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a3ddeec0
编写于
5月 29, 2020
作者:
X
xjqbest
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix
上级
a09255fb
变更
5
显示空白变更内容
内联
并排
Showing
5 changed file
with
18 addition
and
16 deletion
+18
-16
core/reader.py
core/reader.py
+4
-2
core/trainers/single_infer.py
core/trainers/single_infer.py
+6
-6
core/trainers/single_trainer.py
core/trainers/single_trainer.py
+3
-3
core/utils/dataset_instance.py
core/utils/dataset_instance.py
+2
-2
models/rank/dnn/model.py
models/rank/dnn/model.py
+3
-3
未找到文件。
core/reader.py
浏览文件 @
a3ddeec0
...
@@ -59,10 +59,12 @@ class SlotReader(dg.MultiSlotDataGenerator):
...
@@ -59,10 +59,12 @@ class SlotReader(dg.MultiSlotDataGenerator):
def
init
(
self
,
sparse_slots
,
dense_slots
,
padding
=
0
):
def
init
(
self
,
sparse_slots
,
dense_slots
,
padding
=
0
):
from
operator
import
mul
from
operator
import
mul
self
.
sparse_slots
=
[]
self
.
sparse_slots
=
[]
if
sparse_slots
.
strip
()
!=
"#"
:
if
sparse_slots
.
strip
()
!=
"#"
and
sparse_slots
.
strip
(
)
!=
"?"
and
sparse_slots
.
strip
()
!=
""
:
self
.
sparse_slots
=
sparse_slots
.
strip
().
split
(
" "
)
self
.
sparse_slots
=
sparse_slots
.
strip
().
split
(
" "
)
self
.
dense_slots
=
[]
self
.
dense_slots
=
[]
if
dense_slots
.
strip
()
!=
"#"
:
if
dense_slots
.
strip
()
!=
"#"
and
dense_slots
.
strip
(
)
!=
"?"
and
dense_slots
.
strip
()
!=
""
:
self
.
dense_slots
=
dense_slots
.
strip
().
split
(
" "
)
self
.
dense_slots
=
dense_slots
.
strip
().
split
(
" "
)
self
.
dense_slots_shape
=
[
self
.
dense_slots_shape
=
[
reduce
(
mul
,
reduce
(
mul
,
...
...
core/trainers/single_infer.py
浏览文件 @
a3ddeec0
...
@@ -78,14 +78,14 @@ class SingleInfer(TranspileTrainer):
...
@@ -78,14 +78,14 @@ class SingleInfer(TranspileTrainer):
pipe_cmd
=
"python {} {} {} {}"
.
format
(
reader
,
reader_class
,
pipe_cmd
=
"python {} {} {} {}"
.
format
(
reader
,
reader_class
,
"TRAIN"
,
self
.
_config_yaml
)
"TRAIN"
,
self
.
_config_yaml
)
else
:
else
:
if
sparse_slots
is
None
:
if
sparse_slots
==
""
:
sparse_slots
=
"
#
"
sparse_slots
=
"
?
"
if
dense_slots
is
None
:
if
dense_slots
==
""
:
dense_slots
=
"
#
"
dense_slots
=
"
?
"
padding
=
envs
.
get_global_env
(
name
+
"padding"
,
0
)
padding
=
envs
.
get_global_env
(
name
+
"padding"
,
0
)
pipe_cmd
=
"python {} {} {} {} {} {} {} {}"
.
format
(
pipe_cmd
=
"python {} {} {} {} {} {} {} {}"
.
format
(
reader
,
"slot"
,
"slot"
,
self
.
_config_yaml
,
"fake"
,
\
reader
,
"slot"
,
"slot"
,
self
.
_config_yaml
,
"fake"
,
\
sparse_slots
.
replace
(
" "
,
"
#"
),
dense_slots
.
replace
(
" "
,
"#
"
),
str
(
padding
))
sparse_slots
.
replace
(
" "
,
"
?"
),
dense_slots
.
replace
(
" "
,
"?
"
),
str
(
padding
))
dataset
=
fluid
.
DatasetFactory
().
create_dataset
()
dataset
=
fluid
.
DatasetFactory
().
create_dataset
()
dataset
.
set_batch_size
(
envs
.
get_global_env
(
name
+
"batch_size"
))
dataset
.
set_batch_size
(
envs
.
get_global_env
(
name
+
"batch_size"
))
...
@@ -290,7 +290,7 @@ class SingleInfer(TranspileTrainer):
...
@@ -290,7 +290,7 @@ class SingleInfer(TranspileTrainer):
def
load
(
self
,
is_fleet
=
False
):
def
load
(
self
,
is_fleet
=
False
):
name
=
"runner."
+
self
.
_runner_name
+
"."
name
=
"runner."
+
self
.
_runner_name
+
"."
dirname
=
envs
.
get_global_env
(
"epoch.
init_model_path"
,
None
)
dirname
=
envs
.
get_global_env
(
name
+
"
init_model_path"
,
None
)
if
dirname
is
None
or
dirname
==
""
:
if
dirname
is
None
or
dirname
==
""
:
return
return
print
(
"single_infer going to load "
,
dirname
)
print
(
"single_infer going to load "
,
dirname
)
...
...
core/trainers/single_trainer.py
浏览文件 @
a3ddeec0
...
@@ -73,13 +73,13 @@ class SingleTrainer(TranspileTrainer):
...
@@ -73,13 +73,13 @@ class SingleTrainer(TranspileTrainer):
"TRAIN"
,
self
.
_config_yaml
)
"TRAIN"
,
self
.
_config_yaml
)
else
:
else
:
if
sparse_slots
==
""
:
if
sparse_slots
==
""
:
sparse_slots
=
"
#
"
sparse_slots
=
"
?
"
if
dense_slots
==
""
:
if
dense_slots
==
""
:
dense_slots
=
"
#
"
dense_slots
=
"
?
"
padding
=
envs
.
get_global_env
(
name
+
"padding"
,
0
)
padding
=
envs
.
get_global_env
(
name
+
"padding"
,
0
)
pipe_cmd
=
"python {} {} {} {} {} {} {} {}"
.
format
(
pipe_cmd
=
"python {} {} {} {} {} {} {} {}"
.
format
(
reader
,
"slot"
,
"slot"
,
self
.
_config_yaml
,
"fake"
,
\
reader
,
"slot"
,
"slot"
,
self
.
_config_yaml
,
"fake"
,
\
sparse_slots
.
replace
(
" "
,
"
#"
),
dense_slots
.
replace
(
" "
,
"#
"
),
str
(
padding
))
sparse_slots
.
replace
(
" "
,
"
?"
),
dense_slots
.
replace
(
" "
,
"?
"
),
str
(
padding
))
dataset
=
fluid
.
DatasetFactory
().
create_dataset
()
dataset
=
fluid
.
DatasetFactory
().
create_dataset
()
dataset
.
set_batch_size
(
envs
.
get_global_env
(
name
+
"batch_size"
))
dataset
.
set_batch_size
(
envs
.
get_global_env
(
name
+
"batch_size"
))
...
...
core/utils/dataset_instance.py
浏览文件 @
a3ddeec0
...
@@ -32,8 +32,8 @@ elif sys.argv[2].upper() == "EVALUATE":
...
@@ -32,8 +32,8 @@ elif sys.argv[2].upper() == "EVALUATE":
else
:
else
:
reader_name
=
"SlotReader"
reader_name
=
"SlotReader"
namespace
=
sys
.
argv
[
4
]
namespace
=
sys
.
argv
[
4
]
sparse_slots
=
sys
.
argv
[
5
].
replace
(
"
#
"
,
" "
)
sparse_slots
=
sys
.
argv
[
5
].
replace
(
"
?
"
,
" "
)
dense_slots
=
sys
.
argv
[
6
].
replace
(
"
#
"
,
" "
)
dense_slots
=
sys
.
argv
[
6
].
replace
(
"
?
"
,
" "
)
padding
=
int
(
sys
.
argv
[
7
])
padding
=
int
(
sys
.
argv
[
7
])
yaml_abs_path
=
sys
.
argv
[
3
]
yaml_abs_path
=
sys
.
argv
[
3
]
...
...
models/rank/dnn/model.py
浏览文件 @
a3ddeec0
...
@@ -36,7 +36,7 @@ class Model(ModelBase):
...
@@ -36,7 +36,7 @@ class Model(ModelBase):
def
net
(
self
,
input
,
is_infer
=
False
):
def
net
(
self
,
input
,
is_infer
=
False
):
self
.
sparse_inputs
=
self
.
_sparse_data_var
[
1
:]
self
.
sparse_inputs
=
self
.
_sparse_data_var
[
1
:]
self
.
dense_input
=
self
.
_dense_data_var
[
0
]
self
.
dense_input
=
[]
#
self._dense_data_var[0]
self
.
label_input
=
self
.
_sparse_data_var
[
0
]
self
.
label_input
=
self
.
_sparse_data_var
[
0
]
def
embedding_layer
(
input
):
def
embedding_layer
(
input
):
...
@@ -52,8 +52,8 @@ class Model(ModelBase):
...
@@ -52,8 +52,8 @@ class Model(ModelBase):
return
emb_sum
return
emb_sum
sparse_embed_seq
=
list
(
map
(
embedding_layer
,
self
.
sparse_inputs
))
sparse_embed_seq
=
list
(
map
(
embedding_layer
,
self
.
sparse_inputs
))
concated
=
fluid
.
layers
.
concat
(
concated
=
fluid
.
layers
.
concat
(
sparse_embed_seq
,
axis
=
1
)
sparse_embed_seq
+
[
self
.
dense_input
],
axis
=
1
)
#
sparse_embed_seq + [self.dense_input], axis=1)
fcs
=
[
concated
]
fcs
=
[
concated
]
hidden_layers
=
envs
.
get_global_env
(
"hyper_parameters.fc_sizes"
)
hidden_layers
=
envs
.
get_global_env
(
"hyper_parameters.fc_sizes"
)
...
...
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