2024-04-08 21:04:22 +02:00
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#!/bin/bash
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source ~/miniconda3/etc/profile.d/conda.sh
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conda activate voicecraft
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export CUDA_VISIBLE_DEVICES=0,1,2,3
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export WORLD_SIZE=4
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dataset=gigaspeech
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mkdir -p ./logs/${dataset}
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exp_root="path/to/store/exp_results"
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exp_name=e830M_ft
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dataset_dir="path/to/stored_extracted_codes_and_phonemes/xl" # xs if you only extracted xs in previous step
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encodec_codes_folder_name="encodec_16khz_4codebooks"
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2024-04-09 00:12:51 +02:00
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load_model_from="./pretrained_models/giga830M.pth"
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2024-04-08 21:04:22 +02:00
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# export CUDA_LAUNCH_BLOCKING=1 # for debugging
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torchrun --nnodes=1 --rdzv-backend=c10d --rdzv-endpoint=localhost:41977 --nproc_per_node=${WORLD_SIZE} \
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../main.py \
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--load_model_from ${load_model_from} \
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--reduced_eog 1 \
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--drop_long 1 \
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--eos 2051 \
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--n_special 4 \
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--pad_x 0 \
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--codebook_weight "[3,1,1,1]" \
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--encodec_sr 50 \
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--num_steps 500000 \
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--lr 0.00001 \
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--warmup_fraction 0.1 \
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--optimizer_name "AdamW" \
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--d_model 2048 \
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--audio_embedding_dim 2048 \
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--nhead 16 \
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--num_decoder_layers 16 \
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--max_num_tokens 20000 \
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2024-04-09 00:12:51 +02:00
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--gradient_accumulation_steps 12 \
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2024-04-08 21:04:22 +02:00
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--val_max_num_tokens 6000 \
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--num_buckets 6 \
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--audio_max_length 20 \
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--audio_min_length 2 \
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--text_max_length 400 \
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--text_min_length 10 \
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--mask_len_min 1 \
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--mask_len_max 600 \
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--tb_write_every_n_steps 10 \
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--print_every_n_steps 400 \
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--val_every_n_steps 1600 \
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--text_vocab_size 100 \
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--text_pad_token 100 \
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--phn_folder_name "phonemes" \
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--manifest_name "manifest" \
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--encodec_folder_name ${encodec_codes_folder_name} \
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--audio_vocab_size 2048 \
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--empty_token 2048 \
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--eog 2049 \
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--audio_pad_token 2050 \
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--n_codebooks 4 \
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--max_n_spans 3 \
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--shuffle_mask_embedding 0 \
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--mask_sample_dist poisson1 \
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--max_mask_portion 0.9 \
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--min_gap 5 \
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--num_workers 8 \
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--dynamic_batching 1 \
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--dataset $dataset \
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--exp_dir "${exp_root}/${dataset}/${exp_name}" \
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--dataset_dir ${dataset_dir}
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# >> ./logs/${dataset}/${exp_name}.log 2>&1
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