#!/bin/bash # TODO SLURM header goes here source ~/miniconda3/etc/profile.d/conda.sh conda activate voicestar ### ==================== ### ==================== ### ==================== dataset=librilight mkdir -p ./logs exp_root="path/to/save/log_and_ckpt/VoiceStar/runs" exp_name="VoiceStar_840M_30s_new" # dataset_dir="['/path/to/librilight/preprocessed','/path/to/emilia/preprocessed']" manifest_folder_name='manifest_final_encodec' encodec_codes_folder_name="encodec_4cb" # sent to sub script export HOSTNAMES=`scontrol show hostnames "$SLURM_JOB_NODELIST"` export MASTER_ADDR=$(scontrol show hostnames "$SLURM_JOB_NODELIST" | head -n 1) export MASTER_PORT=11751 export COUNT_NODE=`scontrol show hostnames "$SLURM_JOB_NODELIST" | wc -l` GRAD_ACC_STEPS=3 srun torchrun --nnodes=${SLURM_JOB_NUM_NODES} --nproc_per_node=${SLURM_GPUS_PER_NODE} --rdzv_backend=c10d --rdzv_id=${SLURM_NODEID} --rdzv_endpoint="${MASTER_ADDR}:${MASTER_PORT}" \ ../main.py \ --uniform_weight_start_step 50000 \ --local_wandb 1 \ --resume \ --multinodes 1 \ --no_loss_on_prefix 1 \ --neighbor_prompt_prob 0.5 \ --x_sep_token 498 \ --y_sep_token 2052 \ --n_special 5 \ --rope_base 10000 \ --progress_no_multiple 1 \ --progress_scale 2000 \ --early_stop_step 7500 \ --early_stop_threshold -1 \ --precision "float16" \ --use_sinusoidal 0 \ --drop_long 1 \ --pad_x 0 \ --codebook_weight "[5,1,0.5,0.1]" \ --encodec_sr 50 \ --num_steps 100000 \ --lr 0.035 \ --warmup_fraction 0.02 \ --optimizer_name "ScaledAdam" \ --pseudo_epoch_size 3000 \ --reduce_lr_start_step 3000 \ --reduce_lr_start_epoch 4 \ --clipping_update_period 1000 \ --d_model 1024 \ --audio_embedding_dim 1024 \ --nhead 16 \ --num_encoder_layer 12 \ --num_decoder_layer 40 \ --max_num_tokens 20000 \ --gradient_accumulation_steps ${GRAD_ACC_STEPS} \ --val_max_num_tokens 8000 \ --num_buckets 20 \ --max_prompt_len 10 \ --audio_max_length 30 \ --audio_min_length 1 \ --text_max_length 2000 \ --text_min_length 10 \ --tb_write_every_n_steps 50 \ --print_every_n_steps 500 \ --val_every_n_steps 1000 \ --save_every_n_steps 1000000 \ --text_vocab_size 500 \ --text_pad_token 500 \ --phn_folder_name "phoneme" \ --manifest_name ${manifest_folder_name} \ --encodec_folder_name ${encodec_codes_folder_name} \ --enc_dec 1 \ --audio_vocab_size 2048 \ --reduced_eog 1 \ --empty_token 2048 \ --eog 2049 \ --audio_pad_token 2050 \ --eos 2051 \ --n_codebooks 4 \ --exp_dir "${exp_root}/${exp_name}" \ --dataset_dir ${dataset_dir} \ >> ./logs/${exp_name}_${SLURM_JOB_ID}_gradAccSteps${GRAD_ACC_STEPS}.log 2>&1