train_infer_python.txt 1.6 KB
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===========================train_params===========================
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model_name:Pix2pix
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python:python3.7
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gpu_list:0
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##
auto_cast:null
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epochs:lite_train_lite_infer=10|whole_train_whole_infer=200
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output_dir:./output/
dataset.train.batch_size:lite_train_lite_infer=1|whole_train_whole_infer=1
pretrained_model:null
train_model_name:pix2pix_facades*/*checkpoint.pdparams
train_infer_img_dir:./data/facades/test
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##
trainer:norm_train
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norm_train:tools/main.py -c configs/pix2pix_facades.yaml --seed 123 -o dataset.train.num_workers=0 log_config.interval=1
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pact_train:null
fpgm_train:null
distill_train:null
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##
===========================eval_params=========================== 
eval:null
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##
===========================infer_params===========================
--output_dir:./output/
load:null
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norm_export:tools/export_model.py -c configs/pix2pix_facades.yaml --inputs_size="-1,3,-1,-1" --load 
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quant_export:null 
fpgm_export:null
distill_export:null
export1:null
export2:null
inference_dir:pix2pixmodel_netG
train_model:./inference/pix2pix_facade/pix2pixmodel_netG
infer_export:null
infer_quant:False
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inference:tools/inference.py --model_type pix2pix --seed 123 -c configs/pix2pix_facades.yaml --output_path test_tipc/output/
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--device:cpu
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--model_path:
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--benchmark:True
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===========================train_benchmark_params==========================
batch_size:1
fp_items:fp32
epoch:10
--profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
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flags:null