nautilus sftp://edessale@nexuscfar00.umiacs.umd.edu/fs/vulcan-projects/Force_Learning


/fs/vulcan-projects/Force_Learning/EMG_Learning/VideoX-Fun/models/Wan2.1-Fun-V1.1-1.3B-Control-Camera


https://huggingface.co/alibaba-pai/Wan2.2-Fun-5B-Control
https://huggingface.co/alibaba-pai/Wan2.1-Fun-V1.1-1.3B-Control-Camera


export DATASET_NAME=""
export DATASET_META_NAME="/fs/vulcan-projects/Force_Learning/EMG/videoxfun_metadata.json"
export MODEL_NAME="/fs/vulcan-projects/Force_Learning/EMG_Learning/VideoX-Fun/models/Wan2.1-Fun-V1.1-1.3B-Control-Camera"

export MODEL_NAME="/fs/vulcan-projects/Force_Learning/EMG_Learning/VideoX-Fun/models/Wan2.2-Fun-5B-Control"
export DATASET_NAME=""
export DATASET_META_NAME="/fs/vulcan-projects/Force_Learning/EMG/videoxfun_metadata.json"
accelerate launch --mixed_precision="bf16" scripts/wan2.2_fun/train_control.py \
  --config_path="config/wan2.2/wan_civitai_5b.yaml" \
  --pretrained_model_name_or_path=$MODEL_NAME \
  --train_data_dir=$DATASET_NAME \
  --train_data_meta=$DATASET_META_NAME \
  --image_sample_size=640 \
  --video_sample_size=640 \
  --token_sample_size=640 \
  --video_sample_stride=1 \
  --video_sample_n_frames=49 \
  --train_batch_size=1 \
  --video_repeat=1 \
  --gradient_accumulation_steps=1 \
  --dataloader_num_workers=2 \
  --num_train_epochs=100 \
  --checkpointing_steps=200 \
  --learning_rate=2e-05 \
  --lr_scheduler="constant_with_warmup" \
  --lr_warmup_steps=100 \
  --seed=42 \
  --output_dir="output_dir" \
  --gradient_checkpointing \
  --mixed_precision="bf16" \
  --adam_weight_decay=3e-2 \
  --adam_epsilon=1e-10 \
  --vae_mini_batch=1 \
  --max_grad_norm=0.05 \
  --random_hw_adapt \
  --control_signal_mode emg \
  --training_with_video_token_length \
  --uniform_sampling \
  --boundary_type="full" \
  --train_mode="control_ref" \
  --control_ref_image="first_frame" \
  --add_inpaint_info \
  --add_full_ref_image_in_self_attention \
  --trainable_modules "." 
    
    
    
accelerate launch  --mixed_precision="bf16" scripts/wan2.1_fun/train_control.py \
  --config_path="config/wan2.1/wan_civitai.yaml" \
  --pretrained_model_name_or_path=$MODEL_NAME \
  --train_data_dir=$DATASET_NAME \
  --train_data_meta=$DATASET_META_NAME \
  --image_sample_size=640 \
  --video_sample_size=640 \
  --token_sample_size=640 \
  --video_sample_stride=1 \
  --video_sample_n_frames=49 \
  --train_batch_size=1 \
  --video_repeat=1 \
  --gradient_accumulation_steps=1 \
  --dataloader_num_workers=2 \
  --num_train_epochs=100 \
  --checkpointing_steps=200 \
  --learning_rate=2e-05 \
  --lr_scheduler="constant_with_warmup" \
  --lr_warmup_steps=100 \
  --seed=42 \
  --output_dir="output_dir" \
  --gradient_checkpointing \
  --mixed_precision="bf16" \
  --adam_weight_decay=3e-2 \
  --adam_epsilon=1e-10 \
  --vae_mini_batch=1 \
  --max_grad_norm=0.05 \
  --random_hw_adapt \
  --training_with_video_token_length \
  --uniform_sampling \
  --train_mode="control_ref" \
  --control_ref_image="random" \
  --add_full_ref_image_in_self_attention \
  --trainable_modules "." \
    --profile_timings_every=100 \
  --validation_num_samples 200 \
  --validation_steps 3 \
  --resume_from_checkpoint "/fs/vulcan-projects/Force_Learning/EMG_Learning/VideoX-Fun/output_dir/checkpoint-2800"

        
    
cd /fs/vulcan-projects/Force_Learning/EMG_Learning/VideoX-Fun

python3 scripts/wan2.1_fun/generate_emg_dataset_wan.py \
  --config_path config/wan2.1/wan_civitai.yaml \
  --pretrained_model_name_or_path "$MODEL_NAME" \
  --transformer_path /fs/vulcan-projects/Force_Learning/EMG_Learning/VideoX-Fun/output_dir/checkpoint-2800 \
  --train_data_dir "$DATASET_NAME" \
  --train_data_meta "$DATASET_META_NAME" \
  --image_sample_size 640 \
  --video_sample_size 640 \
  --video_sample_stride 1 \
  --video_sample_n_frames 49 \
  --train_mode "control_ref" \
  --add_full_ref_image_in_self_attention \
  --n_samples 8 \
  --output_dir output_dir/emg_generations
    

export DATASET_NAME=""
export DATASET_META_NAME="/fs/vulcan-projects/Force_Learning/EMG/videoxfun_metadata.json"
export MODEL_NAME="/fs/vulcan-projects/Force_Learning/EMG_Learning/VideoX-Fun/models/Wan2.1-Fun-V1.1-1.3B-Control-Camera"


accelerate launch --mixed_precision="bf16" scripts/wan2.1_fun/train_control_lora.py \
  --config_path="config/wan2.1/wan_civitai.yaml" \
  --pretrained_model_name_or_path=$MODEL_NAME \
  --train_data_dir=$DATASET_NAME \
  --train_data_meta=$DATASET_META_NAME \
  --image_sample_size=640 \
  --video_sample_size=640 \
  --token_sample_size=640 \
  --video_sample_stride=1 \
  --video_sample_n_frames=49 \
  --train_batch_size=4 \
  --video_repeat=1 \
  --gradient_accumulation_steps=1 \
  --dataloader_num_workers=2 \
  --num_train_epochs=100 \
  --checkpointing_steps=200 \
  --learning_rate=1e-04 \
  --seed=42 \
  --output_dir="output_dir" \
  --gradient_checkpointing \
  --mixed_precision="bf16" \
  --adam_weight_decay=3e-2 \
  --adam_epsilon=1e-10 \
  --vae_mini_batch=1 \
  --max_grad_norm=0.05 \
  --random_hw_adapt \
  --training_with_video_token_length \
  --uniform_sampling \
  --train_mode="control_ref" \
  --control_ref_image="random" \
  --add_full_ref_image_in_self_attention \
  --rank=64 \
  --network_alpha=32 \
  --target_name="q,k,v,ffn.0,ffn.2" \
  --use_peft_lora \
  --profile_timings_every=100