Is it possible to fine-tune Minimax H3 with silent videos?

Here is my cmd:

accelerate launch examples/minimax_h3/model_training/train.py \
  --dataset_base_path data/diffsynth_example_dataset/minimax_h3/MiniMax-H3-FL2VA \
  --dataset_metadata_path data/diffsynth_example_dataset/minimax_h3/MiniMax-H3-FL2VA/metadata.csv \
  --data_file_keys "video" \
  --extra_inputs "input_image" \
  --height 480 \
  --width 832 \
  --num_frames 124 \
  --dataset_repeat 1 \
  --model_id_with_origin_paths "MiniMax/MiniMax-H3:FL2VA/text_encoder/model*.safetensors,MiniMax/MiniMax-H3:FL2VA/video_vae/source/model.safetensors,MiniMax/MiniMax-H3:FL2VA/audio_vae/model.safetensors" \
  --learning_rate 1e-4 \
  --num_epochs 1 \
  --remove_prefix_in_ckpt "pipe.dit." \
  --output_path "./models/train/MiniMax-H3-FL2VA-split-cache" \
  --lora_base_model "dit" \
  --lora_target_modules "qkv_proj,out_proj" \
  --lora_rank 32 \
  --use_gradient_checkpointing \
  --task "sft:data_process"

# FL2VA - stage 2 (train)
accelerate launch examples/minimax_h3/model_training/train.py \
  --dataset_base_path ./models/train/MiniMax-H3-FL2VA-split-cache \
  --data_file_keys "video" \
  --extra_inputs "input_image" \
  --height 480 \
  --width 832 \
  --num_frames 124 \
  --dataset_repeat 100 \
  --model_id_with_origin_paths "MiniMax/MiniMax-H3:FL2VA/transformer/model*.safetensors" \
  --learning_rate 1e-4 \
  --num_epochs 5 \
  --remove_prefix_in_ckpt "pipe.dit." \
  --output_path "./models/train/MiniMax-H3-FL2VA-split" \
  --lora_base_model "dit" \
  --lora_target_modules "qkv_proj,out_proj" \
  --lora_rank 32 \
  --use_gradient_checkpointing \
  --find_unused_parameters \
  --task "sft:train"  

I remove input_audio and get this error:

File "/home/test/project/DiffSynth-Studio/diffsynth/diffusion/loss.py", line 78, in FlowMatchSFTMiniMaxH3AudioVideoLoss
    audio_noise = torch.randn_like(inputs["audio_input_latents"])
                                   ~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
KeyError: 'audio_input_latents'

How to fine-tune Minimax H3 using Videos without audio?

Start with examples/minimax_h3/model_training/train.py and trace the data inputs into diffsynth/diffusion/loss.py, especially FlowMatchSFTMiniMaxH3AudioVideoLoss. Reproduce the command without input_audio and inspect where audio_input_latents is expected. Done means silent-video fine-tuning no longer raises the reported KeyError and the training path has a defined outcome for missing audio.