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ML
ffm-baseline
Commits
ca517060
Commit
ca517060
authored
Apr 12, 2019
by
王志伟
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测试知识图谱的数据,测试60天
parent
9fc4a68d
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3 deletions
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-3
feature.py
tensnsorflow/es/feature.py
+1
-1
submit.sh
tensnsorflow/es/submit.sh
+2
-2
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tensnsorflow/es/feature.py
View file @
ca517060
...
...
@@ -32,7 +32,7 @@ def get_data():
validate_date
=
con_sql
(
db
,
sql
)[
0
]
.
values
.
tolist
()[
0
]
print
(
"validate_date:"
+
validate_date
)
temp
=
datetime
.
datetime
.
strptime
(
validate_date
,
"
%
Y-
%
m-
%
d"
)
start
=
(
temp
-
datetime
.
timedelta
(
days
=
30
))
.
strftime
(
"
%
Y-
%
m-
%
d"
)
start
=
(
temp
-
datetime
.
timedelta
(
days
=
30
0
))
.
strftime
(
"
%
Y-
%
m-
%
d"
)
print
(
start
)
db
=
pymysql
.
connect
(
host
=
'10.66.157.22'
,
port
=
4000
,
user
=
'root'
,
passwd
=
'3SYz54LS9#^9sBvC'
,
db
=
'jerry_test'
)
sql
=
"select e.y,e.z,e.stat_date,e.ucity_id,feat.level2_ids,e.ccity_name,u.device_type,u.manufacturer,"
\
...
...
tensnsorflow/es/submit.sh
View file @
ca517060
...
...
@@ -36,11 +36,11 @@ ${PYTHON_PATH} ${MODEL_PATH}/train.py --ctr_task_wgt=0.5 --learning_rate=0.0001
echo
"infer native..."
${
PYTHON_PATH
}
${
MODEL_PATH
}
/train.py
--ctr_task_wgt
=
0.5
--learning_rate
=
0.0001
--deep_layers
=
512,256,128,64,32
--dropout
=
0.3,0.3,0.3,0.3,0.3
--optimizer
=
Adam
--num_epochs
=
1
--embedding_size
=
16
--batch_size
=
1024
--field_size
=
8
--feature_size
=
300000
--l2_reg
=
0.005
--log_steps
=
100
--num_threads
=
36
--model_dir
=
${
DATA_PATH
}
/model_ckpt/DeepCvrMTL/
--data_dir
=
${
DATA_PATH
}
/native
--task_type
=
infer
>
${
DATA_PATH
}
/native_infer.log
${
PYTHON_PATH
}
${
MODEL_PATH
}
/train.py
--ctr_task_wgt
=
0.5
--learning_rate
=
0.0001
--deep_layers
=
512,256,128,64,32
--dropout
=
0.3,0.3,0.3,0.3,0.3
--optimizer
=
Adam
--num_epochs
=
1
--embedding_size
=
16
--batch_size
=
1024
--field_size
=
15
--feature_size
=
300000
--l2_reg
=
0.005
--log_steps
=
100
--num_threads
=
36
--model_dir
=
${
DATA_PATH
}
/model_ckpt/DeepCvrMTL/
--data_dir
=
${
DATA_PATH
}
/native
--task_type
=
infer
>
${
DATA_PATH
}
/native_infer.log
echo
"infer nearby..."
${
PYTHON_PATH
}
${
MODEL_PATH
}
/train.py
--ctr_task_wgt
=
0.5
--learning_rate
=
0.0001
--deep_layers
=
512,256,128,64,32
--dropout
=
0.3,0.3,0.3,0.3,0.3
--optimizer
=
Adam
--num_epochs
=
1
--embedding_size
=
16
--batch_size
=
1024
--field_size
=
8
--feature_size
=
300000
--l2_reg
=
0.005
--log_steps
=
100
--num_threads
=
36
--model_dir
=
${
DATA_PATH
}
/model_ckpt/DeepCvrMTL/
--data_dir
=
${
DATA_PATH
}
/nearby
--task_type
=
infer
>
${
DATA_PATH
}
/nearby_infer.log
${
PYTHON_PATH
}
${
MODEL_PATH
}
/train.py
--ctr_task_wgt
=
0.5
--learning_rate
=
0.0001
--deep_layers
=
512,256,128,64,32
--dropout
=
0.3,0.3,0.3,0.3,0.3
--optimizer
=
Adam
--num_epochs
=
1
--embedding_size
=
16
--batch_size
=
1024
--field_size
=
15
--feature_size
=
300000
--l2_reg
=
0.005
--log_steps
=
100
--num_threads
=
36
--model_dir
=
${
DATA_PATH
}
/model_ckpt/DeepCvrMTL/
--data_dir
=
${
DATA_PATH
}
/nearby
--task_type
=
infer
>
${
DATA_PATH
}
/nearby_infer.log
echo
"sort and 2sql"
${
PYTHON_PATH
}
${
MODEL_PATH
}
/to_database.py
>
${
DATA_PATH
}
/insert_database.log
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