This commit is contained in:
SolitaryThinker
2025-06-26 00:18:57 -07:00
parent 1212ed991f
commit c620f8549e
2 changed files with 8 additions and 9 deletions
@@ -42,8 +42,8 @@ export WANDB_BASE_URL="https://api.wandb.ai"
export WANDB_MODE=online
# export FASTVIDEO_ATTENTION_BACKEND=TORCH_SDPA
DATA_DIR=data/crush-smol_preprocessed/combined_parquet_dataset
VALIDATION_DIR=data/crush-smol_preprocessed/validation_parquet_dataset
DATA_DIR=data/crush-smol_processed/combined_parquet_dataset
VALIDATION_DIR=data/crush-smol_processed/validation_parquet_dataset
NUM_GPUS=8
# export CUDA_VISIBLE_DEVICES=4,5
# IP=[MASTER NODE IP]
@@ -67,8 +67,8 @@ srun torchrun \
--num_gpus $NUM_GPUS \
--sp_size $NUM_GPUS \
--tp_size $NUM_GPUS \
--dp_size $SLURM_JOB_NUM_NODES \
--dp_shards $NUM_GPUS \
--hsdp_replicate_dim $SLURM_JOB_NUM_NODES \
--hsdp_shard_dim $NUM_GPUS \
--train_sp_batch_size 1\
--dataloader_num_workers 10\
--gradient_accumulation_steps=2\
@@ -87,12 +87,11 @@ srun torchrun \
--tracker_project_name wan_i2v_finetune \
--num_height 480 \
--num_width 832 \
--num_frames 81 \
--shift 3 \
--num_frames 77 \
--validation_guidance_scale "1.0" \
--num_euler_timesteps 50 \
--multi_phased_distill_schedule "4000-1" \
--weight_decay 1e-4 \
--not_apply_cfg_solver \
--master_weight_type "fp32" \
--dit_precision "fp32" \
--max_grad_norm 1.0
@@ -10,7 +10,7 @@ NUM_GPUS=8
# If you do not have 32 GPUs and to fit in memory, you can: 1. increase sp_size. 2. reduce num_latent_t
torchrun --nnodes 1 --nproc_per_node $NUM_GPUS\
fastvideo/v1/training/wan_training_pipeline.py\
fastvideo/v1/training/wan_i2v_training_pipeline.py\
--model_path Wan-AI/Wan2.1-I2V-14B-480P-Diffusers \
--inference_mode False\
--pretrained_model_name_or_path Wan-AI/Wan2.1-I2V-14B-480P-Diffusers \
@@ -48,4 +48,4 @@ torchrun --nnodes 1 --nproc_per_node $NUM_GPUS\
--weight_decay 1e-4 \
--not_apply_cfg_solver \
--dit_precision "fp32" \
--max_grad_norm 1.0
--max_grad_norm 1.0