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train_segan.sh
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train_segan.sh
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#!/bin/bash
# Place the CUDA_VISIBLE_DEVICES="xxxx" required before the python call
# e.g. to specify the first two GPUs in your system: CUDA_VISIBLE_DEVICES="0,1" python ...
# SEGAN with no pre-emph and no bias in conv layers (just filters to downconv + deconv)
#CUDA_VISIBLE_DEVICES="2,3" python main.py --init_noise_std 0. --save_path segan_vanilla \
# --init_l1_weight 100. --batch_size 100 --g_nl prelu \
# --save_freq 50 --epoch 50
# SEGAN with pre-emphasis to try to discriminate more high freq (better disc of high freqs)
#CUDA_VISIBLE_DEVICES="1,2,3" python main.py --init_noise_std 0. --save_path segan_preemph \
# --init_l1_weight 100. --batch_size 100 --g_nl prelu \
# --save_freq 50 --preemph 0.95 --epoch 86
# Apply pre-emphasis AND apply biases to all conv layers (best SEGAN atm)
CUDA_VISIBLE_DEVICES="1,2,3" python main.py --init_noise_std 0. --save_path segan_allbiased_preemph \
--init_l1_weight 100. --batch_size 100 --g_nl prelu \
--save_freq 50 --preemph 0.95 --epoch 86 --bias_deconv True \
--bias_downconv True --bias_D_conv True