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run_train_adain.sh
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run_train_adain.sh
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#!/bin/bash
source activate torch_0.4
PYTHON=/share/mini1/sw/std/python/anaconda3-2019.07/v3.7/envs/torch_0.4/bin/python
#$PYTHON main.py --wav_dir dump/wav16/
#exp=exp/0705stada_doub0/
root=/share/mini1/res/t/vc/studio/timap-en/vctk/
wav_dir=$root/resmp_wav22050/
mc_dir=$root/dump/0721mc_10spk_22050/
#mc_dir=$root/dump/0825mc_109spk_22050
#mc_dir=$root/dump/0915mc_109spk_22050_few_shot20
#mc_dir=$root/dump/0921mc_109spk_22050_few_shot5
num_spks=10
exp_root=/share/mini1/res/t/vc/studio/timap-en/vctk/exp/vc-gan/
#exp_name=0731stgan_gse_0/
exp_name=0924stgan3_0
#exp_name=0801stgan_gse_1/
#exp_name=0811stadain_map_2
exp=$exp_root/$exp_name
main_script=$root/vc_gan/main_stgan_adain.py
#main_script=$root/vc-gan/main_stgan_adain_gse.py
#main_script=$root/vc-gan/main_stgan_adain_r1.py
#main_script=$root/vc-gan/main_stadain_map.py
$PYTHON $main_script \
--device 1\
--wav_dir $wav_dir \
--model_save_dir ${exp}/ckpt/ \
--sample_step 10000 \
--model_save_step 10000\
--log_dir ${exp}/tb/\
--num_speakers $num_spks \
--train_data_dir $mc_dir/train \
--test_data_dir $mc_dir/test \
--sample_dir $exp/samples/ \
--num_workers 8 \
--n_critic 1\
--d_lr 0.0001\
--g_lr 0.0002\
--lambda_id 2 \
--lambda_gp 1.0 \
--lambda_rec 4 \
--lambda_adv 1 \
--lambda_spid 1 \
--lambda_cls 0.0 \
--min_length 256 \
--test_src_spk p232 \
--test_trg_spk p293 \
--sampling_rate 22050 \
--speaker_path $mc_dir/speaker_used.json \
--generator GeneratorSplit\
--discriminator PatchDiscriminator \
--spenc SPEncoder \
--res_block Style2ResidualBlock1DBeta \
--batch_size 8 \
--drop_id_step 10000\
#--few_shot 5 \
#--resume_iters 70000\
#--spk_cls \