataset
(
self
):
namespace
=
"train.reader"
...
...
@@ -43,7 +54,7 @@ class TranspileTrainer(Trainer):
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'
,
'
reader
_instance.py'
)
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
)
...
...
@@ -123,7 +134,11 @@ class TranspileTrainer(Trainer):
print
(
"Need to be implement"
)
context
[
'is_exit'
]
=
True
def
train
(
self
,
context
):
def
dataloader_train
(
self
,
context
):
print
(
"Need to be implement"
)
context
[
'is_exit'
]
=
True
def
dataset_train
(
self
,
context
):
print
(
"Need to be implement"
)
context
[
'is_exit'
]
=
True
...
...
fleetrec/core/utils/dataloader_instance.py
0 → 100644
浏览文件 @
65909976
# 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.
from
__future__
import
print_function
import
os
import
sys
from
fleetrec.core.utils.envs
import
lazy_instance
from
fleetrec.core.utils.envs
import
get_global_env
def
dataloader
(
readerclass
,
train
,
yaml_file
):
namespace
=
"train.reader"
if
train
==
"TRAIN"
:
reader_name
=
"TrainReader"
data_path
=
get_global_env
(
"train_data_path"
,
None
,
namespace
)
else
:
reader_name
=
"EvaluateReader"
data_path
=
get_global_env
(
"test_data_path"
,
None
,
namespace
)
files
=
[
str
(
data_path
)
+
"/%s"
%
x
for
x
in
os
.
listdir
(
data_path
)]
reader_class
=
lazy_instance
(
readerclass
,
reader_name
)
reader
=
reader_class
(
yaml_file
)
reader
.
init
()
def
gen_reader
():
for
file
in
files
:
with
open
(
file
,
'r'
)
as
f
:
for
line
in
f
:
line
=
line
.
rstrip
(
'
\n
'
).
split
(
'
\t
'
)
iter
=
reader
.
generate_sample
(
line
)
for
parsed_line
in
iter
():
if
parsed_line
is
None
:
continue
else
:
values
=
[]
for
pased
in
parsed_line
:
values
.
append
(
pased
[
1
])
yield
values
return
gen_reader
fleetrec/core/utils/
reader
_instance.py
→
fleetrec/core/utils/
dataset
_instance.py
浏览文件 @
65909976
文件已移动
fleetrec/models/ctr/dnn/model.py
浏览文件 @
65909976
...
...
@@ -57,6 +57,8 @@ class Model(ModelBase):
self
.
_data_var
.
append
(
input
)
self
.
_data_var
.
append
(
self
.
label_input
)
self
.
_data_loader
=
fluid
.
io
.
PyReader
(
feed_list
=
self
.
_data_var
,
capacity
=
64
,
use_double_buffer
=
False
,
iterable
=
False
)
def
net
(
self
):
trainer
=
envs
.
get_trainer
()
...
...
fleetrec/run.py
浏览文件 @
65909976
...
...
@@ -85,6 +85,7 @@ def single_engine(args):
single_envs
[
"train.trainer.threads"
]
=
"2"
single_envs
[
"train.trainer.engine"
]
=
"single"
single_envs
[
"train.trainer.device"
]
=
args
.
device
single_envs
[
"train.trainer.platform"
]
=
envs
.
get_platform
()
set_runtime_envs
(
single_envs
,
args
.
model
)
trainer
=
TrainerFactory
.
create
(
args
.
model
)
...
...
@@ -98,6 +99,7 @@ def cluster_engine(args):
cluster_envs
[
"train.trainer.trainer"
]
=
"ClusterTrainer"
cluster_envs
[
"train.trainer.engine"
]
=
"cluster"
cluster_envs
[
"train.trainer.device"
]
=
args
.
device
cluster_envs
[
"train.trainer.platform"
]
=
envs
.
get_platform
()
set_runtime_envs
(
cluster_envs
,
args
.
model
)
...
...
@@ -111,6 +113,7 @@ def cluster_mpi_engine(args):
cluster_envs
=
{}
cluster_envs
[
"train.trainer.trainer"
]
=
"CtrCodingTrainer"
cluster_envs
[
"train.trainer.device"
]
=
args
.
device
cluster_envs
[
"train.trainer.platform"
]
=
envs
.
get_platform
()
set_runtime_envs
(
cluster_envs
,
args
.
model
)
...
...
@@ -131,7 +134,10 @@ def local_cluster_engine(args):
cluster_envs
[
"train.trainer.strategy"
]
=
"async"
cluster_envs
[
"train.trainer.threads"
]
=
"2"
cluster_envs
[
"train.trainer.engine"
]
=
"local_cluster"
cluster_envs
[
"train.trainer.device"
]
=
args
.
device
cluster_envs
[
"train.trainer.platform"
]
=
envs
.
get_platform
()
cluster_envs
[
"CPU_NUM"
]
=
"2"
set_runtime_envs
(
cluster_envs
,
args
.
model
)
...
...
@@ -154,7 +160,9 @@ def local_mpi_engine(args):
cluster_envs
[
"train.trainer.trainer"
]
=
"CtrCodingTrainer"
cluster_envs
[
"log_dir"
]
=
"logs"
cluster_envs
[
"train.trainer.engine"
]
=
"local_cluster"
cluster_envs
[
"train.trainer.device"
]
=
args
.
device
cluster_envs
[
"train.trainer.platform"
]
=
envs
.
get_platform
()
set_runtime_envs
(
cluster_envs
,
args
.
model
)
launch
=
LocalMPIEngine
(
cluster_envs
,
args
.
model
)
...
...
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