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https://github.com/modelscope/DiffSynth-Studio.git
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DiffSynth-Studio 2.0 major update
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@@ -10,4 +10,5 @@ accelerate launch --config_file examples/wanvideo/model_training/full/accelerate
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--remove_prefix_in_ckpt "pipe.dit." \
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--output_path "./models/train/Wan2.1-FLF2V-14B-720P_full" \
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--trainable_models "dit" \
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--extra_inputs "input_image,end_image"
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--extra_inputs "input_image,end_image" \
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--initialize_model_on_cpu
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@@ -10,4 +10,5 @@ accelerate launch --config_file examples/wanvideo/model_training/full/accelerate
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--remove_prefix_in_ckpt "pipe.dit." \
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--output_path "./models/train/Wan2.1-I2V-14B-480P_full" \
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--trainable_models "dit" \
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--extra_inputs "input_image"
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--extra_inputs "input_image" \
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--initialize_model_on_cpu
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@@ -12,4 +12,5 @@ accelerate launch --config_file examples/wanvideo/model_training/full/accelerate
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--output_path "./models/train/Wan2.1-I2V-14B-720P_full" \
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--trainable_models "dit" \
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--extra_inputs "input_image" \
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--use_gradient_checkpointing_offload
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--use_gradient_checkpointing_offload \
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--initialize_model_on_cpu
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@@ -9,7 +9,7 @@ accelerate launch --config_file examples/wanvideo/model_training/full/accelerate
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--learning_rate 1e-4 \
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--num_epochs 5 \
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--remove_prefix_in_ckpt "pipe.dit." \
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--output_path "./models/train/Wan2.2-Fun-A14B-Control-Camera_high_niose_full" \
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--output_path "./models/train/Wan2.2-Fun-A14B-Control-Camera_high_noise_full" \
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--trainable_models "dit" \
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--extra_inputs "input_image,camera_control_direction,camera_control_speed" \
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--max_timestep_boundary 0.358 \
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@@ -9,7 +9,7 @@ accelerate launch --config_file examples/wanvideo/model_training/full/accelerate
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--learning_rate 1e-4 \
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--num_epochs 5 \
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--remove_prefix_in_ckpt "pipe.dit." \
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--output_path "./models/train/Wan2.2-Fun-A14B-Control_high_niose_full" \
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--output_path "./models/train/Wan2.2-Fun-A14B-Control_high_noise_full" \
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--trainable_models "dit" \
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--extra_inputs "control_video,reference_image" \
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--max_timestep_boundary 0.358 \
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@@ -8,7 +8,7 @@ accelerate launch --config_file examples/wanvideo/model_training/full/accelerate
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--learning_rate 1e-4 \
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--num_epochs 5 \
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--remove_prefix_in_ckpt "pipe.dit." \
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--output_path "./models/train/Wan2.2-Fun-A14B-InP_high_niose_full" \
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--output_path "./models/train/Wan2.2-Fun-A14B-InP_high_noise_full" \
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--trainable_models "dit" \
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--extra_inputs "input_image,end_image" \
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--max_timestep_boundary 0.358 \
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@@ -1,13 +1,12 @@
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accelerate launch --config_file examples/wanvideo/model_training/full/accelerate_config_14B.yaml examples/wanvideo/model_training/train.py \
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--dataset_base_path data/example_video_dataset/wans2v \
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--dataset_metadata_path data/example_video_dataset/wans2v/metadata.csv \
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--dataset_base_path data/example_video_dataset \
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--dataset_metadata_path data/example_video_dataset/metadata_s2v.csv \
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--data_file_keys "video,input_audio,s2v_pose_video" \
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--height 448 \
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--width 832 \
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--num_frames 81 \
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--dataset_repeat 100 \
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--model_id_with_origin_paths "Wan-AI/Wan2.2-S2V-14B:diffusion_pytorch_model*.safetensors,Wan-AI/Wan2.2-S2V-14B:wav2vec2-large-xlsr-53-english/model.safetensors,Wan-AI/Wan2.2-S2V-14B:models_t5_umt5-xxl-enc-bf16.pth,Wan-AI/Wan2.2-S2V-14B:Wan2.1_VAE.pth" \
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--audio_processor_config "Wan-AI/Wan2.2-S2V-14B:wav2vec2-large-xlsr-53-english/" \
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--learning_rate 1e-5 \
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--num_epochs 1 \
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--trainable_models "dit" \
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@@ -15,7 +15,8 @@ accelerate launch --config_file examples/wanvideo/model_training/full/accelerate
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--extra_inputs "vace_video,vace_reference_image" \
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--use_gradient_checkpointing_offload \
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--max_timestep_boundary 0.358 \
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--min_timestep_boundary 0
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--min_timestep_boundary 0 \
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--initialize_model_on_cpu
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# boundary corresponds to timesteps [900, 1000]
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@@ -36,5 +37,6 @@ accelerate launch --config_file examples/wanvideo/model_training/full/accelerate
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--extra_inputs "vace_video,vace_reference_image" \
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--use_gradient_checkpointing_offload \
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--max_timestep_boundary 1 \
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--min_timestep_boundary 0.358
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--min_timestep_boundary 0.358 \
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--initialize_model_on_cpu
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# boundary corresponds to timesteps [0, 900]
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@@ -1,38 +0,0 @@
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import multiprocessing, os
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def run_task(scripts, thread_id, thread_num):
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for script_id, script in enumerate(scripts):
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if script_id % thread_num == thread_id:
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log_file_name = script.replace("/", "_") + ".txt"
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cmd = f"CUDA_VISIBLE_DEVICES={thread_id} bash {script} > data/log/{log_file_name} 2>&1"
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os.makedirs("data/log", exist_ok=True)
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print(cmd, flush=True)
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os.system(cmd)
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if __name__ == "__main__":
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# 1.3B
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scripts = []
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for file_name in os.listdir("examples/wanvideo/model_training/full"):
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if file_name != "run_test.py" and "14B" not in file_name:
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scripts.append(os.path.join("examples/wanvideo/model_training/full", file_name))
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processes = [multiprocessing.Process(target=run_task, args=(scripts, i, 8)) for i in range(8)]
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for p in processes:
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p.start()
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for p in processes:
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p.join()
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# 14B
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scripts = []
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for file_name in os.listdir("examples/wanvideo/model_training/full"):
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if file_name != "run_test.py" and "14B" in file_name:
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scripts.append(os.path.join("examples/wanvideo/model_training/full", file_name))
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for script in scripts:
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log_file_name = script.replace("/", "_") + ".txt"
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cmd = f"bash {script} > data/log/{log_file_name} 2>&1"
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print(cmd, flush=True)
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os.system(cmd)
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print("Done!")
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