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WARNING 02-08 03:03:20 [envs.py:235] Flash Attention library "flash_attn" not found, using pytorch attention implementation
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================================================================================
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CONFIGURATION PARAMETERS:
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================================================================================
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cfg_scale_text : 5.0
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data_root : data_inference/wan_i2v/
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dit_root : ./weights/Wan2.1-I2V-14B-480P/
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extra_module_root : weights/Stable-Video-Infinity/version-1.0/svi-shot.safetensors
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lora_alpha : 1.0
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max_prompts_per_sample : None
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max_width : 832
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num_clips : 10
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num_motion_frames : 1
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num_persistent_param_in_dit : 6000000000
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num_steps : 50
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output : videos/svi_shot/
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prompt_path : /mnt/vita/scratch/vita-students/users/wuli/code/DigitalHuman/VBench/20260207_test/sample1/prompt.txt
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prompt_prefix : none
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prompt_repeat_times : 1
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ref_image_path : /mnt/vita/scratch/vita-students/users/wuli/code/DigitalHuman/VBench/20260207_test/sample1/train_000001.jpg
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ref_pad_cfg : False
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ref_pad_num : -1
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repeat_first_clip : False
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seed_times : 42
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test_samples : None
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tile_size : [30, 52]
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tile_stride : [15, 26]
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tiled : False
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train_architecture : lora
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use_first_aug : False
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use_first_prompt_only : True
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================================================================================
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Total number of cfg parameters: 27
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================================================================================
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Using direct paths for reference image and prompt file
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Reference image: /mnt/vita/scratch/vita-students/users/wuli/code/DigitalHuman/VBench/20260207_test/sample1/train_000001.jpg
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Prompt file: /mnt/vita/scratch/vita-students/users/wuli/code/DigitalHuman/VBench/20260207_test/sample1/prompt.txt
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Generated 1 test scenario with 1 prompts
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Loading models from: ./weights/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
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model_name: wan_video_image_encoder model_class: WanImageEncoder
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The following models are loaded: ['wan_video_image_encoder'].
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Loading models from: ['./weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
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model_name: wan_video_dit model_class: WanModel
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This model is initialized with extra kwargs: {'has_image_input': True, 'patch_size': [1, 2, 2], 'in_dim': 36, 'dim': 5120, 'ffn_dim': 13824, 'freq_dim': 256, 'text_dim': 4096, 'out_dim': 16, 'num_heads': 40, 'num_layers': 40, 'eps': 1e-06}
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The following models are loaded: ['wan_video_dit'].
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Loading models from: ./weights/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
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model_name: wan_video_text_encoder model_class: WanTextEncoder
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The following models are loaded: ['wan_video_text_encoder'].
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Loading models from: ./weights/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
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model_name: wan_video_vae model_class: WanVideoVAE
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The following models are loaded: ['wan_video_vae'].
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Loading LoRA models from file: weights/Stable-Video-Infinity/version-1.0/svi-shot.safetensors
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Adding LoRA to wan_video_dit (['./weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']).
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400 tensors are updated.
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Using wan_video_text_encoder from ./weights/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
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Using wan_video_dit from ['./weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', './weights/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
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Using wan_video_vae from ./weights/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
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Using wan_video_image_encoder from ./weights/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
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####################################################################################################
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STARTING SAMPLE 1/1: train_000001
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####################################################################################################
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Reference image: /mnt/vita/scratch/vita-students/users/wuli/code/DigitalHuman/VBench/20260207_test/sample1/train_000001.jpg
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Available prompts: 1
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Video dimensions: 832x528
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Processing train_000001 with 1 prompts
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Generating 10 clips using the first prompt repeatedly
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Created output directory for sample: videos/svi_shot/train_000001_20260208_030504
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================================================================================
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PROCESSING SAMPLE: train_000001
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CHUNK: 1/10
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PROMPT: An Amtrak train, numbered 146, travels along a set of tracks under a clear blue sky with scattered clouds, surrounded by a forested landscape.
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NOTE: Using first prompt only (use_first_prompt_only=True)
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================================================================================
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Starting video generation...
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