train_infer_python.txt 1.8 KB
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===========================train_params===========================
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model_name:StyleGANv2
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python:python3.7
gpu_list:0
##
auto_cast:null
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total_iters:lite_train_lite_infer=10|lite_train_whole_infer=10|whole_train_whole_infer=800
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output_dir:./output/
dataset.train.batch_size:lite_train_lite_infer=3|whole_train_whole_infer=3
pretrained_model:null
train_model_name:stylegan_v2_256_ffhq*/*checkpoint.pdparams
train_infer_img_dir:null
null:null
##
trainer:norm_train
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norm_train:tools/main.py -c configs/stylegan_v2_256_ffhq.yaml --seed 123 -o dataset.train.num_workers=0 log_config.interval=1 snapshot_config.interval=10
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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/stylegan_v2_256_ffhq.yaml  --inputs_size="1,1,512;1,1"  --model_name inference --load 
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quant_export:null 
fpgm_export:null
distill_export:null
export1:null
export2:null
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inference_dir:inference
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train_model:./inference/stylegan2/stylegan2model_gen
infer_export:null
infer_quant:False
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inference:tools/inference.py --model_type stylegan2 --seed 123 -c configs/stylegan_v2_256_ffhq.yaml --output_path test_tipc/output/
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--device:gpu
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--model_path:
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--benchmark:True
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===========================train_benchmark_params==========================
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batch_size:8
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fp_items:fp32
epoch:100
--profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
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flags:null
===========================infer_benchmark_params==========================
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random_infer_input:[{float32,[1, 512]},{float32,[1]}]