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体验新版 GitCode,发现更多精彩内容 >>
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5a462155
编写于
12月 14, 2021
作者:
L
LDOUBLEV
浏览文件
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差异文件
fix nonfinte
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96a5f32b
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3
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Showing
3 changed file
with
5 addition
and
12 deletion
+5
-12
test_tipc/configs/ch_PP-OCRv2_det_PACT/train_infer_python.txt
..._tipc/configs/ch_PP-OCRv2_det_PACT/train_infer_python.txt
+1
-1
test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/train_infer_python.txt
...figs/ch_ppocr_mobile_v2.0_det_PACT/train_infer_python.txt
+3
-3
test_tipc/test_train_inference_python.sh
test_tipc/test_train_inference_python.sh
+1
-8
未找到文件。
test_tipc/configs/ch_PP-OCRv2_det_PACT/train_infer_python.txt
浏览文件 @
5a462155
...
@@ -26,7 +26,7 @@ null:null
...
@@ -26,7 +26,7 @@ null:null
##
##
===========================infer_params===========================
===========================infer_params===========================
Global.save_inference_dir:./output/
Global.save_inference_dir:./output/
Global.
pretrained_model
:
Global.
checkpoints
:
norm_export:null
norm_export:null
quant_export:deploy/slim/quantization/export_model.py -c configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.yml -o
quant_export:deploy/slim/quantization/export_model.py -c configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.yml -o
fpgm_export:
fpgm_export:
...
...
test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/train_infer_python.txt
浏览文件 @
5a462155
...
@@ -4,7 +4,7 @@ python:python3.7
...
@@ -4,7 +4,7 @@ python:python3.7
gpu_list:0|0,1
gpu_list:0|0,1
Global.use_gpu:True|True
Global.use_gpu:True|True
Global.auto_cast:null
Global.auto_cast:null
Global.epoch_num:lite_train_lite_infer=
5
|whole_train_whole_infer=300
Global.epoch_num:lite_train_lite_infer=
20
|whole_train_whole_infer=300
Global.save_model_dir:./output/
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4
Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4
Global.pretrained_model:null
Global.pretrained_model:null
...
@@ -26,7 +26,7 @@ null:null
...
@@ -26,7 +26,7 @@ null:null
##
##
===========================infer_params===========================
===========================infer_params===========================
Global.save_inference_dir:./output/
Global.save_inference_dir:./output/
Global.
pretrained_model
:
Global.
checkpoints
:
norm_export:null
norm_export:null
quant_export:deploy/slim/quantization/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
quant_export:deploy/slim/quantization/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
fpgm_export:null
fpgm_export:null
...
@@ -48,4 +48,4 @@ inference:tools/infer/predict_det.py
...
@@ -48,4 +48,4 @@ inference:tools/infer/predict_det.py
--image_dir:./inference/ch_det_data_50/all-sum-510/
--image_dir:./inference/ch_det_data_50/all-sum-510/
null:null
null:null
--benchmark:True
--benchmark:True
null:null
null:null
\ No newline at end of file
test_tipc/test_train_inference_python.sh
浏览文件 @
5a462155
...
@@ -322,10 +322,6 @@ else
...
@@ -322,10 +322,6 @@ else
save_log
=
"
${
LOG_PATH
}
/
${
trainer
}
_gpus_
${
gpu
}
_autocast_
${
autocast
}
_nodes_
${
nodes
}
"
save_log
=
"
${
LOG_PATH
}
/
${
trainer
}
_gpus_
${
gpu
}
_autocast_
${
autocast
}
_nodes_
${
nodes
}
"
fi
fi
# load pretrain from norm training if current trainer is pact or fpgm trainer
if
([
${
trainer
}
=
${
pact_key
}
]
||
[
${
trainer
}
=
${
fpgm_key
}
])
&&
[
${
nodes
}
-le
1
]
;
then
set_pretrain
=
"
${
load_norm_train_model
}
"
fi
set_save_model
=
$(
func_set_params
"
${
save_model_key
}
"
"
${
save_log
}
"
)
set_save_model
=
$(
func_set_params
"
${
save_model_key
}
"
"
${
save_log
}
"
)
if
[
${#
gpu
}
-le
2
]
;
then
# train with cpu or single gpu
if
[
${#
gpu
}
-le
2
]
;
then
# train with cpu or single gpu
...
@@ -341,10 +337,7 @@ else
...
@@ -341,10 +337,7 @@ else
status_check
$?
"
${
cmd
}
"
"
${
status_log
}
"
status_check
$?
"
${
cmd
}
"
"
${
status_log
}
"
set_eval_pretrain
=
$(
func_set_params
"
${
pretrain_model_key
}
"
"
${
save_log
}
/
${
train_model_name
}
"
)
set_eval_pretrain
=
$(
func_set_params
"
${
pretrain_model_key
}
"
"
${
save_log
}
/
${
train_model_name
}
"
)
# save norm trained models to set pretrain for pact training and fpgm training
if
[
${
trainer
}
=
${
trainer_norm
}
]
&&
[
${
nodes
}
-le
1
]
;
then
load_norm_train_model
=
${
set_eval_pretrain
}
fi
# run eval
# run eval
if
[
${
eval_py
}
!=
"null"
]
;
then
if
[
${
eval_py
}
!=
"null"
]
;
then
set_eval_params1
=
$(
func_set_params
"
${
eval_key1
}
"
"
${
eval_value1
}
"
)
set_eval_params1
=
$(
func_set_params
"
${
eval_key1
}
"
"
${
eval_value1
}
"
)
...
...
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