File size: 3,616 Bytes
0a2e9f2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 | #!/bin/bash
export PYTHONPATH=$PYTHONPATH:$PWD
export NCCL_TIMEOUT=3600000
OUTPUT_DIR="outputs_wanx14b/train14b_posecontrol_prefix_2d_tokenreplace"
mkdir -p ${OUTPUT_DIR}
LOG_FILE="${OUTPUT_DIR}/train14b_posecontrol_prefix_2d_tokenreplace.log"
echo "=========================================="
echo " Training Wan2.1-14B with Pose Control & Token Replace"
echo "=========================================="
echo "Output directory: ${OUTPUT_DIR}"
echo "Log file: ${LOG_FILE}"
echo ""
# Classifier-Free Guidance
# cfg 1.0 -> dropout text condition during training (text="")
# pose_cfg 0.1 -> 10% probability dropout pose control and reference image (black image)
# refimg_cfg 0.1 -> 10% probability dropout reference image (black image)
# refimg_crop 0.3 -> 30% probability mask reference image
# zoomin 0.1 -> 10% probability zoom in
# bucket_name 768_v2 -> Training with 768 resolution (20% 512 / 80% 768 see opensora/utils/bucket.py)
# change_pose 0.7 70% face region enhancement
# ref_keep -> dropout pose control and keep reference
# token_replace_prob
accelerate launch \
--config_file scripts/accelerate_configs/hk_multinode_config.yaml \
--num_processes 8 \
--num_machines 1 \
opensora/train/wanx_train/train_wanx_refextractor_mask2_controlnet2.py \
--seed 43 \
--output_dir="${OUTPUT_DIR}" \
--checkpointing_steps=1000 \
--checkpoints_total_limit 2 \
--report_to tensorboard \
--num_train_epochs 100 \
--gradient_accumulation_steps=1 \
--allow_tf32 \
--mixed_precision="bf16" \
--optimizer adam \
--adam_beta1 0.9 \
--adam_beta2 0.95 \
--adam_weight_decay 1e-4 \
--learning_rate=1e-5 \
--lr_scheduler="constant_with_warmup" \
--lr_warmup_steps=5000 \
--max_grad_norm 1.0 \
--diffusion_formula FlowMatching \
--load_condition \
--dataloader_num_workers 4 \
--dataset bodydance_3 \
--data "../datasets/opensource_dataset/combined_imgvid_dataset.csv" \
--bucket_name 768_v2 \
--cfg 1.0 \
--pose_cfg 0.1 \
--refimg_cfg 0.1 \
--refimg_crop 0.3 \
--zoomin 0.1 \
--change_pose 0.5 \
--ref_keep 0.3 \
--one_more_second \
--train_fps 16 \
--ema_start_step 0 \
--ema_decay 0.999 \
--evaluation_steps 5 \
--evaluation_every 1000 \
--valid_data "../datasets/opensource_dataset/combined_imgvid_dataset.csv" \
--max_num_evaluate_samples 10 \
--dit_name wanx_refextractor_2d_controlnet_prefix \
--config_path configs/wan2.1_t2v_14b.json \
--text_encoder_name wanx-t2v \
--text_encoder_path ../pretrained_models/Wan2.1-T2V-14B-Diffusers/ \
--vae_name wanx \
--vae_path ../pretrained_models/Wan2.1-T2V-14B-Diffusers/vae/ \
--refextractor_config_path configs/wan2.1_t2v_14b_refextractor_2d_withmask2.json \
--controlnet_config_path configs/wan2.1_t2v_14b_controlnet_1.json \
--load_encoders \
--task t2v \
--face_mask \
--hand_mask \
--face_weight 1.0 \
--gradient_checkpointing \
--training_modules attn1 patch_embedding input_hint_block controlnet image_to_cond \
--resume_from_checkpoint="latest" \
--pretrained ./outputs_wanx14b/train14b_posecontrol_prefix_2d/checkpoint-xxx/fp32_model_xxx \
--pose_poolA ../datasets/opensource_pose_pool/images_pose_pool_24_18pt_abs.csv \
--pose_poolB ../datasets/opensource_pose_pool/images_pose_pool_18_16pt_abs.csv \
--init_from_transformer \
--token_replace_prob 0.2 \
2>&1 | tee -a "${LOG_FILE}"
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