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diff --git a/experiments/cfg3_eps64/logs/gpu_0.log b/experiments/cfg3_eps64/logs/gpu_0.log
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+[GPU 0] Starting work on images 0 to 6
+======================================
+[GPU 0] Processing bear.jpg (Image 0/50)
+======================================
+[GPU 0] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 0] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  16%|█▌        | 78/500 [01:52<10:33,  1.50s/it, loss=1944.0000, t=952]
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Attacking:  18%|█▊        | 89/500 [02:08<09:38,  1.41s/it, loss=2000.0000, t=992]
Attacking:  18%|█▊        | 90/500 [02:08<09:35,  1.40s/it, loss=2000.0000, t=992]
Attacking:  18%|█▊        | 90/500 [02:09<09:35,  1.40s/it, loss=2032.0000, t=1e+3]
Attacking:  18%|█▊        | 91/500 [02:10<09:31,  1.40s/it, loss=2032.0000, t=1e+3]
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Attacking:  19%|█▉        | 96/500 [02:17<09:27,  1.40s/it, loss=1912.0000, t=940]
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Attacking:  20%|██        | 100/500 [02:23<09:23,  1.41s/it, loss=2040.0000, t=1e+3]
Attacking:  20%|██        | 100/500 [02:23<09:23,  1.41s/it, loss=1896.0000, t=912] 
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Attacking:  20%|██        | 101/500 [02:24<09:17,  1.40s/it, loss=2032.0000, t=1e+3]
Attacking:  20%|██        | 102/500 [02:25<09:14,  1.39s/it, loss=2032.0000, t=1e+3]
Attacking:  20%|██        | 102/500 [02:26<09:14,  1.39s/it, loss=1984.0000, t=992] 
Attacking:  21%|██        | 103/500 [02:27<09:12,  1.39s/it, loss=1984.0000, t=992]
Attacking:  21%|██        | 103/500 [02:27<09:12,  1.39s/it, loss=2000.0000, t=992]
Attacking:  21%|██        | 104/500 [02:28<09:27,  1.43s/it, loss=2000.0000, t=992]
Attacking:  21%|██        | 104/500 [02:29<09:27,  1.43s/it, loss=1912.0000, t=952]
Attacking:  21%|██        | 105/500 [02:30<09:26,  1.44s/it, loss=1912.0000, t=952]
Attacking:  21%|██        | 105/500 [02:30<09:26,  1.44s/it, loss=1928.0000, t=964]
Attacking:  21%|██        | 106/500 [02:31<09:29,  1.45s/it, loss=1928.0000, t=964]
Attacking:  21%|██        | 106/500 [02:32<09:29,  1.45s/it, loss=1904.0000, t=928]
Attacking:  21%|██▏       | 107/500 [02:33<09:34,  1.46s/it, loss=1904.0000, t=928]
Attacking:  21%|██▏       | 107/500 [02:33<09:34,  1.46s/it, loss=1904.0000, t=912]
Attacking:  22%|██▏       | 108/500 [02:34<09:32,  1.46s/it, loss=1904.0000, t=912]
Attacking:  22%|██▏       | 108/500 [02:35<09:32,  1.46s/it, loss=1912.0000, t=952]
Attacking:  22%|██▏       | 109/500 [02:36<09:34,  1.47s/it, loss=1912.0000, t=952]
Attacking:  22%|██▏       | 109/500 [02:36<09:34,  1.47s/it, loss=1952.0000, t=984]
Attacking:  22%|██▏       | 110/500 [02:37<09:29,  1.46s/it, loss=1952.0000, t=984]
Attacking:  22%|██▏       | 110/500 [02:38<09:29,  1.46s/it, loss=1912.0000, t=952]
Attacking:  22%|██▏       | 111/500 [02:38<09:33,  1.48s/it, loss=1912.0000, t=952]
Attacking:  22%|██▏       | 111/500 [02:39<09:33,  1.48s/it, loss=1992.0000, t=992]
Attacking:  22%|██▏       | 112/500 [02:40<09:41,  1.50s/it, loss=1992.0000, t=992]
Attacking:  22%|██▏       | 112/500 [02:41<09:41,  1.50s/it, loss=1976.0000, t=992]
Attacking:  23%|██▎       | 113/500 [02:42<09:56,  1.54s/it, loss=1976.0000, t=992]
Attacking:  23%|██▎       | 113/500 [02:43<09:56,  1.54s/it, loss=1936.0000, t=984]
Attacking:  23%|██▎       | 114/500 [02:43<10:12,  1.59s/it, loss=1936.0000, t=984]
Attacking:  23%|██▎       | 114/500 [02:44<10:12,  1.59s/it, loss=1920.0000, t=972]
Attacking:  23%|██▎       | 115/500 [02:45<10:09,  1.58s/it, loss=1920.0000, t=972]
Attacking:  23%|██▎       | 115/500 [02:46<10:09,  1.58s/it, loss=1904.0000, t=940]
Attacking:  23%|██▎       | 116/500 [02:47<10:09,  1.59s/it, loss=1904.0000, t=940]
Attacking:  23%|██▎       | 116/500 [02:47<10:09,  1.59s/it, loss=1896.0000, t=912]
Attacking:  23%|██▎       | 117/500 [02:48<10:05,  1.58s/it, loss=1896.0000, t=912]
Attacking:  23%|██▎       | 117/500 [02:49<10:05,  1.58s/it, loss=1904.0000, t=940]
Attacking:  24%|██▎       | 118/500 [02:50<09:55,  1.56s/it, loss=1904.0000, t=940]
Attacking:  24%|██▎       | 118/500 [02:50<09:55,  1.56s/it, loss=1976.0000, t=992]
Attacking:  24%|██▍       | 119/500 [02:51<10:01,  1.58s/it, loss=1976.0000, t=992]
Attacking:  24%|██▍       | 119/500 [02:53<10:01,  1.58s/it, loss=1936.0000, t=984]
Attacking:  24%|██▍       | 120/500 [02:54<11:50,  1.87s/it, loss=1936.0000, t=984]
Attacking:  24%|██▍       | 120/500 [02:55<11:50,  1.87s/it, loss=1920.0000, t=972]
Attacking:  24%|██▍       | 121/500 [02:55<11:20,  1.79s/it, loss=1920.0000, t=972]
Attacking:  24%|██▍       | 121/500 [02:56<11:20,  1.79s/it, loss=1904.0000, t=964]
Attacking:  24%|██▍       | 122/500 [02:57<10:38,  1.69s/it, loss=1904.0000, t=964]
Attacking:  24%|██▍       | 122/500 [02:58<10:38,  1.69s/it, loss=1904.0000, t=952]
Attacking:  25%|██▍       | 123/500 [02:58<10:19,  1.64s/it, loss=1904.0000, t=952]
Attacking:  25%|██▍       | 123/500 [02:59<10:19,  1.64s/it, loss=1896.0000, t=928]
Attacking:  25%|██▍       | 124/500 [03:00<10:16,  1.64s/it, loss=1896.0000, t=928]
Attacking:  25%|██▍       | 124/500 [03:01<10:16,  1.64s/it, loss=1904.0000, t=940]
Attacking:  25%|██▌       | 125/500 [03:01<09:49,  1.57s/it, loss=1904.0000, t=940]
Attacking:  25%|██▌       | 125/500 [03:02<09:49,  1.57s/it, loss=1920.0000, t=972]
Attacking:  25%|██▌       | 126/500 [03:03<09:32,  1.53s/it, loss=1920.0000, t=972]
Attacking:  25%|██▌       | 126/500 [03:04<09:32,  1.53s/it, loss=1976.0000, t=992]
Attacking:  25%|██▌       | 127/500 [03:04<09:30,  1.53s/it, loss=1976.0000, t=992]
Attacking:  25%|██▌       | 127/500 [03:05<09:30,  1.53s/it, loss=1904.0000, t=952]
Attacking:  26%|██▌       | 128/500 [03:06<09:32,  1.54s/it, loss=1904.0000, t=952]
Attacking:  26%|██▌       | 128/500 [03:07<09:32,  1.54s/it, loss=1904.0000, t=964]
Attacking:  26%|██▌       | 129/500 [03:07<09:19,  1.51s/it, loss=1904.0000, t=964]
Attacking:  26%|██▌       | 129/500 [03:08<09:19,  1.51s/it, loss=1976.0000, t=992]
Attacking:  26%|██▌       | 130/500 [03:09<09:10,  1.49s/it, loss=1976.0000, t=992]
Attacking:  26%|██▌       | 130/500 [03:09<09:10,  1.49s/it, loss=1888.0000, t=900]
Attacking:  26%|██▌       | 131/500 [03:10<09:01,  1.47s/it, loss=1888.0000, t=900]
Attacking:  26%|██▌       | 131/500 [03:11<09:01,  1.47s/it, loss=1896.0000, t=940]
Attacking:  26%|██▋       | 132/500 [03:12<08:55,  1.45s/it, loss=1896.0000, t=940]
Attacking:  26%|██▋       | 132/500 [03:12<08:55,  1.45s/it, loss=1896.0000, t=928]
Attacking:  27%|██▋       | 133/500 [03:13<08:47,  1.44s/it, loss=1896.0000, t=928]
Attacking:  27%|██▋       | 133/500 [03:14<08:47,  1.44s/it, loss=1896.0000, t=928]
Attacking:  27%|██▋       | 134/500 [03:15<08:50,  1.45s/it, loss=1896.0000, t=928]
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Attacking:  27%|██▋       | 135/500 [03:16<08:54,  1.46s/it, loss=1896.0000, t=940]
Attacking:  27%|██▋       | 135/500 [03:17<08:54,  1.46s/it, loss=1888.0000, t=900]
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Attacking:  27%|██▋       | 136/500 [03:18<08:46,  1.45s/it, loss=1896.0000, t=952]
Attacking:  27%|██▋       | 137/500 [03:19<08:52,  1.47s/it, loss=1896.0000, t=952]
Attacking:  27%|██▋       | 137/500 [03:20<08:52,  1.47s/it, loss=1920.0000, t=972]
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Attacking:  28%|██▊       | 138/500 [03:21<08:52,  1.47s/it, loss=2016.0000, t=1e+3]
Attacking:  28%|██▊       | 139/500 [03:22<08:48,  1.46s/it, loss=2016.0000, t=1e+3]
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Attacking:  28%|██▊       | 140/500 [03:23<08:42,  1.45s/it, loss=1928.0000, t=984]
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Attacking:  28%|██▊       | 141/500 [03:25<08:36,  1.44s/it, loss=1888.0000, t=940]
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Attacking:  28%|██▊       | 142/500 [03:27<08:37,  1.45s/it, loss=2000.0000, t=1e+3]
Attacking:  29%|██▊       | 143/500 [03:28<08:57,  1.51s/it, loss=2000.0000, t=1e+3]
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Attacking:  29%|██▉       | 144/500 [03:29<09:11,  1.55s/it, loss=1888.0000, t=940]
Attacking:  29%|██▉       | 144/500 [03:30<09:11,  1.55s/it, loss=1888.0000, t=952]
Attacking:  29%|██▉       | 145/500 [03:31<09:25,  1.59s/it, loss=1888.0000, t=952]
Attacking:  29%|██▉       | 145/500 [03:32<09:25,  1.59s/it, loss=1904.0000, t=964]
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Attacking:  29%|██▉       | 146/500 [03:34<09:25,  1.60s/it, loss=1880.0000, t=928]
Attacking:  29%|██▉       | 147/500 [03:35<09:46,  1.66s/it, loss=1880.0000, t=928]
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Attacking:  30%|██▉       | 148/500 [03:36<09:50,  1.68s/it, loss=1888.0000, t=912]
Attacking:  30%|██▉       | 148/500 [03:37<09:50,  1.68s/it, loss=1896.0000, t=964]
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Attacking:  30%|██▉       | 149/500 [03:39<09:36,  1.64s/it, loss=2008.0000, t=1e+3]
Attacking:  30%|███       | 150/500 [03:39<09:27,  1.62s/it, loss=2008.0000, t=1e+3]
Attacking:  30%|███       | 150/500 [03:40<09:27,  1.62s/it, loss=1920.0000, t=984] 
Attacking:  30%|███       | 151/500 [03:41<09:10,  1.58s/it, loss=1920.0000, t=984]
Attacking:  30%|███       | 151/500 [03:42<09:10,  1.58s/it, loss=1880.0000, t=912]
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Attacking:  91%|█████████ | 455/500 [11:55<01:11,  1.58s/it, loss=1952.0000, t=1e+3]
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Attacking: 100%|██████████| 500/500 [13:06<00:00,  1.57s/it, loss=1840.0000, t=928]
+Max Diff: 0.501961
+Mean Diff: 0.253091
+Saved adversarial image to attacked/images/bear.jpg
+Saved loss curve to attacked/loss_curve/bear_loss.png
+[GPU 0] Stage 3/3: Test
+Loading models for testing bear...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for bear...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 60.34it/s]
+Saved video to attacked/videos/bear.mp4
+Saved frames to attacked/frames/bear
+[GPU 0] Finished bear.jpg
+======================================
+[GPU 0] Processing blackswan.jpg (Image 1/50)
+======================================
+[GPU 0] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 0] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   4%|▍         | 19/500 [00:34<13:15,  1.65s/it, loss=2368.0000, t=992]
Attacking:   4%|▍         | 20/500 [00:35<13:04,  1.63s/it, loss=2368.0000, t=992]
Attacking:   4%|▍         | 20/500 [00:36<13:04,  1.63s/it, loss=2432.0000, t=1e+3]
Attacking:   4%|▍         | 21/500 [00:37<13:04,  1.64s/it, loss=2432.0000, t=1e+3]
Attacking:   4%|▍         | 21/500 [00:37<13:04,  1.64s/it, loss=2288.0000, t=940] 
Attacking:   4%|▍         | 22/500 [00:38<13:07,  1.65s/it, loss=2288.0000, t=940]
Attacking:   4%|▍         | 22/500 [00:39<13:07,  1.65s/it, loss=2288.0000, t=928]
Attacking:   5%|▍         | 23/500 [00:40<12:47,  1.61s/it, loss=2288.0000, t=928]
Attacking:   5%|▍         | 23/500 [00:40<12:47,  1.61s/it, loss=2400.0000, t=1e+3]
Attacking:   5%|▍         | 24/500 [00:41<12:28,  1.57s/it, loss=2400.0000, t=1e+3]
Attacking:   5%|▍         | 24/500 [00:42<12:28,  1.57s/it, loss=2256.0000, t=900] 
Attacking:   5%|▌         | 25/500 [00:43<12:42,  1.60s/it, loss=2256.0000, t=900]
Attacking:   5%|▌         | 25/500 [00:44<12:42,  1.60s/it, loss=2288.0000, t=984]
Attacking:   5%|▌         | 26/500 [00:45<12:47,  1.62s/it, loss=2288.0000, t=984]
Attacking:   5%|▌         | 26/500 [00:45<12:47,  1.62s/it, loss=2256.0000, t=900]
Attacking:   5%|▌         | 27/500 [00:46<12:49,  1.63s/it, loss=2256.0000, t=900]
Attacking:   5%|▌         | 27/500 [00:47<12:49,  1.63s/it, loss=2240.0000, t=952]
Attacking:   6%|▌         | 28/500 [00:48<12:52,  1.64s/it, loss=2240.0000, t=952]
Attacking:   6%|▌         | 28/500 [00:49<12:52,  1.64s/it, loss=2256.0000, t=952]
Attacking:   6%|▌         | 29/500 [00:50<12:57,  1.65s/it, loss=2256.0000, t=952]
Attacking:   6%|▌         | 29/500 [00:50<12:57,  1.65s/it, loss=2304.0000, t=992]
Attacking:   6%|▌         | 30/500 [00:51<12:46,  1.63s/it, loss=2304.0000, t=992]
Attacking:   6%|▌         | 30/500 [00:52<12:46,  1.63s/it, loss=2224.0000, t=928]
Attacking:   6%|▌         | 31/500 [00:53<12:56,  1.66s/it, loss=2224.0000, t=928]
Attacking:   6%|▌         | 31/500 [00:54<12:56,  1.66s/it, loss=2240.0000, t=928]
Attacking:   6%|▋         | 32/500 [00:55<13:16,  1.70s/it, loss=2240.0000, t=928]
Attacking:   6%|▋         | 32/500 [00:56<13:16,  1.70s/it, loss=2240.0000, t=928]
Attacking:   7%|▋         | 33/500 [00:56<13:11,  1.69s/it, loss=2240.0000, t=928]
Attacking:   7%|▋         | 33/500 [00:57<13:11,  1.69s/it, loss=2240.0000, t=940]
Attacking:   7%|▋         | 34/500 [00:58<12:37,  1.63s/it, loss=2240.0000, t=940]
Attacking:   7%|▋         | 34/500 [00:59<12:37,  1.63s/it, loss=2224.0000, t=912]
Attacking:   7%|▋         | 35/500 [01:00<12:40,  1.64s/it, loss=2224.0000, t=912]
Attacking:   7%|▋         | 35/500 [01:00<12:40,  1.64s/it, loss=2224.0000, t=900]
Attacking:   7%|▋         | 36/500 [01:01<12:51,  1.66s/it, loss=2224.0000, t=900]
Attacking:   7%|▋         | 36/500 [01:02<12:51,  1.66s/it, loss=2224.0000, t=940]
Attacking:   7%|▋         | 37/500 [01:03<12:56,  1.68s/it, loss=2224.0000, t=940]
Attacking:   7%|▋         | 37/500 [01:04<12:56,  1.68s/it, loss=2368.0000, t=1e+3]
Attacking:   8%|▊         | 38/500 [01:05<12:57,  1.68s/it, loss=2368.0000, t=1e+3]
Attacking:   8%|▊         | 38/500 [01:06<12:57,  1.68s/it, loss=2288.0000, t=992] 
Attacking:   8%|▊         | 39/500 [01:06<12:54,  1.68s/it, loss=2288.0000, t=992]
Attacking:   8%|▊         | 39/500 [01:07<12:54,  1.68s/it, loss=2240.0000, t=984]
Attacking:   8%|▊         | 40/500 [01:08<12:49,  1.67s/it, loss=2240.0000, t=984]
Attacking:   8%|▊         | 40/500 [01:09<12:49,  1.67s/it, loss=2240.0000, t=984]
Attacking:   8%|▊         | 41/500 [01:10<12:54,  1.69s/it, loss=2240.0000, t=984]
Attacking:   8%|▊         | 41/500 [01:11<12:54,  1.69s/it, loss=2224.0000, t=964]
Attacking:   8%|▊         | 42/500 [01:11<12:45,  1.67s/it, loss=2224.0000, t=964]
Attacking:   8%|▊         | 42/500 [01:12<12:45,  1.67s/it, loss=2192.0000, t=900]
Attacking:   9%|▊         | 43/500 [01:13<12:39,  1.66s/it, loss=2192.0000, t=900]
Attacking:   9%|▊         | 43/500 [01:14<12:39,  1.66s/it, loss=2192.0000, t=940]
Attacking:   9%|▉         | 44/500 [01:15<12:41,  1.67s/it, loss=2192.0000, t=940]
Attacking:   9%|▉         | 44/500 [01:15<12:41,  1.67s/it, loss=2176.0000, t=900]
Attacking:   9%|▉         | 45/500 [01:16<12:20,  1.63s/it, loss=2176.0000, t=900]
Attacking:   9%|▉         | 45/500 [01:17<12:20,  1.63s/it, loss=2208.0000, t=972]
Attacking:   9%|▉         | 46/500 [01:18<12:36,  1.67s/it, loss=2208.0000, t=972]
Attacking:   9%|▉         | 46/500 [01:19<12:36,  1.67s/it, loss=2208.0000, t=928]
Attacking:   9%|▉         | 47/500 [01:20<13:04,  1.73s/it, loss=2208.0000, t=928]
Attacking:   9%|▉         | 47/500 [01:21<13:04,  1.73s/it, loss=2336.0000, t=1e+3]
Attacking:  10%|▉         | 48/500 [01:21<12:33,  1.67s/it, loss=2336.0000, t=1e+3]
Attacking:  10%|▉         | 48/500 [01:22<12:33,  1.67s/it, loss=2208.0000, t=984] 
Attacking:  10%|▉         | 49/500 [01:23<12:38,  1.68s/it, loss=2208.0000, t=984]
Attacking:  10%|▉         | 49/500 [01:24<12:38,  1.68s/it, loss=2336.0000, t=1e+3]
Attacking:  10%|█         | 50/500 [01:25<12:47,  1.71s/it, loss=2336.0000, t=1e+3]
Attacking:  10%|█         | 50/500 [01:26<12:47,  1.71s/it, loss=2176.0000, t=952] 
Attacking:  10%|█         | 51/500 [01:26<12:35,  1.68s/it, loss=2176.0000, t=952]
Attacking:  10%|█         | 51/500 [01:27<12:35,  1.68s/it, loss=2160.0000, t=912]
Attacking:  10%|█         | 52/500 [01:28<12:34,  1.68s/it, loss=2160.0000, t=912]
Attacking:  10%|█         | 52/500 [01:29<12:34,  1.68s/it, loss=2176.0000, t=912]
Attacking:  11%|█         | 53/500 [01:30<12:33,  1.68s/it, loss=2176.0000, t=912]
Attacking:  11%|█         | 53/500 [01:31<12:33,  1.68s/it, loss=2192.0000, t=964]
Attacking:  11%|█         | 54/500 [01:31<12:22,  1.66s/it, loss=2192.0000, t=964]
Attacking:  11%|█         | 54/500 [01:32<12:22,  1.66s/it, loss=2208.0000, t=984]
Attacking:  11%|█         | 55/500 [01:33<12:05,  1.63s/it, loss=2208.0000, t=984]
Attacking:  11%|█         | 55/500 [01:34<12:05,  1.63s/it, loss=2192.0000, t=972]
Attacking:  11%|█         | 56/500 [01:35<11:59,  1.62s/it, loss=2192.0000, t=972]
Attacking:  11%|█         | 56/500 [01:35<11:59,  1.62s/it, loss=2176.0000, t=940]
Attacking:  11%|█▏        | 57/500 [01:36<12:00,  1.63s/it, loss=2176.0000, t=940]
Attacking:  11%|█▏        | 57/500 [01:37<12:00,  1.63s/it, loss=2160.0000, t=912]
Attacking:  12%|█▏        | 58/500 [01:38<11:49,  1.60s/it, loss=2160.0000, t=912]
Attacking:  12%|█▏        | 58/500 [01:39<11:49,  1.60s/it, loss=2176.0000, t=972]
Attacking:  12%|█▏        | 59/500 [01:40<12:24,  1.69s/it, loss=2176.0000, t=972]
Attacking:  12%|█▏        | 59/500 [01:41<12:24,  1.69s/it, loss=2176.0000, t=972]
Attacking:  12%|█▏        | 60/500 [01:41<12:24,  1.69s/it, loss=2176.0000, t=972]
Attacking:  12%|█▏        | 60/500 [01:42<12:24,  1.69s/it, loss=2192.0000, t=984]
Attacking:  12%|█▏        | 61/500 [01:43<12:17,  1.68s/it, loss=2192.0000, t=984]
Attacking:  12%|█▏        | 61/500 [01:44<12:17,  1.68s/it, loss=2160.0000, t=900]
Attacking:  12%|█▏        | 62/500 [01:45<12:15,  1.68s/it, loss=2160.0000, t=900]
Attacking:  12%|█▏        | 62/500 [01:46<12:15,  1.68s/it, loss=2304.0000, t=1e+3]
Attacking:  13%|█▎        | 63/500 [01:46<12:12,  1.68s/it, loss=2304.0000, t=1e+3]
Attacking:  13%|█▎        | 63/500 [01:47<12:12,  1.68s/it, loss=2144.0000, t=900] 
Attacking:  13%|█▎        | 64/500 [01:48<11:52,  1.64s/it, loss=2144.0000, t=900]
Attacking:  13%|█▎        | 64/500 [01:49<11:52,  1.64s/it, loss=2160.0000, t=952]
Attacking:  13%|█▎        | 65/500 [01:50<11:50,  1.63s/it, loss=2160.0000, t=952]
Attacking:  13%|█▎        | 65/500 [01:50<11:50,  1.63s/it, loss=2304.0000, t=1e+3]
Attacking:  13%|█▎        | 66/500 [01:51<11:45,  1.63s/it, loss=2304.0000, t=1e+3]
Attacking:  13%|█▎        | 66/500 [01:52<11:45,  1.63s/it, loss=2160.0000, t=940] 
Attacking:  13%|█▎        | 67/500 [01:53<11:40,  1.62s/it, loss=2160.0000, t=940]
Attacking:  13%|█▎        | 67/500 [01:54<11:40,  1.62s/it, loss=2144.0000, t=940]
Attacking:  14%|█▎        | 68/500 [01:54<11:44,  1.63s/it, loss=2144.0000, t=940]
Attacking:  14%|█▎        | 68/500 [01:55<11:44,  1.63s/it, loss=2160.0000, t=972]
Attacking:  14%|█▍        | 69/500 [01:56<11:48,  1.64s/it, loss=2160.0000, t=972]
Attacking:  14%|█▍        | 69/500 [01:57<11:48,  1.64s/it, loss=2240.0000, t=992]
Attacking:  14%|█▍        | 70/500 [01:58<11:51,  1.65s/it, loss=2240.0000, t=992]
Attacking:  14%|█▍        | 70/500 [01:59<11:51,  1.65s/it, loss=2224.0000, t=992]
Attacking:  14%|█▍        | 71/500 [02:00<12:04,  1.69s/it, loss=2224.0000, t=992]
Attacking:  14%|█▍        | 71/500 [02:00<12:04,  1.69s/it, loss=2224.0000, t=992]
Attacking:  14%|█▍        | 72/500 [02:01<12:02,  1.69s/it, loss=2224.0000, t=992]
Attacking:  14%|█▍        | 72/500 [02:02<12:02,  1.69s/it, loss=2288.0000, t=1e+3]
Attacking:  15%|█▍        | 73/500 [02:03<12:18,  1.73s/it, loss=2288.0000, t=1e+3]
Attacking:  15%|█▍        | 73/500 [02:04<12:18,  1.73s/it, loss=2208.0000, t=992] 
Attacking:  15%|█▍        | 74/500 [02:05<12:03,  1.70s/it, loss=2208.0000, t=992]
Attacking:  15%|█▍        | 74/500 [02:06<12:03,  1.70s/it, loss=2208.0000, t=992]
Attacking:  15%|█▌        | 75/500 [02:06<12:07,  1.71s/it, loss=2208.0000, t=992]
Attacking:  15%|█▌        | 75/500 [02:07<12:07,  1.71s/it, loss=2144.0000, t=912]
Attacking:  15%|█▌        | 76/500 [02:08<11:46,  1.67s/it, loss=2144.0000, t=912]
Attacking:  15%|█▌        | 76/500 [02:09<11:46,  1.67s/it, loss=2272.0000, t=1e+3]
Attacking:  15%|█▌        | 77/500 [02:10<11:28,  1.63s/it, loss=2272.0000, t=1e+3]
Attacking:  15%|█▌        | 77/500 [02:10<11:28,  1.63s/it, loss=2144.0000, t=900] 
Attacking:  16%|█▌        | 78/500 [02:11<11:04,  1.57s/it, loss=2144.0000, t=900]
Attacking:  16%|█▌        | 78/500 [02:12<11:04,  1.57s/it, loss=2224.0000, t=992]
Attacking:  16%|█▌        | 79/500 [02:13<11:05,  1.58s/it, loss=2224.0000, t=992]
Attacking:  16%|█▌        | 79/500 [02:13<11:05,  1.58s/it, loss=2272.0000, t=1e+3]
Attacking:  16%|█▌        | 80/500 [02:14<11:02,  1.58s/it, loss=2272.0000, t=1e+3]
Attacking:  16%|█▌        | 80/500 [02:15<11:02,  1.58s/it, loss=2144.0000, t=964] 
Attacking:  16%|█▌        | 81/500 [02:16<11:08,  1.60s/it, loss=2144.0000, t=964]
Attacking:  16%|█▌        | 81/500 [02:17<11:08,  1.60s/it, loss=2176.0000, t=984]
Attacking:  16%|█▋        | 82/500 [02:17<11:10,  1.60s/it, loss=2176.0000, t=984]
Attacking:  16%|█▋        | 82/500 [02:18<11:10,  1.60s/it, loss=2128.0000, t=912]
Attacking:  17%|█▋        | 83/500 [02:19<11:08,  1.60s/it, loss=2128.0000, t=912]
Attacking:  17%|█▋        | 83/500 [02:20<11:08,  1.60s/it, loss=2144.0000, t=940]
Attacking:  17%|█▋        | 84/500 [02:21<11:22,  1.64s/it, loss=2144.0000, t=940]
Attacking:  17%|█▋        | 84/500 [02:22<11:22,  1.64s/it, loss=2144.0000, t=900]
Attacking:  17%|█▋        | 85/500 [02:22<11:20,  1.64s/it, loss=2144.0000, t=900]
Attacking:  17%|█▋        | 85/500 [02:23<11:20,  1.64s/it, loss=2224.0000, t=992]
Attacking:  17%|█▋        | 86/500 [02:24<11:24,  1.65s/it, loss=2224.0000, t=992]
Attacking:  17%|█▋        | 86/500 [02:25<11:24,  1.65s/it, loss=2128.0000, t=964]
Attacking:  17%|█▋        | 87/500 [02:26<11:37,  1.69s/it, loss=2128.0000, t=964]
Attacking:  17%|█▋        | 87/500 [02:27<11:37,  1.69s/it, loss=2144.0000, t=964]
Attacking:  18%|█▊        | 88/500 [02:28<11:34,  1.68s/it, loss=2144.0000, t=964]
Attacking:  18%|█▊        | 88/500 [02:28<11:34,  1.68s/it, loss=2128.0000, t=952]
Attacking:  18%|█▊        | 89/500 [02:29<11:35,  1.69s/it, loss=2128.0000, t=952]
Attacking:  18%|█▊        | 89/500 [02:30<11:35,  1.69s/it, loss=2144.0000, t=952]
Attacking:  18%|█▊        | 90/500 [02:31<11:30,  1.68s/it, loss=2144.0000, t=952]
Attacking:  18%|█▊        | 90/500 [02:32<11:30,  1.68s/it, loss=2128.0000, t=940]
Attacking:  18%|█▊        | 91/500 [02:33<11:35,  1.70s/it, loss=2128.0000, t=940]
Attacking:  18%|█▊        | 91/500 [02:33<11:35,  1.70s/it, loss=2208.0000, t=992]
Attacking:  18%|█▊        | 92/500 [02:34<11:14,  1.65s/it, loss=2208.0000, t=992]
Attacking:  18%|█▊        | 92/500 [02:35<11:14,  1.65s/it, loss=2128.0000, t=940]
Attacking:  19%|█▊        | 93/500 [02:36<11:05,  1.64s/it, loss=2128.0000, t=940]
Attacking:  19%|█▊        | 93/500 [02:36<11:05,  1.64s/it, loss=2112.0000, t=912]
Attacking:  19%|█▉        | 94/500 [02:37<10:56,  1.62s/it, loss=2112.0000, t=912]
Attacking:  19%|█▉        | 94/500 [02:38<10:56,  1.62s/it, loss=2128.0000, t=912]
Attacking:  19%|█▉        | 95/500 [02:39<10:59,  1.63s/it, loss=2128.0000, t=912]
Attacking:  19%|█▉        | 95/500 [02:40<10:59,  1.63s/it, loss=2272.0000, t=1e+3]
Attacking:  19%|█▉        | 96/500 [02:41<11:01,  1.64s/it, loss=2272.0000, t=1e+3]
Attacking:  19%|█▉        | 96/500 [02:41<11:01,  1.64s/it, loss=2128.0000, t=912] 
Attacking:  19%|█▉        | 97/500 [02:42<11:05,  1.65s/it, loss=2128.0000, t=912]
Attacking:  19%|█▉        | 97/500 [02:43<11:05,  1.65s/it, loss=2160.0000, t=984]
Attacking:  20%|█▉        | 98/500 [02:44<11:11,  1.67s/it, loss=2160.0000, t=984]
Attacking:  20%|█▉        | 98/500 [02:45<11:11,  1.67s/it, loss=2128.0000, t=940]
Attacking:  20%|█▉        | 99/500 [02:46<11:12,  1.68s/it, loss=2128.0000, t=940]
Attacking:  20%|█▉        | 99/500 [02:46<11:12,  1.68s/it, loss=2128.0000, t=964]
Attacking:  20%|██        | 100/500 [02:47<10:57,  1.64s/it, loss=2128.0000, t=964]
Attacking:  20%|██        | 100/500 [02:48<10:57,  1.64s/it, loss=2112.0000, t=912]
Attacking:  20%|██        | 101/500 [02:49<10:37,  1.60s/it, loss=2112.0000, t=912]
Attacking:  20%|██        | 101/500 [02:50<10:37,  1.60s/it, loss=2128.0000, t=940]
Attacking:  20%|██        | 102/500 [02:50<10:42,  1.62s/it, loss=2128.0000, t=940]
Attacking:  20%|██        | 102/500 [02:51<10:42,  1.62s/it, loss=2208.0000, t=992]
Attacking:  21%|██        | 103/500 [02:52<10:40,  1.61s/it, loss=2208.0000, t=992]
Attacking:  21%|██        | 103/500 [02:53<10:40,  1.61s/it, loss=2144.0000, t=972]
Attacking:  21%|██        | 104/500 [02:54<10:52,  1.65s/it, loss=2144.0000, t=972]
Attacking:  21%|██        | 104/500 [02:55<10:52,  1.65s/it, loss=2128.0000, t=912]
Attacking:  21%|██        | 105/500 [02:55<10:53,  1.65s/it, loss=2128.0000, t=912]
Attacking:  21%|██        | 105/500 [02:56<10:53,  1.65s/it, loss=2128.0000, t=964]
Attacking:  21%|██        | 106/500 [02:57<10:57,  1.67s/it, loss=2128.0000, t=964]
Attacking:  21%|██        | 106/500 [02:58<10:57,  1.67s/it, loss=2128.0000, t=952]
Attacking:  21%|██▏       | 107/500 [02:59<11:17,  1.72s/it, loss=2128.0000, t=952]
Attacking:  21%|██▏       | 107/500 [03:00<11:17,  1.72s/it, loss=2112.0000, t=912]
Attacking:  22%|██▏       | 108/500 [03:01<10:58,  1.68s/it, loss=2112.0000, t=912]
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Attacking: 100%|██████████| 500/500 [13:05<00:00,  1.57s/it, loss=2064.0000, t=940]
+Max Diff: 0.501961
+Mean Diff: 0.224020
+Saved adversarial image to attacked/images/blackswan.jpg
+Saved loss curve to attacked/loss_curve/blackswan_loss.png
+[GPU 0] Stage 3/3: Test
+Loading models for testing blackswan...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for blackswan...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
Saving video:   6%|▌         | 1/17 [00:00<00:02,  7.55it/s]
Saving video: 100%|██████████| 17/17 [00:00<00:00, 107.57it/s]
+Saved video to attacked/videos/blackswan.mp4
+Saved frames to attacked/frames/blackswan
+[GPU 0] Finished blackswan.jpg
+======================================
+[GPU 0] Processing bmx-bumps.jpg (Image 2/50)
+======================================
+[GPU 0] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 0] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  18%|█▊        | 88/500 [02:21<11:08,  1.62s/it, loss=2336.0000, t=992]
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Attacking:  20%|██        | 100/500 [02:40<10:27,  1.57s/it, loss=2240.0000, t=964]
Attacking:  20%|██        | 100/500 [02:40<10:27,  1.57s/it, loss=2240.0000, t=964]
Attacking:  20%|██        | 101/500 [02:41<10:22,  1.56s/it, loss=2240.0000, t=964]
Attacking:  20%|██        | 101/500 [02:42<10:22,  1.56s/it, loss=2304.0000, t=992]
Attacking:  20%|██        | 102/500 [02:43<10:35,  1.60s/it, loss=2304.0000, t=992]
Attacking:  20%|██        | 102/500 [02:44<10:35,  1.60s/it, loss=2208.0000, t=940]
Attacking:  21%|██        | 103/500 [02:44<10:35,  1.60s/it, loss=2208.0000, t=940]
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Attacking:  21%|██        | 104/500 [02:46<10:39,  1.62s/it, loss=2240.0000, t=964]
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Attacking:  21%|██        | 105/500 [02:48<10:33,  1.60s/it, loss=2192.0000, t=900]
Attacking:  21%|██        | 105/500 [02:48<10:33,  1.60s/it, loss=2320.0000, t=992]
Attacking:  21%|██        | 106/500 [02:49<10:28,  1.59s/it, loss=2320.0000, t=992]
Attacking:  21%|██        | 106/500 [02:50<10:28,  1.59s/it, loss=2224.0000, t=964]
Attacking:  21%|██▏       | 107/500 [02:51<10:25,  1.59s/it, loss=2224.0000, t=964]
Attacking:  21%|██▏       | 107/500 [02:51<10:25,  1.59s/it, loss=2224.0000, t=952]
Attacking:  22%|██▏       | 108/500 [02:52<10:09,  1.56s/it, loss=2224.0000, t=952]
Attacking:  22%|██▏       | 108/500 [02:53<10:09,  1.56s/it, loss=2192.0000, t=912]
Attacking:  22%|██▏       | 109/500 [02:54<10:13,  1.57s/it, loss=2192.0000, t=912]
Attacking:  22%|██▏       | 109/500 [02:55<10:13,  1.57s/it, loss=2224.0000, t=952]
Attacking:  22%|██▏       | 110/500 [02:55<10:12,  1.57s/it, loss=2224.0000, t=952]
Attacking:  22%|██▏       | 110/500 [02:56<10:12,  1.57s/it, loss=2224.0000, t=964]
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Attacking:  22%|██▏       | 112/500 [03:00<10:23,  1.61s/it, loss=2288.0000, t=1e+3]
Attacking:  23%|██▎       | 113/500 [03:00<10:29,  1.63s/it, loss=2288.0000, t=1e+3]
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Attacking:  23%|██▎       | 114/500 [03:03<10:13,  1.59s/it, loss=2304.0000, t=992]
Attacking:  23%|██▎       | 115/500 [03:03<10:09,  1.58s/it, loss=2304.0000, t=992]
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Attacking:  23%|██▎       | 117/500 [03:07<10:21,  1.62s/it, loss=2288.0000, t=1e+3]
Attacking:  24%|██▎       | 118/500 [03:08<10:05,  1.58s/it, loss=2288.0000, t=1e+3]
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Attacking:  24%|██▍       | 119/500 [03:10<10:10,  1.60s/it, loss=2192.0000, t=900]
Attacking:  24%|██▍       | 119/500 [03:11<10:10,  1.60s/it, loss=2192.0000, t=928]
Attacking:  24%|██▍       | 120/500 [03:12<10:15,  1.62s/it, loss=2192.0000, t=928]
Attacking:  24%|██▍       | 120/500 [03:12<10:15,  1.62s/it, loss=2208.0000, t=940]
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Attacking:  24%|██▍       | 121/500 [03:14<10:05,  1.60s/it, loss=2208.0000, t=952]
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Attacking:  24%|██▍       | 122/500 [03:15<10:10,  1.62s/it, loss=2272.0000, t=984]
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Attacking:  25%|██▍       | 124/500 [03:18<09:29,  1.51s/it, loss=2288.0000, t=1e+3]
Attacking:  25%|██▌       | 125/500 [03:19<09:12,  1.47s/it, loss=2288.0000, t=1e+3]
Attacking:  25%|██▌       | 125/500 [03:20<09:12,  1.47s/it, loss=2272.0000, t=1e+3]
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Attacking:  25%|██▌       | 127/500 [03:22<09:05,  1.46s/it, loss=2176.0000, t=900]
Attacking:  25%|██▌       | 127/500 [03:23<09:05,  1.46s/it, loss=2208.0000, t=952]
Attacking:  26%|██▌       | 128/500 [03:23<08:58,  1.45s/it, loss=2208.0000, t=952]
Attacking:  26%|██▌       | 128/500 [03:24<08:58,  1.45s/it, loss=2192.0000, t=900]
Attacking:  26%|██▌       | 129/500 [03:25<08:51,  1.43s/it, loss=2192.0000, t=900]
Attacking:  26%|██▌       | 129/500 [03:26<08:51,  1.43s/it, loss=2288.0000, t=1e+3]
Attacking:  26%|██▌       | 130/500 [03:26<09:18,  1.51s/it, loss=2288.0000, t=1e+3]
Attacking:  26%|██▌       | 130/500 [03:27<09:18,  1.51s/it, loss=2224.0000, t=972] 
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Attacking:  26%|██▋       | 132/500 [03:29<09:17,  1.52s/it, loss=2192.0000, t=940]
Attacking:  26%|██▋       | 132/500 [03:30<09:17,  1.52s/it, loss=2208.0000, t=952]
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Attacking:  27%|██▋       | 136/500 [03:36<09:18,  1.53s/it, loss=2304.0000, t=992]
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Attacking:  27%|██▋       | 137/500 [03:38<09:15,  1.53s/it, loss=2256.0000, t=984]
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Attacking:  28%|██▊       | 140/500 [03:42<09:01,  1.50s/it, loss=2176.0000, t=900]
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Attacking:  29%|██▉       | 145/500 [03:51<09:31,  1.61s/it, loss=2192.0000, t=940]
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Attacking:  29%|██▉       | 146/500 [03:52<09:34,  1.62s/it, loss=2288.0000, t=1e+3]
Attacking:  29%|██▉       | 147/500 [03:53<09:25,  1.60s/it, loss=2288.0000, t=1e+3]
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Attacking:  30%|██▉       | 148/500 [03:55<09:45,  1.66s/it, loss=2176.0000, t=928]
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Attacking:  91%|█████████ | 455/500 [11:44<01:08,  1.52s/it, loss=2224.0000, t=1e+3]
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Attacking: 100%|██████████| 500/500 [12:53<00:00,  1.55s/it, loss=2128.0000, t=940]
+Max Diff: 0.501961
+Mean Diff: 0.231939
+Saved adversarial image to attacked/images/bmx-bumps.jpg
+Saved loss curve to attacked/loss_curve/bmx-bumps_loss.png
+[GPU 0] Stage 3/3: Test
+Loading models for testing bmx-bumps...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for bmx-bumps...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 83.23it/s]
+Saved video to attacked/videos/bmx-bumps.mp4
+Saved frames to attacked/frames/bmx-bumps
+[GPU 0] Finished bmx-bumps.jpg
+======================================
+[GPU 0] Processing bmx-trees.jpg (Image 3/50)
+======================================
+[GPU 0] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 0] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   3%|▎         | 16/500 [00:27<13:04,  1.62s/it, loss=2384.0000, t=940] 
Attacking:   3%|▎         | 17/500 [00:28<12:58,  1.61s/it, loss=2384.0000, t=940]
Attacking:   3%|▎         | 17/500 [00:28<12:58,  1.61s/it, loss=2400.0000, t=964]
Attacking:   4%|▎         | 18/500 [00:29<12:50,  1.60s/it, loss=2400.0000, t=964]
Attacking:   4%|▎         | 18/500 [00:30<12:50,  1.60s/it, loss=2400.0000, t=964]
Attacking:   4%|▍         | 19/500 [00:31<12:57,  1.62s/it, loss=2400.0000, t=964]
Attacking:   4%|▍         | 19/500 [00:32<12:57,  1.62s/it, loss=2368.0000, t=912]
Attacking:   4%|▍         | 20/500 [00:33<12:50,  1.61s/it, loss=2368.0000, t=912]
Attacking:   4%|▍         | 20/500 [00:33<12:50,  1.61s/it, loss=2384.0000, t=964]
Attacking:   4%|▍         | 21/500 [00:34<12:31,  1.57s/it, loss=2384.0000, t=964]
Attacking:   4%|▍         | 21/500 [00:35<12:31,  1.57s/it, loss=2336.0000, t=928]
Attacking:   4%|▍         | 22/500 [00:36<12:53,  1.62s/it, loss=2336.0000, t=928]
Attacking:   4%|▍         | 22/500 [00:37<12:53,  1.62s/it, loss=2352.0000, t=952]
Attacking:   5%|▍         | 23/500 [00:37<13:09,  1.65s/it, loss=2352.0000, t=952]
Attacking:   5%|▍         | 23/500 [00:38<13:09,  1.65s/it, loss=2352.0000, t=952]
Attacking:   5%|▍         | 24/500 [00:39<12:49,  1.62s/it, loss=2352.0000, t=952]
Attacking:   5%|▍         | 24/500 [00:40<12:49,  1.62s/it, loss=2336.0000, t=912]
Attacking:   5%|▌         | 25/500 [00:41<12:49,  1.62s/it, loss=2336.0000, t=912]
Attacking:   5%|▌         | 25/500 [00:41<12:49,  1.62s/it, loss=2416.0000, t=992]
Attacking:   5%|▌         | 26/500 [00:42<13:02,  1.65s/it, loss=2416.0000, t=992]
Attacking:   5%|▌         | 26/500 [00:43<13:02,  1.65s/it, loss=2336.0000, t=928]
Attacking:   5%|▌         | 27/500 [00:44<12:45,  1.62s/it, loss=2336.0000, t=928]
Attacking:   5%|▌         | 27/500 [00:45<12:45,  1.62s/it, loss=2320.0000, t=912]
Attacking:   6%|▌         | 28/500 [00:45<12:35,  1.60s/it, loss=2320.0000, t=912]
Attacking:   6%|▌         | 28/500 [00:46<12:35,  1.60s/it, loss=2368.0000, t=984]
Attacking:   6%|▌         | 29/500 [00:47<12:49,  1.63s/it, loss=2368.0000, t=984]
Attacking:   6%|▌         | 29/500 [00:48<12:49,  1.63s/it, loss=2320.0000, t=940]
Attacking:   6%|▌         | 30/500 [00:49<12:45,  1.63s/it, loss=2320.0000, t=940]
Attacking:   6%|▌         | 30/500 [00:50<12:45,  1.63s/it, loss=2336.0000, t=964]
Attacking:   6%|▌         | 31/500 [00:51<13:00,  1.67s/it, loss=2336.0000, t=964]
Attacking:   6%|▌         | 31/500 [00:51<13:00,  1.67s/it, loss=2384.0000, t=992]
Attacking:   6%|▋         | 32/500 [00:52<12:59,  1.67s/it, loss=2384.0000, t=992]
Attacking:   6%|▋         | 32/500 [00:53<12:59,  1.67s/it, loss=2352.0000, t=984]
Attacking:   7%|▋         | 33/500 [00:54<12:39,  1.63s/it, loss=2352.0000, t=984]
Attacking:   7%|▋         | 33/500 [00:55<12:39,  1.63s/it, loss=2304.0000, t=912]
Attacking:   7%|▋         | 34/500 [00:55<12:46,  1.64s/it, loss=2304.0000, t=912]
Attacking:   7%|▋         | 34/500 [00:56<12:46,  1.64s/it, loss=2288.0000, t=928]
Attacking:   7%|▋         | 35/500 [00:57<12:40,  1.64s/it, loss=2288.0000, t=928]
Attacking:   7%|▋         | 35/500 [00:58<12:40,  1.64s/it, loss=2288.0000, t=900]
Attacking:   7%|▋         | 36/500 [00:58<12:12,  1.58s/it, loss=2288.0000, t=900]
Attacking:   7%|▋         | 36/500 [00:59<12:12,  1.58s/it, loss=2320.0000, t=972]
Attacking:   7%|▋         | 37/500 [01:00<11:59,  1.55s/it, loss=2320.0000, t=972]
Attacking:   7%|▋         | 37/500 [01:01<11:59,  1.55s/it, loss=2272.0000, t=900]
Attacking:   8%|▊         | 38/500 [01:01<11:41,  1.52s/it, loss=2272.0000, t=900]
Attacking:   8%|▊         | 38/500 [01:02<11:41,  1.52s/it, loss=2336.0000, t=984]
Attacking:   8%|▊         | 39/500 [01:03<11:25,  1.49s/it, loss=2336.0000, t=984]
Attacking:   8%|▊         | 39/500 [01:04<11:25,  1.49s/it, loss=2304.0000, t=964]
Attacking:   8%|▊         | 40/500 [01:04<11:32,  1.51s/it, loss=2304.0000, t=964]
Attacking:   8%|▊         | 40/500 [01:05<11:32,  1.51s/it, loss=2288.0000, t=952]
Attacking:   8%|▊         | 41/500 [01:06<11:22,  1.49s/it, loss=2288.0000, t=952]
Attacking:   8%|▊         | 41/500 [01:06<11:22,  1.49s/it, loss=2272.0000, t=900]
Attacking:   8%|▊         | 42/500 [01:07<11:22,  1.49s/it, loss=2272.0000, t=900]
Attacking:   8%|▊         | 42/500 [01:08<11:22,  1.49s/it, loss=2304.0000, t=972]
Attacking:   9%|▊         | 43/500 [01:09<11:46,  1.55s/it, loss=2304.0000, t=972]
Attacking:   9%|▊         | 43/500 [01:10<11:46,  1.55s/it, loss=2288.0000, t=952]
Attacking:   9%|▉         | 44/500 [01:11<11:46,  1.55s/it, loss=2288.0000, t=952]
Attacking:   9%|▉         | 44/500 [01:11<11:46,  1.55s/it, loss=2288.0000, t=964]
Attacking:   9%|▉         | 45/500 [01:12<11:51,  1.56s/it, loss=2288.0000, t=964]
Attacking:   9%|▉         | 45/500 [01:13<11:51,  1.56s/it, loss=2336.0000, t=992]
Attacking:   9%|▉         | 46/500 [01:14<11:59,  1.59s/it, loss=2336.0000, t=992]
Attacking:   9%|▉         | 46/500 [01:15<11:59,  1.59s/it, loss=2272.0000, t=928]
Attacking:   9%|▉         | 47/500 [01:15<11:52,  1.57s/it, loss=2272.0000, t=928]
Attacking:   9%|▉         | 47/500 [01:16<11:52,  1.57s/it, loss=2272.0000, t=912]
Attacking:  10%|▉         | 48/500 [01:17<12:01,  1.60s/it, loss=2272.0000, t=912]
Attacking:  10%|▉         | 48/500 [01:18<12:01,  1.60s/it, loss=2304.0000, t=984]
Attacking:  10%|▉         | 49/500 [01:19<12:07,  1.61s/it, loss=2304.0000, t=984]
Attacking:  10%|▉         | 49/500 [01:19<12:07,  1.61s/it, loss=2336.0000, t=1e+3]
Attacking:  10%|█         | 50/500 [01:20<12:03,  1.61s/it, loss=2336.0000, t=1e+3]
Attacking:  10%|█         | 50/500 [01:21<12:03,  1.61s/it, loss=2272.0000, t=952] 
Attacking:  10%|█         | 51/500 [01:22<11:56,  1.60s/it, loss=2272.0000, t=952]
Attacking:  10%|█         | 51/500 [01:23<11:56,  1.60s/it, loss=2288.0000, t=964]
Attacking:  10%|█         | 52/500 [01:23<12:04,  1.62s/it, loss=2288.0000, t=964]
Attacking:  10%|█         | 52/500 [01:24<12:04,  1.62s/it, loss=2320.0000, t=992]
Attacking:  11%|█         | 53/500 [01:25<12:04,  1.62s/it, loss=2320.0000, t=992]
Attacking:  11%|█         | 53/500 [01:26<12:04,  1.62s/it, loss=2256.0000, t=900]
Attacking:  11%|█         | 54/500 [01:27<11:55,  1.60s/it, loss=2256.0000, t=900]
Attacking:  11%|█         | 54/500 [01:27<11:55,  1.60s/it, loss=2240.0000, t=900]
Attacking:  11%|█         | 55/500 [01:28<11:38,  1.57s/it, loss=2240.0000, t=900]
Attacking:  11%|█         | 55/500 [01:29<11:38,  1.57s/it, loss=2256.0000, t=940]
Attacking:  11%|█         | 56/500 [01:30<11:16,  1.52s/it, loss=2256.0000, t=940]
Attacking:  11%|█         | 56/500 [01:30<11:16,  1.52s/it, loss=2240.0000, t=928]
Attacking:  11%|█▏        | 57/500 [01:31<10:58,  1.49s/it, loss=2240.0000, t=928]
Attacking:  11%|█▏        | 57/500 [01:32<10:58,  1.49s/it, loss=2272.0000, t=972]
Attacking:  12%|█▏        | 58/500 [01:32<10:52,  1.48s/it, loss=2272.0000, t=972]
Attacking:  12%|█▏        | 58/500 [01:33<10:52,  1.48s/it, loss=2304.0000, t=992]
Attacking:  12%|█▏        | 59/500 [01:34<11:23,  1.55s/it, loss=2304.0000, t=992]
Attacking:  12%|█▏        | 59/500 [01:35<11:23,  1.55s/it, loss=2288.0000, t=984]
Attacking:  12%|█▏        | 60/500 [01:36<11:11,  1.53s/it, loss=2288.0000, t=984]
Attacking:  12%|█▏        | 60/500 [01:36<11:11,  1.53s/it, loss=2288.0000, t=984]
Attacking:  12%|█▏        | 61/500 [01:37<11:24,  1.56s/it, loss=2288.0000, t=984]
Attacking:  12%|█▏        | 61/500 [01:38<11:24,  1.56s/it, loss=2240.0000, t=940]
Attacking:  12%|█▏        | 62/500 [01:39<11:29,  1.57s/it, loss=2240.0000, t=940]
Attacking:  12%|█▏        | 62/500 [01:40<11:29,  1.57s/it, loss=2304.0000, t=992]
Attacking:  13%|█▎        | 63/500 [01:41<11:37,  1.60s/it, loss=2304.0000, t=992]
Attacking:  13%|█▎        | 63/500 [01:41<11:37,  1.60s/it, loss=2240.0000, t=912]
Attacking:  13%|█▎        | 64/500 [01:42<11:28,  1.58s/it, loss=2240.0000, t=912]
Attacking:  13%|█▎        | 64/500 [01:43<11:28,  1.58s/it, loss=2256.0000, t=964]
Attacking:  13%|█▎        | 65/500 [01:44<11:29,  1.59s/it, loss=2256.0000, t=964]
Attacking:  13%|█▎        | 65/500 [01:45<11:29,  1.59s/it, loss=2256.0000, t=972]
Attacking:  13%|█▎        | 66/500 [01:45<11:50,  1.64s/it, loss=2256.0000, t=972]
Attacking:  13%|█▎        | 66/500 [01:46<11:50,  1.64s/it, loss=2240.0000, t=952]
Attacking:  13%|█▎        | 67/500 [01:47<12:10,  1.69s/it, loss=2240.0000, t=952]
Attacking:  13%|█▎        | 67/500 [01:48<12:10,  1.69s/it, loss=2288.0000, t=972]
Attacking:  14%|█▎        | 68/500 [01:49<11:52,  1.65s/it, loss=2288.0000, t=972]
Attacking:  14%|█▎        | 68/500 [01:49<11:52,  1.65s/it, loss=2224.0000, t=940]
Attacking:  14%|█▍        | 69/500 [01:50<11:32,  1.61s/it, loss=2224.0000, t=940]
Attacking:  14%|█▍        | 69/500 [01:51<11:32,  1.61s/it, loss=2256.0000, t=964]
Attacking:  14%|█▍        | 70/500 [01:52<11:32,  1.61s/it, loss=2256.0000, t=964]
Attacking:  14%|█▍        | 70/500 [01:53<11:32,  1.61s/it, loss=2224.0000, t=900]
Attacking:  14%|█▍        | 71/500 [01:54<11:49,  1.65s/it, loss=2224.0000, t=900]
Attacking:  14%|█▍        | 71/500 [01:54<11:49,  1.65s/it, loss=2272.0000, t=984]
Attacking:  14%|█▍        | 72/500 [01:55<11:45,  1.65s/it, loss=2272.0000, t=984]
Attacking:  14%|█▍        | 72/500 [01:56<11:45,  1.65s/it, loss=2224.0000, t=928]
Attacking:  15%|█▍        | 73/500 [01:57<11:39,  1.64s/it, loss=2224.0000, t=928]
Attacking:  15%|█▍        | 73/500 [01:58<11:39,  1.64s/it, loss=2304.0000, t=992]
Attacking:  15%|█▍        | 74/500 [01:59<11:59,  1.69s/it, loss=2304.0000, t=992]
Attacking:  15%|█▍        | 74/500 [02:00<11:59,  1.69s/it, loss=2304.0000, t=1e+3]
Attacking:  15%|█▌        | 75/500 [02:00<11:58,  1.69s/it, loss=2304.0000, t=1e+3]
Attacking:  15%|█▌        | 75/500 [02:01<11:58,  1.69s/it, loss=2256.0000, t=972] 
Attacking:  15%|█▌        | 76/500 [02:02<11:37,  1.65s/it, loss=2256.0000, t=972]
Attacking:  15%|█▌        | 76/500 [02:03<11:37,  1.65s/it, loss=2224.0000, t=900]
Attacking:  15%|█▌        | 77/500 [02:04<11:29,  1.63s/it, loss=2224.0000, t=900]
Attacking:  15%|█▌        | 77/500 [02:04<11:29,  1.63s/it, loss=2272.0000, t=984]
Attacking:  16%|█▌        | 78/500 [02:05<11:30,  1.64s/it, loss=2272.0000, t=984]
Attacking:  16%|█▌        | 78/500 [02:06<11:30,  1.64s/it, loss=2272.0000, t=984]
Attacking:  16%|█▌        | 79/500 [02:07<11:11,  1.60s/it, loss=2272.0000, t=984]
Attacking:  16%|█▌        | 79/500 [02:07<11:11,  1.60s/it, loss=2224.0000, t=900]
Attacking:  16%|█▌        | 80/500 [02:08<11:13,  1.60s/it, loss=2224.0000, t=900]
Attacking:  16%|█▌        | 80/500 [02:09<11:13,  1.60s/it, loss=2208.0000, t=912]
Attacking:  16%|█▌        | 81/500 [02:10<11:25,  1.63s/it, loss=2208.0000, t=912]
Attacking:  16%|█▌        | 81/500 [02:11<11:25,  1.63s/it, loss=2224.0000, t=928]
Attacking:  16%|█▋        | 82/500 [02:12<11:29,  1.65s/it, loss=2224.0000, t=928]
Attacking:  16%|█▋        | 82/500 [02:12<11:29,  1.65s/it, loss=2224.0000, t=940]
Attacking:  17%|█▋        | 83/500 [02:13<11:16,  1.62s/it, loss=2224.0000, t=940]
Attacking:  17%|█▋        | 83/500 [02:14<11:16,  1.62s/it, loss=2304.0000, t=1e+3]
Attacking:  17%|█▋        | 84/500 [02:15<11:18,  1.63s/it, loss=2304.0000, t=1e+3]
Attacking:  17%|█▋        | 84/500 [02:16<11:18,  1.63s/it, loss=2272.0000, t=1e+3]
Attacking:  17%|█▋        | 85/500 [02:17<11:09,  1.61s/it, loss=2272.0000, t=1e+3]
Attacking:  17%|█▋        | 85/500 [02:17<11:09,  1.61s/it, loss=2224.0000, t=952] 
Attacking:  17%|█▋        | 86/500 [02:18<11:00,  1.59s/it, loss=2224.0000, t=952]
Attacking:  17%|█▋        | 86/500 [02:19<11:00,  1.59s/it, loss=2288.0000, t=1e+3]
Attacking:  17%|█▋        | 87/500 [02:20<10:55,  1.59s/it, loss=2288.0000, t=1e+3]
Attacking:  17%|█▋        | 87/500 [02:20<10:55,  1.59s/it, loss=2240.0000, t=972] 
Attacking:  18%|█▊        | 88/500 [02:21<10:39,  1.55s/it, loss=2240.0000, t=972]
Attacking:  18%|█▊        | 88/500 [02:22<10:39,  1.55s/it, loss=2272.0000, t=992]
Attacking:  18%|█▊        | 89/500 [02:23<10:41,  1.56s/it, loss=2272.0000, t=992]
Attacking:  18%|█▊        | 89/500 [02:23<10:41,  1.56s/it, loss=2240.0000, t=964]
Attacking:  18%|█▊        | 90/500 [02:24<10:30,  1.54s/it, loss=2240.0000, t=964]
Attacking:  18%|█▊        | 90/500 [02:25<10:30,  1.54s/it, loss=2208.0000, t=912]
Attacking:  18%|█▊        | 91/500 [02:26<10:33,  1.55s/it, loss=2208.0000, t=912]
Attacking:  18%|█▊        | 91/500 [02:26<10:33,  1.55s/it, loss=2272.0000, t=1e+3]
Attacking:  18%|█▊        | 92/500 [02:27<10:36,  1.56s/it, loss=2272.0000, t=1e+3]
Attacking:  18%|█▊        | 92/500 [02:28<10:36,  1.56s/it, loss=2208.0000, t=900] 
Attacking:  19%|█▊        | 93/500 [02:29<10:30,  1.55s/it, loss=2208.0000, t=900]
Attacking:  19%|█▊        | 93/500 [02:29<10:30,  1.55s/it, loss=2240.0000, t=964]
Attacking:  19%|█▉        | 94/500 [02:30<10:26,  1.54s/it, loss=2240.0000, t=964]
Attacking:  19%|█▉        | 94/500 [02:31<10:26,  1.54s/it, loss=2208.0000, t=900]
Attacking:  19%|█▉        | 95/500 [02:32<10:19,  1.53s/it, loss=2208.0000, t=900]
Attacking:  19%|█▉        | 95/500 [02:33<10:19,  1.53s/it, loss=2272.0000, t=992]
Attacking:  19%|█▉        | 96/500 [02:33<10:13,  1.52s/it, loss=2272.0000, t=992]
Attacking:  19%|█▉        | 96/500 [02:34<10:13,  1.52s/it, loss=2272.0000, t=992]
Attacking:  19%|█▉        | 97/500 [02:35<10:18,  1.54s/it, loss=2272.0000, t=992]
Attacking:  19%|█▉        | 97/500 [02:36<10:18,  1.54s/it, loss=2224.0000, t=964]
Attacking:  20%|█▉        | 98/500 [02:37<10:35,  1.58s/it, loss=2224.0000, t=964]
Attacking:  20%|█▉        | 98/500 [02:37<10:35,  1.58s/it, loss=2192.0000, t=928]
Attacking:  20%|█▉        | 99/500 [02:38<10:14,  1.53s/it, loss=2192.0000, t=928]
Attacking:  20%|█▉        | 99/500 [02:39<10:14,  1.53s/it, loss=2256.0000, t=984]
Attacking:  20%|██        | 100/500 [02:40<10:28,  1.57s/it, loss=2256.0000, t=984]
Attacking:  20%|██        | 100/500 [02:41<10:28,  1.57s/it, loss=2192.0000, t=900]
Attacking:  20%|██        | 101/500 [02:42<10:57,  1.65s/it, loss=2192.0000, t=900]
Attacking:  20%|██        | 101/500 [02:42<10:57,  1.65s/it, loss=2208.0000, t=940]
Attacking:  20%|██        | 102/500 [02:43<11:00,  1.66s/it, loss=2208.0000, t=940]
Attacking:  20%|██        | 102/500 [02:44<11:00,  1.66s/it, loss=2256.0000, t=984]
Attacking:  21%|██        | 103/500 [02:45<10:39,  1.61s/it, loss=2256.0000, t=984]
Attacking:  21%|██        | 103/500 [02:46<10:39,  1.61s/it, loss=2272.0000, t=1e+3]
Attacking:  21%|██        | 104/500 [02:46<10:50,  1.64s/it, loss=2272.0000, t=1e+3]
Attacking:  21%|██        | 104/500 [02:47<10:50,  1.64s/it, loss=2256.0000, t=992] 
Attacking:  21%|██        | 105/500 [02:48<10:38,  1.62s/it, loss=2256.0000, t=992]
Attacking:  21%|██        | 105/500 [02:49<10:38,  1.62s/it, loss=2224.0000, t=964]
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Attacking: 100%|██████████| 500/500 [12:52<00:00,  1.55s/it, loss=2112.0000, t=912]
+Max Diff: 0.501961
+Mean Diff: 0.217792
+Saved adversarial image to attacked/images/bmx-trees.jpg
+Saved loss curve to attacked/loss_curve/bmx-trees_loss.png
+[GPU 0] Stage 3/3: Test
+Loading models for testing bmx-trees...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for bmx-trees...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
Saving video:   6%|▌         | 1/17 [00:00<00:02,  6.30it/s]
Saving video: 100%|██████████| 17/17 [00:00<00:00, 87.21it/s]
+Saved video to attacked/videos/bmx-trees.mp4
+Saved frames to attacked/frames/bmx-trees
+[GPU 0] Finished bmx-trees.jpg
+======================================
+[GPU 0] Processing boat.jpg (Image 4/50)
+======================================
+[GPU 0] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 0] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  13%|█▎        | 64/500 [01:42<11:13,  1.55s/it, loss=2032.0000, t=940]
Attacking:  13%|█▎        | 65/500 [01:43<11:19,  1.56s/it, loss=2032.0000, t=940]
Attacking:  13%|█▎        | 65/500 [01:43<11:19,  1.56s/it, loss=2040.0000, t=964]
Attacking:  13%|█▎        | 66/500 [01:44<11:24,  1.58s/it, loss=2040.0000, t=964]
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Attacking:  13%|█▎        | 67/500 [01:46<11:20,  1.57s/it, loss=1984.0000, t=912]
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Attacking:  14%|█▎        | 68/500 [01:47<11:21,  1.58s/it, loss=2008.0000, t=940]
Attacking:  14%|█▎        | 68/500 [01:48<11:21,  1.58s/it, loss=2000.0000, t=928]
Attacking:  14%|█▍        | 69/500 [01:49<11:30,  1.60s/it, loss=2000.0000, t=928]
Attacking:  14%|█▍        | 69/500 [01:50<11:30,  1.60s/it, loss=2112.0000, t=1e+3]
Attacking:  14%|█▍        | 70/500 [01:51<11:38,  1.62s/it, loss=2112.0000, t=1e+3]
Attacking:  14%|█▍        | 70/500 [01:51<11:38,  1.62s/it, loss=2048.0000, t=972] 
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Attacking:  14%|█▍        | 72/500 [01:54<11:16,  1.58s/it, loss=2000.0000, t=928]
Attacking:  14%|█▍        | 72/500 [01:55<11:16,  1.58s/it, loss=2016.0000, t=940]
Attacking:  15%|█▍        | 73/500 [01:56<11:19,  1.59s/it, loss=2016.0000, t=940]
Attacking:  15%|█▍        | 73/500 [01:56<11:19,  1.59s/it, loss=2040.0000, t=992]
Attacking:  15%|█▍        | 74/500 [01:57<11:05,  1.56s/it, loss=2040.0000, t=992]
Attacking:  15%|█▍        | 74/500 [01:58<11:05,  1.56s/it, loss=1976.0000, t=900]
Attacking:  15%|█▌        | 75/500 [01:58<10:55,  1.54s/it, loss=1976.0000, t=900]
Attacking:  15%|█▌        | 75/500 [01:59<10:55,  1.54s/it, loss=2064.0000, t=984]
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Attacking:  15%|█▌        | 77/500 [02:01<10:44,  1.52s/it, loss=2016.0000, t=964]
Attacking:  15%|█▌        | 77/500 [02:02<10:44,  1.52s/it, loss=2040.0000, t=972]
Attacking:  16%|█▌        | 78/500 [02:03<10:54,  1.55s/it, loss=2040.0000, t=972]
Attacking:  16%|█▌        | 78/500 [02:04<10:54,  1.55s/it, loss=2016.0000, t=952]
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Attacking:  16%|█▌        | 79/500 [02:06<11:03,  1.58s/it, loss=2032.0000, t=964]
Attacking:  16%|█▌        | 80/500 [02:06<11:10,  1.60s/it, loss=2032.0000, t=964]
Attacking:  16%|█▌        | 80/500 [02:07<11:10,  1.60s/it, loss=2000.0000, t=940]
Attacking:  16%|█▌        | 81/500 [02:08<10:53,  1.56s/it, loss=2000.0000, t=940]
Attacking:  16%|█▌        | 81/500 [02:09<10:53,  1.56s/it, loss=2032.0000, t=964]
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Attacking:  16%|█▋        | 82/500 [02:10<11:06,  1.60s/it, loss=2096.0000, t=1e+3]
Attacking:  17%|█▋        | 83/500 [02:11<11:15,  1.62s/it, loss=2096.0000, t=1e+3]
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Attacking:  17%|█▋        | 84/500 [02:13<11:16,  1.63s/it, loss=2000.0000, t=928]
Attacking:  17%|█▋        | 84/500 [02:14<11:16,  1.63s/it, loss=1960.0000, t=900]
Attacking:  17%|█▋        | 85/500 [02:15<11:23,  1.65s/it, loss=1960.0000, t=900]
Attacking:  17%|█▋        | 85/500 [02:15<11:23,  1.65s/it, loss=2000.0000, t=952]
Attacking:  17%|█▋        | 86/500 [02:16<11:25,  1.66s/it, loss=2000.0000, t=952]
Attacking:  17%|█▋        | 86/500 [02:17<11:25,  1.66s/it, loss=1992.0000, t=940]
Attacking:  17%|█▋        | 87/500 [02:18<11:13,  1.63s/it, loss=1992.0000, t=940]
Attacking:  17%|█▋        | 87/500 [02:18<11:13,  1.63s/it, loss=2032.0000, t=972]
Attacking:  18%|█▊        | 88/500 [02:19<10:59,  1.60s/it, loss=2032.0000, t=972]
Attacking:  18%|█▊        | 88/500 [02:20<10:59,  1.60s/it, loss=1968.0000, t=912]
Attacking:  18%|█▊        | 89/500 [02:21<10:45,  1.57s/it, loss=1968.0000, t=912]
Attacking:  18%|█▊        | 89/500 [02:21<10:45,  1.57s/it, loss=1968.0000, t=912]
Attacking:  18%|█▊        | 90/500 [02:22<10:38,  1.56s/it, loss=1968.0000, t=912]
Attacking:  18%|█▊        | 90/500 [02:23<10:38,  1.56s/it, loss=2032.0000, t=992]
Attacking:  18%|█▊        | 91/500 [02:24<10:36,  1.56s/it, loss=2032.0000, t=992]
Attacking:  18%|█▊        | 91/500 [02:25<10:36,  1.56s/it, loss=1984.0000, t=940]
Attacking:  18%|█▊        | 92/500 [02:26<10:55,  1.61s/it, loss=1984.0000, t=940]
Attacking:  18%|█▊        | 92/500 [02:26<10:55,  1.61s/it, loss=2000.0000, t=952]
Attacking:  19%|█▊        | 93/500 [02:27<10:54,  1.61s/it, loss=2000.0000, t=952]
Attacking:  19%|█▊        | 93/500 [02:28<10:54,  1.61s/it, loss=1968.0000, t=912]
Attacking:  19%|█▉        | 94/500 [02:29<10:54,  1.61s/it, loss=1968.0000, t=912]
Attacking:  19%|█▉        | 94/500 [02:30<10:54,  1.61s/it, loss=2048.0000, t=984]
Attacking:  19%|█▉        | 95/500 [02:30<10:39,  1.58s/it, loss=2048.0000, t=984]
Attacking:  19%|█▉        | 95/500 [02:31<10:39,  1.58s/it, loss=2080.0000, t=1e+3]
Attacking:  19%|█▉        | 96/500 [02:32<10:41,  1.59s/it, loss=2080.0000, t=1e+3]
Attacking:  19%|█▉        | 96/500 [02:33<10:41,  1.59s/it, loss=2024.0000, t=992] 
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Attacking:  19%|█▉        | 97/500 [02:34<10:25,  1.55s/it, loss=1968.0000, t=900]
Attacking:  20%|█▉        | 98/500 [02:35<10:17,  1.54s/it, loss=1968.0000, t=900]
Attacking:  20%|█▉        | 98/500 [02:36<10:17,  1.54s/it, loss=1968.0000, t=912]
Attacking:  20%|█▉        | 99/500 [02:37<10:24,  1.56s/it, loss=1968.0000, t=912]
Attacking:  20%|█▉        | 99/500 [02:37<10:24,  1.56s/it, loss=1952.0000, t=900]
Attacking:  20%|██        | 100/500 [02:38<10:19,  1.55s/it, loss=1952.0000, t=900]
Attacking:  20%|██        | 100/500 [02:39<10:19,  1.55s/it, loss=2048.0000, t=984]
Attacking:  20%|██        | 101/500 [02:40<10:16,  1.54s/it, loss=2048.0000, t=984]
Attacking:  20%|██        | 101/500 [02:40<10:16,  1.54s/it, loss=2016.0000, t=992]
Attacking:  20%|██        | 102/500 [02:41<10:15,  1.55s/it, loss=2016.0000, t=992]
Attacking:  20%|██        | 102/500 [02:42<10:15,  1.55s/it, loss=2008.0000, t=964]
Attacking:  21%|██        | 103/500 [02:43<10:33,  1.60s/it, loss=2008.0000, t=964]
Attacking:  21%|██        | 103/500 [02:44<10:33,  1.60s/it, loss=1984.0000, t=952]
Attacking:  21%|██        | 104/500 [02:45<10:47,  1.64s/it, loss=1984.0000, t=952]
Attacking:  21%|██        | 104/500 [02:45<10:47,  1.64s/it, loss=1968.0000, t=940]
Attacking:  21%|██        | 105/500 [02:46<10:40,  1.62s/it, loss=1968.0000, t=940]
Attacking:  21%|██        | 105/500 [02:47<10:40,  1.62s/it, loss=2064.0000, t=1e+3]
Attacking:  21%|██        | 106/500 [02:48<10:30,  1.60s/it, loss=2064.0000, t=1e+3]
Attacking:  21%|██        | 106/500 [02:49<10:30,  1.60s/it, loss=1952.0000, t=900] 
Attacking:  21%|██▏       | 107/500 [02:49<10:33,  1.61s/it, loss=1952.0000, t=900]
Attacking:  21%|██▏       | 107/500 [02:50<10:33,  1.61s/it, loss=2016.0000, t=972]
Attacking:  22%|██▏       | 108/500 [02:51<10:37,  1.63s/it, loss=2016.0000, t=972]
Attacking:  22%|██▏       | 108/500 [02:52<10:37,  1.63s/it, loss=1952.0000, t=912]
Attacking:  22%|██▏       | 109/500 [02:53<10:43,  1.65s/it, loss=1952.0000, t=912]
Attacking:  22%|██▏       | 109/500 [02:53<10:43,  1.65s/it, loss=2016.0000, t=992]
Attacking:  22%|██▏       | 110/500 [02:54<10:36,  1.63s/it, loss=2016.0000, t=992]
Attacking:  22%|██▏       | 110/500 [02:55<10:36,  1.63s/it, loss=2000.0000, t=964]
Attacking:  22%|██▏       | 111/500 [02:56<10:28,  1.62s/it, loss=2000.0000, t=964]
Attacking:  22%|██▏       | 111/500 [02:57<10:28,  1.62s/it, loss=1960.0000, t=912]
Attacking:  22%|██▏       | 112/500 [02:58<10:30,  1.62s/it, loss=1960.0000, t=912]
Attacking:  22%|██▏       | 112/500 [02:58<10:30,  1.62s/it, loss=2000.0000, t=964]
Attacking:  23%|██▎       | 113/500 [02:59<10:22,  1.61s/it, loss=2000.0000, t=964]
Attacking:  23%|██▎       | 113/500 [03:00<10:22,  1.61s/it, loss=1992.0000, t=964]
Attacking:  23%|██▎       | 114/500 [03:01<10:06,  1.57s/it, loss=1992.0000, t=964]
Attacking:  23%|██▎       | 114/500 [03:01<10:06,  1.57s/it, loss=2008.0000, t=992]
Attacking:  23%|██▎       | 115/500 [03:02<10:02,  1.57s/it, loss=2008.0000, t=992]
Attacking:  23%|██▎       | 115/500 [03:03<10:02,  1.57s/it, loss=2000.0000, t=992]
Attacking:  23%|██▎       | 116/500 [03:04<09:50,  1.54s/it, loss=2000.0000, t=992]
Attacking:  23%|██▎       | 116/500 [03:04<09:50,  1.54s/it, loss=1944.0000, t=912]
Attacking:  23%|██▎       | 117/500 [03:05<09:38,  1.51s/it, loss=1944.0000, t=912]
Attacking:  23%|██▎       | 117/500 [03:06<09:38,  1.51s/it, loss=1976.0000, t=952]
Attacking:  24%|██▎       | 118/500 [03:07<09:26,  1.48s/it, loss=1976.0000, t=952]
Attacking:  24%|██▎       | 118/500 [03:07<09:26,  1.48s/it, loss=2024.0000, t=984]
Attacking:  24%|██▍       | 119/500 [03:08<09:30,  1.50s/it, loss=2024.0000, t=984]
Attacking:  24%|██▍       | 119/500 [03:09<09:30,  1.50s/it, loss=1944.0000, t=900]
Attacking:  24%|██▍       | 120/500 [03:10<10:08,  1.60s/it, loss=1944.0000, t=900]
Attacking:  24%|██▍       | 120/500 [03:11<10:08,  1.60s/it, loss=1944.0000, t=912]
Attacking:  24%|██▍       | 121/500 [03:11<09:58,  1.58s/it, loss=1944.0000, t=912]
Attacking:  24%|██▍       | 121/500 [03:12<09:58,  1.58s/it, loss=1936.0000, t=900]
Attacking:  24%|██▍       | 122/500 [03:13<09:53,  1.57s/it, loss=1936.0000, t=900]
Attacking:  24%|██▍       | 122/500 [03:14<09:53,  1.57s/it, loss=1968.0000, t=940]
Attacking:  25%|██▍       | 123/500 [03:15<10:03,  1.60s/it, loss=1968.0000, t=940]
Attacking:  25%|██▍       | 123/500 [03:15<10:03,  1.60s/it, loss=2024.0000, t=984]
Attacking:  25%|██▍       | 124/500 [03:16<09:49,  1.57s/it, loss=2024.0000, t=984]
Attacking:  25%|██▍       | 124/500 [03:17<09:49,  1.57s/it, loss=2000.0000, t=992]
Attacking:  25%|██▌       | 125/500 [03:18<09:50,  1.57s/it, loss=2000.0000, t=992]
Attacking:  25%|██▌       | 125/500 [03:18<09:50,  1.57s/it, loss=1968.0000, t=940]
Attacking:  25%|██▌       | 126/500 [03:19<09:56,  1.60s/it, loss=1968.0000, t=940]
Attacking:  25%|██▌       | 126/500 [03:20<09:56,  1.60s/it, loss=1976.0000, t=952]
Attacking:  25%|██▌       | 127/500 [03:21<10:01,  1.61s/it, loss=1976.0000, t=952]
Attacking:  25%|██▌       | 127/500 [03:22<10:01,  1.61s/it, loss=1984.0000, t=964]
Attacking:  26%|██▌       | 128/500 [03:23<09:56,  1.60s/it, loss=1984.0000, t=964]
Attacking:  26%|██▌       | 128/500 [03:23<09:56,  1.60s/it, loss=1928.0000, t=900]
Attacking:  26%|██▌       | 129/500 [03:24<09:50,  1.59s/it, loss=1928.0000, t=900]
Attacking:  26%|██▌       | 129/500 [03:25<09:50,  1.59s/it, loss=2000.0000, t=972]
Attacking:  26%|██▌       | 130/500 [03:26<10:00,  1.62s/it, loss=2000.0000, t=972]
Attacking:  26%|██▌       | 130/500 [03:26<10:00,  1.62s/it, loss=1952.0000, t=940]
Attacking:  26%|██▌       | 131/500 [03:27<09:36,  1.56s/it, loss=1952.0000, t=940]
Attacking:  26%|██▌       | 131/500 [03:28<09:36,  1.56s/it, loss=1992.0000, t=972]
Attacking:  26%|██▋       | 132/500 [03:29<09:43,  1.59s/it, loss=1992.0000, t=972]
Attacking:  26%|██▋       | 132/500 [03:30<09:43,  1.59s/it, loss=1992.0000, t=972]
Attacking:  27%|██▋       | 133/500 [03:30<09:26,  1.54s/it, loss=1992.0000, t=972]
Attacking:  27%|██▋       | 133/500 [03:31<09:26,  1.54s/it, loss=1992.0000, t=972]
Attacking:  27%|██▋       | 134/500 [03:32<09:35,  1.57s/it, loss=1992.0000, t=972]
Attacking:  27%|██▋       | 134/500 [03:33<09:35,  1.57s/it, loss=1984.0000, t=972]
Attacking:  27%|██▋       | 135/500 [03:33<09:21,  1.54s/it, loss=1984.0000, t=972]
Attacking:  27%|██▋       | 135/500 [03:34<09:21,  1.54s/it, loss=1984.0000, t=964]
Attacking:  27%|██▋       | 136/500 [03:35<09:08,  1.51s/it, loss=1984.0000, t=964]
Attacking:  27%|██▋       | 136/500 [03:35<09:08,  1.51s/it, loss=1984.0000, t=972]
Attacking:  27%|██▋       | 137/500 [03:36<08:58,  1.48s/it, loss=1984.0000, t=972]
Attacking:  27%|██▋       | 137/500 [03:37<08:58,  1.48s/it, loss=1936.0000, t=912]
Attacking:  28%|██▊       | 138/500 [03:38<08:48,  1.46s/it, loss=1936.0000, t=912]
Attacking:  28%|██▊       | 138/500 [03:38<08:48,  1.46s/it, loss=1960.0000, t=952]
Attacking:  28%|██▊       | 139/500 [03:39<08:57,  1.49s/it, loss=1960.0000, t=952]
Attacking:  28%|██▊       | 139/500 [03:40<08:57,  1.49s/it, loss=1992.0000, t=972]
Attacking:  28%|██▊       | 140/500 [03:41<08:53,  1.48s/it, loss=1992.0000, t=972]
Attacking:  28%|██▊       | 140/500 [03:41<08:53,  1.48s/it, loss=2048.0000, t=1e+3]
Attacking:  28%|██▊       | 141/500 [03:42<08:57,  1.50s/it, loss=2048.0000, t=1e+3]
Attacking:  28%|██▊       | 141/500 [03:43<08:57,  1.50s/it, loss=1992.0000, t=972] 
Attacking:  28%|██▊       | 142/500 [03:44<09:05,  1.52s/it, loss=1992.0000, t=972]
Attacking:  28%|██▊       | 142/500 [03:45<09:05,  1.52s/it, loss=1928.0000, t=912]
Attacking:  29%|██▊       | 143/500 [03:45<09:04,  1.53s/it, loss=1928.0000, t=912]
Attacking:  29%|██▊       | 143/500 [03:46<09:04,  1.53s/it, loss=1992.0000, t=992]
Attacking:  29%|██▉       | 144/500 [03:47<09:14,  1.56s/it, loss=1992.0000, t=992]
Attacking:  29%|██▉       | 144/500 [03:48<09:14,  1.56s/it, loss=1952.0000, t=940]
Attacking:  29%|██▉       | 145/500 [03:49<09:20,  1.58s/it, loss=1952.0000, t=940]
Attacking:  29%|██▉       | 145/500 [03:49<09:20,  1.58s/it, loss=1944.0000, t=928]
Attacking:  29%|██▉       | 146/500 [03:50<09:13,  1.56s/it, loss=1944.0000, t=928]
Attacking:  29%|██▉       | 146/500 [03:51<09:13,  1.56s/it, loss=1928.0000, t=900]
Attacking:  29%|██▉       | 147/500 [03:52<09:11,  1.56s/it, loss=1928.0000, t=900]
Attacking:  29%|██▉       | 147/500 [03:53<09:11,  1.56s/it, loss=1928.0000, t=900]
Attacking:  30%|██▉       | 148/500 [03:53<09:22,  1.60s/it, loss=1928.0000, t=900]
Attacking:  30%|██▉       | 148/500 [03:54<09:22,  1.60s/it, loss=1960.0000, t=940]
Attacking:  30%|██▉       | 149/500 [03:55<09:14,  1.58s/it, loss=1960.0000, t=940]
Attacking:  30%|██▉       | 149/500 [03:56<09:14,  1.58s/it, loss=1984.0000, t=972]
Attacking:  30%|███       | 150/500 [03:56<09:07,  1.57s/it, loss=1984.0000, t=972]
Attacking:  30%|███       | 150/500 [03:57<09:07,  1.57s/it, loss=1920.0000, t=900]
Attacking:  30%|███       | 151/500 [03:58<09:12,  1.58s/it, loss=1920.0000, t=900]
Attacking:  30%|███       | 151/500 [03:59<09:12,  1.58s/it, loss=2040.0000, t=1e+3]
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Attacking:  91%|█████████▏| 457/500 [11:48<01:06,  1.54s/it, loss=1960.0000, t=984]
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Attacking: 100%|██████████| 500/500 [12:53<00:00,  1.55s/it, loss=1888.0000, t=912]
+Max Diff: 0.501961
+Mean Diff: 0.246876
+Saved adversarial image to attacked/images/boat.jpg
+Saved loss curve to attacked/loss_curve/boat_loss.png
+[GPU 0] Stage 3/3: Test
+Loading models for testing boat...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for boat...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 79.64it/s]
+Saved video to attacked/videos/boat.mp4
+Saved frames to attacked/frames/boat
+[GPU 0] Finished boat.jpg
+======================================
+[GPU 0] Processing breakdance-flare.jpg (Image 5/50)
+======================================
+[GPU 0] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 0] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   5%|▍         | 23/500 [00:37<12:27,  1.57s/it, loss=2208.0000, t=940]
Attacking:   5%|▍         | 24/500 [00:38<12:40,  1.60s/it, loss=2208.0000, t=940]
Attacking:   5%|▍         | 24/500 [00:39<12:40,  1.60s/it, loss=2176.0000, t=900]
Attacking:   5%|▌         | 25/500 [00:39<12:54,  1.63s/it, loss=2176.0000, t=900]
Attacking:   5%|▌         | 25/500 [00:40<12:54,  1.63s/it, loss=2240.0000, t=964]
Attacking:   5%|▌         | 26/500 [00:41<12:42,  1.61s/it, loss=2240.0000, t=964]
Attacking:   5%|▌         | 26/500 [00:42<12:42,  1.61s/it, loss=2288.0000, t=1e+3]
Attacking:   5%|▌         | 27/500 [00:43<12:49,  1.63s/it, loss=2288.0000, t=1e+3]
Attacking:   5%|▌         | 27/500 [00:43<12:49,  1.63s/it, loss=2192.0000, t=928] 
Attacking:   6%|▌         | 28/500 [00:44<12:53,  1.64s/it, loss=2192.0000, t=928]
Attacking:   6%|▌         | 28/500 [00:45<12:53,  1.64s/it, loss=2240.0000, t=972]
Attacking:   6%|▌         | 29/500 [00:46<12:56,  1.65s/it, loss=2240.0000, t=972]
Attacking:   6%|▌         | 29/500 [00:47<12:56,  1.65s/it, loss=2208.0000, t=964]
Attacking:   6%|▌         | 30/500 [00:47<12:28,  1.59s/it, loss=2208.0000, t=964]
Attacking:   6%|▌         | 30/500 [00:48<12:28,  1.59s/it, loss=2256.0000, t=992]
Attacking:   6%|▌         | 31/500 [00:49<12:34,  1.61s/it, loss=2256.0000, t=992]
Attacking:   6%|▌         | 31/500 [00:50<12:34,  1.61s/it, loss=2208.0000, t=984]
Attacking:   6%|▋         | 32/500 [00:51<12:42,  1.63s/it, loss=2208.0000, t=984]
Attacking:   6%|▋         | 32/500 [00:52<12:42,  1.63s/it, loss=2208.0000, t=964]
Attacking:   7%|▋         | 33/500 [00:52<12:43,  1.63s/it, loss=2208.0000, t=964]
Attacking:   7%|▋         | 33/500 [00:53<12:43,  1.63s/it, loss=2240.0000, t=1e+3]
Attacking:   7%|▋         | 34/500 [00:54<12:39,  1.63s/it, loss=2240.0000, t=1e+3]
Attacking:   7%|▋         | 34/500 [00:55<12:39,  1.63s/it, loss=2176.0000, t=940] 
Attacking:   7%|▋         | 35/500 [00:56<12:25,  1.60s/it, loss=2176.0000, t=940]
Attacking:   7%|▋         | 35/500 [00:56<12:25,  1.60s/it, loss=2176.0000, t=940]
Attacking:   7%|▋         | 36/500 [00:57<12:28,  1.61s/it, loss=2176.0000, t=940]
Attacking:   7%|▋         | 36/500 [00:58<12:28,  1.61s/it, loss=2256.0000, t=1e+3]
Attacking:   7%|▋         | 37/500 [00:59<12:18,  1.59s/it, loss=2256.0000, t=1e+3]
Attacking:   7%|▋         | 37/500 [01:00<12:18,  1.59s/it, loss=2176.0000, t=940] 
Attacking:   8%|▊         | 38/500 [01:00<12:23,  1.61s/it, loss=2176.0000, t=940]
Attacking:   8%|▊         | 38/500 [01:01<12:23,  1.61s/it, loss=2208.0000, t=984]
Attacking:   8%|▊         | 39/500 [01:02<12:29,  1.62s/it, loss=2208.0000, t=984]
Attacking:   8%|▊         | 39/500 [01:03<12:29,  1.62s/it, loss=2240.0000, t=1e+3]
Attacking:   8%|▊         | 40/500 [01:04<12:13,  1.59s/it, loss=2240.0000, t=1e+3]
Attacking:   8%|▊         | 40/500 [01:04<12:13,  1.59s/it, loss=2192.0000, t=972] 
Attacking:   8%|▊         | 41/500 [01:05<11:50,  1.55s/it, loss=2192.0000, t=972]
Attacking:   8%|▊         | 41/500 [01:06<11:50,  1.55s/it, loss=2192.0000, t=984]
Attacking:   8%|▊         | 42/500 [01:07<11:43,  1.54s/it, loss=2192.0000, t=984]
Attacking:   8%|▊         | 42/500 [01:07<11:43,  1.54s/it, loss=2192.0000, t=964]
Attacking:   9%|▊         | 43/500 [01:08<11:44,  1.54s/it, loss=2192.0000, t=964]
Attacking:   9%|▊         | 43/500 [01:09<11:44,  1.54s/it, loss=2160.0000, t=928]
Attacking:   9%|▉         | 44/500 [01:10<11:41,  1.54s/it, loss=2160.0000, t=928]
Attacking:   9%|▉         | 44/500 [01:10<11:41,  1.54s/it, loss=2144.0000, t=928]
Attacking:   9%|▉         | 45/500 [01:11<11:40,  1.54s/it, loss=2144.0000, t=928]
Attacking:   9%|▉         | 45/500 [01:12<11:40,  1.54s/it, loss=2224.0000, t=1e+3]
Attacking:   9%|▉         | 46/500 [01:13<12:09,  1.61s/it, loss=2224.0000, t=1e+3]
Attacking:   9%|▉         | 46/500 [01:14<12:09,  1.61s/it, loss=2160.0000, t=952] 
Attacking:   9%|▉         | 47/500 [01:15<12:04,  1.60s/it, loss=2160.0000, t=952]
Attacking:   9%|▉         | 47/500 [01:15<12:04,  1.60s/it, loss=2224.0000, t=1e+3]
Attacking:  10%|▉         | 48/500 [01:16<12:05,  1.61s/it, loss=2224.0000, t=1e+3]
Attacking:  10%|▉         | 48/500 [01:17<12:05,  1.61s/it, loss=2176.0000, t=984] 
Attacking:  10%|▉         | 49/500 [01:18<12:02,  1.60s/it, loss=2176.0000, t=984]
Attacking:  10%|▉         | 49/500 [01:18<12:02,  1.60s/it, loss=2128.0000, t=928]
Attacking:  10%|█         | 50/500 [01:19<11:51,  1.58s/it, loss=2128.0000, t=928]
Attacking:  10%|█         | 50/500 [01:20<11:51,  1.58s/it, loss=2176.0000, t=964]
Attacking:  10%|█         | 51/500 [01:21<11:54,  1.59s/it, loss=2176.0000, t=964]
Attacking:  10%|█         | 51/500 [01:22<11:54,  1.59s/it, loss=2176.0000, t=984]
Attacking:  10%|█         | 52/500 [01:23<12:04,  1.62s/it, loss=2176.0000, t=984]
Attacking:  10%|█         | 52/500 [01:23<12:04,  1.62s/it, loss=2144.0000, t=940]
Attacking:  11%|█         | 53/500 [01:24<11:56,  1.60s/it, loss=2144.0000, t=940]
Attacking:  11%|█         | 53/500 [01:25<11:56,  1.60s/it, loss=2176.0000, t=972]
Attacking:  11%|█         | 54/500 [01:26<11:49,  1.59s/it, loss=2176.0000, t=972]
Attacking:  11%|█         | 54/500 [01:26<11:49,  1.59s/it, loss=2144.0000, t=952]
Attacking:  11%|█         | 55/500 [01:27<11:55,  1.61s/it, loss=2144.0000, t=952]
Attacking:  11%|█         | 55/500 [01:28<11:55,  1.61s/it, loss=2176.0000, t=972]
Attacking:  11%|█         | 56/500 [01:29<12:08,  1.64s/it, loss=2176.0000, t=972]
Attacking:  11%|█         | 56/500 [01:30<12:08,  1.64s/it, loss=2112.0000, t=900]
Attacking:  11%|█▏        | 57/500 [01:31<12:07,  1.64s/it, loss=2112.0000, t=900]
Attacking:  11%|█▏        | 57/500 [01:32<12:07,  1.64s/it, loss=2144.0000, t=952]
Attacking:  12%|█▏        | 58/500 [01:33<12:29,  1.70s/it, loss=2144.0000, t=952]
Attacking:  12%|█▏        | 58/500 [01:33<12:29,  1.70s/it, loss=2160.0000, t=984]
Attacking:  12%|█▏        | 59/500 [01:34<12:38,  1.72s/it, loss=2160.0000, t=984]
Attacking:  12%|█▏        | 59/500 [01:35<12:38,  1.72s/it, loss=2176.0000, t=992]
Attacking:  12%|█▏        | 60/500 [01:36<12:32,  1.71s/it, loss=2176.0000, t=992]
Attacking:  12%|█▏        | 60/500 [01:37<12:32,  1.71s/it, loss=2128.0000, t=940]
Attacking:  12%|█▏        | 61/500 [01:38<12:24,  1.70s/it, loss=2128.0000, t=940]
Attacking:  12%|█▏        | 61/500 [01:39<12:24,  1.70s/it, loss=2096.0000, t=912]
Attacking:  12%|█▏        | 62/500 [01:39<12:28,  1.71s/it, loss=2096.0000, t=912]
Attacking:  12%|█▏        | 62/500 [01:40<12:28,  1.71s/it, loss=2112.0000, t=928]
Attacking:  13%|█▎        | 63/500 [01:41<12:31,  1.72s/it, loss=2112.0000, t=928]
Attacking:  13%|█▎        | 63/500 [01:42<12:31,  1.72s/it, loss=2128.0000, t=952]
Attacking:  13%|█▎        | 64/500 [01:43<12:05,  1.66s/it, loss=2128.0000, t=952]
Attacking:  13%|█▎        | 64/500 [01:43<12:05,  1.66s/it, loss=2144.0000, t=964]
Attacking:  13%|█▎        | 65/500 [01:44<11:38,  1.60s/it, loss=2144.0000, t=964]
Attacking:  13%|█▎        | 65/500 [01:45<11:38,  1.60s/it, loss=2144.0000, t=972]
Attacking:  13%|█▎        | 66/500 [01:46<11:30,  1.59s/it, loss=2144.0000, t=972]
Attacking:  13%|█▎        | 66/500 [01:46<11:30,  1.59s/it, loss=2112.0000, t=940]
Attacking:  13%|█▎        | 67/500 [01:47<11:11,  1.55s/it, loss=2112.0000, t=940]
Attacking:  13%|█▎        | 67/500 [01:48<11:11,  1.55s/it, loss=2128.0000, t=964]
Attacking:  14%|█▎        | 68/500 [01:49<11:06,  1.54s/it, loss=2128.0000, t=964]
Attacking:  14%|█▎        | 68/500 [01:49<11:06,  1.54s/it, loss=2144.0000, t=972]
Attacking:  14%|█▍        | 69/500 [01:50<11:09,  1.55s/it, loss=2144.0000, t=972]
Attacking:  14%|█▍        | 69/500 [01:51<11:09,  1.55s/it, loss=2080.0000, t=912]
Attacking:  14%|█▍        | 70/500 [01:52<11:01,  1.54s/it, loss=2080.0000, t=912]
Attacking:  14%|█▍        | 70/500 [01:52<11:01,  1.54s/it, loss=2144.0000, t=984]
Attacking:  14%|█▍        | 71/500 [01:53<10:48,  1.51s/it, loss=2144.0000, t=984]
Attacking:  14%|█▍        | 71/500 [01:54<10:48,  1.51s/it, loss=2080.0000, t=912]
Attacking:  14%|█▍        | 72/500 [01:55<10:31,  1.47s/it, loss=2080.0000, t=912]
Attacking:  14%|█▍        | 72/500 [01:55<10:31,  1.47s/it, loss=2176.0000, t=1e+3]
Attacking:  15%|█▍        | 73/500 [01:56<10:30,  1.48s/it, loss=2176.0000, t=1e+3]
Attacking:  15%|█▍        | 73/500 [01:57<10:30,  1.48s/it, loss=2096.0000, t=940] 
Attacking:  15%|█▍        | 74/500 [01:58<10:34,  1.49s/it, loss=2096.0000, t=940]
Attacking:  15%|█▍        | 74/500 [01:58<10:34,  1.49s/it, loss=2144.0000, t=972]
Attacking:  15%|█▌        | 75/500 [01:59<10:44,  1.52s/it, loss=2144.0000, t=972]
Attacking:  15%|█▌        | 75/500 [02:00<10:44,  1.52s/it, loss=2080.0000, t=900]
Attacking:  15%|█▌        | 76/500 [02:01<10:59,  1.55s/it, loss=2080.0000, t=900]
Attacking:  15%|█▌        | 76/500 [02:02<10:59,  1.55s/it, loss=2144.0000, t=972]
Attacking:  15%|█▌        | 77/500 [02:02<11:05,  1.57s/it, loss=2144.0000, t=972]
Attacking:  15%|█▌        | 77/500 [02:03<11:05,  1.57s/it, loss=2128.0000, t=964]
Attacking:  16%|█▌        | 78/500 [02:04<11:13,  1.60s/it, loss=2128.0000, t=964]
Attacking:  16%|█▌        | 78/500 [02:05<11:13,  1.60s/it, loss=2080.0000, t=928]
Attacking:  16%|█▌        | 79/500 [02:06<11:11,  1.60s/it, loss=2080.0000, t=928]
Attacking:  16%|█▌        | 79/500 [02:06<11:11,  1.60s/it, loss=2080.0000, t=928]
Attacking:  16%|█▌        | 80/500 [02:07<11:02,  1.58s/it, loss=2080.0000, t=928]
Attacking:  16%|█▌        | 80/500 [02:08<11:02,  1.58s/it, loss=2096.0000, t=952]
Attacking:  16%|█▌        | 81/500 [02:09<11:09,  1.60s/it, loss=2096.0000, t=952]
Attacking:  16%|█▌        | 81/500 [02:10<11:09,  1.60s/it, loss=2144.0000, t=992]
Attacking:  16%|█▋        | 82/500 [02:10<10:59,  1.58s/it, loss=2144.0000, t=992]
Attacking:  16%|█▋        | 82/500 [02:11<10:59,  1.58s/it, loss=2096.0000, t=952]
Attacking:  17%|█▋        | 83/500 [02:12<11:06,  1.60s/it, loss=2096.0000, t=952]
Attacking:  17%|█▋        | 83/500 [02:13<11:06,  1.60s/it, loss=2112.0000, t=964]
Attacking:  17%|█▋        | 84/500 [02:14<11:28,  1.66s/it, loss=2112.0000, t=964]
Attacking:  17%|█▋        | 84/500 [02:15<11:28,  1.66s/it, loss=2112.0000, t=964]
Attacking:  17%|█▋        | 85/500 [02:16<11:45,  1.70s/it, loss=2112.0000, t=964]
Attacking:  17%|█▋        | 85/500 [02:16<11:45,  1.70s/it, loss=2160.0000, t=1e+3]
Attacking:  17%|█▋        | 86/500 [02:17<11:18,  1.64s/it, loss=2160.0000, t=1e+3]
Attacking:  17%|█▋        | 86/500 [02:18<11:18,  1.64s/it, loss=2112.0000, t=984] 
Attacking:  17%|█▋        | 87/500 [02:19<11:13,  1.63s/it, loss=2112.0000, t=984]
Attacking:  17%|█▋        | 87/500 [02:19<11:13,  1.63s/it, loss=2064.0000, t=900]
Attacking:  18%|█▊        | 88/500 [02:20<11:09,  1.62s/it, loss=2064.0000, t=900]
Attacking:  18%|█▊        | 88/500 [02:21<11:09,  1.62s/it, loss=2048.0000, t=900]
Attacking:  18%|█▊        | 89/500 [02:22<11:10,  1.63s/it, loss=2048.0000, t=900]
Attacking:  18%|█▊        | 89/500 [02:23<11:10,  1.63s/it, loss=2144.0000, t=992]
Attacking:  18%|█▊        | 90/500 [02:24<11:01,  1.61s/it, loss=2144.0000, t=992]
Attacking:  18%|█▊        | 90/500 [02:24<11:01,  1.61s/it, loss=2144.0000, t=1e+3]
Attacking:  18%|█▊        | 91/500 [02:25<10:39,  1.56s/it, loss=2144.0000, t=1e+3]
Attacking:  18%|█▊        | 91/500 [02:26<10:39,  1.56s/it, loss=2112.0000, t=984] 
Attacking:  18%|█▊        | 92/500 [02:26<10:24,  1.53s/it, loss=2112.0000, t=984]
Attacking:  18%|█▊        | 92/500 [02:27<10:24,  1.53s/it, loss=2080.0000, t=940]
Attacking:  19%|█▊        | 93/500 [02:28<10:15,  1.51s/it, loss=2080.0000, t=940]
Attacking:  19%|█▊        | 93/500 [02:29<10:15,  1.51s/it, loss=2112.0000, t=984]
Attacking:  19%|█▉        | 94/500 [02:29<10:07,  1.50s/it, loss=2112.0000, t=984]
Attacking:  19%|█▉        | 94/500 [02:30<10:07,  1.50s/it, loss=2080.0000, t=928]
Attacking:  19%|█▉        | 95/500 [02:31<10:12,  1.51s/it, loss=2080.0000, t=928]
Attacking:  19%|█▉        | 95/500 [02:32<10:12,  1.51s/it, loss=2080.0000, t=940]
Attacking:  19%|█▉        | 96/500 [02:32<10:11,  1.51s/it, loss=2080.0000, t=940]
Attacking:  19%|█▉        | 96/500 [02:33<10:11,  1.51s/it, loss=2048.0000, t=900]
Attacking:  19%|█▉        | 97/500 [02:34<10:15,  1.53s/it, loss=2048.0000, t=900]
Attacking:  19%|█▉        | 97/500 [02:35<10:15,  1.53s/it, loss=2112.0000, t=964]
Attacking:  20%|█▉        | 98/500 [02:35<10:06,  1.51s/it, loss=2112.0000, t=964]
Attacking:  20%|█▉        | 98/500 [02:36<10:06,  1.51s/it, loss=2112.0000, t=984]
Attacking:  20%|█▉        | 99/500 [02:37<10:15,  1.53s/it, loss=2112.0000, t=984]
Attacking:  20%|█▉        | 99/500 [02:38<10:15,  1.53s/it, loss=2080.0000, t=940]
Attacking:  20%|██        | 100/500 [02:39<10:05,  1.51s/it, loss=2080.0000, t=940]
Attacking:  20%|██        | 100/500 [02:39<10:05,  1.51s/it, loss=2064.0000, t=928]
Attacking:  20%|██        | 101/500 [02:40<10:06,  1.52s/it, loss=2064.0000, t=928]
Attacking:  20%|██        | 101/500 [02:41<10:06,  1.52s/it, loss=2160.0000, t=1e+3]
Attacking:  20%|██        | 102/500 [02:42<09:55,  1.50s/it, loss=2160.0000, t=1e+3]
Attacking:  20%|██        | 102/500 [02:42<09:55,  1.50s/it, loss=2048.0000, t=900] 
Attacking:  21%|██        | 103/500 [02:43<10:08,  1.53s/it, loss=2048.0000, t=900]
Attacking:  21%|██        | 103/500 [02:44<10:08,  1.53s/it, loss=2064.0000, t=912]
Attacking:  21%|██        | 104/500 [02:45<10:00,  1.52s/it, loss=2064.0000, t=912]
Attacking:  21%|██        | 104/500 [02:45<10:00,  1.52s/it, loss=2112.0000, t=972]
Attacking:  21%|██        | 105/500 [02:46<09:52,  1.50s/it, loss=2112.0000, t=972]
Attacking:  21%|██        | 105/500 [02:47<09:52,  1.50s/it, loss=2080.0000, t=940]
Attacking:  21%|██        | 106/500 [02:48<10:24,  1.59s/it, loss=2080.0000, t=940]
Attacking:  21%|██        | 106/500 [02:49<10:24,  1.59s/it, loss=2112.0000, t=964]
Attacking:  21%|██▏       | 107/500 [02:49<10:27,  1.60s/it, loss=2112.0000, t=964]
Attacking:  21%|██▏       | 107/500 [02:50<10:27,  1.60s/it, loss=2112.0000, t=984]
Attacking:  22%|██▏       | 108/500 [02:51<10:13,  1.57s/it, loss=2112.0000, t=984]
Attacking:  22%|██▏       | 108/500 [02:52<10:13,  1.57s/it, loss=2048.0000, t=900]
Attacking:  22%|██▏       | 109/500 [02:52<10:02,  1.54s/it, loss=2048.0000, t=900]
Attacking:  22%|██▏       | 109/500 [02:53<10:02,  1.54s/it, loss=2096.0000, t=964]
Attacking:  22%|██▏       | 110/500 [02:54<09:51,  1.52s/it, loss=2096.0000, t=964]
Attacking:  22%|██▏       | 110/500 [02:55<09:51,  1.52s/it, loss=2080.0000, t=952]
Attacking:  22%|██▏       | 111/500 [02:55<09:50,  1.52s/it, loss=2080.0000, t=952]
Attacking:  22%|██▏       | 111/500 [02:56<09:50,  1.52s/it, loss=2064.0000, t=928]
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Attacking: 100%|██████████| 500/500 [12:51<00:00,  1.54s/it, loss=2016.0000, t=952]
+Max Diff: 0.501961
+Mean Diff: 0.250317
+Saved adversarial image to attacked/images/breakdance-flare.jpg
+Saved loss curve to attacked/loss_curve/breakdance-flare_loss.png
+[GPU 0] Stage 3/3: Test
+Loading models for testing breakdance-flare...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for breakdance-flare...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 85.26it/s]
+Saved video to attacked/videos/breakdance-flare.mp4
+Saved frames to attacked/frames/breakdance-flare
+[GPU 0] Finished breakdance-flare.jpg
+======================================
+[GPU 0] Processing bus.jpg (Image 6/50)
+======================================
+[GPU 0] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 0] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  17%|█▋        | 86/500 [02:17<10:46,  1.56s/it, loss=2032.0000, t=964]
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Attacking:  17%|█▋        | 87/500 [02:19<11:03,  1.61s/it, loss=1968.0000, t=900]
Attacking:  18%|█▊        | 88/500 [02:19<11:12,  1.63s/it, loss=1968.0000, t=900]
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Attacking:  20%|██        | 100/500 [02:40<11:18,  1.70s/it, loss=1992.0000, t=940]
Attacking:  20%|██        | 100/500 [02:40<11:18,  1.70s/it, loss=2040.0000, t=1e+3]
Attacking:  20%|██        | 101/500 [02:41<11:00,  1.66s/it, loss=2040.0000, t=1e+3]
Attacking:  20%|██        | 101/500 [02:42<11:00,  1.66s/it, loss=2032.0000, t=1e+3]
Attacking:  20%|██        | 102/500 [02:43<10:55,  1.65s/it, loss=2032.0000, t=1e+3]
Attacking:  20%|██        | 102/500 [02:43<10:55,  1.65s/it, loss=2032.0000, t=984] 
Attacking:  21%|██        | 103/500 [02:44<10:29,  1.58s/it, loss=2032.0000, t=984]
Attacking:  21%|██        | 103/500 [02:45<10:29,  1.58s/it, loss=1984.0000, t=940]
Attacking:  21%|██        | 104/500 [02:46<10:08,  1.54s/it, loss=1984.0000, t=940]
Attacking:  21%|██        | 104/500 [02:46<10:08,  1.54s/it, loss=2048.0000, t=992]
Attacking:  21%|██        | 105/500 [02:47<09:51,  1.50s/it, loss=2048.0000, t=992]
Attacking:  21%|██        | 105/500 [02:48<09:51,  1.50s/it, loss=2024.0000, t=1e+3]
Attacking:  21%|██        | 106/500 [02:49<09:49,  1.49s/it, loss=2024.0000, t=1e+3]
Attacking:  21%|██        | 106/500 [02:49<09:49,  1.49s/it, loss=2008.0000, t=964] 
Attacking:  21%|██▏       | 107/500 [02:50<09:37,  1.47s/it, loss=2008.0000, t=964]
Attacking:  21%|██▏       | 107/500 [02:51<09:37,  1.47s/it, loss=2024.0000, t=1e+3]
Attacking:  22%|██▏       | 108/500 [02:51<09:33,  1.46s/it, loss=2024.0000, t=1e+3]
Attacking:  22%|██▏       | 108/500 [02:52<09:33,  1.46s/it, loss=2024.0000, t=1e+3]
Attacking:  22%|██▏       | 109/500 [02:53<09:24,  1.44s/it, loss=2024.0000, t=1e+3]
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Attacking:  22%|██▏       | 110/500 [02:54<09:16,  1.43s/it, loss=2000.0000, t=964]
Attacking:  22%|██▏       | 110/500 [02:55<09:16,  1.43s/it, loss=2048.0000, t=992]
Attacking:  22%|██▏       | 111/500 [02:56<09:38,  1.49s/it, loss=2048.0000, t=992]
Attacking:  22%|██▏       | 111/500 [02:57<09:38,  1.49s/it, loss=1984.0000, t=940]
Attacking:  22%|██▏       | 112/500 [02:57<09:42,  1.50s/it, loss=1984.0000, t=940]
Attacking:  22%|██▏       | 112/500 [02:58<09:42,  1.50s/it, loss=2016.0000, t=972]
Attacking:  23%|██▎       | 113/500 [02:59<09:59,  1.55s/it, loss=2016.0000, t=972]
Attacking:  23%|██▎       | 113/500 [03:00<09:59,  1.55s/it, loss=2024.0000, t=1e+3]
Attacking:  23%|██▎       | 114/500 [03:01<09:59,  1.55s/it, loss=2024.0000, t=1e+3]
Attacking:  23%|██▎       | 114/500 [03:01<09:59,  1.55s/it, loss=2024.0000, t=1e+3]
Attacking:  23%|██▎       | 115/500 [03:02<10:27,  1.63s/it, loss=2024.0000, t=1e+3]
Attacking:  23%|██▎       | 115/500 [03:03<10:27,  1.63s/it, loss=2000.0000, t=952] 
Attacking:  23%|██▎       | 116/500 [03:04<10:41,  1.67s/it, loss=2000.0000, t=952]
Attacking:  23%|██▎       | 116/500 [03:05<10:41,  1.67s/it, loss=1984.0000, t=940]
Attacking:  23%|██▎       | 117/500 [03:06<10:55,  1.71s/it, loss=1984.0000, t=940]
Attacking:  23%|██▎       | 117/500 [03:07<10:55,  1.71s/it, loss=1960.0000, t=928]
Attacking:  24%|██▎       | 118/500 [03:08<10:50,  1.70s/it, loss=1960.0000, t=928]
Attacking:  24%|██▎       | 118/500 [03:09<10:50,  1.70s/it, loss=1968.0000, t=928]
Attacking:  24%|██▍       | 119/500 [03:09<10:47,  1.70s/it, loss=1968.0000, t=928]
Attacking:  24%|██▍       | 119/500 [03:10<10:47,  1.70s/it, loss=1952.0000, t=912]
Attacking:  24%|██▍       | 120/500 [03:11<10:54,  1.72s/it, loss=1952.0000, t=912]
Attacking:  24%|██▍       | 120/500 [03:12<10:54,  1.72s/it, loss=2000.0000, t=964]
Attacking:  24%|██▍       | 121/500 [03:13<10:48,  1.71s/it, loss=2000.0000, t=964]
Attacking:  24%|██▍       | 121/500 [03:14<10:48,  1.71s/it, loss=1960.0000, t=928]
Attacking:  24%|██▍       | 122/500 [03:15<10:45,  1.71s/it, loss=1960.0000, t=928]
Attacking:  24%|██▍       | 122/500 [03:15<10:45,  1.71s/it, loss=2000.0000, t=964]
Attacking:  25%|██▍       | 123/500 [03:16<10:43,  1.71s/it, loss=2000.0000, t=964]
Attacking:  25%|██▍       | 123/500 [03:17<10:43,  1.71s/it, loss=2016.0000, t=984]
Attacking:  25%|██▍       | 124/500 [03:18<10:43,  1.71s/it, loss=2016.0000, t=984]
Attacking:  25%|██▍       | 124/500 [03:19<10:43,  1.71s/it, loss=1952.0000, t=900]
Attacking:  25%|██▌       | 125/500 [03:20<10:40,  1.71s/it, loss=1952.0000, t=900]
Attacking:  25%|██▌       | 125/500 [03:20<10:40,  1.71s/it, loss=1976.0000, t=940]
Attacking:  25%|██▌       | 126/500 [03:21<10:16,  1.65s/it, loss=1976.0000, t=940]
Attacking:  25%|██▌       | 126/500 [03:22<10:16,  1.65s/it, loss=1992.0000, t=964]
Attacking:  25%|██▌       | 127/500 [03:23<10:13,  1.65s/it, loss=1992.0000, t=964]
Attacking:  25%|██▌       | 127/500 [03:24<10:13,  1.65s/it, loss=1984.0000, t=952]
Attacking:  26%|██▌       | 128/500 [03:24<10:01,  1.62s/it, loss=1984.0000, t=952]
Attacking:  26%|██▌       | 128/500 [03:25<10:01,  1.62s/it, loss=2016.0000, t=1e+3]
Attacking:  26%|██▌       | 129/500 [03:26<09:59,  1.62s/it, loss=2016.0000, t=1e+3]
Attacking:  26%|██▌       | 129/500 [03:27<09:59,  1.62s/it, loss=2000.0000, t=964] 
Attacking:  26%|██▌       | 130/500 [03:27<09:43,  1.58s/it, loss=2000.0000, t=964]
Attacking:  26%|██▌       | 130/500 [03:28<09:43,  1.58s/it, loss=1992.0000, t=964]
Attacking:  26%|██▌       | 131/500 [03:29<09:33,  1.56s/it, loss=1992.0000, t=964]
Attacking:  26%|██▌       | 131/500 [03:30<09:33,  1.56s/it, loss=2016.0000, t=972]
Attacking:  26%|██▋       | 132/500 [03:30<09:29,  1.55s/it, loss=2016.0000, t=972]
Attacking:  26%|██▋       | 132/500 [03:31<09:29,  1.55s/it, loss=1992.0000, t=964]
Attacking:  27%|██▋       | 133/500 [03:32<09:35,  1.57s/it, loss=1992.0000, t=964]
Attacking:  27%|██▋       | 133/500 [03:33<09:35,  1.57s/it, loss=2024.0000, t=984]
Attacking:  27%|██▋       | 134/500 [03:34<09:28,  1.55s/it, loss=2024.0000, t=984]
Attacking:  27%|██▋       | 134/500 [03:34<09:28,  1.55s/it, loss=2032.0000, t=992]
Attacking:  27%|██▋       | 135/500 [03:35<09:18,  1.53s/it, loss=2032.0000, t=992]
Attacking:  27%|██▋       | 135/500 [03:36<09:18,  1.53s/it, loss=1960.0000, t=912]
Attacking:  27%|██▋       | 136/500 [03:37<09:09,  1.51s/it, loss=1960.0000, t=912]
Attacking:  27%|██▋       | 136/500 [03:37<09:09,  1.51s/it, loss=2000.0000, t=964]
Attacking:  27%|██▋       | 137/500 [03:38<09:02,  1.50s/it, loss=2000.0000, t=964]
Attacking:  27%|██▋       | 137/500 [03:39<09:02,  1.50s/it, loss=1960.0000, t=912]
Attacking:  28%|██▊       | 138/500 [03:40<09:02,  1.50s/it, loss=1960.0000, t=912]
Attacking:  28%|██▊       | 138/500 [03:40<09:02,  1.50s/it, loss=2040.0000, t=992]
Attacking:  28%|██▊       | 139/500 [03:41<08:59,  1.49s/it, loss=2040.0000, t=992]
Attacking:  28%|██▊       | 139/500 [03:42<08:59,  1.49s/it, loss=2000.0000, t=972]
Attacking:  28%|██▊       | 140/500 [03:43<09:05,  1.52s/it, loss=2000.0000, t=972]
Attacking:  28%|██▊       | 140/500 [03:43<09:05,  1.52s/it, loss=2000.0000, t=964]
Attacking:  28%|██▊       | 141/500 [03:44<09:09,  1.53s/it, loss=2000.0000, t=964]
Attacking:  28%|██▊       | 141/500 [03:45<09:09,  1.53s/it, loss=1992.0000, t=964]
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Attacking:  28%|██▊       | 142/500 [03:47<09:20,  1.57s/it, loss=1960.0000, t=928]
Attacking:  29%|██▊       | 143/500 [03:47<09:26,  1.59s/it, loss=1960.0000, t=928]
Attacking:  29%|██▊       | 143/500 [03:48<09:26,  1.59s/it, loss=1968.0000, t=940]
Attacking:  29%|██▉       | 144/500 [03:49<09:23,  1.58s/it, loss=1968.0000, t=940]
Attacking:  29%|██▉       | 144/500 [03:50<09:23,  1.58s/it, loss=2040.0000, t=992]
Attacking:  29%|██▉       | 145/500 [03:51<09:34,  1.62s/it, loss=2040.0000, t=992]
Attacking:  29%|██▉       | 145/500 [03:51<09:34,  1.62s/it, loss=1960.0000, t=928]
Attacking:  29%|██▉       | 146/500 [03:52<09:22,  1.59s/it, loss=1960.0000, t=928]
Attacking:  29%|██▉       | 146/500 [03:53<09:22,  1.59s/it, loss=2032.0000, t=992]
Attacking:  29%|██▉       | 147/500 [03:54<09:16,  1.58s/it, loss=2032.0000, t=992]
Attacking:  29%|██▉       | 147/500 [03:55<09:16,  1.58s/it, loss=1968.0000, t=952]
Attacking:  30%|██▉       | 148/500 [03:55<09:14,  1.57s/it, loss=1968.0000, t=952]
Attacking:  30%|██▉       | 148/500 [03:56<09:14,  1.57s/it, loss=1960.0000, t=940]
Attacking:  30%|██▉       | 149/500 [03:57<09:23,  1.61s/it, loss=1960.0000, t=940]
Attacking:  30%|██▉       | 149/500 [03:58<09:23,  1.61s/it, loss=1968.0000, t=952]
Attacking:  30%|███       | 150/500 [03:59<09:32,  1.64s/it, loss=1968.0000, t=952]
Attacking:  30%|███       | 150/500 [04:00<09:32,  1.64s/it, loss=2032.0000, t=992]
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Attacking:  30%|███       | 151/500 [04:01<09:32,  1.64s/it, loss=1960.0000, t=940]
Attacking:  30%|███       | 152/500 [04:02<09:27,  1.63s/it, loss=1960.0000, t=940]
Attacking:  30%|███       | 152/500 [04:03<09:27,  1.63s/it, loss=1992.0000, t=972]
Attacking:  31%|███       | 153/500 [04:03<09:11,  1.59s/it, loss=1992.0000, t=972]
Attacking:  31%|███       | 153/500 [04:04<09:11,  1.59s/it, loss=1968.0000, t=928]
Attacking:  31%|███       | 154/500 [04:05<08:57,  1.55s/it, loss=1968.0000, t=928]
Attacking:  31%|███       | 154/500 [04:06<08:57,  1.55s/it, loss=1944.0000, t=912]
Attacking:  31%|███       | 155/500 [04:06<08:45,  1.52s/it, loss=1944.0000, t=912]
Attacking:  31%|███       | 155/500 [04:07<08:45,  1.52s/it, loss=1944.0000, t=900]
Attacking:  31%|███       | 156/500 [04:08<09:00,  1.57s/it, loss=1944.0000, t=900]
Attacking:  31%|███       | 156/500 [04:09<09:00,  1.57s/it, loss=2008.0000, t=984]
Attacking:  31%|███▏      | 157/500 [04:10<08:56,  1.56s/it, loss=2008.0000, t=984]
Attacking:  31%|███▏      | 157/500 [04:10<08:56,  1.56s/it, loss=2008.0000, t=1e+3]
Attacking:  32%|███▏      | 158/500 [04:11<08:54,  1.56s/it, loss=2008.0000, t=1e+3]
Attacking:  32%|███▏      | 158/500 [04:12<08:54,  1.56s/it, loss=1936.0000, t=900] 
Attacking:  32%|███▏      | 159/500 [04:13<08:47,  1.55s/it, loss=1936.0000, t=900]
Attacking:  32%|███▏      | 159/500 [04:14<08:47,  1.55s/it, loss=2000.0000, t=984]
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Attacking:  99%|█████████▊| 493/500 [12:45<00:10,  1.55s/it, loss=1952.0000, t=984]
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Attacking:  99%|█████████▉| 495/500 [12:48<00:07,  1.55s/it, loss=1936.0000, t=964]
Attacking:  99%|█████████▉| 495/500 [12:48<00:07,  1.55s/it, loss=1952.0000, t=984]
Attacking:  99%|█████████▉| 496/500 [12:49<00:06,  1.52s/it, loss=1952.0000, t=984]
Attacking:  99%|█████████▉| 496/500 [12:50<00:06,  1.52s/it, loss=1888.0000, t=900]
Attacking:  99%|█████████▉| 497/500 [12:50<00:04,  1.50s/it, loss=1888.0000, t=900]
Attacking:  99%|█████████▉| 497/500 [12:51<00:04,  1.50s/it, loss=1896.0000, t=912]
Attacking: 100%|█████████▉| 498/500 [12:52<00:03,  1.51s/it, loss=1896.0000, t=912]
Attacking: 100%|█████████▉| 498/500 [12:53<00:03,  1.51s/it, loss=1936.0000, t=972]
Attacking: 100%|█████████▉| 499/500 [12:53<00:01,  1.50s/it, loss=1936.0000, t=972]
Attacking: 100%|█████████▉| 499/500 [12:54<00:01,  1.50s/it, loss=1952.0000, t=984]
Attacking: 100%|██████████| 500/500 [12:55<00:00,  1.51s/it, loss=1952.0000, t=984]
Attacking: 100%|██████████| 500/500 [12:55<00:00,  1.55s/it, loss=1952.0000, t=984]
+Max Diff: 0.501961
+Mean Diff: 0.244069
+Saved adversarial image to attacked/images/bus.jpg
+Saved loss curve to attacked/loss_curve/bus_loss.png
+[GPU 0] Stage 3/3: Test
+Loading models for testing bus...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for bus...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 42.68it/s]
+Saved video to attacked/videos/bus.mp4
+Saved frames to attacked/frames/bus
+[GPU 0] Finished bus.jpg
+[GPU 0] All assigned tasks completed.
diff --git a/experiments/cfg3_eps64/logs/gpu_1.log b/experiments/cfg3_eps64/logs/gpu_1.log
new file mode 100644
index 0000000000000000000000000000000000000000..868f65337566fa39189c3068f97432c234e5e7a0
--- /dev/null
+++ b/experiments/cfg3_eps64/logs/gpu_1.log
@@ -0,0 +1,513 @@
+[GPU 1] Starting work on images 7 to 13
+======================================
+[GPU 1] Processing camel.jpg (Image 7/50)
+======================================
+[GPU 1] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 1] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   6%|▋         | 32/500 [00:46<11:31,  1.48s/it, loss=2496.0000, t=940]
Attacking:   6%|▋         | 32/500 [00:47<11:31,  1.48s/it, loss=2576.0000, t=1e+3]
Attacking:   7%|▋         | 33/500 [00:48<11:14,  1.44s/it, loss=2576.0000, t=1e+3]
Attacking:   7%|▋         | 33/500 [00:48<11:14,  1.44s/it, loss=2512.0000, t=912] 
Attacking:   7%|▋         | 34/500 [00:49<11:10,  1.44s/it, loss=2512.0000, t=912]
Attacking:   7%|▋         | 34/500 [00:50<11:10,  1.44s/it, loss=2528.0000, t=984]
Attacking:   7%|▋         | 35/500 [00:51<11:02,  1.42s/it, loss=2528.0000, t=984]
Attacking:   7%|▋         | 35/500 [00:51<11:02,  1.42s/it, loss=2480.0000, t=964]
Attacking:   7%|▋         | 36/500 [00:52<10:54,  1.41s/it, loss=2480.0000, t=964]
Attacking:   7%|▋         | 36/500 [00:53<10:54,  1.41s/it, loss=2496.0000, t=912]
Attacking:   7%|▋         | 37/500 [00:53<10:47,  1.40s/it, loss=2496.0000, t=912]
Attacking:   7%|▋         | 37/500 [00:54<10:47,  1.40s/it, loss=2480.0000, t=912]
Attacking:   8%|▊         | 38/500 [00:55<10:41,  1.39s/it, loss=2480.0000, t=912]
Attacking:   8%|▊         | 38/500 [00:55<10:41,  1.39s/it, loss=2480.0000, t=912]
Attacking:   8%|▊         | 39/500 [00:56<10:39,  1.39s/it, loss=2480.0000, t=912]
Attacking:   8%|▊         | 39/500 [00:57<10:39,  1.39s/it, loss=2480.0000, t=940]
Attacking:   8%|▊         | 40/500 [00:58<10:38,  1.39s/it, loss=2480.0000, t=940]
Attacking:   8%|▊         | 40/500 [00:58<10:38,  1.39s/it, loss=2480.0000, t=912]
Attacking:   8%|▊         | 41/500 [00:59<10:38,  1.39s/it, loss=2480.0000, t=912]
Attacking:   8%|▊         | 41/500 [00:59<10:38,  1.39s/it, loss=2528.0000, t=992]
Attacking:   8%|▊         | 42/500 [01:00<10:38,  1.39s/it, loss=2528.0000, t=992]
Attacking:   8%|▊         | 42/500 [01:01<10:38,  1.39s/it, loss=2480.0000, t=900]
Attacking:   9%|▊         | 43/500 [01:02<10:35,  1.39s/it, loss=2480.0000, t=900]
Attacking:   9%|▊         | 43/500 [01:02<10:35,  1.39s/it, loss=2496.0000, t=972]
Attacking:   9%|▉         | 44/500 [01:03<10:31,  1.39s/it, loss=2496.0000, t=972]
Attacking:   9%|▉         | 44/500 [01:04<10:31,  1.39s/it, loss=2480.0000, t=964]
Attacking:   9%|▉         | 45/500 [01:04<10:30,  1.39s/it, loss=2480.0000, t=964]
Attacking:   9%|▉         | 45/500 [01:05<10:30,  1.39s/it, loss=2480.0000, t=964]
Attacking:   9%|▉         | 46/500 [01:06<10:30,  1.39s/it, loss=2480.0000, t=964]
Attacking:   9%|▉         | 46/500 [01:06<10:30,  1.39s/it, loss=2512.0000, t=984]
Attacking:   9%|▉         | 47/500 [01:07<10:27,  1.38s/it, loss=2512.0000, t=984]
Attacking:   9%|▉         | 47/500 [01:08<10:27,  1.38s/it, loss=2480.0000, t=952]
Attacking:  10%|▉         | 48/500 [01:09<10:25,  1.38s/it, loss=2480.0000, t=952]
Attacking:  10%|▉         | 48/500 [01:09<10:25,  1.38s/it, loss=2480.0000, t=964]
Attacking:  10%|▉         | 49/500 [01:10<10:22,  1.38s/it, loss=2480.0000, t=964]
Attacking:  10%|▉         | 49/500 [01:11<10:22,  1.38s/it, loss=2464.0000, t=964]
Attacking:  10%|█         | 50/500 [01:11<10:20,  1.38s/it, loss=2464.0000, t=964]
Attacking:  10%|█         | 50/500 [01:12<10:20,  1.38s/it, loss=2464.0000, t=900]
Attacking:  10%|█         | 51/500 [01:13<10:17,  1.37s/it, loss=2464.0000, t=900]
Attacking:  10%|█         | 51/500 [01:13<10:17,  1.37s/it, loss=2528.0000, t=1e+3]
Attacking:  10%|█         | 52/500 [01:14<10:14,  1.37s/it, loss=2528.0000, t=1e+3]
Attacking:  10%|█         | 52/500 [01:15<10:14,  1.37s/it, loss=2496.0000, t=992] 
Attacking:  11%|█         | 53/500 [01:15<10:12,  1.37s/it, loss=2496.0000, t=992]
Attacking:  11%|█         | 53/500 [01:16<10:12,  1.37s/it, loss=2528.0000, t=1e+3]
Attacking:  11%|█         | 54/500 [01:17<10:12,  1.37s/it, loss=2528.0000, t=1e+3]
Attacking:  11%|█         | 54/500 [01:17<10:12,  1.37s/it, loss=2464.0000, t=912] 
Attacking:  11%|█         | 55/500 [01:18<10:17,  1.39s/it, loss=2464.0000, t=912]
Attacking:  11%|█         | 55/500 [01:19<10:17,  1.39s/it, loss=2528.0000, t=1e+3]
Attacking:  11%|█         | 56/500 [01:20<10:17,  1.39s/it, loss=2528.0000, t=1e+3]
Attacking:  11%|█         | 56/500 [01:20<10:17,  1.39s/it, loss=2512.0000, t=1e+3]
Attacking:  11%|█▏        | 57/500 [01:21<10:13,  1.39s/it, loss=2512.0000, t=1e+3]
Attacking:  11%|█▏        | 57/500 [01:22<10:13,  1.39s/it, loss=2448.0000, t=952] 
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Attacking:  12%|█▏        | 58/500 [01:23<10:11,  1.38s/it, loss=2448.0000, t=964]
Attacking:  12%|█▏        | 59/500 [01:24<10:28,  1.43s/it, loss=2448.0000, t=964]
Attacking:  12%|█▏        | 59/500 [01:24<10:28,  1.43s/it, loss=2448.0000, t=928]
Attacking:  12%|█▏        | 60/500 [01:25<10:20,  1.41s/it, loss=2448.0000, t=928]
Attacking:  12%|█▏        | 60/500 [01:26<10:20,  1.41s/it, loss=2432.0000, t=940]
Attacking:  12%|█▏        | 61/500 [01:27<10:26,  1.43s/it, loss=2432.0000, t=940]
Attacking:  12%|█▏        | 61/500 [01:27<10:26,  1.43s/it, loss=2448.0000, t=940]
Attacking:  12%|█▏        | 62/500 [01:28<10:33,  1.45s/it, loss=2448.0000, t=940]
Attacking:  12%|█▏        | 62/500 [01:29<10:33,  1.45s/it, loss=2448.0000, t=972]
Attacking:  13%|█▎        | 63/500 [01:30<10:33,  1.45s/it, loss=2448.0000, t=972]
Attacking:  13%|█▎        | 63/500 [01:30<10:33,  1.45s/it, loss=2448.0000, t=940]
Attacking:  13%|█▎        | 64/500 [01:31<10:30,  1.45s/it, loss=2448.0000, t=940]
Attacking:  13%|█▎        | 64/500 [01:32<10:30,  1.45s/it, loss=2448.0000, t=972]
Attacking:  13%|█▎        | 65/500 [01:33<10:34,  1.46s/it, loss=2448.0000, t=972]
Attacking:  13%|█▎        | 65/500 [01:33<10:34,  1.46s/it, loss=2432.0000, t=900]
Attacking:  13%|█▎        | 66/500 [01:34<10:35,  1.46s/it, loss=2432.0000, t=900]
Attacking:  13%|█▎        | 66/500 [01:35<10:35,  1.46s/it, loss=2512.0000, t=1e+3]
Attacking:  13%|█▎        | 67/500 [01:36<10:33,  1.46s/it, loss=2512.0000, t=1e+3]
Attacking:  13%|█▎        | 67/500 [01:36<10:33,  1.46s/it, loss=2464.0000, t=984] 
Attacking:  14%|█▎        | 68/500 [01:37<10:36,  1.47s/it, loss=2464.0000, t=984]
Attacking:  14%|█▎        | 68/500 [01:38<10:36,  1.47s/it, loss=2416.0000, t=928]
Attacking:  14%|█▍        | 69/500 [01:39<10:33,  1.47s/it, loss=2416.0000, t=928]
Attacking:  14%|█▍        | 69/500 [01:39<10:33,  1.47s/it, loss=2416.0000, t=940]
Attacking:  14%|█▍        | 70/500 [01:40<10:30,  1.47s/it, loss=2416.0000, t=940]
Attacking:  14%|█▍        | 70/500 [01:41<10:30,  1.47s/it, loss=2432.0000, t=972]
Attacking:  14%|█▍        | 71/500 [01:41<10:27,  1.46s/it, loss=2432.0000, t=972]
Attacking:  14%|█▍        | 71/500 [01:42<10:27,  1.46s/it, loss=2432.0000, t=900]
Attacking:  14%|█▍        | 72/500 [01:43<10:23,  1.46s/it, loss=2432.0000, t=900]
Attacking:  14%|█▍        | 72/500 [01:44<10:23,  1.46s/it, loss=2416.0000, t=952]
Attacking:  15%|█▍        | 73/500 [01:44<10:21,  1.46s/it, loss=2416.0000, t=952]
Attacking:  15%|█▍        | 73/500 [01:45<10:21,  1.46s/it, loss=2416.0000, t=900]
Attacking:  15%|█▍        | 74/500 [01:46<10:24,  1.47s/it, loss=2416.0000, t=900]
Attacking:  15%|█▍        | 74/500 [01:47<10:24,  1.47s/it, loss=2416.0000, t=928]
Attacking:  15%|█▌        | 75/500 [01:47<10:24,  1.47s/it, loss=2416.0000, t=928]
Attacking:  15%|█▌        | 75/500 [01:48<10:24,  1.47s/it, loss=2496.0000, t=1e+3]
Attacking:  15%|█▌        | 76/500 [01:49<10:34,  1.50s/it, loss=2496.0000, t=1e+3]
Attacking:  15%|█▌        | 76/500 [01:50<10:34,  1.50s/it, loss=2432.0000, t=952] 
Attacking:  15%|█▌        | 77/500 [01:50<10:38,  1.51s/it, loss=2432.0000, t=952]
Attacking:  15%|█▌        | 77/500 [01:51<10:38,  1.51s/it, loss=2416.0000, t=940]
Attacking:  16%|█▌        | 78/500 [01:52<10:50,  1.54s/it, loss=2416.0000, t=940]
Attacking:  16%|█▌        | 78/500 [01:53<10:50,  1.54s/it, loss=2416.0000, t=912]
Attacking:  16%|█▌        | 79/500 [01:54<10:57,  1.56s/it, loss=2416.0000, t=912]
Attacking:  16%|█▌        | 79/500 [01:54<10:57,  1.56s/it, loss=2432.0000, t=964]
Attacking:  16%|█▌        | 80/500 [01:55<10:53,  1.56s/it, loss=2432.0000, t=964]
Attacking:  16%|█▌        | 80/500 [01:56<10:53,  1.56s/it, loss=2480.0000, t=1e+3]
Attacking:  16%|█▌        | 81/500 [01:57<10:29,  1.50s/it, loss=2480.0000, t=1e+3]
Attacking:  16%|█▌        | 81/500 [01:57<10:29,  1.50s/it, loss=2432.0000, t=952] 
Attacking:  16%|█▋        | 82/500 [01:58<10:16,  1.47s/it, loss=2432.0000, t=952]
Attacking:  16%|█▋        | 82/500 [01:59<10:16,  1.47s/it, loss=2496.0000, t=1e+3]
Attacking:  17%|█▋        | 83/500 [01:59<10:03,  1.45s/it, loss=2496.0000, t=1e+3]
Attacking:  17%|█▋        | 83/500 [02:00<10:03,  1.45s/it, loss=2464.0000, t=992] 
Attacking:  17%|█▋        | 84/500 [02:01<10:10,  1.47s/it, loss=2464.0000, t=992]
Attacking:  17%|█▋        | 84/500 [02:01<10:10,  1.47s/it, loss=2432.0000, t=952]
Attacking:  17%|█▋        | 85/500 [02:02<09:59,  1.45s/it, loss=2432.0000, t=952]
Attacking:  17%|█▋        | 85/500 [02:03<09:59,  1.45s/it, loss=2448.0000, t=992]
Attacking:  17%|█▋        | 86/500 [02:04<09:48,  1.42s/it, loss=2448.0000, t=992]
Attacking:  17%|█▋        | 86/500 [02:04<09:48,  1.42s/it, loss=2400.0000, t=964]
Attacking:  17%|█▋        | 87/500 [02:05<09:42,  1.41s/it, loss=2400.0000, t=964]
Attacking:  17%|█▋        | 87/500 [02:06<09:42,  1.41s/it, loss=2400.0000, t=912]
Attacking:  18%|█▊        | 88/500 [02:06<09:39,  1.41s/it, loss=2400.0000, t=912]
Attacking:  18%|█▊        | 88/500 [02:07<09:39,  1.41s/it, loss=2400.0000, t=912]
Attacking:  18%|█▊        | 89/500 [02:08<09:34,  1.40s/it, loss=2400.0000, t=912]
Attacking:  18%|█▊        | 89/500 [02:08<09:34,  1.40s/it, loss=2400.0000, t=952]
Attacking:  18%|█▊        | 90/500 [02:09<09:34,  1.40s/it, loss=2400.0000, t=952]
Attacking:  18%|█▊        | 90/500 [02:10<09:34,  1.40s/it, loss=2400.0000, t=912]
Attacking:  18%|█▊        | 91/500 [02:11<09:29,  1.39s/it, loss=2400.0000, t=912]
Attacking:  18%|█▊        | 91/500 [02:11<09:29,  1.39s/it, loss=2400.0000, t=952]
Attacking:  18%|█▊        | 92/500 [02:12<09:27,  1.39s/it, loss=2400.0000, t=952]
Attacking:  18%|█▊        | 92/500 [02:13<09:27,  1.39s/it, loss=2448.0000, t=992]
Attacking:  19%|█▊        | 93/500 [02:13<09:27,  1.39s/it, loss=2448.0000, t=992]
Attacking:  19%|█▊        | 93/500 [02:14<09:27,  1.39s/it, loss=2432.0000, t=984]
Attacking:  19%|█▉        | 94/500 [02:15<09:22,  1.39s/it, loss=2432.0000, t=984]
Attacking:  19%|█▉        | 94/500 [02:15<09:22,  1.39s/it, loss=2400.0000, t=900]
Attacking:  19%|█▉        | 95/500 [02:16<09:21,  1.39s/it, loss=2400.0000, t=900]
Attacking:  19%|█▉        | 95/500 [02:17<09:21,  1.39s/it, loss=2400.0000, t=928]
Attacking:  19%|█▉        | 96/500 [02:18<09:20,  1.39s/it, loss=2400.0000, t=928]
Attacking:  19%|█▉        | 96/500 [02:18<09:20,  1.39s/it, loss=2432.0000, t=984]
Attacking:  19%|█▉        | 97/500 [02:19<09:19,  1.39s/it, loss=2432.0000, t=984]
Attacking:  19%|█▉        | 97/500 [02:19<09:19,  1.39s/it, loss=2416.0000, t=972]
Attacking:  20%|█▉        | 98/500 [02:20<09:16,  1.38s/it, loss=2416.0000, t=972]
Attacking:  20%|█▉        | 98/500 [02:21<09:16,  1.38s/it, loss=2400.0000, t=928]
Attacking:  20%|█▉        | 99/500 [02:22<09:21,  1.40s/it, loss=2400.0000, t=928]
Attacking:  20%|█▉        | 99/500 [02:22<09:21,  1.40s/it, loss=2400.0000, t=900]
Attacking:  20%|██        | 100/500 [02:23<09:17,  1.39s/it, loss=2400.0000, t=900]
Attacking:  20%|██        | 100/500 [02:24<09:17,  1.39s/it, loss=2400.0000, t=928]
Attacking:  20%|██        | 101/500 [02:25<09:14,  1.39s/it, loss=2400.0000, t=928]
Attacking:  20%|██        | 101/500 [02:25<09:14,  1.39s/it, loss=2400.0000, t=928]
Attacking:  20%|██        | 102/500 [02:26<09:16,  1.40s/it, loss=2400.0000, t=928]
Attacking:  20%|██        | 102/500 [02:26<09:16,  1.40s/it, loss=2480.0000, t=1e+3]
Attacking:  21%|██        | 103/500 [02:27<09:14,  1.40s/it, loss=2480.0000, t=1e+3]
Attacking:  21%|██        | 103/500 [02:28<09:14,  1.40s/it, loss=2448.0000, t=992] 
Attacking:  21%|██        | 104/500 [02:29<09:19,  1.41s/it, loss=2448.0000, t=992]
Attacking:  21%|██        | 104/500 [02:29<09:19,  1.41s/it, loss=2400.0000, t=900]
Attacking:  21%|██        | 105/500 [02:30<09:34,  1.45s/it, loss=2400.0000, t=900]
Attacking:  21%|██        | 105/500 [02:31<09:34,  1.45s/it, loss=2400.0000, t=964]
Attacking:  21%|██        | 106/500 [02:32<09:35,  1.46s/it, loss=2400.0000, t=964]
Attacking:  21%|██        | 106/500 [02:32<09:35,  1.46s/it, loss=2496.0000, t=1e+3]
Attacking:  21%|██▏       | 107/500 [02:33<09:40,  1.48s/it, loss=2496.0000, t=1e+3]
Attacking:  21%|██▏       | 107/500 [02:34<09:40,  1.48s/it, loss=2400.0000, t=900] 
Attacking:  22%|██▏       | 108/500 [02:35<09:39,  1.48s/it, loss=2400.0000, t=900]
Attacking:  22%|██▏       | 108/500 [02:36<09:39,  1.48s/it, loss=2400.0000, t=940]
Attacking:  22%|██▏       | 109/500 [02:36<09:51,  1.51s/it, loss=2400.0000, t=940]
Attacking:  22%|██▏       | 109/500 [02:37<09:51,  1.51s/it, loss=2464.0000, t=1e+3]
Attacking:  22%|██▏       | 110/500 [02:38<09:55,  1.53s/it, loss=2464.0000, t=1e+3]
Attacking:  22%|██▏       | 110/500 [02:39<09:55,  1.53s/it, loss=2400.0000, t=940] 
Attacking:  22%|██▏       | 111/500 [02:40<10:02,  1.55s/it, loss=2400.0000, t=940]
Attacking:  22%|██▏       | 111/500 [02:40<10:02,  1.55s/it, loss=2384.0000, t=940]
Attacking:  22%|██▏       | 112/500 [02:41<10:12,  1.58s/it, loss=2384.0000, t=940]
Attacking:  22%|██▏       | 112/500 [02:42<10:12,  1.58s/it, loss=2400.0000, t=952]
Attacking:  23%|██▎       | 113/500 [02:43<10:19,  1.60s/it, loss=2400.0000, t=952]
Attacking:  23%|██▎       | 113/500 [02:44<10:19,  1.60s/it, loss=2384.0000, t=928]
Attacking:  23%|██▎       | 114/500 [02:44<10:13,  1.59s/it, loss=2384.0000, t=928]
Attacking:  23%|██▎       | 114/500 [02:45<10:13,  1.59s/it, loss=2384.0000, t=928]
Attacking:  23%|██▎       | 115/500 [02:46<10:00,  1.56s/it, loss=2384.0000, t=928]
Attacking:  23%|██▎       | 115/500 [02:47<10:00,  1.56s/it, loss=2384.0000, t=964]
Attacking:  23%|██▎       | 116/500 [02:47<09:52,  1.54s/it, loss=2384.0000, t=964]
Attacking:  23%|██▎       | 116/500 [02:48<09:52,  1.54s/it, loss=2384.0000, t=972]
Attacking:  23%|██▎       | 117/500 [02:49<09:44,  1.52s/it, loss=2384.0000, t=972]
Attacking:  23%|██▎       | 117/500 [02:49<09:44,  1.52s/it, loss=2384.0000, t=940]
Attacking:  24%|██▎       | 118/500 [02:50<09:35,  1.51s/it, loss=2384.0000, t=940]
Attacking:  24%|██▎       | 118/500 [02:51<09:35,  1.51s/it, loss=2384.0000, t=964]
Attacking:  24%|██▍       | 119/500 [02:52<09:29,  1.50s/it, loss=2384.0000, t=964]
Attacking:  24%|██▍       | 119/500 [02:53<09:29,  1.50s/it, loss=2384.0000, t=952]
Attacking:  24%|██▍       | 120/500 [02:54<10:01,  1.58s/it, loss=2384.0000, t=952]
Attacking:  24%|██▍       | 120/500 [02:54<10:01,  1.58s/it, loss=2384.0000, t=952]
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+Max Diff: 0.501961
+Mean Diff: 0.241055
+Saved adversarial image to attacked/images/camel.jpg
+Saved loss curve to attacked/loss_curve/camel_loss.png
+[GPU 1] Stage 3/3: Test
+Loading models for testing camel...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for camel...
+
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+
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+Saved video to attacked/videos/camel.mp4
+Saved frames to attacked/frames/camel
+[GPU 1] Finished camel.jpg
+======================================
+[GPU 1] Processing car-roundabout.jpg (Image 8/50)
+======================================
+[GPU 1] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 1] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  20%|██        | 100/500 [02:47<11:17,  1.69s/it, loss=2128.0000, t=940]
Attacking:  20%|██        | 100/500 [02:48<11:17,  1.69s/it, loss=2208.0000, t=972]
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Attacking:  21%|██        | 103/500 [02:52<11:15,  1.70s/it, loss=2144.0000, t=940]
Attacking:  21%|██        | 103/500 [02:53<11:15,  1.70s/it, loss=2128.0000, t=928]
Attacking:  21%|██        | 104/500 [02:53<11:02,  1.67s/it, loss=2128.0000, t=928]
Attacking:  21%|██        | 104/500 [02:54<11:02,  1.67s/it, loss=2160.0000, t=972]
Attacking:  21%|██        | 105/500 [02:55<11:13,  1.71s/it, loss=2160.0000, t=972]
Attacking:  21%|██        | 105/500 [02:56<11:13,  1.71s/it, loss=2192.0000, t=984]
Attacking:  21%|██        | 106/500 [02:57<11:20,  1.73s/it, loss=2192.0000, t=984]
Attacking:  21%|██        | 106/500 [02:58<11:20,  1.73s/it, loss=2128.0000, t=940]
Attacking:  21%|██▏       | 107/500 [02:59<11:08,  1.70s/it, loss=2128.0000, t=940]
Attacking:  21%|██▏       | 107/500 [03:00<11:08,  1.70s/it, loss=2144.0000, t=964]
Attacking:  22%|██▏       | 108/500 [03:00<11:16,  1.73s/it, loss=2144.0000, t=964]
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Attacking:  22%|██▏       | 109/500 [03:03<11:13,  1.72s/it, loss=2208.0000, t=992]
Attacking:  22%|██▏       | 110/500 [03:04<10:56,  1.68s/it, loss=2208.0000, t=992]
Attacking:  22%|██▏       | 110/500 [03:05<10:56,  1.68s/it, loss=2112.0000, t=928]
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Attacking:  23%|██▎       | 115/500 [03:13<10:13,  1.59s/it, loss=2208.0000, t=992]
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Attacking:  23%|██▎       | 117/500 [03:16<10:19,  1.62s/it, loss=2128.0000, t=952]
Attacking:  24%|██▎       | 118/500 [03:17<10:09,  1.60s/it, loss=2128.0000, t=952]
Attacking:  24%|██▎       | 118/500 [03:17<10:09,  1.60s/it, loss=2144.0000, t=964]
Attacking:  24%|██▍       | 119/500 [03:18<10:09,  1.60s/it, loss=2144.0000, t=964]
Attacking:  24%|██▍       | 119/500 [03:19<10:09,  1.60s/it, loss=2160.0000, t=972]
Attacking:  24%|██▍       | 120/500 [03:20<10:20,  1.63s/it, loss=2160.0000, t=972]
Attacking:  24%|██▍       | 120/500 [03:21<10:20,  1.63s/it, loss=2096.0000, t=900]
Attacking:  24%|██▍       | 121/500 [03:21<10:17,  1.63s/it, loss=2096.0000, t=900]
Attacking:  24%|██▍       | 121/500 [03:22<10:17,  1.63s/it, loss=2112.0000, t=940]
Attacking:  24%|██▍       | 122/500 [03:23<10:26,  1.66s/it, loss=2112.0000, t=940]
Attacking:  24%|██▍       | 122/500 [03:24<10:26,  1.66s/it, loss=2176.0000, t=984]
Attacking:  25%|██▍       | 123/500 [03:25<10:40,  1.70s/it, loss=2176.0000, t=984]
Attacking:  25%|██▍       | 123/500 [03:26<10:40,  1.70s/it, loss=2144.0000, t=964]
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Attacking:  25%|██▍       | 124/500 [03:27<10:35,  1.69s/it, loss=2128.0000, t=952]
Attacking:  25%|██▌       | 125/500 [03:28<10:30,  1.68s/it, loss=2128.0000, t=952]
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Attacking:  99%|█████████▉| 496/500 [13:04<00:06,  1.54s/it, loss=2080.0000, t=972]
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Attacking: 100%|█████████▉| 498/500 [13:07<00:03,  1.55s/it, loss=2064.0000, t=952]
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Attacking: 100%|█████████▉| 499/500 [13:09<00:01,  1.53s/it, loss=2080.0000, t=972]
Attacking: 100%|██████████| 500/500 [13:10<00:00,  1.51s/it, loss=2080.0000, t=972]
Attacking: 100%|██████████| 500/500 [13:10<00:00,  1.58s/it, loss=2080.0000, t=972]
+Max Diff: 0.501961
+Mean Diff: 0.258962
+Saved adversarial image to attacked/images/car-roundabout.jpg
+Saved loss curve to attacked/loss_curve/car-roundabout_loss.png
+[GPU 1] Stage 3/3: Test
+Loading models for testing car-roundabout...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for car-roundabout...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 90.25it/s]
+Saved video to attacked/videos/car-roundabout.mp4
+Saved frames to attacked/frames/car-roundabout
+[GPU 1] Finished car-roundabout.jpg
+======================================
+[GPU 1] Processing car-shadow.jpg (Image 9/50)
+======================================
+[GPU 1] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 1] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   6%|▌         | 30/500 [00:48<12:26,  1.59s/it, loss=2592.0000, t=912]
Attacking:   6%|▌         | 30/500 [00:48<12:26,  1.59s/it, loss=2688.0000, t=984]
Attacking:   6%|▌         | 31/500 [00:49<12:24,  1.59s/it, loss=2688.0000, t=984]
Attacking:   6%|▌         | 31/500 [00:50<12:24,  1.59s/it, loss=2592.0000, t=912]
Attacking:   6%|▋         | 32/500 [00:51<12:24,  1.59s/it, loss=2592.0000, t=912]
Attacking:   6%|▋         | 32/500 [00:51<12:24,  1.59s/it, loss=2640.0000, t=964]
Attacking:   7%|▋         | 33/500 [00:52<12:12,  1.57s/it, loss=2640.0000, t=964]
Attacking:   7%|▋         | 33/500 [00:53<12:12,  1.57s/it, loss=2624.0000, t=964]
Attacking:   7%|▋         | 34/500 [00:54<12:04,  1.55s/it, loss=2624.0000, t=964]
Attacking:   7%|▋         | 34/500 [00:54<12:04,  1.55s/it, loss=2672.0000, t=984]
Attacking:   7%|▋         | 35/500 [00:55<11:57,  1.54s/it, loss=2672.0000, t=984]
Attacking:   7%|▋         | 35/500 [00:56<11:57,  1.54s/it, loss=2624.0000, t=964]
Attacking:   7%|▋         | 36/500 [00:57<12:08,  1.57s/it, loss=2624.0000, t=964]
Attacking:   7%|▋         | 36/500 [00:58<12:08,  1.57s/it, loss=2672.0000, t=984]
Attacking:   7%|▋         | 37/500 [00:58<11:53,  1.54s/it, loss=2672.0000, t=984]
Attacking:   7%|▋         | 37/500 [00:59<11:53,  1.54s/it, loss=2576.0000, t=900]
Attacking:   8%|▊         | 38/500 [01:00<11:38,  1.51s/it, loss=2576.0000, t=900]
Attacking:   8%|▊         | 38/500 [01:01<11:38,  1.51s/it, loss=2576.0000, t=900]
Attacking:   8%|▊         | 39/500 [01:01<11:41,  1.52s/it, loss=2576.0000, t=900]
Attacking:   8%|▊         | 39/500 [01:02<11:41,  1.52s/it, loss=2688.0000, t=984]
Attacking:   8%|▊         | 40/500 [01:03<11:48,  1.54s/it, loss=2688.0000, t=984]
Attacking:   8%|▊         | 40/500 [01:04<11:48,  1.54s/it, loss=2688.0000, t=992]
Attacking:   8%|▊         | 41/500 [01:05<11:48,  1.54s/it, loss=2688.0000, t=992]
Attacking:   8%|▊         | 41/500 [01:05<11:48,  1.54s/it, loss=2560.0000, t=900]
Attacking:   8%|▊         | 42/500 [01:06<11:46,  1.54s/it, loss=2560.0000, t=900]
Attacking:   8%|▊         | 42/500 [01:07<11:46,  1.54s/it, loss=2608.0000, t=964]
Attacking:   9%|▊         | 43/500 [01:08<11:54,  1.56s/it, loss=2608.0000, t=964]
Attacking:   9%|▊         | 43/500 [01:08<11:54,  1.56s/it, loss=2560.0000, t=912]
Attacking:   9%|▉         | 44/500 [01:09<11:41,  1.54s/it, loss=2560.0000, t=912]
Attacking:   9%|▉         | 44/500 [01:10<11:41,  1.54s/it, loss=2672.0000, t=992]
Attacking:   9%|▉         | 45/500 [01:11<11:49,  1.56s/it, loss=2672.0000, t=992]
Attacking:   9%|▉         | 45/500 [01:12<11:49,  1.56s/it, loss=2592.0000, t=952]
Attacking:   9%|▉         | 46/500 [01:12<12:02,  1.59s/it, loss=2592.0000, t=952]
Attacking:   9%|▉         | 46/500 [01:13<12:02,  1.59s/it, loss=2592.0000, t=964]
Attacking:   9%|▉         | 47/500 [01:14<11:55,  1.58s/it, loss=2592.0000, t=964]
Attacking:   9%|▉         | 47/500 [01:15<11:55,  1.58s/it, loss=2688.0000, t=1e+3]
Attacking:  10%|▉         | 48/500 [01:16<11:59,  1.59s/it, loss=2688.0000, t=1e+3]
Attacking:  10%|▉         | 48/500 [01:16<11:59,  1.59s/it, loss=2560.0000, t=912] 
Attacking:  10%|▉         | 49/500 [01:17<12:05,  1.61s/it, loss=2560.0000, t=912]
Attacking:  10%|▉         | 49/500 [01:18<12:05,  1.61s/it, loss=2624.0000, t=972]
Attacking:  10%|█         | 50/500 [01:19<11:53,  1.59s/it, loss=2624.0000, t=972]
Attacking:  10%|█         | 50/500 [01:20<11:53,  1.59s/it, loss=2608.0000, t=972]
Attacking:  10%|█         | 51/500 [01:20<11:56,  1.60s/it, loss=2608.0000, t=972]
Attacking:  10%|█         | 51/500 [01:21<11:56,  1.60s/it, loss=2656.0000, t=1e+3]
Attacking:  10%|█         | 52/500 [01:22<11:47,  1.58s/it, loss=2656.0000, t=1e+3]
Attacking:  10%|█         | 52/500 [01:23<11:47,  1.58s/it, loss=2656.0000, t=992] 
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Attacking:  11%|█         | 53/500 [01:24<11:47,  1.58s/it, loss=2656.0000, t=1e+3]
Attacking:  11%|█         | 54/500 [01:25<11:45,  1.58s/it, loss=2656.0000, t=1e+3]
Attacking:  11%|█         | 54/500 [01:26<11:45,  1.58s/it, loss=2640.0000, t=1e+3]
Attacking:  11%|█         | 55/500 [01:27<11:41,  1.58s/it, loss=2640.0000, t=1e+3]
Attacking:  11%|█         | 55/500 [01:27<11:41,  1.58s/it, loss=2624.0000, t=984] 
Attacking:  11%|█         | 56/500 [01:28<11:25,  1.54s/it, loss=2624.0000, t=984]
Attacking:  11%|█         | 56/500 [01:29<11:25,  1.54s/it, loss=2624.0000, t=984]
Attacking:  11%|█▏        | 57/500 [01:30<11:30,  1.56s/it, loss=2624.0000, t=984]
Attacking:  11%|█▏        | 57/500 [01:30<11:30,  1.56s/it, loss=2592.0000, t=972]
Attacking:  12%|█▏        | 58/500 [01:31<11:23,  1.55s/it, loss=2592.0000, t=972]
Attacking:  12%|█▏        | 58/500 [01:32<11:23,  1.55s/it, loss=2576.0000, t=964]
Attacking:  12%|█▏        | 59/500 [01:33<11:57,  1.63s/it, loss=2576.0000, t=964]
Attacking:  12%|█▏        | 59/500 [01:34<11:57,  1.63s/it, loss=2576.0000, t=972]
Attacking:  12%|█▏        | 60/500 [01:35<11:30,  1.57s/it, loss=2576.0000, t=972]
Attacking:  12%|█▏        | 60/500 [01:35<11:30,  1.57s/it, loss=2592.0000, t=984]
Attacking:  12%|█▏        | 61/500 [01:36<11:08,  1.52s/it, loss=2592.0000, t=984]
Attacking:  12%|█▏        | 61/500 [01:37<11:08,  1.52s/it, loss=2560.0000, t=952]
Attacking:  12%|█▏        | 62/500 [01:38<11:23,  1.56s/it, loss=2560.0000, t=952]
Attacking:  12%|█▏        | 62/500 [01:38<11:23,  1.56s/it, loss=2512.0000, t=900]
Attacking:  13%|█▎        | 63/500 [01:39<11:26,  1.57s/it, loss=2512.0000, t=900]
Attacking:  13%|█▎        | 63/500 [01:40<11:26,  1.57s/it, loss=2560.0000, t=952]
Attacking:  13%|█▎        | 64/500 [01:41<11:30,  1.58s/it, loss=2560.0000, t=952]
Attacking:  13%|█▎        | 64/500 [01:42<11:30,  1.58s/it, loss=2624.0000, t=1e+3]
Attacking:  13%|█▎        | 65/500 [01:42<11:27,  1.58s/it, loss=2624.0000, t=1e+3]
Attacking:  13%|█▎        | 65/500 [01:43<11:27,  1.58s/it, loss=2528.0000, t=928] 
Attacking:  13%|█▎        | 66/500 [01:44<11:32,  1.59s/it, loss=2528.0000, t=928]
Attacking:  13%|█▎        | 66/500 [01:45<11:32,  1.59s/it, loss=2512.0000, t=912]
Attacking:  13%|█▎        | 67/500 [01:46<11:31,  1.60s/it, loss=2512.0000, t=912]
Attacking:  13%|█▎        | 67/500 [01:46<11:31,  1.60s/it, loss=2608.0000, t=984]
Attacking:  14%|█▎        | 68/500 [01:47<11:20,  1.58s/it, loss=2608.0000, t=984]
Attacking:  14%|█▎        | 68/500 [01:48<11:20,  1.58s/it, loss=2528.0000, t=940]
Attacking:  14%|█▍        | 69/500 [01:49<11:20,  1.58s/it, loss=2528.0000, t=940]
Attacking:  14%|█▍        | 69/500 [01:49<11:20,  1.58s/it, loss=2576.0000, t=972]
Attacking:  14%|█▍        | 70/500 [01:50<11:23,  1.59s/it, loss=2576.0000, t=972]
Attacking:  14%|█▍        | 70/500 [01:51<11:23,  1.59s/it, loss=2512.0000, t=900]
Attacking:  14%|█▍        | 71/500 [01:52<11:33,  1.62s/it, loss=2512.0000, t=900]
Attacking:  14%|█▍        | 71/500 [01:53<11:33,  1.62s/it, loss=2624.0000, t=992]
Attacking:  14%|█▍        | 72/500 [01:54<11:19,  1.59s/it, loss=2624.0000, t=992]
Attacking:  14%|█▍        | 72/500 [01:54<11:19,  1.59s/it, loss=2528.0000, t=940]
Attacking:  15%|█▍        | 73/500 [01:55<11:30,  1.62s/it, loss=2528.0000, t=940]
Attacking:  15%|█▍        | 73/500 [01:56<11:30,  1.62s/it, loss=2496.0000, t=928]
Attacking:  15%|█▍        | 74/500 [01:57<11:25,  1.61s/it, loss=2496.0000, t=928]
Attacking:  15%|█▍        | 74/500 [01:58<11:25,  1.61s/it, loss=2544.0000, t=952]
Attacking:  15%|█▌        | 75/500 [01:58<11:27,  1.62s/it, loss=2544.0000, t=952]
Attacking:  15%|█▌        | 75/500 [01:59<11:27,  1.62s/it, loss=2608.0000, t=1e+3]
Attacking:  15%|█▌        | 76/500 [02:00<11:24,  1.62s/it, loss=2608.0000, t=1e+3]
Attacking:  15%|█▌        | 76/500 [02:01<11:24,  1.62s/it, loss=2496.0000, t=912] 
Attacking:  15%|█▌        | 77/500 [02:02<11:17,  1.60s/it, loss=2496.0000, t=912]
Attacking:  15%|█▌        | 77/500 [02:02<11:17,  1.60s/it, loss=2496.0000, t=928]
Attacking:  16%|█▌        | 78/500 [02:03<10:59,  1.56s/it, loss=2496.0000, t=928]
Attacking:  16%|█▌        | 78/500 [02:04<10:59,  1.56s/it, loss=2512.0000, t=940]
Attacking:  16%|█▌        | 79/500 [02:05<11:07,  1.59s/it, loss=2512.0000, t=940]
Attacking:  16%|█▌        | 79/500 [02:05<11:07,  1.59s/it, loss=2512.0000, t=928]
Attacking:  16%|█▌        | 80/500 [02:06<11:05,  1.59s/it, loss=2512.0000, t=928]
Attacking:  16%|█▌        | 80/500 [02:07<11:05,  1.59s/it, loss=2528.0000, t=952]
Attacking:  16%|█▌        | 81/500 [02:08<11:28,  1.64s/it, loss=2528.0000, t=952]
Attacking:  16%|█▌        | 81/500 [02:09<11:28,  1.64s/it, loss=2608.0000, t=992]
Attacking:  16%|█▋        | 82/500 [02:10<11:17,  1.62s/it, loss=2608.0000, t=992]
Attacking:  16%|█▋        | 82/500 [02:10<11:17,  1.62s/it, loss=2528.0000, t=952]
Attacking:  17%|█▋        | 83/500 [02:11<11:14,  1.62s/it, loss=2528.0000, t=952]
Attacking:  17%|█▋        | 83/500 [02:12<11:14,  1.62s/it, loss=2496.0000, t=900]
Attacking:  17%|█▋        | 84/500 [02:13<11:09,  1.61s/it, loss=2496.0000, t=900]
Attacking:  17%|█▋        | 84/500 [02:14<11:09,  1.61s/it, loss=2624.0000, t=992]
Attacking:  17%|█▋        | 85/500 [02:15<11:24,  1.65s/it, loss=2624.0000, t=992]
Attacking:  17%|█▋        | 85/500 [02:16<11:24,  1.65s/it, loss=2496.0000, t=900]
Attacking:  17%|█▋        | 86/500 [02:16<11:38,  1.69s/it, loss=2496.0000, t=900]
Attacking:  17%|█▋        | 86/500 [02:17<11:38,  1.69s/it, loss=2512.0000, t=952]
Attacking:  17%|█▋        | 87/500 [02:18<11:31,  1.68s/it, loss=2512.0000, t=952]
Attacking:  17%|█▋        | 87/500 [02:19<11:31,  1.68s/it, loss=2480.0000, t=900]
Attacking:  18%|█▊        | 88/500 [02:20<11:19,  1.65s/it, loss=2480.0000, t=900]
Attacking:  18%|█▊        | 88/500 [02:20<11:19,  1.65s/it, loss=2496.0000, t=940]
Attacking:  18%|█▊        | 89/500 [02:21<11:16,  1.65s/it, loss=2496.0000, t=940]
Attacking:  18%|█▊        | 89/500 [02:22<11:16,  1.65s/it, loss=2480.0000, t=912]
Attacking:  18%|█▊        | 90/500 [02:23<11:19,  1.66s/it, loss=2480.0000, t=912]
Attacking:  18%|█▊        | 90/500 [02:24<11:19,  1.66s/it, loss=2480.0000, t=912]
Attacking:  18%|█▊        | 91/500 [02:25<11:21,  1.67s/it, loss=2480.0000, t=912]
Attacking:  18%|█▊        | 91/500 [02:26<11:21,  1.67s/it, loss=2576.0000, t=984]
Attacking:  18%|█▊        | 92/500 [02:26<11:27,  1.68s/it, loss=2576.0000, t=984]
Attacking:  18%|█▊        | 92/500 [02:27<11:27,  1.68s/it, loss=2560.0000, t=984]
Attacking:  19%|█▊        | 93/500 [02:28<11:14,  1.66s/it, loss=2560.0000, t=984]
Attacking:  19%|█▊        | 93/500 [02:29<11:14,  1.66s/it, loss=2528.0000, t=964]
Attacking:  19%|█▉        | 94/500 [02:30<11:06,  1.64s/it, loss=2528.0000, t=964]
Attacking:  19%|█▉        | 94/500 [02:30<11:06,  1.64s/it, loss=2560.0000, t=984]
Attacking:  19%|█▉        | 95/500 [02:31<11:03,  1.64s/it, loss=2560.0000, t=984]
Attacking:  19%|█▉        | 95/500 [02:32<11:03,  1.64s/it, loss=2528.0000, t=972]
Attacking:  19%|█▉        | 96/500 [02:33<10:49,  1.61s/it, loss=2528.0000, t=972]
Attacking:  19%|█▉        | 96/500 [02:33<10:49,  1.61s/it, loss=2592.0000, t=1e+3]
Attacking:  19%|█▉        | 97/500 [02:34<10:46,  1.61s/it, loss=2592.0000, t=1e+3]
Attacking:  19%|█▉        | 97/500 [02:35<10:46,  1.61s/it, loss=2512.0000, t=952] 
Attacking:  20%|█▉        | 98/500 [02:36<10:34,  1.58s/it, loss=2512.0000, t=952]
Attacking:  20%|█▉        | 98/500 [02:37<10:34,  1.58s/it, loss=2496.0000, t=952]
Attacking:  20%|█▉        | 99/500 [02:37<10:36,  1.59s/it, loss=2496.0000, t=952]
Attacking:  20%|█▉        | 99/500 [02:38<10:36,  1.59s/it, loss=2480.0000, t=912]
Attacking:  20%|██        | 100/500 [02:39<10:26,  1.57s/it, loss=2480.0000, t=912]
Attacking:  20%|██        | 100/500 [02:40<10:26,  1.57s/it, loss=2496.0000, t=952]
Attacking:  20%|██        | 101/500 [02:41<10:21,  1.56s/it, loss=2496.0000, t=952]
Attacking:  20%|██        | 101/500 [02:41<10:21,  1.56s/it, loss=2496.0000, t=940]
Attacking:  20%|██        | 102/500 [02:42<10:48,  1.63s/it, loss=2496.0000, t=940]
Attacking:  20%|██        | 102/500 [02:43<10:48,  1.63s/it, loss=2480.0000, t=928]
Attacking:  21%|██        | 103/500 [02:44<10:58,  1.66s/it, loss=2480.0000, t=928]
Attacking:  21%|██        | 103/500 [02:45<10:58,  1.66s/it, loss=2512.0000, t=952]
Attacking:  21%|██        | 104/500 [02:46<10:44,  1.63s/it, loss=2512.0000, t=952]
Attacking:  21%|██        | 104/500 [02:46<10:44,  1.63s/it, loss=2592.0000, t=1e+3]
Attacking:  21%|██        | 105/500 [02:47<10:45,  1.64s/it, loss=2592.0000, t=1e+3]
Attacking:  21%|██        | 105/500 [02:48<10:45,  1.64s/it, loss=2592.0000, t=1e+3]
Attacking:  21%|██        | 106/500 [02:49<10:52,  1.66s/it, loss=2592.0000, t=1e+3]
Attacking:  21%|██        | 106/500 [02:50<10:52,  1.66s/it, loss=2528.0000, t=972] 
Attacking:  21%|██▏       | 107/500 [02:51<10:51,  1.66s/it, loss=2528.0000, t=972]
Attacking:  21%|██▏       | 107/500 [02:51<10:51,  1.66s/it, loss=2592.0000, t=992]
Attacking:  22%|██▏       | 108/500 [02:52<10:39,  1.63s/it, loss=2592.0000, t=992]
Attacking:  22%|██▏       | 108/500 [02:53<10:39,  1.63s/it, loss=2480.0000, t=912]
Attacking:  22%|██▏       | 109/500 [02:54<10:29,  1.61s/it, loss=2480.0000, t=912]
Attacking:  22%|██▏       | 109/500 [02:55<10:29,  1.61s/it, loss=2560.0000, t=984]
Attacking:  22%|██▏       | 110/500 [02:55<10:30,  1.62s/it, loss=2560.0000, t=984]
Attacking:  22%|██▏       | 110/500 [02:56<10:30,  1.62s/it, loss=2480.0000, t=928]
Attacking:  22%|██▏       | 111/500 [02:57<10:40,  1.65s/it, loss=2480.0000, t=928]
Attacking:  22%|██▏       | 111/500 [02:58<10:40,  1.65s/it, loss=2592.0000, t=1e+3]
Attacking:  22%|██▏       | 112/500 [02:59<10:38,  1.64s/it, loss=2592.0000, t=1e+3]
Attacking:  22%|██▏       | 112/500 [02:59<10:38,  1.64s/it, loss=2464.0000, t=900] 
Attacking:  23%|██▎       | 113/500 [03:00<10:32,  1.64s/it, loss=2464.0000, t=900]
Attacking:  23%|██▎       | 113/500 [03:01<10:32,  1.64s/it, loss=2464.0000, t=900]
Attacking:  23%|██▎       | 114/500 [03:02<10:42,  1.66s/it, loss=2464.0000, t=900]
Attacking:  23%|██▎       | 114/500 [03:03<10:42,  1.66s/it, loss=2592.0000, t=992]
Attacking:  23%|██▎       | 115/500 [03:04<10:43,  1.67s/it, loss=2592.0000, t=992]
Attacking:  23%|██▎       | 115/500 [03:05<10:43,  1.67s/it, loss=2528.0000, t=972]
Attacking:  23%|██▎       | 116/500 [03:05<10:34,  1.65s/it, loss=2528.0000, t=972]
Attacking:  23%|██▎       | 116/500 [03:06<10:34,  1.65s/it, loss=2592.0000, t=1e+3]
Attacking:  23%|██▎       | 117/500 [03:07<10:22,  1.63s/it, loss=2592.0000, t=1e+3]
Attacking:  23%|██▎       | 117/500 [03:08<10:22,  1.63s/it, loss=2576.0000, t=1e+3]
Attacking:  24%|██▎       | 118/500 [03:08<10:06,  1.59s/it, loss=2576.0000, t=1e+3]
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Attacking: 100%|██████████| 500/500 [12:54<00:00,  1.55s/it, loss=2416.0000, t=900]
+Max Diff: 0.501961
+Mean Diff: 0.256656
+Saved adversarial image to attacked/images/car-shadow.jpg
+Saved loss curve to attacked/loss_curve/car-shadow_loss.png
+[GPU 1] Stage 3/3: Test
+Loading models for testing car-shadow...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for car-shadow...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 114.45it/s]
+Saved video to attacked/videos/car-shadow.mp4
+Saved frames to attacked/frames/car-shadow
+[GPU 1] Finished car-shadow.jpg
+======================================
+[GPU 1] Processing car-turn.jpg (Image 10/50)
+======================================
+[GPU 1] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 1] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  20%|██        | 100/500 [02:41<10:19,  1.55s/it, loss=1760.0000, t=992]
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Attacking:  21%|██        | 103/500 [02:45<10:17,  1.56s/it, loss=1728.0000, t=952]
Attacking:  21%|██        | 103/500 [02:46<10:17,  1.56s/it, loss=1696.0000, t=912]
Attacking:  21%|██        | 104/500 [02:47<10:14,  1.55s/it, loss=1696.0000, t=912]
Attacking:  21%|██        | 104/500 [02:47<10:14,  1.55s/it, loss=1720.0000, t=940]
Attacking:  21%|██        | 105/500 [02:48<10:06,  1.54s/it, loss=1720.0000, t=940]
Attacking:  21%|██        | 105/500 [02:49<10:06,  1.54s/it, loss=1728.0000, t=972]
Attacking:  21%|██        | 106/500 [02:50<10:04,  1.53s/it, loss=1728.0000, t=972]
Attacking:  21%|██        | 106/500 [02:51<10:04,  1.53s/it, loss=1720.0000, t=952]
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Attacking:  21%|██▏       | 107/500 [02:52<10:06,  1.54s/it, loss=1736.0000, t=972]
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Attacking:  23%|██▎       | 115/500 [03:04<09:28,  1.48s/it, loss=1720.0000, t=964]
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Attacking:  24%|██▎       | 118/500 [03:09<09:24,  1.48s/it, loss=1704.0000, t=928]
Attacking:  24%|██▍       | 119/500 [03:10<09:20,  1.47s/it, loss=1704.0000, t=928]
Attacking:  24%|██▍       | 119/500 [03:10<09:20,  1.47s/it, loss=1768.0000, t=1e+3]
Attacking:  24%|██▍       | 120/500 [03:11<09:54,  1.56s/it, loss=1768.0000, t=1e+3]
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Attacking:  24%|██▍       | 122/500 [03:15<10:01,  1.59s/it, loss=1680.0000, t=900]
Attacking:  25%|██▍       | 123/500 [03:16<10:01,  1.60s/it, loss=1680.0000, t=900]
Attacking:  25%|██▍       | 123/500 [03:17<10:01,  1.60s/it, loss=1688.0000, t=928]
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Attacking:  26%|██▌       | 128/500 [03:24<09:49,  1.58s/it, loss=1696.0000, t=940]
Attacking:  26%|██▌       | 128/500 [03:25<09:49,  1.58s/it, loss=1744.0000, t=992]
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Attacking:  26%|██▌       | 130/500 [03:28<09:46,  1.59s/it, loss=1712.0000, t=952]
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Attacking:  26%|██▋       | 132/500 [03:31<09:54,  1.62s/it, loss=1720.0000, t=964] 
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Attacking:  27%|██▋       | 135/500 [03:36<10:09,  1.67s/it, loss=1688.0000, t=912]
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Attacking:  27%|██▋       | 136/500 [03:38<10:00,  1.65s/it, loss=1768.0000, t=1e+3]
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Attacking:  27%|██▋       | 137/500 [03:40<09:51,  1.63s/it, loss=1712.0000, t=972] 
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Attacking:  99%|█████████▉| 495/500 [12:52<00:07,  1.55s/it, loss=1704.0000, t=1e+3]
Attacking:  99%|█████████▉| 496/500 [12:53<00:06,  1.56s/it, loss=1704.0000, t=1e+3]
Attacking:  99%|█████████▉| 496/500 [12:53<00:06,  1.56s/it, loss=1648.0000, t=940] 
Attacking:  99%|█████████▉| 497/500 [12:54<00:04,  1.58s/it, loss=1648.0000, t=940]
Attacking:  99%|█████████▉| 497/500 [12:55<00:04,  1.58s/it, loss=1632.0000, t=912]
Attacking: 100%|█████████▉| 498/500 [12:56<00:03,  1.60s/it, loss=1632.0000, t=912]
Attacking: 100%|█████████▉| 498/500 [12:57<00:03,  1.60s/it, loss=1648.0000, t=940]
Attacking: 100%|█████████▉| 499/500 [12:57<00:01,  1.59s/it, loss=1648.0000, t=940]
Attacking: 100%|█████████▉| 499/500 [12:58<00:01,  1.59s/it, loss=1656.0000, t=964]
Attacking: 100%|██████████| 500/500 [12:59<00:00,  1.59s/it, loss=1656.0000, t=964]
Attacking: 100%|██████████| 500/500 [12:59<00:00,  1.56s/it, loss=1656.0000, t=964]
+Max Diff: 0.501961
+Mean Diff: 0.235519
+Saved adversarial image to attacked/images/car-turn.jpg
+Saved loss curve to attacked/loss_curve/car-turn_loss.png
+[GPU 1] Stage 3/3: Test
+Loading models for testing car-turn...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for car-turn...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 97.19it/s]
+Saved video to attacked/videos/car-turn.mp4
+Saved frames to attacked/frames/car-turn
+[GPU 1] Finished car-turn.jpg
+======================================
+[GPU 1] Processing carousel.jpg (Image 11/50)
+======================================
+[GPU 1] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 1] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   6%|▌         | 29/500 [00:48<12:22,  1.58s/it, loss=2480.0000, t=940]
Attacking:   6%|▌         | 30/500 [00:49<12:02,  1.54s/it, loss=2480.0000, t=940]
Attacking:   6%|▌         | 30/500 [00:50<12:02,  1.54s/it, loss=2528.0000, t=972]
Attacking:   6%|▌         | 31/500 [00:50<11:46,  1.51s/it, loss=2528.0000, t=972]
Attacking:   6%|▌         | 31/500 [00:51<11:46,  1.51s/it, loss=2480.0000, t=952]
Attacking:   6%|▋         | 32/500 [00:52<11:37,  1.49s/it, loss=2480.0000, t=952]
Attacking:   6%|▋         | 32/500 [00:53<11:37,  1.49s/it, loss=2448.0000, t=912]
Attacking:   7%|▋         | 33/500 [00:53<11:54,  1.53s/it, loss=2448.0000, t=912]
Attacking:   7%|▋         | 33/500 [00:54<11:54,  1.53s/it, loss=2512.0000, t=972]
Attacking:   7%|▋         | 34/500 [00:55<11:45,  1.51s/it, loss=2512.0000, t=972]
Attacking:   7%|▋         | 34/500 [00:56<11:45,  1.51s/it, loss=2496.0000, t=992]
Attacking:   7%|▋         | 35/500 [00:56<11:34,  1.49s/it, loss=2496.0000, t=992]
Attacking:   7%|▋         | 35/500 [00:57<11:34,  1.49s/it, loss=2464.0000, t=952]
Attacking:   7%|▋         | 36/500 [00:58<11:36,  1.50s/it, loss=2464.0000, t=952]
Attacking:   7%|▋         | 36/500 [00:59<11:36,  1.50s/it, loss=2464.0000, t=940]
Attacking:   7%|▋         | 37/500 [01:00<11:47,  1.53s/it, loss=2464.0000, t=940]
Attacking:   7%|▋         | 37/500 [01:00<11:47,  1.53s/it, loss=2480.0000, t=992]
Attacking:   8%|▊         | 38/500 [01:01<11:48,  1.53s/it, loss=2480.0000, t=992]
Attacking:   8%|▊         | 38/500 [01:02<11:48,  1.53s/it, loss=2432.0000, t=900]
Attacking:   8%|▊         | 39/500 [01:03<11:49,  1.54s/it, loss=2432.0000, t=900]
Attacking:   8%|▊         | 39/500 [01:03<11:49,  1.54s/it, loss=2496.0000, t=972]
Attacking:   8%|▊         | 40/500 [01:04<11:55,  1.56s/it, loss=2496.0000, t=972]
Attacking:   8%|▊         | 40/500 [01:05<11:55,  1.56s/it, loss=2464.0000, t=952]
Attacking:   8%|▊         | 41/500 [01:06<11:49,  1.55s/it, loss=2464.0000, t=952]
Attacking:   8%|▊         | 41/500 [01:06<11:49,  1.55s/it, loss=2480.0000, t=972]
Attacking:   8%|▊         | 42/500 [01:07<11:55,  1.56s/it, loss=2480.0000, t=972]
Attacking:   8%|▊         | 42/500 [01:08<11:55,  1.56s/it, loss=2448.0000, t=940]
Attacking:   9%|▊         | 43/500 [01:09<11:56,  1.57s/it, loss=2448.0000, t=940]
Attacking:   9%|▊         | 43/500 [01:10<11:56,  1.57s/it, loss=2448.0000, t=952]
Attacking:   9%|▉         | 44/500 [01:10<11:52,  1.56s/it, loss=2448.0000, t=952]
Attacking:   9%|▉         | 44/500 [01:11<11:52,  1.56s/it, loss=2448.0000, t=928]
Attacking:   9%|▉         | 45/500 [01:12<11:49,  1.56s/it, loss=2448.0000, t=928]
Attacking:   9%|▉         | 45/500 [01:13<11:49,  1.56s/it, loss=2464.0000, t=964]
Attacking:   9%|▉         | 46/500 [01:14<11:44,  1.55s/it, loss=2464.0000, t=964]
Attacking:   9%|▉         | 46/500 [01:14<11:44,  1.55s/it, loss=2400.0000, t=900]
Attacking:   9%|▉         | 47/500 [01:15<11:43,  1.55s/it, loss=2400.0000, t=900]
Attacking:   9%|▉         | 47/500 [01:16<11:43,  1.55s/it, loss=2496.0000, t=1e+3]
Attacking:  10%|▉         | 48/500 [01:17<11:43,  1.56s/it, loss=2496.0000, t=1e+3]
Attacking:  10%|▉         | 48/500 [01:17<11:43,  1.56s/it, loss=2416.0000, t=912] 
Attacking:  10%|▉         | 49/500 [01:18<11:48,  1.57s/it, loss=2416.0000, t=912]
Attacking:  10%|▉         | 49/500 [01:19<11:48,  1.57s/it, loss=2496.0000, t=1e+3]
Attacking:  10%|█         | 50/500 [01:20<11:34,  1.54s/it, loss=2496.0000, t=1e+3]
Attacking:  10%|█         | 50/500 [01:20<11:34,  1.54s/it, loss=2400.0000, t=900] 
Attacking:  10%|█         | 51/500 [01:21<11:27,  1.53s/it, loss=2400.0000, t=900]
Attacking:  10%|█         | 51/500 [01:22<11:27,  1.53s/it, loss=2496.0000, t=1e+3]
Attacking:  10%|█         | 52/500 [01:23<11:35,  1.55s/it, loss=2496.0000, t=1e+3]
Attacking:  10%|█         | 52/500 [01:24<11:35,  1.55s/it, loss=2416.0000, t=984] 
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Attacking:  11%|█         | 53/500 [01:25<11:51,  1.59s/it, loss=2464.0000, t=972]
Attacking:  11%|█         | 54/500 [01:26<11:44,  1.58s/it, loss=2464.0000, t=972]
Attacking:  11%|█         | 54/500 [01:27<11:44,  1.58s/it, loss=2464.0000, t=972]
Attacking:  11%|█         | 55/500 [01:28<11:42,  1.58s/it, loss=2464.0000, t=972]
Attacking:  11%|█         | 55/500 [01:28<11:42,  1.58s/it, loss=2416.0000, t=940]
Attacking:  11%|█         | 56/500 [01:29<11:51,  1.60s/it, loss=2416.0000, t=940]
Attacking:  11%|█         | 56/500 [01:30<11:51,  1.60s/it, loss=2432.0000, t=952]
Attacking:  11%|█▏        | 57/500 [01:31<11:48,  1.60s/it, loss=2432.0000, t=952]
Attacking:  11%|█▏        | 57/500 [01:32<11:48,  1.60s/it, loss=2400.0000, t=912]
Attacking:  12%|█▏        | 58/500 [01:33<12:00,  1.63s/it, loss=2400.0000, t=912]
Attacking:  12%|█▏        | 58/500 [01:34<12:00,  1.63s/it, loss=2416.0000, t=984]
Attacking:  12%|█▏        | 59/500 [01:35<13:05,  1.78s/it, loss=2416.0000, t=984]
Attacking:  12%|█▏        | 59/500 [01:35<13:05,  1.78s/it, loss=2400.0000, t=928]
Attacking:  12%|█▏        | 60/500 [01:36<12:31,  1.71s/it, loss=2400.0000, t=928]
Attacking:  12%|█▏        | 60/500 [01:37<12:31,  1.71s/it, loss=2416.0000, t=984]
Attacking:  12%|█▏        | 61/500 [01:38<12:21,  1.69s/it, loss=2416.0000, t=984]
Attacking:  12%|█▏        | 61/500 [01:39<12:21,  1.69s/it, loss=2400.0000, t=912]
Attacking:  12%|█▏        | 62/500 [01:40<12:14,  1.68s/it, loss=2400.0000, t=912]
Attacking:  12%|█▏        | 62/500 [01:40<12:14,  1.68s/it, loss=2384.0000, t=912]
Attacking:  13%|█▎        | 63/500 [01:41<12:12,  1.68s/it, loss=2384.0000, t=912]
Attacking:  13%|█▎        | 63/500 [01:42<12:12,  1.68s/it, loss=2400.0000, t=928]
Attacking:  13%|█▎        | 64/500 [01:43<12:10,  1.68s/it, loss=2400.0000, t=928]
Attacking:  13%|█▎        | 64/500 [01:44<12:10,  1.68s/it, loss=2448.0000, t=964]
Attacking:  13%|█▎        | 65/500 [01:45<12:05,  1.67s/it, loss=2448.0000, t=964]
Attacking:  13%|█▎        | 65/500 [01:45<12:05,  1.67s/it, loss=2448.0000, t=964]
Attacking:  13%|█▎        | 66/500 [01:46<12:05,  1.67s/it, loss=2448.0000, t=964]
Attacking:  13%|█▎        | 66/500 [01:47<12:05,  1.67s/it, loss=2432.0000, t=952]
Attacking:  13%|█▎        | 67/500 [01:48<11:57,  1.66s/it, loss=2432.0000, t=952]
Attacking:  13%|█▎        | 67/500 [01:49<11:57,  1.66s/it, loss=2416.0000, t=952]
Attacking:  14%|█▎        | 68/500 [01:50<11:51,  1.65s/it, loss=2416.0000, t=952]
Attacking:  14%|█▎        | 68/500 [01:50<11:51,  1.65s/it, loss=2416.0000, t=952]
Attacking:  14%|█▍        | 69/500 [01:51<11:37,  1.62s/it, loss=2416.0000, t=952]
Attacking:  14%|█▍        | 69/500 [01:52<11:37,  1.62s/it, loss=2416.0000, t=984]
Attacking:  14%|█▍        | 70/500 [01:53<11:16,  1.57s/it, loss=2416.0000, t=984]
Attacking:  14%|█▍        | 70/500 [01:53<11:16,  1.57s/it, loss=2416.0000, t=952]
Attacking:  14%|█▍        | 71/500 [01:54<11:21,  1.59s/it, loss=2416.0000, t=952]
Attacking:  14%|█▍        | 71/500 [01:55<11:21,  1.59s/it, loss=2400.0000, t=984]
Attacking:  14%|█▍        | 72/500 [01:56<11:16,  1.58s/it, loss=2400.0000, t=984]
Attacking:  14%|█▍        | 72/500 [01:56<11:16,  1.58s/it, loss=2464.0000, t=972]
Attacking:  15%|█▍        | 73/500 [01:57<11:08,  1.57s/it, loss=2464.0000, t=972]
Attacking:  15%|█▍        | 73/500 [01:58<11:08,  1.57s/it, loss=2400.0000, t=984]
Attacking:  15%|█▍        | 74/500 [01:59<11:28,  1.62s/it, loss=2400.0000, t=984]
Attacking:  15%|█▍        | 74/500 [02:00<11:28,  1.62s/it, loss=2400.0000, t=952]
Attacking:  15%|█▌        | 75/500 [02:01<11:33,  1.63s/it, loss=2400.0000, t=952]
Attacking:  15%|█▌        | 75/500 [02:01<11:33,  1.63s/it, loss=2400.0000, t=984]
Attacking:  15%|█▌        | 76/500 [02:02<11:19,  1.60s/it, loss=2400.0000, t=984]
Attacking:  15%|█▌        | 76/500 [02:03<11:19,  1.60s/it, loss=2432.0000, t=964]
Attacking:  15%|█▌        | 77/500 [02:04<11:00,  1.56s/it, loss=2432.0000, t=964]
Attacking:  15%|█▌        | 77/500 [02:04<11:00,  1.56s/it, loss=2416.0000, t=992]
Attacking:  16%|█▌        | 78/500 [02:05<10:56,  1.56s/it, loss=2416.0000, t=992]
Attacking:  16%|█▌        | 78/500 [02:06<10:56,  1.56s/it, loss=2368.0000, t=912]
Attacking:  16%|█▌        | 79/500 [02:07<10:47,  1.54s/it, loss=2368.0000, t=912]
Attacking:  16%|█▌        | 79/500 [02:07<10:47,  1.54s/it, loss=2384.0000, t=928]
Attacking:  16%|█▌        | 80/500 [02:08<10:55,  1.56s/it, loss=2384.0000, t=928]
Attacking:  16%|█▌        | 80/500 [02:09<10:55,  1.56s/it, loss=2448.0000, t=1e+3]
Attacking:  16%|█▌        | 81/500 [02:10<11:16,  1.61s/it, loss=2448.0000, t=1e+3]
Attacking:  16%|█▌        | 81/500 [02:11<11:16,  1.61s/it, loss=2416.0000, t=992] 
Attacking:  16%|█▋        | 82/500 [02:12<10:58,  1.58s/it, loss=2416.0000, t=992]
Attacking:  16%|█▋        | 82/500 [02:12<10:58,  1.58s/it, loss=2400.0000, t=912]
Attacking:  17%|█▋        | 83/500 [02:13<10:54,  1.57s/it, loss=2400.0000, t=912]
Attacking:  17%|█▋        | 83/500 [02:14<10:54,  1.57s/it, loss=2400.0000, t=952]
Attacking:  17%|█▋        | 84/500 [02:15<10:48,  1.56s/it, loss=2400.0000, t=952]
Attacking:  17%|█▋        | 84/500 [02:15<10:48,  1.56s/it, loss=2400.0000, t=992]
Attacking:  17%|█▋        | 85/500 [02:16<10:43,  1.55s/it, loss=2400.0000, t=992]
Attacking:  17%|█▋        | 85/500 [02:17<10:43,  1.55s/it, loss=2416.0000, t=964]
Attacking:  17%|█▋        | 86/500 [02:18<10:50,  1.57s/it, loss=2416.0000, t=964]
Attacking:  17%|█▋        | 86/500 [02:19<10:50,  1.57s/it, loss=2448.0000, t=972]
Attacking:  17%|█▋        | 87/500 [02:19<10:57,  1.59s/it, loss=2448.0000, t=972]
Attacking:  17%|█▋        | 87/500 [02:20<10:57,  1.59s/it, loss=2352.0000, t=912]
Attacking:  18%|█▊        | 88/500 [02:21<11:02,  1.61s/it, loss=2352.0000, t=912]
Attacking:  18%|█▊        | 88/500 [02:22<11:02,  1.61s/it, loss=2432.0000, t=972]
Attacking:  18%|█▊        | 89/500 [02:23<10:48,  1.58s/it, loss=2432.0000, t=972]
Attacking:  18%|█▊        | 89/500 [02:23<10:48,  1.58s/it, loss=2416.0000, t=972]
Attacking:  18%|█▊        | 90/500 [02:24<10:49,  1.59s/it, loss=2416.0000, t=972]
Attacking:  18%|█▊        | 90/500 [02:25<10:49,  1.59s/it, loss=2384.0000, t=984]
Attacking:  18%|█▊        | 91/500 [02:26<10:36,  1.56s/it, loss=2384.0000, t=984]
Attacking:  18%|█▊        | 91/500 [02:26<10:36,  1.56s/it, loss=2352.0000, t=912]
Attacking:  18%|█▊        | 92/500 [02:27<10:47,  1.59s/it, loss=2352.0000, t=912]
Attacking:  18%|█▊        | 92/500 [02:28<10:47,  1.59s/it, loss=2416.0000, t=964]
Attacking:  19%|█▊        | 93/500 [02:29<10:50,  1.60s/it, loss=2416.0000, t=964]
Attacking:  19%|█▊        | 93/500 [02:30<10:50,  1.60s/it, loss=2400.0000, t=992]
Attacking:  19%|█▉        | 94/500 [02:30<10:43,  1.59s/it, loss=2400.0000, t=992]
Attacking:  19%|█▉        | 94/500 [02:31<10:43,  1.59s/it, loss=2352.0000, t=900]
Attacking:  19%|█▉        | 95/500 [02:32<10:48,  1.60s/it, loss=2352.0000, t=900]
Attacking:  19%|█▉        | 95/500 [02:33<10:48,  1.60s/it, loss=2432.0000, t=1e+3]
Attacking:  19%|█▉        | 96/500 [02:34<10:28,  1.56s/it, loss=2432.0000, t=1e+3]
Attacking:  19%|█▉        | 96/500 [02:34<10:28,  1.56s/it, loss=2384.0000, t=952] 
Attacking:  19%|█▉        | 97/500 [02:35<10:17,  1.53s/it, loss=2384.0000, t=952]
Attacking:  19%|█▉        | 97/500 [02:36<10:17,  1.53s/it, loss=2400.0000, t=984]
Attacking:  20%|█▉        | 98/500 [02:37<10:20,  1.54s/it, loss=2400.0000, t=984]
Attacking:  20%|█▉        | 98/500 [02:37<10:20,  1.54s/it, loss=2432.0000, t=1e+3]
Attacking:  20%|█▉        | 99/500 [02:38<10:28,  1.57s/it, loss=2432.0000, t=1e+3]
Attacking:  20%|█▉        | 99/500 [02:39<10:28,  1.57s/it, loss=2368.0000, t=928] 
Attacking:  20%|██        | 100/500 [02:40<10:30,  1.58s/it, loss=2368.0000, t=928]
Attacking:  20%|██        | 100/500 [02:41<10:30,  1.58s/it, loss=2384.0000, t=984]
Attacking:  20%|██        | 101/500 [02:41<10:32,  1.58s/it, loss=2384.0000, t=984]
Attacking:  20%|██        | 101/500 [02:42<10:32,  1.58s/it, loss=2384.0000, t=952]
Attacking:  20%|██        | 102/500 [02:43<10:21,  1.56s/it, loss=2384.0000, t=952]
Attacking:  20%|██        | 102/500 [02:44<10:21,  1.56s/it, loss=2432.0000, t=1e+3]
Attacking:  21%|██        | 103/500 [02:45<10:26,  1.58s/it, loss=2432.0000, t=1e+3]
Attacking:  21%|██        | 103/500 [02:45<10:26,  1.58s/it, loss=2368.0000, t=928] 
Attacking:  21%|██        | 104/500 [02:46<10:33,  1.60s/it, loss=2368.0000, t=928]
Attacking:  21%|██        | 104/500 [02:47<10:33,  1.60s/it, loss=2400.0000, t=964]
Attacking:  21%|██        | 105/500 [02:48<10:19,  1.57s/it, loss=2400.0000, t=964]
Attacking:  21%|██        | 105/500 [02:48<10:19,  1.57s/it, loss=2368.0000, t=940]
Attacking:  21%|██        | 106/500 [02:49<10:11,  1.55s/it, loss=2368.0000, t=940]
Attacking:  21%|██        | 106/500 [02:50<10:11,  1.55s/it, loss=2384.0000, t=952]
Attacking:  21%|██▏       | 107/500 [02:51<10:03,  1.54s/it, loss=2384.0000, t=952]
Attacking:  21%|██▏       | 107/500 [02:51<10:03,  1.54s/it, loss=2432.0000, t=1e+3]
Attacking:  22%|██▏       | 108/500 [02:52<10:10,  1.56s/it, loss=2432.0000, t=1e+3]
Attacking:  22%|██▏       | 108/500 [02:53<10:10,  1.56s/it, loss=2352.0000, t=900] 
Attacking:  22%|██▏       | 109/500 [02:54<10:17,  1.58s/it, loss=2352.0000, t=900]
Attacking:  22%|██▏       | 109/500 [02:55<10:17,  1.58s/it, loss=2384.0000, t=952]
Attacking:  22%|██▏       | 110/500 [02:55<10:09,  1.56s/it, loss=2384.0000, t=952]
Attacking:  22%|██▏       | 110/500 [02:56<10:09,  1.56s/it, loss=2400.0000, t=964]
Attacking:  22%|██▏       | 111/500 [02:57<09:57,  1.54s/it, loss=2400.0000, t=964]
Attacking:  22%|██▏       | 111/500 [02:58<09:57,  1.54s/it, loss=2384.0000, t=984]
Attacking:  22%|██▏       | 112/500 [02:59<10:08,  1.57s/it, loss=2384.0000, t=984]
Attacking:  22%|██▏       | 112/500 [02:59<10:08,  1.57s/it, loss=2400.0000, t=992]
Attacking:  23%|██▎       | 113/500 [03:00<10:10,  1.58s/it, loss=2400.0000, t=992]
Attacking:  23%|██▎       | 113/500 [03:01<10:10,  1.58s/it, loss=2368.0000, t=940]
Attacking:  23%|██▎       | 114/500 [03:02<10:12,  1.59s/it, loss=2368.0000, t=940]
Attacking:  23%|██▎       | 114/500 [03:03<10:12,  1.59s/it, loss=2352.0000, t=900]
Attacking:  23%|██▎       | 115/500 [03:03<10:08,  1.58s/it, loss=2352.0000, t=900]
Attacking:  23%|██▎       | 115/500 [03:04<10:08,  1.58s/it, loss=2416.0000, t=964]
Attacking:  23%|██▎       | 116/500 [03:05<10:19,  1.61s/it, loss=2416.0000, t=964]
Attacking:  23%|██▎       | 116/500 [03:06<10:19,  1.61s/it, loss=2400.0000, t=992]
Attacking:  23%|██▎       | 117/500 [03:07<10:27,  1.64s/it, loss=2400.0000, t=992]
Attacking:  23%|██▎       | 117/500 [03:08<10:27,  1.64s/it, loss=2368.0000, t=984]
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Attacking: 100%|██████████| 500/500 [12:56<00:00,  1.55s/it, loss=2288.0000, t=928]
+Max Diff: 0.501961
+Mean Diff: 0.262982
+Saved adversarial image to attacked/images/carousel.jpg
+Saved loss curve to attacked/loss_curve/carousel_loss.png
+[GPU 1] Stage 3/3: Test
+Loading models for testing carousel...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for carousel...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 46.75it/s]
+Saved video to attacked/videos/carousel.mp4
+Saved frames to attacked/frames/carousel
+[GPU 1] Finished carousel.jpg
+======================================
+[GPU 1] Processing cow.jpg (Image 12/50)
+======================================
+[GPU 1] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 1] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  16%|█▌        | 79/500 [02:07<11:23,  1.62s/it, loss=1944.0000, t=900]
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Attacking:  16%|█▌        | 81/500 [02:10<11:15,  1.61s/it, loss=2016.0000, t=1e+3]
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Attacking:  18%|█▊        | 88/500 [02:21<10:56,  1.59s/it, loss=2008.0000, t=1e+3]
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Attacking:  19%|█▉        | 95/500 [02:33<11:06,  1.65s/it, loss=1960.0000, t=940]
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Attacking:  19%|█▉        | 96/500 [02:35<10:57,  1.63s/it, loss=1952.0000, t=940]
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Attacking:  20%|█▉        | 98/500 [02:38<10:51,  1.62s/it, loss=1952.0000, t=928]
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Attacking:  20%|██        | 100/500 [02:40<10:50,  1.63s/it, loss=1960.0000, t=940]
Attacking:  20%|██        | 100/500 [02:41<10:50,  1.63s/it, loss=1992.0000, t=972]
Attacking:  20%|██        | 101/500 [02:42<10:50,  1.63s/it, loss=1992.0000, t=972]
Attacking:  20%|██        | 101/500 [02:43<10:50,  1.63s/it, loss=1968.0000, t=984]
Attacking:  20%|██        | 102/500 [02:43<10:48,  1.63s/it, loss=1968.0000, t=984]
Attacking:  20%|██        | 102/500 [02:44<10:48,  1.63s/it, loss=1976.0000, t=964]
Attacking:  21%|██        | 103/500 [02:45<10:48,  1.63s/it, loss=1976.0000, t=964]
Attacking:  21%|██        | 103/500 [02:46<10:48,  1.63s/it, loss=1928.0000, t=900]
Attacking:  21%|██        | 104/500 [02:47<10:37,  1.61s/it, loss=1928.0000, t=900]
Attacking:  21%|██        | 104/500 [02:48<10:37,  1.61s/it, loss=1984.0000, t=972]
Attacking:  21%|██        | 105/500 [02:48<10:52,  1.65s/it, loss=1984.0000, t=972]
Attacking:  21%|██        | 105/500 [02:49<10:52,  1.65s/it, loss=1936.0000, t=912]
Attacking:  21%|██        | 106/500 [02:50<10:49,  1.65s/it, loss=1936.0000, t=912]
Attacking:  21%|██        | 106/500 [02:51<10:49,  1.65s/it, loss=1960.0000, t=952]
Attacking:  21%|██▏       | 107/500 [02:52<10:52,  1.66s/it, loss=1960.0000, t=952]
Attacking:  21%|██▏       | 107/500 [02:52<10:52,  1.66s/it, loss=1968.0000, t=984]
Attacking:  22%|██▏       | 108/500 [02:53<10:44,  1.64s/it, loss=1968.0000, t=984]
Attacking:  22%|██▏       | 108/500 [02:54<10:44,  1.64s/it, loss=1952.0000, t=928]
Attacking:  22%|██▏       | 109/500 [02:55<10:50,  1.66s/it, loss=1952.0000, t=928]
Attacking:  22%|██▏       | 109/500 [02:56<10:50,  1.66s/it, loss=1952.0000, t=940]
Attacking:  22%|██▏       | 110/500 [02:57<10:26,  1.61s/it, loss=1952.0000, t=940]
Attacking:  22%|██▏       | 110/500 [02:57<10:26,  1.61s/it, loss=1960.0000, t=952]
Attacking:  22%|██▏       | 111/500 [02:58<10:10,  1.57s/it, loss=1960.0000, t=952]
Attacking:  22%|██▏       | 111/500 [02:59<10:10,  1.57s/it, loss=1928.0000, t=900]
Attacking:  22%|██▏       | 112/500 [03:00<10:27,  1.62s/it, loss=1928.0000, t=900]
Attacking:  22%|██▏       | 112/500 [03:01<10:27,  1.62s/it, loss=2000.0000, t=1e+3]
Attacking:  23%|██▎       | 113/500 [03:01<10:37,  1.65s/it, loss=2000.0000, t=1e+3]
Attacking:  23%|██▎       | 113/500 [03:02<10:37,  1.65s/it, loss=1944.0000, t=928] 
Attacking:  23%|██▎       | 114/500 [03:03<10:34,  1.64s/it, loss=1944.0000, t=928]
Attacking:  23%|██▎       | 114/500 [03:04<10:34,  1.64s/it, loss=1952.0000, t=940]
Attacking:  23%|██▎       | 115/500 [03:05<10:43,  1.67s/it, loss=1952.0000, t=940]
Attacking:  23%|██▎       | 115/500 [03:06<10:43,  1.67s/it, loss=1952.0000, t=952]
Attacking:  23%|██▎       | 116/500 [03:06<10:39,  1.67s/it, loss=1952.0000, t=952]
Attacking:  23%|██▎       | 116/500 [03:07<10:39,  1.67s/it, loss=2000.0000, t=1e+3]
Attacking:  23%|██▎       | 117/500 [03:08<10:17,  1.61s/it, loss=2000.0000, t=1e+3]
Attacking:  23%|██▎       | 117/500 [03:09<10:17,  1.61s/it, loss=1992.0000, t=1e+3]
Attacking:  24%|██▎       | 118/500 [03:09<09:56,  1.56s/it, loss=1992.0000, t=1e+3]
Attacking:  24%|██▎       | 118/500 [03:10<09:56,  1.56s/it, loss=1952.0000, t=940] 
Attacking:  24%|██▍       | 119/500 [03:11<09:48,  1.54s/it, loss=1952.0000, t=940]
Attacking:  24%|██▍       | 119/500 [03:12<09:48,  1.54s/it, loss=1952.0000, t=952]
Attacking:  24%|██▍       | 120/500 [03:13<10:11,  1.61s/it, loss=1952.0000, t=952]
Attacking:  24%|██▍       | 120/500 [03:13<10:11,  1.61s/it, loss=1960.0000, t=992]
Attacking:  24%|██▍       | 121/500 [03:14<09:51,  1.56s/it, loss=1960.0000, t=992]
Attacking:  24%|██▍       | 121/500 [03:15<09:51,  1.56s/it, loss=1984.0000, t=972]
Attacking:  24%|██▍       | 122/500 [03:16<09:33,  1.52s/it, loss=1984.0000, t=972]
Attacking:  24%|██▍       | 122/500 [03:16<09:33,  1.52s/it, loss=1984.0000, t=1e+3]
Attacking:  25%|██▍       | 123/500 [03:17<09:24,  1.50s/it, loss=1984.0000, t=1e+3]
Attacking:  25%|██▍       | 123/500 [03:18<09:24,  1.50s/it, loss=1936.0000, t=928] 
Attacking:  25%|██▍       | 124/500 [03:19<09:36,  1.53s/it, loss=1936.0000, t=928]
Attacking:  25%|██▍       | 124/500 [03:19<09:36,  1.53s/it, loss=1984.0000, t=1e+3]
Attacking:  25%|██▌       | 125/500 [03:20<09:38,  1.54s/it, loss=1984.0000, t=1e+3]
Attacking:  25%|██▌       | 125/500 [03:21<09:38,  1.54s/it, loss=1936.0000, t=928] 
Attacking:  25%|██▌       | 126/500 [03:22<09:40,  1.55s/it, loss=1936.0000, t=928]
Attacking:  25%|██▌       | 126/500 [03:23<09:40,  1.55s/it, loss=1976.0000, t=964]
Attacking:  25%|██▌       | 127/500 [03:23<09:48,  1.58s/it, loss=1976.0000, t=964]
Attacking:  25%|██▌       | 127/500 [03:24<09:48,  1.58s/it, loss=1920.0000, t=912]
Attacking:  26%|██▌       | 128/500 [03:25<09:52,  1.59s/it, loss=1920.0000, t=912]
Attacking:  26%|██▌       | 128/500 [03:26<09:52,  1.59s/it, loss=1936.0000, t=928]
Attacking:  26%|██▌       | 129/500 [03:27<09:56,  1.61s/it, loss=1936.0000, t=928]
Attacking:  26%|██▌       | 129/500 [03:27<09:56,  1.61s/it, loss=1936.0000, t=940]
Attacking:  26%|██▌       | 130/500 [03:28<10:04,  1.63s/it, loss=1936.0000, t=940]
Attacking:  26%|██▌       | 130/500 [03:29<10:04,  1.63s/it, loss=1952.0000, t=952]
Attacking:  26%|██▌       | 131/500 [03:30<09:56,  1.62s/it, loss=1952.0000, t=952]
Attacking:  26%|██▌       | 131/500 [03:31<09:56,  1.62s/it, loss=1920.0000, t=900]
Attacking:  26%|██▋       | 132/500 [03:32<09:56,  1.62s/it, loss=1920.0000, t=900]
Attacking:  26%|██▋       | 132/500 [03:32<09:56,  1.62s/it, loss=1968.0000, t=964]
Attacking:  27%|██▋       | 133/500 [03:33<09:57,  1.63s/it, loss=1968.0000, t=964]
Attacking:  27%|██▋       | 133/500 [03:34<09:57,  1.63s/it, loss=1968.0000, t=964]
Attacking:  27%|██▋       | 134/500 [03:35<10:00,  1.64s/it, loss=1968.0000, t=964]
Attacking:  27%|██▋       | 134/500 [03:36<10:00,  1.64s/it, loss=1912.0000, t=900]
Attacking:  27%|██▋       | 135/500 [03:36<09:48,  1.61s/it, loss=1912.0000, t=900]
Attacking:  27%|██▋       | 135/500 [03:37<09:48,  1.61s/it, loss=1960.0000, t=992]
Attacking:  27%|██▋       | 136/500 [03:38<09:57,  1.64s/it, loss=1960.0000, t=992]
Attacking:  27%|██▋       | 136/500 [03:39<09:57,  1.64s/it, loss=1920.0000, t=900]
Attacking:  27%|██▋       | 137/500 [03:40<09:54,  1.64s/it, loss=1920.0000, t=900]
Attacking:  27%|██▋       | 137/500 [03:41<09:54,  1.64s/it, loss=1920.0000, t=912]
Attacking:  28%|██▊       | 138/500 [03:41<09:59,  1.66s/it, loss=1920.0000, t=912]
Attacking:  28%|██▊       | 138/500 [03:42<09:59,  1.66s/it, loss=1960.0000, t=992]
Attacking:  28%|██▊       | 139/500 [03:43<09:59,  1.66s/it, loss=1960.0000, t=992]
Attacking:  28%|██▊       | 139/500 [03:44<09:59,  1.66s/it, loss=1928.0000, t=912]
Attacking:  28%|██▊       | 140/500 [03:45<09:54,  1.65s/it, loss=1928.0000, t=912]
Attacking:  28%|██▊       | 140/500 [03:45<09:54,  1.65s/it, loss=1936.0000, t=940]
Attacking:  28%|██▊       | 141/500 [03:46<09:40,  1.62s/it, loss=1936.0000, t=940]
Attacking:  28%|██▊       | 141/500 [03:47<09:40,  1.62s/it, loss=1984.0000, t=1e+3]
Attacking:  28%|██▊       | 142/500 [03:48<09:31,  1.60s/it, loss=1984.0000, t=1e+3]
Attacking:  28%|██▊       | 142/500 [03:49<09:31,  1.60s/it, loss=1968.0000, t=972] 
Attacking:  29%|██▊       | 143/500 [03:49<09:27,  1.59s/it, loss=1968.0000, t=972]
Attacking:  29%|██▊       | 143/500 [03:50<09:27,  1.59s/it, loss=1928.0000, t=912]
Attacking:  29%|██▉       | 144/500 [03:51<09:22,  1.58s/it, loss=1928.0000, t=912]
Attacking:  29%|██▉       | 144/500 [03:52<09:22,  1.58s/it, loss=1912.0000, t=900]
Attacking:  29%|██▉       | 145/500 [03:53<09:18,  1.57s/it, loss=1912.0000, t=900]
Attacking:  29%|██▉       | 145/500 [03:53<09:18,  1.57s/it, loss=1960.0000, t=984]
Attacking:  29%|██▉       | 146/500 [03:54<09:13,  1.56s/it, loss=1960.0000, t=984]
Attacking:  29%|██▉       | 146/500 [03:55<09:13,  1.56s/it, loss=1952.0000, t=952]
Attacking:  29%|██▉       | 147/500 [03:56<09:06,  1.55s/it, loss=1952.0000, t=952]
Attacking:  29%|██▉       | 147/500 [03:56<09:06,  1.55s/it, loss=1960.0000, t=984]
Attacking:  30%|██▉       | 148/500 [03:57<08:54,  1.52s/it, loss=1960.0000, t=984]
Attacking:  30%|██▉       | 148/500 [03:58<08:54,  1.52s/it, loss=1960.0000, t=984]
Attacking:  30%|██▉       | 149/500 [03:58<08:43,  1.49s/it, loss=1960.0000, t=984]
Attacking:  30%|██▉       | 149/500 [03:59<08:43,  1.49s/it, loss=1952.0000, t=952]
Attacking:  30%|███       | 150/500 [04:00<08:35,  1.47s/it, loss=1952.0000, t=952]
Attacking:  30%|███       | 150/500 [04:00<08:35,  1.47s/it, loss=1912.0000, t=900]
Attacking:  30%|███       | 151/500 [04:01<08:31,  1.47s/it, loss=1912.0000, t=900]
Attacking:  30%|███       | 151/500 [04:02<08:31,  1.47s/it, loss=1952.0000, t=952]
Attacking:  30%|███       | 152/500 [04:03<08:35,  1.48s/it, loss=1952.0000, t=952]
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Attacking:  31%|███       | 153/500 [04:04<08:31,  1.48s/it, loss=1920.0000, t=912]
Attacking:  31%|███       | 153/500 [04:05<08:31,  1.48s/it, loss=1968.0000, t=972]
Attacking:  31%|███       | 154/500 [04:06<08:24,  1.46s/it, loss=1968.0000, t=972]
Attacking:  31%|███       | 154/500 [04:07<08:24,  1.46s/it, loss=1936.0000, t=952]
Attacking:  31%|███       | 155/500 [04:07<08:47,  1.53s/it, loss=1936.0000, t=952]
Attacking:  31%|███       | 155/500 [04:08<08:47,  1.53s/it, loss=1952.0000, t=992]
Attacking:  31%|███       | 156/500 [04:09<08:39,  1.51s/it, loss=1952.0000, t=992]
Attacking:  31%|███       | 156/500 [04:09<08:39,  1.51s/it, loss=1912.0000, t=912]
Attacking:  31%|███▏      | 157/500 [04:10<08:31,  1.49s/it, loss=1912.0000, t=912]
Attacking:  31%|███▏      | 157/500 [04:11<08:31,  1.49s/it, loss=1936.0000, t=952]
Attacking:  32%|███▏      | 158/500 [04:12<08:42,  1.53s/it, loss=1936.0000, t=952]
Attacking:  32%|███▏      | 158/500 [04:13<08:42,  1.53s/it, loss=1960.0000, t=972]
Attacking:  32%|███▏      | 159/500 [04:14<08:54,  1.57s/it, loss=1960.0000, t=972]
Attacking:  32%|███▏      | 159/500 [04:14<08:54,  1.57s/it, loss=1976.0000, t=1e+3]
Attacking:  32%|███▏      | 160/500 [04:15<08:58,  1.58s/it, loss=1976.0000, t=1e+3]
Attacking:  32%|███▏      | 160/500 [04:16<08:58,  1.58s/it, loss=1960.0000, t=964] 
Attacking:  32%|███▏      | 161/500 [04:17<08:49,  1.56s/it, loss=1960.0000, t=964]
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Attacking:  32%|███▏      | 162/500 [04:19<08:46,  1.56s/it, loss=1968.0000, t=972]
Attacking:  33%|███▎      | 163/500 [04:20<08:38,  1.54s/it, loss=1968.0000, t=972]
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Attacking:  99%|█████████▉| 496/500 [12:52<00:06,  1.53s/it, loss=1896.0000, t=992]
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Attacking: 100%|█████████▉| 498/500 [12:55<00:03,  1.54s/it, loss=1848.0000, t=900]
Attacking: 100%|█████████▉| 499/500 [12:56<00:01,  1.57s/it, loss=1848.0000, t=900]
Attacking: 100%|█████████▉| 499/500 [12:56<00:01,  1.57s/it, loss=1912.0000, t=992]
Attacking: 100%|██████████| 500/500 [12:57<00:00,  1.59s/it, loss=1912.0000, t=992]
Attacking: 100%|██████████| 500/500 [12:57<00:00,  1.56s/it, loss=1912.0000, t=992]
+Max Diff: 0.501961
+Mean Diff: 0.270753
+Saved adversarial image to attacked/images/cow.jpg
+Saved loss curve to attacked/loss_curve/cow_loss.png
+[GPU 1] Stage 3/3: Test
+Loading models for testing cow...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for cow...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 59.45it/s]
+Saved video to attacked/videos/cow.mp4
+Saved frames to attacked/frames/cow
+[GPU 1] Finished cow.jpg
+======================================
+[GPU 1] Processing dance-jump.jpg (Image 13/50)
+======================================
+[GPU 1] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 1] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   7%|▋         | 33/500 [00:53<12:10,  1.56s/it, loss=2496.0000, t=984]
Attacking:   7%|▋         | 34/500 [00:54<12:16,  1.58s/it, loss=2496.0000, t=984]
Attacking:   7%|▋         | 34/500 [00:54<12:16,  1.58s/it, loss=2512.0000, t=984]
Attacking:   7%|▋         | 35/500 [00:55<12:15,  1.58s/it, loss=2512.0000, t=984]
Attacking:   7%|▋         | 35/500 [00:56<12:15,  1.58s/it, loss=2496.0000, t=964]
Attacking:   7%|▋         | 36/500 [00:57<12:33,  1.62s/it, loss=2496.0000, t=964]
Attacking:   7%|▋         | 36/500 [00:58<12:33,  1.62s/it, loss=2464.0000, t=928]
Attacking:   7%|▋         | 37/500 [00:59<12:38,  1.64s/it, loss=2464.0000, t=928]
Attacking:   7%|▋         | 37/500 [00:59<12:38,  1.64s/it, loss=2448.0000, t=900]
Attacking:   8%|▊         | 38/500 [01:00<12:55,  1.68s/it, loss=2448.0000, t=900]
Attacking:   8%|▊         | 38/500 [01:01<12:55,  1.68s/it, loss=2480.0000, t=952]
Attacking:   8%|▊         | 39/500 [01:02<12:53,  1.68s/it, loss=2480.0000, t=952]
Attacking:   8%|▊         | 39/500 [01:03<12:53,  1.68s/it, loss=2464.0000, t=972]
Attacking:   8%|▊         | 40/500 [01:04<12:56,  1.69s/it, loss=2464.0000, t=972]
Attacking:   8%|▊         | 40/500 [01:05<12:56,  1.69s/it, loss=2464.0000, t=912]
Attacking:   8%|▊         | 41/500 [01:05<12:50,  1.68s/it, loss=2464.0000, t=912]
Attacking:   8%|▊         | 41/500 [01:06<12:50,  1.68s/it, loss=2464.0000, t=952]
Attacking:   8%|▊         | 42/500 [01:07<12:57,  1.70s/it, loss=2464.0000, t=952]
Attacking:   8%|▊         | 42/500 [01:08<12:57,  1.70s/it, loss=2496.0000, t=972]
Attacking:   9%|▊         | 43/500 [01:09<13:07,  1.72s/it, loss=2496.0000, t=972]
Attacking:   9%|▊         | 43/500 [01:10<13:07,  1.72s/it, loss=2464.0000, t=972]
Attacking:   9%|▉         | 44/500 [01:11<12:57,  1.71s/it, loss=2464.0000, t=972]
Attacking:   9%|▉         | 44/500 [01:11<12:57,  1.71s/it, loss=2496.0000, t=984]
Attacking:   9%|▉         | 45/500 [01:12<13:02,  1.72s/it, loss=2496.0000, t=984]
Attacking:   9%|▉         | 45/500 [01:13<13:02,  1.72s/it, loss=2480.0000, t=964]
Attacking:   9%|▉         | 46/500 [01:14<12:53,  1.70s/it, loss=2480.0000, t=964]
Attacking:   9%|▉         | 46/500 [01:15<12:53,  1.70s/it, loss=2544.0000, t=1e+3]
Attacking:   9%|▉         | 47/500 [01:16<12:59,  1.72s/it, loss=2544.0000, t=1e+3]
Attacking:   9%|▉         | 47/500 [01:17<12:59,  1.72s/it, loss=2464.0000, t=952] 
Attacking:  10%|▉         | 48/500 [01:17<12:47,  1.70s/it, loss=2464.0000, t=952]
Attacking:  10%|▉         | 48/500 [01:18<12:47,  1.70s/it, loss=2416.0000, t=912]
Attacking:  10%|▉         | 49/500 [01:19<12:30,  1.66s/it, loss=2416.0000, t=912]
Attacking:  10%|▉         | 49/500 [01:20<12:30,  1.66s/it, loss=2432.0000, t=928]
Attacking:  10%|█         | 50/500 [01:21<12:31,  1.67s/it, loss=2432.0000, t=928]
Attacking:  10%|█         | 50/500 [01:21<12:31,  1.67s/it, loss=2448.0000, t=952]
Attacking:  10%|█         | 51/500 [01:22<12:22,  1.65s/it, loss=2448.0000, t=952]
Attacking:  10%|█         | 51/500 [01:23<12:22,  1.65s/it, loss=2496.0000, t=992]
Attacking:  10%|█         | 52/500 [01:24<12:02,  1.61s/it, loss=2496.0000, t=992]
Attacking:  10%|█         | 52/500 [01:25<12:02,  1.61s/it, loss=2432.0000, t=940]
Attacking:  11%|█         | 53/500 [01:25<11:56,  1.60s/it, loss=2432.0000, t=940]
Attacking:  11%|█         | 53/500 [01:26<11:56,  1.60s/it, loss=2448.0000, t=972]
Attacking:  11%|█         | 54/500 [01:27<11:34,  1.56s/it, loss=2448.0000, t=972]
Attacking:  11%|█         | 54/500 [01:27<11:34,  1.56s/it, loss=2416.0000, t=900]
Attacking:  11%|█         | 55/500 [01:28<11:23,  1.54s/it, loss=2416.0000, t=900]
Attacking:  11%|█         | 55/500 [01:29<11:23,  1.54s/it, loss=2432.0000, t=940]
Attacking:  11%|█         | 56/500 [01:30<11:16,  1.52s/it, loss=2432.0000, t=940]
Attacking:  11%|█         | 56/500 [01:30<11:16,  1.52s/it, loss=2432.0000, t=940]
Attacking:  11%|█▏        | 57/500 [01:31<11:11,  1.52s/it, loss=2432.0000, t=940]
Attacking:  11%|█▏        | 57/500 [01:32<11:11,  1.52s/it, loss=2464.0000, t=984]
Attacking:  12%|█▏        | 58/500 [01:33<10:58,  1.49s/it, loss=2464.0000, t=984]
Attacking:  12%|█▏        | 58/500 [01:33<10:58,  1.49s/it, loss=2448.0000, t=964]
Attacking:  12%|█▏        | 59/500 [01:34<11:02,  1.50s/it, loss=2448.0000, t=964]
Attacking:  12%|█▏        | 59/500 [01:35<11:02,  1.50s/it, loss=2432.0000, t=952]
Attacking:  12%|█▏        | 60/500 [01:36<10:48,  1.47s/it, loss=2432.0000, t=952]
Attacking:  12%|█▏        | 60/500 [01:36<10:48,  1.47s/it, loss=2400.0000, t=912]
Attacking:  12%|█▏        | 61/500 [01:37<11:02,  1.51s/it, loss=2400.0000, t=912]
Attacking:  12%|█▏        | 61/500 [01:38<11:02,  1.51s/it, loss=2496.0000, t=1e+3]
Attacking:  12%|█▏        | 62/500 [01:39<10:49,  1.48s/it, loss=2496.0000, t=1e+3]
Attacking:  12%|█▏        | 62/500 [01:39<10:49,  1.48s/it, loss=2432.0000, t=964] 
Attacking:  13%|█▎        | 63/500 [01:40<11:03,  1.52s/it, loss=2432.0000, t=964]
Attacking:  13%|█▎        | 63/500 [01:41<11:03,  1.52s/it, loss=2432.0000, t=972]
Attacking:  13%|█▎        | 64/500 [01:42<11:29,  1.58s/it, loss=2432.0000, t=972]
Attacking:  13%|█▎        | 64/500 [01:43<11:29,  1.58s/it, loss=2448.0000, t=984]
Attacking:  13%|█▎        | 65/500 [01:44<11:44,  1.62s/it, loss=2448.0000, t=984]
Attacking:  13%|█▎        | 65/500 [01:45<11:44,  1.62s/it, loss=2400.0000, t=928]
Attacking:  13%|█▎        | 66/500 [01:45<11:47,  1.63s/it, loss=2400.0000, t=928]
Attacking:  13%|█▎        | 66/500 [01:46<11:47,  1.63s/it, loss=2464.0000, t=992]
Attacking:  13%|█▎        | 67/500 [01:47<11:52,  1.65s/it, loss=2464.0000, t=992]
Attacking:  13%|█▎        | 67/500 [01:48<11:52,  1.65s/it, loss=2464.0000, t=1e+3]
Attacking:  14%|█▎        | 68/500 [01:49<11:47,  1.64s/it, loss=2464.0000, t=1e+3]
Attacking:  14%|█▎        | 68/500 [01:50<11:47,  1.64s/it, loss=2400.0000, t=940] 
Attacking:  14%|█▍        | 69/500 [01:51<12:06,  1.68s/it, loss=2400.0000, t=940]
Attacking:  14%|█▍        | 69/500 [01:51<12:06,  1.68s/it, loss=2464.0000, t=992]
Attacking:  14%|█▍        | 70/500 [01:52<12:32,  1.75s/it, loss=2464.0000, t=992]
Attacking:  14%|█▍        | 70/500 [01:53<12:32,  1.75s/it, loss=2416.0000, t=964]
Attacking:  14%|█▍        | 71/500 [01:54<12:45,  1.78s/it, loss=2416.0000, t=964]
Attacking:  14%|█▍        | 71/500 [01:55<12:45,  1.78s/it, loss=2368.0000, t=900]
Attacking:  14%|█▍        | 72/500 [01:56<12:05,  1.69s/it, loss=2368.0000, t=900]
Attacking:  14%|█▍        | 72/500 [01:56<12:05,  1.69s/it, loss=2368.0000, t=900]
Attacking:  15%|█▍        | 73/500 [01:57<11:49,  1.66s/it, loss=2368.0000, t=900]
Attacking:  15%|█▍        | 73/500 [01:58<11:49,  1.66s/it, loss=2432.0000, t=984]
Attacking:  15%|█▍        | 74/500 [01:59<11:25,  1.61s/it, loss=2432.0000, t=984]
Attacking:  15%|█▍        | 74/500 [01:59<11:25,  1.61s/it, loss=2400.0000, t=940]
Attacking:  15%|█▌        | 75/500 [02:00<11:11,  1.58s/it, loss=2400.0000, t=940]
Attacking:  15%|█▌        | 75/500 [02:01<11:11,  1.58s/it, loss=2368.0000, t=900]
Attacking:  15%|█▌        | 76/500 [02:02<11:16,  1.60s/it, loss=2368.0000, t=900]
Attacking:  15%|█▌        | 76/500 [02:03<11:16,  1.60s/it, loss=2432.0000, t=984]
Attacking:  15%|█▌        | 77/500 [02:04<11:29,  1.63s/it, loss=2432.0000, t=984]
Attacking:  15%|█▌        | 77/500 [02:05<11:29,  1.63s/it, loss=2384.0000, t=928]
Attacking:  16%|█▌        | 78/500 [02:06<12:10,  1.73s/it, loss=2384.0000, t=928]
Attacking:  16%|█▌        | 78/500 [02:06<12:10,  1.73s/it, loss=2368.0000, t=912]
Attacking:  16%|█▌        | 79/500 [02:07<11:49,  1.69s/it, loss=2368.0000, t=912]
Attacking:  16%|█▌        | 79/500 [02:08<11:49,  1.69s/it, loss=2400.0000, t=972]
Attacking:  16%|█▌        | 80/500 [02:09<11:35,  1.66s/it, loss=2400.0000, t=972]
Attacking:  16%|█▌        | 80/500 [02:10<11:35,  1.66s/it, loss=2400.0000, t=984]
Attacking:  16%|█▌        | 81/500 [02:10<11:24,  1.63s/it, loss=2400.0000, t=984]
Attacking:  16%|█▌        | 81/500 [02:11<11:24,  1.63s/it, loss=2384.0000, t=972]
Attacking:  16%|█▋        | 82/500 [02:12<11:12,  1.61s/it, loss=2384.0000, t=972]
Attacking:  16%|█▋        | 82/500 [02:13<11:12,  1.61s/it, loss=2400.0000, t=952]
Attacking:  17%|█▋        | 83/500 [02:13<10:52,  1.57s/it, loss=2400.0000, t=952]
Attacking:  17%|█▋        | 83/500 [02:14<10:52,  1.57s/it, loss=2368.0000, t=900]
Attacking:  17%|█▋        | 84/500 [02:15<10:39,  1.54s/it, loss=2368.0000, t=900]
Attacking:  17%|█▋        | 84/500 [02:15<10:39,  1.54s/it, loss=2400.0000, t=964]
Attacking:  17%|█▋        | 85/500 [02:16<10:23,  1.50s/it, loss=2400.0000, t=964]
Attacking:  17%|█▋        | 85/500 [02:17<10:23,  1.50s/it, loss=2368.0000, t=928]
Attacking:  17%|█▋        | 86/500 [02:18<10:12,  1.48s/it, loss=2368.0000, t=928]
Attacking:  17%|█▋        | 86/500 [02:18<10:12,  1.48s/it, loss=2368.0000, t=928]
Attacking:  17%|█▋        | 87/500 [02:19<10:06,  1.47s/it, loss=2368.0000, t=928]
Attacking:  17%|█▋        | 87/500 [02:20<10:06,  1.47s/it, loss=2384.0000, t=952]
Attacking:  18%|█▊        | 88/500 [02:21<10:20,  1.51s/it, loss=2384.0000, t=952]
Attacking:  18%|█▊        | 88/500 [02:21<10:20,  1.51s/it, loss=2448.0000, t=992]
Attacking:  18%|█▊        | 89/500 [02:22<10:25,  1.52s/it, loss=2448.0000, t=992]
Attacking:  18%|█▊        | 89/500 [02:23<10:25,  1.52s/it, loss=2352.0000, t=900]
Attacking:  18%|█▊        | 90/500 [02:24<10:48,  1.58s/it, loss=2352.0000, t=900]
Attacking:  18%|█▊        | 90/500 [02:25<10:48,  1.58s/it, loss=2448.0000, t=992]
Attacking:  18%|█▊        | 91/500 [02:26<11:04,  1.63s/it, loss=2448.0000, t=992]
Attacking:  18%|█▊        | 91/500 [02:27<11:04,  1.63s/it, loss=2448.0000, t=1e+3]
Attacking:  18%|█▊        | 92/500 [02:27<11:12,  1.65s/it, loss=2448.0000, t=1e+3]
Attacking:  18%|█▊        | 92/500 [02:28<11:12,  1.65s/it, loss=2400.0000, t=972] 
Attacking:  19%|█▊        | 93/500 [02:29<11:16,  1.66s/it, loss=2400.0000, t=972]
Attacking:  19%|█▊        | 93/500 [02:30<11:16,  1.66s/it, loss=2384.0000, t=972]
Attacking:  19%|█▉        | 94/500 [02:31<11:38,  1.72s/it, loss=2384.0000, t=972]
Attacking:  19%|█▉        | 94/500 [02:32<11:38,  1.72s/it, loss=2432.0000, t=992]
Attacking:  19%|█▉        | 95/500 [02:33<11:43,  1.74s/it, loss=2432.0000, t=992]
Attacking:  19%|█▉        | 95/500 [02:34<11:43,  1.74s/it, loss=2432.0000, t=992]
Attacking:  19%|█▉        | 96/500 [02:34<11:35,  1.72s/it, loss=2432.0000, t=992]
Attacking:  19%|█▉        | 96/500 [02:35<11:35,  1.72s/it, loss=2384.0000, t=940]
Attacking:  19%|█▉        | 97/500 [02:36<11:31,  1.71s/it, loss=2384.0000, t=940]
Attacking:  19%|█▉        | 97/500 [02:37<11:31,  1.71s/it, loss=2368.0000, t=912]
Attacking:  20%|█▉        | 98/500 [02:38<11:28,  1.71s/it, loss=2368.0000, t=912]
Attacking:  20%|█▉        | 98/500 [02:39<11:28,  1.71s/it, loss=2368.0000, t=928]
Attacking:  20%|█▉        | 99/500 [02:40<11:26,  1.71s/it, loss=2368.0000, t=928]
Attacking:  20%|█▉        | 99/500 [02:40<11:26,  1.71s/it, loss=2352.0000, t=900]
Attacking:  20%|██        | 100/500 [02:41<11:27,  1.72s/it, loss=2352.0000, t=900]
Attacking:  20%|██        | 100/500 [02:42<11:27,  1.72s/it, loss=2400.0000, t=964]
Attacking:  20%|██        | 101/500 [02:43<11:42,  1.76s/it, loss=2400.0000, t=964]
Attacking:  20%|██        | 101/500 [02:44<11:42,  1.76s/it, loss=2464.0000, t=1e+3]
Attacking:  20%|██        | 102/500 [02:45<11:25,  1.72s/it, loss=2464.0000, t=1e+3]
Attacking:  20%|██        | 102/500 [02:46<11:25,  1.72s/it, loss=2384.0000, t=952] 
Attacking:  21%|██        | 103/500 [02:47<11:18,  1.71s/it, loss=2384.0000, t=952]
Attacking:  21%|██        | 103/500 [02:47<11:18,  1.71s/it, loss=2432.0000, t=992]
Attacking:  21%|██        | 104/500 [02:48<11:04,  1.68s/it, loss=2432.0000, t=992]
Attacking:  21%|██        | 104/500 [02:49<11:04,  1.68s/it, loss=2368.0000, t=928]
Attacking:  21%|██        | 105/500 [02:50<10:47,  1.64s/it, loss=2368.0000, t=928]
Attacking:  21%|██        | 105/500 [02:50<10:47,  1.64s/it, loss=2352.0000, t=928]
Attacking:  21%|██        | 106/500 [02:51<10:33,  1.61s/it, loss=2352.0000, t=928]
Attacking:  21%|██        | 106/500 [02:52<10:33,  1.61s/it, loss=2336.0000, t=900]
Attacking:  21%|██▏       | 107/500 [02:53<10:21,  1.58s/it, loss=2336.0000, t=900]
Attacking:  21%|██▏       | 107/500 [02:53<10:21,  1.58s/it, loss=2384.0000, t=972]
Attacking:  22%|██▏       | 108/500 [02:54<10:09,  1.55s/it, loss=2384.0000, t=972]
Attacking:  22%|██▏       | 108/500 [02:55<10:09,  1.55s/it, loss=2368.0000, t=952]
Attacking:  22%|██▏       | 109/500 [02:56<10:11,  1.57s/it, loss=2368.0000, t=952]
Attacking:  22%|██▏       | 109/500 [02:57<10:11,  1.57s/it, loss=2368.0000, t=952]
Attacking:  22%|██▏       | 110/500 [02:57<10:24,  1.60s/it, loss=2368.0000, t=952]
Attacking:  22%|██▏       | 110/500 [02:58<10:24,  1.60s/it, loss=2432.0000, t=1e+3]
Attacking:  22%|██▏       | 111/500 [02:59<10:24,  1.60s/it, loss=2432.0000, t=1e+3]
Attacking:  22%|██▏       | 111/500 [03:00<10:24,  1.60s/it, loss=2352.0000, t=940] 
Attacking:  22%|██▏       | 112/500 [03:01<10:03,  1.55s/it, loss=2352.0000, t=940]
Attacking:  22%|██▏       | 112/500 [03:01<10:03,  1.55s/it, loss=2352.0000, t=928]
Attacking:  23%|██▎       | 113/500 [03:02<09:48,  1.52s/it, loss=2352.0000, t=928]
Attacking:  23%|██▎       | 113/500 [03:03<09:48,  1.52s/it, loss=2384.0000, t=964]
Attacking:  23%|██▎       | 114/500 [03:03<09:36,  1.49s/it, loss=2384.0000, t=964]
Attacking:  23%|██▎       | 114/500 [03:04<09:36,  1.49s/it, loss=2352.0000, t=940]
Attacking:  23%|██▎       | 115/500 [03:05<09:25,  1.47s/it, loss=2352.0000, t=940]
Attacking:  23%|██▎       | 115/500 [03:05<09:25,  1.47s/it, loss=2336.0000, t=912]
Attacking:  23%|██▎       | 116/500 [03:06<09:19,  1.46s/it, loss=2336.0000, t=912]
Attacking:  23%|██▎       | 116/500 [03:07<09:19,  1.46s/it, loss=2352.0000, t=928]
Attacking:  23%|██▎       | 117/500 [03:08<09:31,  1.49s/it, loss=2352.0000, t=928]
Attacking:  23%|██▎       | 117/500 [03:09<09:31,  1.49s/it, loss=2432.0000, t=992]
Attacking:  24%|██▎       | 118/500 [03:09<09:46,  1.54s/it, loss=2432.0000, t=992]
Attacking:  24%|██▎       | 118/500 [03:10<09:46,  1.54s/it, loss=2336.0000, t=900]
Attacking:  24%|██▍       | 119/500 [03:11<09:51,  1.55s/it, loss=2336.0000, t=900]
Attacking:  24%|██▍       | 119/500 [03:12<09:51,  1.55s/it, loss=2384.0000, t=964]
Attacking:  24%|██▍       | 120/500 [03:13<10:13,  1.61s/it, loss=2384.0000, t=964]
Attacking:  24%|██▍       | 120/500 [03:14<10:13,  1.61s/it, loss=2384.0000, t=984]
Attacking:  24%|██▍       | 121/500 [03:15<10:28,  1.66s/it, loss=2384.0000, t=984]
Attacking:  24%|██▍       | 121/500 [03:15<10:28,  1.66s/it, loss=2336.0000, t=912]
Attacking:  24%|██▍       | 122/500 [03:16<10:28,  1.66s/it, loss=2336.0000, t=912]
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Attacking: 100%|█████████▉| 499/500 [12:59<00:01,  1.64s/it, loss=2320.0000, t=984]
Attacking: 100%|██████████| 500/500 [13:00<00:00,  1.66s/it, loss=2320.0000, t=984]
Attacking: 100%|██████████| 500/500 [13:00<00:00,  1.56s/it, loss=2320.0000, t=984]
+Max Diff: 0.501961
+Mean Diff: 0.260763
+Saved adversarial image to attacked/images/dance-jump.jpg
+Saved loss curve to attacked/loss_curve/dance-jump_loss.png
+[GPU 1] Stage 3/3: Test
+Loading models for testing dance-jump...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for dance-jump...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 96.90it/s]
+Saved video to attacked/videos/dance-jump.mp4
+Saved frames to attacked/frames/dance-jump
+[GPU 1] Finished dance-jump.jpg
+[GPU 1] All assigned tasks completed.
diff --git a/experiments/cfg3_eps64/logs/gpu_2.log b/experiments/cfg3_eps64/logs/gpu_2.log
new file mode 100644
index 0000000000000000000000000000000000000000..a115c548e1a0a766b055eabc64b5b0b9c3632594
--- /dev/null
+++ b/experiments/cfg3_eps64/logs/gpu_2.log
@@ -0,0 +1,513 @@
+[GPU 2] Starting work on images 14 to 20
+======================================
+[GPU 2] Processing dance-twirl.jpg (Image 14/50)
+======================================
+[GPU 2] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 2] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  24%|██▍       | 122/500 [02:59<10:05,  1.60s/it, loss=1744.0000, t=972]
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Attacking:  25%|██▌       | 127/500 [03:07<09:58,  1.60s/it, loss=1784.0000, t=1e+3]
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Attacking:  99%|█████████▉| 496/500 [13:04<00:06,  1.56s/it, loss=1696.0000, t=984]
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Attacking:  99%|█████████▉| 497/500 [13:06<00:04,  1.59s/it, loss=1720.0000, t=992]
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Attacking: 100%|█████████▉| 498/500 [13:08<00:03,  1.61s/it, loss=1656.0000, t=928]
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Attacking: 100%|█████████▉| 499/500 [13:09<00:01,  1.61s/it, loss=1672.0000, t=972]
Attacking: 100%|██████████| 500/500 [13:10<00:00,  1.60s/it, loss=1672.0000, t=972]
Attacking: 100%|██████████| 500/500 [13:10<00:00,  1.58s/it, loss=1672.0000, t=972]
+Max Diff: 0.501961
+Mean Diff: 0.241651
+Saved adversarial image to attacked/images/dance-twirl.jpg
+Saved loss curve to attacked/loss_curve/dance-twirl_loss.png
+[GPU 2] Stage 3/3: Test
+Loading models for testing dance-twirl...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for dance-twirl...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 38.31it/s]
+Saved video to attacked/videos/dance-twirl.mp4
+Saved frames to attacked/frames/dance-twirl
+[GPU 2] Finished dance-twirl.jpg
+======================================
+[GPU 2] Processing deer.jpg (Image 15/50)
+======================================
+[GPU 2] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 2] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   6%|▌         | 29/500 [00:49<12:47,  1.63s/it, loss=2496.0000, t=984]
Attacking:   6%|▌         | 30/500 [00:49<12:55,  1.65s/it, loss=2496.0000, t=984]
Attacking:   6%|▌         | 30/500 [00:50<12:55,  1.65s/it, loss=2336.0000, t=900]
Attacking:   6%|▌         | 31/500 [00:51<13:13,  1.69s/it, loss=2336.0000, t=900]
Attacking:   6%|▌         | 31/500 [00:52<13:13,  1.69s/it, loss=2320.0000, t=900]
Attacking:   6%|▋         | 32/500 [00:53<12:45,  1.64s/it, loss=2320.0000, t=900]
Attacking:   6%|▋         | 32/500 [00:53<12:45,  1.64s/it, loss=2384.0000, t=952]
Attacking:   7%|▋         | 33/500 [00:54<12:50,  1.65s/it, loss=2384.0000, t=952]
Attacking:   7%|▋         | 33/500 [00:55<12:50,  1.65s/it, loss=2352.0000, t=928]
Attacking:   7%|▋         | 34/500 [00:56<12:48,  1.65s/it, loss=2352.0000, t=928]
Attacking:   7%|▋         | 34/500 [00:57<12:48,  1.65s/it, loss=2432.0000, t=972]
Attacking:   7%|▋         | 35/500 [00:58<12:54,  1.66s/it, loss=2432.0000, t=972]
Attacking:   7%|▋         | 35/500 [00:59<12:54,  1.66s/it, loss=2432.0000, t=972]
Attacking:   7%|▋         | 36/500 [00:59<12:48,  1.66s/it, loss=2432.0000, t=972]
Attacking:   7%|▋         | 36/500 [01:00<12:48,  1.66s/it, loss=2400.0000, t=964]
Attacking:   7%|▋         | 37/500 [01:01<12:47,  1.66s/it, loss=2400.0000, t=964]
Attacking:   7%|▋         | 37/500 [01:02<12:47,  1.66s/it, loss=2336.0000, t=928]
Attacking:   8%|▊         | 38/500 [01:03<12:46,  1.66s/it, loss=2336.0000, t=928]
Attacking:   8%|▊         | 38/500 [01:04<12:46,  1.66s/it, loss=2480.0000, t=984]
Attacking:   8%|▊         | 39/500 [01:04<12:42,  1.65s/it, loss=2480.0000, t=984]
Attacking:   8%|▊         | 39/500 [01:05<12:42,  1.65s/it, loss=2464.0000, t=984]
Attacking:   8%|▊         | 40/500 [01:06<12:26,  1.62s/it, loss=2464.0000, t=984]
Attacking:   8%|▊         | 40/500 [01:07<12:26,  1.62s/it, loss=2464.0000, t=1e+3]
Attacking:   8%|▊         | 41/500 [01:07<12:18,  1.61s/it, loss=2464.0000, t=1e+3]
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Attacking:   8%|▊         | 42/500 [01:09<12:12,  1.60s/it, loss=2368.0000, t=952]
Attacking:   8%|▊         | 42/500 [01:10<12:12,  1.60s/it, loss=2336.0000, t=940]
Attacking:   9%|▊         | 43/500 [01:11<12:07,  1.59s/it, loss=2336.0000, t=940]
Attacking:   9%|▊         | 43/500 [01:11<12:07,  1.59s/it, loss=2368.0000, t=952]
Attacking:   9%|▉         | 44/500 [01:12<12:06,  1.59s/it, loss=2368.0000, t=952]
Attacking:   9%|▉         | 44/500 [01:13<12:06,  1.59s/it, loss=2496.0000, t=1e+3]
Attacking:   9%|▉         | 45/500 [01:14<12:15,  1.62s/it, loss=2496.0000, t=1e+3]
Attacking:   9%|▉         | 45/500 [01:15<12:15,  1.62s/it, loss=2336.0000, t=940] 
Attacking:   9%|▉         | 46/500 [01:16<12:34,  1.66s/it, loss=2336.0000, t=940]
Attacking:   9%|▉         | 46/500 [01:16<12:34,  1.66s/it, loss=2352.0000, t=952]
Attacking:   9%|▉         | 47/500 [01:17<12:27,  1.65s/it, loss=2352.0000, t=952]
Attacking:   9%|▉         | 47/500 [01:18<12:27,  1.65s/it, loss=2448.0000, t=1e+3]
Attacking:  10%|▉         | 48/500 [01:19<12:06,  1.61s/it, loss=2448.0000, t=1e+3]
Attacking:  10%|▉         | 48/500 [01:20<12:06,  1.61s/it, loss=2400.0000, t=972] 
Attacking:  10%|▉         | 49/500 [01:20<12:18,  1.64s/it, loss=2400.0000, t=972]
Attacking:  10%|▉         | 49/500 [01:21<12:18,  1.64s/it, loss=2496.0000, t=992]
Attacking:  10%|█         | 50/500 [01:22<12:10,  1.62s/it, loss=2496.0000, t=992]
Attacking:  10%|█         | 50/500 [01:23<12:10,  1.62s/it, loss=2320.0000, t=900]
Attacking:  10%|█         | 51/500 [01:24<11:54,  1.59s/it, loss=2320.0000, t=900]
Attacking:  10%|█         | 51/500 [01:24<11:54,  1.59s/it, loss=2320.0000, t=940]
Attacking:  10%|█         | 52/500 [01:25<11:56,  1.60s/it, loss=2320.0000, t=940]
Attacking:  10%|█         | 52/500 [01:26<11:56,  1.60s/it, loss=2320.0000, t=940]
Attacking:  11%|█         | 53/500 [01:27<11:53,  1.60s/it, loss=2320.0000, t=940]
Attacking:  11%|█         | 53/500 [01:28<11:53,  1.60s/it, loss=2272.0000, t=900]
Attacking:  11%|█         | 54/500 [01:29<12:05,  1.63s/it, loss=2272.0000, t=900]
Attacking:  11%|█         | 54/500 [01:29<12:05,  1.63s/it, loss=2432.0000, t=1e+3]
Attacking:  11%|█         | 55/500 [01:30<12:09,  1.64s/it, loss=2432.0000, t=1e+3]
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Attacking:  11%|█         | 56/500 [01:32<12:04,  1.63s/it, loss=2272.0000, t=900]
Attacking:  11%|█         | 56/500 [01:33<12:04,  1.63s/it, loss=2320.0000, t=940]
Attacking:  11%|█▏        | 57/500 [01:33<11:58,  1.62s/it, loss=2320.0000, t=940]
Attacking:  11%|█▏        | 57/500 [01:34<11:58,  1.62s/it, loss=2272.0000, t=900]
Attacking:  12%|█▏        | 58/500 [01:35<12:07,  1.64s/it, loss=2272.0000, t=900]
Attacking:  12%|█▏        | 58/500 [01:36<12:07,  1.64s/it, loss=2384.0000, t=972]
Attacking:  12%|█▏        | 59/500 [01:37<12:32,  1.71s/it, loss=2384.0000, t=972]
Attacking:  12%|█▏        | 59/500 [01:38<12:32,  1.71s/it, loss=2368.0000, t=964]
Attacking:  12%|█▏        | 60/500 [01:39<12:17,  1.68s/it, loss=2368.0000, t=964]
Attacking:  12%|█▏        | 60/500 [01:39<12:17,  1.68s/it, loss=2304.0000, t=952]
Attacking:  12%|█▏        | 61/500 [01:40<12:11,  1.67s/it, loss=2304.0000, t=952]
Attacking:  12%|█▏        | 61/500 [01:41<12:11,  1.67s/it, loss=2272.0000, t=900]
Attacking:  12%|█▏        | 62/500 [01:42<12:10,  1.67s/it, loss=2272.0000, t=900]
Attacking:  12%|█▏        | 62/500 [01:43<12:10,  1.67s/it, loss=2320.0000, t=952]
Attacking:  13%|█▎        | 63/500 [01:43<11:59,  1.65s/it, loss=2320.0000, t=952]
Attacking:  13%|█▎        | 63/500 [01:44<11:59,  1.65s/it, loss=2272.0000, t=912]
Attacking:  13%|█▎        | 64/500 [01:45<11:42,  1.61s/it, loss=2272.0000, t=912]
Attacking:  13%|█▎        | 64/500 [01:46<11:42,  1.61s/it, loss=2480.0000, t=992]
Attacking:  13%|█▎        | 65/500 [01:47<11:43,  1.62s/it, loss=2480.0000, t=992]
Attacking:  13%|█▎        | 65/500 [01:47<11:43,  1.62s/it, loss=2272.0000, t=900]
Attacking:  13%|█▎        | 66/500 [01:48<11:45,  1.63s/it, loss=2272.0000, t=900]
Attacking:  13%|█▎        | 66/500 [01:49<11:45,  1.63s/it, loss=2368.0000, t=972]
Attacking:  13%|█▎        | 67/500 [01:50<11:31,  1.60s/it, loss=2368.0000, t=972]
Attacking:  13%|█▎        | 67/500 [01:50<11:31,  1.60s/it, loss=2304.0000, t=952]
Attacking:  14%|█▎        | 68/500 [01:51<11:17,  1.57s/it, loss=2304.0000, t=952]
Attacking:  14%|█▎        | 68/500 [01:52<11:17,  1.57s/it, loss=2464.0000, t=992]
Attacking:  14%|█▍        | 69/500 [01:53<11:33,  1.61s/it, loss=2464.0000, t=992]
Attacking:  14%|█▍        | 69/500 [01:54<11:33,  1.61s/it, loss=2400.0000, t=984]
Attacking:  14%|█▍        | 70/500 [01:55<11:33,  1.61s/it, loss=2400.0000, t=984]
Attacking:  14%|█▍        | 70/500 [01:55<11:33,  1.61s/it, loss=2368.0000, t=972]
Attacking:  14%|█▍        | 71/500 [01:56<11:42,  1.64s/it, loss=2368.0000, t=972]
Attacking:  14%|█▍        | 71/500 [01:57<11:42,  1.64s/it, loss=2336.0000, t=964]
Attacking:  14%|█▍        | 72/500 [01:58<11:54,  1.67s/it, loss=2336.0000, t=964]
Attacking:  14%|█▍        | 72/500 [01:59<11:54,  1.67s/it, loss=2256.0000, t=912]
Attacking:  15%|█▍        | 73/500 [02:00<11:39,  1.64s/it, loss=2256.0000, t=912]
Attacking:  15%|█▍        | 73/500 [02:00<11:39,  1.64s/it, loss=2256.0000, t=912]
Attacking:  15%|█▍        | 74/500 [02:01<11:57,  1.68s/it, loss=2256.0000, t=912]
Attacking:  15%|█▍        | 74/500 [02:02<11:57,  1.68s/it, loss=2272.0000, t=940]
Attacking:  15%|█▌        | 75/500 [02:03<12:02,  1.70s/it, loss=2272.0000, t=940]
Attacking:  15%|█▌        | 75/500 [02:04<12:02,  1.70s/it, loss=2272.0000, t=940]
Attacking:  15%|█▌        | 76/500 [02:05<11:56,  1.69s/it, loss=2272.0000, t=940]
Attacking:  15%|█▌        | 76/500 [02:06<11:56,  1.69s/it, loss=2256.0000, t=928]
Attacking:  15%|█▌        | 77/500 [02:06<11:48,  1.68s/it, loss=2256.0000, t=928]
Attacking:  15%|█▌        | 77/500 [02:07<11:48,  1.68s/it, loss=2272.0000, t=928]
Attacking:  16%|█▌        | 78/500 [02:08<11:48,  1.68s/it, loss=2272.0000, t=928]
Attacking:  16%|█▌        | 78/500 [02:09<11:48,  1.68s/it, loss=2400.0000, t=984]
Attacking:  16%|█▌        | 79/500 [02:10<11:53,  1.70s/it, loss=2400.0000, t=984]
Attacking:  16%|█▌        | 79/500 [02:11<11:53,  1.70s/it, loss=2240.0000, t=900]
Attacking:  16%|█▌        | 80/500 [02:11<11:31,  1.65s/it, loss=2240.0000, t=900]
Attacking:  16%|█▌        | 80/500 [02:12<11:31,  1.65s/it, loss=2240.0000, t=912]
Attacking:  16%|█▌        | 81/500 [02:13<11:50,  1.70s/it, loss=2240.0000, t=912]
Attacking:  16%|█▌        | 81/500 [02:14<11:50,  1.70s/it, loss=2272.0000, t=940]
Attacking:  16%|█▋        | 82/500 [02:15<12:15,  1.76s/it, loss=2272.0000, t=940]
Attacking:  16%|█▋        | 82/500 [02:16<12:15,  1.76s/it, loss=2464.0000, t=992]
Attacking:  17%|█▋        | 83/500 [02:17<12:00,  1.73s/it, loss=2464.0000, t=992]
Attacking:  17%|█▋        | 83/500 [02:17<12:00,  1.73s/it, loss=2272.0000, t=928]
Attacking:  17%|█▋        | 84/500 [02:18<11:36,  1.67s/it, loss=2272.0000, t=928]
Attacking:  17%|█▋        | 84/500 [02:19<11:36,  1.67s/it, loss=2224.0000, t=900]
Attacking:  17%|█▋        | 85/500 [02:20<11:24,  1.65s/it, loss=2224.0000, t=900]
Attacking:  17%|█▋        | 85/500 [02:21<11:24,  1.65s/it, loss=2240.0000, t=900]
Attacking:  17%|█▋        | 86/500 [02:22<11:19,  1.64s/it, loss=2240.0000, t=900]
Attacking:  17%|█▋        | 86/500 [02:22<11:19,  1.64s/it, loss=2224.0000, t=900]
Attacking:  17%|█▋        | 87/500 [02:23<11:08,  1.62s/it, loss=2224.0000, t=900]
Attacking:  17%|█▋        | 87/500 [02:24<11:08,  1.62s/it, loss=2272.0000, t=940]
Attacking:  18%|█▊        | 88/500 [02:25<11:06,  1.62s/it, loss=2272.0000, t=940]
Attacking:  18%|█▊        | 88/500 [02:26<11:06,  1.62s/it, loss=2240.0000, t=912]
Attacking:  18%|█▊        | 89/500 [02:27<11:26,  1.67s/it, loss=2240.0000, t=912]
Attacking:  18%|█▊        | 89/500 [02:27<11:26,  1.67s/it, loss=2272.0000, t=940]
Attacking:  18%|█▊        | 90/500 [02:28<11:16,  1.65s/it, loss=2272.0000, t=940]
Attacking:  18%|█▊        | 90/500 [02:29<11:16,  1.65s/it, loss=2416.0000, t=1e+3]
Attacking:  18%|█▊        | 91/500 [02:30<11:17,  1.66s/it, loss=2416.0000, t=1e+3]
Attacking:  18%|█▊        | 91/500 [02:31<11:17,  1.66s/it, loss=2304.0000, t=964] 
Attacking:  18%|█▊        | 92/500 [02:31<11:19,  1.67s/it, loss=2304.0000, t=964]
Attacking:  18%|█▊        | 92/500 [02:32<11:19,  1.67s/it, loss=2240.0000, t=912]
Attacking:  19%|█▊        | 93/500 [02:33<11:03,  1.63s/it, loss=2240.0000, t=912]
Attacking:  19%|█▊        | 93/500 [02:34<11:03,  1.63s/it, loss=2288.0000, t=952]
Attacking:  19%|█▉        | 94/500 [02:35<10:55,  1.61s/it, loss=2288.0000, t=952]
Attacking:  19%|█▉        | 94/500 [02:35<10:55,  1.61s/it, loss=2336.0000, t=972]
Attacking:  19%|█▉        | 95/500 [02:36<10:47,  1.60s/it, loss=2336.0000, t=972]
Attacking:  19%|█▉        | 95/500 [02:37<10:47,  1.60s/it, loss=2336.0000, t=972]
Attacking:  19%|█▉        | 96/500 [02:38<10:59,  1.63s/it, loss=2336.0000, t=972]
Attacking:  19%|█▉        | 96/500 [02:39<10:59,  1.63s/it, loss=2336.0000, t=972]
Attacking:  19%|█▉        | 97/500 [02:39<10:52,  1.62s/it, loss=2336.0000, t=972]
Attacking:  19%|█▉        | 97/500 [02:40<10:52,  1.62s/it, loss=2240.0000, t=928]
Attacking:  20%|█▉        | 98/500 [02:41<10:47,  1.61s/it, loss=2240.0000, t=928]
Attacking:  20%|█▉        | 98/500 [02:42<10:47,  1.61s/it, loss=2304.0000, t=964]
Attacking:  20%|█▉        | 99/500 [02:43<10:40,  1.60s/it, loss=2304.0000, t=964]
Attacking:  20%|█▉        | 99/500 [02:43<10:40,  1.60s/it, loss=2304.0000, t=964]
Attacking:  20%|██        | 100/500 [02:44<10:42,  1.61s/it, loss=2304.0000, t=964]
Attacking:  20%|██        | 100/500 [02:45<10:42,  1.61s/it, loss=2384.0000, t=984]
Attacking:  20%|██        | 101/500 [02:46<10:31,  1.58s/it, loss=2384.0000, t=984]
Attacking:  20%|██        | 101/500 [02:47<10:31,  1.58s/it, loss=2288.0000, t=952]
Attacking:  20%|██        | 102/500 [02:47<10:43,  1.62s/it, loss=2288.0000, t=952]
Attacking:  20%|██        | 102/500 [02:48<10:43,  1.62s/it, loss=2368.0000, t=984]
Attacking:  21%|██        | 103/500 [02:49<10:54,  1.65s/it, loss=2368.0000, t=984]
Attacking:  21%|██        | 103/500 [02:50<10:54,  1.65s/it, loss=2256.0000, t=928]
Attacking:  21%|██        | 104/500 [02:51<10:46,  1.63s/it, loss=2256.0000, t=928]
Attacking:  21%|██        | 104/500 [02:52<10:46,  1.63s/it, loss=2400.0000, t=1e+3]
Attacking:  21%|██        | 105/500 [02:52<10:43,  1.63s/it, loss=2400.0000, t=1e+3]
Attacking:  21%|██        | 105/500 [02:53<10:43,  1.63s/it, loss=2256.0000, t=928] 
Attacking:  21%|██        | 106/500 [02:54<10:46,  1.64s/it, loss=2256.0000, t=928]
Attacking:  21%|██        | 106/500 [02:55<10:46,  1.64s/it, loss=2208.0000, t=900]
Attacking:  21%|██▏       | 107/500 [02:56<10:47,  1.65s/it, loss=2208.0000, t=900]
Attacking:  21%|██▏       | 107/500 [02:57<10:47,  1.65s/it, loss=2224.0000, t=900]
Attacking:  22%|██▏       | 108/500 [02:57<10:39,  1.63s/it, loss=2224.0000, t=900]
Attacking:  22%|██▏       | 108/500 [02:58<10:39,  1.63s/it, loss=2400.0000, t=1e+3]
Attacking:  22%|██▏       | 109/500 [02:59<10:42,  1.64s/it, loss=2400.0000, t=1e+3]
Attacking:  22%|██▏       | 109/500 [03:00<10:42,  1.64s/it, loss=2320.0000, t=972] 
Attacking:  22%|██▏       | 110/500 [03:01<10:38,  1.64s/it, loss=2320.0000, t=972]
Attacking:  22%|██▏       | 110/500 [03:01<10:38,  1.64s/it, loss=2368.0000, t=984]
Attacking:  22%|██▏       | 111/500 [03:02<10:28,  1.62s/it, loss=2368.0000, t=984]
Attacking:  22%|██▏       | 111/500 [03:03<10:28,  1.62s/it, loss=2320.0000, t=972]
Attacking:  22%|██▏       | 112/500 [03:04<10:15,  1.59s/it, loss=2320.0000, t=972]
Attacking:  22%|██▏       | 112/500 [03:04<10:15,  1.59s/it, loss=2224.0000, t=912]
Attacking:  23%|██▎       | 113/500 [03:05<10:08,  1.57s/it, loss=2224.0000, t=912]
Attacking:  23%|██▎       | 113/500 [03:06<10:08,  1.57s/it, loss=2336.0000, t=972]
Attacking:  23%|██▎       | 114/500 [03:07<09:58,  1.55s/it, loss=2336.0000, t=972]
Attacking:  23%|██▎       | 114/500 [03:07<09:58,  1.55s/it, loss=2416.0000, t=992]
Attacking:  23%|██▎       | 115/500 [03:08<09:48,  1.53s/it, loss=2416.0000, t=992]
Attacking:  23%|██▎       | 115/500 [03:09<09:48,  1.53s/it, loss=2384.0000, t=1e+3]
Attacking:  23%|██▎       | 116/500 [03:10<09:57,  1.56s/it, loss=2384.0000, t=1e+3]
Attacking:  23%|██▎       | 116/500 [03:11<09:57,  1.56s/it, loss=2224.0000, t=912] 
Attacking:  23%|██▎       | 117/500 [03:11<09:53,  1.55s/it, loss=2224.0000, t=912]
Attacking:  23%|██▎       | 117/500 [03:12<09:53,  1.55s/it, loss=2272.0000, t=952]
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Attacking: 100%|██████████| 500/500 [13:01<00:00,  1.56s/it, loss=2176.0000, t=940]
+Max Diff: 0.501961
+Mean Diff: 0.245114
+Saved adversarial image to attacked/images/deer.jpg
+Saved loss curve to attacked/loss_curve/deer_loss.png
+[GPU 2] Stage 3/3: Test
+Loading models for testing deer...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for deer...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 35.80it/s]
+Saved video to attacked/videos/deer.mp4
+Saved frames to attacked/frames/deer
+[GPU 2] Finished deer.jpg
+======================================
+[GPU 2] Processing dog.jpg (Image 16/50)
+======================================
+[GPU 2] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 2] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  99%|█████████▉| 496/500 [12:47<00:06,  1.55s/it, loss=2320.0000, t=1e+3]
Attacking:  99%|█████████▉| 496/500 [12:48<00:06,  1.55s/it, loss=2304.0000, t=1e+3]
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Attacking: 100%|█████████▉| 498/500 [12:50<00:03,  1.60s/it, loss=2240.0000, t=912]
Attacking: 100%|█████████▉| 498/500 [12:51<00:03,  1.60s/it, loss=2304.0000, t=992]
Attacking: 100%|█████████▉| 499/500 [12:52<00:01,  1.65s/it, loss=2304.0000, t=992]
Attacking: 100%|█████████▉| 499/500 [12:53<00:01,  1.65s/it, loss=2240.0000, t=912]
Attacking: 100%|██████████| 500/500 [12:54<00:00,  1.64s/it, loss=2240.0000, t=912]
Attacking: 100%|██████████| 500/500 [12:54<00:00,  1.55s/it, loss=2240.0000, t=912]
+Max Diff: 0.501961
+Mean Diff: 0.268917
+Saved adversarial image to attacked/images/dog.jpg
+Saved loss curve to attacked/loss_curve/dog_loss.png
+[GPU 2] Stage 3/3: Test
+Loading models for testing dog...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for dog...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 47.97it/s]
+Saved video to attacked/videos/dog.mp4
+Saved frames to attacked/frames/dog
+[GPU 2] Finished dog.jpg
+======================================
+[GPU 2] Processing elephant.jpg (Image 17/50)
+======================================
+[GPU 2] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 2] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   6%|▌         | 28/500 [00:45<12:25,  1.58s/it, loss=2336.0000, t=952]
Attacking:   6%|▌         | 29/500 [00:46<12:19,  1.57s/it, loss=2336.0000, t=952]
Attacking:   6%|▌         | 29/500 [00:47<12:19,  1.57s/it, loss=2368.0000, t=992]
Attacking:   6%|▌         | 30/500 [00:48<12:04,  1.54s/it, loss=2368.0000, t=992]
Attacking:   6%|▌         | 30/500 [00:48<12:04,  1.54s/it, loss=2320.0000, t=972]
Attacking:   6%|▌         | 31/500 [00:49<11:51,  1.52s/it, loss=2320.0000, t=972]
Attacking:   6%|▌         | 31/500 [00:50<11:51,  1.52s/it, loss=2304.0000, t=912]
Attacking:   6%|▋         | 32/500 [00:51<11:55,  1.53s/it, loss=2304.0000, t=912]
Attacking:   6%|▋         | 32/500 [00:51<11:55,  1.53s/it, loss=2336.0000, t=940]
Attacking:   7%|▋         | 33/500 [00:52<11:48,  1.52s/it, loss=2336.0000, t=940]
Attacking:   7%|▋         | 33/500 [00:53<11:48,  1.52s/it, loss=2384.0000, t=1e+3]
Attacking:   7%|▋         | 34/500 [00:53<11:35,  1.49s/it, loss=2384.0000, t=1e+3]
Attacking:   7%|▋         | 34/500 [00:54<11:35,  1.49s/it, loss=2320.0000, t=900] 
Attacking:   7%|▋         | 35/500 [00:55<11:28,  1.48s/it, loss=2320.0000, t=900]
Attacking:   7%|▋         | 35/500 [00:56<11:28,  1.48s/it, loss=2368.0000, t=928]
Attacking:   7%|▋         | 36/500 [00:56<11:41,  1.51s/it, loss=2368.0000, t=928]
Attacking:   7%|▋         | 36/500 [00:57<11:41,  1.51s/it, loss=2320.0000, t=964]
Attacking:   7%|▋         | 37/500 [00:58<11:47,  1.53s/it, loss=2320.0000, t=964]
Attacking:   7%|▋         | 37/500 [00:59<11:47,  1.53s/it, loss=2304.0000, t=900]
Attacking:   8%|▊         | 38/500 [01:00<12:05,  1.57s/it, loss=2304.0000, t=900]
Attacking:   8%|▊         | 38/500 [01:01<12:05,  1.57s/it, loss=2320.0000, t=964]
Attacking:   8%|▊         | 39/500 [01:01<12:18,  1.60s/it, loss=2320.0000, t=964]
Attacking:   8%|▊         | 39/500 [01:02<12:18,  1.60s/it, loss=2320.0000, t=964]
Attacking:   8%|▊         | 40/500 [01:03<12:04,  1.58s/it, loss=2320.0000, t=964]
Attacking:   8%|▊         | 40/500 [01:04<12:04,  1.58s/it, loss=2272.0000, t=900]
Attacking:   8%|▊         | 41/500 [01:04<11:57,  1.56s/it, loss=2272.0000, t=900]
Attacking:   8%|▊         | 41/500 [01:05<11:57,  1.56s/it, loss=2304.0000, t=952]
Attacking:   8%|▊         | 42/500 [01:06<12:02,  1.58s/it, loss=2304.0000, t=952]
Attacking:   8%|▊         | 42/500 [01:07<12:02,  1.58s/it, loss=2304.0000, t=972]
Attacking:   9%|▊         | 43/500 [01:08<12:30,  1.64s/it, loss=2304.0000, t=972]
Attacking:   9%|▊         | 43/500 [01:09<12:30,  1.64s/it, loss=2336.0000, t=992]
Attacking:   9%|▉         | 44/500 [01:09<12:21,  1.63s/it, loss=2336.0000, t=992]
Attacking:   9%|▉         | 44/500 [01:10<12:21,  1.63s/it, loss=2304.0000, t=940]
Attacking:   9%|▉         | 45/500 [01:11<11:57,  1.58s/it, loss=2304.0000, t=940]
Attacking:   9%|▉         | 45/500 [01:12<11:57,  1.58s/it, loss=2288.0000, t=952]
Attacking:   9%|▉         | 46/500 [01:12<11:53,  1.57s/it, loss=2288.0000, t=952]
Attacking:   9%|▉         | 46/500 [01:13<11:53,  1.57s/it, loss=2368.0000, t=992]
Attacking:   9%|▉         | 47/500 [01:14<12:02,  1.59s/it, loss=2368.0000, t=992]
Attacking:   9%|▉         | 47/500 [01:15<12:02,  1.59s/it, loss=2272.0000, t=928]
Attacking:  10%|▉         | 48/500 [01:16<12:03,  1.60s/it, loss=2272.0000, t=928]
Attacking:  10%|▉         | 48/500 [01:16<12:03,  1.60s/it, loss=2336.0000, t=984]
Attacking:  10%|▉         | 49/500 [01:17<11:41,  1.56s/it, loss=2336.0000, t=984]
Attacking:  10%|▉         | 49/500 [01:18<11:41,  1.56s/it, loss=2272.0000, t=928]
Attacking:  10%|█         | 50/500 [01:19<11:52,  1.58s/it, loss=2272.0000, t=928]
Attacking:  10%|█         | 50/500 [01:20<11:52,  1.58s/it, loss=2336.0000, t=984]
Attacking:  10%|█         | 51/500 [01:21<12:08,  1.62s/it, loss=2336.0000, t=984]
Attacking:  10%|█         | 51/500 [01:21<12:08,  1.62s/it, loss=2304.0000, t=972]
Attacking:  10%|█         | 52/500 [01:22<12:09,  1.63s/it, loss=2304.0000, t=972]
Attacking:  10%|█         | 52/500 [01:23<12:09,  1.63s/it, loss=2304.0000, t=940]
Attacking:  11%|█         | 53/500 [01:24<12:13,  1.64s/it, loss=2304.0000, t=940]
Attacking:  11%|█         | 53/500 [01:25<12:13,  1.64s/it, loss=2304.0000, t=984]
Attacking:  11%|█         | 54/500 [01:25<12:10,  1.64s/it, loss=2304.0000, t=984]
Attacking:  11%|█         | 54/500 [01:26<12:10,  1.64s/it, loss=2304.0000, t=984]
Attacking:  11%|█         | 55/500 [01:27<12:13,  1.65s/it, loss=2304.0000, t=984]
Attacking:  11%|█         | 55/500 [01:28<12:13,  1.65s/it, loss=2272.0000, t=952]
Attacking:  11%|█         | 56/500 [01:29<12:08,  1.64s/it, loss=2272.0000, t=952]
Attacking:  11%|█         | 56/500 [01:30<12:08,  1.64s/it, loss=2336.0000, t=1e+3]
Attacking:  11%|█▏        | 57/500 [01:30<12:03,  1.63s/it, loss=2336.0000, t=1e+3]
Attacking:  11%|█▏        | 57/500 [01:31<12:03,  1.63s/it, loss=2320.0000, t=992] 
Attacking:  12%|█▏        | 58/500 [01:32<12:07,  1.65s/it, loss=2320.0000, t=992]
Attacking:  12%|█▏        | 58/500 [01:33<12:07,  1.65s/it, loss=2320.0000, t=992]
Attacking:  12%|█▏        | 59/500 [01:34<12:22,  1.68s/it, loss=2320.0000, t=992]
Attacking:  12%|█▏        | 59/500 [01:34<12:22,  1.68s/it, loss=2288.0000, t=972]
Attacking:  12%|█▏        | 60/500 [01:35<11:54,  1.62s/it, loss=2288.0000, t=972]
Attacking:  12%|█▏        | 60/500 [01:36<11:54,  1.62s/it, loss=2336.0000, t=1e+3]
Attacking:  12%|█▏        | 61/500 [01:37<11:43,  1.60s/it, loss=2336.0000, t=1e+3]
Attacking:  12%|█▏        | 61/500 [01:37<11:43,  1.60s/it, loss=2304.0000, t=992] 
Attacking:  12%|█▏        | 62/500 [01:38<11:21,  1.56s/it, loss=2304.0000, t=992]
Attacking:  12%|█▏        | 62/500 [01:39<11:21,  1.56s/it, loss=2288.0000, t=972]
Attacking:  13%|█▎        | 63/500 [01:40<11:21,  1.56s/it, loss=2288.0000, t=972]
Attacking:  13%|█▎        | 63/500 [01:41<11:21,  1.56s/it, loss=2304.0000, t=992]
Attacking:  13%|█▎        | 64/500 [01:42<11:30,  1.58s/it, loss=2304.0000, t=992]
Attacking:  13%|█▎        | 64/500 [01:42<11:30,  1.58s/it, loss=2240.0000, t=900]
Attacking:  13%|█▎        | 65/500 [01:43<11:28,  1.58s/it, loss=2240.0000, t=900]
Attacking:  13%|█▎        | 65/500 [01:44<11:28,  1.58s/it, loss=2320.0000, t=1e+3]
Attacking:  13%|█▎        | 66/500 [01:45<11:14,  1.55s/it, loss=2320.0000, t=1e+3]
Attacking:  13%|█▎        | 66/500 [01:45<11:14,  1.55s/it, loss=2272.0000, t=940] 
Attacking:  13%|█▎        | 67/500 [01:46<11:01,  1.53s/it, loss=2272.0000, t=940]
Attacking:  13%|█▎        | 67/500 [01:47<11:01,  1.53s/it, loss=2272.0000, t=964]
Attacking:  14%|█▎        | 68/500 [01:48<11:08,  1.55s/it, loss=2272.0000, t=964]
Attacking:  14%|█▎        | 68/500 [01:48<11:08,  1.55s/it, loss=2256.0000, t=964]
Attacking:  14%|█▍        | 69/500 [01:49<11:17,  1.57s/it, loss=2256.0000, t=964]
Attacking:  14%|█▍        | 69/500 [01:50<11:17,  1.57s/it, loss=2272.0000, t=952]
Attacking:  14%|█▍        | 70/500 [01:51<11:20,  1.58s/it, loss=2272.0000, t=952]
Attacking:  14%|█▍        | 70/500 [01:51<11:20,  1.58s/it, loss=2304.0000, t=1e+3]
Attacking:  14%|█▍        | 71/500 [01:52<11:00,  1.54s/it, loss=2304.0000, t=1e+3]
Attacking:  14%|█▍        | 71/500 [01:53<11:00,  1.54s/it, loss=2256.0000, t=972] 
Attacking:  14%|█▍        | 72/500 [01:54<10:49,  1.52s/it, loss=2256.0000, t=972]
Attacking:  14%|█▍        | 72/500 [01:54<10:49,  1.52s/it, loss=2240.0000, t=928]
Attacking:  15%|█▍        | 73/500 [01:55<10:46,  1.51s/it, loss=2240.0000, t=928]
Attacking:  15%|█▍        | 73/500 [01:56<10:46,  1.51s/it, loss=2304.0000, t=1e+3]
Attacking:  15%|█▍        | 74/500 [01:57<11:10,  1.57s/it, loss=2304.0000, t=1e+3]
Attacking:  15%|█▍        | 74/500 [01:58<11:10,  1.57s/it, loss=2240.0000, t=940] 
Attacking:  15%|█▌        | 75/500 [01:59<11:21,  1.60s/it, loss=2240.0000, t=940]
Attacking:  15%|█▌        | 75/500 [01:59<11:21,  1.60s/it, loss=2240.0000, t=964]
Attacking:  15%|█▌        | 76/500 [02:00<11:08,  1.58s/it, loss=2240.0000, t=964]
Attacking:  15%|█▌        | 76/500 [02:01<11:08,  1.58s/it, loss=2256.0000, t=940]
Attacking:  15%|█▌        | 77/500 [02:02<11:15,  1.60s/it, loss=2256.0000, t=940]
Attacking:  15%|█▌        | 77/500 [02:03<11:15,  1.60s/it, loss=2256.0000, t=984]
Attacking:  16%|█▌        | 78/500 [02:03<11:12,  1.59s/it, loss=2256.0000, t=984]
Attacking:  16%|█▌        | 78/500 [02:04<11:12,  1.59s/it, loss=2240.0000, t=928]
Attacking:  16%|█▌        | 79/500 [02:05<11:24,  1.63s/it, loss=2240.0000, t=928]
Attacking:  16%|█▌        | 79/500 [02:06<11:24,  1.63s/it, loss=2224.0000, t=912]
Attacking:  16%|█▌        | 80/500 [02:07<11:06,  1.59s/it, loss=2224.0000, t=912]
Attacking:  16%|█▌        | 80/500 [02:07<11:06,  1.59s/it, loss=2304.0000, t=992]
Attacking:  16%|█▌        | 81/500 [02:08<11:15,  1.61s/it, loss=2304.0000, t=992]
Attacking:  16%|█▌        | 81/500 [02:09<11:15,  1.61s/it, loss=2304.0000, t=1e+3]
Attacking:  16%|█▋        | 82/500 [02:10<11:16,  1.62s/it, loss=2304.0000, t=1e+3]
Attacking:  16%|█▋        | 82/500 [02:11<11:16,  1.62s/it, loss=2256.0000, t=972] 
Attacking:  17%|█▋        | 83/500 [02:12<11:18,  1.63s/it, loss=2256.0000, t=972]
Attacking:  17%|█▋        | 83/500 [02:12<11:18,  1.63s/it, loss=2256.0000, t=952]
Attacking:  17%|█▋        | 84/500 [02:13<11:11,  1.61s/it, loss=2256.0000, t=952]
Attacking:  17%|█▋        | 84/500 [02:14<11:11,  1.61s/it, loss=2288.0000, t=992]
Attacking:  17%|█▋        | 85/500 [02:15<11:02,  1.60s/it, loss=2288.0000, t=992]
Attacking:  17%|█▋        | 85/500 [02:15<11:02,  1.60s/it, loss=2288.0000, t=1e+3]
Attacking:  17%|█▋        | 86/500 [02:16<10:52,  1.58s/it, loss=2288.0000, t=1e+3]
Attacking:  17%|█▋        | 86/500 [02:17<10:52,  1.58s/it, loss=2272.0000, t=984] 
Attacking:  17%|█▋        | 87/500 [02:18<10:47,  1.57s/it, loss=2272.0000, t=984]
Attacking:  17%|█▋        | 87/500 [02:18<10:47,  1.57s/it, loss=2256.0000, t=964]
Attacking:  18%|█▊        | 88/500 [02:19<10:42,  1.56s/it, loss=2256.0000, t=964]
Attacking:  18%|█▊        | 88/500 [02:20<10:42,  1.56s/it, loss=2256.0000, t=972]
Attacking:  18%|█▊        | 89/500 [02:21<10:31,  1.54s/it, loss=2256.0000, t=972]
Attacking:  18%|█▊        | 89/500 [02:21<10:31,  1.54s/it, loss=2240.0000, t=972]
Attacking:  18%|█▊        | 90/500 [02:22<10:12,  1.49s/it, loss=2240.0000, t=972]
Attacking:  18%|█▊        | 90/500 [02:23<10:12,  1.49s/it, loss=2304.0000, t=1e+3]
Attacking:  18%|█▊        | 91/500 [02:24<10:05,  1.48s/it, loss=2304.0000, t=1e+3]
Attacking:  18%|█▊        | 91/500 [02:24<10:05,  1.48s/it, loss=2240.0000, t=964] 
Attacking:  18%|█▊        | 92/500 [02:25<10:06,  1.49s/it, loss=2240.0000, t=964]
Attacking:  18%|█▊        | 92/500 [02:26<10:06,  1.49s/it, loss=2288.0000, t=1e+3]
Attacking:  19%|█▊        | 93/500 [02:27<10:01,  1.48s/it, loss=2288.0000, t=1e+3]
Attacking:  19%|█▊        | 93/500 [02:27<10:01,  1.48s/it, loss=2272.0000, t=992] 
Attacking:  19%|█▉        | 94/500 [02:28<09:50,  1.45s/it, loss=2272.0000, t=992]
Attacking:  19%|█▉        | 94/500 [02:29<09:50,  1.45s/it, loss=2208.0000, t=912]
Attacking:  19%|█▉        | 95/500 [02:29<09:48,  1.45s/it, loss=2208.0000, t=912]
Attacking:  19%|█▉        | 95/500 [02:30<09:48,  1.45s/it, loss=2224.0000, t=972]
Attacking:  19%|█▉        | 96/500 [02:31<09:42,  1.44s/it, loss=2224.0000, t=972]
Attacking:  19%|█▉        | 96/500 [02:31<09:42,  1.44s/it, loss=2208.0000, t=912]
Attacking:  19%|█▉        | 97/500 [02:32<09:43,  1.45s/it, loss=2208.0000, t=912]
Attacking:  19%|█▉        | 97/500 [02:33<09:43,  1.45s/it, loss=2224.0000, t=964]
Attacking:  20%|█▉        | 98/500 [02:34<09:53,  1.48s/it, loss=2224.0000, t=964]
Attacking:  20%|█▉        | 98/500 [02:35<09:53,  1.48s/it, loss=2224.0000, t=972]
Attacking:  20%|█▉        | 99/500 [02:35<10:02,  1.50s/it, loss=2224.0000, t=972]
Attacking:  20%|█▉        | 99/500 [02:36<10:02,  1.50s/it, loss=2224.0000, t=964]
Attacking:  20%|██        | 100/500 [02:37<10:09,  1.52s/it, loss=2224.0000, t=964]
Attacking:  20%|██        | 100/500 [02:38<10:09,  1.52s/it, loss=2208.0000, t=912]
Attacking:  20%|██        | 101/500 [02:39<10:20,  1.56s/it, loss=2208.0000, t=912]
Attacking:  20%|██        | 101/500 [02:39<10:20,  1.56s/it, loss=2208.0000, t=952]
Attacking:  20%|██        | 102/500 [02:40<10:04,  1.52s/it, loss=2208.0000, t=952]
Attacking:  20%|██        | 102/500 [02:41<10:04,  1.52s/it, loss=2304.0000, t=1e+3]
Attacking:  21%|██        | 103/500 [02:42<10:11,  1.54s/it, loss=2304.0000, t=1e+3]
Attacking:  21%|██        | 103/500 [02:42<10:11,  1.54s/it, loss=2192.0000, t=900] 
Attacking:  21%|██        | 104/500 [02:43<10:22,  1.57s/it, loss=2192.0000, t=900]
Attacking:  21%|██        | 104/500 [02:44<10:22,  1.57s/it, loss=2240.0000, t=984]
Attacking:  21%|██        | 105/500 [02:45<10:33,  1.60s/it, loss=2240.0000, t=984]
Attacking:  21%|██        | 105/500 [02:46<10:33,  1.60s/it, loss=2208.0000, t=940]
Attacking:  21%|██        | 106/500 [02:47<10:38,  1.62s/it, loss=2208.0000, t=940]
Attacking:  21%|██        | 106/500 [02:47<10:38,  1.62s/it, loss=2240.0000, t=984]
Attacking:  21%|██▏       | 107/500 [02:48<10:35,  1.62s/it, loss=2240.0000, t=984]
Attacking:  21%|██▏       | 107/500 [02:49<10:35,  1.62s/it, loss=2208.0000, t=964]
Attacking:  22%|██▏       | 108/500 [02:50<10:13,  1.56s/it, loss=2208.0000, t=964]
Attacking:  22%|██▏       | 108/500 [02:50<10:13,  1.56s/it, loss=2208.0000, t=940]
Attacking:  22%|██▏       | 109/500 [02:51<10:04,  1.55s/it, loss=2208.0000, t=940]
Attacking:  22%|██▏       | 109/500 [02:52<10:04,  1.55s/it, loss=2208.0000, t=952]
Attacking:  22%|██▏       | 110/500 [02:53<09:49,  1.51s/it, loss=2208.0000, t=952]
Attacking:  22%|██▏       | 110/500 [02:53<09:49,  1.51s/it, loss=2192.0000, t=928]
Attacking:  22%|██▏       | 111/500 [02:54<09:51,  1.52s/it, loss=2192.0000, t=928]
Attacking:  22%|██▏       | 111/500 [02:55<09:51,  1.52s/it, loss=2224.0000, t=984]
Attacking:  22%|██▏       | 112/500 [02:56<10:07,  1.57s/it, loss=2224.0000, t=984]
Attacking:  22%|██▏       | 112/500 [02:57<10:07,  1.57s/it, loss=2224.0000, t=972]
Attacking:  23%|██▎       | 113/500 [02:57<10:12,  1.58s/it, loss=2224.0000, t=972]
Attacking:  23%|██▎       | 113/500 [02:58<10:12,  1.58s/it, loss=2224.0000, t=972]
Attacking:  23%|██▎       | 114/500 [02:59<10:08,  1.58s/it, loss=2224.0000, t=972]
Attacking:  23%|██▎       | 114/500 [03:00<10:08,  1.58s/it, loss=2208.0000, t=952]
Attacking:  23%|██▎       | 115/500 [03:01<10:04,  1.57s/it, loss=2208.0000, t=952]
Attacking:  23%|██▎       | 115/500 [03:01<10:04,  1.57s/it, loss=2272.0000, t=1e+3]
Attacking:  23%|██▎       | 116/500 [03:02<10:18,  1.61s/it, loss=2272.0000, t=1e+3]
Attacking:  23%|██▎       | 116/500 [03:03<10:18,  1.61s/it, loss=2272.0000, t=992] 
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+Max Diff: 0.501961
+Mean Diff: 0.235416
+Saved adversarial image to attacked/images/elephant.jpg
+Saved loss curve to attacked/loss_curve/elephant_loss.png
+[GPU 2] Stage 3/3: Test
+Loading models for testing elephant...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for elephant...
+
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+
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+Saved video to attacked/videos/elephant.mp4
+Saved frames to attacked/frames/elephant
+[GPU 2] Finished elephant.jpg
+======================================
+[GPU 2] Processing flamingo.jpg (Image 18/50)
+======================================
+[GPU 2] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 2] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  20%|██        | 100/500 [02:38<10:35,  1.59s/it, loss=2240.0000, t=984]
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Attacking: 100%|█████████▉| 499/500 [12:52<00:01,  1.58s/it, loss=2160.0000, t=940]
Attacking: 100%|██████████| 500/500 [12:52<00:00,  1.62s/it, loss=2160.0000, t=940]
Attacking: 100%|██████████| 500/500 [12:52<00:00,  1.55s/it, loss=2160.0000, t=940]
+Max Diff: 0.501961
+Mean Diff: 0.222475
+Saved adversarial image to attacked/images/flamingo.jpg
+Saved loss curve to attacked/loss_curve/flamingo_loss.png
+[GPU 2] Stage 3/3: Test
+Loading models for testing flamingo...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for flamingo...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 50.87it/s]
+Saved video to attacked/videos/flamingo.mp4
+Saved frames to attacked/frames/flamingo
+[GPU 2] Finished flamingo.jpg
+======================================
+[GPU 2] Processing girl.jpg (Image 19/50)
+======================================
+[GPU 2] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 2] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   6%|▌         | 29/500 [00:46<11:56,  1.52s/it, loss=2208.0000, t=940]
Attacking:   6%|▌         | 29/500 [00:47<11:56,  1.52s/it, loss=2176.0000, t=900]
Attacking:   6%|▌         | 30/500 [00:48<11:48,  1.51s/it, loss=2176.0000, t=900]
Attacking:   6%|▌         | 30/500 [00:49<11:48,  1.51s/it, loss=2304.0000, t=1e+3]
Attacking:   6%|▌         | 31/500 [00:50<12:09,  1.55s/it, loss=2304.0000, t=1e+3]
Attacking:   6%|▌         | 31/500 [00:50<12:09,  1.55s/it, loss=2192.0000, t=912] 
Attacking:   6%|▋         | 32/500 [00:51<11:59,  1.54s/it, loss=2192.0000, t=912]
Attacking:   6%|▋         | 32/500 [00:52<11:59,  1.54s/it, loss=2336.0000, t=1e+3]
Attacking:   7%|▋         | 33/500 [00:53<12:00,  1.54s/it, loss=2336.0000, t=1e+3]
Attacking:   7%|▋         | 33/500 [00:53<12:00,  1.54s/it, loss=2240.0000, t=964] 
Attacking:   7%|▋         | 34/500 [00:54<12:13,  1.57s/it, loss=2240.0000, t=964]
Attacking:   7%|▋         | 34/500 [00:55<12:13,  1.57s/it, loss=2256.0000, t=972]
Attacking:   7%|▋         | 35/500 [00:56<12:15,  1.58s/it, loss=2256.0000, t=972]
Attacking:   7%|▋         | 35/500 [00:57<12:15,  1.58s/it, loss=2304.0000, t=1e+3]
Attacking:   7%|▋         | 36/500 [00:58<12:31,  1.62s/it, loss=2304.0000, t=1e+3]
Attacking:   7%|▋         | 36/500 [00:58<12:31,  1.62s/it, loss=2192.0000, t=928] 
Attacking:   7%|▋         | 37/500 [00:59<12:18,  1.59s/it, loss=2192.0000, t=928]
Attacking:   7%|▋         | 37/500 [01:00<12:18,  1.59s/it, loss=2208.0000, t=952]
Attacking:   8%|▊         | 38/500 [01:01<12:24,  1.61s/it, loss=2208.0000, t=952]
Attacking:   8%|▊         | 38/500 [01:02<12:24,  1.61s/it, loss=2272.0000, t=984]
Attacking:   8%|▊         | 39/500 [01:02<12:13,  1.59s/it, loss=2272.0000, t=984]
Attacking:   8%|▊         | 39/500 [01:03<12:13,  1.59s/it, loss=2272.0000, t=984]
Attacking:   8%|▊         | 40/500 [01:04<12:05,  1.58s/it, loss=2272.0000, t=984]
Attacking:   8%|▊         | 40/500 [01:05<12:05,  1.58s/it, loss=2224.0000, t=964]
Attacking:   8%|▊         | 41/500 [01:06<12:09,  1.59s/it, loss=2224.0000, t=964]
Attacking:   8%|▊         | 41/500 [01:06<12:09,  1.59s/it, loss=2304.0000, t=992]
Attacking:   8%|▊         | 42/500 [01:07<12:14,  1.60s/it, loss=2304.0000, t=992]
Attacking:   8%|▊         | 42/500 [01:08<12:14,  1.60s/it, loss=2304.0000, t=992]
Attacking:   9%|▊         | 43/500 [01:09<12:12,  1.60s/it, loss=2304.0000, t=992]
Attacking:   9%|▊         | 43/500 [01:09<12:12,  1.60s/it, loss=2192.0000, t=940]
Attacking:   9%|▉         | 44/500 [01:10<12:01,  1.58s/it, loss=2192.0000, t=940]
Attacking:   9%|▉         | 44/500 [01:11<12:01,  1.58s/it, loss=2208.0000, t=964]
Attacking:   9%|▉         | 45/500 [01:12<11:35,  1.53s/it, loss=2208.0000, t=964]
Attacking:   9%|▉         | 45/500 [01:12<11:35,  1.53s/it, loss=2160.0000, t=912]
Attacking:   9%|▉         | 46/500 [01:13<11:25,  1.51s/it, loss=2160.0000, t=912]
Attacking:   9%|▉         | 46/500 [01:14<11:25,  1.51s/it, loss=2160.0000, t=900]
Attacking:   9%|▉         | 47/500 [01:15<11:45,  1.56s/it, loss=2160.0000, t=900]
Attacking:   9%|▉         | 47/500 [01:16<11:45,  1.56s/it, loss=2176.0000, t=940]
Attacking:  10%|▉         | 48/500 [01:17<12:00,  1.59s/it, loss=2176.0000, t=940]
Attacking:  10%|▉         | 48/500 [01:17<12:00,  1.59s/it, loss=2160.0000, t=900]
Attacking:  10%|▉         | 49/500 [01:18<11:56,  1.59s/it, loss=2160.0000, t=900]
Attacking:  10%|▉         | 49/500 [01:19<11:56,  1.59s/it, loss=2144.0000, t=900]
Attacking:  10%|█         | 50/500 [01:20<11:58,  1.60s/it, loss=2144.0000, t=900]
Attacking:  10%|█         | 50/500 [01:20<11:58,  1.60s/it, loss=2272.0000, t=1e+3]
Attacking:  10%|█         | 51/500 [01:21<11:54,  1.59s/it, loss=2272.0000, t=1e+3]
Attacking:  10%|█         | 51/500 [01:22<11:54,  1.59s/it, loss=2192.0000, t=964] 
Attacking:  10%|█         | 52/500 [01:23<12:00,  1.61s/it, loss=2192.0000, t=964]
Attacking:  10%|█         | 52/500 [01:24<12:00,  1.61s/it, loss=2160.0000, t=940]
Attacking:  11%|█         | 53/500 [01:25<11:52,  1.59s/it, loss=2160.0000, t=940]
Attacking:  11%|█         | 53/500 [01:25<11:52,  1.59s/it, loss=2160.0000, t=940]
Attacking:  11%|█         | 54/500 [01:26<11:32,  1.55s/it, loss=2160.0000, t=940]
Attacking:  11%|█         | 54/500 [01:27<11:32,  1.55s/it, loss=2272.0000, t=992]
Attacking:  11%|█         | 55/500 [01:28<11:40,  1.57s/it, loss=2272.0000, t=992]
Attacking:  11%|█         | 55/500 [01:28<11:40,  1.57s/it, loss=2176.0000, t=952]
Attacking:  11%|█         | 56/500 [01:29<11:50,  1.60s/it, loss=2176.0000, t=952]
Attacking:  11%|█         | 56/500 [01:30<11:50,  1.60s/it, loss=2272.0000, t=992]
Attacking:  11%|█▏        | 57/500 [01:31<11:32,  1.56s/it, loss=2272.0000, t=992]
Attacking:  11%|█▏        | 57/500 [01:31<11:32,  1.56s/it, loss=2176.0000, t=952]
Attacking:  12%|█▏        | 58/500 [01:32<11:28,  1.56s/it, loss=2176.0000, t=952]
Attacking:  12%|█▏        | 58/500 [01:33<11:28,  1.56s/it, loss=2144.0000, t=912]
Attacking:  12%|█▏        | 59/500 [01:34<11:50,  1.61s/it, loss=2144.0000, t=912]
Attacking:  12%|█▏        | 59/500 [01:35<11:50,  1.61s/it, loss=2144.0000, t=928]
Attacking:  12%|█▏        | 60/500 [01:36<11:42,  1.60s/it, loss=2144.0000, t=928]
Attacking:  12%|█▏        | 60/500 [01:36<11:42,  1.60s/it, loss=2128.0000, t=900]
Attacking:  12%|█▏        | 61/500 [01:37<11:57,  1.63s/it, loss=2128.0000, t=900]
Attacking:  12%|█▏        | 61/500 [01:38<11:57,  1.63s/it, loss=2160.0000, t=952]
Attacking:  12%|█▏        | 62/500 [01:39<11:58,  1.64s/it, loss=2160.0000, t=952]
Attacking:  12%|█▏        | 62/500 [01:40<11:58,  1.64s/it, loss=2176.0000, t=952]
Attacking:  13%|█▎        | 63/500 [01:41<12:05,  1.66s/it, loss=2176.0000, t=952]
Attacking:  13%|█▎        | 63/500 [01:41<12:05,  1.66s/it, loss=2112.0000, t=900]
Attacking:  13%|█▎        | 64/500 [01:42<11:45,  1.62s/it, loss=2112.0000, t=900]
Attacking:  13%|█▎        | 64/500 [01:43<11:45,  1.62s/it, loss=2160.0000, t=952]
Attacking:  13%|█▎        | 65/500 [01:44<11:16,  1.56s/it, loss=2160.0000, t=952]
Attacking:  13%|█▎        | 65/500 [01:44<11:16,  1.56s/it, loss=2256.0000, t=992]
Attacking:  13%|█▎        | 66/500 [01:45<11:26,  1.58s/it, loss=2256.0000, t=992]
Attacking:  13%|█▎        | 66/500 [01:46<11:26,  1.58s/it, loss=2240.0000, t=992]
Attacking:  13%|█▎        | 67/500 [01:47<11:21,  1.57s/it, loss=2240.0000, t=992]
Attacking:  13%|█▎        | 67/500 [01:48<11:21,  1.57s/it, loss=2224.0000, t=984]
Attacking:  14%|█▎        | 68/500 [01:48<11:24,  1.58s/it, loss=2224.0000, t=984]
Attacking:  14%|█▎        | 68/500 [01:49<11:24,  1.58s/it, loss=2112.0000, t=900]
Attacking:  14%|█▍        | 69/500 [01:50<11:11,  1.56s/it, loss=2112.0000, t=900]
Attacking:  14%|█▍        | 69/500 [01:51<11:11,  1.56s/it, loss=2112.0000, t=900]
Attacking:  14%|█▍        | 70/500 [01:51<11:05,  1.55s/it, loss=2112.0000, t=900]
Attacking:  14%|█▍        | 70/500 [01:52<11:05,  1.55s/it, loss=2144.0000, t=940]
Attacking:  14%|█▍        | 71/500 [01:53<11:07,  1.56s/it, loss=2144.0000, t=940]
Attacking:  14%|█▍        | 71/500 [01:54<11:07,  1.56s/it, loss=2176.0000, t=972]
Attacking:  14%|█▍        | 72/500 [01:54<10:54,  1.53s/it, loss=2176.0000, t=972]
Attacking:  14%|█▍        | 72/500 [01:55<10:54,  1.53s/it, loss=2112.0000, t=928]
Attacking:  15%|█▍        | 73/500 [01:56<11:02,  1.55s/it, loss=2112.0000, t=928]
Attacking:  15%|█▍        | 73/500 [01:57<11:02,  1.55s/it, loss=2208.0000, t=984]
Attacking:  15%|█▍        | 74/500 [01:58<11:09,  1.57s/it, loss=2208.0000, t=984]
Attacking:  15%|█▍        | 74/500 [01:58<11:09,  1.57s/it, loss=2112.0000, t=912]
Attacking:  15%|█▌        | 75/500 [01:59<11:21,  1.60s/it, loss=2112.0000, t=912]
Attacking:  15%|█▌        | 75/500 [02:00<11:21,  1.60s/it, loss=2128.0000, t=952]
Attacking:  15%|█▌        | 76/500 [02:01<11:04,  1.57s/it, loss=2128.0000, t=952]
Attacking:  15%|█▌        | 76/500 [02:01<11:04,  1.57s/it, loss=2256.0000, t=992]
Attacking:  15%|█▌        | 77/500 [02:02<10:55,  1.55s/it, loss=2256.0000, t=992]
Attacking:  15%|█▌        | 77/500 [02:03<10:55,  1.55s/it, loss=2160.0000, t=972]
Attacking:  16%|█▌        | 78/500 [02:04<10:41,  1.52s/it, loss=2160.0000, t=972]
Attacking:  16%|█▌        | 78/500 [02:04<10:41,  1.52s/it, loss=2176.0000, t=972]
Attacking:  16%|█▌        | 79/500 [02:05<10:38,  1.52s/it, loss=2176.0000, t=972]
Attacking:  16%|█▌        | 79/500 [02:06<10:38,  1.52s/it, loss=2096.0000, t=900]
Attacking:  16%|█▌        | 80/500 [02:07<10:40,  1.53s/it, loss=2096.0000, t=900]
Attacking:  16%|█▌        | 80/500 [02:08<10:40,  1.53s/it, loss=2112.0000, t=912]
Attacking:  16%|█▌        | 81/500 [02:08<10:44,  1.54s/it, loss=2112.0000, t=912]
Attacking:  16%|█▌        | 81/500 [02:09<10:44,  1.54s/it, loss=2128.0000, t=952]
Attacking:  16%|█▋        | 82/500 [02:10<10:41,  1.53s/it, loss=2128.0000, t=952]
Attacking:  16%|█▋        | 82/500 [02:11<10:41,  1.53s/it, loss=2240.0000, t=992]
Attacking:  17%|█▋        | 83/500 [02:12<10:48,  1.56s/it, loss=2240.0000, t=992]
Attacking:  17%|█▋        | 83/500 [02:12<10:48,  1.56s/it, loss=2208.0000, t=1e+3]
Attacking:  17%|█▋        | 84/500 [02:13<10:54,  1.57s/it, loss=2208.0000, t=1e+3]
Attacking:  17%|█▋        | 84/500 [02:14<10:54,  1.57s/it, loss=2208.0000, t=1e+3]
Attacking:  17%|█▋        | 85/500 [02:15<10:53,  1.57s/it, loss=2208.0000, t=1e+3]
Attacking:  17%|█▋        | 85/500 [02:16<10:53,  1.57s/it, loss=2160.0000, t=972] 
Attacking:  17%|█▋        | 86/500 [02:16<11:02,  1.60s/it, loss=2160.0000, t=972]
Attacking:  17%|█▋        | 86/500 [02:17<11:02,  1.60s/it, loss=2144.0000, t=964]
Attacking:  17%|█▋        | 87/500 [02:18<11:10,  1.62s/it, loss=2144.0000, t=964]
Attacking:  17%|█▋        | 87/500 [02:19<11:10,  1.62s/it, loss=2224.0000, t=992]
Attacking:  18%|█▊        | 88/500 [02:20<11:08,  1.62s/it, loss=2224.0000, t=992]
Attacking:  18%|█▊        | 88/500 [02:20<11:08,  1.62s/it, loss=2224.0000, t=992]
Attacking:  18%|█▊        | 89/500 [02:21<11:04,  1.62s/it, loss=2224.0000, t=992]
Attacking:  18%|█▊        | 89/500 [02:22<11:04,  1.62s/it, loss=2112.0000, t=928]
Attacking:  18%|█▊        | 90/500 [02:23<10:52,  1.59s/it, loss=2112.0000, t=928]
Attacking:  18%|█▊        | 90/500 [02:24<10:52,  1.59s/it, loss=2224.0000, t=992]
Attacking:  18%|█▊        | 91/500 [02:24<10:50,  1.59s/it, loss=2224.0000, t=992]
Attacking:  18%|█▊        | 91/500 [02:25<10:50,  1.59s/it, loss=2112.0000, t=940]
Attacking:  18%|█▊        | 92/500 [02:26<10:34,  1.56s/it, loss=2112.0000, t=940]
Attacking:  18%|█▊        | 92/500 [02:27<10:34,  1.56s/it, loss=2128.0000, t=952]
Attacking:  19%|█▊        | 93/500 [02:27<10:27,  1.54s/it, loss=2128.0000, t=952]
Attacking:  19%|█▊        | 93/500 [02:28<10:27,  1.54s/it, loss=2144.0000, t=964]
Attacking:  19%|█▉        | 94/500 [02:29<10:44,  1.59s/it, loss=2144.0000, t=964]
Attacking:  19%|█▉        | 94/500 [02:30<10:44,  1.59s/it, loss=2144.0000, t=964]
Attacking:  19%|█▉        | 95/500 [02:31<10:36,  1.57s/it, loss=2144.0000, t=964]
Attacking:  19%|█▉        | 95/500 [02:31<10:36,  1.57s/it, loss=2080.0000, t=900]
Attacking:  19%|█▉        | 96/500 [02:32<10:28,  1.55s/it, loss=2080.0000, t=900]
Attacking:  19%|█▉        | 96/500 [02:33<10:28,  1.55s/it, loss=2240.0000, t=992]
Attacking:  19%|█▉        | 97/500 [02:34<10:43,  1.60s/it, loss=2240.0000, t=992]
Attacking:  19%|█▉        | 97/500 [02:35<10:43,  1.60s/it, loss=2208.0000, t=992]
Attacking:  20%|█▉        | 98/500 [02:36<10:57,  1.64s/it, loss=2208.0000, t=992]
Attacking:  20%|█▉        | 98/500 [02:36<10:57,  1.64s/it, loss=2144.0000, t=972]
Attacking:  20%|█▉        | 99/500 [02:37<11:00,  1.65s/it, loss=2144.0000, t=972]
Attacking:  20%|█▉        | 99/500 [02:38<11:00,  1.65s/it, loss=2144.0000, t=972]
Attacking:  20%|██        | 100/500 [02:39<10:48,  1.62s/it, loss=2144.0000, t=972]
Attacking:  20%|██        | 100/500 [02:40<10:48,  1.62s/it, loss=2112.0000, t=952]
Attacking:  20%|██        | 101/500 [02:40<10:54,  1.64s/it, loss=2112.0000, t=952]
Attacking:  20%|██        | 101/500 [02:41<10:54,  1.64s/it, loss=2080.0000, t=912]
Attacking:  20%|██        | 102/500 [02:42<10:58,  1.65s/it, loss=2080.0000, t=912]
Attacking:  20%|██        | 102/500 [02:43<10:58,  1.65s/it, loss=2112.0000, t=940]
Attacking:  21%|██        | 103/500 [02:44<10:46,  1.63s/it, loss=2112.0000, t=940]
Attacking:  21%|██        | 103/500 [02:44<10:46,  1.63s/it, loss=2208.0000, t=1e+3]
Attacking:  21%|██        | 104/500 [02:45<10:30,  1.59s/it, loss=2208.0000, t=1e+3]
Attacking:  21%|██        | 104/500 [02:46<10:30,  1.59s/it, loss=2208.0000, t=992] 
Attacking:  21%|██        | 105/500 [02:47<10:07,  1.54s/it, loss=2208.0000, t=992]
Attacking:  21%|██        | 105/500 [02:47<10:07,  1.54s/it, loss=2080.0000, t=900]
Attacking:  21%|██        | 106/500 [02:48<10:02,  1.53s/it, loss=2080.0000, t=900]
Attacking:  21%|██        | 106/500 [02:49<10:02,  1.53s/it, loss=2080.0000, t=900]
Attacking:  21%|██▏       | 107/500 [02:50<09:48,  1.50s/it, loss=2080.0000, t=900]
Attacking:  21%|██▏       | 107/500 [02:50<09:48,  1.50s/it, loss=2096.0000, t=928]
Attacking:  22%|██▏       | 108/500 [02:51<09:38,  1.48s/it, loss=2096.0000, t=928]
Attacking:  22%|██▏       | 108/500 [02:52<09:38,  1.48s/it, loss=2208.0000, t=992]
Attacking:  22%|██▏       | 109/500 [02:52<09:30,  1.46s/it, loss=2208.0000, t=992]
Attacking:  22%|██▏       | 109/500 [02:53<09:30,  1.46s/it, loss=2208.0000, t=992]
Attacking:  22%|██▏       | 110/500 [02:54<09:28,  1.46s/it, loss=2208.0000, t=992]
Attacking:  22%|██▏       | 110/500 [02:55<09:28,  1.46s/it, loss=2176.0000, t=984]
Attacking:  22%|██▏       | 111/500 [02:55<09:35,  1.48s/it, loss=2176.0000, t=984]
Attacking:  22%|██▏       | 111/500 [02:56<09:35,  1.48s/it, loss=2080.0000, t=900]
Attacking:  22%|██▏       | 112/500 [02:57<09:53,  1.53s/it, loss=2080.0000, t=900]
Attacking:  22%|██▏       | 112/500 [02:58<09:53,  1.53s/it, loss=2144.0000, t=972]
Attacking:  23%|██▎       | 113/500 [02:59<09:44,  1.51s/it, loss=2144.0000, t=972]
Attacking:  23%|██▎       | 113/500 [02:59<09:44,  1.51s/it, loss=2096.0000, t=928]
Attacking:  23%|██▎       | 114/500 [03:00<09:51,  1.53s/it, loss=2096.0000, t=928]
Attacking:  23%|██▎       | 114/500 [03:01<09:51,  1.53s/it, loss=2192.0000, t=1e+3]
Attacking:  23%|██▎       | 115/500 [03:02<10:06,  1.58s/it, loss=2192.0000, t=1e+3]
Attacking:  23%|██▎       | 115/500 [03:03<10:06,  1.58s/it, loss=2112.0000, t=952] 
Attacking:  23%|██▎       | 116/500 [03:03<10:10,  1.59s/it, loss=2112.0000, t=952]
Attacking:  23%|██▎       | 116/500 [03:04<10:10,  1.59s/it, loss=2080.0000, t=928]
Attacking:  23%|██▎       | 117/500 [03:05<10:11,  1.60s/it, loss=2080.0000, t=928]
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+Max Diff: 0.501961
+Mean Diff: 0.246552
+Saved adversarial image to attacked/images/girl.jpg
+Saved loss curve to attacked/loss_curve/girl_loss.png
+[GPU 2] Stage 3/3: Test
+Loading models for testing girl...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for girl...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 80.15it/s]
+Saved video to attacked/videos/girl.mp4
+Saved frames to attacked/frames/girl
+[GPU 2] Finished girl.jpg
+======================================
+[GPU 2] Processing goat.jpg (Image 20/50)
+======================================
+[GPU 2] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 2] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  21%|██        | 106/500 [02:48<09:43,  1.48s/it, loss=2416.0000, t=984]
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Attacking:  24%|██▎       | 118/500 [03:06<10:15,  1.61s/it, loss=2384.0000, t=964]
Attacking:  24%|██▎       | 118/500 [03:07<10:15,  1.61s/it, loss=2400.0000, t=972]
Attacking:  24%|██▍       | 119/500 [03:08<10:22,  1.63s/it, loss=2400.0000, t=972]
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Attacking:  24%|██▍       | 120/500 [03:10<10:33,  1.67s/it, loss=2384.0000, t=972]
Attacking:  24%|██▍       | 120/500 [03:11<10:33,  1.67s/it, loss=2496.0000, t=1e+3]
Attacking:  24%|██▍       | 121/500 [03:12<10:39,  1.69s/it, loss=2496.0000, t=1e+3]
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Attacking: 100%|█████████▉| 499/500 [12:53<00:01,  1.51s/it, loss=2336.0000, t=952]
Attacking: 100%|██████████| 500/500 [12:54<00:00,  1.49s/it, loss=2336.0000, t=952]
Attacking: 100%|██████████| 500/500 [12:54<00:00,  1.55s/it, loss=2336.0000, t=952]
+Max Diff: 0.501961
+Mean Diff: 0.266795
+Saved adversarial image to attacked/images/goat.jpg
+Saved loss curve to attacked/loss_curve/goat_loss.png
+[GPU 2] Stage 3/3: Test
+Loading models for testing goat...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for goat...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 124.75it/s]
+Saved video to attacked/videos/goat.mp4
+Saved frames to attacked/frames/goat
+[GPU 2] Finished goat.jpg
+[GPU 2] All assigned tasks completed.
diff --git a/experiments/cfg3_eps64/logs/gpu_3.log b/experiments/cfg3_eps64/logs/gpu_3.log
new file mode 100644
index 0000000000000000000000000000000000000000..bccfb254b66da834e67957810aa7937855423e16
--- /dev/null
+++ b/experiments/cfg3_eps64/logs/gpu_3.log
@@ -0,0 +1,488 @@
+[GPU 3] Starting work on images 21 to 27
+======================================
+[GPU 3] Processing golf.jpg (Image 21/50)
+======================================
+[GPU 3] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 3] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   5%|▌         | 27/500 [00:40<12:12,  1.55s/it, loss=2288.0000, t=900]
Attacking:   6%|▌         | 28/500 [00:41<12:10,  1.55s/it, loss=2288.0000, t=900]
Attacking:   6%|▌         | 28/500 [00:42<12:10,  1.55s/it, loss=2384.0000, t=1e+3]
Attacking:   6%|▌         | 29/500 [00:43<12:00,  1.53s/it, loss=2384.0000, t=1e+3]
Attacking:   6%|▌         | 29/500 [00:43<12:00,  1.53s/it, loss=2288.0000, t=900] 
Attacking:   6%|▌         | 30/500 [00:44<11:55,  1.52s/it, loss=2288.0000, t=900]
Attacking:   6%|▌         | 30/500 [00:45<11:55,  1.52s/it, loss=2400.0000, t=1e+3]
Attacking:   6%|▌         | 31/500 [00:46<12:15,  1.57s/it, loss=2400.0000, t=1e+3]
Attacking:   6%|▌         | 31/500 [00:47<12:15,  1.57s/it, loss=2320.0000, t=952] 
Attacking:   6%|▋         | 32/500 [00:48<12:29,  1.60s/it, loss=2320.0000, t=952]
Attacking:   6%|▋         | 32/500 [00:48<12:29,  1.60s/it, loss=2304.0000, t=940]
Attacking:   7%|▋         | 33/500 [00:49<12:35,  1.62s/it, loss=2304.0000, t=940]
Attacking:   7%|▋         | 33/500 [00:50<12:35,  1.62s/it, loss=2304.0000, t=984]
Attacking:   7%|▋         | 34/500 [00:51<12:31,  1.61s/it, loss=2304.0000, t=984]
Attacking:   7%|▋         | 34/500 [00:52<12:31,  1.61s/it, loss=2320.0000, t=964]
Attacking:   7%|▋         | 35/500 [00:52<12:17,  1.59s/it, loss=2320.0000, t=964]
Attacking:   7%|▋         | 35/500 [00:53<12:17,  1.59s/it, loss=2368.0000, t=1e+3]
Attacking:   7%|▋         | 36/500 [00:54<12:06,  1.57s/it, loss=2368.0000, t=1e+3]
Attacking:   7%|▋         | 36/500 [00:55<12:06,  1.57s/it, loss=2272.0000, t=940] 
Attacking:   7%|▋         | 37/500 [00:55<11:53,  1.54s/it, loss=2272.0000, t=940]
Attacking:   7%|▋         | 37/500 [00:56<11:53,  1.54s/it, loss=2336.0000, t=972]
Attacking:   8%|▊         | 38/500 [00:57<11:37,  1.51s/it, loss=2336.0000, t=972]
Attacking:   8%|▊         | 38/500 [00:57<11:37,  1.51s/it, loss=2256.0000, t=912]
Attacking:   8%|▊         | 39/500 [00:58<11:25,  1.49s/it, loss=2256.0000, t=912]
Attacking:   8%|▊         | 39/500 [00:59<11:25,  1.49s/it, loss=2288.0000, t=984]
Attacking:   8%|▊         | 40/500 [01:00<11:19,  1.48s/it, loss=2288.0000, t=984]
Attacking:   8%|▊         | 40/500 [01:00<11:19,  1.48s/it, loss=2288.0000, t=912]
Attacking:   8%|▊         | 41/500 [01:01<11:13,  1.47s/it, loss=2288.0000, t=912]
Attacking:   8%|▊         | 41/500 [01:02<11:13,  1.47s/it, loss=2272.0000, t=940]
Attacking:   8%|▊         | 42/500 [01:03<11:10,  1.46s/it, loss=2272.0000, t=940]
Attacking:   8%|▊         | 42/500 [01:03<11:10,  1.46s/it, loss=2272.0000, t=952]
Attacking:   9%|▊         | 43/500 [01:04<11:12,  1.47s/it, loss=2272.0000, t=952]
Attacking:   9%|▊         | 43/500 [01:05<11:12,  1.47s/it, loss=2256.0000, t=900]
Attacking:   9%|▉         | 44/500 [01:06<11:00,  1.45s/it, loss=2256.0000, t=900]
Attacking:   9%|▉         | 44/500 [01:06<11:00,  1.45s/it, loss=2288.0000, t=964]
Attacking:   9%|▉         | 45/500 [01:07<10:59,  1.45s/it, loss=2288.0000, t=964]
Attacking:   9%|▉         | 45/500 [01:08<10:59,  1.45s/it, loss=2320.0000, t=972]
Attacking:   9%|▉         | 46/500 [01:08<10:52,  1.44s/it, loss=2320.0000, t=972]
Attacking:   9%|▉         | 46/500 [01:09<10:52,  1.44s/it, loss=2288.0000, t=964]
Attacking:   9%|▉         | 47/500 [01:10<11:04,  1.47s/it, loss=2288.0000, t=964]
Attacking:   9%|▉         | 47/500 [01:11<11:04,  1.47s/it, loss=2320.0000, t=964]
Attacking:  10%|▉         | 48/500 [01:12<11:11,  1.48s/it, loss=2320.0000, t=964]
Attacking:  10%|▉         | 48/500 [01:12<11:11,  1.48s/it, loss=2336.0000, t=1e+3]
Attacking:  10%|▉         | 49/500 [01:13<11:30,  1.53s/it, loss=2336.0000, t=1e+3]
Attacking:  10%|▉         | 49/500 [01:14<11:30,  1.53s/it, loss=2288.0000, t=964] 
Attacking:  10%|█         | 50/500 [01:15<11:31,  1.54s/it, loss=2288.0000, t=964]
Attacking:  10%|█         | 50/500 [01:15<11:31,  1.54s/it, loss=2256.0000, t=952]
Attacking:  10%|█         | 51/500 [01:16<11:26,  1.53s/it, loss=2256.0000, t=952]
Attacking:  10%|█         | 51/500 [01:17<11:26,  1.53s/it, loss=2240.0000, t=900]
Attacking:  10%|█         | 52/500 [01:18<11:13,  1.50s/it, loss=2240.0000, t=900]
Attacking:  10%|█         | 52/500 [01:18<11:13,  1.50s/it, loss=2224.0000, t=900]
Attacking:  11%|█         | 53/500 [01:19<10:58,  1.47s/it, loss=2224.0000, t=900]
Attacking:  11%|█         | 53/500 [01:20<10:58,  1.47s/it, loss=2272.0000, t=952]
Attacking:  11%|█         | 54/500 [01:20<10:50,  1.46s/it, loss=2272.0000, t=952]
Attacking:  11%|█         | 54/500 [01:21<10:50,  1.46s/it, loss=2256.0000, t=940]
Attacking:  11%|█         | 55/500 [01:22<10:57,  1.48s/it, loss=2256.0000, t=940]
Attacking:  11%|█         | 55/500 [01:23<10:57,  1.48s/it, loss=2272.0000, t=984]
Attacking:  11%|█         | 56/500 [01:24<11:10,  1.51s/it, loss=2272.0000, t=984]
Attacking:  11%|█         | 56/500 [01:24<11:10,  1.51s/it, loss=2288.0000, t=964]
Attacking:  11%|█▏        | 57/500 [01:25<11:10,  1.51s/it, loss=2288.0000, t=964]
Attacking:  11%|█▏        | 57/500 [01:26<11:10,  1.51s/it, loss=2256.0000, t=952]
Attacking:  12%|█▏        | 58/500 [01:27<11:03,  1.50s/it, loss=2256.0000, t=952]
Attacking:  12%|█▏        | 58/500 [01:28<11:03,  1.50s/it, loss=2240.0000, t=912]
Attacking:  12%|█▏        | 59/500 [01:29<12:24,  1.69s/it, loss=2240.0000, t=912]
Attacking:  12%|█▏        | 59/500 [01:29<12:24,  1.69s/it, loss=2256.0000, t=952]
Attacking:  12%|█▏        | 60/500 [01:30<12:03,  1.64s/it, loss=2256.0000, t=952]
Attacking:  12%|█▏        | 60/500 [01:31<12:03,  1.64s/it, loss=2224.0000, t=912]
Attacking:  12%|█▏        | 61/500 [01:32<11:43,  1.60s/it, loss=2224.0000, t=912]
Attacking:  12%|█▏        | 61/500 [01:32<11:43,  1.60s/it, loss=2336.0000, t=1e+3]
Attacking:  12%|█▏        | 62/500 [01:33<11:26,  1.57s/it, loss=2336.0000, t=1e+3]
Attacking:  12%|█▏        | 62/500 [01:34<11:26,  1.57s/it, loss=2272.0000, t=972] 
Attacking:  13%|█▎        | 63/500 [01:35<11:26,  1.57s/it, loss=2272.0000, t=972]
Attacking:  13%|█▎        | 63/500 [01:36<11:26,  1.57s/it, loss=2272.0000, t=992]
Attacking:  13%|█▎        | 64/500 [01:36<11:20,  1.56s/it, loss=2272.0000, t=992]
Attacking:  13%|█▎        | 64/500 [01:37<11:20,  1.56s/it, loss=2256.0000, t=964]
Attacking:  13%|█▎        | 65/500 [01:38<11:14,  1.55s/it, loss=2256.0000, t=964]
Attacking:  13%|█▎        | 65/500 [01:39<11:14,  1.55s/it, loss=2208.0000, t=900]
Attacking:  13%|█▎        | 66/500 [01:39<11:18,  1.56s/it, loss=2208.0000, t=900]
Attacking:  13%|█▎        | 66/500 [01:40<11:18,  1.56s/it, loss=2224.0000, t=900]
Attacking:  13%|█▎        | 67/500 [01:41<11:17,  1.56s/it, loss=2224.0000, t=900]
Attacking:  13%|█▎        | 67/500 [01:42<11:17,  1.56s/it, loss=2304.0000, t=972]
Attacking:  14%|█▎        | 68/500 [01:43<11:25,  1.59s/it, loss=2304.0000, t=972]
Attacking:  14%|█▎        | 68/500 [01:43<11:25,  1.59s/it, loss=2240.0000, t=952]
Attacking:  14%|█▍        | 69/500 [01:44<11:20,  1.58s/it, loss=2240.0000, t=952]
Attacking:  14%|█▍        | 69/500 [01:45<11:20,  1.58s/it, loss=2320.0000, t=1e+3]
Attacking:  14%|█▍        | 70/500 [01:46<11:33,  1.61s/it, loss=2320.0000, t=1e+3]
Attacking:  14%|█▍        | 70/500 [01:47<11:33,  1.61s/it, loss=2208.0000, t=900] 
Attacking:  14%|█▍        | 71/500 [01:48<11:27,  1.60s/it, loss=2208.0000, t=900]
Attacking:  14%|█▍        | 71/500 [01:48<11:27,  1.60s/it, loss=2256.0000, t=952]
Attacking:  14%|█▍        | 72/500 [01:49<11:37,  1.63s/it, loss=2256.0000, t=952]
Attacking:  14%|█▍        | 72/500 [01:50<11:37,  1.63s/it, loss=2224.0000, t=928]
Attacking:  15%|█▍        | 73/500 [01:51<11:41,  1.64s/it, loss=2224.0000, t=928]
Attacking:  15%|█▍        | 73/500 [01:52<11:41,  1.64s/it, loss=2272.0000, t=972]
Attacking:  15%|█▍        | 74/500 [01:53<11:55,  1.68s/it, loss=2272.0000, t=972]
Attacking:  15%|█▍        | 74/500 [01:54<11:55,  1.68s/it, loss=2272.0000, t=992]
Attacking:  15%|█▌        | 75/500 [01:54<12:00,  1.70s/it, loss=2272.0000, t=992]
Attacking:  15%|█▌        | 75/500 [01:55<12:00,  1.70s/it, loss=2224.0000, t=928]
Attacking:  15%|█▌        | 76/500 [01:56<11:51,  1.68s/it, loss=2224.0000, t=928]
Attacking:  15%|█▌        | 76/500 [01:57<11:51,  1.68s/it, loss=2256.0000, t=964]
Attacking:  15%|█▌        | 77/500 [01:58<11:41,  1.66s/it, loss=2256.0000, t=964]
Attacking:  15%|█▌        | 77/500 [01:58<11:41,  1.66s/it, loss=2240.0000, t=984]
Attacking:  16%|█▌        | 78/500 [01:59<11:34,  1.65s/it, loss=2240.0000, t=984]
Attacking:  16%|█▌        | 78/500 [02:00<11:34,  1.65s/it, loss=2208.0000, t=928]
Attacking:  16%|█▌        | 79/500 [02:01<11:45,  1.67s/it, loss=2208.0000, t=928]
Attacking:  16%|█▌        | 79/500 [02:02<11:45,  1.67s/it, loss=2272.0000, t=972]
Attacking:  16%|█▌        | 80/500 [02:03<11:36,  1.66s/it, loss=2272.0000, t=972]
Attacking:  16%|█▌        | 80/500 [02:03<11:36,  1.66s/it, loss=2208.0000, t=912]
Attacking:  16%|█▌        | 81/500 [02:04<11:35,  1.66s/it, loss=2208.0000, t=912]
Attacking:  16%|█▌        | 81/500 [02:05<11:35,  1.66s/it, loss=2272.0000, t=992]
Attacking:  16%|█▋        | 82/500 [02:06<11:28,  1.65s/it, loss=2272.0000, t=992]
Attacking:  16%|█▋        | 82/500 [02:07<11:28,  1.65s/it, loss=2224.0000, t=984]
Attacking:  17%|█▋        | 83/500 [02:08<11:31,  1.66s/it, loss=2224.0000, t=984]
Attacking:  17%|█▋        | 83/500 [02:08<11:31,  1.66s/it, loss=2272.0000, t=972]
Attacking:  17%|█▋        | 84/500 [02:09<11:07,  1.61s/it, loss=2272.0000, t=972]
Attacking:  17%|█▋        | 84/500 [02:10<11:07,  1.61s/it, loss=2256.0000, t=992]
Attacking:  17%|█▋        | 85/500 [02:11<11:09,  1.61s/it, loss=2256.0000, t=992]
Attacking:  17%|█▋        | 85/500 [02:11<11:09,  1.61s/it, loss=2256.0000, t=992]
Attacking:  17%|█▋        | 86/500 [02:12<11:05,  1.61s/it, loss=2256.0000, t=992]
Attacking:  17%|█▋        | 86/500 [02:13<11:05,  1.61s/it, loss=2208.0000, t=912]
Attacking:  17%|█▋        | 87/500 [02:14<11:08,  1.62s/it, loss=2208.0000, t=912]
Attacking:  17%|█▋        | 87/500 [02:15<11:08,  1.62s/it, loss=2256.0000, t=964]
Attacking:  18%|█▊        | 88/500 [02:16<11:19,  1.65s/it, loss=2256.0000, t=964]
Attacking:  18%|█▊        | 88/500 [02:16<11:19,  1.65s/it, loss=2272.0000, t=972]
Attacking:  18%|█▊        | 89/500 [02:17<11:06,  1.62s/it, loss=2272.0000, t=972]
Attacking:  18%|█▊        | 89/500 [02:18<11:06,  1.62s/it, loss=2256.0000, t=992]
Attacking:  18%|█▊        | 90/500 [02:19<10:58,  1.61s/it, loss=2256.0000, t=992]
Attacking:  18%|█▊        | 90/500 [02:20<10:58,  1.61s/it, loss=2208.0000, t=912]
Attacking:  18%|█▊        | 91/500 [02:20<10:54,  1.60s/it, loss=2208.0000, t=912]
Attacking:  18%|█▊        | 91/500 [02:21<10:54,  1.60s/it, loss=2272.0000, t=972]
Attacking:  18%|█▊        | 92/500 [02:22<11:00,  1.62s/it, loss=2272.0000, t=972]
Attacking:  18%|█▊        | 92/500 [02:23<11:00,  1.62s/it, loss=2208.0000, t=928]
Attacking:  19%|█▊        | 93/500 [02:24<10:58,  1.62s/it, loss=2208.0000, t=928]
Attacking:  19%|█▊        | 93/500 [02:24<10:58,  1.62s/it, loss=2224.0000, t=952]
Attacking:  19%|█▉        | 94/500 [02:25<10:53,  1.61s/it, loss=2224.0000, t=952]
Attacking:  19%|█▉        | 94/500 [02:26<10:53,  1.61s/it, loss=2192.0000, t=912]
Attacking:  19%|█▉        | 95/500 [02:27<10:58,  1.63s/it, loss=2192.0000, t=912]
Attacking:  19%|█▉        | 95/500 [02:28<10:58,  1.63s/it, loss=2256.0000, t=992]
Attacking:  19%|█▉        | 96/500 [02:29<11:07,  1.65s/it, loss=2256.0000, t=992]
Attacking:  19%|█▉        | 96/500 [02:29<11:07,  1.65s/it, loss=2288.0000, t=1e+3]
Attacking:  19%|█▉        | 97/500 [02:30<11:03,  1.65s/it, loss=2288.0000, t=1e+3]
Attacking:  19%|█▉        | 97/500 [02:31<11:03,  1.65s/it, loss=2256.0000, t=992] 
Attacking:  20%|█▉        | 98/500 [02:32<11:09,  1.67s/it, loss=2256.0000, t=992]
Attacking:  20%|█▉        | 98/500 [02:33<11:09,  1.67s/it, loss=2224.0000, t=952]
Attacking:  20%|█▉        | 99/500 [02:34<11:07,  1.67s/it, loss=2224.0000, t=952]
Attacking:  20%|█▉        | 99/500 [02:34<11:07,  1.67s/it, loss=2224.0000, t=984]
Attacking:  20%|██        | 100/500 [02:35<11:02,  1.66s/it, loss=2224.0000, t=984]
Attacking:  20%|██        | 100/500 [02:36<11:02,  1.66s/it, loss=2240.0000, t=992]
Attacking:  20%|██        | 101/500 [02:37<11:08,  1.68s/it, loss=2240.0000, t=992]
Attacking:  20%|██        | 101/500 [02:38<11:08,  1.68s/it, loss=2240.0000, t=952]
Attacking:  20%|██        | 102/500 [02:39<11:00,  1.66s/it, loss=2240.0000, t=952]
Attacking:  20%|██        | 102/500 [02:39<11:00,  1.66s/it, loss=2256.0000, t=972]
Attacking:  21%|██        | 103/500 [02:40<11:05,  1.68s/it, loss=2256.0000, t=972]
Attacking:  21%|██        | 103/500 [02:41<11:05,  1.68s/it, loss=2224.0000, t=984]
Attacking:  21%|██        | 104/500 [02:42<11:11,  1.70s/it, loss=2224.0000, t=984]
Attacking:  21%|██        | 104/500 [02:43<11:11,  1.70s/it, loss=2256.0000, t=972]
Attacking:  21%|██        | 105/500 [02:44<11:06,  1.69s/it, loss=2256.0000, t=972]
Attacking:  21%|██        | 105/500 [02:45<11:06,  1.69s/it, loss=2256.0000, t=972]
Attacking:  21%|██        | 106/500 [02:45<11:11,  1.70s/it, loss=2256.0000, t=972]
Attacking:  21%|██        | 106/500 [02:46<11:11,  1.70s/it, loss=2256.0000, t=992]
Attacking:  21%|██▏       | 107/500 [02:47<11:00,  1.68s/it, loss=2256.0000, t=992]
Attacking:  21%|██▏       | 107/500 [02:48<11:00,  1.68s/it, loss=2208.0000, t=940]
Attacking:  22%|██▏       | 108/500 [02:49<10:57,  1.68s/it, loss=2208.0000, t=940]
Attacking:  22%|██▏       | 108/500 [02:49<10:57,  1.68s/it, loss=2192.0000, t=912]
Attacking:  22%|██▏       | 109/500 [02:50<10:45,  1.65s/it, loss=2192.0000, t=912]
Attacking:  22%|██▏       | 109/500 [02:51<10:45,  1.65s/it, loss=2256.0000, t=992]
Attacking:  22%|██▏       | 110/500 [02:52<10:24,  1.60s/it, loss=2256.0000, t=992]
Attacking:  22%|██▏       | 110/500 [02:53<10:24,  1.60s/it, loss=2208.0000, t=952]
Attacking:  22%|██▏       | 111/500 [02:53<10:13,  1.58s/it, loss=2208.0000, t=952]
Attacking:  22%|██▏       | 111/500 [02:54<10:13,  1.58s/it, loss=2240.0000, t=972]
Attacking:  22%|██▏       | 112/500 [02:55<10:34,  1.64s/it, loss=2240.0000, t=972]
Attacking:  22%|██▏       | 112/500 [02:56<10:34,  1.64s/it, loss=2240.0000, t=972]
Attacking:  23%|██▎       | 113/500 [02:57<10:33,  1.64s/it, loss=2240.0000, t=972]
Attacking:  23%|██▎       | 113/500 [02:58<10:33,  1.64s/it, loss=2208.0000, t=952]
Attacking:  23%|██▎       | 114/500 [02:58<10:40,  1.66s/it, loss=2208.0000, t=952]
Attacking:  23%|██▎       | 114/500 [02:59<10:40,  1.66s/it, loss=2208.0000, t=940]
Attacking:  23%|██▎       | 115/500 [03:00<10:43,  1.67s/it, loss=2208.0000, t=940]
Attacking:  23%|██▎       | 115/500 [03:01<10:43,  1.67s/it, loss=2240.0000, t=964]
Attacking:  23%|██▎       | 116/500 [03:02<10:48,  1.69s/it, loss=2240.0000, t=964]
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Attacking: 100%|██████████| 500/500 [13:28<00:00,  1.62s/it, loss=2144.0000, t=952]
+Max Diff: 0.501961
+Mean Diff: 0.250869
+Saved adversarial image to attacked/images/golf.jpg
+Saved loss curve to attacked/loss_curve/golf_loss.png
+[GPU 3] Stage 3/3: Test
+Loading models for testing golf...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for golf...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 49.50it/s]
+Saved video to attacked/videos/golf.mp4
+Saved frames to attacked/frames/golf
+[GPU 3] Finished golf.jpg
+======================================
+[GPU 3] Processing hike.jpg (Image 22/50)
+======================================
+[GPU 3] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 3] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  20%|██        | 100/500 [02:45<10:17,  1.54s/it, loss=2272.0000, t=992]
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Attacking:  20%|██        | 102/500 [02:48<09:55,  1.50s/it, loss=2176.0000, t=900]
Attacking:  20%|██        | 102/500 [02:49<09:55,  1.50s/it, loss=2192.0000, t=940]
Attacking:  21%|██        | 103/500 [02:50<09:49,  1.49s/it, loss=2192.0000, t=940]
Attacking:  21%|██        | 103/500 [02:50<09:49,  1.49s/it, loss=2176.0000, t=912]
Attacking:  21%|██        | 104/500 [02:51<09:41,  1.47s/it, loss=2176.0000, t=912]
Attacking:  21%|██        | 104/500 [02:52<09:41,  1.47s/it, loss=2192.0000, t=940]
Attacking:  21%|██        | 105/500 [02:53<09:41,  1.47s/it, loss=2192.0000, t=940]
Attacking:  21%|██        | 105/500 [02:53<09:41,  1.47s/it, loss=2224.0000, t=984]
Attacking:  21%|██        | 106/500 [02:54<09:53,  1.51s/it, loss=2224.0000, t=984]
Attacking:  21%|██        | 106/500 [02:55<09:53,  1.51s/it, loss=2192.0000, t=928]
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Attacking:  22%|██▏       | 110/500 [03:01<09:56,  1.53s/it, loss=2208.0000, t=972]
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Attacking:  23%|██▎       | 116/500 [03:10<10:16,  1.61s/it, loss=2192.0000, t=928]
Attacking:  23%|██▎       | 116/500 [03:11<10:16,  1.61s/it, loss=2176.0000, t=928]
Attacking:  23%|██▎       | 117/500 [03:12<10:32,  1.65s/it, loss=2176.0000, t=928]
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Attacking:  24%|██▎       | 118/500 [03:13<10:38,  1.67s/it, loss=2192.0000, t=952]
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Attacking:  24%|██▍       | 119/500 [03:16<10:27,  1.65s/it, loss=2176.0000, t=900]
Attacking:  24%|██▍       | 120/500 [03:17<10:56,  1.73s/it, loss=2176.0000, t=900]
Attacking:  24%|██▍       | 120/500 [03:18<10:56,  1.73s/it, loss=2272.0000, t=1e+3]
Attacking:  24%|██▍       | 121/500 [03:19<10:44,  1.70s/it, loss=2272.0000, t=1e+3]
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Attacking:  25%|██▍       | 124/500 [03:24<10:15,  1.64s/it, loss=2224.0000, t=984]
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Attacking:  25%|██▌       | 127/500 [03:28<10:02,  1.61s/it, loss=2272.0000, t=1e+3]
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Attacking:  26%|██▌       | 128/500 [03:30<09:54,  1.60s/it, loss=2192.0000, t=964]
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Attacking:  83%|████████▎ | 417/500 [10:52<02:00,  1.45s/it, loss=2128.0000, t=940]
Attacking:  83%|████████▎ | 417/500 [10:52<02:00,  1.45s/it, loss=2128.0000, t=900]
Attacking:  84%|████████▎ | 418/500 [10:53<01:57,  1.43s/it, loss=2128.0000, t=900]
Attacking:  84%|████████▎ | 418/500 [10:54<01:57,  1.43s/it, loss=2128.0000, t=940]
Attacking:  84%|████████▍ | 419/500 [10:54<01:55,  1.43s/it, loss=2128.0000, t=940]
Attacking:  84%|████████▍ | 419/500 [10:55<01:55,  1.43s/it, loss=2128.0000, t=900]
Attacking:  84%|████████▍ | 420/500 [10:56<01:53,  1.42s/it, loss=2128.0000, t=900]
Attacking:  84%|████████▍ | 420/500 [10:56<01:53,  1.42s/it, loss=2224.0000, t=1e+3]
Attacking:  84%|████████▍ | 421/500 [10:57<01:53,  1.44s/it, loss=2224.0000, t=1e+3]
Attacking:  84%|████████▍ | 421/500 [10:58<01:53,  1.44s/it, loss=2144.0000, t=912] 
Attacking:  84%|████████▍ | 422/500 [10:59<01:54,  1.47s/it, loss=2144.0000, t=912]
Attacking:  84%|████████▍ | 422/500 [11:00<01:54,  1.47s/it, loss=2176.0000, t=984]
Attacking:  85%|████████▍ | 423/500 [11:01<01:59,  1.55s/it, loss=2176.0000, t=984]
Attacking:  85%|████████▍ | 423/500 [11:01<01:59,  1.55s/it, loss=2128.0000, t=900]
Attacking:  85%|████████▍ | 424/500 [11:02<01:56,  1.54s/it, loss=2128.0000, t=900]
Attacking:  85%|████████▍ | 424/500 [11:03<01:56,  1.54s/it, loss=2128.0000, t=928]
Attacking:  85%|████████▌ | 425/500 [11:04<01:58,  1.58s/it, loss=2128.0000, t=928]
Attacking:  85%|████████▌ | 425/500 [11:04<01:58,  1.58s/it, loss=2160.0000, t=972]
Attacking:  85%|████████▌ | 426/500 [11:05<01:57,  1.58s/it, loss=2160.0000, t=972]
Attacking:  85%|████████▌ | 426/500 [11:06<01:57,  1.58s/it, loss=2160.0000, t=972]
Attacking:  85%|████████▌ | 427/500 [11:07<01:57,  1.61s/it, loss=2160.0000, t=972]
Attacking:  85%|████████▌ | 427/500 [11:08<01:57,  1.61s/it, loss=2128.0000, t=952]
Attacking:  86%|████████▌ | 428/500 [11:09<01:59,  1.66s/it, loss=2128.0000, t=952]
Attacking:  86%|████████▌ | 428/500 [11:09<01:59,  1.66s/it, loss=2144.0000, t=940]
Attacking:  86%|████████▌ | 429/500 [11:10<01:53,  1.60s/it, loss=2144.0000, t=940]
Attacking:  86%|████████▌ | 429/500 [11:11<01:53,  1.60s/it, loss=2176.0000, t=984]
Attacking:  86%|████████▌ | 430/500 [11:12<01:53,  1.62s/it, loss=2176.0000, t=984]
Attacking:  86%|████████▌ | 430/500 [11:13<01:53,  1.62s/it, loss=2144.0000, t=912]
Attacking:  86%|████████▌ | 431/500 [11:14<01:53,  1.64s/it, loss=2144.0000, t=912]
Attacking:  86%|████████▌ | 431/500 [11:14<01:53,  1.64s/it, loss=2224.0000, t=1e+3]
Attacking:  86%|████████▋ | 432/500 [11:15<01:49,  1.62s/it, loss=2224.0000, t=1e+3]
Attacking:  86%|████████▋ | 432/500 [11:16<01:49,  1.62s/it, loss=2192.0000, t=992] 
Attacking:  87%|████████▋ | 433/500 [11:17<01:46,  1.59s/it, loss=2192.0000, t=992]
Attacking:  87%|████████▋ | 433/500 [11:17<01:46,  1.59s/it, loss=2144.0000, t=972]
Attacking:  87%|████████▋ | 434/500 [11:18<01:47,  1.63s/it, loss=2144.0000, t=972]
Attacking:  87%|████████▋ | 434/500 [11:19<01:47,  1.63s/it, loss=2160.0000, t=972]
Attacking:  87%|████████▋ | 435/500 [11:20<01:46,  1.64s/it, loss=2160.0000, t=972]
Attacking:  87%|████████▋ | 435/500 [11:21<01:46,  1.64s/it, loss=2128.0000, t=952]
Attacking:  87%|████████▋ | 436/500 [11:22<01:43,  1.62s/it, loss=2128.0000, t=952]
Attacking:  87%|████████▋ | 436/500 [11:23<01:43,  1.62s/it, loss=2176.0000, t=984]
Attacking:  87%|████████▋ | 437/500 [11:24<01:47,  1.70s/it, loss=2176.0000, t=984]
Attacking:  87%|████████▋ | 437/500 [11:24<01:47,  1.70s/it, loss=2160.0000, t=972]
Attacking:  88%|████████▊ | 438/500 [11:25<01:46,  1.72s/it, loss=2160.0000, t=972]
Attacking:  88%|████████▊ | 438/500 [11:26<01:46,  1.72s/it, loss=2144.0000, t=952]
Attacking:  88%|████████▊ | 439/500 [11:27<01:41,  1.67s/it, loss=2144.0000, t=952]
Attacking:  88%|████████▊ | 439/500 [11:28<01:41,  1.67s/it, loss=2144.0000, t=940]
Attacking:  88%|████████▊ | 440/500 [11:28<01:39,  1.66s/it, loss=2144.0000, t=940]
Attacking:  88%|████████▊ | 440/500 [11:29<01:39,  1.66s/it, loss=2144.0000, t=964]
Attacking:  88%|████████▊ | 441/500 [11:30<01:37,  1.65s/it, loss=2144.0000, t=964]
Attacking:  88%|████████▊ | 441/500 [11:31<01:37,  1.65s/it, loss=2160.0000, t=972]
Attacking:  88%|████████▊ | 442/500 [11:32<01:32,  1.59s/it, loss=2160.0000, t=972]
Attacking:  88%|████████▊ | 442/500 [11:32<01:32,  1.59s/it, loss=2144.0000, t=940]
Attacking:  89%|████████▊ | 443/500 [11:33<01:28,  1.56s/it, loss=2144.0000, t=940]
Attacking:  89%|████████▊ | 443/500 [11:34<01:28,  1.56s/it, loss=2160.0000, t=972]
Attacking:  89%|████████▉ | 444/500 [11:34<01:25,  1.53s/it, loss=2160.0000, t=972]
Attacking:  89%|████████▉ | 444/500 [11:35<01:25,  1.53s/it, loss=2144.0000, t=928]
Attacking:  89%|████████▉ | 445/500 [11:36<01:23,  1.51s/it, loss=2144.0000, t=928]
Attacking:  89%|████████▉ | 445/500 [11:37<01:23,  1.51s/it, loss=2144.0000, t=952]
Attacking:  89%|████████▉ | 446/500 [11:37<01:19,  1.48s/it, loss=2144.0000, t=952]
Attacking:  89%|████████▉ | 446/500 [11:38<01:19,  1.48s/it, loss=2144.0000, t=912]
Attacking:  89%|████████▉ | 447/500 [11:39<01:19,  1.49s/it, loss=2144.0000, t=912]
Attacking:  89%|████████▉ | 447/500 [11:40<01:19,  1.49s/it, loss=2208.0000, t=992]
Attacking:  90%|████████▉ | 448/500 [11:40<01:17,  1.50s/it, loss=2208.0000, t=992]
Attacking:  90%|████████▉ | 448/500 [11:41<01:17,  1.50s/it, loss=2144.0000, t=964]
Attacking:  90%|████████▉ | 449/500 [11:42<01:16,  1.51s/it, loss=2144.0000, t=964]
Attacking:  90%|████████▉ | 449/500 [11:43<01:16,  1.51s/it, loss=2240.0000, t=1e+3]
Attacking:  90%|█████████ | 450/500 [11:44<01:17,  1.55s/it, loss=2240.0000, t=1e+3]
Attacking:  90%|█████████ | 450/500 [11:44<01:17,  1.55s/it, loss=2144.0000, t=952] 
Attacking:  90%|█████████ | 451/500 [11:45<01:15,  1.54s/it, loss=2144.0000, t=952]
Attacking:  90%|█████████ | 451/500 [11:46<01:15,  1.54s/it, loss=2176.0000, t=984]
Attacking:  90%|█████████ | 452/500 [11:47<01:15,  1.56s/it, loss=2176.0000, t=984]
Attacking:  90%|█████████ | 452/500 [11:48<01:15,  1.56s/it, loss=2128.0000, t=940]
Attacking:  91%|█████████ | 453/500 [11:48<01:15,  1.61s/it, loss=2128.0000, t=940]
Attacking:  91%|█████████ | 453/500 [11:49<01:15,  1.61s/it, loss=2192.0000, t=992]
Attacking:  91%|█████████ | 454/500 [11:50<01:12,  1.58s/it, loss=2192.0000, t=992]
Attacking:  91%|█████████ | 454/500 [11:51<01:12,  1.58s/it, loss=2192.0000, t=992]
Attacking:  91%|█████████ | 455/500 [11:51<01:10,  1.57s/it, loss=2192.0000, t=992]
Attacking:  91%|█████████ | 455/500 [11:52<01:10,  1.57s/it, loss=2144.0000, t=972]
Attacking:  91%|█████████ | 456/500 [11:53<01:11,  1.63s/it, loss=2144.0000, t=972]
Attacking:  91%|█████████ | 456/500 [11:54<01:11,  1.63s/it, loss=2144.0000, t=964]
Attacking:  91%|█████████▏| 457/500 [11:55<01:10,  1.65s/it, loss=2144.0000, t=964]
Attacking:  91%|█████████▏| 457/500 [11:56<01:10,  1.65s/it, loss=2176.0000, t=984]
Attacking:  92%|█████████▏| 458/500 [11:56<01:06,  1.59s/it, loss=2176.0000, t=984]
Attacking:  92%|█████████▏| 458/500 [11:57<01:06,  1.59s/it, loss=2144.0000, t=972]
Attacking:  92%|█████████▏| 459/500 [11:58<01:05,  1.59s/it, loss=2144.0000, t=972]
Attacking:  92%|█████████▏| 459/500 [11:59<01:05,  1.59s/it, loss=2128.0000, t=952]
Attacking:  92%|█████████▏| 460/500 [12:00<01:04,  1.62s/it, loss=2128.0000, t=952]
Attacking:  92%|█████████▏| 460/500 [12:01<01:04,  1.62s/it, loss=2144.0000, t=972]
Attacking:  92%|█████████▏| 461/500 [12:01<01:04,  1.66s/it, loss=2144.0000, t=972]
Attacking:  92%|█████████▏| 461/500 [12:02<01:04,  1.66s/it, loss=2144.0000, t=964]
Attacking:  92%|█████████▏| 462/500 [12:03<01:03,  1.66s/it, loss=2144.0000, t=964]
Attacking:  92%|█████████▏| 462/500 [12:04<01:03,  1.66s/it, loss=2144.0000, t=972]
Attacking:  93%|█████████▎| 463/500 [12:05<01:02,  1.69s/it, loss=2144.0000, t=972]
Attacking:  93%|█████████▎| 463/500 [12:06<01:02,  1.69s/it, loss=2128.0000, t=964]
Attacking:  93%|█████████▎| 464/500 [12:06<00:59,  1.67s/it, loss=2128.0000, t=964]
Attacking:  93%|█████████▎| 464/500 [12:07<00:59,  1.67s/it, loss=2128.0000, t=912]
Attacking:  93%|█████████▎| 465/500 [12:08<00:56,  1.60s/it, loss=2128.0000, t=912]
Attacking:  93%|█████████▎| 465/500 [12:09<00:56,  1.60s/it, loss=2128.0000, t=928]
Attacking:  93%|█████████▎| 466/500 [12:09<00:54,  1.59s/it, loss=2128.0000, t=928]
Attacking:  93%|█████████▎| 466/500 [12:10<00:54,  1.59s/it, loss=2128.0000, t=940]
Attacking:  93%|█████████▎| 467/500 [12:11<00:52,  1.58s/it, loss=2128.0000, t=940]
Attacking:  93%|█████████▎| 467/500 [12:12<00:52,  1.58s/it, loss=2192.0000, t=992]
Attacking:  94%|█████████▎| 468/500 [12:13<00:50,  1.59s/it, loss=2192.0000, t=992]
Attacking:  94%|█████████▎| 468/500 [12:13<00:50,  1.59s/it, loss=2176.0000, t=984]
Attacking:  94%|█████████▍| 469/500 [12:14<00:49,  1.61s/it, loss=2176.0000, t=984]
Attacking:  94%|█████████▍| 469/500 [12:15<00:49,  1.61s/it, loss=2176.0000, t=984]
Attacking:  94%|█████████▍| 470/500 [12:16<00:47,  1.59s/it, loss=2176.0000, t=984]
Attacking:  94%|█████████▍| 470/500 [12:16<00:47,  1.59s/it, loss=2144.0000, t=972]
Attacking:  94%|█████████▍| 471/500 [12:17<00:45,  1.56s/it, loss=2144.0000, t=972]
Attacking:  94%|█████████▍| 471/500 [12:18<00:45,  1.56s/it, loss=2208.0000, t=1e+3]
Attacking:  94%|█████████▍| 472/500 [12:19<00:43,  1.55s/it, loss=2208.0000, t=1e+3]
Attacking:  94%|█████████▍| 472/500 [12:19<00:43,  1.55s/it, loss=2144.0000, t=964] 
Attacking:  95%|█████████▍| 473/500 [12:20<00:41,  1.52s/it, loss=2144.0000, t=964]
Attacking:  95%|█████████▍| 473/500 [12:21<00:41,  1.52s/it, loss=2128.0000, t=940]
Attacking:  95%|█████████▍| 474/500 [12:22<00:39,  1.50s/it, loss=2128.0000, t=940]
Attacking:  95%|█████████▍| 474/500 [12:22<00:39,  1.50s/it, loss=2128.0000, t=952]
Attacking:  95%|█████████▌| 475/500 [12:23<00:37,  1.50s/it, loss=2128.0000, t=952]
Attacking:  95%|█████████▌| 475/500 [12:24<00:37,  1.50s/it, loss=2192.0000, t=992]
Attacking:  95%|█████████▌| 476/500 [12:25<00:35,  1.49s/it, loss=2192.0000, t=992]
Attacking:  95%|█████████▌| 476/500 [12:25<00:35,  1.49s/it, loss=2208.0000, t=1e+3]
Attacking:  95%|█████████▌| 477/500 [12:26<00:34,  1.49s/it, loss=2208.0000, t=1e+3]
Attacking:  95%|█████████▌| 477/500 [12:27<00:34,  1.49s/it, loss=2128.0000, t=900] 
Attacking:  96%|█████████▌| 478/500 [12:28<00:32,  1.47s/it, loss=2128.0000, t=900]
Attacking:  96%|█████████▌| 478/500 [12:28<00:32,  1.47s/it, loss=2128.0000, t=940]
Attacking:  96%|█████████▌| 479/500 [12:29<00:30,  1.47s/it, loss=2128.0000, t=940]
Attacking:  96%|█████████▌| 479/500 [12:30<00:30,  1.47s/it, loss=2128.0000, t=912]
Attacking:  96%|█████████▌| 480/500 [12:31<00:29,  1.49s/it, loss=2128.0000, t=912]
Attacking:  96%|█████████▌| 480/500 [12:31<00:29,  1.49s/it, loss=2128.0000, t=940]
Attacking:  96%|█████████▌| 481/500 [12:32<00:29,  1.53s/it, loss=2128.0000, t=940]
Attacking:  96%|█████████▌| 481/500 [12:33<00:29,  1.53s/it, loss=2128.0000, t=900]
Attacking:  96%|█████████▋| 482/500 [12:34<00:27,  1.52s/it, loss=2128.0000, t=900]
Attacking:  96%|█████████▋| 482/500 [12:35<00:27,  1.52s/it, loss=2144.0000, t=964]
Attacking:  97%|█████████▋| 483/500 [12:35<00:26,  1.54s/it, loss=2144.0000, t=964]
Attacking:  97%|█████████▋| 483/500 [12:36<00:26,  1.54s/it, loss=2144.0000, t=928]
Attacking:  97%|█████████▋| 484/500 [12:37<00:24,  1.54s/it, loss=2144.0000, t=928]
Attacking:  97%|█████████▋| 484/500 [12:38<00:24,  1.54s/it, loss=2144.0000, t=964]
Attacking:  97%|█████████▋| 485/500 [12:39<00:23,  1.60s/it, loss=2144.0000, t=964]
Attacking:  97%|█████████▋| 485/500 [12:39<00:23,  1.60s/it, loss=2192.0000, t=992]
Attacking:  97%|█████████▋| 486/500 [12:40<00:22,  1.61s/it, loss=2192.0000, t=992]
Attacking:  97%|█████████▋| 486/500 [12:41<00:22,  1.61s/it, loss=2128.0000, t=940]
Attacking:  97%|█████████▋| 487/500 [12:42<00:21,  1.64s/it, loss=2128.0000, t=940]
Attacking:  97%|█████████▋| 487/500 [12:43<00:21,  1.64s/it, loss=2128.0000, t=928]
Attacking:  98%|█████████▊| 488/500 [12:44<00:20,  1.67s/it, loss=2128.0000, t=928]
Attacking:  98%|█████████▊| 488/500 [12:45<00:20,  1.67s/it, loss=2128.0000, t=912]
Attacking:  98%|█████████▊| 489/500 [12:45<00:18,  1.66s/it, loss=2128.0000, t=912]
Attacking:  98%|█████████▊| 489/500 [12:46<00:18,  1.66s/it, loss=2128.0000, t=940]
Attacking:  98%|█████████▊| 490/500 [12:47<00:17,  1.76s/it, loss=2128.0000, t=940]
Attacking:  98%|█████████▊| 490/500 [12:48<00:17,  1.76s/it, loss=2144.0000, t=972]
Attacking:  98%|█████████▊| 491/500 [12:49<00:15,  1.76s/it, loss=2144.0000, t=972]
Attacking:  98%|█████████▊| 491/500 [12:50<00:15,  1.76s/it, loss=2128.0000, t=952]
Attacking:  98%|█████████▊| 492/500 [12:51<00:13,  1.75s/it, loss=2128.0000, t=952]
Attacking:  98%|█████████▊| 492/500 [12:52<00:13,  1.75s/it, loss=2192.0000, t=992]
Attacking:  99%|█████████▊| 493/500 [12:53<00:12,  1.74s/it, loss=2192.0000, t=992]
Attacking:  99%|█████████▊| 493/500 [12:53<00:12,  1.74s/it, loss=2192.0000, t=992]
Attacking:  99%|█████████▉| 494/500 [12:54<00:10,  1.71s/it, loss=2192.0000, t=992]
Attacking:  99%|█████████▉| 494/500 [12:55<00:10,  1.71s/it, loss=2128.0000, t=900]
Attacking:  99%|█████████▉| 495/500 [12:56<00:08,  1.70s/it, loss=2128.0000, t=900]
Attacking:  99%|█████████▉| 495/500 [12:56<00:08,  1.70s/it, loss=2192.0000, t=992]
Attacking:  99%|█████████▉| 496/500 [12:57<00:06,  1.64s/it, loss=2192.0000, t=992]
Attacking:  99%|█████████▉| 496/500 [12:58<00:06,  1.64s/it, loss=2192.0000, t=992]
Attacking:  99%|█████████▉| 497/500 [12:59<00:04,  1.66s/it, loss=2192.0000, t=992]
Attacking:  99%|█████████▉| 497/500 [13:00<00:04,  1.66s/it, loss=2128.0000, t=928]
Attacking: 100%|█████████▉| 498/500 [13:01<00:03,  1.68s/it, loss=2128.0000, t=928]
Attacking: 100%|█████████▉| 498/500 [13:01<00:03,  1.68s/it, loss=2128.0000, t=928]
Attacking: 100%|█████████▉| 499/500 [13:02<00:01,  1.65s/it, loss=2128.0000, t=928]
Attacking: 100%|█████████▉| 499/500 [13:03<00:01,  1.65s/it, loss=2128.0000, t=952]
Attacking: 100%|██████████| 500/500 [13:04<00:00,  1.60s/it, loss=2128.0000, t=952]
Attacking: 100%|██████████| 500/500 [13:04<00:00,  1.57s/it, loss=2128.0000, t=952]
+Max Diff: 0.501961
+Mean Diff: 0.264530
+Saved adversarial image to attacked/images/hike.jpg
+Saved loss curve to attacked/loss_curve/hike_loss.png
+[GPU 3] Stage 3/3: Test
+Loading models for testing hike...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for hike...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 51.67it/s]
+Saved video to attacked/videos/hike.mp4
+Saved frames to attacked/frames/hike
+[GPU 3] Finished hike.jpg
+======================================
+[GPU 3] Processing hockey.jpg (Image 23/50)
+======================================
+[GPU 3] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 3] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   5%|▌         | 27/500 [00:45<12:47,  1.62s/it, loss=2368.0000, t=900]
Attacking:   6%|▌         | 28/500 [00:46<12:47,  1.63s/it, loss=2368.0000, t=900]
Attacking:   6%|▌         | 28/500 [00:47<12:47,  1.63s/it, loss=2400.0000, t=928]
Attacking:   6%|▌         | 29/500 [00:47<12:43,  1.62s/it, loss=2400.0000, t=928]
Attacking:   6%|▌         | 29/500 [00:48<12:43,  1.62s/it, loss=2368.0000, t=928]
Attacking:   6%|▌         | 30/500 [00:49<12:38,  1.61s/it, loss=2368.0000, t=928]
Attacking:   6%|▌         | 30/500 [00:50<12:38,  1.61s/it, loss=2480.0000, t=992]
Attacking:   6%|▌         | 31/500 [00:51<12:38,  1.62s/it, loss=2480.0000, t=992]
Attacking:   6%|▌         | 31/500 [00:51<12:38,  1.62s/it, loss=2480.0000, t=992]
Attacking:   6%|▋         | 32/500 [00:52<12:34,  1.61s/it, loss=2480.0000, t=992]
Attacking:   6%|▋         | 32/500 [00:53<12:34,  1.61s/it, loss=2352.0000, t=900]
Attacking:   7%|▋         | 33/500 [00:54<12:24,  1.59s/it, loss=2352.0000, t=900]
Attacking:   7%|▋         | 33/500 [00:55<12:24,  1.59s/it, loss=2432.0000, t=972]
Attacking:   7%|▋         | 34/500 [00:55<12:15,  1.58s/it, loss=2432.0000, t=972]
Attacking:   7%|▋         | 34/500 [00:56<12:15,  1.58s/it, loss=2432.0000, t=972]
Attacking:   7%|▋         | 35/500 [00:57<12:04,  1.56s/it, loss=2432.0000, t=972]
Attacking:   7%|▋         | 35/500 [00:58<12:04,  1.56s/it, loss=2480.0000, t=992]
Attacking:   7%|▋         | 36/500 [00:59<12:10,  1.57s/it, loss=2480.0000, t=992]
Attacking:   7%|▋         | 36/500 [00:59<12:10,  1.57s/it, loss=2432.0000, t=972]
Attacking:   7%|▋         | 37/500 [01:00<11:54,  1.54s/it, loss=2432.0000, t=972]
Attacking:   7%|▋         | 37/500 [01:01<11:54,  1.54s/it, loss=2336.0000, t=912]
Attacking:   8%|▊         | 38/500 [01:01<11:35,  1.51s/it, loss=2336.0000, t=912]
Attacking:   8%|▊         | 38/500 [01:02<11:35,  1.51s/it, loss=2416.0000, t=972]
Attacking:   8%|▊         | 39/500 [01:03<11:23,  1.48s/it, loss=2416.0000, t=972]
Attacking:   8%|▊         | 39/500 [01:03<11:23,  1.48s/it, loss=2336.0000, t=928]
Attacking:   8%|▊         | 40/500 [01:04<11:20,  1.48s/it, loss=2336.0000, t=928]
Attacking:   8%|▊         | 40/500 [01:05<11:20,  1.48s/it, loss=2416.0000, t=972]
Attacking:   8%|▊         | 41/500 [01:06<11:11,  1.46s/it, loss=2416.0000, t=972]
Attacking:   8%|▊         | 41/500 [01:06<11:11,  1.46s/it, loss=2384.0000, t=964]
Attacking:   8%|▊         | 42/500 [01:07<11:01,  1.44s/it, loss=2384.0000, t=964]
Attacking:   8%|▊         | 42/500 [01:08<11:01,  1.44s/it, loss=2336.0000, t=900]
Attacking:   9%|▊         | 43/500 [01:09<10:55,  1.44s/it, loss=2336.0000, t=900]
Attacking:   9%|▊         | 43/500 [01:09<10:55,  1.44s/it, loss=2384.0000, t=964]
Attacking:   9%|▉         | 44/500 [01:10<11:02,  1.45s/it, loss=2384.0000, t=964]
Attacking:   9%|▉         | 44/500 [01:11<11:02,  1.45s/it, loss=2336.0000, t=912]
Attacking:   9%|▉         | 45/500 [01:12<11:19,  1.49s/it, loss=2336.0000, t=912]
Attacking:   9%|▉         | 45/500 [01:12<11:19,  1.49s/it, loss=2400.0000, t=972]
Attacking:   9%|▉         | 46/500 [01:13<11:44,  1.55s/it, loss=2400.0000, t=972]
Attacking:   9%|▉         | 46/500 [01:14<11:44,  1.55s/it, loss=2400.0000, t=972]
Attacking:   9%|▉         | 47/500 [01:15<11:33,  1.53s/it, loss=2400.0000, t=972]
Attacking:   9%|▉         | 47/500 [01:15<11:33,  1.53s/it, loss=2336.0000, t=912]
Attacking:  10%|▉         | 48/500 [01:16<11:29,  1.53s/it, loss=2336.0000, t=912]
Attacking:  10%|▉         | 48/500 [01:17<11:29,  1.53s/it, loss=2352.0000, t=952]
Attacking:  10%|▉         | 49/500 [01:18<11:25,  1.52s/it, loss=2352.0000, t=952]
Attacking:  10%|▉         | 49/500 [01:18<11:25,  1.52s/it, loss=2304.0000, t=912]
Attacking:  10%|█         | 50/500 [01:19<11:17,  1.51s/it, loss=2304.0000, t=912]
Attacking:  10%|█         | 50/500 [01:20<11:17,  1.51s/it, loss=2304.0000, t=900]
Attacking:  10%|█         | 51/500 [01:21<11:13,  1.50s/it, loss=2304.0000, t=900]
Attacking:  10%|█         | 51/500 [01:21<11:13,  1.50s/it, loss=2320.0000, t=912]
Attacking:  10%|█         | 52/500 [01:22<11:13,  1.50s/it, loss=2320.0000, t=912]
Attacking:  10%|█         | 52/500 [01:23<11:13,  1.50s/it, loss=2432.0000, t=984]
Attacking:  11%|█         | 53/500 [01:24<11:25,  1.53s/it, loss=2432.0000, t=984]
Attacking:  11%|█         | 53/500 [01:24<11:25,  1.53s/it, loss=2336.0000, t=940]
Attacking:  11%|█         | 54/500 [01:25<11:10,  1.50s/it, loss=2336.0000, t=940]
Attacking:  11%|█         | 54/500 [01:26<11:10,  1.50s/it, loss=2432.0000, t=1e+3]
Attacking:  11%|█         | 55/500 [01:27<11:18,  1.52s/it, loss=2432.0000, t=1e+3]
Attacking:  11%|█         | 55/500 [01:28<11:18,  1.52s/it, loss=2416.0000, t=1e+3]
Attacking:  11%|█         | 56/500 [01:29<11:31,  1.56s/it, loss=2416.0000, t=1e+3]
Attacking:  11%|█         | 56/500 [01:29<11:31,  1.56s/it, loss=2320.0000, t=912] 
Attacking:  11%|█▏        | 57/500 [01:30<11:37,  1.57s/it, loss=2320.0000, t=912]
Attacking:  11%|█▏        | 57/500 [01:31<11:37,  1.57s/it, loss=2432.0000, t=1e+3]
Attacking:  12%|█▏        | 58/500 [01:32<11:40,  1.58s/it, loss=2432.0000, t=1e+3]
Attacking:  12%|█▏        | 58/500 [01:33<11:40,  1.58s/it, loss=2432.0000, t=992] 
Attacking:  12%|█▏        | 59/500 [01:34<12:09,  1.65s/it, loss=2432.0000, t=992]
Attacking:  12%|█▏        | 59/500 [01:34<12:09,  1.65s/it, loss=2368.0000, t=972]
Attacking:  12%|█▏        | 60/500 [01:35<12:04,  1.65s/it, loss=2368.0000, t=972]
Attacking:  12%|█▏        | 60/500 [01:36<12:04,  1.65s/it, loss=2416.0000, t=984]
Attacking:  12%|█▏        | 61/500 [01:37<12:05,  1.65s/it, loss=2416.0000, t=984]
Attacking:  12%|█▏        | 61/500 [01:38<12:05,  1.65s/it, loss=2320.0000, t=940]
Attacking:  12%|█▏        | 62/500 [01:39<12:03,  1.65s/it, loss=2320.0000, t=940]
Attacking:  12%|█▏        | 62/500 [01:39<12:03,  1.65s/it, loss=2368.0000, t=964]
Attacking:  13%|█▎        | 63/500 [01:40<11:55,  1.64s/it, loss=2368.0000, t=964]
Attacking:  13%|█▎        | 63/500 [01:41<11:55,  1.64s/it, loss=2304.0000, t=912]
Attacking:  13%|█▎        | 64/500 [01:42<11:52,  1.63s/it, loss=2304.0000, t=912]
Attacking:  13%|█▎        | 64/500 [01:42<11:52,  1.63s/it, loss=2416.0000, t=984]
Attacking:  13%|█▎        | 65/500 [01:43<11:40,  1.61s/it, loss=2416.0000, t=984]
Attacking:  13%|█▎        | 65/500 [01:44<11:40,  1.61s/it, loss=2352.0000, t=964]
Attacking:  13%|█▎        | 66/500 [01:45<11:34,  1.60s/it, loss=2352.0000, t=964]
Attacking:  13%|█▎        | 66/500 [01:45<11:34,  1.60s/it, loss=2320.0000, t=940]
Attacking:  13%|█▎        | 67/500 [01:46<11:16,  1.56s/it, loss=2320.0000, t=940]
Attacking:  13%|█▎        | 67/500 [01:47<11:16,  1.56s/it, loss=2384.0000, t=972]
Attacking:  14%|█▎        | 68/500 [01:48<11:08,  1.55s/it, loss=2384.0000, t=972]
Attacking:  14%|█▎        | 68/500 [01:49<11:08,  1.55s/it, loss=2288.0000, t=900]
Attacking:  14%|█▍        | 69/500 [01:49<11:06,  1.55s/it, loss=2288.0000, t=900]
Attacking:  14%|█▍        | 69/500 [01:50<11:06,  1.55s/it, loss=2320.0000, t=940]
Attacking:  14%|█▍        | 70/500 [01:51<11:16,  1.57s/it, loss=2320.0000, t=940]
Attacking:  14%|█▍        | 70/500 [01:52<11:16,  1.57s/it, loss=2288.0000, t=912]
Attacking:  14%|█▍        | 71/500 [01:53<11:27,  1.60s/it, loss=2288.0000, t=912]
Attacking:  14%|█▍        | 71/500 [01:53<11:27,  1.60s/it, loss=2352.0000, t=964]
Attacking:  14%|█▍        | 72/500 [01:54<11:20,  1.59s/it, loss=2352.0000, t=964]
Attacking:  14%|█▍        | 72/500 [01:55<11:20,  1.59s/it, loss=2400.0000, t=984]
Attacking:  15%|█▍        | 73/500 [01:56<11:15,  1.58s/it, loss=2400.0000, t=984]
Attacking:  15%|█▍        | 73/500 [01:56<11:15,  1.58s/it, loss=2416.0000, t=992]
Attacking:  15%|█▍        | 74/500 [01:57<10:52,  1.53s/it, loss=2416.0000, t=992]
Attacking:  15%|█▍        | 74/500 [01:58<10:52,  1.53s/it, loss=2288.0000, t=912]
Attacking:  15%|█▌        | 75/500 [01:59<10:55,  1.54s/it, loss=2288.0000, t=912]
Attacking:  15%|█▌        | 75/500 [02:00<10:55,  1.54s/it, loss=2400.0000, t=984]
Attacking:  15%|█▌        | 76/500 [02:00<11:04,  1.57s/it, loss=2400.0000, t=984]
Attacking:  15%|█▌        | 76/500 [02:01<11:04,  1.57s/it, loss=2304.0000, t=940]
Attacking:  15%|█▌        | 77/500 [02:02<11:05,  1.57s/it, loss=2304.0000, t=940]
Attacking:  15%|█▌        | 77/500 [02:03<11:05,  1.57s/it, loss=2288.0000, t=928]
Attacking:  16%|█▌        | 78/500 [02:04<11:02,  1.57s/it, loss=2288.0000, t=928]
Attacking:  16%|█▌        | 78/500 [02:04<11:02,  1.57s/it, loss=2320.0000, t=952]
Attacking:  16%|█▌        | 79/500 [02:05<10:45,  1.53s/it, loss=2320.0000, t=952]
Attacking:  16%|█▌        | 79/500 [02:06<10:45,  1.53s/it, loss=2336.0000, t=972]
Attacking:  16%|█▌        | 80/500 [02:07<10:36,  1.52s/it, loss=2336.0000, t=972]
Attacking:  16%|█▌        | 80/500 [02:07<10:36,  1.52s/it, loss=2288.0000, t=928]
Attacking:  16%|█▌        | 81/500 [02:08<10:28,  1.50s/it, loss=2288.0000, t=928]
Attacking:  16%|█▌        | 81/500 [02:09<10:28,  1.50s/it, loss=2272.0000, t=912]
Attacking:  16%|█▋        | 82/500 [02:10<10:42,  1.54s/it, loss=2272.0000, t=912]
Attacking:  16%|█▋        | 82/500 [02:10<10:42,  1.54s/it, loss=2400.0000, t=992]
Attacking:  17%|█▋        | 83/500 [02:11<10:50,  1.56s/it, loss=2400.0000, t=992]
Attacking:  17%|█▋        | 83/500 [02:12<10:50,  1.56s/it, loss=2304.0000, t=952]
Attacking:  17%|█▋        | 84/500 [02:13<10:38,  1.53s/it, loss=2304.0000, t=952]
Attacking:  17%|█▋        | 84/500 [02:13<10:38,  1.53s/it, loss=2320.0000, t=964]
Attacking:  17%|█▋        | 85/500 [02:14<10:37,  1.54s/it, loss=2320.0000, t=964]
Attacking:  17%|█▋        | 85/500 [02:15<10:37,  1.54s/it, loss=2336.0000, t=972]
Attacking:  17%|█▋        | 86/500 [02:16<10:35,  1.54s/it, loss=2336.0000, t=972]
Attacking:  17%|█▋        | 86/500 [02:16<10:35,  1.54s/it, loss=2272.0000, t=912]
Attacking:  17%|█▋        | 87/500 [02:17<10:22,  1.51s/it, loss=2272.0000, t=912]
Attacking:  17%|█▋        | 87/500 [02:18<10:22,  1.51s/it, loss=2256.0000, t=900]
Attacking:  18%|█▊        | 88/500 [02:19<10:24,  1.52s/it, loss=2256.0000, t=900]
Attacking:  18%|█▊        | 88/500 [02:19<10:24,  1.52s/it, loss=2272.0000, t=928]
Attacking:  18%|█▊        | 89/500 [02:20<10:18,  1.51s/it, loss=2272.0000, t=928]
Attacking:  18%|█▊        | 89/500 [02:21<10:18,  1.51s/it, loss=2320.0000, t=964]
Attacking:  18%|█▊        | 90/500 [02:22<10:27,  1.53s/it, loss=2320.0000, t=964]
Attacking:  18%|█▊        | 90/500 [02:22<10:27,  1.53s/it, loss=2272.0000, t=928]
Attacking:  18%|█▊        | 91/500 [02:23<10:20,  1.52s/it, loss=2272.0000, t=928]
Attacking:  18%|█▊        | 91/500 [02:24<10:20,  1.52s/it, loss=2272.0000, t=928]
Attacking:  18%|█▊        | 92/500 [02:25<10:17,  1.51s/it, loss=2272.0000, t=928]
Attacking:  18%|█▊        | 92/500 [02:26<10:17,  1.51s/it, loss=2288.0000, t=940]
Attacking:  19%|█▊        | 93/500 [02:26<10:22,  1.53s/it, loss=2288.0000, t=940]
Attacking:  19%|█▊        | 93/500 [02:27<10:22,  1.53s/it, loss=2272.0000, t=928]
Attacking:  19%|█▉        | 94/500 [02:28<10:17,  1.52s/it, loss=2272.0000, t=928]
Attacking:  19%|█▉        | 94/500 [02:29<10:17,  1.52s/it, loss=2304.0000, t=952]
Attacking:  19%|█▉        | 95/500 [02:29<10:27,  1.55s/it, loss=2304.0000, t=952]
Attacking:  19%|█▉        | 95/500 [02:30<10:27,  1.55s/it, loss=2240.0000, t=912]
Attacking:  19%|█▉        | 96/500 [02:31<10:26,  1.55s/it, loss=2240.0000, t=912]
Attacking:  19%|█▉        | 96/500 [02:32<10:26,  1.55s/it, loss=2304.0000, t=952]
Attacking:  19%|█▉        | 97/500 [02:33<10:21,  1.54s/it, loss=2304.0000, t=952]
Attacking:  19%|█▉        | 97/500 [02:33<10:21,  1.54s/it, loss=2368.0000, t=992]
Attacking:  20%|█▉        | 98/500 [02:34<10:15,  1.53s/it, loss=2368.0000, t=992]
Attacking:  20%|█▉        | 98/500 [02:35<10:15,  1.53s/it, loss=2336.0000, t=972]
Attacking:  20%|█▉        | 99/500 [02:36<10:11,  1.53s/it, loss=2336.0000, t=972]
Attacking:  20%|█▉        | 99/500 [02:36<10:11,  1.53s/it, loss=2256.0000, t=912]
Attacking:  20%|██        | 100/500 [02:37<10:14,  1.54s/it, loss=2256.0000, t=912]
Attacking:  20%|██        | 100/500 [02:38<10:14,  1.54s/it, loss=2272.0000, t=940]
Attacking:  20%|██        | 101/500 [02:39<10:23,  1.56s/it, loss=2272.0000, t=940]
Attacking:  20%|██        | 101/500 [02:39<10:23,  1.56s/it, loss=2368.0000, t=1e+3]
Attacking:  20%|██        | 102/500 [02:40<10:23,  1.57s/it, loss=2368.0000, t=1e+3]
Attacking:  20%|██        | 102/500 [02:41<10:23,  1.57s/it, loss=2368.0000, t=984] 
Attacking:  21%|██        | 103/500 [02:42<10:18,  1.56s/it, loss=2368.0000, t=984]
Attacking:  21%|██        | 103/500 [02:42<10:18,  1.56s/it, loss=2240.0000, t=900]
Attacking:  21%|██        | 104/500 [02:43<10:00,  1.52s/it, loss=2240.0000, t=900]
Attacking:  21%|██        | 104/500 [02:44<10:00,  1.52s/it, loss=2320.0000, t=964]
Attacking:  21%|██        | 105/500 [02:45<10:06,  1.54s/it, loss=2320.0000, t=964]
Attacking:  21%|██        | 105/500 [02:46<10:06,  1.54s/it, loss=2368.0000, t=992]
Attacking:  21%|██        | 106/500 [02:46<10:01,  1.53s/it, loss=2368.0000, t=992]
Attacking:  21%|██        | 106/500 [02:47<10:01,  1.53s/it, loss=2256.0000, t=912]
Attacking:  21%|██▏       | 107/500 [02:48<10:09,  1.55s/it, loss=2256.0000, t=912]
Attacking:  21%|██▏       | 107/500 [02:49<10:09,  1.55s/it, loss=2288.0000, t=952]
Attacking:  22%|██▏       | 108/500 [02:50<10:20,  1.58s/it, loss=2288.0000, t=952]
Attacking:  22%|██▏       | 108/500 [02:50<10:20,  1.58s/it, loss=2304.0000, t=964]
Attacking:  22%|██▏       | 109/500 [02:51<10:25,  1.60s/it, loss=2304.0000, t=964]
Attacking:  22%|██▏       | 109/500 [02:52<10:25,  1.60s/it, loss=2368.0000, t=984]
Attacking:  22%|██▏       | 110/500 [02:53<10:16,  1.58s/it, loss=2368.0000, t=984]
Attacking:  22%|██▏       | 110/500 [02:54<10:16,  1.58s/it, loss=2272.0000, t=940]
Attacking:  22%|██▏       | 111/500 [02:54<10:14,  1.58s/it, loss=2272.0000, t=940]
Attacking:  22%|██▏       | 111/500 [02:55<10:14,  1.58s/it, loss=2320.0000, t=972]
Attacking:  22%|██▏       | 112/500 [02:56<10:02,  1.55s/it, loss=2320.0000, t=972]
Attacking:  22%|██▏       | 112/500 [02:57<10:02,  1.55s/it, loss=2368.0000, t=1e+3]
Attacking:  23%|██▎       | 113/500 [02:58<10:11,  1.58s/it, loss=2368.0000, t=1e+3]
Attacking:  23%|██▎       | 113/500 [02:58<10:11,  1.58s/it, loss=2304.0000, t=964] 
Attacking:  23%|██▎       | 114/500 [02:59<10:20,  1.61s/it, loss=2304.0000, t=964]
Attacking:  23%|██▎       | 114/500 [03:00<10:20,  1.61s/it, loss=2320.0000, t=972]
Attacking:  23%|██▎       | 115/500 [03:01<10:27,  1.63s/it, loss=2320.0000, t=972]
Attacking:  23%|██▎       | 115/500 [03:02<10:27,  1.63s/it, loss=2288.0000, t=952]
Attacking:  23%|██▎       | 116/500 [03:02<10:18,  1.61s/it, loss=2288.0000, t=952]
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Attacking: 100%|██████████| 500/500 [12:54<00:00,  1.55s/it, loss=2192.0000, t=940]
+Max Diff: 0.501961
+Mean Diff: 0.251099
+Saved adversarial image to attacked/images/hockey.jpg
+Saved loss curve to attacked/loss_curve/hockey_loss.png
+[GPU 3] Stage 3/3: Test
+Loading models for testing hockey...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for hockey...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 54.31it/s]
+Saved video to attacked/videos/hockey.mp4
+Saved frames to attacked/frames/hockey
+[GPU 3] Finished hockey.jpg
+======================================
+[GPU 3] Processing horsejump-high.jpg (Image 24/50)
+======================================
+[GPU 3] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 3] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  20%|██        | 100/500 [02:38<10:26,  1.57s/it, loss=2384.0000, t=964]
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Attacking:  24%|██▎       | 118/500 [03:07<10:01,  1.57s/it, loss=2416.0000, t=1e+3]
Attacking:  24%|██▍       | 119/500 [03:08<09:59,  1.57s/it, loss=2416.0000, t=1e+3]
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Attacking: 100%|██████████| 500/500 [12:56<00:00,  1.54s/it, loss=2288.0000, t=900]
Attacking: 100%|██████████| 500/500 [12:56<00:00,  1.55s/it, loss=2288.0000, t=900]
+Max Diff: 0.501961
+Mean Diff: 0.244468
+Saved adversarial image to attacked/images/horsejump-high.jpg
+Saved loss curve to attacked/loss_curve/horsejump-high_loss.png
+[GPU 3] Stage 3/3: Test
+Loading models for testing horsejump-high...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for horsejump-high...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 63.11it/s]
+Saved video to attacked/videos/horsejump-high.mp4
+Saved frames to attacked/frames/horsejump-high
+[GPU 3] Finished horsejump-high.jpg
+======================================
+[GPU 3] Processing horsejump-low.jpg (Image 25/50)
+======================================
+[GPU 3] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 3] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   6%|▌         | 29/500 [00:46<12:23,  1.58s/it, loss=2320.0000, t=992]
Attacking:   6%|▌         | 29/500 [00:47<12:23,  1.58s/it, loss=2240.0000, t=952]
Attacking:   6%|▌         | 30/500 [00:47<12:27,  1.59s/it, loss=2240.0000, t=952]
Attacking:   6%|▌         | 30/500 [00:48<12:27,  1.59s/it, loss=2320.0000, t=992]
Attacking:   6%|▌         | 31/500 [00:49<12:21,  1.58s/it, loss=2320.0000, t=992]
Attacking:   6%|▌         | 31/500 [00:50<12:21,  1.58s/it, loss=2256.0000, t=972]
Attacking:   6%|▋         | 32/500 [00:50<12:06,  1.55s/it, loss=2256.0000, t=972]
Attacking:   6%|▋         | 32/500 [00:51<12:06,  1.55s/it, loss=2304.0000, t=992]
Attacking:   7%|▋         | 33/500 [00:52<12:28,  1.60s/it, loss=2304.0000, t=992]
Attacking:   7%|▋         | 33/500 [00:53<12:28,  1.60s/it, loss=2240.0000, t=964]
Attacking:   7%|▋         | 34/500 [00:54<12:28,  1.61s/it, loss=2240.0000, t=964]
Attacking:   7%|▋         | 34/500 [00:54<12:28,  1.61s/it, loss=2224.0000, t=952]
Attacking:   7%|▋         | 35/500 [00:55<12:15,  1.58s/it, loss=2224.0000, t=952]
Attacking:   7%|▋         | 35/500 [00:56<12:15,  1.58s/it, loss=2208.0000, t=912]
Attacking:   7%|▋         | 36/500 [00:57<12:09,  1.57s/it, loss=2208.0000, t=912]
Attacking:   7%|▋         | 36/500 [00:58<12:09,  1.57s/it, loss=2224.0000, t=964]
Attacking:   7%|▋         | 37/500 [00:59<12:13,  1.58s/it, loss=2224.0000, t=964]
Attacking:   7%|▋         | 37/500 [00:59<12:13,  1.58s/it, loss=2224.0000, t=964]
Attacking:   8%|▊         | 38/500 [01:00<12:16,  1.60s/it, loss=2224.0000, t=964]
Attacking:   8%|▊         | 38/500 [01:01<12:16,  1.60s/it, loss=2240.0000, t=972]
Attacking:   8%|▊         | 39/500 [01:02<11:53,  1.55s/it, loss=2240.0000, t=972]
Attacking:   8%|▊         | 39/500 [01:02<11:53,  1.55s/it, loss=2240.0000, t=952]
Attacking:   8%|▊         | 40/500 [01:03<11:35,  1.51s/it, loss=2240.0000, t=952]
Attacking:   8%|▊         | 40/500 [01:04<11:35,  1.51s/it, loss=2208.0000, t=928]
Attacking:   8%|▊         | 41/500 [01:04<11:24,  1.49s/it, loss=2208.0000, t=928]
Attacking:   8%|▊         | 41/500 [01:05<11:24,  1.49s/it, loss=2272.0000, t=984]
Attacking:   8%|▊         | 42/500 [01:06<11:27,  1.50s/it, loss=2272.0000, t=984]
Attacking:   8%|▊         | 42/500 [01:07<11:27,  1.50s/it, loss=2224.0000, t=964]
Attacking:   9%|▊         | 43/500 [01:07<11:28,  1.51s/it, loss=2224.0000, t=964]
Attacking:   9%|▊         | 43/500 [01:08<11:28,  1.51s/it, loss=2192.0000, t=900]
Attacking:   9%|▉         | 44/500 [01:09<11:43,  1.54s/it, loss=2192.0000, t=900]
Attacking:   9%|▉         | 44/500 [01:10<11:43,  1.54s/it, loss=2208.0000, t=964]
Attacking:   9%|▉         | 45/500 [01:11<11:36,  1.53s/it, loss=2208.0000, t=964]
Attacking:   9%|▉         | 45/500 [01:11<11:36,  1.53s/it, loss=2224.0000, t=972]
Attacking:   9%|▉         | 46/500 [01:12<11:47,  1.56s/it, loss=2224.0000, t=972]
Attacking:   9%|▉         | 46/500 [01:13<11:47,  1.56s/it, loss=2208.0000, t=964]
Attacking:   9%|▉         | 47/500 [01:14<11:39,  1.54s/it, loss=2208.0000, t=964]
Attacking:   9%|▉         | 47/500 [01:15<11:39,  1.54s/it, loss=2192.0000, t=940]
Attacking:  10%|▉         | 48/500 [01:15<12:03,  1.60s/it, loss=2192.0000, t=940]
Attacking:  10%|▉         | 48/500 [01:16<12:03,  1.60s/it, loss=2304.0000, t=1e+3]
Attacking:  10%|▉         | 49/500 [01:17<12:11,  1.62s/it, loss=2304.0000, t=1e+3]
Attacking:  10%|▉         | 49/500 [01:18<12:11,  1.62s/it, loss=2224.0000, t=972] 
Attacking:  10%|█         | 50/500 [01:19<12:25,  1.66s/it, loss=2224.0000, t=972]
Attacking:  10%|█         | 50/500 [01:20<12:25,  1.66s/it, loss=2272.0000, t=992]
Attacking:  10%|█         | 51/500 [01:21<12:22,  1.65s/it, loss=2272.0000, t=992]
Attacking:  10%|█         | 51/500 [01:21<12:22,  1.65s/it, loss=2192.0000, t=952]
Attacking:  10%|█         | 52/500 [01:22<12:09,  1.63s/it, loss=2192.0000, t=952]
Attacking:  10%|█         | 52/500 [01:23<12:09,  1.63s/it, loss=2192.0000, t=912]
Attacking:  11%|█         | 53/500 [01:24<12:01,  1.61s/it, loss=2192.0000, t=912]
Attacking:  11%|█         | 53/500 [01:25<12:01,  1.61s/it, loss=2208.0000, t=972]
Attacking:  11%|█         | 54/500 [01:25<12:10,  1.64s/it, loss=2208.0000, t=972]
Attacking:  11%|█         | 54/500 [01:26<12:10,  1.64s/it, loss=2176.0000, t=900]
Attacking:  11%|█         | 55/500 [01:27<12:11,  1.64s/it, loss=2176.0000, t=900]
Attacking:  11%|█         | 55/500 [01:28<12:11,  1.64s/it, loss=2192.0000, t=952]
Attacking:  11%|█         | 56/500 [01:29<12:28,  1.68s/it, loss=2192.0000, t=952]
Attacking:  11%|█         | 56/500 [01:30<12:28,  1.68s/it, loss=2272.0000, t=992]
Attacking:  11%|█▏        | 57/500 [01:30<12:20,  1.67s/it, loss=2272.0000, t=992]
Attacking:  11%|█▏        | 57/500 [01:31<12:20,  1.67s/it, loss=2176.0000, t=952]
Attacking:  12%|█▏        | 58/500 [01:32<12:12,  1.66s/it, loss=2176.0000, t=952]
Attacking:  12%|█▏        | 58/500 [01:33<12:12,  1.66s/it, loss=2224.0000, t=984]
Attacking:  12%|█▏        | 59/500 [01:34<12:34,  1.71s/it, loss=2224.0000, t=984]
Attacking:  12%|█▏        | 59/500 [01:35<12:34,  1.71s/it, loss=2208.0000, t=984]
Attacking:  12%|█▏        | 60/500 [01:36<12:17,  1.68s/it, loss=2208.0000, t=984]
Attacking:  12%|█▏        | 60/500 [01:36<12:17,  1.68s/it, loss=2160.0000, t=912]
Attacking:  12%|█▏        | 61/500 [01:37<12:01,  1.64s/it, loss=2160.0000, t=912]
Attacking:  12%|█▏        | 61/500 [01:38<12:01,  1.64s/it, loss=2176.0000, t=952]
Attacking:  12%|█▏        | 62/500 [01:39<11:41,  1.60s/it, loss=2176.0000, t=952]
Attacking:  12%|█▏        | 62/500 [01:39<11:41,  1.60s/it, loss=2224.0000, t=984]
Attacking:  13%|█▎        | 63/500 [01:40<11:20,  1.56s/it, loss=2224.0000, t=984]
Attacking:  13%|█▎        | 63/500 [01:41<11:20,  1.56s/it, loss=2272.0000, t=1e+3]
Attacking:  13%|█▎        | 64/500 [01:42<11:20,  1.56s/it, loss=2272.0000, t=1e+3]
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Attacking:  13%|█▎        | 65/500 [01:43<11:15,  1.55s/it, loss=2208.0000, t=984]
Attacking:  13%|█▎        | 65/500 [01:44<11:15,  1.55s/it, loss=2160.0000, t=928]
Attacking:  13%|█▎        | 66/500 [01:45<11:09,  1.54s/it, loss=2160.0000, t=928]
Attacking:  13%|█▎        | 66/500 [01:45<11:09,  1.54s/it, loss=2240.0000, t=992]
Attacking:  13%|█▎        | 67/500 [01:46<11:01,  1.53s/it, loss=2240.0000, t=992]
Attacking:  13%|█▎        | 67/500 [01:47<11:01,  1.53s/it, loss=2160.0000, t=928]
Attacking:  14%|█▎        | 68/500 [01:48<11:15,  1.56s/it, loss=2160.0000, t=928]
Attacking:  14%|█▎        | 68/500 [01:48<11:15,  1.56s/it, loss=2160.0000, t=940]
Attacking:  14%|█▍        | 69/500 [01:49<11:06,  1.55s/it, loss=2160.0000, t=940]
Attacking:  14%|█▍        | 69/500 [01:50<11:06,  1.55s/it, loss=2240.0000, t=992]
Attacking:  14%|█▍        | 70/500 [01:51<10:58,  1.53s/it, loss=2240.0000, t=992]
Attacking:  14%|█▍        | 70/500 [01:51<10:58,  1.53s/it, loss=2176.0000, t=972]
Attacking:  14%|█▍        | 71/500 [01:52<10:54,  1.53s/it, loss=2176.0000, t=972]
Attacking:  14%|█▍        | 71/500 [01:53<10:54,  1.53s/it, loss=2160.0000, t=928]
Attacking:  14%|█▍        | 72/500 [01:54<10:52,  1.52s/it, loss=2160.0000, t=928]
Attacking:  14%|█▍        | 72/500 [01:54<10:52,  1.52s/it, loss=2144.0000, t=928]
Attacking:  15%|█▍        | 73/500 [01:55<10:42,  1.51s/it, loss=2144.0000, t=928]
Attacking:  15%|█▍        | 73/500 [01:56<10:42,  1.51s/it, loss=2144.0000, t=912]
Attacking:  15%|█▍        | 74/500 [01:57<10:46,  1.52s/it, loss=2144.0000, t=912]
Attacking:  15%|█▍        | 74/500 [01:58<10:46,  1.52s/it, loss=2272.0000, t=1e+3]
Attacking:  15%|█▌        | 75/500 [01:58<10:56,  1.55s/it, loss=2272.0000, t=1e+3]
Attacking:  15%|█▌        | 75/500 [01:59<10:56,  1.55s/it, loss=2224.0000, t=992] 
Attacking:  15%|█▌        | 76/500 [02:00<10:51,  1.54s/it, loss=2224.0000, t=992]
Attacking:  15%|█▌        | 76/500 [02:01<10:51,  1.54s/it, loss=2144.0000, t=928]
Attacking:  15%|█▌        | 77/500 [02:02<10:54,  1.55s/it, loss=2144.0000, t=928]
Attacking:  15%|█▌        | 77/500 [02:02<10:54,  1.55s/it, loss=2144.0000, t=900]
Attacking:  16%|█▌        | 78/500 [02:03<10:48,  1.54s/it, loss=2144.0000, t=900]
Attacking:  16%|█▌        | 78/500 [02:04<10:48,  1.54s/it, loss=2144.0000, t=912]
Attacking:  16%|█▌        | 79/500 [02:05<10:45,  1.53s/it, loss=2144.0000, t=912]
Attacking:  16%|█▌        | 79/500 [02:05<10:45,  1.53s/it, loss=2144.0000, t=912]
Attacking:  16%|█▌        | 80/500 [02:06<10:59,  1.57s/it, loss=2144.0000, t=912]
Attacking:  16%|█▌        | 80/500 [02:07<10:59,  1.57s/it, loss=2160.0000, t=952]
Attacking:  16%|█▌        | 81/500 [02:08<10:54,  1.56s/it, loss=2160.0000, t=952]
Attacking:  16%|█▌        | 81/500 [02:09<10:54,  1.56s/it, loss=2256.0000, t=1e+3]
Attacking:  16%|█▋        | 82/500 [02:09<11:09,  1.60s/it, loss=2256.0000, t=1e+3]
Attacking:  16%|█▋        | 82/500 [02:10<11:09,  1.60s/it, loss=2128.0000, t=912] 
Attacking:  17%|█▋        | 83/500 [02:11<11:11,  1.61s/it, loss=2128.0000, t=912]
Attacking:  17%|█▋        | 83/500 [02:12<11:11,  1.61s/it, loss=2256.0000, t=1e+3]
Attacking:  17%|█▋        | 84/500 [02:13<11:09,  1.61s/it, loss=2256.0000, t=1e+3]
Attacking:  17%|█▋        | 84/500 [02:13<11:09,  1.61s/it, loss=2208.0000, t=992] 
Attacking:  17%|█▋        | 85/500 [02:14<11:06,  1.61s/it, loss=2208.0000, t=992]
Attacking:  17%|█▋        | 85/500 [02:15<11:06,  1.61s/it, loss=2144.0000, t=940]
Attacking:  17%|█▋        | 86/500 [02:16<10:57,  1.59s/it, loss=2144.0000, t=940]
Attacking:  17%|█▋        | 86/500 [02:17<10:57,  1.59s/it, loss=2128.0000, t=928]
Attacking:  17%|█▋        | 87/500 [02:17<11:02,  1.60s/it, loss=2128.0000, t=928]
Attacking:  17%|█▋        | 87/500 [02:18<11:02,  1.60s/it, loss=2128.0000, t=912]
Attacking:  18%|█▊        | 88/500 [02:19<10:50,  1.58s/it, loss=2128.0000, t=912]
Attacking:  18%|█▊        | 88/500 [02:20<10:50,  1.58s/it, loss=2160.0000, t=972]
Attacking:  18%|█▊        | 89/500 [02:21<10:56,  1.60s/it, loss=2160.0000, t=972]
Attacking:  18%|█▊        | 89/500 [02:21<10:56,  1.60s/it, loss=2192.0000, t=984]
Attacking:  18%|█▊        | 90/500 [02:22<10:55,  1.60s/it, loss=2192.0000, t=984]
Attacking:  18%|█▊        | 90/500 [02:23<10:55,  1.60s/it, loss=2144.0000, t=940]
Attacking:  18%|█▊        | 91/500 [02:24<10:56,  1.61s/it, loss=2144.0000, t=940]
Attacking:  18%|█▊        | 91/500 [02:25<10:56,  1.61s/it, loss=2224.0000, t=992]
Attacking:  18%|█▊        | 92/500 [02:25<10:47,  1.59s/it, loss=2224.0000, t=992]
Attacking:  18%|█▊        | 92/500 [02:26<10:47,  1.59s/it, loss=2208.0000, t=992]
Attacking:  19%|█▊        | 93/500 [02:27<10:37,  1.57s/it, loss=2208.0000, t=992]
Attacking:  19%|█▊        | 93/500 [02:28<10:37,  1.57s/it, loss=2128.0000, t=912]
Attacking:  19%|█▉        | 94/500 [02:28<10:35,  1.56s/it, loss=2128.0000, t=912]
Attacking:  19%|█▉        | 94/500 [02:29<10:35,  1.56s/it, loss=2112.0000, t=912]
Attacking:  19%|█▉        | 95/500 [02:30<10:29,  1.56s/it, loss=2112.0000, t=912]
Attacking:  19%|█▉        | 95/500 [02:31<10:29,  1.56s/it, loss=2144.0000, t=940]
Attacking:  19%|█▉        | 96/500 [02:32<10:29,  1.56s/it, loss=2144.0000, t=940]
Attacking:  19%|█▉        | 96/500 [02:32<10:29,  1.56s/it, loss=2240.0000, t=1e+3]
Attacking:  19%|█▉        | 97/500 [02:33<10:27,  1.56s/it, loss=2240.0000, t=1e+3]
Attacking:  19%|█▉        | 97/500 [02:34<10:27,  1.56s/it, loss=2144.0000, t=972] 
Attacking:  20%|█▉        | 98/500 [02:35<10:13,  1.53s/it, loss=2144.0000, t=972]
Attacking:  20%|█▉        | 98/500 [02:35<10:13,  1.53s/it, loss=2128.0000, t=940]
Attacking:  20%|█▉        | 99/500 [02:36<10:02,  1.50s/it, loss=2128.0000, t=940]
Attacking:  20%|█▉        | 99/500 [02:37<10:02,  1.50s/it, loss=2208.0000, t=992]
Attacking:  20%|██        | 100/500 [02:38<10:03,  1.51s/it, loss=2208.0000, t=992]
Attacking:  20%|██        | 100/500 [02:38<10:03,  1.51s/it, loss=2208.0000, t=992]
Attacking:  20%|██        | 101/500 [02:39<09:59,  1.50s/it, loss=2208.0000, t=992]
Attacking:  20%|██        | 101/500 [02:40<09:59,  1.50s/it, loss=2128.0000, t=928]
Attacking:  20%|██        | 102/500 [02:41<09:57,  1.50s/it, loss=2128.0000, t=928]
Attacking:  20%|██        | 102/500 [02:41<09:57,  1.50s/it, loss=2144.0000, t=972]
Attacking:  21%|██        | 103/500 [02:42<09:52,  1.49s/it, loss=2144.0000, t=972]
Attacking:  21%|██        | 103/500 [02:43<09:52,  1.49s/it, loss=2144.0000, t=972]
Attacking:  21%|██        | 104/500 [02:44<10:03,  1.53s/it, loss=2144.0000, t=972]
Attacking:  21%|██        | 104/500 [02:44<10:03,  1.53s/it, loss=2208.0000, t=992]
Attacking:  21%|██        | 105/500 [02:45<09:52,  1.50s/it, loss=2208.0000, t=992]
Attacking:  21%|██        | 105/500 [02:46<09:52,  1.50s/it, loss=2160.0000, t=972]
Attacking:  21%|██        | 106/500 [02:47<10:01,  1.53s/it, loss=2160.0000, t=972]
Attacking:  21%|██        | 106/500 [02:47<10:01,  1.53s/it, loss=2208.0000, t=992]
Attacking:  21%|██▏       | 107/500 [02:48<09:54,  1.51s/it, loss=2208.0000, t=992]
Attacking:  21%|██▏       | 107/500 [02:49<09:54,  1.51s/it, loss=2112.0000, t=900]
Attacking:  22%|██▏       | 108/500 [02:50<09:49,  1.50s/it, loss=2112.0000, t=900]
Attacking:  22%|██▏       | 108/500 [02:50<09:49,  1.50s/it, loss=2240.0000, t=1e+3]
Attacking:  22%|██▏       | 109/500 [02:51<09:46,  1.50s/it, loss=2240.0000, t=1e+3]
Attacking:  22%|██▏       | 109/500 [02:52<09:46,  1.50s/it, loss=2112.0000, t=900] 
Attacking:  22%|██▏       | 110/500 [02:53<09:40,  1.49s/it, loss=2112.0000, t=900]
Attacking:  22%|██▏       | 110/500 [02:53<09:40,  1.49s/it, loss=2112.0000, t=912]
Attacking:  22%|██▏       | 111/500 [02:54<09:37,  1.48s/it, loss=2112.0000, t=912]
Attacking:  22%|██▏       | 111/500 [02:55<09:37,  1.48s/it, loss=2240.0000, t=1e+3]
Attacking:  22%|██▏       | 112/500 [02:56<09:36,  1.49s/it, loss=2240.0000, t=1e+3]
Attacking:  22%|██▏       | 112/500 [02:56<09:36,  1.49s/it, loss=2112.0000, t=928] 
Attacking:  23%|██▎       | 113/500 [02:57<09:35,  1.49s/it, loss=2112.0000, t=928]
Attacking:  23%|██▎       | 113/500 [02:58<09:35,  1.49s/it, loss=2176.0000, t=984]
Attacking:  23%|██▎       | 114/500 [02:58<09:29,  1.48s/it, loss=2176.0000, t=984]
Attacking:  23%|██▎       | 114/500 [02:59<09:29,  1.48s/it, loss=2224.0000, t=1e+3]
Attacking:  23%|██▎       | 115/500 [03:00<09:24,  1.47s/it, loss=2224.0000, t=1e+3]
Attacking:  23%|██▎       | 115/500 [03:01<09:24,  1.47s/it, loss=2128.0000, t=940] 
Attacking:  23%|██▎       | 116/500 [03:01<09:33,  1.49s/it, loss=2128.0000, t=940]
Attacking:  23%|██▎       | 116/500 [03:02<09:33,  1.49s/it, loss=2112.0000, t=900]
Attacking:  23%|██▎       | 117/500 [03:03<09:34,  1.50s/it, loss=2112.0000, t=900]
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Attacking: 100%|██████████| 500/500 [12:56<00:00,  1.55s/it, loss=2064.0000, t=940]
+Max Diff: 0.501961
+Mean Diff: 0.258727
+Saved adversarial image to attacked/images/horsejump-low.jpg
+Saved loss curve to attacked/loss_curve/horsejump-low_loss.png
+[GPU 3] Stage 3/3: Test
+Loading models for testing horsejump-low...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for horsejump-low...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 60.34it/s]
+Saved video to attacked/videos/horsejump-low.mp4
+Saved frames to attacked/frames/horsejump-low
+[GPU 3] Finished horsejump-low.jpg
+======================================
+[GPU 3] Processing hoverboard.jpg (Image 26/50)
+======================================
+[GPU 3] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 3] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  89%|████████▉ | 445/500 [11:33<01:27,  1.59s/it, loss=2304.0000, t=984]
Attacking:  89%|████████▉ | 445/500 [11:34<01:27,  1.59s/it, loss=2272.0000, t=972]
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Attacking:  89%|████████▉ | 447/500 [11:36<01:24,  1.59s/it, loss=2208.0000, t=912]
Attacking:  89%|████████▉ | 447/500 [11:37<01:24,  1.59s/it, loss=2224.0000, t=928]
Attacking:  90%|████████▉ | 448/500 [11:38<01:21,  1.56s/it, loss=2224.0000, t=928]
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Attacking:  91%|█████████ | 456/500 [11:51<01:08,  1.56s/it, loss=2256.0000, t=964]
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Attacking:  92%|█████████▏| 458/500 [11:54<01:03,  1.51s/it, loss=2288.0000, t=984]
Attacking:  92%|█████████▏| 459/500 [11:55<01:01,  1.49s/it, loss=2288.0000, t=984]
Attacking:  92%|█████████▏| 459/500 [11:55<01:01,  1.49s/it, loss=2304.0000, t=1e+3]
Attacking:  92%|█████████▏| 460/500 [11:56<00:58,  1.47s/it, loss=2304.0000, t=1e+3]
Attacking:  92%|█████████▏| 460/500 [11:57<00:58,  1.47s/it, loss=2272.0000, t=972] 
Attacking:  92%|█████████▏| 461/500 [11:58<00:56,  1.46s/it, loss=2272.0000, t=972]
Attacking:  92%|█████████▏| 461/500 [11:58<00:56,  1.46s/it, loss=2224.0000, t=928]
Attacking:  92%|█████████▏| 462/500 [11:59<00:55,  1.46s/it, loss=2224.0000, t=928]
Attacking:  92%|█████████▏| 462/500 [12:00<00:55,  1.46s/it, loss=2320.0000, t=992]
Attacking:  93%|█████████▎| 463/500 [12:01<00:53,  1.44s/it, loss=2320.0000, t=992]
Attacking:  93%|█████████▎| 463/500 [12:01<00:53,  1.44s/it, loss=2208.0000, t=912]
Attacking:  93%|█████████▎| 464/500 [12:02<00:52,  1.47s/it, loss=2208.0000, t=912]
Attacking:  93%|█████████▎| 464/500 [12:03<00:52,  1.47s/it, loss=2272.0000, t=972]
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Attacking:  94%|█████████▍| 470/500 [12:12<00:47,  1.57s/it, loss=2208.0000, t=900]
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Attacking:  94%|█████████▍| 471/500 [12:14<00:44,  1.55s/it, loss=2240.0000, t=952]
Attacking:  94%|█████████▍| 472/500 [12:15<00:43,  1.54s/it, loss=2240.0000, t=952]
Attacking:  94%|█████████▍| 472/500 [12:15<00:43,  1.54s/it, loss=2288.0000, t=984]
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Attacking:  95%|█████████▌| 475/500 [12:20<00:39,  1.59s/it, loss=2256.0000, t=964]
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Attacking:  95%|█████████▌| 477/500 [12:23<00:37,  1.62s/it, loss=2192.0000, t=900]
Attacking:  96%|█████████▌| 478/500 [12:24<00:35,  1.60s/it, loss=2192.0000, t=900]
Attacking:  96%|█████████▌| 478/500 [12:25<00:35,  1.60s/it, loss=2240.0000, t=964]
Attacking:  96%|█████████▌| 479/500 [12:26<00:33,  1.58s/it, loss=2240.0000, t=964]
Attacking:  96%|█████████▌| 479/500 [12:26<00:33,  1.58s/it, loss=2208.0000, t=912]
Attacking:  96%|█████████▌| 480/500 [12:27<00:30,  1.53s/it, loss=2208.0000, t=912]
Attacking:  96%|█████████▌| 480/500 [12:28<00:30,  1.53s/it, loss=2304.0000, t=984]
Attacking:  96%|█████████▌| 481/500 [12:29<00:28,  1.50s/it, loss=2304.0000, t=984]
Attacking:  96%|█████████▌| 481/500 [12:29<00:28,  1.50s/it, loss=2224.0000, t=912]
Attacking:  96%|█████████▋| 482/500 [12:30<00:27,  1.53s/it, loss=2224.0000, t=912]
Attacking:  96%|█████████▋| 482/500 [12:31<00:27,  1.53s/it, loss=2224.0000, t=952]
Attacking:  97%|█████████▋| 483/500 [12:32<00:26,  1.56s/it, loss=2224.0000, t=952]
Attacking:  97%|█████████▋| 483/500 [12:33<00:26,  1.56s/it, loss=2320.0000, t=992]
Attacking:  97%|█████████▋| 484/500 [12:33<00:25,  1.56s/it, loss=2320.0000, t=992]
Attacking:  97%|█████████▋| 484/500 [12:34<00:25,  1.56s/it, loss=2288.0000, t=1e+3]
Attacking:  97%|█████████▋| 485/500 [12:35<00:23,  1.55s/it, loss=2288.0000, t=1e+3]
Attacking:  97%|█████████▋| 485/500 [12:36<00:23,  1.55s/it, loss=2224.0000, t=900] 
Attacking:  97%|█████████▋| 486/500 [12:36<00:21,  1.54s/it, loss=2224.0000, t=900]
Attacking:  97%|█████████▋| 486/500 [12:37<00:21,  1.54s/it, loss=2224.0000, t=940]
Attacking:  97%|█████████▋| 487/500 [12:38<00:19,  1.53s/it, loss=2224.0000, t=940]
Attacking:  97%|█████████▋| 487/500 [12:39<00:19,  1.53s/it, loss=2256.0000, t=964]
Attacking:  98%|█████████▊| 488/500 [12:40<00:18,  1.54s/it, loss=2256.0000, t=964]
Attacking:  98%|█████████▊| 488/500 [12:40<00:18,  1.54s/it, loss=2240.0000, t=964]
Attacking:  98%|█████████▊| 489/500 [12:41<00:17,  1.56s/it, loss=2240.0000, t=964]
Attacking:  98%|█████████▊| 489/500 [12:42<00:17,  1.56s/it, loss=2224.0000, t=928]
Attacking:  98%|█████████▊| 490/500 [12:43<00:16,  1.66s/it, loss=2224.0000, t=928]
Attacking:  98%|█████████▊| 490/500 [12:44<00:16,  1.66s/it, loss=2224.0000, t=940]
Attacking:  98%|█████████▊| 491/500 [12:45<00:14,  1.67s/it, loss=2224.0000, t=940]
Attacking:  98%|█████████▊| 491/500 [12:46<00:14,  1.67s/it, loss=2208.0000, t=900]
Attacking:  98%|█████████▊| 492/500 [12:46<00:13,  1.66s/it, loss=2208.0000, t=900]
Attacking:  98%|█████████▊| 492/500 [12:47<00:13,  1.66s/it, loss=2224.0000, t=952]
Attacking:  99%|█████████▊| 493/500 [12:48<00:11,  1.67s/it, loss=2224.0000, t=952]
Attacking:  99%|█████████▊| 493/500 [12:49<00:11,  1.67s/it, loss=2304.0000, t=1e+3]
Attacking:  99%|█████████▉| 494/500 [12:50<00:10,  1.68s/it, loss=2304.0000, t=1e+3]
Attacking:  99%|█████████▉| 494/500 [12:50<00:10,  1.68s/it, loss=2288.0000, t=984] 
Attacking:  99%|█████████▉| 495/500 [12:51<00:08,  1.65s/it, loss=2288.0000, t=984]
Attacking:  99%|█████████▉| 495/500 [12:52<00:08,  1.65s/it, loss=2224.0000, t=928]
Attacking:  99%|█████████▉| 496/500 [12:53<00:06,  1.63s/it, loss=2224.0000, t=928]
Attacking:  99%|█████████▉| 496/500 [12:54<00:06,  1.63s/it, loss=2304.0000, t=1e+3]
Attacking:  99%|█████████▉| 497/500 [12:54<00:04,  1.59s/it, loss=2304.0000, t=1e+3]
Attacking:  99%|█████████▉| 497/500 [12:55<00:04,  1.59s/it, loss=2224.0000, t=928] 
Attacking: 100%|█████████▉| 498/500 [12:56<00:03,  1.56s/it, loss=2224.0000, t=928]
Attacking: 100%|█████████▉| 498/500 [12:57<00:03,  1.56s/it, loss=2304.0000, t=992]
Attacking: 100%|█████████▉| 499/500 [12:58<00:01,  1.58s/it, loss=2304.0000, t=992]
Attacking: 100%|█████████▉| 499/500 [12:58<00:01,  1.58s/it, loss=2304.0000, t=984]
Attacking: 100%|██████████| 500/500 [12:59<00:00,  1.57s/it, loss=2304.0000, t=984]
Attacking: 100%|██████████| 500/500 [12:59<00:00,  1.56s/it, loss=2304.0000, t=984]
+Max Diff: 0.501961
+Mean Diff: 0.256167
+Saved adversarial image to attacked/images/hoverboard.jpg
+Saved loss curve to attacked/loss_curve/hoverboard_loss.png
+[GPU 3] Stage 3/3: Test
+Loading models for testing hoverboard...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for hoverboard...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 50.95it/s]
+Saved video to attacked/videos/hoverboard.mp4
+Saved frames to attacked/frames/hoverboard
+[GPU 3] Finished hoverboard.jpg
+======================================
+[GPU 3] Processing libby.jpg (Image 27/50)
+======================================
+[GPU 3] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 3] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   5%|▌         | 27/500 [00:43<12:06,  1.54s/it, loss=2128.0000, t=984]
Attacking:   6%|▌         | 28/500 [00:44<11:54,  1.51s/it, loss=2128.0000, t=984]
Attacking:   6%|▌         | 28/500 [00:45<11:54,  1.51s/it, loss=2048.0000, t=952]
Attacking:   6%|▌         | 29/500 [00:46<11:39,  1.49s/it, loss=2048.0000, t=952]
Attacking:   6%|▌         | 29/500 [00:46<11:39,  1.49s/it, loss=2112.0000, t=992]
Attacking:   6%|▌         | 30/500 [00:47<11:43,  1.50s/it, loss=2112.0000, t=992]
Attacking:   6%|▌         | 30/500 [00:48<11:43,  1.50s/it, loss=2048.0000, t=964]
Attacking:   6%|▌         | 31/500 [00:49<11:41,  1.50s/it, loss=2048.0000, t=964]
Attacking:   6%|▌         | 31/500 [00:49<11:41,  1.50s/it, loss=2112.0000, t=984]
Attacking:   6%|▋         | 32/500 [00:50<11:48,  1.51s/it, loss=2112.0000, t=984]
Attacking:   6%|▋         | 32/500 [00:51<11:48,  1.51s/it, loss=2016.0000, t=940]
Attacking:   7%|▋         | 33/500 [00:52<11:38,  1.50s/it, loss=2016.0000, t=940]
Attacking:   7%|▋         | 33/500 [00:52<11:38,  1.50s/it, loss=2024.0000, t=952]
Attacking:   7%|▋         | 34/500 [00:53<11:40,  1.50s/it, loss=2024.0000, t=952]
Attacking:   7%|▋         | 34/500 [00:54<11:40,  1.50s/it, loss=2064.0000, t=972]
Attacking:   7%|▋         | 35/500 [00:55<11:37,  1.50s/it, loss=2064.0000, t=972]
Attacking:   7%|▋         | 35/500 [00:56<11:37,  1.50s/it, loss=2064.0000, t=972]
Attacking:   7%|▋         | 36/500 [00:56<12:08,  1.57s/it, loss=2064.0000, t=972]
Attacking:   7%|▋         | 36/500 [00:57<12:08,  1.57s/it, loss=1992.0000, t=928]
Attacking:   7%|▋         | 37/500 [00:58<12:14,  1.59s/it, loss=1992.0000, t=928]
Attacking:   7%|▋         | 37/500 [00:59<12:14,  1.59s/it, loss=2096.0000, t=984]
Attacking:   8%|▊         | 38/500 [01:00<12:22,  1.61s/it, loss=2096.0000, t=984]
Attacking:   8%|▊         | 38/500 [01:00<12:22,  1.61s/it, loss=2064.0000, t=1e+3]
Attacking:   8%|▊         | 39/500 [01:01<12:25,  1.62s/it, loss=2064.0000, t=1e+3]
Attacking:   8%|▊         | 39/500 [01:02<12:25,  1.62s/it, loss=2064.0000, t=1e+3]
Attacking:   8%|▊         | 40/500 [01:03<12:07,  1.58s/it, loss=2064.0000, t=1e+3]
Attacking:   8%|▊         | 40/500 [01:04<12:07,  1.58s/it, loss=1984.0000, t=900] 
Attacking:   8%|▊         | 41/500 [01:05<12:15,  1.60s/it, loss=1984.0000, t=900]
Attacking:   8%|▊         | 41/500 [01:05<12:15,  1.60s/it, loss=2016.0000, t=952]
Attacking:   8%|▊         | 42/500 [01:06<12:29,  1.64s/it, loss=2016.0000, t=952]
Attacking:   8%|▊         | 42/500 [01:07<12:29,  1.64s/it, loss=2064.0000, t=992]
Attacking:   9%|▊         | 43/500 [01:08<12:26,  1.63s/it, loss=2064.0000, t=992]
Attacking:   9%|▊         | 43/500 [01:09<12:26,  1.63s/it, loss=1960.0000, t=900]
Attacking:   9%|▉         | 44/500 [01:09<12:16,  1.62s/it, loss=1960.0000, t=900]
Attacking:   9%|▉         | 44/500 [01:10<12:16,  1.62s/it, loss=2000.0000, t=940]
Attacking:   9%|▉         | 45/500 [01:11<12:26,  1.64s/it, loss=2000.0000, t=940]
Attacking:   9%|▉         | 45/500 [01:12<12:26,  1.64s/it, loss=2016.0000, t=964]
Attacking:   9%|▉         | 46/500 [01:13<12:28,  1.65s/it, loss=2016.0000, t=964]
Attacking:   9%|▉         | 46/500 [01:14<12:28,  1.65s/it, loss=2064.0000, t=1e+3]
Attacking:   9%|▉         | 47/500 [01:14<12:33,  1.66s/it, loss=2064.0000, t=1e+3]
Attacking:   9%|▉         | 47/500 [01:15<12:33,  1.66s/it, loss=2048.0000, t=1e+3]
Attacking:  10%|▉         | 48/500 [01:16<12:24,  1.65s/it, loss=2048.0000, t=1e+3]
Attacking:  10%|▉         | 48/500 [01:17<12:24,  1.65s/it, loss=1984.0000, t=940] 
Attacking:  10%|▉         | 49/500 [01:18<12:14,  1.63s/it, loss=1984.0000, t=940]
Attacking:  10%|▉         | 49/500 [01:18<12:14,  1.63s/it, loss=2024.0000, t=952]
Attacking:  10%|█         | 50/500 [01:19<11:53,  1.59s/it, loss=2024.0000, t=952]
Attacking:  10%|█         | 50/500 [01:20<11:53,  1.59s/it, loss=2048.0000, t=1e+3]
Attacking:  10%|█         | 51/500 [01:21<11:41,  1.56s/it, loss=2048.0000, t=1e+3]
Attacking:  10%|█         | 51/500 [01:21<11:41,  1.56s/it, loss=2064.0000, t=992] 
Attacking:  10%|█         | 52/500 [01:22<11:27,  1.53s/it, loss=2064.0000, t=992]
Attacking:  10%|█         | 52/500 [01:23<11:27,  1.53s/it, loss=1992.0000, t=952]
Attacking:  11%|█         | 53/500 [01:24<11:25,  1.53s/it, loss=1992.0000, t=952]
Attacking:  11%|█         | 53/500 [01:24<11:25,  1.53s/it, loss=2048.0000, t=992]
Attacking:  11%|█         | 54/500 [01:25<11:03,  1.49s/it, loss=2048.0000, t=992]
Attacking:  11%|█         | 54/500 [01:26<11:03,  1.49s/it, loss=1952.0000, t=900]
Attacking:  11%|█         | 55/500 [01:26<10:53,  1.47s/it, loss=1952.0000, t=900]
Attacking:  11%|█         | 55/500 [01:27<10:53,  1.47s/it, loss=2000.0000, t=952]
Attacking:  11%|█         | 56/500 [01:28<11:03,  1.49s/it, loss=2000.0000, t=952]
Attacking:  11%|█         | 56/500 [01:29<11:03,  1.49s/it, loss=1984.0000, t=940]
Attacking:  11%|█▏        | 57/500 [01:30<11:03,  1.50s/it, loss=1984.0000, t=940]
Attacking:  11%|█▏        | 57/500 [01:30<11:03,  1.50s/it, loss=2048.0000, t=1e+3]
Attacking:  12%|█▏        | 58/500 [01:31<11:11,  1.52s/it, loss=2048.0000, t=1e+3]
Attacking:  12%|█▏        | 58/500 [01:32<11:11,  1.52s/it, loss=2024.0000, t=972] 
Attacking:  12%|█▏        | 59/500 [01:33<12:04,  1.64s/it, loss=2024.0000, t=972]
Attacking:  12%|█▏        | 59/500 [01:34<12:04,  1.64s/it, loss=2040.0000, t=1e+3]
Attacking:  12%|█▏        | 60/500 [01:35<11:39,  1.59s/it, loss=2040.0000, t=1e+3]
Attacking:  12%|█▏        | 60/500 [01:35<11:39,  1.59s/it, loss=1960.0000, t=928] 
Attacking:  12%|█▏        | 61/500 [01:36<11:24,  1.56s/it, loss=1960.0000, t=928]
Attacking:  12%|█▏        | 61/500 [01:37<11:24,  1.56s/it, loss=1952.0000, t=928]
Attacking:  12%|█▏        | 62/500 [01:38<11:19,  1.55s/it, loss=1952.0000, t=928]
Attacking:  12%|█▏        | 62/500 [01:38<11:19,  1.55s/it, loss=1976.0000, t=952]
Attacking:  13%|█▎        | 63/500 [01:39<11:23,  1.56s/it, loss=1976.0000, t=952]
Attacking:  13%|█▎        | 63/500 [01:40<11:23,  1.56s/it, loss=1952.0000, t=912]
Attacking:  13%|█▎        | 64/500 [01:41<11:36,  1.60s/it, loss=1952.0000, t=912]
Attacking:  13%|█▎        | 64/500 [01:42<11:36,  1.60s/it, loss=2032.0000, t=992]
Attacking:  13%|█▎        | 65/500 [01:43<11:52,  1.64s/it, loss=2032.0000, t=992]
Attacking:  13%|█▎        | 65/500 [01:43<11:52,  1.64s/it, loss=1976.0000, t=952]
Attacking:  13%|█▎        | 66/500 [01:44<11:38,  1.61s/it, loss=1976.0000, t=952]
Attacking:  13%|█▎        | 66/500 [01:45<11:38,  1.61s/it, loss=2000.0000, t=964]
Attacking:  13%|█▎        | 67/500 [01:46<11:29,  1.59s/it, loss=2000.0000, t=964]
Attacking:  13%|█▎        | 67/500 [01:46<11:29,  1.59s/it, loss=2048.0000, t=984]
Attacking:  14%|█▎        | 68/500 [01:47<11:39,  1.62s/it, loss=2048.0000, t=984]
Attacking:  14%|█▎        | 68/500 [01:48<11:39,  1.62s/it, loss=2032.0000, t=992]
Attacking:  14%|█▍        | 69/500 [01:49<11:27,  1.60s/it, loss=2032.0000, t=992]
Attacking:  14%|█▍        | 69/500 [01:50<11:27,  1.60s/it, loss=1936.0000, t=900]
Attacking:  14%|█▍        | 70/500 [01:50<11:22,  1.59s/it, loss=1936.0000, t=900]
Attacking:  14%|█▍        | 70/500 [01:51<11:22,  1.59s/it, loss=2024.0000, t=1e+3]
Attacking:  14%|█▍        | 71/500 [01:52<11:39,  1.63s/it, loss=2024.0000, t=1e+3]
Attacking:  14%|█▍        | 71/500 [01:53<11:39,  1.63s/it, loss=2000.0000, t=972] 
Attacking:  14%|█▍        | 72/500 [01:54<11:35,  1.62s/it, loss=2000.0000, t=972]
Attacking:  14%|█▍        | 72/500 [01:54<11:35,  1.62s/it, loss=2024.0000, t=992]
Attacking:  15%|█▍        | 73/500 [01:55<11:13,  1.58s/it, loss=2024.0000, t=992]
Attacking:  15%|█▍        | 73/500 [01:56<11:13,  1.58s/it, loss=1944.0000, t=928]
Attacking:  15%|█▍        | 74/500 [01:57<11:03,  1.56s/it, loss=1944.0000, t=928]
Attacking:  15%|█▍        | 74/500 [01:57<11:03,  1.56s/it, loss=2008.0000, t=972]
Attacking:  15%|█▌        | 75/500 [01:58<10:56,  1.54s/it, loss=2008.0000, t=972]
Attacking:  15%|█▌        | 75/500 [01:59<10:56,  1.54s/it, loss=2016.0000, t=1e+3]
Attacking:  15%|█▌        | 76/500 [02:00<10:52,  1.54s/it, loss=2016.0000, t=1e+3]
Attacking:  15%|█▌        | 76/500 [02:00<10:52,  1.54s/it, loss=1928.0000, t=912] 
Attacking:  15%|█▌        | 77/500 [02:01<10:45,  1.53s/it, loss=1928.0000, t=912]
Attacking:  15%|█▌        | 77/500 [02:02<10:45,  1.53s/it, loss=1944.0000, t=940]
Attacking:  16%|█▌        | 78/500 [02:03<10:34,  1.50s/it, loss=1944.0000, t=940]
Attacking:  16%|█▌        | 78/500 [02:03<10:34,  1.50s/it, loss=1912.0000, t=900]
Attacking:  16%|█▌        | 79/500 [02:04<10:52,  1.55s/it, loss=1912.0000, t=900]
Attacking:  16%|█▌        | 79/500 [02:05<10:52,  1.55s/it, loss=1984.0000, t=964]
Attacking:  16%|█▌        | 80/500 [02:06<10:49,  1.55s/it, loss=1984.0000, t=964]
Attacking:  16%|█▌        | 80/500 [02:07<10:49,  1.55s/it, loss=1968.0000, t=940]
Attacking:  16%|█▌        | 81/500 [02:07<10:38,  1.52s/it, loss=1968.0000, t=940]
Attacking:  16%|█▌        | 81/500 [02:08<10:38,  1.52s/it, loss=1912.0000, t=900]
Attacking:  16%|█▋        | 82/500 [02:09<10:29,  1.51s/it, loss=1912.0000, t=900]
Attacking:  16%|█▋        | 82/500 [02:10<10:29,  1.51s/it, loss=1920.0000, t=912]
Attacking:  17%|█▋        | 83/500 [02:10<10:38,  1.53s/it, loss=1920.0000, t=912]
Attacking:  17%|█▋        | 83/500 [02:11<10:38,  1.53s/it, loss=2032.0000, t=984]
Attacking:  17%|█▋        | 84/500 [02:12<10:30,  1.52s/it, loss=2032.0000, t=984]
Attacking:  17%|█▋        | 84/500 [02:13<10:30,  1.52s/it, loss=1968.0000, t=964]
Attacking:  17%|█▋        | 85/500 [02:13<10:28,  1.51s/it, loss=1968.0000, t=964]
Attacking:  17%|█▋        | 85/500 [02:14<10:28,  1.51s/it, loss=1984.0000, t=972]
Attacking:  17%|█▋        | 86/500 [02:15<10:33,  1.53s/it, loss=1984.0000, t=972]
Attacking:  17%|█▋        | 86/500 [02:16<10:33,  1.53s/it, loss=1984.0000, t=964]
Attacking:  17%|█▋        | 87/500 [02:17<10:31,  1.53s/it, loss=1984.0000, t=964]
Attacking:  17%|█▋        | 87/500 [02:17<10:31,  1.53s/it, loss=1968.0000, t=964]
Attacking:  18%|█▊        | 88/500 [02:18<10:21,  1.51s/it, loss=1968.0000, t=964]
Attacking:  18%|█▊        | 88/500 [02:19<10:21,  1.51s/it, loss=2000.0000, t=1e+3]
Attacking:  18%|█▊        | 89/500 [02:20<10:21,  1.51s/it, loss=2000.0000, t=1e+3]
Attacking:  18%|█▊        | 89/500 [02:20<10:21,  1.51s/it, loss=1952.0000, t=952] 
Attacking:  18%|█▊        | 90/500 [02:21<10:22,  1.52s/it, loss=1952.0000, t=952]
Attacking:  18%|█▊        | 90/500 [02:22<10:22,  1.52s/it, loss=2000.0000, t=1e+3]
Attacking:  18%|█▊        | 91/500 [02:23<10:15,  1.50s/it, loss=2000.0000, t=1e+3]
Attacking:  18%|█▊        | 91/500 [02:23<10:15,  1.50s/it, loss=1992.0000, t=1e+3]
Attacking:  18%|█▊        | 92/500 [02:24<10:10,  1.50s/it, loss=1992.0000, t=1e+3]
Attacking:  18%|█▊        | 92/500 [02:25<10:10,  1.50s/it, loss=1928.0000, t=940] 
Attacking:  19%|█▊        | 93/500 [02:25<10:08,  1.49s/it, loss=1928.0000, t=940]
Attacking:  19%|█▊        | 93/500 [02:26<10:08,  1.49s/it, loss=1928.0000, t=940]
Attacking:  19%|█▉        | 94/500 [02:27<10:15,  1.52s/it, loss=1928.0000, t=940]
Attacking:  19%|█▉        | 94/500 [02:28<10:15,  1.52s/it, loss=2008.0000, t=1e+3]
Attacking:  19%|█▉        | 95/500 [02:29<10:23,  1.54s/it, loss=2008.0000, t=1e+3]
Attacking:  19%|█▉        | 95/500 [02:29<10:23,  1.54s/it, loss=2008.0000, t=984] 
Attacking:  19%|█▉        | 96/500 [02:30<10:29,  1.56s/it, loss=2008.0000, t=984]
Attacking:  19%|█▉        | 96/500 [02:31<10:29,  1.56s/it, loss=1936.0000, t=928]
Attacking:  19%|█▉        | 97/500 [02:32<10:36,  1.58s/it, loss=1936.0000, t=928]
Attacking:  19%|█▉        | 97/500 [02:33<10:36,  1.58s/it, loss=1960.0000, t=964]
Attacking:  20%|█▉        | 98/500 [02:33<10:25,  1.55s/it, loss=1960.0000, t=964]
Attacking:  20%|█▉        | 98/500 [02:34<10:25,  1.55s/it, loss=1920.0000, t=940]
Attacking:  20%|█▉        | 99/500 [02:35<10:19,  1.54s/it, loss=1920.0000, t=940]
Attacking:  20%|█▉        | 99/500 [02:36<10:19,  1.54s/it, loss=2008.0000, t=984]
Attacking:  20%|██        | 100/500 [02:36<10:20,  1.55s/it, loss=2008.0000, t=984]
Attacking:  20%|██        | 100/500 [02:37<10:20,  1.55s/it, loss=2008.0000, t=984]
Attacking:  20%|██        | 101/500 [02:38<10:09,  1.53s/it, loss=2008.0000, t=984]
Attacking:  20%|██        | 101/500 [02:39<10:09,  1.53s/it, loss=1920.0000, t=928]
Attacking:  20%|██        | 102/500 [02:39<09:59,  1.51s/it, loss=1920.0000, t=928]
Attacking:  20%|██        | 102/500 [02:40<09:59,  1.51s/it, loss=1992.0000, t=1e+3]
Attacking:  21%|██        | 103/500 [02:41<09:45,  1.48s/it, loss=1992.0000, t=1e+3]
Attacking:  21%|██        | 103/500 [02:41<09:45,  1.48s/it, loss=1920.0000, t=928] 
Attacking:  21%|██        | 104/500 [02:42<09:40,  1.47s/it, loss=1920.0000, t=928]
Attacking:  21%|██        | 104/500 [02:43<09:40,  1.47s/it, loss=1944.0000, t=952]
Attacking:  21%|██        | 105/500 [02:44<09:37,  1.46s/it, loss=1944.0000, t=952]
Attacking:  21%|██        | 105/500 [02:44<09:37,  1.46s/it, loss=1904.0000, t=912]
Attacking:  21%|██        | 106/500 [02:45<09:43,  1.48s/it, loss=1904.0000, t=912]
Attacking:  21%|██        | 106/500 [02:46<09:43,  1.48s/it, loss=1904.0000, t=912]
Attacking:  21%|██▏       | 107/500 [02:47<09:41,  1.48s/it, loss=1904.0000, t=912]
Attacking:  21%|██▏       | 107/500 [02:47<09:41,  1.48s/it, loss=1912.0000, t=928]
Attacking:  22%|██▏       | 108/500 [02:48<09:43,  1.49s/it, loss=1912.0000, t=928]
Attacking:  22%|██▏       | 108/500 [02:49<09:43,  1.49s/it, loss=1936.0000, t=952]
Attacking:  22%|██▏       | 109/500 [02:50<09:31,  1.46s/it, loss=1936.0000, t=952]
Attacking:  22%|██▏       | 109/500 [02:50<09:31,  1.46s/it, loss=1968.0000, t=972]
Attacking:  22%|██▏       | 110/500 [02:51<09:42,  1.49s/it, loss=1968.0000, t=972]
Attacking:  22%|██▏       | 110/500 [02:52<09:42,  1.49s/it, loss=1952.0000, t=964]
Attacking:  22%|██▏       | 111/500 [02:53<09:52,  1.52s/it, loss=1952.0000, t=964]
Attacking:  22%|██▏       | 111/500 [02:53<09:52,  1.52s/it, loss=1912.0000, t=928]
Attacking:  22%|██▏       | 112/500 [02:54<09:42,  1.50s/it, loss=1912.0000, t=928]
Attacking:  22%|██▏       | 112/500 [02:55<09:42,  1.50s/it, loss=1904.0000, t=928]
Attacking:  23%|██▎       | 113/500 [02:56<09:37,  1.49s/it, loss=1904.0000, t=928]
Attacking:  23%|██▎       | 113/500 [02:56<09:37,  1.49s/it, loss=1984.0000, t=1e+3]
Attacking:  23%|██▎       | 114/500 [02:57<09:36,  1.49s/it, loss=1984.0000, t=1e+3]
Attacking:  23%|██▎       | 114/500 [02:58<09:36,  1.49s/it, loss=1984.0000, t=992] 
Attacking:  23%|██▎       | 115/500 [02:59<09:41,  1.51s/it, loss=1984.0000, t=992]
Attacking:  23%|██▎       | 115/500 [02:59<09:41,  1.51s/it, loss=1920.0000, t=940]
Attacking:  23%|██▎       | 116/500 [03:00<09:46,  1.53s/it, loss=1920.0000, t=940]
Attacking:  23%|██▎       | 116/500 [03:01<09:46,  1.53s/it, loss=1904.0000, t=928]
Attacking:  23%|██▎       | 117/500 [03:02<09:38,  1.51s/it, loss=1904.0000, t=928]
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Attacking:  24%|██▎       | 118/500 [03:03<09:35,  1.51s/it, loss=1936.0000, t=952]
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Attacking:  98%|█████████▊| 492/500 [12:33<00:11,  1.42s/it, loss=1920.0000, t=992]
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Attacking:  99%|█████████▉| 496/500 [12:39<00:05,  1.38s/it, loss=1904.0000, t=972]
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Attacking:  99%|█████████▉| 497/500 [12:40<00:04,  1.37s/it, loss=1832.0000, t=912]
Attacking: 100%|█████████▉| 498/500 [12:41<00:02,  1.37s/it, loss=1832.0000, t=912]
Attacking: 100%|█████████▉| 498/500 [12:41<00:02,  1.37s/it, loss=1856.0000, t=940]
Attacking: 100%|█████████▉| 499/500 [12:42<00:01,  1.38s/it, loss=1856.0000, t=940]
Attacking: 100%|█████████▉| 499/500 [12:43<00:01,  1.38s/it, loss=1824.0000, t=900]
Attacking: 100%|██████████| 500/500 [12:44<00:00,  1.37s/it, loss=1824.0000, t=900]
Attacking: 100%|██████████| 500/500 [12:44<00:00,  1.53s/it, loss=1824.0000, t=900]
+Max Diff: 0.501961
+Mean Diff: 0.223016
+Saved adversarial image to attacked/images/libby.jpg
+Saved loss curve to attacked/loss_curve/libby_loss.png
+[GPU 3] Stage 3/3: Test
diff --git a/experiments/cfg3_eps64/logs/gpu_4.log b/experiments/cfg3_eps64/logs/gpu_4.log
new file mode 100644
index 0000000000000000000000000000000000000000..ebd43d7077aabc9a7094c8a9f65e3b076cb9f457
--- /dev/null
+++ b/experiments/cfg3_eps64/logs/gpu_4.log
@@ -0,0 +1,483 @@
+[GPU 4] Starting work on images 28 to 34
+======================================
+[GPU 4] Processing lucia.jpg (Image 28/50)
+======================================
+[GPU 4] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 4] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   2%|▏         | 10/500 [00:15<11:44,  1.44s/it, loss=2400.0000, t=972]
Attacking:   2%|▏         | 11/500 [00:16<11:49,  1.45s/it, loss=2400.0000, t=972]
Attacking:   2%|▏         | 11/500 [00:17<11:49,  1.45s/it, loss=2384.0000, t=972]
Attacking:   2%|▏         | 12/500 [00:18<11:55,  1.47s/it, loss=2384.0000, t=972]
Attacking:   2%|▏         | 12/500 [00:18<11:55,  1.47s/it, loss=2368.0000, t=928]
Attacking:   3%|▎         | 13/500 [00:19<12:36,  1.55s/it, loss=2368.0000, t=928]
Attacking:   3%|▎         | 13/500 [00:20<12:36,  1.55s/it, loss=2368.0000, t=964]
Attacking:   3%|▎         | 14/500 [00:21<12:53,  1.59s/it, loss=2368.0000, t=964]
Attacking:   3%|▎         | 14/500 [00:22<12:53,  1.59s/it, loss=2384.0000, t=952]
Attacking:   3%|▎         | 15/500 [00:23<12:52,  1.59s/it, loss=2384.0000, t=952]
Attacking:   3%|▎         | 15/500 [00:23<12:52,  1.59s/it, loss=2368.0000, t=964]
Attacking:   3%|▎         | 16/500 [00:24<13:10,  1.63s/it, loss=2368.0000, t=964]
Attacking:   3%|▎         | 16/500 [00:25<13:10,  1.63s/it, loss=2384.0000, t=984]
Attacking:   3%|▎         | 17/500 [00:26<12:42,  1.58s/it, loss=2384.0000, t=984]
Attacking:   3%|▎         | 17/500 [00:26<12:42,  1.58s/it, loss=2368.0000, t=972]
Attacking:   4%|▎         | 18/500 [00:27<12:32,  1.56s/it, loss=2368.0000, t=972]
Attacking:   4%|▎         | 18/500 [00:28<12:32,  1.56s/it, loss=2400.0000, t=992]
Attacking:   4%|▍         | 19/500 [00:29<12:16,  1.53s/it, loss=2400.0000, t=992]
Attacking:   4%|▍         | 19/500 [00:29<12:16,  1.53s/it, loss=2352.0000, t=972]
Attacking:   4%|▍         | 20/500 [00:30<12:09,  1.52s/it, loss=2352.0000, t=972]
Attacking:   4%|▍         | 20/500 [00:31<12:09,  1.52s/it, loss=2448.0000, t=1e+3]
Attacking:   4%|▍         | 21/500 [00:32<12:08,  1.52s/it, loss=2448.0000, t=1e+3]
Attacking:   4%|▍         | 21/500 [00:32<12:08,  1.52s/it, loss=2432.0000, t=1e+3]
Attacking:   4%|▍         | 22/500 [00:33<12:01,  1.51s/it, loss=2432.0000, t=1e+3]
Attacking:   4%|▍         | 22/500 [00:34<12:01,  1.51s/it, loss=2336.0000, t=964] 
Attacking:   5%|▍         | 23/500 [00:35<11:53,  1.50s/it, loss=2336.0000, t=964]
Attacking:   5%|▍         | 23/500 [00:35<11:53,  1.50s/it, loss=2352.0000, t=964]
Attacking:   5%|▍         | 24/500 [00:36<11:51,  1.49s/it, loss=2352.0000, t=964]
Attacking:   5%|▍         | 24/500 [00:37<11:51,  1.49s/it, loss=2352.0000, t=984]
Attacking:   5%|▌         | 25/500 [00:38<12:10,  1.54s/it, loss=2352.0000, t=984]
Attacking:   5%|▌         | 25/500 [00:39<12:10,  1.54s/it, loss=2320.0000, t=972]
Attacking:   5%|▌         | 26/500 [00:40<12:34,  1.59s/it, loss=2320.0000, t=972]
Attacking:   5%|▌         | 26/500 [00:40<12:34,  1.59s/it, loss=2320.0000, t=928]
Attacking:   5%|▌         | 27/500 [00:41<12:30,  1.59s/it, loss=2320.0000, t=928]
Attacking:   5%|▌         | 27/500 [00:42<12:30,  1.59s/it, loss=2336.0000, t=952]
Attacking:   6%|▌         | 28/500 [00:43<12:32,  1.59s/it, loss=2336.0000, t=952]
Attacking:   6%|▌         | 28/500 [00:43<12:32,  1.59s/it, loss=2336.0000, t=940]
Attacking:   6%|▌         | 29/500 [00:44<12:25,  1.58s/it, loss=2336.0000, t=940]
Attacking:   6%|▌         | 29/500 [00:45<12:25,  1.58s/it, loss=2320.0000, t=952]
Attacking:   6%|▌         | 30/500 [00:46<12:40,  1.62s/it, loss=2320.0000, t=952]
Attacking:   6%|▌         | 30/500 [00:47<12:40,  1.62s/it, loss=2320.0000, t=964]
Attacking:   6%|▌         | 31/500 [00:48<12:49,  1.64s/it, loss=2320.0000, t=964]
Attacking:   6%|▌         | 31/500 [00:48<12:49,  1.64s/it, loss=2320.0000, t=952]
Attacking:   6%|▋         | 32/500 [00:49<12:30,  1.60s/it, loss=2320.0000, t=952]
Attacking:   6%|▋         | 32/500 [00:50<12:30,  1.60s/it, loss=2400.0000, t=1e+3]
Attacking:   7%|▋         | 33/500 [00:51<12:22,  1.59s/it, loss=2400.0000, t=1e+3]
Attacking:   7%|▋         | 33/500 [00:51<12:22,  1.59s/it, loss=2400.0000, t=1e+3]
Attacking:   7%|▋         | 34/500 [00:52<12:26,  1.60s/it, loss=2400.0000, t=1e+3]
Attacking:   7%|▋         | 34/500 [00:53<12:26,  1.60s/it, loss=2400.0000, t=1e+3]
Attacking:   7%|▋         | 35/500 [00:54<12:15,  1.58s/it, loss=2400.0000, t=1e+3]
Attacking:   7%|▋         | 35/500 [00:55<12:15,  1.58s/it, loss=2304.0000, t=928] 
Attacking:   7%|▋         | 36/500 [00:56<12:16,  1.59s/it, loss=2304.0000, t=928]
Attacking:   7%|▋         | 36/500 [00:56<12:16,  1.59s/it, loss=2368.0000, t=992]
Attacking:   7%|▋         | 37/500 [00:57<12:19,  1.60s/it, loss=2368.0000, t=992]
Attacking:   7%|▋         | 37/500 [00:58<12:19,  1.60s/it, loss=2384.0000, t=1e+3]
Attacking:   8%|▊         | 38/500 [00:59<12:29,  1.62s/it, loss=2384.0000, t=1e+3]
Attacking:   8%|▊         | 38/500 [01:00<12:29,  1.62s/it, loss=2304.0000, t=912] 
Attacking:   8%|▊         | 39/500 [01:00<12:23,  1.61s/it, loss=2304.0000, t=912]
Attacking:   8%|▊         | 39/500 [01:01<12:23,  1.61s/it, loss=2304.0000, t=912]
Attacking:   8%|▊         | 40/500 [01:02<12:29,  1.63s/it, loss=2304.0000, t=912]
Attacking:   8%|▊         | 40/500 [01:03<12:29,  1.63s/it, loss=2288.0000, t=972]
Attacking:   8%|▊         | 41/500 [01:04<12:27,  1.63s/it, loss=2288.0000, t=972]
Attacking:   8%|▊         | 41/500 [01:04<12:27,  1.63s/it, loss=2304.0000, t=940]
Attacking:   8%|▊         | 42/500 [01:05<12:03,  1.58s/it, loss=2304.0000, t=940]
Attacking:   8%|▊         | 42/500 [01:06<12:03,  1.58s/it, loss=2304.0000, t=984]
Attacking:   9%|▊         | 43/500 [01:07<11:55,  1.57s/it, loss=2304.0000, t=984]
Attacking:   9%|▊         | 43/500 [01:07<11:55,  1.57s/it, loss=2288.0000, t=952]
Attacking:   9%|▉         | 44/500 [01:08<11:43,  1.54s/it, loss=2288.0000, t=952]
Attacking:   9%|▉         | 44/500 [01:09<11:43,  1.54s/it, loss=2304.0000, t=912]
Attacking:   9%|▉         | 45/500 [01:10<11:46,  1.55s/it, loss=2304.0000, t=912]
Attacking:   9%|▉         | 45/500 [01:11<11:46,  1.55s/it, loss=2288.0000, t=972]
Attacking:   9%|▉         | 46/500 [01:11<11:58,  1.58s/it, loss=2288.0000, t=972]
Attacking:   9%|▉         | 46/500 [01:12<11:58,  1.58s/it, loss=2336.0000, t=992]
Attacking:   9%|▉         | 47/500 [01:13<11:41,  1.55s/it, loss=2336.0000, t=992]
Attacking:   9%|▉         | 47/500 [01:13<11:41,  1.55s/it, loss=2272.0000, t=928]
Attacking:  10%|▉         | 48/500 [01:14<11:27,  1.52s/it, loss=2272.0000, t=928]
Attacking:  10%|▉         | 48/500 [01:15<11:27,  1.52s/it, loss=2272.0000, t=912]
Attacking:  10%|▉         | 49/500 [01:16<11:19,  1.51s/it, loss=2272.0000, t=912]
Attacking:  10%|▉         | 49/500 [01:17<11:19,  1.51s/it, loss=2272.0000, t=964]
Attacking:  10%|█         | 50/500 [01:17<11:34,  1.54s/it, loss=2272.0000, t=964]
Attacking:  10%|█         | 50/500 [01:18<11:34,  1.54s/it, loss=2272.0000, t=964]
Attacking:  10%|█         | 51/500 [01:19<12:01,  1.61s/it, loss=2272.0000, t=964]
Attacking:  10%|█         | 51/500 [01:20<12:01,  1.61s/it, loss=2288.0000, t=984]
Attacking:  10%|█         | 52/500 [01:21<12:25,  1.67s/it, loss=2288.0000, t=984]
Attacking:  10%|█         | 52/500 [01:22<12:25,  1.67s/it, loss=2256.0000, t=912]
Attacking:  11%|█         | 53/500 [01:23<12:41,  1.70s/it, loss=2256.0000, t=912]
Attacking:  11%|█         | 53/500 [01:24<12:41,  1.70s/it, loss=2256.0000, t=900]
Attacking:  11%|█         | 54/500 [01:25<12:42,  1.71s/it, loss=2256.0000, t=900]
Attacking:  11%|█         | 54/500 [01:25<12:42,  1.71s/it, loss=2272.0000, t=940]
Attacking:  11%|█         | 55/500 [01:26<12:47,  1.73s/it, loss=2272.0000, t=940]
Attacking:  11%|█         | 55/500 [01:27<12:47,  1.73s/it, loss=2272.0000, t=900]
Attacking:  11%|█         | 56/500 [01:28<12:48,  1.73s/it, loss=2272.0000, t=900]
Attacking:  11%|█         | 56/500 [01:29<12:48,  1.73s/it, loss=2256.0000, t=964]
Attacking:  11%|█▏        | 57/500 [01:30<12:51,  1.74s/it, loss=2256.0000, t=964]
Attacking:  11%|█▏        | 57/500 [01:31<12:51,  1.74s/it, loss=2256.0000, t=964]
Attacking:  12%|█▏        | 58/500 [01:31<12:36,  1.71s/it, loss=2256.0000, t=964]
Attacking:  12%|█▏        | 58/500 [01:32<12:36,  1.71s/it, loss=2368.0000, t=1e+3]
Attacking:  12%|█▏        | 59/500 [01:33<12:56,  1.76s/it, loss=2368.0000, t=1e+3]
Attacking:  12%|█▏        | 59/500 [01:34<12:56,  1.76s/it, loss=2256.0000, t=964] 
Attacking:  12%|█▏        | 60/500 [01:35<12:43,  1.74s/it, loss=2256.0000, t=964]
Attacking:  12%|█▏        | 60/500 [01:36<12:43,  1.74s/it, loss=2240.0000, t=912]
Attacking:  12%|█▏        | 61/500 [01:37<12:26,  1.70s/it, loss=2240.0000, t=912]
Attacking:  12%|█▏        | 61/500 [01:37<12:26,  1.70s/it, loss=2256.0000, t=952]
Attacking:  12%|█▏        | 62/500 [01:38<12:16,  1.68s/it, loss=2256.0000, t=952]
Attacking:  12%|█▏        | 62/500 [01:39<12:16,  1.68s/it, loss=2256.0000, t=940]
Attacking:  13%|█▎        | 63/500 [01:40<12:18,  1.69s/it, loss=2256.0000, t=940]
Attacking:  13%|█▎        | 63/500 [01:41<12:18,  1.69s/it, loss=2320.0000, t=992]
Attacking:  13%|█▎        | 64/500 [01:42<12:11,  1.68s/it, loss=2320.0000, t=992]
Attacking:  13%|█▎        | 64/500 [01:42<12:11,  1.68s/it, loss=2256.0000, t=952]
Attacking:  13%|█▎        | 65/500 [01:43<11:59,  1.65s/it, loss=2256.0000, t=952]
Attacking:  13%|█▎        | 65/500 [01:44<11:59,  1.65s/it, loss=2256.0000, t=952]
Attacking:  13%|█▎        | 66/500 [01:45<12:06,  1.67s/it, loss=2256.0000, t=952]
Attacking:  13%|█▎        | 66/500 [01:46<12:06,  1.67s/it, loss=2240.0000, t=912]
Attacking:  13%|█▎        | 67/500 [01:46<11:42,  1.62s/it, loss=2240.0000, t=912]
Attacking:  13%|█▎        | 67/500 [01:47<11:42,  1.62s/it, loss=2256.0000, t=972]
Attacking:  14%|█▎        | 68/500 [01:48<11:23,  1.58s/it, loss=2256.0000, t=972]
Attacking:  14%|█▎        | 68/500 [01:49<11:23,  1.58s/it, loss=2352.0000, t=1e+3]
Attacking:  14%|█▍        | 69/500 [01:50<11:34,  1.61s/it, loss=2352.0000, t=1e+3]
Attacking:  14%|█▍        | 69/500 [01:50<11:34,  1.61s/it, loss=2320.0000, t=992] 
Attacking:  14%|█▍        | 70/500 [01:51<11:42,  1.63s/it, loss=2320.0000, t=992]
Attacking:  14%|█▍        | 70/500 [01:52<11:42,  1.63s/it, loss=2256.0000, t=940]
Attacking:  14%|█▍        | 71/500 [01:53<12:24,  1.74s/it, loss=2256.0000, t=940]
Attacking:  14%|█▍        | 71/500 [01:54<12:24,  1.74s/it, loss=2240.0000, t=972]
Attacking:  14%|█▍        | 72/500 [01:55<12:02,  1.69s/it, loss=2240.0000, t=972]
Attacking:  14%|█▍        | 72/500 [01:56<12:02,  1.69s/it, loss=2240.0000, t=912]
Attacking:  15%|█▍        | 73/500 [01:56<11:45,  1.65s/it, loss=2240.0000, t=912]
Attacking:  15%|█▍        | 73/500 [01:57<11:45,  1.65s/it, loss=2240.0000, t=972]
Attacking:  15%|█▍        | 74/500 [01:58<11:38,  1.64s/it, loss=2240.0000, t=972]
Attacking:  15%|█▍        | 74/500 [01:59<11:38,  1.64s/it, loss=2256.0000, t=984]
Attacking:  15%|█▌        | 75/500 [02:00<11:52,  1.68s/it, loss=2256.0000, t=984]
Attacking:  15%|█▌        | 75/500 [02:01<11:52,  1.68s/it, loss=2224.0000, t=900]
Attacking:  15%|█▌        | 76/500 [02:01<11:52,  1.68s/it, loss=2224.0000, t=900]
Attacking:  15%|█▌        | 76/500 [02:02<11:52,  1.68s/it, loss=2240.0000, t=972]
Attacking:  15%|█▌        | 77/500 [02:03<11:54,  1.69s/it, loss=2240.0000, t=972]
Attacking:  15%|█▌        | 77/500 [02:04<11:54,  1.69s/it, loss=2240.0000, t=964]
Attacking:  16%|█▌        | 78/500 [02:05<11:52,  1.69s/it, loss=2240.0000, t=964]
Attacking:  16%|█▌        | 78/500 [02:06<11:52,  1.69s/it, loss=2304.0000, t=992]
Attacking:  16%|█▌        | 79/500 [02:06<11:43,  1.67s/it, loss=2304.0000, t=992]
Attacking:  16%|█▌        | 79/500 [02:07<11:43,  1.67s/it, loss=2240.0000, t=940]
Attacking:  16%|█▌        | 80/500 [02:08<11:34,  1.65s/it, loss=2240.0000, t=940]
Attacking:  16%|█▌        | 80/500 [02:09<11:34,  1.65s/it, loss=2240.0000, t=964]
Attacking:  16%|█▌        | 81/500 [02:10<11:57,  1.71s/it, loss=2240.0000, t=964]
Attacking:  16%|█▌        | 81/500 [02:11<11:57,  1.71s/it, loss=2304.0000, t=992]
Attacking:  16%|█▋        | 82/500 [02:12<11:48,  1.69s/it, loss=2304.0000, t=992]
Attacking:  16%|█▋        | 82/500 [02:12<11:48,  1.69s/it, loss=2256.0000, t=984]
Attacking:  17%|█▋        | 83/500 [02:13<11:22,  1.64s/it, loss=2256.0000, t=984]
Attacking:  17%|█▋        | 83/500 [02:14<11:22,  1.64s/it, loss=2304.0000, t=992]
Attacking:  17%|█▋        | 84/500 [02:15<11:11,  1.61s/it, loss=2304.0000, t=992]
Attacking:  17%|█▋        | 84/500 [02:16<11:11,  1.61s/it, loss=2224.0000, t=972]
Attacking:  17%|█▋        | 85/500 [02:16<11:21,  1.64s/it, loss=2224.0000, t=972]
Attacking:  17%|█▋        | 85/500 [02:17<11:21,  1.64s/it, loss=2224.0000, t=900]
Attacking:  17%|█▋        | 86/500 [02:18<11:34,  1.68s/it, loss=2224.0000, t=900]
Attacking:  17%|█▋        | 86/500 [02:19<11:34,  1.68s/it, loss=2320.0000, t=1e+3]
Attacking:  17%|█▋        | 87/500 [02:20<11:30,  1.67s/it, loss=2320.0000, t=1e+3]
Attacking:  17%|█▋        | 87/500 [02:21<11:30,  1.67s/it, loss=2224.0000, t=972] 
Attacking:  18%|█▊        | 88/500 [02:21<11:22,  1.66s/it, loss=2224.0000, t=972]
Attacking:  18%|█▊        | 88/500 [02:22<11:22,  1.66s/it, loss=2224.0000, t=900]
Attacking:  18%|█▊        | 89/500 [02:23<11:05,  1.62s/it, loss=2224.0000, t=900]
Attacking:  18%|█▊        | 89/500 [02:24<11:05,  1.62s/it, loss=2224.0000, t=940]
Attacking:  18%|█▊        | 90/500 [02:25<11:11,  1.64s/it, loss=2224.0000, t=940]
Attacking:  18%|█▊        | 90/500 [02:25<11:11,  1.64s/it, loss=2272.0000, t=992]
Attacking:  18%|█▊        | 91/500 [02:26<11:14,  1.65s/it, loss=2272.0000, t=992]
Attacking:  18%|█▊        | 91/500 [02:27<11:14,  1.65s/it, loss=2224.0000, t=928]
Attacking:  18%|█▊        | 92/500 [02:28<10:59,  1.62s/it, loss=2224.0000, t=928]
Attacking:  18%|█▊        | 92/500 [02:28<10:59,  1.62s/it, loss=2224.0000, t=964]
Attacking:  19%|█▊        | 93/500 [02:29<10:44,  1.58s/it, loss=2224.0000, t=964]
Attacking:  19%|█▊        | 93/500 [02:30<10:44,  1.58s/it, loss=2224.0000, t=928]
Attacking:  19%|█▉        | 94/500 [02:31<10:39,  1.57s/it, loss=2224.0000, t=928]
Attacking:  19%|█▉        | 94/500 [02:32<10:39,  1.57s/it, loss=2288.0000, t=992]
Attacking:  19%|█▉        | 95/500 [02:32<10:39,  1.58s/it, loss=2288.0000, t=992]
Attacking:  19%|█▉        | 95/500 [02:33<10:39,  1.58s/it, loss=2208.0000, t=900]
Attacking:  19%|█▉        | 96/500 [02:34<10:44,  1.59s/it, loss=2208.0000, t=900]
Attacking:  19%|█▉        | 96/500 [02:35<10:44,  1.59s/it, loss=2224.0000, t=940]
Attacking:  19%|█▉        | 97/500 [02:36<11:04,  1.65s/it, loss=2224.0000, t=940]
Attacking:  19%|█▉        | 97/500 [02:37<11:04,  1.65s/it, loss=2208.0000, t=912]
Attacking:  20%|█▉        | 98/500 [02:38<11:29,  1.72s/it, loss=2208.0000, t=912]
Attacking:  20%|█▉        | 98/500 [02:38<11:29,  1.72s/it, loss=2208.0000, t=900]
Attacking:  20%|█▉        | 99/500 [02:39<11:16,  1.69s/it, loss=2208.0000, t=900]
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Attacking:  20%|██        | 100/500 [02:41<11:10,  1.68s/it, loss=2208.0000, t=912]
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+Max Diff: 0.501961
+Mean Diff: 0.255450
+Saved adversarial image to attacked/images/lucia.jpg
+Saved loss curve to attacked/loss_curve/lucia_loss.png
+[GPU 4] Stage 3/3: Test
+Loading models for testing lucia...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for lucia...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 43.46it/s]
+Saved video to attacked/videos/lucia.mp4
+Saved frames to attacked/frames/lucia
+[GPU 4] Finished lucia.jpg
+======================================
+[GPU 4] Processing mallard-fly.jpg (Image 29/50)
+======================================
+[GPU 4] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 4] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  12%|█▏        | 62/500 [01:42<11:13,  1.54s/it, loss=2176.0000, t=900]
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Attacking:  14%|█▍        | 70/500 [01:54<11:10,  1.56s/it, loss=2272.0000, t=1e+3]
Attacking:  14%|█▍        | 71/500 [01:55<11:16,  1.58s/it, loss=2272.0000, t=1e+3]
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Attacking:  15%|█▍        | 73/500 [01:58<10:59,  1.54s/it, loss=2144.0000, t=912]
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Attacking:  15%|█▌        | 75/500 [02:02<11:24,  1.61s/it, loss=2192.0000, t=964]
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Attacking:  15%|█▌        | 77/500 [02:05<10:56,  1.55s/it, loss=2208.0000, t=984]
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Attacking:  16%|█▌        | 81/500 [02:12<11:40,  1.67s/it, loss=2144.0000, t=900]
Attacking:  16%|█▋        | 82/500 [02:13<11:49,  1.70s/it, loss=2144.0000, t=900]
Attacking:  16%|█▋        | 82/500 [02:13<11:49,  1.70s/it, loss=2176.0000, t=952]
Attacking:  17%|█▋        | 83/500 [02:14<11:29,  1.65s/it, loss=2176.0000, t=952]
Attacking:  17%|█▋        | 83/500 [02:15<11:29,  1.65s/it, loss=2144.0000, t=912]
Attacking:  17%|█▋        | 84/500 [02:16<11:08,  1.61s/it, loss=2144.0000, t=912]
Attacking:  17%|█▋        | 84/500 [02:16<11:08,  1.61s/it, loss=2160.0000, t=940]
Attacking:  17%|█▋        | 85/500 [02:17<10:56,  1.58s/it, loss=2160.0000, t=940]
Attacking:  17%|█▋        | 85/500 [02:18<10:56,  1.58s/it, loss=2176.0000, t=964]
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Attacking:  17%|█▋        | 87/500 [02:21<10:40,  1.55s/it, loss=2208.0000, t=992]
Attacking:  18%|█▊        | 88/500 [02:22<10:33,  1.54s/it, loss=2208.0000, t=992]
Attacking:  18%|█▊        | 88/500 [02:22<10:33,  1.54s/it, loss=2240.0000, t=1e+3]
Attacking:  18%|█▊        | 89/500 [02:23<10:33,  1.54s/it, loss=2240.0000, t=1e+3]
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Attacking:  18%|█▊        | 90/500 [02:25<10:21,  1.52s/it, loss=2192.0000, t=984]
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Attacking:  18%|█▊        | 91/500 [02:27<10:17,  1.51s/it, loss=2240.0000, t=1e+3]
Attacking:  18%|█▊        | 92/500 [02:28<10:06,  1.49s/it, loss=2240.0000, t=1e+3]
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Attacking:  20%|█▉        | 99/500 [02:39<09:59,  1.49s/it, loss=2176.0000, t=964]
Attacking:  20%|██        | 100/500 [02:40<09:56,  1.49s/it, loss=2176.0000, t=964]
Attacking:  20%|██        | 100/500 [02:40<09:56,  1.49s/it, loss=2176.0000, t=952]
Attacking:  20%|██        | 101/500 [02:41<09:45,  1.47s/it, loss=2176.0000, t=952]
Attacking:  20%|██        | 101/500 [02:42<09:45,  1.47s/it, loss=2144.0000, t=952]
Attacking:  20%|██        | 102/500 [02:42<09:47,  1.47s/it, loss=2144.0000, t=952]
Attacking:  20%|██        | 102/500 [02:43<09:47,  1.47s/it, loss=2208.0000, t=992]
Attacking:  21%|██        | 103/500 [02:44<09:47,  1.48s/it, loss=2208.0000, t=992]
Attacking:  21%|██        | 103/500 [02:45<09:47,  1.48s/it, loss=2128.0000, t=900]
Attacking:  21%|██        | 104/500 [02:46<10:04,  1.53s/it, loss=2128.0000, t=900]
Attacking:  21%|██        | 104/500 [02:46<10:04,  1.53s/it, loss=2160.0000, t=964]
Attacking:  21%|██        | 105/500 [02:47<10:10,  1.54s/it, loss=2160.0000, t=964]
Attacking:  21%|██        | 105/500 [02:48<10:10,  1.54s/it, loss=2128.0000, t=912]
Attacking:  21%|██        | 106/500 [02:49<10:01,  1.53s/it, loss=2128.0000, t=912]
Attacking:  21%|██        | 106/500 [02:49<10:01,  1.53s/it, loss=2160.0000, t=940]
Attacking:  21%|██▏       | 107/500 [02:50<09:57,  1.52s/it, loss=2160.0000, t=940]
Attacking:  21%|██▏       | 107/500 [02:51<09:57,  1.52s/it, loss=2128.0000, t=912]
Attacking:  22%|██▏       | 108/500 [02:52<09:54,  1.52s/it, loss=2128.0000, t=912]
Attacking:  22%|██▏       | 108/500 [02:52<09:54,  1.52s/it, loss=2128.0000, t=912]
Attacking:  22%|██▏       | 109/500 [02:53<09:58,  1.53s/it, loss=2128.0000, t=912]
Attacking:  22%|██▏       | 109/500 [02:54<09:58,  1.53s/it, loss=2144.0000, t=928]
Attacking:  22%|██▏       | 110/500 [02:55<09:50,  1.51s/it, loss=2144.0000, t=928]
Attacking:  22%|██▏       | 110/500 [02:55<09:50,  1.51s/it, loss=2176.0000, t=972]
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Attacking:  22%|██▏       | 112/500 [02:58<09:41,  1.50s/it, loss=2144.0000, t=940]
Attacking:  22%|██▏       | 112/500 [02:58<09:41,  1.50s/it, loss=2192.0000, t=984]
Attacking:  23%|██▎       | 113/500 [02:59<09:43,  1.51s/it, loss=2192.0000, t=984]
Attacking:  23%|██▎       | 113/500 [03:00<09:43,  1.51s/it, loss=2128.0000, t=928]
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Attacking:  23%|██▎       | 114/500 [03:01<09:37,  1.50s/it, loss=2128.0000, t=912]
Attacking:  23%|██▎       | 115/500 [03:02<09:34,  1.49s/it, loss=2128.0000, t=912]
Attacking:  23%|██▎       | 115/500 [03:03<09:34,  1.49s/it, loss=2208.0000, t=992]
Attacking:  23%|██▎       | 116/500 [03:04<09:41,  1.51s/it, loss=2208.0000, t=992]
Attacking:  23%|██▎       | 116/500 [03:04<09:41,  1.51s/it, loss=2240.0000, t=1e+3]
Attacking:  23%|██▎       | 117/500 [03:05<09:38,  1.51s/it, loss=2240.0000, t=1e+3]
Attacking:  23%|██▎       | 117/500 [03:06<09:38,  1.51s/it, loss=2128.0000, t=928] 
Attacking:  24%|██▎       | 118/500 [03:07<09:39,  1.52s/it, loss=2128.0000, t=928]
Attacking:  24%|██▎       | 118/500 [03:08<09:39,  1.52s/it, loss=2176.0000, t=984]
Attacking:  24%|██▍       | 119/500 [03:08<09:50,  1.55s/it, loss=2176.0000, t=984]
Attacking:  24%|██▍       | 119/500 [03:09<09:50,  1.55s/it, loss=2128.0000, t=940]
Attacking:  24%|██▍       | 120/500 [03:10<10:06,  1.60s/it, loss=2128.0000, t=940]
Attacking:  24%|██▍       | 120/500 [03:11<10:06,  1.60s/it, loss=2240.0000, t=1e+3]
Attacking:  24%|██▍       | 121/500 [03:12<09:50,  1.56s/it, loss=2240.0000, t=1e+3]
Attacking:  24%|██▍       | 121/500 [03:12<09:50,  1.56s/it, loss=2176.0000, t=984] 
Attacking:  24%|██▍       | 122/500 [03:13<09:37,  1.53s/it, loss=2176.0000, t=984]
Attacking:  24%|██▍       | 122/500 [03:14<09:37,  1.53s/it, loss=2192.0000, t=992]
Attacking:  25%|██▍       | 123/500 [03:15<09:41,  1.54s/it, loss=2192.0000, t=992]
Attacking:  25%|██▍       | 123/500 [03:15<09:41,  1.54s/it, loss=2224.0000, t=1e+3]
Attacking:  25%|██▍       | 124/500 [03:16<09:37,  1.54s/it, loss=2224.0000, t=1e+3]
Attacking:  25%|██▍       | 124/500 [03:17<09:37,  1.54s/it, loss=2128.0000, t=900] 
Attacking:  25%|██▌       | 125/500 [03:18<09:33,  1.53s/it, loss=2128.0000, t=900]
Attacking:  25%|██▌       | 125/500 [03:18<09:33,  1.53s/it, loss=2144.0000, t=952]
Attacking:  25%|██▌       | 126/500 [03:19<09:30,  1.53s/it, loss=2144.0000, t=952]
Attacking:  25%|██▌       | 126/500 [03:20<09:30,  1.53s/it, loss=2128.0000, t=928]
Attacking:  25%|██▌       | 127/500 [03:21<09:30,  1.53s/it, loss=2128.0000, t=928]
Attacking:  25%|██▌       | 127/500 [03:21<09:30,  1.53s/it, loss=2192.0000, t=992]
Attacking:  26%|██▌       | 128/500 [03:22<09:26,  1.52s/it, loss=2192.0000, t=992]
Attacking:  26%|██▌       | 128/500 [03:23<09:26,  1.52s/it, loss=2192.0000, t=992]
Attacking:  26%|██▌       | 129/500 [03:24<09:19,  1.51s/it, loss=2192.0000, t=992]
Attacking:  26%|██▌       | 129/500 [03:24<09:19,  1.51s/it, loss=2176.0000, t=984]
Attacking:  26%|██▌       | 130/500 [03:25<09:17,  1.51s/it, loss=2176.0000, t=984]
Attacking:  26%|██▌       | 130/500 [03:26<09:17,  1.51s/it, loss=2128.0000, t=900]
Attacking:  26%|██▌       | 131/500 [03:27<09:14,  1.50s/it, loss=2128.0000, t=900]
Attacking:  26%|██▌       | 131/500 [03:27<09:14,  1.50s/it, loss=2128.0000, t=940]
Attacking:  26%|██▋       | 132/500 [03:28<09:10,  1.50s/it, loss=2128.0000, t=940]
Attacking:  26%|██▋       | 132/500 [03:29<09:10,  1.50s/it, loss=2224.0000, t=1e+3]
Attacking:  27%|██▋       | 133/500 [03:30<09:08,  1.49s/it, loss=2224.0000, t=1e+3]
Attacking:  27%|██▋       | 133/500 [03:30<09:08,  1.49s/it, loss=2128.0000, t=952] 
Attacking:  27%|██▋       | 134/500 [03:31<09:17,  1.52s/it, loss=2128.0000, t=952]
Attacking:  27%|██▋       | 134/500 [03:32<09:17,  1.52s/it, loss=2176.0000, t=992]
Attacking:  27%|██▋       | 135/500 [03:33<09:13,  1.52s/it, loss=2176.0000, t=992]
Attacking:  27%|██▋       | 135/500 [03:33<09:13,  1.52s/it, loss=2160.0000, t=984]
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Attacking:  27%|██▋       | 136/500 [03:35<09:17,  1.53s/it, loss=2224.0000, t=1e+3]
Attacking:  27%|██▋       | 137/500 [03:36<09:05,  1.50s/it, loss=2224.0000, t=1e+3]
Attacking:  27%|██▋       | 137/500 [03:36<09:05,  1.50s/it, loss=2144.0000, t=964] 
Attacking:  28%|██▊       | 138/500 [03:37<09:00,  1.49s/it, loss=2144.0000, t=964]
Attacking:  28%|██▊       | 138/500 [03:38<09:00,  1.49s/it, loss=2224.0000, t=1e+3]
Attacking:  28%|██▊       | 139/500 [03:39<09:00,  1.50s/it, loss=2224.0000, t=1e+3]
Attacking:  28%|██▊       | 139/500 [03:39<09:00,  1.50s/it, loss=2208.0000, t=1e+3]
Attacking:  28%|██▊       | 140/500 [03:40<08:58,  1.49s/it, loss=2208.0000, t=1e+3]
Attacking:  28%|██▊       | 140/500 [03:41<08:58,  1.49s/it, loss=2128.0000, t=900] 
Attacking:  28%|██▊       | 141/500 [03:42<09:12,  1.54s/it, loss=2128.0000, t=900]
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+Max Diff: 0.501961
+Mean Diff: 0.257274
+Saved adversarial image to attacked/images/mallard-fly.jpg
+Saved loss curve to attacked/loss_curve/mallard-fly_loss.png
+[GPU 4] Stage 3/3: Test
+Loading models for testing mallard-fly...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for mallard-fly...
+
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+
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+Saved video to attacked/videos/mallard-fly.mp4
+Saved frames to attacked/frames/mallard-fly
+[GPU 4] Finished mallard-fly.jpg
+======================================
+[GPU 4] Processing man-talking.jpg (Image 30/50)
+======================================
+[GPU 4] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 4] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   2%|▏         | 9/500 [00:13<12:35,  1.54s/it, loss=2464.0000, t=900]
Attacking:   2%|▏         | 9/500 [00:14<12:35,  1.54s/it, loss=2448.0000, t=912]
Attacking:   2%|▏         | 10/500 [00:15<12:28,  1.53s/it, loss=2448.0000, t=912]
Attacking:   2%|▏         | 10/500 [00:16<12:28,  1.53s/it, loss=2432.0000, t=900]
Attacking:   2%|▏         | 11/500 [00:17<12:45,  1.57s/it, loss=2432.0000, t=900]
Attacking:   2%|▏         | 11/500 [00:17<12:45,  1.57s/it, loss=2560.0000, t=984]
Attacking:   2%|▏         | 12/500 [00:18<12:35,  1.55s/it, loss=2560.0000, t=984]
Attacking:   2%|▏         | 12/500 [00:19<12:35,  1.55s/it, loss=2464.0000, t=928]
Attacking:   3%|▎         | 13/500 [00:20<12:14,  1.51s/it, loss=2464.0000, t=928]
Attacking:   3%|▎         | 13/500 [00:20<12:14,  1.51s/it, loss=2624.0000, t=1e+3]
Attacking:   3%|▎         | 14/500 [00:21<12:05,  1.49s/it, loss=2624.0000, t=1e+3]
Attacking:   3%|▎         | 14/500 [00:22<12:05,  1.49s/it, loss=2592.0000, t=992] 
Attacking:   3%|▎         | 15/500 [00:23<12:24,  1.53s/it, loss=2592.0000, t=992]
Attacking:   3%|▎         | 15/500 [00:24<12:24,  1.53s/it, loss=2464.0000, t=952]
Attacking:   3%|▎         | 16/500 [00:24<13:03,  1.62s/it, loss=2464.0000, t=952]
Attacking:   3%|▎         | 16/500 [00:25<13:03,  1.62s/it, loss=2544.0000, t=984]
Attacking:   3%|▎         | 17/500 [00:26<12:55,  1.60s/it, loss=2544.0000, t=984]
Attacking:   3%|▎         | 17/500 [00:27<12:55,  1.60s/it, loss=2576.0000, t=992]
Attacking:   4%|▎         | 18/500 [00:28<13:02,  1.62s/it, loss=2576.0000, t=992]
Attacking:   4%|▎         | 18/500 [00:29<13:02,  1.62s/it, loss=2416.0000, t=900]
Attacking:   4%|▍         | 19/500 [00:29<13:07,  1.64s/it, loss=2416.0000, t=900]
Attacking:   4%|▍         | 19/500 [00:30<13:07,  1.64s/it, loss=2416.0000, t=912]
Attacking:   4%|▍         | 20/500 [00:31<12:50,  1.61s/it, loss=2416.0000, t=912]
Attacking:   4%|▍         | 20/500 [00:32<12:50,  1.61s/it, loss=2592.0000, t=1e+3]
Attacking:   4%|▍         | 21/500 [00:33<13:02,  1.63s/it, loss=2592.0000, t=1e+3]
Attacking:   4%|▍         | 21/500 [00:33<13:02,  1.63s/it, loss=2432.0000, t=900] 
Attacking:   4%|▍         | 22/500 [00:34<12:44,  1.60s/it, loss=2432.0000, t=900]
Attacking:   4%|▍         | 22/500 [00:35<12:44,  1.60s/it, loss=2464.0000, t=952]
Attacking:   5%|▍         | 23/500 [00:36<12:45,  1.61s/it, loss=2464.0000, t=952]
Attacking:   5%|▍         | 23/500 [00:37<12:45,  1.61s/it, loss=2560.0000, t=1e+3]
Attacking:   5%|▍         | 24/500 [00:37<13:02,  1.64s/it, loss=2560.0000, t=1e+3]
Attacking:   5%|▍         | 24/500 [00:38<13:02,  1.64s/it, loss=2560.0000, t=992] 
Attacking:   5%|▌         | 25/500 [00:39<12:46,  1.61s/it, loss=2560.0000, t=992]
Attacking:   5%|▌         | 25/500 [00:40<12:46,  1.61s/it, loss=2416.0000, t=928]
Attacking:   5%|▌         | 26/500 [00:41<12:50,  1.63s/it, loss=2416.0000, t=928]
Attacking:   5%|▌         | 26/500 [00:41<12:50,  1.63s/it, loss=2560.0000, t=1e+3]
Attacking:   5%|▌         | 27/500 [00:42<12:50,  1.63s/it, loss=2560.0000, t=1e+3]
Attacking:   5%|▌         | 27/500 [00:43<12:50,  1.63s/it, loss=2544.0000, t=1e+3]
Attacking:   6%|▌         | 28/500 [00:44<12:50,  1.63s/it, loss=2544.0000, t=1e+3]
Attacking:   6%|▌         | 28/500 [00:45<12:50,  1.63s/it, loss=2544.0000, t=1e+3]
Attacking:   6%|▌         | 29/500 [00:46<12:42,  1.62s/it, loss=2544.0000, t=1e+3]
Attacking:   6%|▌         | 29/500 [00:46<12:42,  1.62s/it, loss=2528.0000, t=1e+3]
Attacking:   6%|▌         | 30/500 [00:47<12:27,  1.59s/it, loss=2528.0000, t=1e+3]
Attacking:   6%|▌         | 30/500 [00:48<12:27,  1.59s/it, loss=2464.0000, t=952] 
Attacking:   6%|▌         | 31/500 [00:49<12:20,  1.58s/it, loss=2464.0000, t=952]
Attacking:   6%|▌         | 31/500 [00:49<12:20,  1.58s/it, loss=2464.0000, t=964]
Attacking:   6%|▋         | 32/500 [00:50<12:31,  1.61s/it, loss=2464.0000, t=964]
Attacking:   6%|▋         | 32/500 [00:51<12:31,  1.61s/it, loss=2400.0000, t=928]
Attacking:   7%|▋         | 33/500 [00:52<12:19,  1.58s/it, loss=2400.0000, t=928]
Attacking:   7%|▋         | 33/500 [00:52<12:19,  1.58s/it, loss=2416.0000, t=952]
Attacking:   7%|▋         | 34/500 [00:53<12:05,  1.56s/it, loss=2416.0000, t=952]
Attacking:   7%|▋         | 34/500 [00:54<12:05,  1.56s/it, loss=2384.0000, t=900]
Attacking:   7%|▋         | 35/500 [00:55<12:04,  1.56s/it, loss=2384.0000, t=900]
Attacking:   7%|▋         | 35/500 [00:56<12:04,  1.56s/it, loss=2432.0000, t=964]
Attacking:   7%|▋         | 36/500 [00:57<12:14,  1.58s/it, loss=2432.0000, t=964]
Attacking:   7%|▋         | 36/500 [00:57<12:14,  1.58s/it, loss=2448.0000, t=972]
Attacking:   7%|▋         | 37/500 [00:58<12:03,  1.56s/it, loss=2448.0000, t=972]
Attacking:   7%|▋         | 37/500 [00:59<12:03,  1.56s/it, loss=2416.0000, t=952]
Attacking:   8%|▊         | 38/500 [00:59<11:46,  1.53s/it, loss=2416.0000, t=952]
Attacking:   8%|▊         | 38/500 [01:00<11:46,  1.53s/it, loss=2400.0000, t=912]
Attacking:   8%|▊         | 39/500 [01:01<11:29,  1.50s/it, loss=2400.0000, t=912]
Attacking:   8%|▊         | 39/500 [01:01<11:29,  1.50s/it, loss=2544.0000, t=1e+3]
Attacking:   8%|▊         | 40/500 [01:02<11:16,  1.47s/it, loss=2544.0000, t=1e+3]
Attacking:   8%|▊         | 40/500 [01:03<11:16,  1.47s/it, loss=2416.0000, t=952] 
Attacking:   8%|▊         | 41/500 [01:04<11:28,  1.50s/it, loss=2416.0000, t=952]
Attacking:   8%|▊         | 41/500 [01:04<11:28,  1.50s/it, loss=2528.0000, t=1e+3]
Attacking:   8%|▊         | 42/500 [01:05<11:16,  1.48s/it, loss=2528.0000, t=1e+3]
Attacking:   8%|▊         | 42/500 [01:06<11:16,  1.48s/it, loss=2416.0000, t=952] 
Attacking:   9%|▊         | 43/500 [01:07<11:20,  1.49s/it, loss=2416.0000, t=952]
Attacking:   9%|▊         | 43/500 [01:07<11:20,  1.49s/it, loss=2400.0000, t=952]
Attacking:   9%|▉         | 44/500 [01:08<11:18,  1.49s/it, loss=2400.0000, t=952]
Attacking:   9%|▉         | 44/500 [01:09<11:18,  1.49s/it, loss=2368.0000, t=900]
Attacking:   9%|▉         | 45/500 [01:10<11:22,  1.50s/it, loss=2368.0000, t=900]
Attacking:   9%|▉         | 45/500 [01:10<11:22,  1.50s/it, loss=2368.0000, t=928]
Attacking:   9%|▉         | 46/500 [01:11<11:21,  1.50s/it, loss=2368.0000, t=928]
Attacking:   9%|▉         | 46/500 [01:12<11:21,  1.50s/it, loss=2400.0000, t=964]
Attacking:   9%|▉         | 47/500 [01:13<11:29,  1.52s/it, loss=2400.0000, t=964]
Attacking:   9%|▉         | 47/500 [01:14<11:29,  1.52s/it, loss=2368.0000, t=940]
Attacking:  10%|▉         | 48/500 [01:14<11:25,  1.52s/it, loss=2368.0000, t=940]
Attacking:  10%|▉         | 48/500 [01:15<11:25,  1.52s/it, loss=2384.0000, t=940]
Attacking:  10%|▉         | 49/500 [01:16<11:33,  1.54s/it, loss=2384.0000, t=940]
Attacking:  10%|▉         | 49/500 [01:17<11:33,  1.54s/it, loss=2400.0000, t=964]
Attacking:  10%|█         | 50/500 [01:18<11:30,  1.53s/it, loss=2400.0000, t=964]
Attacking:  10%|█         | 50/500 [01:18<11:30,  1.53s/it, loss=2496.0000, t=1e+3]
Attacking:  10%|█         | 51/500 [01:19<11:27,  1.53s/it, loss=2496.0000, t=1e+3]
Attacking:  10%|█         | 51/500 [01:20<11:27,  1.53s/it, loss=2400.0000, t=952] 
Attacking:  10%|█         | 52/500 [01:20<11:14,  1.51s/it, loss=2400.0000, t=952]
Attacking:  10%|█         | 52/500 [01:21<11:14,  1.51s/it, loss=2368.0000, t=940]
Attacking:  11%|█         | 53/500 [01:22<11:09,  1.50s/it, loss=2368.0000, t=940]
Attacking:  11%|█         | 53/500 [01:23<11:09,  1.50s/it, loss=2496.0000, t=1e+3]
Attacking:  11%|█         | 54/500 [01:23<10:59,  1.48s/it, loss=2496.0000, t=1e+3]
Attacking:  11%|█         | 54/500 [01:24<10:59,  1.48s/it, loss=2496.0000, t=992] 
Attacking:  11%|█         | 55/500 [01:25<11:01,  1.49s/it, loss=2496.0000, t=992]
Attacking:  11%|█         | 55/500 [01:26<11:01,  1.49s/it, loss=2352.0000, t=940]
Attacking:  11%|█         | 56/500 [01:26<11:03,  1.50s/it, loss=2352.0000, t=940]
Attacking:  11%|█         | 56/500 [01:27<11:03,  1.50s/it, loss=2352.0000, t=912]
Attacking:  11%|█▏        | 57/500 [01:28<11:07,  1.51s/it, loss=2352.0000, t=912]
Attacking:  11%|█▏        | 57/500 [01:29<11:07,  1.51s/it, loss=2448.0000, t=984]
Attacking:  12%|█▏        | 58/500 [01:29<11:05,  1.51s/it, loss=2448.0000, t=984]
Attacking:  12%|█▏        | 58/500 [01:30<11:05,  1.51s/it, loss=2448.0000, t=984]
Attacking:  12%|█▏        | 59/500 [01:31<11:30,  1.57s/it, loss=2448.0000, t=984]
Attacking:  12%|█▏        | 59/500 [01:32<11:30,  1.57s/it, loss=2400.0000, t=972]
Attacking:  12%|█▏        | 60/500 [01:33<11:17,  1.54s/it, loss=2400.0000, t=972]
Attacking:  12%|█▏        | 60/500 [01:33<11:17,  1.54s/it, loss=2336.0000, t=928]
Attacking:  12%|█▏        | 61/500 [01:34<11:19,  1.55s/it, loss=2336.0000, t=928]
Attacking:  12%|█▏        | 61/500 [01:35<11:19,  1.55s/it, loss=2336.0000, t=900]
Attacking:  12%|█▏        | 62/500 [01:36<11:32,  1.58s/it, loss=2336.0000, t=900]
Attacking:  12%|█▏        | 62/500 [01:37<11:32,  1.58s/it, loss=2496.0000, t=1e+3]
Attacking:  13%|█▎        | 63/500 [01:38<11:43,  1.61s/it, loss=2496.0000, t=1e+3]
Attacking:  13%|█▎        | 63/500 [01:38<11:43,  1.61s/it, loss=2432.0000, t=984] 
Attacking:  13%|█▎        | 64/500 [01:39<11:32,  1.59s/it, loss=2432.0000, t=984]
Attacking:  13%|█▎        | 64/500 [01:40<11:32,  1.59s/it, loss=2352.0000, t=940]
Attacking:  13%|█▎        | 65/500 [01:41<11:20,  1.56s/it, loss=2352.0000, t=940]
Attacking:  13%|█▎        | 65/500 [01:41<11:20,  1.56s/it, loss=2480.0000, t=1e+3]
Attacking:  13%|█▎        | 66/500 [01:42<11:21,  1.57s/it, loss=2480.0000, t=1e+3]
Attacking:  13%|█▎        | 66/500 [01:43<11:21,  1.57s/it, loss=2368.0000, t=952] 
Attacking:  13%|█▎        | 67/500 [01:44<11:18,  1.57s/it, loss=2368.0000, t=952]
Attacking:  13%|█▎        | 67/500 [01:45<11:18,  1.57s/it, loss=2320.0000, t=928]
Attacking:  14%|█▎        | 68/500 [01:45<11:33,  1.61s/it, loss=2320.0000, t=928]
Attacking:  14%|█▎        | 68/500 [01:46<11:33,  1.61s/it, loss=2352.0000, t=952]
Attacking:  14%|█▍        | 69/500 [01:47<11:24,  1.59s/it, loss=2352.0000, t=952]
Attacking:  14%|█▍        | 69/500 [01:48<11:24,  1.59s/it, loss=2480.0000, t=1e+3]
Attacking:  14%|█▍        | 70/500 [01:48<11:01,  1.54s/it, loss=2480.0000, t=1e+3]
Attacking:  14%|█▍        | 70/500 [01:49<11:01,  1.54s/it, loss=2464.0000, t=992] 
Attacking:  14%|█▍        | 71/500 [01:50<11:05,  1.55s/it, loss=2464.0000, t=992]
Attacking:  14%|█▍        | 71/500 [01:51<11:05,  1.55s/it, loss=2368.0000, t=972]
Attacking:  14%|█▍        | 72/500 [01:51<11:00,  1.54s/it, loss=2368.0000, t=972]
Attacking:  14%|█▍        | 72/500 [01:52<11:00,  1.54s/it, loss=2368.0000, t=964]
Attacking:  15%|█▍        | 73/500 [01:53<10:55,  1.54s/it, loss=2368.0000, t=964]
Attacking:  15%|█▍        | 73/500 [01:54<10:55,  1.54s/it, loss=2368.0000, t=964]
Attacking:  15%|█▍        | 74/500 [01:55<10:53,  1.53s/it, loss=2368.0000, t=964]
Attacking:  15%|█▍        | 74/500 [01:55<10:53,  1.53s/it, loss=2352.0000, t=964]
Attacking:  15%|█▌        | 75/500 [01:56<10:56,  1.54s/it, loss=2352.0000, t=964]
Attacking:  15%|█▌        | 75/500 [01:57<10:56,  1.54s/it, loss=2416.0000, t=984]
Attacking:  15%|█▌        | 76/500 [01:58<10:39,  1.51s/it, loss=2416.0000, t=984]
Attacking:  15%|█▌        | 76/500 [01:58<10:39,  1.51s/it, loss=2448.0000, t=992]
Attacking:  15%|█▌        | 77/500 [01:59<10:31,  1.49s/it, loss=2448.0000, t=992]
Attacking:  15%|█▌        | 77/500 [02:00<10:31,  1.49s/it, loss=2352.0000, t=964]
Attacking:  16%|█▌        | 78/500 [02:00<10:30,  1.49s/it, loss=2352.0000, t=964]
Attacking:  16%|█▌        | 78/500 [02:01<10:30,  1.49s/it, loss=2336.0000, t=940]
Attacking:  16%|█▌        | 79/500 [02:02<10:29,  1.50s/it, loss=2336.0000, t=940]
Attacking:  16%|█▌        | 79/500 [02:03<10:29,  1.50s/it, loss=2464.0000, t=1e+3]
Attacking:  16%|█▌        | 80/500 [02:03<10:24,  1.49s/it, loss=2464.0000, t=1e+3]
Attacking:  16%|█▌        | 80/500 [02:04<10:24,  1.49s/it, loss=2400.0000, t=984] 
Attacking:  16%|█▌        | 81/500 [02:05<10:28,  1.50s/it, loss=2400.0000, t=984]
Attacking:  16%|█▌        | 81/500 [02:06<10:28,  1.50s/it, loss=2368.0000, t=972]
Attacking:  16%|█▋        | 82/500 [02:07<10:30,  1.51s/it, loss=2368.0000, t=972]
Attacking:  16%|█▋        | 82/500 [02:07<10:30,  1.51s/it, loss=2304.0000, t=900]
Attacking:  17%|█▋        | 83/500 [02:08<10:21,  1.49s/it, loss=2304.0000, t=900]
Attacking:  17%|█▋        | 83/500 [02:09<10:21,  1.49s/it, loss=2288.0000, t=912]
Attacking:  17%|█▋        | 84/500 [02:09<10:11,  1.47s/it, loss=2288.0000, t=912]
Attacking:  17%|█▋        | 84/500 [02:10<10:11,  1.47s/it, loss=2448.0000, t=992]
Attacking:  17%|█▋        | 85/500 [02:11<10:12,  1.48s/it, loss=2448.0000, t=992]
Attacking:  17%|█▋        | 85/500 [02:12<10:12,  1.48s/it, loss=2432.0000, t=992]
Attacking:  17%|█▋        | 86/500 [02:13<10:30,  1.52s/it, loss=2432.0000, t=992]
Attacking:  17%|█▋        | 86/500 [02:13<10:30,  1.52s/it, loss=2400.0000, t=984]
Attacking:  17%|█▋        | 87/500 [02:14<10:46,  1.57s/it, loss=2400.0000, t=984]
Attacking:  17%|█▋        | 87/500 [02:15<10:46,  1.57s/it, loss=2448.0000, t=1e+3]
Attacking:  18%|█▊        | 88/500 [02:16<10:52,  1.58s/it, loss=2448.0000, t=1e+3]
Attacking:  18%|█▊        | 88/500 [02:16<10:52,  1.58s/it, loss=2336.0000, t=952] 
Attacking:  18%|█▊        | 89/500 [02:17<10:39,  1.56s/it, loss=2336.0000, t=952]
Attacking:  18%|█▊        | 89/500 [02:18<10:39,  1.56s/it, loss=2400.0000, t=984]
Attacking:  18%|█▊        | 90/500 [02:19<10:48,  1.58s/it, loss=2400.0000, t=984]
Attacking:  18%|█▊        | 90/500 [02:20<10:48,  1.58s/it, loss=2432.0000, t=992]
Attacking:  18%|█▊        | 91/500 [02:20<10:43,  1.57s/it, loss=2432.0000, t=992]
Attacking:  18%|█▊        | 91/500 [02:21<10:43,  1.57s/it, loss=2352.0000, t=972]
Attacking:  18%|█▊        | 92/500 [02:22<10:34,  1.55s/it, loss=2352.0000, t=972]
Attacking:  18%|█▊        | 92/500 [02:23<10:34,  1.55s/it, loss=2304.0000, t=928]
Attacking:  19%|█▊        | 93/500 [02:23<10:19,  1.52s/it, loss=2304.0000, t=928]
Attacking:  19%|█▊        | 93/500 [02:24<10:19,  1.52s/it, loss=2320.0000, t=952]
Attacking:  19%|█▉        | 94/500 [02:25<10:23,  1.54s/it, loss=2320.0000, t=952]
Attacking:  19%|█▉        | 94/500 [02:26<10:23,  1.54s/it, loss=2352.0000, t=972]
Attacking:  19%|█▉        | 95/500 [02:27<10:22,  1.54s/it, loss=2352.0000, t=972]
Attacking:  19%|█▉        | 95/500 [02:27<10:22,  1.54s/it, loss=2288.0000, t=928]
Attacking:  19%|█▉        | 96/500 [02:28<10:33,  1.57s/it, loss=2288.0000, t=928]
Attacking:  19%|█▉        | 96/500 [02:29<10:33,  1.57s/it, loss=2304.0000, t=928]
Attacking:  19%|█▉        | 97/500 [02:30<10:33,  1.57s/it, loss=2304.0000, t=928]
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+Max Diff: 0.501961
+Mean Diff: 0.224128
+Saved adversarial image to attacked/images/man-talking.jpg
+Saved loss curve to attacked/loss_curve/man-talking_loss.png
+[GPU 4] Stage 3/3: Test
+Loading models for testing man-talking...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for man-talking...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 39.10it/s]
+Saved video to attacked/videos/man-talking.mp4
+Saved frames to attacked/frames/man-talking
+[GPU 4] Finished man-talking.jpg
+======================================
+[GPU 4] Processing marllard-water.jpg (Image 31/50)
+======================================
+[GPU 4] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 4] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  11%|█         | 56/500 [01:28<11:13,  1.52s/it, loss=1968.0000, t=900]
Attacking:  11%|█         | 56/500 [01:28<11:13,  1.52s/it, loss=2016.0000, t=964]
Attacking:  11%|█▏        | 57/500 [01:29<11:23,  1.54s/it, loss=2016.0000, t=964]
Attacking:  11%|█▏        | 57/500 [01:30<11:23,  1.54s/it, loss=2064.0000, t=984]
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Attacking:  12%|█▏        | 59/500 [01:33<12:04,  1.64s/it, loss=1960.0000, t=900]
Attacking:  12%|█▏        | 59/500 [01:34<12:04,  1.64s/it, loss=1984.0000, t=952]
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Attacking:  12%|█▏        | 60/500 [01:35<11:59,  1.64s/it, loss=1992.0000, t=952]
Attacking:  12%|█▏        | 61/500 [01:36<11:39,  1.59s/it, loss=1992.0000, t=952]
Attacking:  12%|█▏        | 61/500 [01:37<11:39,  1.59s/it, loss=1960.0000, t=912]
Attacking:  12%|█▏        | 62/500 [01:38<11:42,  1.60s/it, loss=1960.0000, t=912]
Attacking:  12%|█▏        | 62/500 [01:38<11:42,  1.60s/it, loss=1952.0000, t=900]
Attacking:  13%|█▎        | 63/500 [01:39<11:52,  1.63s/it, loss=1952.0000, t=900]
Attacking:  13%|█▎        | 63/500 [01:40<11:52,  1.63s/it, loss=1952.0000, t=928]
Attacking:  13%|█▎        | 64/500 [01:41<11:47,  1.62s/it, loss=1952.0000, t=928]
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Attacking:  13%|█▎        | 65/500 [01:42<11:43,  1.62s/it, loss=1952.0000, t=912]
Attacking:  13%|█▎        | 65/500 [01:43<11:43,  1.62s/it, loss=2008.0000, t=972]
Attacking:  13%|█▎        | 66/500 [01:44<11:29,  1.59s/it, loss=2008.0000, t=972]
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Attacking:  13%|█▎        | 67/500 [01:46<11:33,  1.60s/it, loss=1976.0000, t=952]
Attacking:  13%|█▎        | 67/500 [01:46<11:33,  1.60s/it, loss=1944.0000, t=900]
Attacking:  14%|█▎        | 68/500 [01:47<11:27,  1.59s/it, loss=1944.0000, t=900]
Attacking:  14%|█▎        | 68/500 [01:48<11:27,  1.59s/it, loss=1944.0000, t=900]
Attacking:  14%|█▍        | 69/500 [01:49<11:26,  1.59s/it, loss=1944.0000, t=900]
Attacking:  14%|█▍        | 69/500 [01:49<11:26,  1.59s/it, loss=1952.0000, t=940]
Attacking:  14%|█▍        | 70/500 [01:50<11:13,  1.57s/it, loss=1952.0000, t=940]
Attacking:  14%|█▍        | 70/500 [01:51<11:13,  1.57s/it, loss=2032.0000, t=992]
Attacking:  14%|█▍        | 71/500 [01:52<11:19,  1.58s/it, loss=2032.0000, t=992]
Attacking:  14%|█▍        | 71/500 [01:53<11:19,  1.58s/it, loss=2016.0000, t=984]
Attacking:  14%|█▍        | 72/500 [01:53<11:20,  1.59s/it, loss=2016.0000, t=984]
Attacking:  14%|█▍        | 72/500 [01:54<11:20,  1.59s/it, loss=2032.0000, t=992]
Attacking:  15%|█▍        | 73/500 [01:55<11:06,  1.56s/it, loss=2032.0000, t=992]
Attacking:  15%|█▍        | 73/500 [01:56<11:06,  1.56s/it, loss=1944.0000, t=900]
Attacking:  15%|█▍        | 74/500 [01:56<10:58,  1.55s/it, loss=1944.0000, t=900]
Attacking:  15%|█▍        | 74/500 [01:57<10:58,  1.55s/it, loss=1936.0000, t=900]
Attacking:  15%|█▌        | 75/500 [01:58<10:58,  1.55s/it, loss=1936.0000, t=900]
Attacking:  15%|█▌        | 75/500 [01:59<10:58,  1.55s/it, loss=2048.0000, t=992]
Attacking:  15%|█▌        | 76/500 [02:00<10:49,  1.53s/it, loss=2048.0000, t=992]
Attacking:  15%|█▌        | 76/500 [02:00<10:49,  1.53s/it, loss=2008.0000, t=984]
Attacking:  15%|█▌        | 77/500 [02:01<10:48,  1.53s/it, loss=2008.0000, t=984]
Attacking:  15%|█▌        | 77/500 [02:02<10:48,  1.53s/it, loss=1928.0000, t=900]
Attacking:  16%|█▌        | 78/500 [02:03<10:52,  1.55s/it, loss=1928.0000, t=900]
Attacking:  16%|█▌        | 78/500 [02:03<10:52,  1.55s/it, loss=1968.0000, t=964]
Attacking:  16%|█▌        | 79/500 [02:04<10:40,  1.52s/it, loss=1968.0000, t=964]
Attacking:  16%|█▌        | 79/500 [02:05<10:40,  1.52s/it, loss=1928.0000, t=912]
Attacking:  16%|█▌        | 80/500 [02:06<10:41,  1.53s/it, loss=1928.0000, t=912]
Attacking:  16%|█▌        | 80/500 [02:06<10:41,  1.53s/it, loss=1936.0000, t=928]
Attacking:  16%|█▌        | 81/500 [02:07<10:40,  1.53s/it, loss=1936.0000, t=928]
Attacking:  16%|█▌        | 81/500 [02:08<10:40,  1.53s/it, loss=1952.0000, t=940]
Attacking:  16%|█▋        | 82/500 [02:09<10:52,  1.56s/it, loss=1952.0000, t=940]
Attacking:  16%|█▋        | 82/500 [02:09<10:52,  1.56s/it, loss=1968.0000, t=964]
Attacking:  17%|█▋        | 83/500 [02:10<10:49,  1.56s/it, loss=1968.0000, t=964]
Attacking:  17%|█▋        | 83/500 [02:11<10:49,  1.56s/it, loss=1968.0000, t=952]
Attacking:  17%|█▋        | 84/500 [02:12<10:40,  1.54s/it, loss=1968.0000, t=952]
Attacking:  17%|█▋        | 84/500 [02:13<10:40,  1.54s/it, loss=2016.0000, t=992]
Attacking:  17%|█▋        | 85/500 [02:13<10:44,  1.55s/it, loss=2016.0000, t=992]
Attacking:  17%|█▋        | 85/500 [02:14<10:44,  1.55s/it, loss=1944.0000, t=940]
Attacking:  17%|█▋        | 86/500 [02:15<10:33,  1.53s/it, loss=1944.0000, t=940]
Attacking:  17%|█▋        | 86/500 [02:16<10:33,  1.53s/it, loss=2008.0000, t=984]
Attacking:  17%|█▋        | 87/500 [02:16<10:36,  1.54s/it, loss=2008.0000, t=984]
Attacking:  17%|█▋        | 87/500 [02:17<10:36,  1.54s/it, loss=1952.0000, t=952]
Attacking:  18%|█▊        | 88/500 [02:18<10:27,  1.52s/it, loss=1952.0000, t=952]
Attacking:  18%|█▊        | 88/500 [02:19<10:27,  1.52s/it, loss=2000.0000, t=984]
Attacking:  18%|█▊        | 89/500 [02:20<10:33,  1.54s/it, loss=2000.0000, t=984]
Attacking:  18%|█▊        | 89/500 [02:20<10:33,  1.54s/it, loss=1992.0000, t=984]
Attacking:  18%|█▊        | 90/500 [02:21<10:19,  1.51s/it, loss=1992.0000, t=984]
Attacking:  18%|█▊        | 90/500 [02:22<10:19,  1.51s/it, loss=1920.0000, t=912]
Attacking:  18%|█▊        | 91/500 [02:22<10:10,  1.49s/it, loss=1920.0000, t=912]
Attacking:  18%|█▊        | 91/500 [02:23<10:10,  1.49s/it, loss=1920.0000, t=928]
Attacking:  18%|█▊        | 92/500 [02:24<10:12,  1.50s/it, loss=1920.0000, t=928]
Attacking:  18%|█▊        | 92/500 [02:25<10:12,  1.50s/it, loss=1936.0000, t=940]
Attacking:  19%|█▊        | 93/500 [02:26<10:22,  1.53s/it, loss=1936.0000, t=940]
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Attacking:  19%|█▉        | 94/500 [02:27<10:12,  1.51s/it, loss=1920.0000, t=912]
Attacking:  19%|█▉        | 94/500 [02:28<10:12,  1.51s/it, loss=1936.0000, t=952]
Attacking:  19%|█▉        | 95/500 [02:29<10:12,  1.51s/it, loss=1936.0000, t=952]
Attacking:  19%|█▉        | 95/500 [02:29<10:12,  1.51s/it, loss=1976.0000, t=972]
Attacking:  19%|█▉        | 96/500 [02:30<10:06,  1.50s/it, loss=1976.0000, t=972]
Attacking:  19%|█▉        | 96/500 [02:31<10:06,  1.50s/it, loss=1920.0000, t=928]
Attacking:  19%|█▉        | 97/500 [02:31<10:00,  1.49s/it, loss=1920.0000, t=928]
Attacking:  19%|█▉        | 97/500 [02:32<10:00,  1.49s/it, loss=2008.0000, t=992]
Attacking:  20%|█▉        | 98/500 [02:33<10:02,  1.50s/it, loss=2008.0000, t=992]
Attacking:  20%|█▉        | 98/500 [02:34<10:02,  1.50s/it, loss=1920.0000, t=912]
Attacking:  20%|█▉        | 99/500 [02:35<10:04,  1.51s/it, loss=1920.0000, t=912]
Attacking:  20%|█▉        | 99/500 [02:35<10:04,  1.51s/it, loss=1952.0000, t=964]
Attacking:  20%|██        | 100/500 [02:36<10:02,  1.51s/it, loss=1952.0000, t=964]
Attacking:  20%|██        | 100/500 [02:37<10:02,  1.51s/it, loss=1920.0000, t=928]
Attacking:  20%|██        | 101/500 [02:38<10:04,  1.52s/it, loss=1920.0000, t=928]
Attacking:  20%|██        | 101/500 [02:38<10:04,  1.52s/it, loss=1912.0000, t=928]
Attacking:  20%|██        | 102/500 [02:39<09:58,  1.50s/it, loss=1912.0000, t=928]
Attacking:  20%|██        | 102/500 [02:40<09:58,  1.50s/it, loss=1920.0000, t=912]
Attacking:  21%|██        | 103/500 [02:41<10:11,  1.54s/it, loss=1920.0000, t=912]
Attacking:  21%|██        | 103/500 [02:41<10:11,  1.54s/it, loss=1904.0000, t=912]
Attacking:  21%|██        | 104/500 [02:42<10:10,  1.54s/it, loss=1904.0000, t=912]
Attacking:  21%|██        | 104/500 [02:43<10:10,  1.54s/it, loss=1912.0000, t=900]
Attacking:  21%|██        | 105/500 [02:44<10:00,  1.52s/it, loss=1912.0000, t=900]
Attacking:  21%|██        | 105/500 [02:44<10:00,  1.52s/it, loss=1944.0000, t=964]
Attacking:  21%|██        | 106/500 [02:45<09:52,  1.50s/it, loss=1944.0000, t=964]
Attacking:  21%|██        | 106/500 [02:46<09:52,  1.50s/it, loss=1912.0000, t=912]
Attacking:  21%|██▏       | 107/500 [02:47<09:46,  1.49s/it, loss=1912.0000, t=912]
Attacking:  21%|██▏       | 107/500 [02:47<09:46,  1.49s/it, loss=1984.0000, t=984]
Attacking:  22%|██▏       | 108/500 [02:48<09:46,  1.50s/it, loss=1984.0000, t=984]
Attacking:  22%|██▏       | 108/500 [02:49<09:46,  1.50s/it, loss=1992.0000, t=1e+3]
Attacking:  22%|██▏       | 109/500 [02:50<09:43,  1.49s/it, loss=1992.0000, t=1e+3]
Attacking:  22%|██▏       | 109/500 [02:50<09:43,  1.49s/it, loss=1936.0000, t=952] 
Attacking:  22%|██▏       | 110/500 [02:51<09:47,  1.51s/it, loss=1936.0000, t=952]
Attacking:  22%|██▏       | 110/500 [02:52<09:47,  1.51s/it, loss=1928.0000, t=952]
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Attacking:  22%|██▏       | 111/500 [02:53<09:47,  1.51s/it, loss=1984.0000, t=984]
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Attacking:  22%|██▏       | 112/500 [02:55<09:46,  1.51s/it, loss=2000.0000, t=992]
Attacking:  23%|██▎       | 113/500 [02:56<10:02,  1.56s/it, loss=2000.0000, t=992]
Attacking:  23%|██▎       | 113/500 [02:57<10:02,  1.56s/it, loss=2000.0000, t=992]
Attacking:  23%|██▎       | 114/500 [02:57<09:57,  1.55s/it, loss=2000.0000, t=992]
Attacking:  23%|██▎       | 114/500 [02:58<09:57,  1.55s/it, loss=1944.0000, t=964]
Attacking:  23%|██▎       | 115/500 [02:59<09:47,  1.53s/it, loss=1944.0000, t=964]
Attacking:  23%|██▎       | 115/500 [03:00<09:47,  1.53s/it, loss=1928.0000, t=952]
Attacking:  23%|██▎       | 116/500 [03:00<09:57,  1.56s/it, loss=1928.0000, t=952]
Attacking:  23%|██▎       | 116/500 [03:01<09:57,  1.56s/it, loss=1920.0000, t=952]
Attacking:  23%|██▎       | 117/500 [03:02<09:59,  1.56s/it, loss=1920.0000, t=952]
Attacking:  23%|██▎       | 117/500 [03:03<09:59,  1.56s/it, loss=1904.0000, t=912]
Attacking:  24%|██▎       | 118/500 [03:04<09:56,  1.56s/it, loss=1904.0000, t=912]
Attacking:  24%|██▎       | 118/500 [03:04<09:56,  1.56s/it, loss=1912.0000, t=928]
Attacking:  24%|██▍       | 119/500 [03:05<09:57,  1.57s/it, loss=1912.0000, t=928]
Attacking:  24%|██▍       | 119/500 [03:06<09:57,  1.57s/it, loss=1904.0000, t=940]
Attacking:  24%|██▍       | 120/500 [03:07<10:15,  1.62s/it, loss=1904.0000, t=940]
Attacking:  24%|██▍       | 120/500 [03:08<10:15,  1.62s/it, loss=1904.0000, t=928]
Attacking:  24%|██▍       | 121/500 [03:08<10:03,  1.59s/it, loss=1904.0000, t=928]
Attacking:  24%|██▍       | 121/500 [03:09<10:03,  1.59s/it, loss=1936.0000, t=964]
Attacking:  24%|██▍       | 122/500 [03:10<09:51,  1.56s/it, loss=1936.0000, t=964]
Attacking:  24%|██▍       | 122/500 [03:11<09:51,  1.56s/it, loss=1968.0000, t=984]
Attacking:  25%|██▍       | 123/500 [03:11<09:35,  1.53s/it, loss=1968.0000, t=984]
Attacking:  25%|██▍       | 123/500 [03:12<09:35,  1.53s/it, loss=1976.0000, t=1e+3]
Attacking:  25%|██▍       | 124/500 [03:13<09:31,  1.52s/it, loss=1976.0000, t=1e+3]
Attacking:  25%|██▍       | 124/500 [03:14<09:31,  1.52s/it, loss=1896.0000, t=912] 
Attacking:  25%|██▌       | 125/500 [03:14<09:27,  1.51s/it, loss=1896.0000, t=912]
Attacking:  25%|██▌       | 125/500 [03:15<09:27,  1.51s/it, loss=1920.0000, t=952]
Attacking:  25%|██▌       | 126/500 [03:16<09:39,  1.55s/it, loss=1920.0000, t=952]
Attacking:  25%|██▌       | 126/500 [03:17<09:39,  1.55s/it, loss=1984.0000, t=992]
Attacking:  25%|██▌       | 127/500 [03:18<09:34,  1.54s/it, loss=1984.0000, t=992]
Attacking:  25%|██▌       | 127/500 [03:18<09:34,  1.54s/it, loss=1968.0000, t=984]
Attacking:  26%|██▌       | 128/500 [03:19<09:34,  1.54s/it, loss=1968.0000, t=984]
Attacking:  26%|██▌       | 128/500 [03:20<09:34,  1.54s/it, loss=1920.0000, t=952]
Attacking:  26%|██▌       | 129/500 [03:21<09:24,  1.52s/it, loss=1920.0000, t=952]
Attacking:  26%|██▌       | 129/500 [03:21<09:24,  1.52s/it, loss=1968.0000, t=984]
Attacking:  26%|██▌       | 130/500 [03:22<09:27,  1.53s/it, loss=1968.0000, t=984]
Attacking:  26%|██▌       | 130/500 [03:23<09:27,  1.53s/it, loss=1944.0000, t=972]
Attacking:  26%|██▌       | 131/500 [03:24<09:26,  1.53s/it, loss=1944.0000, t=972]
Attacking:  26%|██▌       | 131/500 [03:24<09:26,  1.53s/it, loss=1944.0000, t=972]
Attacking:  26%|██▋       | 132/500 [03:25<09:17,  1.52s/it, loss=1944.0000, t=972]
Attacking:  26%|██▋       | 132/500 [03:26<09:17,  1.52s/it, loss=1896.0000, t=900]
Attacking:  27%|██▋       | 133/500 [03:27<09:14,  1.51s/it, loss=1896.0000, t=900]
Attacking:  27%|██▋       | 133/500 [03:27<09:14,  1.51s/it, loss=1904.0000, t=928]
Attacking:  27%|██▋       | 134/500 [03:28<09:14,  1.52s/it, loss=1904.0000, t=928]
Attacking:  27%|██▋       | 134/500 [03:29<09:14,  1.52s/it, loss=1896.0000, t=912]
Attacking:  27%|██▋       | 135/500 [03:30<09:11,  1.51s/it, loss=1896.0000, t=912]
Attacking:  27%|██▋       | 135/500 [03:30<09:11,  1.51s/it, loss=1888.0000, t=912]
Attacking:  27%|██▋       | 136/500 [03:31<09:10,  1.51s/it, loss=1888.0000, t=912]
Attacking:  27%|██▋       | 136/500 [03:32<09:10,  1.51s/it, loss=1904.0000, t=928]
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Attacking:  28%|██▊       | 138/500 [03:34<09:03,  1.50s/it, loss=1904.0000, t=940]
Attacking:  28%|██▊       | 138/500 [03:35<09:03,  1.50s/it, loss=1920.0000, t=952]
Attacking:  28%|██▊       | 139/500 [03:36<09:08,  1.52s/it, loss=1920.0000, t=952]
Attacking:  28%|██▊       | 139/500 [03:36<09:08,  1.52s/it, loss=1912.0000, t=952]
Attacking:  28%|██▊       | 140/500 [03:37<09:05,  1.52s/it, loss=1912.0000, t=952]
Attacking:  28%|██▊       | 140/500 [03:38<09:05,  1.52s/it, loss=1992.0000, t=1e+3]
Attacking:  28%|██▊       | 141/500 [03:39<09:02,  1.51s/it, loss=1992.0000, t=1e+3]
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Attacking:  28%|██▊       | 142/500 [03:40<09:01,  1.51s/it, loss=1888.0000, t=912]
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Attacking:  29%|██▊       | 143/500 [03:42<09:04,  1.52s/it, loss=1984.0000, t=992]
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Attacking:  29%|██▉       | 144/500 [03:43<08:54,  1.50s/it, loss=1968.0000, t=992]
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+Max Diff: 0.501961
+Mean Diff: 0.222388
+Saved adversarial image to attacked/images/marllard-water.jpg
+Saved loss curve to attacked/loss_curve/marllard-water_loss.png
+[GPU 4] Stage 3/3: Test
+Loading models for testing marllard-water...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for marllard-water...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 33.91it/s]
+Saved video to attacked/videos/marllard-water.mp4
+Saved frames to attacked/frames/marllard-water
+[GPU 4] Finished marllard-water.jpg
+======================================
+[GPU 4] Processing motocross-jump.jpg (Image 32/50)
+======================================
+[GPU 4] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 4] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   2%|▏         | 12/500 [00:20<12:19,  1.51s/it, loss=2384.0000, t=940]
Attacking:   2%|▏         | 12/500 [00:20<12:19,  1.51s/it, loss=2400.0000, t=972]
Attacking:   3%|▎         | 13/500 [00:21<12:07,  1.49s/it, loss=2400.0000, t=972]
Attacking:   3%|▎         | 13/500 [00:22<12:07,  1.49s/it, loss=2352.0000, t=928]
Attacking:   3%|▎         | 14/500 [00:22<12:02,  1.49s/it, loss=2352.0000, t=928]
Attacking:   3%|▎         | 14/500 [00:23<12:02,  1.49s/it, loss=2400.0000, t=992]
Attacking:   3%|▎         | 15/500 [00:24<11:59,  1.48s/it, loss=2400.0000, t=992]
Attacking:   3%|▎         | 15/500 [00:25<11:59,  1.48s/it, loss=2400.0000, t=984]
Attacking:   3%|▎         | 16/500 [00:26<12:32,  1.56s/it, loss=2400.0000, t=984]
Attacking:   3%|▎         | 16/500 [00:26<12:32,  1.56s/it, loss=2400.0000, t=1e+3]
Attacking:   3%|▎         | 17/500 [00:27<12:27,  1.55s/it, loss=2400.0000, t=1e+3]
Attacking:   3%|▎         | 17/500 [00:28<12:27,  1.55s/it, loss=2384.0000, t=992] 
Attacking:   4%|▎         | 18/500 [00:29<12:46,  1.59s/it, loss=2384.0000, t=992]
Attacking:   4%|▎         | 18/500 [00:30<12:46,  1.59s/it, loss=2368.0000, t=992]
Attacking:   4%|▍         | 19/500 [00:30<12:41,  1.58s/it, loss=2368.0000, t=992]
Attacking:   4%|▍         | 19/500 [00:31<12:41,  1.58s/it, loss=2384.0000, t=1e+3]
Attacking:   4%|▍         | 20/500 [00:32<12:45,  1.59s/it, loss=2384.0000, t=1e+3]
Attacking:   4%|▍         | 20/500 [00:33<12:45,  1.59s/it, loss=2304.0000, t=940] 
Attacking:   4%|▍         | 21/500 [00:34<12:37,  1.58s/it, loss=2304.0000, t=940]
Attacking:   4%|▍         | 21/500 [00:34<12:37,  1.58s/it, loss=2288.0000, t=900]
Attacking:   4%|▍         | 22/500 [00:35<12:29,  1.57s/it, loss=2288.0000, t=900]
Attacking:   4%|▍         | 22/500 [00:36<12:29,  1.57s/it, loss=2304.0000, t=928]
Attacking:   5%|▍         | 23/500 [00:37<12:40,  1.59s/it, loss=2304.0000, t=928]
Attacking:   5%|▍         | 23/500 [00:38<12:40,  1.59s/it, loss=2288.0000, t=928]
Attacking:   5%|▍         | 24/500 [00:38<12:43,  1.60s/it, loss=2288.0000, t=928]
Attacking:   5%|▍         | 24/500 [00:39<12:43,  1.60s/it, loss=2384.0000, t=984]
Attacking:   5%|▌         | 25/500 [00:40<12:36,  1.59s/it, loss=2384.0000, t=984]
Attacking:   5%|▌         | 25/500 [00:41<12:36,  1.59s/it, loss=2288.0000, t=928]
Attacking:   5%|▌         | 26/500 [00:42<12:44,  1.61s/it, loss=2288.0000, t=928]
Attacking:   5%|▌         | 26/500 [00:42<12:44,  1.61s/it, loss=2272.0000, t=900]
Attacking:   5%|▌         | 27/500 [00:43<12:45,  1.62s/it, loss=2272.0000, t=900]
Attacking:   5%|▌         | 27/500 [00:44<12:45,  1.62s/it, loss=2288.0000, t=912]
Attacking:   6%|▌         | 28/500 [00:45<12:38,  1.61s/it, loss=2288.0000, t=912]
Attacking:   6%|▌         | 28/500 [00:46<12:38,  1.61s/it, loss=2336.0000, t=992]
Attacking:   6%|▌         | 29/500 [00:47<12:43,  1.62s/it, loss=2336.0000, t=992]
Attacking:   6%|▌         | 29/500 [00:47<12:43,  1.62s/it, loss=2288.0000, t=928]
Attacking:   6%|▌         | 30/500 [00:48<12:25,  1.59s/it, loss=2288.0000, t=928]
Attacking:   6%|▌         | 30/500 [00:49<12:25,  1.59s/it, loss=2272.0000, t=900]
Attacking:   6%|▌         | 31/500 [00:50<12:24,  1.59s/it, loss=2272.0000, t=900]
Attacking:   6%|▌         | 31/500 [00:50<12:24,  1.59s/it, loss=2336.0000, t=1e+3]
Attacking:   6%|▋         | 32/500 [00:51<12:03,  1.55s/it, loss=2336.0000, t=1e+3]
Attacking:   6%|▋         | 32/500 [00:52<12:03,  1.55s/it, loss=2320.0000, t=992] 
Attacking:   7%|▋         | 33/500 [00:53<11:51,  1.52s/it, loss=2320.0000, t=992]
Attacking:   7%|▋         | 33/500 [00:53<11:51,  1.52s/it, loss=2288.0000, t=952]
Attacking:   7%|▋         | 34/500 [00:54<11:45,  1.51s/it, loss=2288.0000, t=952]
Attacking:   7%|▋         | 34/500 [00:55<11:45,  1.51s/it, loss=2336.0000, t=1e+3]
Attacking:   7%|▋         | 35/500 [00:56<11:39,  1.50s/it, loss=2336.0000, t=1e+3]
Attacking:   7%|▋         | 35/500 [00:56<11:39,  1.50s/it, loss=2256.0000, t=912] 
Attacking:   7%|▋         | 36/500 [00:57<11:47,  1.52s/it, loss=2256.0000, t=912]
Attacking:   7%|▋         | 36/500 [00:58<11:47,  1.52s/it, loss=2320.0000, t=1e+3]
Attacking:   7%|▋         | 37/500 [00:59<11:37,  1.51s/it, loss=2320.0000, t=1e+3]
Attacking:   7%|▋         | 37/500 [00:59<11:37,  1.51s/it, loss=2240.0000, t=900] 
Attacking:   8%|▊         | 38/500 [01:00<11:46,  1.53s/it, loss=2240.0000, t=900]
Attacking:   8%|▊         | 38/500 [01:01<11:46,  1.53s/it, loss=2320.0000, t=984]
Attacking:   8%|▊         | 39/500 [01:02<11:39,  1.52s/it, loss=2320.0000, t=984]
Attacking:   8%|▊         | 39/500 [01:02<11:39,  1.52s/it, loss=2304.0000, t=984]
Attacking:   8%|▊         | 40/500 [01:03<11:27,  1.49s/it, loss=2304.0000, t=984]
Attacking:   8%|▊         | 40/500 [01:04<11:27,  1.49s/it, loss=2240.0000, t=928]
Attacking:   8%|▊         | 41/500 [01:05<11:36,  1.52s/it, loss=2240.0000, t=928]
Attacking:   8%|▊         | 41/500 [01:05<11:36,  1.52s/it, loss=2304.0000, t=1e+3]
Attacking:   8%|▊         | 42/500 [01:06<11:24,  1.49s/it, loss=2304.0000, t=1e+3]
Attacking:   8%|▊         | 42/500 [01:07<11:24,  1.49s/it, loss=2304.0000, t=984] 
Attacking:   9%|▊         | 43/500 [01:08<11:16,  1.48s/it, loss=2304.0000, t=984]
Attacking:   9%|▊         | 43/500 [01:08<11:16,  1.48s/it, loss=2304.0000, t=984]
Attacking:   9%|▉         | 44/500 [01:09<11:03,  1.45s/it, loss=2304.0000, t=984]
Attacking:   9%|▉         | 44/500 [01:09<11:03,  1.45s/it, loss=2272.0000, t=984]
Attacking:   9%|▉         | 45/500 [01:10<10:54,  1.44s/it, loss=2272.0000, t=984]
Attacking:   9%|▉         | 45/500 [01:11<10:54,  1.44s/it, loss=2288.0000, t=1e+3]
Attacking:   9%|▉         | 46/500 [01:12<10:51,  1.43s/it, loss=2288.0000, t=1e+3]
Attacking:   9%|▉         | 46/500 [01:12<10:51,  1.43s/it, loss=2240.0000, t=972] 
Attacking:   9%|▉         | 47/500 [01:13<10:51,  1.44s/it, loss=2240.0000, t=972]
Attacking:   9%|▉         | 47/500 [01:14<10:51,  1.44s/it, loss=2208.0000, t=900]
Attacking:  10%|▉         | 48/500 [01:15<10:45,  1.43s/it, loss=2208.0000, t=900]
Attacking:  10%|▉         | 48/500 [01:15<10:45,  1.43s/it, loss=2224.0000, t=952]
Attacking:  10%|▉         | 49/500 [01:16<11:20,  1.51s/it, loss=2224.0000, t=952]
Attacking:  10%|▉         | 49/500 [01:17<11:20,  1.51s/it, loss=2272.0000, t=984]
Attacking:  10%|█         | 50/500 [01:18<11:25,  1.52s/it, loss=2272.0000, t=984]
Attacking:  10%|█         | 50/500 [01:18<11:25,  1.52s/it, loss=2256.0000, t=992]
Attacking:  10%|█         | 51/500 [01:19<11:06,  1.49s/it, loss=2256.0000, t=992]
Attacking:  10%|█         | 51/500 [01:20<11:06,  1.49s/it, loss=2256.0000, t=992]
Attacking:  10%|█         | 52/500 [01:21<11:20,  1.52s/it, loss=2256.0000, t=992]
Attacking:  10%|█         | 52/500 [01:22<11:20,  1.52s/it, loss=2208.0000, t=952]
Attacking:  11%|█         | 53/500 [01:22<11:32,  1.55s/it, loss=2208.0000, t=952]
Attacking:  11%|█         | 53/500 [01:23<11:32,  1.55s/it, loss=2240.0000, t=972]
Attacking:  11%|█         | 54/500 [01:24<11:49,  1.59s/it, loss=2240.0000, t=972]
Attacking:  11%|█         | 54/500 [01:25<11:49,  1.59s/it, loss=2240.0000, t=972]
Attacking:  11%|█         | 55/500 [01:26<11:58,  1.61s/it, loss=2240.0000, t=972]
Attacking:  11%|█         | 55/500 [01:27<11:58,  1.61s/it, loss=2224.0000, t=964]
Attacking:  11%|█         | 56/500 [01:27<11:45,  1.59s/it, loss=2224.0000, t=964]
Attacking:  11%|█         | 56/500 [01:28<11:45,  1.59s/it, loss=2224.0000, t=972]
Attacking:  11%|█▏        | 57/500 [01:29<11:40,  1.58s/it, loss=2224.0000, t=972]
Attacking:  11%|█▏        | 57/500 [01:30<11:40,  1.58s/it, loss=2192.0000, t=912]
Attacking:  12%|█▏        | 58/500 [01:30<11:30,  1.56s/it, loss=2192.0000, t=912]
Attacking:  12%|█▏        | 58/500 [01:31<11:30,  1.56s/it, loss=2192.0000, t=940]
Attacking:  12%|█▏        | 59/500 [01:32<12:07,  1.65s/it, loss=2192.0000, t=940]
Attacking:  12%|█▏        | 59/500 [01:33<12:07,  1.65s/it, loss=2192.0000, t=900]
Attacking:  12%|█▏        | 60/500 [01:34<11:57,  1.63s/it, loss=2192.0000, t=900]
Attacking:  12%|█▏        | 60/500 [01:35<11:57,  1.63s/it, loss=2192.0000, t=952]
Attacking:  12%|█▏        | 61/500 [01:36<11:58,  1.64s/it, loss=2192.0000, t=952]
Attacking:  12%|█▏        | 61/500 [01:36<11:58,  1.64s/it, loss=2256.0000, t=1e+3]
Attacking:  12%|█▏        | 62/500 [01:37<11:52,  1.63s/it, loss=2256.0000, t=1e+3]
Attacking:  12%|█▏        | 62/500 [01:38<11:52,  1.63s/it, loss=2240.0000, t=984] 
Attacking:  13%|█▎        | 63/500 [01:39<11:54,  1.63s/it, loss=2240.0000, t=984]
Attacking:  13%|█▎        | 63/500 [01:39<11:54,  1.63s/it, loss=2192.0000, t=940]
Attacking:  13%|█▎        | 64/500 [01:40<11:35,  1.59s/it, loss=2192.0000, t=940]
Attacking:  13%|█▎        | 64/500 [01:41<11:35,  1.59s/it, loss=2240.0000, t=1e+3]
Attacking:  13%|█▎        | 65/500 [01:42<11:36,  1.60s/it, loss=2240.0000, t=1e+3]
Attacking:  13%|█▎        | 65/500 [01:43<11:36,  1.60s/it, loss=2240.0000, t=1e+3]
Attacking:  13%|█▎        | 66/500 [01:43<11:24,  1.58s/it, loss=2240.0000, t=1e+3]
Attacking:  13%|█▎        | 66/500 [01:44<11:24,  1.58s/it, loss=2176.0000, t=940] 
Attacking:  13%|█▎        | 67/500 [01:45<11:13,  1.56s/it, loss=2176.0000, t=940]
Attacking:  13%|█▎        | 67/500 [01:46<11:13,  1.56s/it, loss=2176.0000, t=912]
Attacking:  14%|█▎        | 68/500 [01:46<11:10,  1.55s/it, loss=2176.0000, t=912]
Attacking:  14%|█▎        | 68/500 [01:47<11:10,  1.55s/it, loss=2176.0000, t=912]
Attacking:  14%|█▍        | 69/500 [01:48<11:04,  1.54s/it, loss=2176.0000, t=912]
Attacking:  14%|█▍        | 69/500 [01:49<11:04,  1.54s/it, loss=2192.0000, t=952]
Attacking:  14%|█▍        | 70/500 [01:50<10:59,  1.53s/it, loss=2192.0000, t=952]
Attacking:  14%|█▍        | 70/500 [01:50<10:59,  1.53s/it, loss=2160.0000, t=900]
Attacking:  14%|█▍        | 71/500 [01:51<11:02,  1.54s/it, loss=2160.0000, t=900]
Attacking:  14%|█▍        | 71/500 [01:52<11:02,  1.54s/it, loss=2208.0000, t=964]
Attacking:  14%|█▍        | 72/500 [01:53<10:48,  1.51s/it, loss=2208.0000, t=964]
Attacking:  14%|█▍        | 72/500 [01:53<10:48,  1.51s/it, loss=2240.0000, t=984]
Attacking:  15%|█▍        | 73/500 [01:54<10:46,  1.51s/it, loss=2240.0000, t=984]
Attacking:  15%|█▍        | 73/500 [01:55<10:46,  1.51s/it, loss=2176.0000, t=912]
Attacking:  15%|█▍        | 74/500 [01:56<10:49,  1.52s/it, loss=2176.0000, t=912]
Attacking:  15%|█▍        | 74/500 [01:56<10:49,  1.52s/it, loss=2192.0000, t=964]
Attacking:  15%|█▌        | 75/500 [01:57<10:52,  1.54s/it, loss=2192.0000, t=964]
Attacking:  15%|█▌        | 75/500 [01:58<10:52,  1.54s/it, loss=2224.0000, t=984]
Attacking:  15%|█▌        | 76/500 [01:59<10:50,  1.53s/it, loss=2224.0000, t=984]
Attacking:  15%|█▌        | 76/500 [01:59<10:50,  1.53s/it, loss=2176.0000, t=940]
Attacking:  15%|█▌        | 77/500 [02:00<10:56,  1.55s/it, loss=2176.0000, t=940]
Attacking:  15%|█▌        | 77/500 [02:01<10:56,  1.55s/it, loss=2176.0000, t=952]
Attacking:  16%|█▌        | 78/500 [02:02<10:50,  1.54s/it, loss=2176.0000, t=952]
Attacking:  16%|█▌        | 78/500 [02:02<10:50,  1.54s/it, loss=2224.0000, t=1e+3]
Attacking:  16%|█▌        | 79/500 [02:03<10:37,  1.51s/it, loss=2224.0000, t=1e+3]
Attacking:  16%|█▌        | 79/500 [02:04<10:37,  1.51s/it, loss=2160.0000, t=928] 
Attacking:  16%|█▌        | 80/500 [02:05<10:38,  1.52s/it, loss=2160.0000, t=928]
Attacking:  16%|█▌        | 80/500 [02:05<10:38,  1.52s/it, loss=2240.0000, t=1e+3]
Attacking:  16%|█▌        | 81/500 [02:06<10:32,  1.51s/it, loss=2240.0000, t=1e+3]
Attacking:  16%|█▌        | 81/500 [02:07<10:32,  1.51s/it, loss=2160.0000, t=940] 
Attacking:  16%|█▋        | 82/500 [02:08<10:26,  1.50s/it, loss=2160.0000, t=940]
Attacking:  16%|█▋        | 82/500 [02:08<10:26,  1.50s/it, loss=2160.0000, t=928]
Attacking:  17%|█▋        | 83/500 [02:09<10:27,  1.50s/it, loss=2160.0000, t=928]
Attacking:  17%|█▋        | 83/500 [02:10<10:27,  1.50s/it, loss=2208.0000, t=992]
Attacking:  17%|█▋        | 84/500 [02:11<10:25,  1.50s/it, loss=2208.0000, t=992]
Attacking:  17%|█▋        | 84/500 [02:11<10:25,  1.50s/it, loss=2176.0000, t=972]
Attacking:  17%|█▋        | 85/500 [02:12<10:24,  1.51s/it, loss=2176.0000, t=972]
Attacking:  17%|█▋        | 85/500 [02:13<10:24,  1.51s/it, loss=2208.0000, t=984]
Attacking:  17%|█▋        | 86/500 [02:14<10:30,  1.52s/it, loss=2208.0000, t=984]
Attacking:  17%|█▋        | 86/500 [02:14<10:30,  1.52s/it, loss=2144.0000, t=928]
Attacking:  17%|█▋        | 87/500 [02:15<10:24,  1.51s/it, loss=2144.0000, t=928]
Attacking:  17%|█▋        | 87/500 [02:16<10:24,  1.51s/it, loss=2160.0000, t=952]
Attacking:  18%|█▊        | 88/500 [02:17<10:09,  1.48s/it, loss=2160.0000, t=952]
Attacking:  18%|█▊        | 88/500 [02:17<10:09,  1.48s/it, loss=2208.0000, t=1e+3]
Attacking:  18%|█▊        | 89/500 [02:18<10:18,  1.50s/it, loss=2208.0000, t=1e+3]
Attacking:  18%|█▊        | 89/500 [02:19<10:18,  1.50s/it, loss=2144.0000, t=912] 
Attacking:  18%|█▊        | 90/500 [02:20<10:16,  1.50s/it, loss=2144.0000, t=912]
Attacking:  18%|█▊        | 90/500 [02:20<10:16,  1.50s/it, loss=2144.0000, t=912]
Attacking:  18%|█▊        | 91/500 [02:21<10:11,  1.49s/it, loss=2144.0000, t=912]
Attacking:  18%|█▊        | 91/500 [02:22<10:11,  1.49s/it, loss=2144.0000, t=912]
Attacking:  18%|█▊        | 92/500 [02:23<10:33,  1.55s/it, loss=2144.0000, t=912]
Attacking:  18%|█▊        | 92/500 [02:24<10:33,  1.55s/it, loss=2224.0000, t=1e+3]
Attacking:  19%|█▊        | 93/500 [02:24<10:18,  1.52s/it, loss=2224.0000, t=1e+3]
Attacking:  19%|█▊        | 93/500 [02:25<10:18,  1.52s/it, loss=2160.0000, t=952] 
Attacking:  19%|█▉        | 94/500 [02:26<10:11,  1.51s/it, loss=2160.0000, t=952]
Attacking:  19%|█▉        | 94/500 [02:26<10:11,  1.51s/it, loss=2208.0000, t=984]
Attacking:  19%|█▉        | 95/500 [02:27<09:56,  1.47s/it, loss=2208.0000, t=984]
Attacking:  19%|█▉        | 95/500 [02:28<09:56,  1.47s/it, loss=2176.0000, t=964]
Attacking:  19%|█▉        | 96/500 [02:29<09:59,  1.48s/it, loss=2176.0000, t=964]
Attacking:  19%|█▉        | 96/500 [02:29<09:59,  1.48s/it, loss=2160.0000, t=952]
Attacking:  19%|█▉        | 97/500 [02:30<09:53,  1.47s/it, loss=2160.0000, t=952]
Attacking:  19%|█▉        | 97/500 [02:31<09:53,  1.47s/it, loss=2128.0000, t=912]
Attacking:  20%|█▉        | 98/500 [02:32<09:49,  1.47s/it, loss=2128.0000, t=912]
Attacking:  20%|█▉        | 98/500 [02:32<09:49,  1.47s/it, loss=2208.0000, t=1e+3]
Attacking:  20%|█▉        | 99/500 [02:33<10:01,  1.50s/it, loss=2208.0000, t=1e+3]
Attacking:  20%|█▉        | 99/500 [02:34<10:01,  1.50s/it, loss=2176.0000, t=972] 
Attacking:  20%|██        | 100/500 [02:35<09:56,  1.49s/it, loss=2176.0000, t=972]
Attacking:  20%|██        | 100/500 [02:35<09:56,  1.49s/it, loss=2128.0000, t=912]
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+Max Diff: 0.501961
+Mean Diff: 0.242546
+Saved adversarial image to attacked/images/motocross-jump.jpg
+Saved loss curve to attacked/loss_curve/motocross-jump_loss.png
+[GPU 4] Stage 3/3: Test
+Loading models for testing motocross-jump...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for motocross-jump...
+
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+
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+Saved video to attacked/videos/motocross-jump.mp4
+Saved frames to attacked/frames/motocross-jump
+[GPU 4] Finished motocross-jump.jpg
+======================================
+[GPU 4] Processing motorbike.jpg (Image 33/50)
+======================================
+[GPU 4] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 4] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  12%|█▏        | 62/500 [01:38<11:18,  1.55s/it, loss=2448.0000, t=992]
Attacking:  12%|█▏        | 62/500 [01:39<11:18,  1.55s/it, loss=2384.0000, t=928]
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Attacking:  13%|█▎        | 64/500 [01:42<11:12,  1.54s/it, loss=2432.0000, t=1e+3]
Attacking:  13%|█▎        | 65/500 [01:43<11:06,  1.53s/it, loss=2432.0000, t=1e+3]
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Attacking:  14%|█▍        | 70/500 [01:51<10:49,  1.51s/it, loss=2384.0000, t=952]
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Attacking:  14%|█▍        | 72/500 [01:54<10:58,  1.54s/it, loss=2352.0000, t=900]
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Attacking:  15%|█▍        | 73/500 [01:56<10:52,  1.53s/it, loss=2384.0000, t=964]
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Attacking:  15%|█▍        | 74/500 [01:57<10:52,  1.53s/it, loss=2416.0000, t=1e+3]
Attacking:  15%|█▌        | 75/500 [01:58<10:43,  1.51s/it, loss=2416.0000, t=1e+3]
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Attacking:  16%|█▌        | 78/500 [02:04<10:51,  1.54s/it, loss=2384.0000, t=952]
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Attacking:  16%|█▌        | 81/500 [02:08<10:50,  1.55s/it, loss=2432.0000, t=992]
Attacking:  16%|█▋        | 82/500 [02:09<10:58,  1.57s/it, loss=2432.0000, t=992]
Attacking:  16%|█▋        | 82/500 [02:10<10:58,  1.57s/it, loss=2368.0000, t=928]
Attacking:  17%|█▋        | 83/500 [02:11<10:57,  1.58s/it, loss=2368.0000, t=928]
Attacking:  17%|█▋        | 83/500 [02:11<10:57,  1.58s/it, loss=2352.0000, t=900]
Attacking:  17%|█▋        | 84/500 [02:12<10:56,  1.58s/it, loss=2352.0000, t=900]
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Attacking:  17%|█▋        | 85/500 [02:14<11:15,  1.63s/it, loss=2384.0000, t=952]
Attacking:  17%|█▋        | 85/500 [02:15<11:15,  1.63s/it, loss=2416.0000, t=1e+3]
Attacking:  17%|█▋        | 86/500 [02:16<10:57,  1.59s/it, loss=2416.0000, t=1e+3]
Attacking:  17%|█▋        | 86/500 [02:16<10:57,  1.59s/it, loss=2368.0000, t=940] 
Attacking:  17%|█▋        | 87/500 [02:17<10:50,  1.57s/it, loss=2368.0000, t=940]
Attacking:  17%|█▋        | 87/500 [02:18<10:50,  1.57s/it, loss=2400.0000, t=984]
Attacking:  18%|█▊        | 88/500 [02:19<10:29,  1.53s/it, loss=2400.0000, t=984]
Attacking:  18%|█▊        | 88/500 [02:19<10:29,  1.53s/it, loss=2336.0000, t=900]
Attacking:  18%|█▊        | 89/500 [02:20<10:18,  1.50s/it, loss=2336.0000, t=900]
Attacking:  18%|█▊        | 89/500 [02:21<10:18,  1.50s/it, loss=2400.0000, t=1e+3]
Attacking:  18%|█▊        | 90/500 [02:22<10:20,  1.51s/it, loss=2400.0000, t=1e+3]
Attacking:  18%|█▊        | 90/500 [02:22<10:20,  1.51s/it, loss=2400.0000, t=1e+3]
Attacking:  18%|█▊        | 91/500 [02:23<10:16,  1.51s/it, loss=2400.0000, t=1e+3]
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Attacking:  19%|█▊        | 93/500 [02:26<10:25,  1.54s/it, loss=2400.0000, t=1e+3]
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Attacking:  19%|█▉        | 94/500 [02:28<10:21,  1.53s/it, loss=2352.0000, t=940]
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Attacking:  19%|█▉        | 97/500 [02:33<10:05,  1.50s/it, loss=2368.0000, t=972]
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Attacking:  20%|█▉        | 99/500 [02:35<10:17,  1.54s/it, loss=2336.0000, t=940]
Attacking:  20%|█▉        | 99/500 [02:36<10:17,  1.54s/it, loss=2352.0000, t=940]
Attacking:  20%|██        | 100/500 [02:37<10:22,  1.56s/it, loss=2352.0000, t=940]
Attacking:  20%|██        | 100/500 [02:38<10:22,  1.56s/it, loss=2336.0000, t=900]
Attacking:  20%|██        | 101/500 [02:38<10:11,  1.53s/it, loss=2336.0000, t=900]
Attacking:  20%|██        | 101/500 [02:39<10:11,  1.53s/it, loss=2336.0000, t=928]
Attacking:  20%|██        | 102/500 [02:40<10:05,  1.52s/it, loss=2336.0000, t=928]
Attacking:  20%|██        | 102/500 [02:40<10:05,  1.52s/it, loss=2336.0000, t=900]
Attacking:  21%|██        | 103/500 [02:41<09:56,  1.50s/it, loss=2336.0000, t=900]
Attacking:  21%|██        | 103/500 [02:42<09:56,  1.50s/it, loss=2336.0000, t=928]
Attacking:  21%|██        | 104/500 [02:43<09:50,  1.49s/it, loss=2336.0000, t=928]
Attacking:  21%|██        | 104/500 [02:43<09:50,  1.49s/it, loss=2384.0000, t=984]
Attacking:  21%|██        | 105/500 [02:44<09:44,  1.48s/it, loss=2384.0000, t=984]
Attacking:  21%|██        | 105/500 [02:45<09:44,  1.48s/it, loss=2400.0000, t=992]
Attacking:  21%|██        | 106/500 [02:46<09:35,  1.46s/it, loss=2400.0000, t=992]
Attacking:  21%|██        | 106/500 [02:46<09:35,  1.46s/it, loss=2400.0000, t=1e+3]
Attacking:  21%|██▏       | 107/500 [02:47<09:31,  1.45s/it, loss=2400.0000, t=1e+3]
Attacking:  21%|██▏       | 107/500 [02:48<09:31,  1.45s/it, loss=2400.0000, t=1e+3]
Attacking:  22%|██▏       | 108/500 [02:49<09:33,  1.46s/it, loss=2400.0000, t=1e+3]
Attacking:  22%|██▏       | 108/500 [02:49<09:33,  1.46s/it, loss=2400.0000, t=984] 
Attacking:  22%|██▏       | 109/500 [02:50<09:29,  1.46s/it, loss=2400.0000, t=984]
Attacking:  22%|██▏       | 109/500 [02:51<09:29,  1.46s/it, loss=2320.0000, t=900]
Attacking:  22%|██▏       | 110/500 [02:52<09:31,  1.46s/it, loss=2320.0000, t=900]
Attacking:  22%|██▏       | 110/500 [02:52<09:31,  1.46s/it, loss=2352.0000, t=940]
Attacking:  22%|██▏       | 111/500 [02:53<09:49,  1.51s/it, loss=2352.0000, t=940]
Attacking:  22%|██▏       | 111/500 [02:54<09:49,  1.51s/it, loss=2336.0000, t=928]
Attacking:  22%|██▏       | 112/500 [02:55<09:52,  1.53s/it, loss=2336.0000, t=928]
Attacking:  22%|██▏       | 112/500 [02:55<09:52,  1.53s/it, loss=2368.0000, t=964]
Attacking:  23%|██▎       | 113/500 [02:56<09:58,  1.55s/it, loss=2368.0000, t=964]
Attacking:  23%|██▎       | 113/500 [02:57<09:58,  1.55s/it, loss=2320.0000, t=900]
Attacking:  23%|██▎       | 114/500 [02:58<10:00,  1.56s/it, loss=2320.0000, t=900]
Attacking:  23%|██▎       | 114/500 [02:59<10:00,  1.56s/it, loss=2400.0000, t=984]
Attacking:  23%|██▎       | 115/500 [02:59<10:00,  1.56s/it, loss=2400.0000, t=984]
Attacking:  23%|██▎       | 115/500 [03:00<10:00,  1.56s/it, loss=2384.0000, t=984]
Attacking:  23%|██▎       | 116/500 [03:01<09:52,  1.54s/it, loss=2384.0000, t=984]
Attacking:  23%|██▎       | 116/500 [03:02<09:52,  1.54s/it, loss=2336.0000, t=900]
Attacking:  23%|██▎       | 117/500 [03:02<09:42,  1.52s/it, loss=2336.0000, t=900]
Attacking:  23%|██▎       | 117/500 [03:03<09:42,  1.52s/it, loss=2336.0000, t=940]
Attacking:  24%|██▎       | 118/500 [03:04<10:17,  1.62s/it, loss=2336.0000, t=940]
Attacking:  24%|██▎       | 118/500 [03:05<10:17,  1.62s/it, loss=2400.0000, t=992]
Attacking:  24%|██▍       | 119/500 [03:06<10:20,  1.63s/it, loss=2400.0000, t=992]
Attacking:  24%|██▍       | 119/500 [03:07<10:20,  1.63s/it, loss=2384.0000, t=984]
Attacking:  24%|██▍       | 120/500 [03:08<10:23,  1.64s/it, loss=2384.0000, t=984]
Attacking:  24%|██▍       | 120/500 [03:08<10:23,  1.64s/it, loss=2352.0000, t=964]
Attacking:  24%|██▍       | 121/500 [03:09<10:04,  1.60s/it, loss=2352.0000, t=964]
Attacking:  24%|██▍       | 121/500 [03:10<10:04,  1.60s/it, loss=2400.0000, t=1e+3]
Attacking:  24%|██▍       | 122/500 [03:11<10:04,  1.60s/it, loss=2400.0000, t=1e+3]
Attacking:  24%|██▍       | 122/500 [03:11<10:04,  1.60s/it, loss=2336.0000, t=900] 
Attacking:  25%|██▍       | 123/500 [03:12<09:43,  1.55s/it, loss=2336.0000, t=900]
Attacking:  25%|██▍       | 123/500 [03:13<09:43,  1.55s/it, loss=2384.0000, t=984]
Attacking:  25%|██▍       | 124/500 [03:14<09:40,  1.54s/it, loss=2384.0000, t=984]
Attacking:  25%|██▍       | 124/500 [03:14<09:40,  1.54s/it, loss=2352.0000, t=964]
Attacking:  25%|██▌       | 125/500 [03:15<09:42,  1.55s/it, loss=2352.0000, t=964]
Attacking:  25%|██▌       | 125/500 [03:16<09:42,  1.55s/it, loss=2336.0000, t=928]
Attacking:  25%|██▌       | 126/500 [03:17<09:40,  1.55s/it, loss=2336.0000, t=928]
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Attacking:  25%|██▌       | 127/500 [03:18<09:35,  1.54s/it, loss=2352.0000, t=964]
Attacking:  25%|██▌       | 127/500 [03:19<09:35,  1.54s/it, loss=2320.0000, t=940]
Attacking:  26%|██▌       | 128/500 [03:20<09:36,  1.55s/it, loss=2320.0000, t=940]
Attacking:  26%|██▌       | 128/500 [03:21<09:36,  1.55s/it, loss=2320.0000, t=928]
Attacking:  26%|██▌       | 129/500 [03:21<09:32,  1.54s/it, loss=2320.0000, t=928]
Attacking:  26%|██▌       | 129/500 [03:22<09:32,  1.54s/it, loss=2320.0000, t=928]
Attacking:  26%|██▌       | 130/500 [03:23<09:41,  1.57s/it, loss=2320.0000, t=928]
Attacking:  26%|██▌       | 130/500 [03:24<09:41,  1.57s/it, loss=2336.0000, t=952]
Attacking:  26%|██▌       | 131/500 [03:24<09:24,  1.53s/it, loss=2336.0000, t=952]
Attacking:  26%|██▌       | 131/500 [03:25<09:24,  1.53s/it, loss=2384.0000, t=1e+3]
Attacking:  26%|██▋       | 132/500 [03:26<09:28,  1.54s/it, loss=2384.0000, t=1e+3]
Attacking:  26%|██▋       | 132/500 [03:27<09:28,  1.54s/it, loss=2320.0000, t=912] 
Attacking:  27%|██▋       | 133/500 [03:27<09:14,  1.51s/it, loss=2320.0000, t=912]
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Attacking:  27%|██▋       | 134/500 [03:29<09:13,  1.51s/it, loss=2384.0000, t=992]
Attacking:  27%|██▋       | 134/500 [03:30<09:13,  1.51s/it, loss=2336.0000, t=952]
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Attacking:  27%|██▋       | 136/500 [03:32<09:27,  1.56s/it, loss=2304.0000, t=900]
Attacking:  27%|██▋       | 136/500 [03:33<09:27,  1.56s/it, loss=2384.0000, t=1e+3]
Attacking:  27%|██▋       | 137/500 [03:34<09:18,  1.54s/it, loss=2384.0000, t=1e+3]
Attacking:  27%|██▋       | 137/500 [03:34<09:18,  1.54s/it, loss=2336.0000, t=964] 
Attacking:  28%|██▊       | 138/500 [03:35<09:05,  1.51s/it, loss=2336.0000, t=964]
Attacking:  28%|██▊       | 138/500 [03:36<09:05,  1.51s/it, loss=2352.0000, t=972]
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Attacking:  28%|██▊       | 139/500 [03:37<09:08,  1.52s/it, loss=2368.0000, t=1e+3]
Attacking:  28%|██▊       | 140/500 [03:38<09:20,  1.56s/it, loss=2368.0000, t=1e+3]
Attacking:  28%|██▊       | 140/500 [03:39<09:20,  1.56s/it, loss=2304.0000, t=900] 
Attacking:  28%|██▊       | 141/500 [03:40<09:19,  1.56s/it, loss=2304.0000, t=900]
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Attacking:  28%|██▊       | 142/500 [03:41<09:11,  1.54s/it, loss=2368.0000, t=984]
Attacking:  28%|██▊       | 142/500 [03:42<09:11,  1.54s/it, loss=2320.0000, t=940]
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Attacking: 100%|██████████| 500/500 [12:53<00:00,  1.55s/it, loss=2320.0000, t=1e+3]
+Max Diff: 0.501961
+Mean Diff: 0.235172
+Saved adversarial image to attacked/images/motorbike.jpg
+Saved loss curve to attacked/loss_curve/motorbike_loss.png
+[GPU 4] Stage 3/3: Test
+Loading models for testing motorbike...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for motorbike...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 31.02it/s]
+Saved video to attacked/videos/motorbike.mp4
+Saved frames to attacked/frames/motorbike
+[GPU 4] Finished motorbike.jpg
+======================================
+[GPU 4] Processing orchid.jpg (Image 34/50)
+======================================
+[GPU 4] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 4] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   2%|▏         | 8/500 [00:12<12:59,  1.58s/it, loss=1992.0000, t=952]
Attacking:   2%|▏         | 8/500 [00:13<12:59,  1.58s/it, loss=1968.0000, t=912]
Attacking:   2%|▏         | 9/500 [00:14<12:46,  1.56s/it, loss=1968.0000, t=912]
Attacking:   2%|▏         | 9/500 [00:15<12:46,  1.56s/it, loss=1984.0000, t=964]
Attacking:   2%|▏         | 10/500 [00:15<12:29,  1.53s/it, loss=1984.0000, t=964]
Attacking:   2%|▏         | 10/500 [00:16<12:29,  1.53s/it, loss=1952.0000, t=900]
Attacking:   2%|▏         | 11/500 [00:17<12:48,  1.57s/it, loss=1952.0000, t=900]
Attacking:   2%|▏         | 11/500 [00:18<12:48,  1.57s/it, loss=1952.0000, t=940]
Attacking:   2%|▏         | 12/500 [00:19<12:57,  1.59s/it, loss=1952.0000, t=940]
Attacking:   2%|▏         | 12/500 [00:19<12:57,  1.59s/it, loss=2048.0000, t=1e+3]
Attacking:   3%|▎         | 13/500 [00:20<12:56,  1.59s/it, loss=2048.0000, t=1e+3]
Attacking:   3%|▎         | 13/500 [00:21<12:56,  1.59s/it, loss=1968.0000, t=964] 
Attacking:   3%|▎         | 14/500 [00:22<13:08,  1.62s/it, loss=1968.0000, t=964]
Attacking:   3%|▎         | 14/500 [00:23<13:08,  1.62s/it, loss=1952.0000, t=940]
Attacking:   3%|▎         | 15/500 [00:24<13:17,  1.64s/it, loss=1952.0000, t=940]
Attacking:   3%|▎         | 15/500 [00:24<13:17,  1.64s/it, loss=2008.0000, t=1e+3]
Attacking:   3%|▎         | 16/500 [00:25<13:20,  1.65s/it, loss=2008.0000, t=1e+3]
Attacking:   3%|▎         | 16/500 [00:26<13:20,  1.65s/it, loss=1952.0000, t=984] 
Attacking:   3%|▎         | 17/500 [00:27<13:02,  1.62s/it, loss=1952.0000, t=984]
Attacking:   3%|▎         | 17/500 [00:28<13:02,  1.62s/it, loss=1976.0000, t=992]
Attacking:   4%|▎         | 18/500 [00:28<12:53,  1.60s/it, loss=1976.0000, t=992]
Attacking:   4%|▎         | 18/500 [00:29<12:53,  1.60s/it, loss=1968.0000, t=984]
Attacking:   4%|▍         | 19/500 [00:30<12:40,  1.58s/it, loss=1968.0000, t=984]
Attacking:   4%|▍         | 19/500 [00:31<12:40,  1.58s/it, loss=1912.0000, t=912]
Attacking:   4%|▍         | 20/500 [00:31<12:31,  1.57s/it, loss=1912.0000, t=912]
Attacking:   4%|▍         | 20/500 [00:32<12:31,  1.57s/it, loss=1968.0000, t=992]
Attacking:   4%|▍         | 21/500 [00:33<12:25,  1.56s/it, loss=1968.0000, t=992]
Attacking:   4%|▍         | 21/500 [00:34<12:25,  1.56s/it, loss=1920.0000, t=972]
Attacking:   4%|▍         | 22/500 [00:35<12:22,  1.55s/it, loss=1920.0000, t=972]
Attacking:   4%|▍         | 22/500 [00:35<12:22,  1.55s/it, loss=1888.0000, t=928]
Attacking:   5%|▍         | 23/500 [00:36<12:38,  1.59s/it, loss=1888.0000, t=928]
Attacking:   5%|▍         | 23/500 [00:37<12:38,  1.59s/it, loss=1888.0000, t=928]
Attacking:   5%|▍         | 24/500 [00:38<12:46,  1.61s/it, loss=1888.0000, t=928]
Attacking:   5%|▍         | 24/500 [00:39<12:46,  1.61s/it, loss=1912.0000, t=964]
Attacking:   5%|▌         | 25/500 [00:39<12:33,  1.59s/it, loss=1912.0000, t=964]
Attacking:   5%|▌         | 25/500 [00:40<12:33,  1.59s/it, loss=1904.0000, t=940]
Attacking:   5%|▌         | 26/500 [00:41<12:20,  1.56s/it, loss=1904.0000, t=940]
Attacking:   5%|▌         | 26/500 [00:42<12:20,  1.56s/it, loss=1936.0000, t=972]
Attacking:   5%|▌         | 27/500 [00:42<12:12,  1.55s/it, loss=1936.0000, t=972]
Attacking:   5%|▌         | 27/500 [00:43<12:12,  1.55s/it, loss=1920.0000, t=984]
Attacking:   6%|▌         | 28/500 [00:44<12:00,  1.53s/it, loss=1920.0000, t=984]
Attacking:   6%|▌         | 28/500 [00:45<12:00,  1.53s/it, loss=1880.0000, t=952]
Attacking:   6%|▌         | 29/500 [00:45<11:45,  1.50s/it, loss=1880.0000, t=952]
Attacking:   6%|▌         | 29/500 [00:46<11:45,  1.50s/it, loss=1896.0000, t=972]
Attacking:   6%|▌         | 30/500 [00:47<11:41,  1.49s/it, loss=1896.0000, t=972]
Attacking:   6%|▌         | 30/500 [00:48<11:41,  1.49s/it, loss=1888.0000, t=952]
Attacking:   6%|▌         | 31/500 [00:48<11:49,  1.51s/it, loss=1888.0000, t=952]
Attacking:   6%|▌         | 31/500 [00:49<11:49,  1.51s/it, loss=1952.0000, t=1e+3]
Attacking:   6%|▋         | 32/500 [00:50<12:03,  1.54s/it, loss=1952.0000, t=1e+3]
Attacking:   6%|▋         | 32/500 [00:51<12:03,  1.54s/it, loss=1920.0000, t=992] 
Attacking:   7%|▋         | 33/500 [00:52<11:56,  1.53s/it, loss=1920.0000, t=992]
Attacking:   7%|▋         | 33/500 [00:52<11:56,  1.53s/it, loss=1912.0000, t=992]
Attacking:   7%|▋         | 34/500 [00:53<12:03,  1.55s/it, loss=1912.0000, t=992]
Attacking:   7%|▋         | 34/500 [00:54<12:03,  1.55s/it, loss=1864.0000, t=928]
Attacking:   7%|▋         | 35/500 [00:55<12:19,  1.59s/it, loss=1864.0000, t=928]
Attacking:   7%|▋         | 35/500 [00:56<12:19,  1.59s/it, loss=1856.0000, t=912]
Attacking:   7%|▋         | 36/500 [00:57<12:35,  1.63s/it, loss=1856.0000, t=912]
Attacking:   7%|▋         | 36/500 [00:57<12:35,  1.63s/it, loss=1912.0000, t=992]
Attacking:   7%|▋         | 37/500 [00:58<12:45,  1.65s/it, loss=1912.0000, t=992]
Attacking:   7%|▋         | 37/500 [00:59<12:45,  1.65s/it, loss=1880.0000, t=984]
Attacking:   8%|▊         | 38/500 [01:00<12:18,  1.60s/it, loss=1880.0000, t=984]
Attacking:   8%|▊         | 38/500 [01:00<12:18,  1.60s/it, loss=1872.0000, t=928]
Attacking:   8%|▊         | 39/500 [01:01<12:09,  1.58s/it, loss=1872.0000, t=928]
Attacking:   8%|▊         | 39/500 [01:02<12:09,  1.58s/it, loss=1864.0000, t=964]
Attacking:   8%|▊         | 40/500 [01:03<12:13,  1.59s/it, loss=1864.0000, t=964]
Attacking:   8%|▊         | 40/500 [01:04<12:13,  1.59s/it, loss=1856.0000, t=912]
Attacking:   8%|▊         | 41/500 [01:05<12:15,  1.60s/it, loss=1856.0000, t=912]
Attacking:   8%|▊         | 41/500 [01:05<12:15,  1.60s/it, loss=1904.0000, t=992]
Attacking:   8%|▊         | 42/500 [01:06<12:16,  1.61s/it, loss=1904.0000, t=992]
Attacking:   8%|▊         | 42/500 [01:07<12:16,  1.61s/it, loss=1832.0000, t=900]
Attacking:   9%|▊         | 43/500 [01:08<12:21,  1.62s/it, loss=1832.0000, t=900]
Attacking:   9%|▊         | 43/500 [01:09<12:21,  1.62s/it, loss=1832.0000, t=912]
Attacking:   9%|▉         | 44/500 [01:09<12:23,  1.63s/it, loss=1832.0000, t=912]
Attacking:   9%|▉         | 44/500 [01:10<12:23,  1.63s/it, loss=1856.0000, t=972]
Attacking:   9%|▉         | 45/500 [01:11<12:33,  1.66s/it, loss=1856.0000, t=972]
Attacking:   9%|▉         | 45/500 [01:12<12:33,  1.66s/it, loss=1856.0000, t=984]
Attacking:   9%|▉         | 46/500 [01:13<12:40,  1.67s/it, loss=1856.0000, t=984]
Attacking:   9%|▉         | 46/500 [01:14<12:40,  1.67s/it, loss=1848.0000, t=972]
Attacking:   9%|▉         | 47/500 [01:14<12:33,  1.66s/it, loss=1848.0000, t=972]
Attacking:   9%|▉         | 47/500 [01:15<12:33,  1.66s/it, loss=1816.0000, t=900]
Attacking:  10%|▉         | 48/500 [01:16<12:20,  1.64s/it, loss=1816.0000, t=900]
Attacking:  10%|▉         | 48/500 [01:17<12:20,  1.64s/it, loss=1904.0000, t=1e+3]
Attacking:  10%|▉         | 49/500 [01:18<12:16,  1.63s/it, loss=1904.0000, t=1e+3]
Attacking:  10%|▉         | 49/500 [01:19<12:16,  1.63s/it, loss=1808.0000, t=900] 
Attacking:  10%|█         | 50/500 [01:19<12:21,  1.65s/it, loss=1808.0000, t=900]
Attacking:  10%|█         | 50/500 [01:20<12:21,  1.65s/it, loss=1816.0000, t=900]
Attacking:  10%|█         | 51/500 [01:21<12:03,  1.61s/it, loss=1816.0000, t=900]
Attacking:  10%|█         | 51/500 [01:21<12:03,  1.61s/it, loss=1872.0000, t=992]
Attacking:  10%|█         | 52/500 [01:22<11:38,  1.56s/it, loss=1872.0000, t=992]
Attacking:  10%|█         | 52/500 [01:23<11:38,  1.56s/it, loss=1824.0000, t=972]
Attacking:  11%|█         | 53/500 [01:24<11:28,  1.54s/it, loss=1824.0000, t=972]
Attacking:  11%|█         | 53/500 [01:25<11:28,  1.54s/it, loss=1888.0000, t=1e+3]
Attacking:  11%|█         | 54/500 [01:25<11:31,  1.55s/it, loss=1888.0000, t=1e+3]
Attacking:  11%|█         | 54/500 [01:26<11:31,  1.55s/it, loss=1808.0000, t=952] 
Attacking:  11%|█         | 55/500 [01:27<11:29,  1.55s/it, loss=1808.0000, t=952]
Attacking:  11%|█         | 55/500 [01:28<11:29,  1.55s/it, loss=1816.0000, t=900]
Attacking:  11%|█         | 56/500 [01:28<11:21,  1.53s/it, loss=1816.0000, t=900]
Attacking:  11%|█         | 56/500 [01:29<11:21,  1.53s/it, loss=1808.0000, t=940]
Attacking:  11%|█▏        | 57/500 [01:30<11:17,  1.53s/it, loss=1808.0000, t=940]
Attacking:  11%|█▏        | 57/500 [01:31<11:17,  1.53s/it, loss=1888.0000, t=1e+3]
Attacking:  12%|█▏        | 58/500 [01:32<11:32,  1.57s/it, loss=1888.0000, t=1e+3]
Attacking:  12%|█▏        | 58/500 [01:32<11:32,  1.57s/it, loss=1864.0000, t=1e+3]
Attacking:  12%|█▏        | 59/500 [01:33<11:38,  1.58s/it, loss=1864.0000, t=1e+3]
Attacking:  12%|█▏        | 59/500 [01:34<11:38,  1.58s/it, loss=1808.0000, t=964] 
Attacking:  12%|█▏        | 60/500 [01:35<11:36,  1.58s/it, loss=1808.0000, t=964]
Attacking:  12%|█▏        | 60/500 [01:36<11:36,  1.58s/it, loss=1848.0000, t=992]
Attacking:  12%|█▏        | 61/500 [01:36<11:25,  1.56s/it, loss=1848.0000, t=992]
Attacking:  12%|█▏        | 61/500 [01:37<11:25,  1.56s/it, loss=1808.0000, t=964]
Attacking:  12%|█▏        | 62/500 [01:38<11:24,  1.56s/it, loss=1808.0000, t=964]
Attacking:  12%|█▏        | 62/500 [01:39<11:24,  1.56s/it, loss=1792.0000, t=952]
Attacking:  13%|█▎        | 63/500 [01:39<11:17,  1.55s/it, loss=1792.0000, t=952]
Attacking:  13%|█▎        | 63/500 [01:40<11:17,  1.55s/it, loss=1840.0000, t=972]
Attacking:  13%|█▎        | 64/500 [01:41<11:24,  1.57s/it, loss=1840.0000, t=972]
Attacking:  13%|█▎        | 64/500 [01:42<11:24,  1.57s/it, loss=1792.0000, t=940]
Attacking:  13%|█▎        | 65/500 [01:43<11:20,  1.56s/it, loss=1792.0000, t=940]
Attacking:  13%|█▎        | 65/500 [01:43<11:20,  1.56s/it, loss=1824.0000, t=984]
Attacking:  13%|█▎        | 66/500 [01:44<11:28,  1.59s/it, loss=1824.0000, t=984]
Attacking:  13%|█▎        | 66/500 [01:45<11:28,  1.59s/it, loss=1800.0000, t=952]
Attacking:  13%|█▎        | 67/500 [01:46<11:36,  1.61s/it, loss=1800.0000, t=952]
Attacking:  13%|█▎        | 67/500 [01:47<11:36,  1.61s/it, loss=1792.0000, t=952]
Attacking:  14%|█▎        | 68/500 [01:48<11:41,  1.62s/it, loss=1792.0000, t=952]
Attacking:  14%|█▎        | 68/500 [01:48<11:41,  1.62s/it, loss=1768.0000, t=900]
Attacking:  14%|█▍        | 69/500 [01:49<11:29,  1.60s/it, loss=1768.0000, t=900]
Attacking:  14%|█▍        | 69/500 [01:50<11:29,  1.60s/it, loss=1848.0000, t=992]
Attacking:  14%|█▍        | 70/500 [01:51<11:12,  1.56s/it, loss=1848.0000, t=992]
Attacking:  14%|█▍        | 70/500 [01:51<11:12,  1.56s/it, loss=1792.0000, t=964]
Attacking:  14%|█▍        | 71/500 [01:52<11:21,  1.59s/it, loss=1792.0000, t=964]
Attacking:  14%|█▍        | 71/500 [01:53<11:21,  1.59s/it, loss=1768.0000, t=900]
Attacking:  14%|█▍        | 72/500 [01:54<11:14,  1.58s/it, loss=1768.0000, t=900]
Attacking:  14%|█▍        | 72/500 [01:55<11:14,  1.58s/it, loss=1784.0000, t=952]
Attacking:  15%|█▍        | 73/500 [01:55<11:12,  1.57s/it, loss=1784.0000, t=952]
Attacking:  15%|█▍        | 73/500 [01:56<11:12,  1.57s/it, loss=1800.0000, t=972]
Attacking:  15%|█▍        | 74/500 [01:57<11:01,  1.55s/it, loss=1800.0000, t=972]
Attacking:  15%|█▍        | 74/500 [01:57<11:01,  1.55s/it, loss=1768.0000, t=912]
Attacking:  15%|█▌        | 75/500 [01:58<10:45,  1.52s/it, loss=1768.0000, t=912]
Attacking:  15%|█▌        | 75/500 [01:59<10:45,  1.52s/it, loss=1816.0000, t=984]
Attacking:  15%|█▌        | 76/500 [02:00<10:53,  1.54s/it, loss=1816.0000, t=984]
Attacking:  15%|█▌        | 76/500 [02:01<10:53,  1.54s/it, loss=1776.0000, t=928]
Attacking:  15%|█▌        | 77/500 [02:01<10:49,  1.54s/it, loss=1776.0000, t=928]
Attacking:  15%|█▌        | 77/500 [02:02<10:49,  1.54s/it, loss=1840.0000, t=992]
Attacking:  16%|█▌        | 78/500 [02:03<10:52,  1.55s/it, loss=1840.0000, t=992]
Attacking:  16%|█▌        | 78/500 [02:04<10:52,  1.55s/it, loss=1840.0000, t=1e+3]
Attacking:  16%|█▌        | 79/500 [02:04<10:45,  1.53s/it, loss=1840.0000, t=1e+3]
Attacking:  16%|█▌        | 79/500 [02:05<10:45,  1.53s/it, loss=1808.0000, t=984] 
Attacking:  16%|█▌        | 80/500 [02:06<10:41,  1.53s/it, loss=1808.0000, t=984]
Attacking:  16%|█▌        | 80/500 [02:07<10:41,  1.53s/it, loss=1776.0000, t=972]
Attacking:  16%|█▌        | 81/500 [02:07<10:31,  1.51s/it, loss=1776.0000, t=972]
Attacking:  16%|█▌        | 81/500 [02:08<10:31,  1.51s/it, loss=1824.0000, t=992]
Attacking:  16%|█▋        | 82/500 [02:09<10:44,  1.54s/it, loss=1824.0000, t=992]
Attacking:  16%|█▋        | 82/500 [02:10<10:44,  1.54s/it, loss=1768.0000, t=952]
Attacking:  17%|█▋        | 83/500 [02:11<10:54,  1.57s/it, loss=1768.0000, t=952]
Attacking:  17%|█▋        | 83/500 [02:11<10:54,  1.57s/it, loss=1768.0000, t=952]
Attacking:  17%|█▋        | 84/500 [02:12<10:40,  1.54s/it, loss=1768.0000, t=952]
Attacking:  17%|█▋        | 84/500 [02:13<10:40,  1.54s/it, loss=1768.0000, t=972]
Attacking:  17%|█▋        | 85/500 [02:14<10:31,  1.52s/it, loss=1768.0000, t=972]
Attacking:  17%|█▋        | 85/500 [02:14<10:31,  1.52s/it, loss=1776.0000, t=972]
Attacking:  17%|█▋        | 86/500 [02:15<10:20,  1.50s/it, loss=1776.0000, t=972]
Attacking:  17%|█▋        | 86/500 [02:16<10:20,  1.50s/it, loss=1752.0000, t=912]
Attacking:  17%|█▋        | 87/500 [02:17<10:24,  1.51s/it, loss=1752.0000, t=912]
Attacking:  17%|█▋        | 87/500 [02:17<10:24,  1.51s/it, loss=1760.0000, t=964]
Attacking:  18%|█▊        | 88/500 [02:18<10:28,  1.52s/it, loss=1760.0000, t=964]
Attacking:  18%|█▊        | 88/500 [02:19<10:28,  1.52s/it, loss=1784.0000, t=984]
Attacking:  18%|█▊        | 89/500 [02:20<10:26,  1.52s/it, loss=1784.0000, t=984]
Attacking:  18%|█▊        | 89/500 [02:20<10:26,  1.52s/it, loss=1744.0000, t=900]
Attacking:  18%|█▊        | 90/500 [02:21<10:33,  1.54s/it, loss=1744.0000, t=900]
Attacking:  18%|█▊        | 90/500 [02:22<10:33,  1.54s/it, loss=1864.0000, t=1e+3]
Attacking:  18%|█▊        | 91/500 [02:23<10:29,  1.54s/it, loss=1864.0000, t=1e+3]
Attacking:  18%|█▊        | 91/500 [02:24<10:29,  1.54s/it, loss=1760.0000, t=972] 
Attacking:  18%|█▊        | 92/500 [02:24<10:25,  1.53s/it, loss=1760.0000, t=972]
Attacking:  18%|█▊        | 92/500 [02:25<10:25,  1.53s/it, loss=1792.0000, t=972]
Attacking:  19%|█▊        | 93/500 [02:26<10:25,  1.54s/it, loss=1792.0000, t=972]
Attacking:  19%|█▊        | 93/500 [02:27<10:25,  1.54s/it, loss=1760.0000, t=964]
Attacking:  19%|█▉        | 94/500 [02:27<10:19,  1.53s/it, loss=1760.0000, t=964]
Attacking:  19%|█▉        | 94/500 [02:28<10:19,  1.53s/it, loss=1744.0000, t=928]
Attacking:  19%|█▉        | 95/500 [02:29<10:22,  1.54s/it, loss=1744.0000, t=928]
Attacking:  19%|█▉        | 95/500 [02:30<10:22,  1.54s/it, loss=1760.0000, t=972]
Attacking:  19%|█▉        | 96/500 [02:31<10:30,  1.56s/it, loss=1760.0000, t=972]
Attacking:  19%|█▉        | 96/500 [02:31<10:30,  1.56s/it, loss=1816.0000, t=1e+3]
Attacking:  19%|█▉        | 97/500 [02:32<10:11,  1.52s/it, loss=1816.0000, t=1e+3]
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\ No newline at end of file
diff --git a/experiments/cfg3_eps64/logs/gpu_5.log b/experiments/cfg3_eps64/logs/gpu_5.log
new file mode 100644
index 0000000000000000000000000000000000000000..c8b31e59d139c821a7063038a47fe400212267be
--- /dev/null
+++ b/experiments/cfg3_eps64/logs/gpu_5.log
@@ -0,0 +1,483 @@
+[GPU 5] Starting work on images 35 to 41
+======================================
+[GPU 5] Processing parkour.jpg (Image 35/50)
+======================================
+[GPU 5] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 5] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   3%|▎         | 15/500 [00:26<13:17,  1.64s/it, loss=2144.0000, t=984]
Attacking:   3%|▎         | 16/500 [00:27<13:55,  1.73s/it, loss=2144.0000, t=984]
Attacking:   3%|▎         | 16/500 [00:28<13:55,  1.73s/it, loss=2096.0000, t=940]
Attacking:   3%|▎         | 17/500 [00:28<13:35,  1.69s/it, loss=2096.0000, t=940]
Attacking:   3%|▎         | 17/500 [00:29<13:35,  1.69s/it, loss=2144.0000, t=992]
Attacking:   4%|▎         | 18/500 [00:30<13:24,  1.67s/it, loss=2144.0000, t=992]
Attacking:   4%|▎         | 18/500 [00:31<13:24,  1.67s/it, loss=2080.0000, t=912]
Attacking:   4%|▍         | 19/500 [00:32<13:02,  1.63s/it, loss=2080.0000, t=912]
Attacking:   4%|▍         | 19/500 [00:32<13:02,  1.63s/it, loss=2080.0000, t=928]
Attacking:   4%|▍         | 20/500 [00:33<13:02,  1.63s/it, loss=2080.0000, t=928]
Attacking:   4%|▍         | 20/500 [00:34<13:02,  1.63s/it, loss=2064.0000, t=928]
Attacking:   4%|▍         | 21/500 [00:35<13:08,  1.65s/it, loss=2064.0000, t=928]
Attacking:   4%|▍         | 21/500 [00:36<13:08,  1.65s/it, loss=2080.0000, t=940]
Attacking:   4%|▍         | 22/500 [00:37<13:18,  1.67s/it, loss=2080.0000, t=940]
Attacking:   4%|▍         | 22/500 [00:38<13:18,  1.67s/it, loss=2080.0000, t=952]
Attacking:   5%|▍         | 23/500 [00:38<13:21,  1.68s/it, loss=2080.0000, t=952]
Attacking:   5%|▍         | 23/500 [00:39<13:21,  1.68s/it, loss=2080.0000, t=952]
Attacking:   5%|▍         | 24/500 [00:40<13:15,  1.67s/it, loss=2080.0000, t=952]
Attacking:   5%|▍         | 24/500 [00:41<13:15,  1.67s/it, loss=2064.0000, t=952]
Attacking:   5%|▌         | 25/500 [00:42<13:01,  1.65s/it, loss=2064.0000, t=952]
Attacking:   5%|▌         | 25/500 [00:42<13:01,  1.65s/it, loss=2048.0000, t=928]
Attacking:   5%|▌         | 26/500 [00:43<12:53,  1.63s/it, loss=2048.0000, t=928]
Attacking:   5%|▌         | 26/500 [00:44<12:53,  1.63s/it, loss=2112.0000, t=992]
Attacking:   5%|▌         | 27/500 [00:45<13:00,  1.65s/it, loss=2112.0000, t=992]
Attacking:   5%|▌         | 27/500 [00:46<13:00,  1.65s/it, loss=2064.0000, t=964]
Attacking:   6%|▌         | 28/500 [00:46<12:35,  1.60s/it, loss=2064.0000, t=964]
Attacking:   6%|▌         | 28/500 [00:47<12:35,  1.60s/it, loss=2032.0000, t=928]
Attacking:   6%|▌         | 29/500 [00:48<12:38,  1.61s/it, loss=2032.0000, t=928]
Attacking:   6%|▌         | 29/500 [00:49<12:38,  1.61s/it, loss=2096.0000, t=992]
Attacking:   6%|▌         | 30/500 [00:50<12:55,  1.65s/it, loss=2096.0000, t=992]
Attacking:   6%|▌         | 30/500 [00:51<12:55,  1.65s/it, loss=2064.0000, t=984]
Attacking:   6%|▌         | 31/500 [00:51<12:52,  1.65s/it, loss=2064.0000, t=984]
Attacking:   6%|▌         | 31/500 [00:52<12:52,  1.65s/it, loss=2128.0000, t=1e+3]
Attacking:   6%|▋         | 32/500 [00:53<12:44,  1.63s/it, loss=2128.0000, t=1e+3]
Attacking:   6%|▋         | 32/500 [00:54<12:44,  1.63s/it, loss=2048.0000, t=940] 
Attacking:   7%|▋         | 33/500 [00:55<12:52,  1.65s/it, loss=2048.0000, t=940]
Attacking:   7%|▋         | 33/500 [00:55<12:52,  1.65s/it, loss=2096.0000, t=992]
Attacking:   7%|▋         | 34/500 [00:56<12:37,  1.63s/it, loss=2096.0000, t=992]
Attacking:   7%|▋         | 34/500 [00:57<12:37,  1.63s/it, loss=2048.0000, t=972]
Attacking:   7%|▋         | 35/500 [00:58<12:34,  1.62s/it, loss=2048.0000, t=972]
Attacking:   7%|▋         | 35/500 [00:59<12:34,  1.62s/it, loss=2096.0000, t=992]
Attacking:   7%|▋         | 36/500 [01:00<12:50,  1.66s/it, loss=2096.0000, t=992]
Attacking:   7%|▋         | 36/500 [01:00<12:50,  1.66s/it, loss=2024.0000, t=940]
Attacking:   7%|▋         | 37/500 [01:01<12:37,  1.64s/it, loss=2024.0000, t=940]
Attacking:   7%|▋         | 37/500 [01:02<12:37,  1.64s/it, loss=2040.0000, t=964]
Attacking:   8%|▊         | 38/500 [01:03<12:38,  1.64s/it, loss=2040.0000, t=964]
Attacking:   8%|▊         | 38/500 [01:04<12:38,  1.64s/it, loss=2016.0000, t=912]
Attacking:   8%|▊         | 39/500 [01:04<12:35,  1.64s/it, loss=2016.0000, t=912]
Attacking:   8%|▊         | 39/500 [01:05<12:35,  1.64s/it, loss=2048.0000, t=972]
Attacking:   8%|▊         | 40/500 [01:06<12:41,  1.65s/it, loss=2048.0000, t=972]
Attacking:   8%|▊         | 40/500 [01:07<12:41,  1.65s/it, loss=2080.0000, t=992]
Attacking:   8%|▊         | 41/500 [01:08<12:31,  1.64s/it, loss=2080.0000, t=992]
Attacking:   8%|▊         | 41/500 [01:09<12:31,  1.64s/it, loss=2008.0000, t=900]
Attacking:   8%|▊         | 42/500 [01:09<12:26,  1.63s/it, loss=2008.0000, t=900]
Attacking:   8%|▊         | 42/500 [01:10<12:26,  1.63s/it, loss=1992.0000, t=900]
Attacking:   9%|▊         | 43/500 [01:11<12:15,  1.61s/it, loss=1992.0000, t=900]
Attacking:   9%|▊         | 43/500 [01:12<12:15,  1.61s/it, loss=2008.0000, t=928]
Attacking:   9%|▉         | 44/500 [01:13<12:22,  1.63s/it, loss=2008.0000, t=928]
Attacking:   9%|▉         | 44/500 [01:13<12:22,  1.63s/it, loss=2024.0000, t=972]
Attacking:   9%|▉         | 45/500 [01:14<12:25,  1.64s/it, loss=2024.0000, t=972]
Attacking:   9%|▉         | 45/500 [01:15<12:25,  1.64s/it, loss=2016.0000, t=952]
Attacking:   9%|▉         | 46/500 [01:16<12:29,  1.65s/it, loss=2016.0000, t=952]
Attacking:   9%|▉         | 46/500 [01:17<12:29,  1.65s/it, loss=2008.0000, t=952]
Attacking:   9%|▉         | 47/500 [01:18<12:20,  1.63s/it, loss=2008.0000, t=952]
Attacking:   9%|▉         | 47/500 [01:18<12:20,  1.63s/it, loss=2040.0000, t=984]
Attacking:  10%|▉         | 48/500 [01:19<12:13,  1.62s/it, loss=2040.0000, t=984]
Attacking:  10%|▉         | 48/500 [01:20<12:13,  1.62s/it, loss=2064.0000, t=992]
Attacking:  10%|▉         | 49/500 [01:21<12:01,  1.60s/it, loss=2064.0000, t=992]
Attacking:  10%|▉         | 49/500 [01:21<12:01,  1.60s/it, loss=1984.0000, t=928]
Attacking:  10%|█         | 50/500 [01:22<11:53,  1.59s/it, loss=1984.0000, t=928]
Attacking:  10%|█         | 50/500 [01:23<11:53,  1.59s/it, loss=2008.0000, t=972]
Attacking:  10%|█         | 51/500 [01:24<11:39,  1.56s/it, loss=2008.0000, t=972]
Attacking:  10%|█         | 51/500 [01:24<11:39,  1.56s/it, loss=1992.0000, t=928]
Attacking:  10%|█         | 52/500 [01:25<11:22,  1.52s/it, loss=1992.0000, t=928]
Attacking:  10%|█         | 52/500 [01:26<11:22,  1.52s/it, loss=2000.0000, t=952]
Attacking:  11%|█         | 53/500 [01:27<11:22,  1.53s/it, loss=2000.0000, t=952]
Attacking:  11%|█         | 53/500 [01:27<11:22,  1.53s/it, loss=2048.0000, t=992]
Attacking:  11%|█         | 54/500 [01:28<11:16,  1.52s/it, loss=2048.0000, t=992]
Attacking:  11%|█         | 54/500 [01:29<11:16,  1.52s/it, loss=2000.0000, t=972]
Attacking:  11%|█         | 55/500 [01:30<11:13,  1.51s/it, loss=2000.0000, t=972]
Attacking:  11%|█         | 55/500 [01:30<11:13,  1.51s/it, loss=2064.0000, t=1e+3]
Attacking:  11%|█         | 56/500 [01:31<11:01,  1.49s/it, loss=2064.0000, t=1e+3]
Attacking:  11%|█         | 56/500 [01:32<11:01,  1.49s/it, loss=1992.0000, t=952] 
Attacking:  11%|█▏        | 57/500 [01:33<11:01,  1.49s/it, loss=1992.0000, t=952]
Attacking:  11%|█▏        | 57/500 [01:33<11:01,  1.49s/it, loss=2064.0000, t=1e+3]
Attacking:  12%|█▏        | 58/500 [01:34<11:00,  1.49s/it, loss=2064.0000, t=1e+3]
Attacking:  12%|█▏        | 58/500 [01:35<11:00,  1.49s/it, loss=2040.0000, t=992] 
Attacking:  12%|█▏        | 59/500 [01:36<11:32,  1.57s/it, loss=2040.0000, t=992]
Attacking:  12%|█▏        | 59/500 [01:37<11:32,  1.57s/it, loss=1992.0000, t=972]
Attacking:  12%|█▏        | 60/500 [01:37<11:23,  1.55s/it, loss=1992.0000, t=972]
Attacking:  12%|█▏        | 60/500 [01:38<11:23,  1.55s/it, loss=1960.0000, t=900]
Attacking:  12%|█▏        | 61/500 [01:39<11:25,  1.56s/it, loss=1960.0000, t=900]
Attacking:  12%|█▏        | 61/500 [01:40<11:25,  1.56s/it, loss=1976.0000, t=952]
Attacking:  12%|█▏        | 62/500 [01:41<11:38,  1.59s/it, loss=1976.0000, t=952]
Attacking:  12%|█▏        | 62/500 [01:41<11:38,  1.59s/it, loss=1976.0000, t=952]
Attacking:  13%|█▎        | 63/500 [01:42<11:29,  1.58s/it, loss=1976.0000, t=952]
Attacking:  13%|█▎        | 63/500 [01:43<11:29,  1.58s/it, loss=1952.0000, t=900]
Attacking:  13%|█▎        | 64/500 [01:44<11:33,  1.59s/it, loss=1952.0000, t=900]
Attacking:  13%|█▎        | 64/500 [01:44<11:33,  1.59s/it, loss=1968.0000, t=952]
Attacking:  13%|█▎        | 65/500 [01:45<11:17,  1.56s/it, loss=1968.0000, t=952]
Attacking:  13%|█▎        | 65/500 [01:46<11:17,  1.56s/it, loss=1968.0000, t=928]
Attacking:  13%|█▎        | 66/500 [01:47<11:03,  1.53s/it, loss=1968.0000, t=928]
Attacking:  13%|█▎        | 66/500 [01:48<11:03,  1.53s/it, loss=1976.0000, t=972]
Attacking:  13%|█▎        | 67/500 [01:48<11:12,  1.55s/it, loss=1976.0000, t=972]
Attacking:  13%|█▎        | 67/500 [01:49<11:12,  1.55s/it, loss=1976.0000, t=972]
Attacking:  14%|█▎        | 68/500 [01:50<11:02,  1.53s/it, loss=1976.0000, t=972]
Attacking:  14%|█▎        | 68/500 [01:51<11:02,  1.53s/it, loss=2000.0000, t=984]
Attacking:  14%|█▍        | 69/500 [01:51<11:04,  1.54s/it, loss=2000.0000, t=984]
Attacking:  14%|█▍        | 69/500 [01:52<11:04,  1.54s/it, loss=2024.0000, t=992]
Attacking:  14%|█▍        | 70/500 [01:53<11:06,  1.55s/it, loss=2024.0000, t=992]
Attacking:  14%|█▍        | 70/500 [01:54<11:06,  1.55s/it, loss=1952.0000, t=900]
Attacking:  14%|█▍        | 71/500 [01:54<10:51,  1.52s/it, loss=1952.0000, t=900]
Attacking:  14%|█▍        | 71/500 [01:55<10:51,  1.52s/it, loss=1952.0000, t=912]
Attacking:  14%|█▍        | 72/500 [01:56<11:05,  1.56s/it, loss=1952.0000, t=912]
Attacking:  14%|█▍        | 72/500 [01:57<11:05,  1.56s/it, loss=2032.0000, t=1e+3]
Attacking:  15%|█▍        | 73/500 [01:58<11:16,  1.58s/it, loss=2032.0000, t=1e+3]
Attacking:  15%|█▍        | 73/500 [01:59<11:16,  1.58s/it, loss=2016.0000, t=992] 
Attacking:  15%|█▍        | 74/500 [02:00<11:37,  1.64s/it, loss=2016.0000, t=992]
Attacking:  15%|█▍        | 74/500 [02:00<11:37,  1.64s/it, loss=1984.0000, t=984]
Attacking:  15%|█▌        | 75/500 [02:01<11:42,  1.65s/it, loss=1984.0000, t=984]
Attacking:  15%|█▌        | 75/500 [02:02<11:42,  1.65s/it, loss=2024.0000, t=1e+3]
Attacking:  15%|█▌        | 76/500 [02:03<12:19,  1.74s/it, loss=2024.0000, t=1e+3]
Attacking:  15%|█▌        | 76/500 [02:04<12:19,  1.74s/it, loss=1936.0000, t=900] 
Attacking:  15%|█▌        | 77/500 [02:05<11:58,  1.70s/it, loss=1936.0000, t=900]
Attacking:  15%|█▌        | 77/500 [02:05<11:58,  1.70s/it, loss=1960.0000, t=964]
Attacking:  16%|█▌        | 78/500 [02:06<11:42,  1.66s/it, loss=1960.0000, t=964]
Attacking:  16%|█▌        | 78/500 [02:07<11:42,  1.66s/it, loss=1936.0000, t=912]
Attacking:  16%|█▌        | 79/500 [02:08<11:29,  1.64s/it, loss=1936.0000, t=912]
Attacking:  16%|█▌        | 79/500 [02:09<11:29,  1.64s/it, loss=1944.0000, t=940]
Attacking:  16%|█▌        | 80/500 [02:09<11:16,  1.61s/it, loss=1944.0000, t=940]
Attacking:  16%|█▌        | 80/500 [02:10<11:16,  1.61s/it, loss=2016.0000, t=1e+3]
Attacking:  16%|█▌        | 81/500 [02:11<10:51,  1.56s/it, loss=2016.0000, t=1e+3]
Attacking:  16%|█▌        | 81/500 [02:12<10:51,  1.56s/it, loss=2016.0000, t=1e+3]
Attacking:  16%|█▋        | 82/500 [02:13<11:08,  1.60s/it, loss=2016.0000, t=1e+3]
Attacking:  16%|█▋        | 82/500 [02:13<11:08,  1.60s/it, loss=2000.0000, t=992] 
Attacking:  17%|█▋        | 83/500 [02:14<11:04,  1.59s/it, loss=2000.0000, t=992]
Attacking:  17%|█▋        | 83/500 [02:15<11:04,  1.59s/it, loss=2000.0000, t=992]
Attacking:  17%|█▋        | 84/500 [02:16<10:56,  1.58s/it, loss=2000.0000, t=992]
Attacking:  17%|█▋        | 84/500 [02:16<10:56,  1.58s/it, loss=2008.0000, t=1e+3]
Attacking:  17%|█▋        | 85/500 [02:17<10:53,  1.58s/it, loss=2008.0000, t=1e+3]
Attacking:  17%|█▋        | 85/500 [02:18<10:53,  1.58s/it, loss=2016.0000, t=1e+3]
Attacking:  17%|█▋        | 86/500 [02:19<10:56,  1.59s/it, loss=2016.0000, t=1e+3]
Attacking:  17%|█▋        | 86/500 [02:20<10:56,  1.59s/it, loss=1976.0000, t=984] 
Attacking:  17%|█▋        | 87/500 [02:20<10:56,  1.59s/it, loss=1976.0000, t=984]
Attacking:  17%|█▋        | 87/500 [02:21<10:56,  1.59s/it, loss=1936.0000, t=928]
Attacking:  18%|█▊        | 88/500 [02:22<11:05,  1.62s/it, loss=1936.0000, t=928]
Attacking:  18%|█▊        | 88/500 [02:23<11:05,  1.62s/it, loss=1936.0000, t=912]
Attacking:  18%|█▊        | 89/500 [02:24<10:55,  1.60s/it, loss=1936.0000, t=912]
Attacking:  18%|█▊        | 89/500 [02:24<10:55,  1.60s/it, loss=1936.0000, t=952]
Attacking:  18%|█▊        | 90/500 [02:25<10:51,  1.59s/it, loss=1936.0000, t=952]
Attacking:  18%|█▊        | 90/500 [02:26<10:51,  1.59s/it, loss=1968.0000, t=984]
Attacking:  18%|█▊        | 91/500 [02:27<10:38,  1.56s/it, loss=1968.0000, t=984]
Attacking:  18%|█▊        | 91/500 [02:27<10:38,  1.56s/it, loss=1936.0000, t=940]
Attacking:  18%|█▊        | 92/500 [02:28<10:36,  1.56s/it, loss=1936.0000, t=940]
Attacking:  18%|█▊        | 92/500 [02:29<10:36,  1.56s/it, loss=1936.0000, t=928]
Attacking:  19%|█▊        | 93/500 [02:30<10:47,  1.59s/it, loss=1936.0000, t=928]
Attacking:  19%|█▊        | 93/500 [02:31<10:47,  1.59s/it, loss=2016.0000, t=1e+3]
Attacking:  19%|█▉        | 94/500 [02:32<10:51,  1.60s/it, loss=2016.0000, t=1e+3]
Attacking:  19%|█▉        | 94/500 [02:32<10:51,  1.60s/it, loss=1928.0000, t=952] 
Attacking:  19%|█▉        | 95/500 [02:33<10:50,  1.60s/it, loss=1928.0000, t=952]
Attacking:  19%|█▉        | 95/500 [02:34<10:50,  1.60s/it, loss=1936.0000, t=940]
Attacking:  19%|█▉        | 96/500 [02:35<10:45,  1.60s/it, loss=1936.0000, t=940]
Attacking:  19%|█▉        | 96/500 [02:36<10:45,  1.60s/it, loss=1928.0000, t=912]
Attacking:  19%|█▉        | 97/500 [02:36<10:47,  1.61s/it, loss=1928.0000, t=912]
Attacking:  19%|█▉        | 97/500 [02:37<10:47,  1.61s/it, loss=1944.0000, t=972]
Attacking:  20%|█▉        | 98/500 [02:38<10:46,  1.61s/it, loss=1944.0000, t=972]
Attacking:  20%|█▉        | 98/500 [02:39<10:46,  1.61s/it, loss=1936.0000, t=952]
Attacking:  20%|█▉        | 99/500 [02:40<10:42,  1.60s/it, loss=1936.0000, t=952]
Attacking:  20%|█▉        | 99/500 [02:40<10:42,  1.60s/it, loss=1936.0000, t=972]
Attacking:  20%|██        | 100/500 [02:41<10:27,  1.57s/it, loss=1936.0000, t=972]
Attacking:  20%|██        | 100/500 [02:42<10:27,  1.57s/it, loss=2000.0000, t=1e+3]
Attacking:  20%|██        | 101/500 [02:43<10:25,  1.57s/it, loss=2000.0000, t=1e+3]
Attacking:  20%|██        | 101/500 [02:44<10:25,  1.57s/it, loss=1984.0000, t=992] 
Attacking:  20%|██        | 102/500 [02:44<10:36,  1.60s/it, loss=1984.0000, t=992]
Attacking:  20%|██        | 102/500 [02:45<10:36,  1.60s/it, loss=1992.0000, t=992]
Attacking:  21%|██        | 103/500 [02:46<10:26,  1.58s/it, loss=1992.0000, t=992]
Attacking:  21%|██        | 103/500 [02:47<10:26,  1.58s/it, loss=1960.0000, t=984]
Attacking:  21%|██        | 104/500 [02:48<10:28,  1.59s/it, loss=1960.0000, t=984]
Attacking:  21%|██        | 104/500 [02:48<10:28,  1.59s/it, loss=1952.0000, t=972]
Attacking:  21%|██        | 105/500 [02:49<10:22,  1.58s/it, loss=1952.0000, t=972]
Attacking:  21%|██        | 105/500 [02:50<10:22,  1.58s/it, loss=1920.0000, t=928]
Attacking:  21%|██        | 106/500 [02:51<10:14,  1.56s/it, loss=1920.0000, t=928]
Attacking:  21%|██        | 106/500 [02:51<10:14,  1.56s/it, loss=2000.0000, t=1e+3]
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+Max Diff: 0.501961
+Mean Diff: 0.240779
+Saved adversarial image to attacked/images/parkour.jpg
+Saved loss curve to attacked/loss_curve/parkour_loss.png
+[GPU 5] Stage 3/3: Test
+Loading models for testing parkour...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for parkour...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 41.62it/s]
+Saved video to attacked/videos/parkour.mp4
+Saved frames to attacked/frames/parkour
+[GPU 5] Finished parkour.jpg
+======================================
+[GPU 5] Processing picking.jpg (Image 36/50)
+======================================
+[GPU 5] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 5] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  18%|█▊        | 89/500 [02:17<10:05,  1.47s/it, loss=2208.0000, t=964]
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Attacking:  20%|██        | 100/500 [02:33<09:57,  1.49s/it, loss=2240.0000, t=992]
Attacking:  20%|██        | 100/500 [02:33<09:57,  1.49s/it, loss=2192.0000, t=972]
Attacking:  20%|██        | 101/500 [02:34<09:50,  1.48s/it, loss=2192.0000, t=972]
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Attacking:  20%|██        | 102/500 [02:36<09:42,  1.46s/it, loss=2208.0000, t=952]
Attacking:  20%|██        | 102/500 [02:36<09:42,  1.46s/it, loss=2176.0000, t=940]
Attacking:  21%|██        | 103/500 [02:37<09:43,  1.47s/it, loss=2176.0000, t=940]
Attacking:  21%|██        | 103/500 [02:38<09:43,  1.47s/it, loss=2192.0000, t=940]
Attacking:  21%|██        | 104/500 [02:38<09:33,  1.45s/it, loss=2192.0000, t=940]
Attacking:  21%|██        | 104/500 [02:39<09:33,  1.45s/it, loss=2176.0000, t=928]
Attacking:  21%|██        | 105/500 [02:40<09:37,  1.46s/it, loss=2176.0000, t=928]
Attacking:  21%|██        | 105/500 [02:41<09:37,  1.46s/it, loss=2192.0000, t=928]
Attacking:  21%|██        | 106/500 [02:41<09:37,  1.47s/it, loss=2192.0000, t=928]
Attacking:  21%|██        | 106/500 [02:42<09:37,  1.47s/it, loss=2192.0000, t=964]
Attacking:  21%|██▏       | 107/500 [02:43<09:38,  1.47s/it, loss=2192.0000, t=964]
Attacking:  21%|██▏       | 107/500 [02:44<09:38,  1.47s/it, loss=2192.0000, t=952]
Attacking:  22%|██▏       | 108/500 [02:45<09:57,  1.52s/it, loss=2192.0000, t=952]
Attacking:  22%|██▏       | 108/500 [02:45<09:57,  1.52s/it, loss=2176.0000, t=964]
Attacking:  22%|██▏       | 109/500 [02:46<10:06,  1.55s/it, loss=2176.0000, t=964]
Attacking:  22%|██▏       | 109/500 [02:47<10:06,  1.55s/it, loss=2176.0000, t=912]
Attacking:  22%|██▏       | 110/500 [02:48<09:55,  1.53s/it, loss=2176.0000, t=912]
Attacking:  22%|██▏       | 110/500 [02:48<09:55,  1.53s/it, loss=2208.0000, t=964]
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Attacking:  23%|██▎       | 113/500 [02:53<09:55,  1.54s/it, loss=2240.0000, t=992]
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Attacking:  23%|██▎       | 115/500 [02:56<10:16,  1.60s/it, loss=2192.0000, t=972]
Attacking:  23%|██▎       | 116/500 [02:57<10:22,  1.62s/it, loss=2192.0000, t=972]
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Attacking:  24%|██▍       | 121/500 [03:06<10:01,  1.59s/it, loss=2192.0000, t=984]
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Attacking:  24%|██▍       | 122/500 [03:07<10:12,  1.62s/it, loss=2176.0000, t=940]
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Attacking:  25%|██▍       | 123/500 [03:09<09:59,  1.59s/it, loss=2256.0000, t=1e+3]
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Attacking:  25%|██▌       | 125/500 [03:11<09:41,  1.55s/it, loss=2192.0000, t=984]
Attacking:  25%|██▌       | 125/500 [03:12<09:41,  1.55s/it, loss=2176.0000, t=940]
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Attacking:  25%|██▌       | 126/500 [03:14<09:24,  1.51s/it, loss=2256.0000, t=1e+3]
Attacking:  25%|██▌       | 127/500 [03:14<09:42,  1.56s/it, loss=2256.0000, t=1e+3]
Attacking:  25%|██▌       | 127/500 [03:15<09:42,  1.56s/it, loss=2176.0000, t=940] 
Attacking:  26%|██▌       | 128/500 [03:16<09:48,  1.58s/it, loss=2176.0000, t=940]
Attacking:  26%|██▌       | 128/500 [03:17<09:48,  1.58s/it, loss=2160.0000, t=900]
Attacking:  26%|██▌       | 129/500 [03:18<09:42,  1.57s/it, loss=2160.0000, t=900]
Attacking:  26%|██▌       | 129/500 [03:18<09:42,  1.57s/it, loss=2160.0000, t=912]
Attacking:  26%|██▌       | 130/500 [03:19<09:40,  1.57s/it, loss=2160.0000, t=912]
Attacking:  26%|██▌       | 130/500 [03:20<09:40,  1.57s/it, loss=2176.0000, t=952]
Attacking:  26%|██▌       | 131/500 [03:21<09:44,  1.58s/it, loss=2176.0000, t=952]
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Attacking:  27%|██▋       | 135/500 [03:27<09:09,  1.51s/it, loss=2240.0000, t=1e+3]
Attacking:  27%|██▋       | 136/500 [03:28<09:08,  1.51s/it, loss=2240.0000, t=1e+3]
Attacking:  27%|██▋       | 136/500 [03:29<09:08,  1.51s/it, loss=2160.0000, t=900] 
Attacking:  27%|██▋       | 137/500 [03:30<09:01,  1.49s/it, loss=2160.0000, t=900]
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Attacking:  28%|██▊       | 138/500 [03:32<08:58,  1.49s/it, loss=2240.0000, t=1e+3]
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Attacking:  29%|██▉       | 144/500 [03:41<09:00,  1.52s/it, loss=2208.0000, t=992]
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Attacking: 100%|██████████| 500/500 [12:54<00:00,  1.55s/it, loss=2128.0000, t=952]
+Max Diff: 0.501961
+Mean Diff: 0.208588
+Saved adversarial image to attacked/images/picking.jpg
+Saved loss curve to attacked/loss_curve/picking_loss.png
+[GPU 5] Stage 3/3: Test
+Loading models for testing picking...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for picking...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 40.95it/s]
+Saved video to attacked/videos/picking.mp4
+Saved frames to attacked/frames/picking
+[GPU 5] Finished picking.jpg
+======================================
+[GPU 5] Processing picnic.jpg (Image 37/50)
+======================================
+[GPU 5] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 5] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   3%|▎         | 16/500 [00:24<12:00,  1.49s/it, loss=2464.0000, t=972]
Attacking:   3%|▎         | 17/500 [00:25<11:44,  1.46s/it, loss=2464.0000, t=972]
Attacking:   3%|▎         | 17/500 [00:25<11:44,  1.46s/it, loss=2432.0000, t=928]
Attacking:   4%|▎         | 18/500 [00:26<11:44,  1.46s/it, loss=2432.0000, t=928]
Attacking:   4%|▎         | 18/500 [00:27<11:44,  1.46s/it, loss=2448.0000, t=952]
Attacking:   4%|▍         | 19/500 [00:28<11:47,  1.47s/it, loss=2448.0000, t=952]
Attacking:   4%|▍         | 19/500 [00:29<11:47,  1.47s/it, loss=2432.0000, t=940]
Attacking:   4%|▍         | 20/500 [00:29<12:11,  1.52s/it, loss=2432.0000, t=940]
Attacking:   4%|▍         | 20/500 [00:30<12:11,  1.52s/it, loss=2512.0000, t=984]
Attacking:   4%|▍         | 21/500 [00:31<12:40,  1.59s/it, loss=2512.0000, t=984]
Attacking:   4%|▍         | 21/500 [00:32<12:40,  1.59s/it, loss=2496.0000, t=1e+3]
Attacking:   4%|▍         | 22/500 [00:33<12:27,  1.56s/it, loss=2496.0000, t=1e+3]
Attacking:   4%|▍         | 22/500 [00:33<12:27,  1.56s/it, loss=2496.0000, t=1e+3]
Attacking:   5%|▍         | 23/500 [00:34<12:26,  1.57s/it, loss=2496.0000, t=1e+3]
Attacking:   5%|▍         | 23/500 [00:35<12:26,  1.57s/it, loss=2400.0000, t=900] 
Attacking:   5%|▍         | 24/500 [00:36<12:29,  1.57s/it, loss=2400.0000, t=900]
Attacking:   5%|▍         | 24/500 [00:36<12:29,  1.57s/it, loss=2496.0000, t=1e+3]
Attacking:   5%|▌         | 25/500 [00:37<12:12,  1.54s/it, loss=2496.0000, t=1e+3]
Attacking:   5%|▌         | 25/500 [00:38<12:12,  1.54s/it, loss=2416.0000, t=912] 
Attacking:   5%|▌         | 26/500 [00:39<12:02,  1.52s/it, loss=2416.0000, t=912]
Attacking:   5%|▌         | 26/500 [00:40<12:02,  1.52s/it, loss=2480.0000, t=984]
Attacking:   5%|▌         | 27/500 [00:40<12:19,  1.56s/it, loss=2480.0000, t=984]
Attacking:   5%|▌         | 27/500 [00:41<12:19,  1.56s/it, loss=2400.0000, t=940]
Attacking:   6%|▌         | 28/500 [00:42<12:34,  1.60s/it, loss=2400.0000, t=940]
Attacking:   6%|▌         | 28/500 [00:43<12:34,  1.60s/it, loss=2400.0000, t=952]
Attacking:   6%|▌         | 29/500 [00:44<12:19,  1.57s/it, loss=2400.0000, t=952]
Attacking:   6%|▌         | 29/500 [00:44<12:19,  1.57s/it, loss=2496.0000, t=1e+3]
Attacking:   6%|▌         | 30/500 [00:45<12:18,  1.57s/it, loss=2496.0000, t=1e+3]
Attacking:   6%|▌         | 30/500 [00:46<12:18,  1.57s/it, loss=2384.0000, t=912] 
Attacking:   6%|▌         | 31/500 [00:47<12:07,  1.55s/it, loss=2384.0000, t=912]
Attacking:   6%|▌         | 31/500 [00:48<12:07,  1.55s/it, loss=2480.0000, t=1e+3]
Attacking:   6%|▋         | 32/500 [00:48<12:25,  1.59s/it, loss=2480.0000, t=1e+3]
Attacking:   6%|▋         | 32/500 [00:49<12:25,  1.59s/it, loss=2400.0000, t=952] 
Attacking:   7%|▋         | 33/500 [00:50<12:27,  1.60s/it, loss=2400.0000, t=952]
Attacking:   7%|▋         | 33/500 [00:51<12:27,  1.60s/it, loss=2416.0000, t=964]
Attacking:   7%|▋         | 34/500 [00:52<12:28,  1.61s/it, loss=2416.0000, t=964]
Attacking:   7%|▋         | 34/500 [00:52<12:28,  1.61s/it, loss=2416.0000, t=972]
Attacking:   7%|▋         | 35/500 [00:53<12:28,  1.61s/it, loss=2416.0000, t=972]
Attacking:   7%|▋         | 35/500 [00:54<12:28,  1.61s/it, loss=2368.0000, t=900]
Attacking:   7%|▋         | 36/500 [00:55<12:29,  1.61s/it, loss=2368.0000, t=900]
Attacking:   7%|▋         | 36/500 [00:56<12:29,  1.61s/it, loss=2416.0000, t=972]
Attacking:   7%|▋         | 37/500 [00:57<12:27,  1.62s/it, loss=2416.0000, t=972]
Attacking:   7%|▋         | 37/500 [00:57<12:27,  1.62s/it, loss=2400.0000, t=940]
Attacking:   8%|▊         | 38/500 [00:58<12:32,  1.63s/it, loss=2400.0000, t=940]
Attacking:   8%|▊         | 38/500 [00:59<12:32,  1.63s/it, loss=2384.0000, t=952]
Attacking:   8%|▊         | 39/500 [01:00<12:16,  1.60s/it, loss=2384.0000, t=952]
Attacking:   8%|▊         | 39/500 [01:00<12:16,  1.60s/it, loss=2400.0000, t=972]
Attacking:   8%|▊         | 40/500 [01:01<11:55,  1.56s/it, loss=2400.0000, t=972]
Attacking:   8%|▊         | 40/500 [01:02<11:55,  1.56s/it, loss=2368.0000, t=940]
Attacking:   8%|▊         | 41/500 [01:03<11:42,  1.53s/it, loss=2368.0000, t=940]
Attacking:   8%|▊         | 41/500 [01:03<11:42,  1.53s/it, loss=2480.0000, t=992]
Attacking:   8%|▊         | 42/500 [01:04<11:41,  1.53s/it, loss=2480.0000, t=992]
Attacking:   8%|▊         | 42/500 [01:05<11:41,  1.53s/it, loss=2368.0000, t=952]
Attacking:   9%|▊         | 43/500 [01:06<11:40,  1.53s/it, loss=2368.0000, t=952]
Attacking:   9%|▊         | 43/500 [01:06<11:40,  1.53s/it, loss=2432.0000, t=984]
Attacking:   9%|▉         | 44/500 [01:07<11:24,  1.50s/it, loss=2432.0000, t=984]
Attacking:   9%|▉         | 44/500 [01:08<11:24,  1.50s/it, loss=2368.0000, t=952]
Attacking:   9%|▉         | 45/500 [01:09<11:24,  1.50s/it, loss=2368.0000, t=952]
Attacking:   9%|▉         | 45/500 [01:09<11:24,  1.50s/it, loss=2368.0000, t=928]
Attacking:   9%|▉         | 46/500 [01:10<11:25,  1.51s/it, loss=2368.0000, t=928]
Attacking:   9%|▉         | 46/500 [01:11<11:25,  1.51s/it, loss=2384.0000, t=972]
Attacking:   9%|▉         | 47/500 [01:12<11:14,  1.49s/it, loss=2384.0000, t=972]
Attacking:   9%|▉         | 47/500 [01:12<11:14,  1.49s/it, loss=2480.0000, t=1e+3]
Attacking:  10%|▉         | 48/500 [01:13<11:09,  1.48s/it, loss=2480.0000, t=1e+3]
Attacking:  10%|▉         | 48/500 [01:14<11:09,  1.48s/it, loss=2352.0000, t=912] 
Attacking:  10%|▉         | 49/500 [01:15<11:20,  1.51s/it, loss=2352.0000, t=912]
Attacking:  10%|▉         | 49/500 [01:15<11:20,  1.51s/it, loss=2368.0000, t=940]
Attacking:  10%|█         | 50/500 [01:16<11:11,  1.49s/it, loss=2368.0000, t=940]
Attacking:  10%|█         | 50/500 [01:17<11:11,  1.49s/it, loss=2352.0000, t=940]
Attacking:  10%|█         | 51/500 [01:18<11:25,  1.53s/it, loss=2352.0000, t=940]
Attacking:  10%|█         | 51/500 [01:18<11:25,  1.53s/it, loss=2336.0000, t=912]
Attacking:  10%|█         | 52/500 [01:19<11:29,  1.54s/it, loss=2336.0000, t=912]
Attacking:  10%|█         | 52/500 [01:20<11:29,  1.54s/it, loss=2464.0000, t=992]
Attacking:  11%|█         | 53/500 [01:21<11:25,  1.53s/it, loss=2464.0000, t=992]
Attacking:  11%|█         | 53/500 [01:21<11:25,  1.53s/it, loss=2400.0000, t=984]
Attacking:  11%|█         | 54/500 [01:22<11:15,  1.51s/it, loss=2400.0000, t=984]
Attacking:  11%|█         | 54/500 [01:23<11:15,  1.51s/it, loss=2336.0000, t=928]
Attacking:  11%|█         | 55/500 [01:24<11:08,  1.50s/it, loss=2336.0000, t=928]
Attacking:  11%|█         | 55/500 [01:24<11:08,  1.50s/it, loss=2352.0000, t=964]
Attacking:  11%|█         | 56/500 [01:25<11:22,  1.54s/it, loss=2352.0000, t=964]
Attacking:  11%|█         | 56/500 [01:26<11:22,  1.54s/it, loss=2320.0000, t=900]
Attacking:  11%|█▏        | 57/500 [01:27<11:21,  1.54s/it, loss=2320.0000, t=900]
Attacking:  11%|█▏        | 57/500 [01:28<11:21,  1.54s/it, loss=2368.0000, t=972]
Attacking:  12%|█▏        | 58/500 [01:28<11:18,  1.53s/it, loss=2368.0000, t=972]
Attacking:  12%|█▏        | 58/500 [01:29<11:18,  1.53s/it, loss=2384.0000, t=984]
Attacking:  12%|█▏        | 59/500 [01:30<12:02,  1.64s/it, loss=2384.0000, t=984]
Attacking:  12%|█▏        | 59/500 [01:31<12:02,  1.64s/it, loss=2352.0000, t=972]
Attacking:  12%|█▏        | 60/500 [01:32<11:37,  1.58s/it, loss=2352.0000, t=972]
Attacking:  12%|█▏        | 60/500 [01:32<11:37,  1.58s/it, loss=2352.0000, t=972]
Attacking:  12%|█▏        | 61/500 [01:33<11:24,  1.56s/it, loss=2352.0000, t=972]
Attacking:  12%|█▏        | 61/500 [01:34<11:24,  1.56s/it, loss=2432.0000, t=1e+3]
Attacking:  12%|█▏        | 62/500 [01:35<11:22,  1.56s/it, loss=2432.0000, t=1e+3]
Attacking:  12%|█▏        | 62/500 [01:35<11:22,  1.56s/it, loss=2320.0000, t=928] 
Attacking:  13%|█▎        | 63/500 [01:36<11:08,  1.53s/it, loss=2320.0000, t=928]
Attacking:  13%|█▎        | 63/500 [01:37<11:08,  1.53s/it, loss=2336.0000, t=952]
Attacking:  13%|█▎        | 64/500 [01:38<11:01,  1.52s/it, loss=2336.0000, t=952]
Attacking:  13%|█▎        | 64/500 [01:38<11:01,  1.52s/it, loss=2320.0000, t=952]
Attacking:  13%|█▎        | 65/500 [01:39<10:44,  1.48s/it, loss=2320.0000, t=952]
Attacking:  13%|█▎        | 65/500 [01:40<10:44,  1.48s/it, loss=2304.0000, t=912]
Attacking:  13%|█▎        | 66/500 [01:41<10:39,  1.47s/it, loss=2304.0000, t=912]
Attacking:  13%|█▎        | 66/500 [01:41<10:39,  1.47s/it, loss=2336.0000, t=964]
Attacking:  13%|█▎        | 67/500 [01:42<10:32,  1.46s/it, loss=2336.0000, t=964]
Attacking:  13%|█▎        | 67/500 [01:43<10:32,  1.46s/it, loss=2320.0000, t=952]
Attacking:  14%|█▎        | 68/500 [01:44<10:36,  1.47s/it, loss=2320.0000, t=952]
Attacking:  14%|█▎        | 68/500 [01:44<10:36,  1.47s/it, loss=2320.0000, t=964]
Attacking:  14%|█▍        | 69/500 [01:45<10:32,  1.47s/it, loss=2320.0000, t=964]
Attacking:  14%|█▍        | 69/500 [01:46<10:32,  1.47s/it, loss=2288.0000, t=900]
Attacking:  14%|█▍        | 70/500 [01:46<10:27,  1.46s/it, loss=2288.0000, t=900]
Attacking:  14%|█▍        | 70/500 [01:47<10:27,  1.46s/it, loss=2304.0000, t=952]
Attacking:  14%|█▍        | 71/500 [01:48<10:33,  1.48s/it, loss=2304.0000, t=952]
Attacking:  14%|█▍        | 71/500 [01:49<10:33,  1.48s/it, loss=2320.0000, t=952]
Attacking:  14%|█▍        | 72/500 [01:49<10:29,  1.47s/it, loss=2320.0000, t=952]
Attacking:  14%|█▍        | 72/500 [01:50<10:29,  1.47s/it, loss=2320.0000, t=940]
Attacking:  15%|█▍        | 73/500 [01:51<10:47,  1.52s/it, loss=2320.0000, t=940]
Attacking:  15%|█▍        | 73/500 [01:52<10:47,  1.52s/it, loss=2288.0000, t=900]
Attacking:  15%|█▍        | 74/500 [01:53<10:58,  1.55s/it, loss=2288.0000, t=900]
Attacking:  15%|█▍        | 74/500 [01:53<10:58,  1.55s/it, loss=2304.0000, t=940]
Attacking:  15%|█▌        | 75/500 [01:54<10:53,  1.54s/it, loss=2304.0000, t=940]
Attacking:  15%|█▌        | 75/500 [01:55<10:53,  1.54s/it, loss=2416.0000, t=1e+3]
Attacking:  15%|█▌        | 76/500 [01:56<10:40,  1.51s/it, loss=2416.0000, t=1e+3]
Attacking:  15%|█▌        | 76/500 [01:56<10:40,  1.51s/it, loss=2368.0000, t=984] 
Attacking:  15%|█▌        | 77/500 [01:57<10:48,  1.53s/it, loss=2368.0000, t=984]
Attacking:  15%|█▌        | 77/500 [01:58<10:48,  1.53s/it, loss=2400.0000, t=1e+3]
Attacking:  16%|█▌        | 78/500 [01:59<10:49,  1.54s/it, loss=2400.0000, t=1e+3]
Attacking:  16%|█▌        | 78/500 [01:59<10:49,  1.54s/it, loss=2320.0000, t=964] 
Attacking:  16%|█▌        | 79/500 [02:00<10:48,  1.54s/it, loss=2320.0000, t=964]
Attacking:  16%|█▌        | 79/500 [02:01<10:48,  1.54s/it, loss=2304.0000, t=952]
Attacking:  16%|█▌        | 80/500 [02:02<10:43,  1.53s/it, loss=2304.0000, t=952]
Attacking:  16%|█▌        | 80/500 [02:03<10:43,  1.53s/it, loss=2304.0000, t=952]
Attacking:  16%|█▌        | 81/500 [02:03<10:47,  1.55s/it, loss=2304.0000, t=952]
Attacking:  16%|█▌        | 81/500 [02:04<10:47,  1.55s/it, loss=2304.0000, t=964]
Attacking:  16%|█▋        | 82/500 [02:05<11:05,  1.59s/it, loss=2304.0000, t=964]
Attacking:  16%|█▋        | 82/500 [02:06<11:05,  1.59s/it, loss=2400.0000, t=992]
Attacking:  17%|█▋        | 83/500 [02:07<10:42,  1.54s/it, loss=2400.0000, t=992]
Attacking:  17%|█▋        | 83/500 [02:07<10:42,  1.54s/it, loss=2352.0000, t=984]
Attacking:  17%|█▋        | 84/500 [02:08<10:43,  1.55s/it, loss=2352.0000, t=984]
Attacking:  17%|█▋        | 84/500 [02:09<10:43,  1.55s/it, loss=2320.0000, t=964]
Attacking:  17%|█▋        | 85/500 [02:10<10:36,  1.53s/it, loss=2320.0000, t=964]
Attacking:  17%|█▋        | 85/500 [02:10<10:36,  1.53s/it, loss=2304.0000, t=972]
Attacking:  17%|█▋        | 86/500 [02:11<10:30,  1.52s/it, loss=2304.0000, t=972]
Attacking:  17%|█▋        | 86/500 [02:12<10:30,  1.52s/it, loss=2400.0000, t=992]
Attacking:  17%|█▋        | 87/500 [02:13<10:33,  1.53s/it, loss=2400.0000, t=992]
Attacking:  17%|█▋        | 87/500 [02:13<10:33,  1.53s/it, loss=2272.0000, t=912]
Attacking:  18%|█▊        | 88/500 [02:14<10:30,  1.53s/it, loss=2272.0000, t=912]
Attacking:  18%|█▊        | 88/500 [02:15<10:30,  1.53s/it, loss=2272.0000, t=900]
Attacking:  18%|█▊        | 89/500 [02:16<10:27,  1.53s/it, loss=2272.0000, t=900]
Attacking:  18%|█▊        | 89/500 [02:16<10:27,  1.53s/it, loss=2320.0000, t=972]
Attacking:  18%|█▊        | 90/500 [02:17<10:21,  1.51s/it, loss=2320.0000, t=972]
Attacking:  18%|█▊        | 90/500 [02:18<10:21,  1.51s/it, loss=2400.0000, t=992]
Attacking:  18%|█▊        | 91/500 [02:19<10:29,  1.54s/it, loss=2400.0000, t=992]
Attacking:  18%|█▊        | 91/500 [02:20<10:29,  1.54s/it, loss=2384.0000, t=992]
Attacking:  18%|█▊        | 92/500 [02:20<10:33,  1.55s/it, loss=2384.0000, t=992]
Attacking:  18%|█▊        | 92/500 [02:21<10:33,  1.55s/it, loss=2288.0000, t=912]
Attacking:  19%|█▊        | 93/500 [02:22<10:21,  1.53s/it, loss=2288.0000, t=912]
Attacking:  19%|█▊        | 93/500 [02:22<10:21,  1.53s/it, loss=2272.0000, t=900]
Attacking:  19%|█▉        | 94/500 [02:23<10:17,  1.52s/it, loss=2272.0000, t=900]
Attacking:  19%|█▉        | 94/500 [02:24<10:17,  1.52s/it, loss=2288.0000, t=928]
Attacking:  19%|█▉        | 95/500 [02:25<10:12,  1.51s/it, loss=2288.0000, t=928]
Attacking:  19%|█▉        | 95/500 [02:25<10:12,  1.51s/it, loss=2304.0000, t=972]
Attacking:  19%|█▉        | 96/500 [02:26<10:05,  1.50s/it, loss=2304.0000, t=972]
Attacking:  19%|█▉        | 96/500 [02:27<10:05,  1.50s/it, loss=2384.0000, t=1e+3]
Attacking:  19%|█▉        | 97/500 [02:28<09:51,  1.47s/it, loss=2384.0000, t=1e+3]
Attacking:  19%|█▉        | 97/500 [02:28<09:51,  1.47s/it, loss=2304.0000, t=940] 
Attacking:  20%|█▉        | 98/500 [02:29<09:54,  1.48s/it, loss=2304.0000, t=940]
Attacking:  20%|█▉        | 98/500 [02:30<09:54,  1.48s/it, loss=2384.0000, t=992]
Attacking:  20%|█▉        | 99/500 [02:31<10:03,  1.51s/it, loss=2384.0000, t=992]
Attacking:  20%|█▉        | 99/500 [02:31<10:03,  1.51s/it, loss=2384.0000, t=992]
Attacking:  20%|██        | 100/500 [02:32<10:10,  1.53s/it, loss=2384.0000, t=992]
Attacking:  20%|██        | 100/500 [02:33<10:10,  1.53s/it, loss=2288.0000, t=940]
Attacking:  20%|██        | 101/500 [02:34<10:09,  1.53s/it, loss=2288.0000, t=940]
Attacking:  20%|██        | 101/500 [02:35<10:09,  1.53s/it, loss=2336.0000, t=984]
Attacking:  20%|██        | 102/500 [02:35<10:04,  1.52s/it, loss=2336.0000, t=984]
Attacking:  20%|██        | 102/500 [02:36<10:04,  1.52s/it, loss=2304.0000, t=972]
Attacking:  21%|██        | 103/500 [02:37<09:58,  1.51s/it, loss=2304.0000, t=972]
Attacking:  21%|██        | 103/500 [02:38<09:58,  1.51s/it, loss=2272.0000, t=900]
Attacking:  21%|██        | 104/500 [02:38<10:12,  1.55s/it, loss=2272.0000, t=900]
Attacking:  21%|██        | 104/500 [02:39<10:12,  1.55s/it, loss=2288.0000, t=940]
Attacking:  21%|██        | 105/500 [02:40<10:06,  1.53s/it, loss=2288.0000, t=940]
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+Max Diff: 0.501961
+Mean Diff: 0.229133
+Saved adversarial image to attacked/images/picnic.jpg
+Saved loss curve to attacked/loss_curve/picnic_loss.png
+[GPU 5] Stage 3/3: Test
+Loading models for testing picnic...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for picnic...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 38.74it/s]
+Saved video to attacked/videos/picnic.mp4
+Saved frames to attacked/frames/picnic
+[GPU 5] Finished picnic.jpg
+======================================
+[GPU 5] Processing rhino.jpg (Image 38/50)
+======================================
+[GPU 5] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 5] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  20%|██        | 100/500 [02:33<09:58,  1.50s/it, loss=2272.0000, t=952]
Attacking:  20%|██        | 100/500 [02:34<09:58,  1.50s/it, loss=2256.0000, t=940]
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Attacking:  21%|██        | 103/500 [02:38<09:55,  1.50s/it, loss=2240.0000, t=940]
Attacking:  21%|██        | 103/500 [02:38<09:55,  1.50s/it, loss=2288.0000, t=1e+3]
Attacking:  21%|██        | 104/500 [02:39<09:51,  1.49s/it, loss=2288.0000, t=1e+3]
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Attacking:  21%|██        | 106/500 [02:42<09:49,  1.50s/it, loss=2240.0000, t=972]
Attacking:  21%|██        | 106/500 [02:43<09:49,  1.50s/it, loss=2256.0000, t=952]
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Attacking:  22%|██▏       | 110/500 [02:48<09:37,  1.48s/it, loss=2240.0000, t=940]
Attacking:  22%|██▏       | 110/500 [02:49<09:37,  1.48s/it, loss=2272.0000, t=1e+3]
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Attacking:  24%|██▍       | 120/500 [03:05<10:15,  1.62s/it, loss=2240.0000, t=912]
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Attacking:  24%|██▍       | 121/500 [03:06<10:07,  1.60s/it, loss=2272.0000, t=1e+3]
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Attacking:  25%|██▌       | 127/500 [03:16<09:50,  1.58s/it, loss=2224.0000, t=900]
Attacking:  26%|██▌       | 128/500 [03:17<09:49,  1.59s/it, loss=2224.0000, t=900]
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Attacking:  26%|██▌       | 130/500 [03:20<09:42,  1.57s/it, loss=2272.0000, t=1e+3]
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Attacking:  90%|████████▉ | 449/500 [11:31<01:21,  1.59s/it, loss=2208.0000, t=1e+3]
Attacking:  90%|████████▉ | 449/500 [11:32<01:21,  1.59s/it, loss=2208.0000, t=992] 
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Attacking:  97%|█████████▋| 486/500 [12:29<00:23,  1.64s/it, loss=2208.0000, t=1e+3]
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+Max Diff: 0.501961
+Mean Diff: 0.242558
+Saved adversarial image to attacked/images/rhino.jpg
+Saved loss curve to attacked/loss_curve/rhino_loss.png
+[GPU 5] Stage 3/3: Test
+Loading models for testing rhino...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for rhino...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 40.88it/s]
+Saved video to attacked/videos/rhino.mp4
+Saved frames to attacked/frames/rhino
+[GPU 5] Finished rhino.jpg
+======================================
+[GPU 5] Processing rollerblade.jpg (Image 39/50)
+======================================
+[GPU 5] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 5] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   3%|▎         | 16/500 [00:25<13:42,  1.70s/it, loss=2288.0000, t=1e+3]
Attacking:   3%|▎         | 16/500 [00:25<13:42,  1.70s/it, loss=2272.0000, t=972] 
Attacking:   3%|▎         | 17/500 [00:26<13:28,  1.67s/it, loss=2272.0000, t=972]
Attacking:   3%|▎         | 17/500 [00:27<13:28,  1.67s/it, loss=2240.0000, t=940]
Attacking:   4%|▎         | 18/500 [00:28<13:20,  1.66s/it, loss=2240.0000, t=940]
Attacking:   4%|▎         | 18/500 [00:29<13:20,  1.66s/it, loss=2224.0000, t=928]
Attacking:   4%|▍         | 19/500 [00:29<12:54,  1.61s/it, loss=2224.0000, t=928]
Attacking:   4%|▍         | 19/500 [00:30<12:54,  1.61s/it, loss=2256.0000, t=972]
Attacking:   4%|▍         | 20/500 [00:31<12:44,  1.59s/it, loss=2256.0000, t=972]
Attacking:   4%|▍         | 20/500 [00:32<12:44,  1.59s/it, loss=2272.0000, t=972]
Attacking:   4%|▍         | 21/500 [00:33<12:45,  1.60s/it, loss=2272.0000, t=972]
Attacking:   4%|▍         | 21/500 [00:33<12:45,  1.60s/it, loss=2192.0000, t=900]
Attacking:   4%|▍         | 22/500 [00:34<12:43,  1.60s/it, loss=2192.0000, t=900]
Attacking:   4%|▍         | 22/500 [00:35<12:43,  1.60s/it, loss=2208.0000, t=900]
Attacking:   5%|▍         | 23/500 [00:36<12:37,  1.59s/it, loss=2208.0000, t=900]
Attacking:   5%|▍         | 23/500 [00:36<12:37,  1.59s/it, loss=2176.0000, t=900]
Attacking:   5%|▍         | 24/500 [00:37<12:34,  1.58s/it, loss=2176.0000, t=900]
Attacking:   5%|▍         | 24/500 [00:38<12:34,  1.58s/it, loss=2224.0000, t=952]
Attacking:   5%|▌         | 25/500 [00:39<12:32,  1.58s/it, loss=2224.0000, t=952]
Attacking:   5%|▌         | 25/500 [00:40<12:32,  1.58s/it, loss=2240.0000, t=964]
Attacking:   5%|▌         | 26/500 [00:40<12:24,  1.57s/it, loss=2240.0000, t=964]
Attacking:   5%|▌         | 26/500 [00:41<12:24,  1.57s/it, loss=2192.0000, t=912]
Attacking:   5%|▌         | 27/500 [00:42<12:07,  1.54s/it, loss=2192.0000, t=912]
Attacking:   5%|▌         | 27/500 [00:43<12:07,  1.54s/it, loss=2272.0000, t=992]
Attacking:   6%|▌         | 28/500 [00:43<11:57,  1.52s/it, loss=2272.0000, t=992]
Attacking:   6%|▌         | 28/500 [00:44<11:57,  1.52s/it, loss=2208.0000, t=952]
Attacking:   6%|▌         | 29/500 [00:45<12:01,  1.53s/it, loss=2208.0000, t=952]
Attacking:   6%|▌         | 29/500 [00:46<12:01,  1.53s/it, loss=2224.0000, t=964]
Attacking:   6%|▌         | 30/500 [00:46<11:58,  1.53s/it, loss=2224.0000, t=964]
Attacking:   6%|▌         | 30/500 [00:47<11:58,  1.53s/it, loss=2224.0000, t=964]
Attacking:   6%|▌         | 31/500 [00:48<11:47,  1.51s/it, loss=2224.0000, t=964]
Attacking:   6%|▌         | 31/500 [00:49<11:47,  1.51s/it, loss=2176.0000, t=928]
Attacking:   6%|▋         | 32/500 [00:49<11:42,  1.50s/it, loss=2176.0000, t=928]
Attacking:   6%|▋         | 32/500 [00:50<11:42,  1.50s/it, loss=2256.0000, t=992]
Attacking:   7%|▋         | 33/500 [00:51<11:42,  1.50s/it, loss=2256.0000, t=992]
Attacking:   7%|▋         | 33/500 [00:52<11:42,  1.50s/it, loss=2256.0000, t=1e+3]
Attacking:   7%|▋         | 34/500 [00:52<11:36,  1.50s/it, loss=2256.0000, t=1e+3]
Attacking:   7%|▋         | 34/500 [00:53<11:36,  1.50s/it, loss=2176.0000, t=940] 
Attacking:   7%|▋         | 35/500 [00:54<11:31,  1.49s/it, loss=2176.0000, t=940]
Attacking:   7%|▋         | 35/500 [00:54<11:31,  1.49s/it, loss=2192.0000, t=952]
Attacking:   7%|▋         | 36/500 [00:55<11:28,  1.48s/it, loss=2192.0000, t=952]
Attacking:   7%|▋         | 36/500 [00:56<11:28,  1.48s/it, loss=2176.0000, t=912]
Attacking:   7%|▋         | 37/500 [00:57<11:21,  1.47s/it, loss=2176.0000, t=912]
Attacking:   7%|▋         | 37/500 [00:57<11:21,  1.47s/it, loss=2240.0000, t=992]
Attacking:   8%|▊         | 38/500 [00:58<11:35,  1.51s/it, loss=2240.0000, t=992]
Attacking:   8%|▊         | 38/500 [00:59<11:35,  1.51s/it, loss=2176.0000, t=928]
Attacking:   8%|▊         | 39/500 [01:00<11:35,  1.51s/it, loss=2176.0000, t=928]
Attacking:   8%|▊         | 39/500 [01:01<11:35,  1.51s/it, loss=2240.0000, t=992]
Attacking:   8%|▊         | 40/500 [01:01<11:43,  1.53s/it, loss=2240.0000, t=992]
Attacking:   8%|▊         | 40/500 [01:02<11:43,  1.53s/it, loss=2160.0000, t=928]
Attacking:   8%|▊         | 41/500 [01:03<11:38,  1.52s/it, loss=2160.0000, t=928]
Attacking:   8%|▊         | 41/500 [01:04<11:38,  1.52s/it, loss=2176.0000, t=940]
Attacking:   8%|▊         | 42/500 [01:04<11:41,  1.53s/it, loss=2176.0000, t=940]
Attacking:   8%|▊         | 42/500 [01:05<11:41,  1.53s/it, loss=2208.0000, t=984]
Attacking:   9%|▊         | 43/500 [01:06<11:54,  1.56s/it, loss=2208.0000, t=984]
Attacking:   9%|▊         | 43/500 [01:07<11:54,  1.56s/it, loss=2160.0000, t=928]
Attacking:   9%|▉         | 44/500 [01:08<11:51,  1.56s/it, loss=2160.0000, t=928]
Attacking:   9%|▉         | 44/500 [01:08<11:51,  1.56s/it, loss=2144.0000, t=900]
Attacking:   9%|▉         | 45/500 [01:09<11:59,  1.58s/it, loss=2144.0000, t=900]
Attacking:   9%|▉         | 45/500 [01:10<11:59,  1.58s/it, loss=2144.0000, t=900]
Attacking:   9%|▉         | 46/500 [01:11<11:50,  1.57s/it, loss=2144.0000, t=900]
Attacking:   9%|▉         | 46/500 [01:11<11:50,  1.57s/it, loss=2192.0000, t=964]
Attacking:   9%|▉         | 47/500 [01:12<11:34,  1.53s/it, loss=2192.0000, t=964]
Attacking:   9%|▉         | 47/500 [01:13<11:34,  1.53s/it, loss=2208.0000, t=972]
Attacking:  10%|▉         | 48/500 [01:14<11:25,  1.52s/it, loss=2208.0000, t=972]
Attacking:  10%|▉         | 48/500 [01:14<11:25,  1.52s/it, loss=2224.0000, t=992]
Attacking:  10%|▉         | 49/500 [01:15<11:22,  1.51s/it, loss=2224.0000, t=992]
Attacking:  10%|▉         | 49/500 [01:16<11:22,  1.51s/it, loss=2176.0000, t=940]
Attacking:  10%|█         | 50/500 [01:17<11:30,  1.53s/it, loss=2176.0000, t=940]
Attacking:  10%|█         | 50/500 [01:18<11:30,  1.53s/it, loss=2160.0000, t=940]
Attacking:  10%|█         | 51/500 [01:18<11:36,  1.55s/it, loss=2160.0000, t=940]
Attacking:  10%|█         | 51/500 [01:19<11:36,  1.55s/it, loss=2208.0000, t=992]
Attacking:  10%|█         | 52/500 [01:20<11:24,  1.53s/it, loss=2208.0000, t=992]
Attacking:  10%|█         | 52/500 [01:21<11:24,  1.53s/it, loss=2160.0000, t=952]
Attacking:  11%|█         | 53/500 [01:21<11:30,  1.54s/it, loss=2160.0000, t=952]
Attacking:  11%|█         | 53/500 [01:22<11:30,  1.54s/it, loss=2144.0000, t=928]
Attacking:  11%|█         | 54/500 [01:23<11:19,  1.52s/it, loss=2144.0000, t=928]
Attacking:  11%|█         | 54/500 [01:24<11:19,  1.52s/it, loss=2144.0000, t=928]
Attacking:  11%|█         | 55/500 [01:24<11:14,  1.52s/it, loss=2144.0000, t=928]
Attacking:  11%|█         | 55/500 [01:25<11:14,  1.52s/it, loss=2128.0000, t=900]
Attacking:  11%|█         | 56/500 [01:26<11:17,  1.53s/it, loss=2128.0000, t=900]
Attacking:  11%|█         | 56/500 [01:27<11:17,  1.53s/it, loss=2208.0000, t=984]
Attacking:  11%|█▏        | 57/500 [01:28<11:13,  1.52s/it, loss=2208.0000, t=984]
Attacking:  11%|█▏        | 57/500 [01:28<11:13,  1.52s/it, loss=2208.0000, t=1e+3]
Attacking:  12%|█▏        | 58/500 [01:29<11:04,  1.50s/it, loss=2208.0000, t=1e+3]
Attacking:  12%|█▏        | 58/500 [01:30<11:04,  1.50s/it, loss=2192.0000, t=1e+3]
Attacking:  12%|█▏        | 59/500 [01:31<11:12,  1.52s/it, loss=2192.0000, t=1e+3]
Attacking:  12%|█▏        | 59/500 [01:31<11:12,  1.52s/it, loss=2192.0000, t=984] 
Attacking:  12%|█▏        | 60/500 [01:32<11:05,  1.51s/it, loss=2192.0000, t=984]
Attacking:  12%|█▏        | 60/500 [01:33<11:05,  1.51s/it, loss=2192.0000, t=984]
Attacking:  12%|█▏        | 61/500 [01:33<10:53,  1.49s/it, loss=2192.0000, t=984]
Attacking:  12%|█▏        | 61/500 [01:34<10:53,  1.49s/it, loss=2208.0000, t=984]
Attacking:  12%|█▏        | 62/500 [01:35<10:41,  1.46s/it, loss=2208.0000, t=984]
Attacking:  12%|█▏        | 62/500 [01:36<10:41,  1.46s/it, loss=2208.0000, t=1e+3]
Attacking:  13%|█▎        | 63/500 [01:36<10:47,  1.48s/it, loss=2208.0000, t=1e+3]
Attacking:  13%|█▎        | 63/500 [01:37<10:47,  1.48s/it, loss=2176.0000, t=972] 
Attacking:  13%|█▎        | 64/500 [01:38<10:55,  1.50s/it, loss=2176.0000, t=972]
Attacking:  13%|█▎        | 64/500 [01:39<10:55,  1.50s/it, loss=2160.0000, t=964]
Attacking:  13%|█▎        | 65/500 [01:40<11:01,  1.52s/it, loss=2160.0000, t=964]
Attacking:  13%|█▎        | 65/500 [01:40<11:01,  1.52s/it, loss=2192.0000, t=992]
Attacking:  13%|█▎        | 66/500 [01:41<10:57,  1.52s/it, loss=2192.0000, t=992]
Attacking:  13%|█▎        | 66/500 [01:42<10:57,  1.52s/it, loss=2176.0000, t=984]
Attacking:  13%|█▎        | 67/500 [01:43<10:55,  1.51s/it, loss=2176.0000, t=984]
Attacking:  13%|█▎        | 67/500 [01:43<10:55,  1.51s/it, loss=2176.0000, t=1e+3]
Attacking:  14%|█▎        | 68/500 [01:44<11:17,  1.57s/it, loss=2176.0000, t=1e+3]
Attacking:  14%|█▎        | 68/500 [01:45<11:17,  1.57s/it, loss=2128.0000, t=940] 
Attacking:  14%|█▍        | 69/500 [01:46<11:20,  1.58s/it, loss=2128.0000, t=940]
Attacking:  14%|█▍        | 69/500 [01:47<11:20,  1.58s/it, loss=2160.0000, t=964]
Attacking:  14%|█▍        | 70/500 [01:47<11:10,  1.56s/it, loss=2160.0000, t=964]
Attacking:  14%|█▍        | 70/500 [01:48<11:10,  1.56s/it, loss=2176.0000, t=984]
Attacking:  14%|█▍        | 71/500 [01:49<11:15,  1.57s/it, loss=2176.0000, t=984]
Attacking:  14%|█▍        | 71/500 [01:50<11:15,  1.57s/it, loss=2112.0000, t=912]
Attacking:  14%|█▍        | 72/500 [01:51<11:21,  1.59s/it, loss=2112.0000, t=912]
Attacking:  14%|█▍        | 72/500 [01:51<11:21,  1.59s/it, loss=2128.0000, t=940]
Attacking:  15%|█▍        | 73/500 [01:52<11:14,  1.58s/it, loss=2128.0000, t=940]
Attacking:  15%|█▍        | 73/500 [01:53<11:14,  1.58s/it, loss=2128.0000, t=952]
Attacking:  15%|█▍        | 74/500 [01:54<11:04,  1.56s/it, loss=2128.0000, t=952]
Attacking:  15%|█▍        | 74/500 [01:54<11:04,  1.56s/it, loss=2176.0000, t=1e+3]
Attacking:  15%|█▌        | 75/500 [01:55<10:52,  1.54s/it, loss=2176.0000, t=1e+3]
Attacking:  15%|█▌        | 75/500 [01:56<10:52,  1.54s/it, loss=2176.0000, t=972] 
Attacking:  15%|█▌        | 76/500 [01:57<10:36,  1.50s/it, loss=2176.0000, t=972]
Attacking:  15%|█▌        | 76/500 [01:57<10:36,  1.50s/it, loss=2096.0000, t=912]
Attacking:  15%|█▌        | 77/500 [01:58<10:28,  1.49s/it, loss=2096.0000, t=912]
Attacking:  15%|█▌        | 77/500 [01:59<10:28,  1.49s/it, loss=2176.0000, t=992]
Attacking:  16%|█▌        | 78/500 [01:59<10:23,  1.48s/it, loss=2176.0000, t=992]
Attacking:  16%|█▌        | 78/500 [02:00<10:23,  1.48s/it, loss=2160.0000, t=984]
Attacking:  16%|█▌        | 79/500 [02:01<10:37,  1.51s/it, loss=2160.0000, t=984]
Attacking:  16%|█▌        | 79/500 [02:02<10:37,  1.51s/it, loss=2160.0000, t=984]
Attacking:  16%|█▌        | 80/500 [02:03<10:49,  1.55s/it, loss=2160.0000, t=984]
Attacking:  16%|█▌        | 80/500 [02:03<10:49,  1.55s/it, loss=2096.0000, t=928]
Attacking:  16%|█▌        | 81/500 [02:04<10:45,  1.54s/it, loss=2096.0000, t=928]
Attacking:  16%|█▌        | 81/500 [02:05<10:45,  1.54s/it, loss=2096.0000, t=912]
Attacking:  16%|█▋        | 82/500 [02:06<10:54,  1.57s/it, loss=2096.0000, t=912]
Attacking:  16%|█▋        | 82/500 [02:07<10:54,  1.57s/it, loss=2176.0000, t=1e+3]
Attacking:  17%|█▋        | 83/500 [02:07<10:59,  1.58s/it, loss=2176.0000, t=1e+3]
Attacking:  17%|█▋        | 83/500 [02:08<10:59,  1.58s/it, loss=2080.0000, t=900] 
Attacking:  17%|█▋        | 84/500 [02:09<10:46,  1.55s/it, loss=2080.0000, t=900]
Attacking:  17%|█▋        | 84/500 [02:10<10:46,  1.55s/it, loss=2112.0000, t=940]
Attacking:  17%|█▋        | 85/500 [02:11<10:46,  1.56s/it, loss=2112.0000, t=940]
Attacking:  17%|█▋        | 85/500 [02:11<10:46,  1.56s/it, loss=2176.0000, t=972]
Attacking:  17%|█▋        | 86/500 [02:12<10:28,  1.52s/it, loss=2176.0000, t=972]
Attacking:  17%|█▋        | 86/500 [02:13<10:28,  1.52s/it, loss=2144.0000, t=964]
Attacking:  17%|█▋        | 87/500 [02:13<10:21,  1.50s/it, loss=2144.0000, t=964]
Attacking:  17%|█▋        | 87/500 [02:14<10:21,  1.50s/it, loss=2112.0000, t=940]
Attacking:  18%|█▊        | 88/500 [02:15<10:27,  1.52s/it, loss=2112.0000, t=940]
Attacking:  18%|█▊        | 88/500 [02:16<10:27,  1.52s/it, loss=2176.0000, t=1e+3]
Attacking:  18%|█▊        | 89/500 [02:17<10:35,  1.55s/it, loss=2176.0000, t=1e+3]
Attacking:  18%|█▊        | 89/500 [02:17<10:35,  1.55s/it, loss=2112.0000, t=940] 
Attacking:  18%|█▊        | 90/500 [02:18<10:31,  1.54s/it, loss=2112.0000, t=940]
Attacking:  18%|█▊        | 90/500 [02:19<10:31,  1.54s/it, loss=2080.0000, t=900]
Attacking:  18%|█▊        | 91/500 [02:20<10:28,  1.54s/it, loss=2080.0000, t=900]
Attacking:  18%|█▊        | 91/500 [02:20<10:28,  1.54s/it, loss=2144.0000, t=984]
Attacking:  18%|█▊        | 92/500 [02:21<10:22,  1.53s/it, loss=2144.0000, t=984]
Attacking:  18%|█▊        | 92/500 [02:22<10:22,  1.53s/it, loss=2160.0000, t=984]
Attacking:  19%|█▊        | 93/500 [02:23<10:14,  1.51s/it, loss=2160.0000, t=984]
Attacking:  19%|█▊        | 93/500 [02:23<10:14,  1.51s/it, loss=2112.0000, t=952]
Attacking:  19%|█▉        | 94/500 [02:24<10:13,  1.51s/it, loss=2112.0000, t=952]
Attacking:  19%|█▉        | 94/500 [02:25<10:13,  1.51s/it, loss=2176.0000, t=1e+3]
Attacking:  19%|█▉        | 95/500 [02:26<10:07,  1.50s/it, loss=2176.0000, t=1e+3]
Attacking:  19%|█▉        | 95/500 [02:26<10:07,  1.50s/it, loss=2160.0000, t=1e+3]
Attacking:  19%|█▉        | 96/500 [02:27<10:16,  1.53s/it, loss=2160.0000, t=1e+3]
Attacking:  19%|█▉        | 96/500 [02:28<10:16,  1.53s/it, loss=2160.0000, t=992] 
Attacking:  19%|█▉        | 97/500 [02:29<10:15,  1.53s/it, loss=2160.0000, t=992]
Attacking:  19%|█▉        | 97/500 [02:29<10:15,  1.53s/it, loss=2080.0000, t=912]
Attacking:  20%|█▉        | 98/500 [02:30<10:06,  1.51s/it, loss=2080.0000, t=912]
Attacking:  20%|█▉        | 98/500 [02:31<10:06,  1.51s/it, loss=2112.0000, t=952]
Attacking:  20%|█▉        | 99/500 [02:32<10:10,  1.52s/it, loss=2112.0000, t=952]
Attacking:  20%|█▉        | 99/500 [02:32<10:10,  1.52s/it, loss=2160.0000, t=1e+3]
Attacking:  20%|██        | 100/500 [02:33<10:06,  1.52s/it, loss=2160.0000, t=1e+3]
Attacking:  20%|██        | 100/500 [02:34<10:06,  1.52s/it, loss=2096.0000, t=928] 
Attacking:  20%|██        | 101/500 [02:35<10:00,  1.51s/it, loss=2096.0000, t=928]
Attacking:  20%|██        | 101/500 [02:35<10:00,  1.51s/it, loss=2144.0000, t=984]
Attacking:  20%|██        | 102/500 [02:36<09:54,  1.49s/it, loss=2144.0000, t=984]
Attacking:  20%|██        | 102/500 [02:37<09:54,  1.49s/it, loss=2144.0000, t=1e+3]
Attacking:  21%|██        | 103/500 [02:38<09:51,  1.49s/it, loss=2144.0000, t=1e+3]
Attacking:  21%|██        | 103/500 [02:38<09:51,  1.49s/it, loss=2128.0000, t=964] 
Attacking:  21%|██        | 104/500 [02:39<09:42,  1.47s/it, loss=2128.0000, t=964]
Attacking:  21%|██        | 104/500 [02:40<09:42,  1.47s/it, loss=2096.0000, t=952]
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Attacking: 100%|██████████| 500/500 [12:50<00:00,  1.54s/it, loss=2048.0000, t=964]
+Max Diff: 0.501961
+Mean Diff: 0.244730
+Saved adversarial image to attacked/images/rollerblade.jpg
+Saved loss curve to attacked/loss_curve/rollerblade_loss.png
+[GPU 5] Stage 3/3: Test
+Loading models for testing rollerblade...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for rollerblade...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 45.68it/s]
+Saved video to attacked/videos/rollerblade.mp4
+Saved frames to attacked/frames/rollerblade
+[GPU 5] Finished rollerblade.jpg
+======================================
+[GPU 5] Processing scooter-black.jpg (Image 40/50)
+======================================
+[GPU 5] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 5] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  13%|█▎        | 64/500 [01:40<11:12,  1.54s/it, loss=2304.0000, t=972]
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Attacking:  14%|█▎        | 68/500 [01:46<11:12,  1.56s/it, loss=2272.0000, t=964]
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Attacking:  15%|█▌        | 75/500 [01:56<10:26,  1.47s/it, loss=2288.0000, t=1e+3]
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Attacking:  15%|█▌        | 77/500 [01:59<10:22,  1.47s/it, loss=2224.0000, t=928]
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Attacking:  17%|█▋        | 84/500 [02:10<10:50,  1.56s/it, loss=2304.0000, t=1e+3]
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Attacking:  20%|██        | 100/500 [02:34<10:26,  1.57s/it, loss=2288.0000, t=984]
Attacking:  20%|██        | 100/500 [02:35<10:26,  1.57s/it, loss=2272.0000, t=1e+3]
Attacking:  20%|██        | 101/500 [02:36<10:20,  1.56s/it, loss=2272.0000, t=1e+3]
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Attacking:  20%|██        | 102/500 [02:37<10:23,  1.57s/it, loss=2256.0000, t=964]
Attacking:  20%|██        | 102/500 [02:38<10:23,  1.57s/it, loss=2208.0000, t=912]
Attacking:  21%|██        | 103/500 [02:39<10:09,  1.53s/it, loss=2208.0000, t=912]
Attacking:  21%|██        | 103/500 [02:39<10:09,  1.53s/it, loss=2272.0000, t=984]
Attacking:  21%|██        | 104/500 [02:40<10:02,  1.52s/it, loss=2272.0000, t=984]
Attacking:  21%|██        | 104/500 [02:41<10:02,  1.52s/it, loss=2240.0000, t=972]
Attacking:  21%|██        | 105/500 [02:42<09:54,  1.50s/it, loss=2240.0000, t=972]
Attacking:  21%|██        | 105/500 [02:42<09:54,  1.50s/it, loss=2224.0000, t=940]
Attacking:  21%|██        | 106/500 [02:43<09:45,  1.49s/it, loss=2224.0000, t=940]
Attacking:  21%|██        | 106/500 [02:44<09:45,  1.49s/it, loss=2208.0000, t=928]
Attacking:  21%|██▏       | 107/500 [02:45<09:55,  1.52s/it, loss=2208.0000, t=928]
Attacking:  21%|██▏       | 107/500 [02:45<09:55,  1.52s/it, loss=2240.0000, t=952]
Attacking:  22%|██▏       | 108/500 [02:46<10:04,  1.54s/it, loss=2240.0000, t=952]
Attacking:  22%|██▏       | 108/500 [02:47<10:04,  1.54s/it, loss=2288.0000, t=992]
Attacking:  22%|██▏       | 109/500 [02:48<09:58,  1.53s/it, loss=2288.0000, t=992]
Attacking:  22%|██▏       | 109/500 [02:49<09:58,  1.53s/it, loss=2256.0000, t=1e+3]
Attacking:  22%|██▏       | 110/500 [02:49<10:10,  1.56s/it, loss=2256.0000, t=1e+3]
Attacking:  22%|██▏       | 110/500 [02:50<10:10,  1.56s/it, loss=2224.0000, t=952] 
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Attacking:  22%|██▏       | 111/500 [02:52<10:00,  1.54s/it, loss=2192.0000, t=912]
Attacking:  22%|██▏       | 112/500 [02:52<10:01,  1.55s/it, loss=2192.0000, t=912]
Attacking:  22%|██▏       | 112/500 [02:53<10:01,  1.55s/it, loss=2304.0000, t=992]
Attacking:  23%|██▎       | 113/500 [02:54<09:58,  1.55s/it, loss=2304.0000, t=992]
Attacking:  23%|██▎       | 113/500 [02:55<09:58,  1.55s/it, loss=2192.0000, t=928]
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Attacking:  23%|██▎       | 114/500 [02:56<10:00,  1.56s/it, loss=2224.0000, t=964]
Attacking:  23%|██▎       | 115/500 [02:57<09:53,  1.54s/it, loss=2224.0000, t=964]
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Attacking:  24%|██▍       | 119/500 [03:03<09:56,  1.56s/it, loss=2240.0000, t=972]
Attacking:  24%|██▍       | 119/500 [03:04<09:56,  1.56s/it, loss=2272.0000, t=992]
Attacking:  24%|██▍       | 120/500 [03:05<10:13,  1.62s/it, loss=2272.0000, t=992]
Attacking:  24%|██▍       | 120/500 [03:06<10:13,  1.62s/it, loss=2176.0000, t=900]
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Attacking:  25%|██▍       | 123/500 [03:09<09:29,  1.51s/it, loss=2208.0000, t=940]
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Attacking:  25%|██▍       | 124/500 [03:11<09:20,  1.49s/it, loss=2176.0000, t=900]
Attacking:  25%|██▍       | 124/500 [03:11<09:20,  1.49s/it, loss=2272.0000, t=1e+3]
Attacking:  25%|██▌       | 125/500 [03:12<09:12,  1.47s/it, loss=2272.0000, t=1e+3]
Attacking:  25%|██▌       | 125/500 [03:13<09:12,  1.47s/it, loss=2176.0000, t=900] 
Attacking:  25%|██▌       | 126/500 [03:14<09:12,  1.48s/it, loss=2176.0000, t=900]
Attacking:  25%|██▌       | 126/500 [03:14<09:12,  1.48s/it, loss=2272.0000, t=984]
Attacking:  25%|██▌       | 127/500 [03:15<09:14,  1.49s/it, loss=2272.0000, t=984]
Attacking:  25%|██▌       | 127/500 [03:16<09:14,  1.49s/it, loss=2176.0000, t=912]
Attacking:  26%|██▌       | 128/500 [03:17<09:25,  1.52s/it, loss=2176.0000, t=912]
Attacking:  26%|██▌       | 128/500 [03:18<09:25,  1.52s/it, loss=2288.0000, t=992]
Attacking:  26%|██▌       | 129/500 [03:18<09:24,  1.52s/it, loss=2288.0000, t=992]
Attacking:  26%|██▌       | 129/500 [03:19<09:24,  1.52s/it, loss=2256.0000, t=1e+3]
Attacking:  26%|██▌       | 130/500 [03:20<09:21,  1.52s/it, loss=2256.0000, t=1e+3]
Attacking:  26%|██▌       | 130/500 [03:21<09:21,  1.52s/it, loss=2192.0000, t=928] 
Attacking:  26%|██▌       | 131/500 [03:21<09:19,  1.52s/it, loss=2192.0000, t=928]
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Attacking:  26%|██▋       | 132/500 [03:23<09:12,  1.50s/it, loss=2208.0000, t=952]
Attacking:  26%|██▋       | 132/500 [03:24<09:12,  1.50s/it, loss=2224.0000, t=964]
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Attacking:  27%|██▋       | 134/500 [03:26<09:01,  1.48s/it, loss=2192.0000, t=912]
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Attacking:  27%|██▋       | 137/500 [03:30<08:51,  1.46s/it, loss=2272.0000, t=992]
Attacking:  27%|██▋       | 137/500 [03:31<08:51,  1.46s/it, loss=2192.0000, t=912]
Attacking:  28%|██▊       | 138/500 [03:32<09:00,  1.49s/it, loss=2192.0000, t=912]
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Attacking:  28%|██▊       | 139/500 [03:34<09:07,  1.52s/it, loss=2208.0000, t=952]
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Attacking:  29%|██▉       | 144/500 [03:41<09:11,  1.55s/it, loss=2256.0000, t=1e+3]
Attacking:  29%|██▉       | 144/500 [03:42<09:11,  1.55s/it, loss=2176.0000, t=912] 
Attacking:  29%|██▉       | 145/500 [03:43<09:10,  1.55s/it, loss=2176.0000, t=912]
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Attacking: 100%|██████████| 500/500 [12:54<00:00,  1.55s/it, loss=2176.0000, t=972]
+Max Diff: 0.501961
+Mean Diff: 0.260653
+Saved adversarial image to attacked/images/scooter-black.jpg
+Saved loss curve to attacked/loss_curve/scooter-black_loss.png
+[GPU 5] Stage 3/3: Test
+Loading models for testing scooter-black...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for scooter-black...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 60.40it/s]
+Saved video to attacked/videos/scooter-black.mp4
+Saved frames to attacked/frames/scooter-black
+[GPU 5] Finished scooter-black.jpg
+======================================
+[GPU 5] Processing scooter-gray.jpg (Image 41/50)
+======================================
+[GPU 5] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 5] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   3%|▎         | 16/500 [00:27<13:38,  1.69s/it, loss=2448.0000, t=1e+3]
Attacking:   3%|▎         | 17/500 [00:27<13:14,  1.64s/it, loss=2448.0000, t=1e+3]
Attacking:   3%|▎         | 17/500 [00:28<13:14,  1.64s/it, loss=2400.0000, t=972] 
Attacking:   4%|▎         | 18/500 [00:29<13:18,  1.66s/it, loss=2400.0000, t=972]
Attacking:   4%|▎         | 18/500 [00:30<13:18,  1.66s/it, loss=2384.0000, t=964]
Attacking:   4%|▍         | 19/500 [00:31<13:27,  1.68s/it, loss=2384.0000, t=964]
Attacking:   4%|▍         | 19/500 [00:31<13:27,  1.68s/it, loss=2336.0000, t=912]
Attacking:   4%|▍         | 20/500 [00:32<12:58,  1.62s/it, loss=2336.0000, t=912]
Attacking:   4%|▍         | 20/500 [00:33<12:58,  1.62s/it, loss=2336.0000, t=928]
Attacking:   4%|▍         | 21/500 [00:34<12:36,  1.58s/it, loss=2336.0000, t=928]
Attacking:   4%|▍         | 21/500 [00:34<12:36,  1.58s/it, loss=2320.0000, t=912]
Attacking:   4%|▍         | 22/500 [00:35<12:23,  1.56s/it, loss=2320.0000, t=912]
Attacking:   4%|▍         | 22/500 [00:36<12:23,  1.56s/it, loss=2400.0000, t=992]
Attacking:   5%|▍         | 23/500 [00:37<12:13,  1.54s/it, loss=2400.0000, t=992]
Attacking:   5%|▍         | 23/500 [00:37<12:13,  1.54s/it, loss=2368.0000, t=964]
Attacking:   5%|▍         | 24/500 [00:38<12:17,  1.55s/it, loss=2368.0000, t=964]
Attacking:   5%|▍         | 24/500 [00:39<12:17,  1.55s/it, loss=2336.0000, t=952]
Attacking:   5%|▌         | 25/500 [00:40<12:05,  1.53s/it, loss=2336.0000, t=952]
Attacking:   5%|▌         | 25/500 [00:40<12:05,  1.53s/it, loss=2304.0000, t=912]
Attacking:   5%|▌         | 26/500 [00:41<11:58,  1.52s/it, loss=2304.0000, t=912]
Attacking:   5%|▌         | 26/500 [00:42<11:58,  1.52s/it, loss=2368.0000, t=964]
Attacking:   5%|▌         | 27/500 [00:43<11:53,  1.51s/it, loss=2368.0000, t=964]
Attacking:   5%|▌         | 27/500 [00:43<11:53,  1.51s/it, loss=2368.0000, t=972]
Attacking:   6%|▌         | 28/500 [00:44<11:50,  1.51s/it, loss=2368.0000, t=972]
Attacking:   6%|▌         | 28/500 [00:45<11:50,  1.51s/it, loss=2336.0000, t=952]
Attacking:   6%|▌         | 29/500 [00:46<11:59,  1.53s/it, loss=2336.0000, t=952]
Attacking:   6%|▌         | 29/500 [00:46<11:59,  1.53s/it, loss=2352.0000, t=972]
Attacking:   6%|▌         | 30/500 [00:47<11:51,  1.51s/it, loss=2352.0000, t=972]
Attacking:   6%|▌         | 30/500 [00:48<11:51,  1.51s/it, loss=2304.0000, t=912]
Attacking:   6%|▌         | 31/500 [00:49<11:56,  1.53s/it, loss=2304.0000, t=912]
Attacking:   6%|▌         | 31/500 [00:50<11:56,  1.53s/it, loss=2320.0000, t=952]
Attacking:   6%|▋         | 32/500 [00:50<11:58,  1.54s/it, loss=2320.0000, t=952]
Attacking:   6%|▋         | 32/500 [00:51<11:58,  1.54s/it, loss=2304.0000, t=940]
Attacking:   7%|▋         | 33/500 [00:52<11:56,  1.53s/it, loss=2304.0000, t=940]
Attacking:   7%|▋         | 33/500 [00:53<11:56,  1.53s/it, loss=2304.0000, t=940]
Attacking:   7%|▋         | 34/500 [00:53<11:46,  1.52s/it, loss=2304.0000, t=940]
Attacking:   7%|▋         | 34/500 [00:54<11:46,  1.52s/it, loss=2288.0000, t=928]
Attacking:   7%|▋         | 35/500 [00:55<11:52,  1.53s/it, loss=2288.0000, t=928]
Attacking:   7%|▋         | 35/500 [00:56<11:52,  1.53s/it, loss=2304.0000, t=952]
Attacking:   7%|▋         | 36/500 [00:57<11:54,  1.54s/it, loss=2304.0000, t=952]
Attacking:   7%|▋         | 36/500 [00:57<11:54,  1.54s/it, loss=2368.0000, t=992]
Attacking:   7%|▋         | 37/500 [00:58<11:42,  1.52s/it, loss=2368.0000, t=992]
Attacking:   7%|▋         | 37/500 [00:59<11:42,  1.52s/it, loss=2352.0000, t=1e+3]
Attacking:   8%|▊         | 38/500 [01:00<11:47,  1.53s/it, loss=2352.0000, t=1e+3]
Attacking:   8%|▊         | 38/500 [01:00<11:47,  1.53s/it, loss=2272.0000, t=900] 
Attacking:   8%|▊         | 39/500 [01:01<12:03,  1.57s/it, loss=2272.0000, t=900]
Attacking:   8%|▊         | 39/500 [01:02<12:03,  1.57s/it, loss=2320.0000, t=972]
Attacking:   8%|▊         | 40/500 [01:03<12:10,  1.59s/it, loss=2320.0000, t=972]
Attacking:   8%|▊         | 40/500 [01:04<12:10,  1.59s/it, loss=2272.0000, t=928]
Attacking:   8%|▊         | 41/500 [01:04<11:58,  1.57s/it, loss=2272.0000, t=928]
Attacking:   8%|▊         | 41/500 [01:05<11:58,  1.57s/it, loss=2304.0000, t=964]
Attacking:   8%|▊         | 42/500 [01:06<11:52,  1.56s/it, loss=2304.0000, t=964]
Attacking:   8%|▊         | 42/500 [01:07<11:52,  1.56s/it, loss=2336.0000, t=992]
Attacking:   9%|▊         | 43/500 [01:07<11:50,  1.55s/it, loss=2336.0000, t=992]
Attacking:   9%|▊         | 43/500 [01:08<11:50,  1.55s/it, loss=2336.0000, t=1e+3]
Attacking:   9%|▉         | 44/500 [01:09<11:40,  1.54s/it, loss=2336.0000, t=1e+3]
Attacking:   9%|▉         | 44/500 [01:10<11:40,  1.54s/it, loss=2256.0000, t=912] 
Attacking:   9%|▉         | 45/500 [01:11<11:44,  1.55s/it, loss=2256.0000, t=912]
Attacking:   9%|▉         | 45/500 [01:11<11:44,  1.55s/it, loss=2256.0000, t=912]
Attacking:   9%|▉         | 46/500 [01:12<11:43,  1.55s/it, loss=2256.0000, t=912]
Attacking:   9%|▉         | 46/500 [01:13<11:43,  1.55s/it, loss=2272.0000, t=940]
Attacking:   9%|▉         | 47/500 [01:14<11:43,  1.55s/it, loss=2272.0000, t=940]
Attacking:   9%|▉         | 47/500 [01:14<11:43,  1.55s/it, loss=2272.0000, t=952]
Attacking:  10%|▉         | 48/500 [01:15<11:32,  1.53s/it, loss=2272.0000, t=952]
Attacking:  10%|▉         | 48/500 [01:16<11:32,  1.53s/it, loss=2320.0000, t=984]
Attacking:  10%|▉         | 49/500 [01:17<11:26,  1.52s/it, loss=2320.0000, t=984]
Attacking:  10%|▉         | 49/500 [01:17<11:26,  1.52s/it, loss=2320.0000, t=992]
Attacking:  10%|█         | 50/500 [01:18<11:29,  1.53s/it, loss=2320.0000, t=992]
Attacking:  10%|█         | 50/500 [01:19<11:29,  1.53s/it, loss=2288.0000, t=972]
Attacking:  10%|█         | 51/500 [01:20<11:25,  1.53s/it, loss=2288.0000, t=972]
Attacking:  10%|█         | 51/500 [01:20<11:25,  1.53s/it, loss=2320.0000, t=1e+3]
Attacking:  10%|█         | 52/500 [01:21<11:15,  1.51s/it, loss=2320.0000, t=1e+3]
Attacking:  10%|█         | 52/500 [01:22<11:15,  1.51s/it, loss=2240.0000, t=912] 
Attacking:  11%|█         | 53/500 [01:23<11:22,  1.53s/it, loss=2240.0000, t=912]
Attacking:  11%|█         | 53/500 [01:23<11:22,  1.53s/it, loss=2256.0000, t=940]
Attacking:  11%|█         | 54/500 [01:24<11:14,  1.51s/it, loss=2256.0000, t=940]
Attacking:  11%|█         | 54/500 [01:25<11:14,  1.51s/it, loss=2224.0000, t=912]
Attacking:  11%|█         | 55/500 [01:26<10:58,  1.48s/it, loss=2224.0000, t=912]
Attacking:  11%|█         | 55/500 [01:26<10:58,  1.48s/it, loss=2240.0000, t=928]
Attacking:  11%|█         | 56/500 [01:27<11:03,  1.49s/it, loss=2240.0000, t=928]
Attacking:  11%|█         | 56/500 [01:28<11:03,  1.49s/it, loss=2272.0000, t=964]
Attacking:  11%|█▏        | 57/500 [01:29<10:57,  1.48s/it, loss=2272.0000, t=964]
Attacking:  11%|█▏        | 57/500 [01:29<10:57,  1.48s/it, loss=2256.0000, t=940]
Attacking:  12%|█▏        | 58/500 [01:30<11:06,  1.51s/it, loss=2256.0000, t=940]
Attacking:  12%|█▏        | 58/500 [01:31<11:06,  1.51s/it, loss=2304.0000, t=984]
Attacking:  12%|█▏        | 59/500 [01:32<11:43,  1.59s/it, loss=2304.0000, t=984]
Attacking:  12%|█▏        | 59/500 [01:33<11:43,  1.59s/it, loss=2272.0000, t=972]
Attacking:  12%|█▏        | 60/500 [01:34<11:50,  1.62s/it, loss=2272.0000, t=972]
Attacking:  12%|█▏        | 60/500 [01:34<11:50,  1.62s/it, loss=2272.0000, t=972]
Attacking:  12%|█▏        | 61/500 [01:35<11:33,  1.58s/it, loss=2272.0000, t=972]
Attacking:  12%|█▏        | 61/500 [01:36<11:33,  1.58s/it, loss=2256.0000, t=964]
Attacking:  12%|█▏        | 62/500 [01:37<11:13,  1.54s/it, loss=2256.0000, t=964]
Attacking:  12%|█▏        | 62/500 [01:37<11:13,  1.54s/it, loss=2288.0000, t=1e+3]
Attacking:  13%|█▎        | 63/500 [01:38<11:04,  1.52s/it, loss=2288.0000, t=1e+3]
Attacking:  13%|█▎        | 63/500 [01:39<11:04,  1.52s/it, loss=2256.0000, t=964] 
Attacking:  13%|█▎        | 64/500 [01:40<10:55,  1.50s/it, loss=2256.0000, t=964]
Attacking:  13%|█▎        | 64/500 [01:40<10:55,  1.50s/it, loss=2224.0000, t=928]
Attacking:  13%|█▎        | 65/500 [01:41<10:52,  1.50s/it, loss=2224.0000, t=928]
Attacking:  13%|█▎        | 65/500 [01:42<10:52,  1.50s/it, loss=2288.0000, t=1e+3]
Attacking:  13%|█▎        | 66/500 [01:43<10:49,  1.50s/it, loss=2288.0000, t=1e+3]
Attacking:  13%|█▎        | 66/500 [01:43<10:49,  1.50s/it, loss=2240.0000, t=940] 
Attacking:  13%|█▎        | 67/500 [01:44<10:42,  1.48s/it, loss=2240.0000, t=940]
Attacking:  13%|█▎        | 67/500 [01:45<10:42,  1.48s/it, loss=2304.0000, t=992]
Attacking:  14%|█▎        | 68/500 [01:46<10:51,  1.51s/it, loss=2304.0000, t=992]
Attacking:  14%|█▎        | 68/500 [01:46<10:51,  1.51s/it, loss=2272.0000, t=1e+3]
Attacking:  14%|█▍        | 69/500 [01:47<10:51,  1.51s/it, loss=2272.0000, t=1e+3]
Attacking:  14%|█▍        | 69/500 [01:48<10:51,  1.51s/it, loss=2224.0000, t=940] 
Attacking:  14%|█▍        | 70/500 [01:49<10:55,  1.52s/it, loss=2224.0000, t=940]
Attacking:  14%|█▍        | 70/500 [01:49<10:55,  1.52s/it, loss=2208.0000, t=912]
Attacking:  14%|█▍        | 71/500 [01:50<11:04,  1.55s/it, loss=2208.0000, t=912]
Attacking:  14%|█▍        | 71/500 [01:51<11:04,  1.55s/it, loss=2240.0000, t=952]
Attacking:  14%|█▍        | 72/500 [01:52<11:09,  1.57s/it, loss=2240.0000, t=952]
Attacking:  14%|█▍        | 72/500 [01:53<11:09,  1.57s/it, loss=2224.0000, t=940]
Attacking:  15%|█▍        | 73/500 [01:53<11:10,  1.57s/it, loss=2224.0000, t=940]
Attacking:  15%|█▍        | 73/500 [01:54<11:10,  1.57s/it, loss=2256.0000, t=972]
Attacking:  15%|█▍        | 74/500 [01:55<11:04,  1.56s/it, loss=2256.0000, t=972]
Attacking:  15%|█▍        | 74/500 [01:56<11:04,  1.56s/it, loss=2256.0000, t=972]
Attacking:  15%|█▌        | 75/500 [01:56<11:02,  1.56s/it, loss=2256.0000, t=972]
Attacking:  15%|█▌        | 75/500 [01:57<11:02,  1.56s/it, loss=2224.0000, t=928]
Attacking:  15%|█▌        | 76/500 [01:58<11:06,  1.57s/it, loss=2224.0000, t=928]
Attacking:  15%|█▌        | 76/500 [01:59<11:06,  1.57s/it, loss=2288.0000, t=1e+3]
Attacking:  15%|█▌        | 77/500 [02:00<10:54,  1.55s/it, loss=2288.0000, t=1e+3]
Attacking:  15%|█▌        | 77/500 [02:00<10:54,  1.55s/it, loss=2288.0000, t=992] 
Attacking:  16%|█▌        | 78/500 [02:01<10:49,  1.54s/it, loss=2288.0000, t=992]
Attacking:  16%|█▌        | 78/500 [02:02<10:49,  1.54s/it, loss=2208.0000, t=928]
Attacking:  16%|█▌        | 79/500 [02:03<10:32,  1.50s/it, loss=2208.0000, t=928]
Attacking:  16%|█▌        | 79/500 [02:03<10:32,  1.50s/it, loss=2272.0000, t=984]
Attacking:  16%|█▌        | 80/500 [02:04<10:24,  1.49s/it, loss=2272.0000, t=984]
Attacking:  16%|█▌        | 80/500 [02:05<10:24,  1.49s/it, loss=2272.0000, t=984]
Attacking:  16%|█▌        | 81/500 [02:06<10:30,  1.50s/it, loss=2272.0000, t=984]
Attacking:  16%|█▌        | 81/500 [02:06<10:30,  1.50s/it, loss=2272.0000, t=984]
Attacking:  16%|█▋        | 82/500 [02:07<10:29,  1.51s/it, loss=2272.0000, t=984]
Attacking:  16%|█▋        | 82/500 [02:08<10:29,  1.51s/it, loss=2224.0000, t=952]
Attacking:  17%|█▋        | 83/500 [02:09<10:31,  1.52s/it, loss=2224.0000, t=952]
Attacking:  17%|█▋        | 83/500 [02:09<10:31,  1.52s/it, loss=2192.0000, t=900]
Attacking:  17%|█▋        | 84/500 [02:10<10:18,  1.49s/it, loss=2192.0000, t=900]
Attacking:  17%|█▋        | 84/500 [02:11<10:18,  1.49s/it, loss=2208.0000, t=940]
Attacking:  17%|█▋        | 85/500 [02:11<10:16,  1.49s/it, loss=2208.0000, t=940]
Attacking:  17%|█▋        | 85/500 [02:12<10:16,  1.49s/it, loss=2240.0000, t=964]
Attacking:  17%|█▋        | 86/500 [02:13<10:21,  1.50s/it, loss=2240.0000, t=964]
Attacking:  17%|█▋        | 86/500 [02:14<10:21,  1.50s/it, loss=2288.0000, t=992]
Attacking:  17%|█▋        | 87/500 [02:15<10:24,  1.51s/it, loss=2288.0000, t=992]
Attacking:  17%|█▋        | 87/500 [02:15<10:24,  1.51s/it, loss=2192.0000, t=900]
Attacking:  18%|█▊        | 88/500 [02:16<10:21,  1.51s/it, loss=2192.0000, t=900]
Attacking:  18%|█▊        | 88/500 [02:17<10:21,  1.51s/it, loss=2208.0000, t=940]
Attacking:  18%|█▊        | 89/500 [02:18<10:25,  1.52s/it, loss=2208.0000, t=940]
Attacking:  18%|█▊        | 89/500 [02:18<10:25,  1.52s/it, loss=2208.0000, t=952]
Attacking:  18%|█▊        | 90/500 [02:19<10:15,  1.50s/it, loss=2208.0000, t=952]
Attacking:  18%|█▊        | 90/500 [02:20<10:15,  1.50s/it, loss=2176.0000, t=900]
Attacking:  18%|█▊        | 91/500 [02:21<10:13,  1.50s/it, loss=2176.0000, t=900]
Attacking:  18%|█▊        | 91/500 [02:21<10:13,  1.50s/it, loss=2256.0000, t=1e+3]
Attacking:  18%|█▊        | 92/500 [02:22<10:07,  1.49s/it, loss=2256.0000, t=1e+3]
Attacking:  18%|█▊        | 92/500 [02:23<10:07,  1.49s/it, loss=2272.0000, t=992] 
Attacking:  19%|█▊        | 93/500 [02:24<10:08,  1.49s/it, loss=2272.0000, t=992]
Attacking:  19%|█▊        | 93/500 [02:24<10:08,  1.49s/it, loss=2208.0000, t=952]
Attacking:  19%|█▉        | 94/500 [02:25<10:04,  1.49s/it, loss=2208.0000, t=952]
Attacking:  19%|█▉        | 94/500 [02:26<10:04,  1.49s/it, loss=2256.0000, t=1e+3]
Attacking:  19%|█▉        | 95/500 [02:27<10:15,  1.52s/it, loss=2256.0000, t=1e+3]
Attacking:  19%|█▉        | 95/500 [02:27<10:15,  1.52s/it, loss=2208.0000, t=928] 
Attacking:  19%|█▉        | 96/500 [02:28<10:18,  1.53s/it, loss=2208.0000, t=928]
Attacking:  19%|█▉        | 96/500 [02:29<10:18,  1.53s/it, loss=2272.0000, t=992]
Attacking:  19%|█▉        | 97/500 [02:30<10:09,  1.51s/it, loss=2272.0000, t=992]
Attacking:  19%|█▉        | 97/500 [02:30<10:09,  1.51s/it, loss=2208.0000, t=940]
Attacking:  20%|█▉        | 98/500 [02:31<09:58,  1.49s/it, loss=2208.0000, t=940]
Attacking:  20%|█▉        | 98/500 [02:32<09:58,  1.49s/it, loss=2208.0000, t=952]
Attacking:  20%|█▉        | 99/500 [02:33<10:07,  1.51s/it, loss=2208.0000, t=952]
Attacking:  20%|█▉        | 99/500 [02:33<10:07,  1.51s/it, loss=2256.0000, t=984]
Attacking:  20%|██        | 100/500 [02:34<10:08,  1.52s/it, loss=2256.0000, t=984]
Attacking:  20%|██        | 100/500 [02:35<10:08,  1.52s/it, loss=2256.0000, t=1e+3]
Attacking:  20%|██        | 101/500 [02:36<10:17,  1.55s/it, loss=2256.0000, t=1e+3]
Attacking:  20%|██        | 101/500 [02:36<10:17,  1.55s/it, loss=2176.0000, t=912] 
Attacking:  20%|██        | 102/500 [02:37<10:11,  1.54s/it, loss=2176.0000, t=912]
Attacking:  20%|██        | 102/500 [02:38<10:11,  1.54s/it, loss=2176.0000, t=900]
Attacking:  21%|██        | 103/500 [02:39<10:14,  1.55s/it, loss=2176.0000, t=900]
Attacking:  21%|██        | 103/500 [02:40<10:14,  1.55s/it, loss=2256.0000, t=984]
Attacking:  21%|██        | 104/500 [02:40<10:06,  1.53s/it, loss=2256.0000, t=984]
Attacking:  21%|██        | 104/500 [02:41<10:06,  1.53s/it, loss=2256.0000, t=984]
Attacking:  21%|██        | 105/500 [02:42<10:16,  1.56s/it, loss=2256.0000, t=984]
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\ No newline at end of file
diff --git a/experiments/cfg3_eps64/logs/gpu_6.log b/experiments/cfg3_eps64/logs/gpu_6.log
new file mode 100644
index 0000000000000000000000000000000000000000..fd10960be637ccb2796664f73263f89225372f14
--- /dev/null
+++ b/experiments/cfg3_eps64/logs/gpu_6.log
@@ -0,0 +1,483 @@
+[GPU 6] Starting work on images 42 to 48
+======================================
+[GPU 6] Processing ship.jpg (Image 42/50)
+======================================
+[GPU 6] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 6] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  11%|█         | 55/500 [01:30<11:36,  1.57s/it, loss=2016.0000, t=912]
Attacking:  11%|█         | 55/500 [01:31<11:36,  1.57s/it, loss=2016.0000, t=928]
Attacking:  11%|█         | 56/500 [01:31<11:41,  1.58s/it, loss=2016.0000, t=928]
Attacking:  11%|█         | 56/500 [01:32<11:41,  1.58s/it, loss=2024.0000, t=940]
Attacking:  11%|█▏        | 57/500 [01:33<11:29,  1.56s/it, loss=2024.0000, t=940]
Attacking:  11%|█▏        | 57/500 [01:34<11:29,  1.56s/it, loss=2008.0000, t=900]
Attacking:  12%|█▏        | 58/500 [01:34<11:25,  1.55s/it, loss=2008.0000, t=900]
Attacking:  12%|█▏        | 58/500 [01:35<11:25,  1.55s/it, loss=2048.0000, t=972]
Attacking:  12%|█▏        | 59/500 [01:36<11:44,  1.60s/it, loss=2048.0000, t=972]
Attacking:  12%|█▏        | 59/500 [01:37<11:44,  1.60s/it, loss=2096.0000, t=984]
Attacking:  12%|█▏        | 60/500 [01:38<11:35,  1.58s/it, loss=2096.0000, t=984]
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Attacking:  12%|█▏        | 61/500 [01:39<11:28,  1.57s/it, loss=2008.0000, t=912]
Attacking:  12%|█▏        | 61/500 [01:40<11:28,  1.57s/it, loss=2032.0000, t=952]
Attacking:  12%|█▏        | 62/500 [01:41<11:39,  1.60s/it, loss=2032.0000, t=952]
Attacking:  12%|█▏        | 62/500 [01:42<11:39,  1.60s/it, loss=2008.0000, t=900]
Attacking:  13%|█▎        | 63/500 [01:42<11:32,  1.58s/it, loss=2008.0000, t=900]
Attacking:  13%|█▎        | 63/500 [01:43<11:32,  1.58s/it, loss=2000.0000, t=912]
Attacking:  13%|█▎        | 64/500 [01:44<11:38,  1.60s/it, loss=2000.0000, t=912]
Attacking:  13%|█▎        | 64/500 [01:45<11:38,  1.60s/it, loss=2080.0000, t=984]
Attacking:  13%|█▎        | 65/500 [01:46<11:46,  1.63s/it, loss=2080.0000, t=984]
Attacking:  13%|█▎        | 65/500 [01:47<11:46,  1.63s/it, loss=2032.0000, t=964]
Attacking:  13%|█▎        | 66/500 [01:47<11:54,  1.65s/it, loss=2032.0000, t=964]
Attacking:  13%|█▎        | 66/500 [01:48<11:54,  1.65s/it, loss=2080.0000, t=984]
Attacking:  13%|█▎        | 67/500 [01:49<11:55,  1.65s/it, loss=2080.0000, t=984]
Attacking:  13%|█▎        | 67/500 [01:50<11:55,  1.65s/it, loss=2112.0000, t=1e+3]
Attacking:  14%|█▎        | 68/500 [01:51<11:53,  1.65s/it, loss=2112.0000, t=1e+3]
Attacking:  14%|█▎        | 68/500 [01:52<11:53,  1.65s/it, loss=2000.0000, t=940] 
Attacking:  14%|█▍        | 69/500 [01:52<11:51,  1.65s/it, loss=2000.0000, t=940]
Attacking:  14%|█▍        | 69/500 [01:53<11:51,  1.65s/it, loss=2000.0000, t=952]
Attacking:  14%|█▍        | 70/500 [01:54<11:44,  1.64s/it, loss=2000.0000, t=952]
Attacking:  14%|█▍        | 70/500 [01:55<11:44,  1.64s/it, loss=1984.0000, t=912]
Attacking:  14%|█▍        | 71/500 [01:56<11:21,  1.59s/it, loss=1984.0000, t=912]
Attacking:  14%|█▍        | 71/500 [01:56<11:21,  1.59s/it, loss=2080.0000, t=984]
Attacking:  14%|█▍        | 72/500 [01:57<11:20,  1.59s/it, loss=2080.0000, t=984]
Attacking:  14%|█▍        | 72/500 [01:58<11:20,  1.59s/it, loss=2096.0000, t=1e+3]
Attacking:  15%|█▍        | 73/500 [01:59<11:15,  1.58s/it, loss=2096.0000, t=1e+3]
Attacking:  15%|█▍        | 73/500 [01:59<11:15,  1.58s/it, loss=2080.0000, t=1e+3]
Attacking:  15%|█▍        | 74/500 [02:00<11:13,  1.58s/it, loss=2080.0000, t=1e+3]
Attacking:  15%|█▍        | 74/500 [02:01<11:13,  1.58s/it, loss=2008.0000, t=940] 
Attacking:  15%|█▌        | 75/500 [02:02<11:18,  1.60s/it, loss=2008.0000, t=940]
Attacking:  15%|█▌        | 75/500 [02:03<11:18,  1.60s/it, loss=2080.0000, t=992]
Attacking:  15%|█▌        | 76/500 [02:04<11:30,  1.63s/it, loss=2080.0000, t=992]
Attacking:  15%|█▌        | 76/500 [02:04<11:30,  1.63s/it, loss=2000.0000, t=940]
Attacking:  15%|█▌        | 77/500 [02:05<11:34,  1.64s/it, loss=2000.0000, t=940]
Attacking:  15%|█▌        | 77/500 [02:06<11:34,  1.64s/it, loss=2096.0000, t=1e+3]
Attacking:  16%|█▌        | 78/500 [02:07<11:26,  1.63s/it, loss=2096.0000, t=1e+3]
Attacking:  16%|█▌        | 78/500 [02:08<11:26,  1.63s/it, loss=1968.0000, t=900] 
Attacking:  16%|█▌        | 79/500 [02:08<11:19,  1.61s/it, loss=1968.0000, t=900]
Attacking:  16%|█▌        | 79/500 [02:09<11:19,  1.61s/it, loss=2080.0000, t=992]
Attacking:  16%|█▌        | 80/500 [02:10<11:20,  1.62s/it, loss=2080.0000, t=992]
Attacking:  16%|█▌        | 80/500 [02:11<11:20,  1.62s/it, loss=2080.0000, t=1e+3]
Attacking:  16%|█▌        | 81/500 [02:12<11:25,  1.64s/it, loss=2080.0000, t=1e+3]
Attacking:  16%|█▌        | 81/500 [02:12<11:25,  1.64s/it, loss=2024.0000, t=972] 
Attacking:  16%|█▋        | 82/500 [02:13<11:14,  1.61s/it, loss=2024.0000, t=972]
Attacking:  16%|█▋        | 82/500 [02:14<11:14,  1.61s/it, loss=1976.0000, t=900]
Attacking:  17%|█▋        | 83/500 [02:15<11:15,  1.62s/it, loss=1976.0000, t=900]
Attacking:  17%|█▋        | 83/500 [02:16<11:15,  1.62s/it, loss=2096.0000, t=1e+3]
Attacking:  17%|█▋        | 84/500 [02:16<11:04,  1.60s/it, loss=2096.0000, t=1e+3]
Attacking:  17%|█▋        | 84/500 [02:17<11:04,  1.60s/it, loss=2064.0000, t=992] 
Attacking:  17%|█▋        | 85/500 [02:18<11:00,  1.59s/it, loss=2064.0000, t=992]
Attacking:  17%|█▋        | 85/500 [02:19<11:00,  1.59s/it, loss=1968.0000, t=900]
Attacking:  17%|█▋        | 86/500 [02:20<10:56,  1.59s/it, loss=1968.0000, t=900]
Attacking:  17%|█▋        | 86/500 [02:20<10:56,  1.59s/it, loss=2016.0000, t=972]
Attacking:  17%|█▋        | 87/500 [02:21<10:51,  1.58s/it, loss=2016.0000, t=972]
Attacking:  17%|█▋        | 87/500 [02:22<10:51,  1.58s/it, loss=1976.0000, t=928]
Attacking:  18%|█▊        | 88/500 [02:23<10:36,  1.55s/it, loss=1976.0000, t=928]
Attacking:  18%|█▊        | 88/500 [02:23<10:36,  1.55s/it, loss=1984.0000, t=940]
Attacking:  18%|█▊        | 89/500 [02:24<10:39,  1.56s/it, loss=1984.0000, t=940]
Attacking:  18%|█▊        | 89/500 [02:25<10:39,  1.56s/it, loss=1960.0000, t=900]
Attacking:  18%|█▊        | 90/500 [02:26<10:46,  1.58s/it, loss=1960.0000, t=900]
Attacking:  18%|█▊        | 90/500 [02:27<10:46,  1.58s/it, loss=1968.0000, t=900]
Attacking:  18%|█▊        | 91/500 [02:27<10:50,  1.59s/it, loss=1968.0000, t=900]
Attacking:  18%|█▊        | 91/500 [02:28<10:50,  1.59s/it, loss=1960.0000, t=900]
Attacking:  18%|█▊        | 92/500 [02:29<10:42,  1.58s/it, loss=1960.0000, t=900]
Attacking:  18%|█▊        | 92/500 [02:30<10:42,  1.58s/it, loss=2000.0000, t=964]
Attacking:  19%|█▊        | 93/500 [02:31<10:44,  1.58s/it, loss=2000.0000, t=964]
Attacking:  19%|█▊        | 93/500 [02:31<10:44,  1.58s/it, loss=2040.0000, t=984]
Attacking:  19%|█▉        | 94/500 [02:32<10:30,  1.55s/it, loss=2040.0000, t=984]
Attacking:  19%|█▉        | 94/500 [02:33<10:30,  1.55s/it, loss=2064.0000, t=1e+3]
Attacking:  19%|█▉        | 95/500 [02:34<10:42,  1.59s/it, loss=2064.0000, t=1e+3]
Attacking:  19%|█▉        | 95/500 [02:35<10:42,  1.59s/it, loss=2064.0000, t=1e+3]
Attacking:  19%|█▉        | 96/500 [02:35<10:47,  1.60s/it, loss=2064.0000, t=1e+3]
Attacking:  19%|█▉        | 96/500 [02:36<10:47,  1.60s/it, loss=2048.0000, t=992] 
Attacking:  19%|█▉        | 97/500 [02:37<10:47,  1.61s/it, loss=2048.0000, t=992]
Attacking:  19%|█▉        | 97/500 [02:38<10:47,  1.61s/it, loss=1952.0000, t=900]
Attacking:  20%|█▉        | 98/500 [02:39<10:49,  1.62s/it, loss=1952.0000, t=900]
Attacking:  20%|█▉        | 98/500 [02:39<10:49,  1.62s/it, loss=1992.0000, t=964]
Attacking:  20%|█▉        | 99/500 [02:40<10:45,  1.61s/it, loss=1992.0000, t=964]
Attacking:  20%|█▉        | 99/500 [02:41<10:45,  1.61s/it, loss=2000.0000, t=972]
Attacking:  20%|██        | 100/500 [02:42<10:34,  1.59s/it, loss=2000.0000, t=972]
Attacking:  20%|██        | 100/500 [02:42<10:34,  1.59s/it, loss=2032.0000, t=984]
Attacking:  20%|██        | 101/500 [02:43<10:20,  1.55s/it, loss=2032.0000, t=984]
Attacking:  20%|██        | 101/500 [02:44<10:20,  1.55s/it, loss=2032.0000, t=984]
Attacking:  20%|██        | 102/500 [02:45<10:22,  1.56s/it, loss=2032.0000, t=984]
Attacking:  20%|██        | 102/500 [02:46<10:22,  1.56s/it, loss=2048.0000, t=992]
Attacking:  21%|██        | 103/500 [02:47<10:28,  1.58s/it, loss=2048.0000, t=992]
Attacking:  21%|██        | 103/500 [02:47<10:28,  1.58s/it, loss=1976.0000, t=952]
Attacking:  21%|██        | 104/500 [02:48<10:27,  1.58s/it, loss=1976.0000, t=952]
Attacking:  21%|██        | 104/500 [02:49<10:27,  1.58s/it, loss=2000.0000, t=972]
Attacking:  21%|██        | 105/500 [02:50<10:40,  1.62s/it, loss=2000.0000, t=972]
Attacking:  21%|██        | 105/500 [02:50<10:40,  1.62s/it, loss=2048.0000, t=992]
Attacking:  21%|██        | 106/500 [02:51<10:23,  1.58s/it, loss=2048.0000, t=992]
Attacking:  21%|██        | 106/500 [02:52<10:23,  1.58s/it, loss=1976.0000, t=952]
Attacking:  21%|██▏       | 107/500 [02:53<10:34,  1.61s/it, loss=1976.0000, t=952]
Attacking:  21%|██▏       | 107/500 [02:54<10:34,  1.61s/it, loss=1976.0000, t=952]
Attacking:  22%|██▏       | 108/500 [02:55<10:37,  1.63s/it, loss=1976.0000, t=952]
Attacking:  22%|██▏       | 108/500 [02:55<10:37,  1.63s/it, loss=1968.0000, t=952]
Attacking:  22%|██▏       | 109/500 [02:56<10:44,  1.65s/it, loss=1968.0000, t=952]
Attacking:  22%|██▏       | 109/500 [02:57<10:44,  1.65s/it, loss=1952.0000, t=912]
Attacking:  22%|██▏       | 110/500 [02:58<10:42,  1.65s/it, loss=1952.0000, t=912]
Attacking:  22%|██▏       | 110/500 [02:59<10:42,  1.65s/it, loss=2048.0000, t=1e+3]
Attacking:  22%|██▏       | 111/500 [03:00<10:39,  1.64s/it, loss=2048.0000, t=1e+3]
Attacking:  22%|██▏       | 111/500 [03:00<10:39,  1.64s/it, loss=1952.0000, t=928] 
Attacking:  22%|██▏       | 112/500 [03:01<10:43,  1.66s/it, loss=1952.0000, t=928]
Attacking:  22%|██▏       | 112/500 [03:02<10:43,  1.66s/it, loss=1952.0000, t=928]
Attacking:  23%|██▎       | 113/500 [03:03<10:53,  1.69s/it, loss=1952.0000, t=928]
Attacking:  23%|██▎       | 113/500 [03:04<10:53,  1.69s/it, loss=1976.0000, t=964]
Attacking:  23%|██▎       | 114/500 [03:04<10:21,  1.61s/it, loss=1976.0000, t=964]
Attacking:  23%|██▎       | 114/500 [03:05<10:21,  1.61s/it, loss=1952.0000, t=912]
Attacking:  23%|██▎       | 115/500 [03:06<10:07,  1.58s/it, loss=1952.0000, t=912]
Attacking:  23%|██▎       | 115/500 [03:07<10:07,  1.58s/it, loss=1936.0000, t=900]
Attacking:  23%|██▎       | 116/500 [03:08<10:02,  1.57s/it, loss=1936.0000, t=900]
Attacking:  23%|██▎       | 116/500 [03:08<10:02,  1.57s/it, loss=1968.0000, t=928]
Attacking:  23%|██▎       | 117/500 [03:09<10:00,  1.57s/it, loss=1968.0000, t=928]
Attacking:  23%|██▎       | 117/500 [03:10<10:00,  1.57s/it, loss=1952.0000, t=928]
Attacking:  24%|██▎       | 118/500 [03:11<09:55,  1.56s/it, loss=1952.0000, t=928]
Attacking:  24%|██▎       | 118/500 [03:11<09:55,  1.56s/it, loss=2048.0000, t=992]
Attacking:  24%|██▍       | 119/500 [03:12<09:51,  1.55s/it, loss=2048.0000, t=992]
Attacking:  24%|██▍       | 119/500 [03:13<09:51,  1.55s/it, loss=1952.0000, t=928]
Attacking:  24%|██▍       | 120/500 [03:14<10:06,  1.60s/it, loss=1952.0000, t=928]
Attacking:  24%|██▍       | 120/500 [03:15<10:06,  1.60s/it, loss=2048.0000, t=1e+3]
Attacking:  24%|██▍       | 121/500 [03:15<09:51,  1.56s/it, loss=2048.0000, t=1e+3]
Attacking:  24%|██▍       | 121/500 [03:16<09:51,  1.56s/it, loss=2032.0000, t=1e+3]
Attacking:  24%|██▍       | 122/500 [03:17<09:47,  1.55s/it, loss=2032.0000, t=1e+3]
Attacking:  24%|██▍       | 122/500 [03:18<09:47,  1.55s/it, loss=2032.0000, t=992] 
Attacking:  25%|██▍       | 123/500 [03:18<09:48,  1.56s/it, loss=2032.0000, t=992]
Attacking:  25%|██▍       | 123/500 [03:19<09:48,  1.56s/it, loss=1952.0000, t=940]
Attacking:  25%|██▍       | 124/500 [03:20<09:43,  1.55s/it, loss=1952.0000, t=940]
Attacking:  25%|██▍       | 124/500 [03:21<09:43,  1.55s/it, loss=1960.0000, t=952]
Attacking:  25%|██▌       | 125/500 [03:22<10:06,  1.62s/it, loss=1960.0000, t=952]
Attacking:  25%|██▌       | 125/500 [03:23<10:06,  1.62s/it, loss=1936.0000, t=900]
Attacking:  25%|██▌       | 126/500 [03:23<10:15,  1.65s/it, loss=1936.0000, t=900]
Attacking:  25%|██▌       | 126/500 [03:24<10:15,  1.65s/it, loss=1952.0000, t=940]
Attacking:  25%|██▌       | 127/500 [03:25<10:20,  1.66s/it, loss=1952.0000, t=940]
Attacking:  25%|██▌       | 127/500 [03:26<10:20,  1.66s/it, loss=2048.0000, t=1e+3]
Attacking:  26%|██▌       | 128/500 [03:27<10:13,  1.65s/it, loss=2048.0000, t=1e+3]
Attacking:  26%|██▌       | 128/500 [03:28<10:13,  1.65s/it, loss=2016.0000, t=984] 
Attacking:  26%|██▌       | 129/500 [03:28<10:04,  1.63s/it, loss=2016.0000, t=984]
Attacking:  26%|██▌       | 129/500 [03:29<10:04,  1.63s/it, loss=2032.0000, t=992]
Attacking:  26%|██▌       | 130/500 [03:30<09:51,  1.60s/it, loss=2032.0000, t=992]
Attacking:  26%|██▌       | 130/500 [03:31<09:51,  1.60s/it, loss=1968.0000, t=952]
Attacking:  26%|██▌       | 131/500 [03:31<09:47,  1.59s/it, loss=1968.0000, t=952]
Attacking:  26%|██▌       | 131/500 [03:32<09:47,  1.59s/it, loss=1968.0000, t=964]
Attacking:  26%|██▋       | 132/500 [03:33<09:42,  1.58s/it, loss=1968.0000, t=964]
Attacking:  26%|██▋       | 132/500 [03:34<09:42,  1.58s/it, loss=1968.0000, t=972]
Attacking:  27%|██▋       | 133/500 [03:35<10:01,  1.64s/it, loss=1968.0000, t=972]
Attacking:  27%|██▋       | 133/500 [03:36<10:01,  1.64s/it, loss=2016.0000, t=992]
Attacking:  27%|██▋       | 134/500 [03:37<10:03,  1.65s/it, loss=2016.0000, t=992]
Attacking:  27%|██▋       | 134/500 [03:37<10:03,  1.65s/it, loss=1968.0000, t=964]
Attacking:  27%|██▋       | 135/500 [03:38<10:09,  1.67s/it, loss=1968.0000, t=964]
Attacking:  27%|██▋       | 135/500 [03:39<10:09,  1.67s/it, loss=1984.0000, t=972]
Attacking:  27%|██▋       | 136/500 [03:40<10:03,  1.66s/it, loss=1984.0000, t=972]
Attacking:  27%|██▋       | 136/500 [03:41<10:03,  1.66s/it, loss=1944.0000, t=900]
Attacking:  27%|██▋       | 137/500 [03:41<09:51,  1.63s/it, loss=1944.0000, t=900]
Attacking:  27%|██▋       | 137/500 [03:42<09:51,  1.63s/it, loss=2032.0000, t=992]
Attacking:  28%|██▊       | 138/500 [03:43<09:52,  1.64s/it, loss=2032.0000, t=992]
Attacking:  28%|██▊       | 138/500 [03:44<09:52,  1.64s/it, loss=1960.0000, t=952]
Attacking:  28%|██▊       | 139/500 [03:45<09:53,  1.64s/it, loss=1960.0000, t=952]
Attacking:  28%|██▊       | 139/500 [03:45<09:53,  1.64s/it, loss=1984.0000, t=972]
Attacking:  28%|██▊       | 140/500 [03:46<09:44,  1.62s/it, loss=1984.0000, t=972]
Attacking:  28%|██▊       | 140/500 [03:47<09:44,  1.62s/it, loss=1920.0000, t=900]
Attacking:  28%|██▊       | 141/500 [03:48<09:36,  1.61s/it, loss=1920.0000, t=900]
Attacking:  28%|██▊       | 141/500 [03:49<09:36,  1.61s/it, loss=1952.0000, t=912]
Attacking:  28%|██▊       | 142/500 [03:49<09:37,  1.61s/it, loss=1952.0000, t=912]
Attacking:  28%|██▊       | 142/500 [03:50<09:37,  1.61s/it, loss=1984.0000, t=952]
Attacking:  29%|██▊       | 143/500 [03:51<09:33,  1.61s/it, loss=1984.0000, t=952]
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+Max Diff: 0.501961
+Mean Diff: 0.208382
+Saved adversarial image to attacked/images/ship.jpg
+Saved loss curve to attacked/loss_curve/ship_loss.png
+[GPU 6] Stage 3/3: Test
+Loading models for testing ship...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for ship...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 43.62it/s]
+Saved video to attacked/videos/ship.mp4
+Saved frames to attacked/frames/ship
+[GPU 6] Finished ship.jpg
+======================================
+[GPU 6] Processing sportsfield.jpg (Image 43/50)
+======================================
+[GPU 6] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 6] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   3%|▎         | 14/500 [00:22<12:09,  1.50s/it, loss=2240.0000, t=940]
Attacking:   3%|▎         | 15/500 [00:23<12:02,  1.49s/it, loss=2240.0000, t=940]
Attacking:   3%|▎         | 15/500 [00:24<12:02,  1.49s/it, loss=2288.0000, t=984]
Attacking:   3%|▎         | 16/500 [00:25<12:27,  1.54s/it, loss=2288.0000, t=984]
Attacking:   3%|▎         | 16/500 [00:25<12:27,  1.54s/it, loss=2304.0000, t=992]
Attacking:   3%|▎         | 17/500 [00:26<12:25,  1.54s/it, loss=2304.0000, t=992]
Attacking:   3%|▎         | 17/500 [00:27<12:25,  1.54s/it, loss=2256.0000, t=972]
Attacking:   4%|▎         | 18/500 [00:28<12:21,  1.54s/it, loss=2256.0000, t=972]
Attacking:   4%|▎         | 18/500 [00:28<12:21,  1.54s/it, loss=2176.0000, t=912]
Attacking:   4%|▍         | 19/500 [00:29<12:12,  1.52s/it, loss=2176.0000, t=912]
Attacking:   4%|▍         | 19/500 [00:30<12:12,  1.52s/it, loss=2272.0000, t=972]
Attacking:   4%|▍         | 20/500 [00:31<12:11,  1.52s/it, loss=2272.0000, t=972]
Attacking:   4%|▍         | 20/500 [00:31<12:11,  1.52s/it, loss=2192.0000, t=928]
Attacking:   4%|▍         | 21/500 [00:32<12:14,  1.53s/it, loss=2192.0000, t=928]
Attacking:   4%|▍         | 21/500 [00:33<12:14,  1.53s/it, loss=2304.0000, t=1e+3]
Attacking:   4%|▍         | 22/500 [00:34<11:57,  1.50s/it, loss=2304.0000, t=1e+3]
Attacking:   4%|▍         | 22/500 [00:34<11:57,  1.50s/it, loss=2288.0000, t=1e+3]
Attacking:   5%|▍         | 23/500 [00:35<12:09,  1.53s/it, loss=2288.0000, t=1e+3]
Attacking:   5%|▍         | 23/500 [00:36<12:09,  1.53s/it, loss=2160.0000, t=900] 
Attacking:   5%|▍         | 24/500 [00:37<11:57,  1.51s/it, loss=2160.0000, t=900]
Attacking:   5%|▍         | 24/500 [00:37<11:57,  1.51s/it, loss=2256.0000, t=984]
Attacking:   5%|▌         | 25/500 [00:38<11:46,  1.49s/it, loss=2256.0000, t=984]
Attacking:   5%|▌         | 25/500 [00:39<11:46,  1.49s/it, loss=2208.0000, t=964]
Attacking:   5%|▌         | 26/500 [00:40<11:42,  1.48s/it, loss=2208.0000, t=964]
Attacking:   5%|▌         | 26/500 [00:40<11:42,  1.48s/it, loss=2208.0000, t=952]
Attacking:   5%|▌         | 27/500 [00:41<11:50,  1.50s/it, loss=2208.0000, t=952]
Attacking:   5%|▌         | 27/500 [00:42<11:50,  1.50s/it, loss=2256.0000, t=992]
Attacking:   6%|▌         | 28/500 [00:43<11:45,  1.50s/it, loss=2256.0000, t=992]
Attacking:   6%|▌         | 28/500 [00:43<11:45,  1.50s/it, loss=2256.0000, t=992]
Attacking:   6%|▌         | 29/500 [00:44<11:49,  1.51s/it, loss=2256.0000, t=992]
Attacking:   6%|▌         | 29/500 [00:45<11:49,  1.51s/it, loss=2224.0000, t=984]
Attacking:   6%|▌         | 30/500 [00:46<11:56,  1.53s/it, loss=2224.0000, t=984]
Attacking:   6%|▌         | 30/500 [00:46<11:56,  1.53s/it, loss=2192.0000, t=952]
Attacking:   6%|▌         | 31/500 [00:47<11:49,  1.51s/it, loss=2192.0000, t=952]
Attacking:   6%|▌         | 31/500 [00:48<11:49,  1.51s/it, loss=2224.0000, t=984]
Attacking:   6%|▋         | 32/500 [00:49<11:51,  1.52s/it, loss=2224.0000, t=984]
Attacking:   6%|▋         | 32/500 [00:49<11:51,  1.52s/it, loss=2208.0000, t=964]
Attacking:   7%|▋         | 33/500 [00:50<11:37,  1.49s/it, loss=2208.0000, t=964]
Attacking:   7%|▋         | 33/500 [00:51<11:37,  1.49s/it, loss=2144.0000, t=912]
Attacking:   7%|▋         | 34/500 [00:52<11:45,  1.51s/it, loss=2144.0000, t=912]
Attacking:   7%|▋         | 34/500 [00:52<11:45,  1.51s/it, loss=2128.0000, t=900]
Attacking:   7%|▋         | 35/500 [00:53<11:50,  1.53s/it, loss=2128.0000, t=900]
Attacking:   7%|▋         | 35/500 [00:54<11:50,  1.53s/it, loss=2144.0000, t=900]
Attacking:   7%|▋         | 36/500 [00:55<11:51,  1.53s/it, loss=2144.0000, t=900]
Attacking:   7%|▋         | 36/500 [00:55<11:51,  1.53s/it, loss=2160.0000, t=940]
Attacking:   7%|▋         | 37/500 [00:56<11:41,  1.52s/it, loss=2160.0000, t=940]
Attacking:   7%|▋         | 37/500 [00:57<11:41,  1.52s/it, loss=2240.0000, t=1e+3]
Attacking:   8%|▊         | 38/500 [00:58<11:34,  1.50s/it, loss=2240.0000, t=1e+3]
Attacking:   8%|▊         | 38/500 [00:58<11:34,  1.50s/it, loss=2144.0000, t=928] 
Attacking:   8%|▊         | 39/500 [00:59<11:26,  1.49s/it, loss=2144.0000, t=928]
Attacking:   8%|▊         | 39/500 [01:00<11:26,  1.49s/it, loss=2240.0000, t=1e+3]
Attacking:   8%|▊         | 40/500 [01:01<11:33,  1.51s/it, loss=2240.0000, t=1e+3]
Attacking:   8%|▊         | 40/500 [01:01<11:33,  1.51s/it, loss=2160.0000, t=952] 
Attacking:   8%|▊         | 41/500 [01:02<11:28,  1.50s/it, loss=2160.0000, t=952]
Attacking:   8%|▊         | 41/500 [01:03<11:28,  1.50s/it, loss=2112.0000, t=912]
Attacking:   8%|▊         | 42/500 [01:04<11:27,  1.50s/it, loss=2112.0000, t=912]
Attacking:   8%|▊         | 42/500 [01:04<11:27,  1.50s/it, loss=2240.0000, t=1e+3]
Attacking:   9%|▊         | 43/500 [01:05<11:29,  1.51s/it, loss=2240.0000, t=1e+3]
Attacking:   9%|▊         | 43/500 [01:06<11:29,  1.51s/it, loss=2208.0000, t=972] 
Attacking:   9%|▉         | 44/500 [01:07<11:33,  1.52s/it, loss=2208.0000, t=972]
Attacking:   9%|▉         | 44/500 [01:08<11:33,  1.52s/it, loss=2192.0000, t=984]
Attacking:   9%|▉         | 45/500 [01:08<11:29,  1.52s/it, loss=2192.0000, t=984]
Attacking:   9%|▉         | 45/500 [01:09<11:29,  1.52s/it, loss=2192.0000, t=984]
Attacking:   9%|▉         | 46/500 [01:10<11:24,  1.51s/it, loss=2192.0000, t=984]
Attacking:   9%|▉         | 46/500 [01:10<11:24,  1.51s/it, loss=2208.0000, t=1e+3]
Attacking:   9%|▉         | 47/500 [01:11<11:15,  1.49s/it, loss=2208.0000, t=1e+3]
Attacking:   9%|▉         | 47/500 [01:12<11:15,  1.49s/it, loss=2128.0000, t=928] 
Attacking:  10%|▉         | 48/500 [01:13<11:08,  1.48s/it, loss=2128.0000, t=928]
Attacking:  10%|▉         | 48/500 [01:13<11:08,  1.48s/it, loss=2144.0000, t=952]
Attacking:  10%|▉         | 49/500 [01:14<11:13,  1.49s/it, loss=2144.0000, t=952]
Attacking:  10%|▉         | 49/500 [01:15<11:13,  1.49s/it, loss=2112.0000, t=912]
Attacking:  10%|█         | 50/500 [01:16<11:08,  1.49s/it, loss=2112.0000, t=912]
Attacking:  10%|█         | 50/500 [01:16<11:08,  1.49s/it, loss=2144.0000, t=940]
Attacking:  10%|█         | 51/500 [01:17<11:16,  1.51s/it, loss=2144.0000, t=940]
Attacking:  10%|█         | 51/500 [01:18<11:16,  1.51s/it, loss=2128.0000, t=952]
Attacking:  10%|█         | 52/500 [01:19<10:57,  1.47s/it, loss=2128.0000, t=952]
Attacking:  10%|█         | 52/500 [01:19<10:57,  1.47s/it, loss=2176.0000, t=984]
Attacking:  11%|█         | 53/500 [01:20<10:51,  1.46s/it, loss=2176.0000, t=984]
Attacking:  11%|█         | 53/500 [01:21<10:51,  1.46s/it, loss=2112.0000, t=940]
Attacking:  11%|█         | 54/500 [01:22<11:02,  1.49s/it, loss=2112.0000, t=940]
Attacking:  11%|█         | 54/500 [01:22<11:02,  1.49s/it, loss=2144.0000, t=972]
Attacking:  11%|█         | 55/500 [01:23<11:06,  1.50s/it, loss=2144.0000, t=972]
Attacking:  11%|█         | 55/500 [01:24<11:06,  1.50s/it, loss=2080.0000, t=912]
Attacking:  11%|█         | 56/500 [01:25<11:13,  1.52s/it, loss=2080.0000, t=912]
Attacking:  11%|█         | 56/500 [01:25<11:13,  1.52s/it, loss=2144.0000, t=972]
Attacking:  11%|█▏        | 57/500 [01:26<11:08,  1.51s/it, loss=2144.0000, t=972]
Attacking:  11%|█▏        | 57/500 [01:27<11:08,  1.51s/it, loss=2112.0000, t=940]
Attacking:  12%|█▏        | 58/500 [01:28<11:14,  1.53s/it, loss=2112.0000, t=940]
Attacking:  12%|█▏        | 58/500 [01:29<11:14,  1.53s/it, loss=2096.0000, t=928]
Attacking:  12%|█▏        | 59/500 [01:30<11:55,  1.62s/it, loss=2096.0000, t=928]
Attacking:  12%|█▏        | 59/500 [01:30<11:55,  1.62s/it, loss=2192.0000, t=1e+3]
Attacking:  12%|█▏        | 60/500 [01:31<11:45,  1.60s/it, loss=2192.0000, t=1e+3]
Attacking:  12%|█▏        | 60/500 [01:32<11:45,  1.60s/it, loss=2144.0000, t=964] 
Attacking:  12%|█▏        | 61/500 [01:33<11:48,  1.61s/it, loss=2144.0000, t=964]
Attacking:  12%|█▏        | 61/500 [01:34<11:48,  1.61s/it, loss=2144.0000, t=984]
Attacking:  12%|█▏        | 62/500 [01:34<11:46,  1.61s/it, loss=2144.0000, t=984]
Attacking:  12%|█▏        | 62/500 [01:35<11:46,  1.61s/it, loss=2176.0000, t=1e+3]
Attacking:  13%|█▎        | 63/500 [01:36<11:29,  1.58s/it, loss=2176.0000, t=1e+3]
Attacking:  13%|█▎        | 63/500 [01:37<11:29,  1.58s/it, loss=2176.0000, t=992] 
Attacking:  13%|█▎        | 64/500 [01:38<11:37,  1.60s/it, loss=2176.0000, t=992]
Attacking:  13%|█▎        | 64/500 [01:38<11:37,  1.60s/it, loss=2160.0000, t=992]
Attacking:  13%|█▎        | 65/500 [01:39<11:33,  1.59s/it, loss=2160.0000, t=992]
Attacking:  13%|█▎        | 65/500 [01:40<11:33,  1.59s/it, loss=2112.0000, t=940]
Attacking:  13%|█▎        | 66/500 [01:41<11:29,  1.59s/it, loss=2112.0000, t=940]
Attacking:  13%|█▎        | 66/500 [01:42<11:29,  1.59s/it, loss=2144.0000, t=984]
Attacking:  13%|█▎        | 67/500 [01:42<11:39,  1.62s/it, loss=2144.0000, t=984]
Attacking:  13%|█▎        | 67/500 [01:43<11:39,  1.62s/it, loss=2128.0000, t=964]
Attacking:  14%|█▎        | 68/500 [01:44<11:37,  1.61s/it, loss=2128.0000, t=964]
Attacking:  14%|█▎        | 68/500 [01:45<11:37,  1.61s/it, loss=2144.0000, t=972]
Attacking:  14%|█▍        | 69/500 [01:46<11:17,  1.57s/it, loss=2144.0000, t=972]
Attacking:  14%|█▍        | 69/500 [01:46<11:17,  1.57s/it, loss=2080.0000, t=912]
Attacking:  14%|█▍        | 70/500 [01:47<11:11,  1.56s/it, loss=2080.0000, t=912]
Attacking:  14%|█▍        | 70/500 [01:48<11:11,  1.56s/it, loss=2080.0000, t=928]
Attacking:  14%|█▍        | 71/500 [01:49<11:12,  1.57s/it, loss=2080.0000, t=928]
Attacking:  14%|█▍        | 71/500 [01:49<11:12,  1.57s/it, loss=2096.0000, t=940]
Attacking:  14%|█▍        | 72/500 [01:50<11:01,  1.55s/it, loss=2096.0000, t=940]
Attacking:  14%|█▍        | 72/500 [01:51<11:01,  1.55s/it, loss=2160.0000, t=984]
Attacking:  15%|█▍        | 73/500 [01:52<10:55,  1.54s/it, loss=2160.0000, t=984]
Attacking:  15%|█▍        | 73/500 [01:52<10:55,  1.54s/it, loss=2064.0000, t=900]
Attacking:  15%|█▍        | 74/500 [01:53<10:53,  1.53s/it, loss=2064.0000, t=900]
Attacking:  15%|█▍        | 74/500 [01:54<10:53,  1.53s/it, loss=2096.0000, t=952]
Attacking:  15%|█▌        | 75/500 [01:55<10:45,  1.52s/it, loss=2096.0000, t=952]
Attacking:  15%|█▌        | 75/500 [01:55<10:45,  1.52s/it, loss=2128.0000, t=972]
Attacking:  15%|█▌        | 76/500 [01:56<10:40,  1.51s/it, loss=2128.0000, t=972]
Attacking:  15%|█▌        | 76/500 [01:57<10:40,  1.51s/it, loss=2064.0000, t=912]
Attacking:  15%|█▌        | 77/500 [01:58<10:39,  1.51s/it, loss=2064.0000, t=912]
Attacking:  15%|█▌        | 77/500 [01:58<10:39,  1.51s/it, loss=2128.0000, t=964]
Attacking:  16%|█▌        | 78/500 [01:59<10:42,  1.52s/it, loss=2128.0000, t=964]
Attacking:  16%|█▌        | 78/500 [02:00<10:42,  1.52s/it, loss=2112.0000, t=964]
Attacking:  16%|█▌        | 79/500 [02:01<10:39,  1.52s/it, loss=2112.0000, t=964]
Attacking:  16%|█▌        | 79/500 [02:01<10:39,  1.52s/it, loss=2064.0000, t=912]
Attacking:  16%|█▌        | 80/500 [02:02<10:30,  1.50s/it, loss=2064.0000, t=912]
Attacking:  16%|█▌        | 80/500 [02:03<10:30,  1.50s/it, loss=2048.0000, t=900]
Attacking:  16%|█▌        | 81/500 [02:04<10:28,  1.50s/it, loss=2048.0000, t=900]
Attacking:  16%|█▌        | 81/500 [02:04<10:28,  1.50s/it, loss=2080.0000, t=940]
Attacking:  16%|█▋        | 82/500 [02:05<10:19,  1.48s/it, loss=2080.0000, t=940]
Attacking:  16%|█▋        | 82/500 [02:06<10:19,  1.48s/it, loss=2128.0000, t=972]
Attacking:  17%|█▋        | 83/500 [02:07<10:14,  1.47s/it, loss=2128.0000, t=972]
Attacking:  17%|█▋        | 83/500 [02:07<10:14,  1.47s/it, loss=2096.0000, t=940]
Attacking:  17%|█▋        | 84/500 [02:08<10:03,  1.45s/it, loss=2096.0000, t=940]
Attacking:  17%|█▋        | 84/500 [02:09<10:03,  1.45s/it, loss=2096.0000, t=952]
Attacking:  17%|█▋        | 85/500 [02:10<10:09,  1.47s/it, loss=2096.0000, t=952]
Attacking:  17%|█▋        | 85/500 [02:10<10:09,  1.47s/it, loss=2128.0000, t=972]
Attacking:  17%|█▋        | 86/500 [02:11<10:14,  1.48s/it, loss=2128.0000, t=972]
Attacking:  17%|█▋        | 86/500 [02:12<10:14,  1.48s/it, loss=2064.0000, t=912]
Attacking:  17%|█▋        | 87/500 [02:13<10:19,  1.50s/it, loss=2064.0000, t=912]
Attacking:  17%|█▋        | 87/500 [02:13<10:19,  1.50s/it, loss=2128.0000, t=972]
Attacking:  18%|█▊        | 88/500 [02:14<10:15,  1.49s/it, loss=2128.0000, t=972]
Attacking:  18%|█▊        | 88/500 [02:15<10:15,  1.49s/it, loss=2160.0000, t=992]
Attacking:  18%|█▊        | 89/500 [02:16<10:15,  1.50s/it, loss=2160.0000, t=992]
Attacking:  18%|█▊        | 89/500 [02:16<10:15,  1.50s/it, loss=2048.0000, t=900]
Attacking:  18%|█▊        | 90/500 [02:17<10:13,  1.50s/it, loss=2048.0000, t=900]
Attacking:  18%|█▊        | 90/500 [02:18<10:13,  1.50s/it, loss=2096.0000, t=952]
Attacking:  18%|█▊        | 91/500 [02:19<10:27,  1.54s/it, loss=2096.0000, t=952]
Attacking:  18%|█▊        | 91/500 [02:19<10:27,  1.54s/it, loss=2048.0000, t=900]
Attacking:  18%|█▊        | 92/500 [02:20<10:30,  1.55s/it, loss=2048.0000, t=900]
Attacking:  18%|█▊        | 92/500 [02:21<10:30,  1.55s/it, loss=2048.0000, t=900]
Attacking:  19%|█▊        | 93/500 [02:22<10:24,  1.53s/it, loss=2048.0000, t=900]
Attacking:  19%|█▊        | 93/500 [02:22<10:24,  1.53s/it, loss=2080.0000, t=940]
Attacking:  19%|█▉        | 94/500 [02:23<10:13,  1.51s/it, loss=2080.0000, t=940]
Attacking:  19%|█▉        | 94/500 [02:24<10:13,  1.51s/it, loss=2112.0000, t=972]
Attacking:  19%|█▉        | 95/500 [02:25<10:08,  1.50s/it, loss=2112.0000, t=972]
Attacking:  19%|█▉        | 95/500 [02:25<10:08,  1.50s/it, loss=2112.0000, t=972]
Attacking:  19%|█▉        | 96/500 [02:26<10:01,  1.49s/it, loss=2112.0000, t=972]
Attacking:  19%|█▉        | 96/500 [02:27<10:01,  1.49s/it, loss=2064.0000, t=940]
Attacking:  19%|█▉        | 97/500 [02:28<09:51,  1.47s/it, loss=2064.0000, t=940]
Attacking:  19%|█▉        | 97/500 [02:28<09:51,  1.47s/it, loss=2040.0000, t=900]
Attacking:  20%|█▉        | 98/500 [02:29<09:49,  1.47s/it, loss=2040.0000, t=900]
Attacking:  20%|█▉        | 98/500 [02:30<09:49,  1.47s/it, loss=2128.0000, t=984]
Attacking:  20%|█▉        | 99/500 [02:31<10:01,  1.50s/it, loss=2128.0000, t=984]
Attacking:  20%|█▉        | 99/500 [02:31<10:01,  1.50s/it, loss=2112.0000, t=972]
Attacking:  20%|██        | 100/500 [02:32<10:11,  1.53s/it, loss=2112.0000, t=972]
Attacking:  20%|██        | 100/500 [02:33<10:11,  1.53s/it, loss=2080.0000, t=940]
Attacking:  20%|██        | 101/500 [02:34<10:08,  1.52s/it, loss=2080.0000, t=940]
Attacking:  20%|██        | 101/500 [02:34<10:08,  1.52s/it, loss=2144.0000, t=992]
Attacking:  20%|██        | 102/500 [02:35<09:56,  1.50s/it, loss=2144.0000, t=992]
Attacking:  20%|██        | 102/500 [02:36<09:56,  1.50s/it, loss=2048.0000, t=928]
Attacking:  21%|██        | 103/500 [02:37<09:55,  1.50s/it, loss=2048.0000, t=928]
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+Max Diff: 0.501961
+Mean Diff: 0.207282
+Saved adversarial image to attacked/images/sportsfield.jpg
+Saved loss curve to attacked/loss_curve/sportsfield_loss.png
+[GPU 6] Stage 3/3: Test
+Loading models for testing sportsfield...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for sportsfield...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 81.97it/s]
+Saved video to attacked/videos/sportsfield.mp4
+Saved frames to attacked/frames/sportsfield
+[GPU 6] Finished sportsfield.jpg
+======================================
+[GPU 6] Processing stroller.jpg (Image 44/50)
+======================================
+[GPU 6] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 6] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  20%|██        | 100/500 [02:32<09:55,  1.49s/it, loss=2352.0000, t=928]
Attacking:  20%|██        | 100/500 [02:32<09:55,  1.49s/it, loss=2336.0000, t=912]
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Attacking:  21%|██        | 103/500 [02:36<09:56,  1.50s/it, loss=2320.0000, t=900]
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Attacking:  21%|██▏       | 107/500 [02:43<09:51,  1.51s/it, loss=2384.0000, t=972]
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Attacking:  22%|██▏       | 108/500 [02:44<09:48,  1.50s/it, loss=2304.0000, t=900]
Attacking:  22%|██▏       | 109/500 [02:45<09:46,  1.50s/it, loss=2304.0000, t=900]
Attacking:  22%|██▏       | 109/500 [02:46<09:46,  1.50s/it, loss=2368.0000, t=964]
Attacking:  22%|██▏       | 110/500 [02:47<09:58,  1.53s/it, loss=2368.0000, t=964]
Attacking:  22%|██▏       | 110/500 [02:47<09:58,  1.53s/it, loss=2320.0000, t=912]
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Attacking:  23%|██▎       | 115/500 [02:54<09:51,  1.54s/it, loss=2416.0000, t=1e+3]
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Attacking:  24%|██▍       | 119/500 [03:01<09:57,  1.57s/it, loss=2400.0000, t=984]
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Attacking:  25%|██▍       | 123/500 [03:07<09:22,  1.49s/it, loss=2416.0000, t=1e+3]
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Attacking:  26%|██▌       | 128/500 [03:14<09:17,  1.50s/it, loss=2320.0000, t=900]
Attacking:  26%|██▌       | 128/500 [03:15<09:17,  1.50s/it, loss=2320.0000, t=912]
Attacking:  26%|██▌       | 129/500 [03:16<09:10,  1.48s/it, loss=2320.0000, t=912]
Attacking:  26%|██▌       | 129/500 [03:16<09:10,  1.48s/it, loss=2336.0000, t=952]
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Attacking:  26%|██▌       | 130/500 [03:18<09:05,  1.47s/it, loss=2400.0000, t=984]
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+Max Diff: 0.501961
+Mean Diff: 0.268361
+Saved adversarial image to attacked/images/stroller.jpg
+Saved loss curve to attacked/loss_curve/stroller_loss.png
+[GPU 6] Stage 3/3: Test
+Loading models for testing stroller...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for stroller...
+
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+
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+Saved video to attacked/videos/stroller.mp4
+Saved frames to attacked/frames/stroller
+[GPU 6] Finished stroller.jpg
+======================================
+[GPU 6] Processing swing.jpg (Image 45/50)
+======================================
+[GPU 6] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 6] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   3%|▎         | 15/500 [00:23<12:02,  1.49s/it, loss=2272.0000, t=900]
Attacking:   3%|▎         | 16/500 [00:24<12:36,  1.56s/it, loss=2272.0000, t=900]
Attacking:   3%|▎         | 16/500 [00:25<12:36,  1.56s/it, loss=2272.0000, t=964]
Attacking:   3%|▎         | 17/500 [00:26<12:37,  1.57s/it, loss=2272.0000, t=964]
Attacking:   3%|▎         | 17/500 [00:26<12:37,  1.57s/it, loss=2272.0000, t=972]
Attacking:   4%|▎         | 18/500 [00:27<12:18,  1.53s/it, loss=2272.0000, t=972]
Attacking:   4%|▎         | 18/500 [00:28<12:18,  1.53s/it, loss=2272.0000, t=972]
Attacking:   4%|▍         | 19/500 [00:29<12:03,  1.50s/it, loss=2272.0000, t=972]
Attacking:   4%|▍         | 19/500 [00:29<12:03,  1.50s/it, loss=2256.0000, t=964]
Attacking:   4%|▍         | 20/500 [00:30<12:05,  1.51s/it, loss=2256.0000, t=964]
Attacking:   4%|▍         | 20/500 [00:31<12:05,  1.51s/it, loss=2336.0000, t=1e+3]
Attacking:   4%|▍         | 21/500 [00:32<11:53,  1.49s/it, loss=2336.0000, t=1e+3]
Attacking:   4%|▍         | 21/500 [00:32<11:53,  1.49s/it, loss=2304.0000, t=992] 
Attacking:   4%|▍         | 22/500 [00:33<11:49,  1.48s/it, loss=2304.0000, t=992]
Attacking:   4%|▍         | 22/500 [00:34<11:49,  1.48s/it, loss=2336.0000, t=1e+3]
Attacking:   5%|▍         | 23/500 [00:34<11:45,  1.48s/it, loss=2336.0000, t=1e+3]
Attacking:   5%|▍         | 23/500 [00:35<11:45,  1.48s/it, loss=2304.0000, t=1e+3]
Attacking:   5%|▍         | 24/500 [00:36<11:41,  1.47s/it, loss=2304.0000, t=1e+3]
Attacking:   5%|▍         | 24/500 [00:37<11:41,  1.47s/it, loss=2240.0000, t=940] 
Attacking:   5%|▌         | 25/500 [00:37<11:33,  1.46s/it, loss=2240.0000, t=940]
Attacking:   5%|▌         | 25/500 [00:38<11:33,  1.46s/it, loss=2240.0000, t=928]
Attacking:   5%|▌         | 26/500 [00:39<11:43,  1.48s/it, loss=2240.0000, t=928]
Attacking:   5%|▌         | 26/500 [00:40<11:43,  1.48s/it, loss=2240.0000, t=964]
Attacking:   5%|▌         | 27/500 [00:40<11:50,  1.50s/it, loss=2240.0000, t=964]
Attacking:   5%|▌         | 27/500 [00:41<11:50,  1.50s/it, loss=2240.0000, t=940]
Attacking:   6%|▌         | 28/500 [00:42<11:47,  1.50s/it, loss=2240.0000, t=940]
Attacking:   6%|▌         | 28/500 [00:43<11:47,  1.50s/it, loss=2208.0000, t=928]
Attacking:   6%|▌         | 29/500 [00:43<11:44,  1.50s/it, loss=2208.0000, t=928]
Attacking:   6%|▌         | 29/500 [00:44<11:44,  1.50s/it, loss=2224.0000, t=940]
Attacking:   6%|▌         | 30/500 [00:45<11:42,  1.49s/it, loss=2224.0000, t=940]
Attacking:   6%|▌         | 30/500 [00:46<11:42,  1.49s/it, loss=2224.0000, t=900]
Attacking:   6%|▌         | 31/500 [00:46<11:36,  1.49s/it, loss=2224.0000, t=900]
Attacking:   6%|▌         | 31/500 [00:47<11:36,  1.49s/it, loss=2208.0000, t=928]
Attacking:   6%|▋         | 32/500 [00:48<11:28,  1.47s/it, loss=2208.0000, t=928]
Attacking:   6%|▋         | 32/500 [00:49<11:28,  1.47s/it, loss=2208.0000, t=900]
Attacking:   7%|▋         | 33/500 [00:49<11:35,  1.49s/it, loss=2208.0000, t=900]
Attacking:   7%|▋         | 33/500 [00:50<11:35,  1.49s/it, loss=2208.0000, t=940]
Attacking:   7%|▋         | 34/500 [00:51<11:33,  1.49s/it, loss=2208.0000, t=940]
Attacking:   7%|▋         | 34/500 [00:52<11:33,  1.49s/it, loss=2272.0000, t=972]
Attacking:   7%|▋         | 35/500 [00:52<11:40,  1.51s/it, loss=2272.0000, t=972]
Attacking:   7%|▋         | 35/500 [00:53<11:40,  1.51s/it, loss=2208.0000, t=928]
Attacking:   7%|▋         | 36/500 [00:54<11:31,  1.49s/it, loss=2208.0000, t=928]
Attacking:   7%|▋         | 36/500 [00:54<11:31,  1.49s/it, loss=2240.0000, t=964]
Attacking:   7%|▋         | 37/500 [00:55<11:25,  1.48s/it, loss=2240.0000, t=964]
Attacking:   7%|▋         | 37/500 [00:56<11:25,  1.48s/it, loss=2208.0000, t=900]
Attacking:   8%|▊         | 38/500 [00:57<11:34,  1.50s/it, loss=2208.0000, t=900]
Attacking:   8%|▊         | 38/500 [00:58<11:34,  1.50s/it, loss=2256.0000, t=984]
Attacking:   8%|▊         | 39/500 [00:58<11:40,  1.52s/it, loss=2256.0000, t=984]
Attacking:   8%|▊         | 39/500 [00:59<11:40,  1.52s/it, loss=2272.0000, t=992]
Attacking:   8%|▊         | 40/500 [01:00<11:34,  1.51s/it, loss=2272.0000, t=992]
Attacking:   8%|▊         | 40/500 [01:01<11:34,  1.51s/it, loss=2192.0000, t=940]
Attacking:   8%|▊         | 41/500 [01:01<11:32,  1.51s/it, loss=2192.0000, t=940]
Attacking:   8%|▊         | 41/500 [01:02<11:32,  1.51s/it, loss=2224.0000, t=964]
Attacking:   8%|▊         | 42/500 [01:03<11:26,  1.50s/it, loss=2224.0000, t=964]
Attacking:   8%|▊         | 42/500 [01:04<11:26,  1.50s/it, loss=2304.0000, t=1e+3]
Attacking:   9%|▊         | 43/500 [01:04<11:34,  1.52s/it, loss=2304.0000, t=1e+3]
Attacking:   9%|▊         | 43/500 [01:05<11:34,  1.52s/it, loss=2224.0000, t=984] 
Attacking:   9%|▉         | 44/500 [01:06<11:45,  1.55s/it, loss=2224.0000, t=984]
Attacking:   9%|▉         | 44/500 [01:07<11:45,  1.55s/it, loss=2208.0000, t=972]
Attacking:   9%|▉         | 45/500 [01:08<11:44,  1.55s/it, loss=2208.0000, t=972]
Attacking:   9%|▉         | 45/500 [01:08<11:44,  1.55s/it, loss=2208.0000, t=972]
Attacking:   9%|▉         | 46/500 [01:09<11:38,  1.54s/it, loss=2208.0000, t=972]
Attacking:   9%|▉         | 46/500 [01:10<11:38,  1.54s/it, loss=2208.0000, t=952]
Attacking:   9%|▉         | 47/500 [01:11<11:34,  1.53s/it, loss=2208.0000, t=952]
Attacking:   9%|▉         | 47/500 [01:11<11:34,  1.53s/it, loss=2192.0000, t=900]
Attacking:  10%|▉         | 48/500 [01:12<11:29,  1.53s/it, loss=2192.0000, t=900]
Attacking:  10%|▉         | 48/500 [01:13<11:29,  1.53s/it, loss=2176.0000, t=940]
Attacking:  10%|▉         | 49/500 [01:14<11:26,  1.52s/it, loss=2176.0000, t=940]
Attacking:  10%|▉         | 49/500 [01:14<11:26,  1.52s/it, loss=2176.0000, t=940]
Attacking:  10%|█         | 50/500 [01:15<11:19,  1.51s/it, loss=2176.0000, t=940]
Attacking:  10%|█         | 50/500 [01:16<11:19,  1.51s/it, loss=2176.0000, t=940]
Attacking:  10%|█         | 51/500 [01:17<11:14,  1.50s/it, loss=2176.0000, t=940]
Attacking:  10%|█         | 51/500 [01:17<11:14,  1.50s/it, loss=2176.0000, t=952]
Attacking:  10%|█         | 52/500 [01:18<11:22,  1.52s/it, loss=2176.0000, t=952]
Attacking:  10%|█         | 52/500 [01:19<11:22,  1.52s/it, loss=2176.0000, t=928]
Attacking:  11%|█         | 53/500 [01:20<11:30,  1.55s/it, loss=2176.0000, t=928]
Attacking:  11%|█         | 53/500 [01:20<11:30,  1.55s/it, loss=2160.0000, t=928]
Attacking:  11%|█         | 54/500 [01:21<11:25,  1.54s/it, loss=2160.0000, t=928]
Attacking:  11%|█         | 54/500 [01:22<11:25,  1.54s/it, loss=2176.0000, t=940]
Attacking:  11%|█         | 55/500 [01:23<11:24,  1.54s/it, loss=2176.0000, t=940]
Attacking:  11%|█         | 55/500 [01:24<11:24,  1.54s/it, loss=2176.0000, t=972]
Attacking:  11%|█         | 56/500 [01:24<11:22,  1.54s/it, loss=2176.0000, t=972]
Attacking:  11%|█         | 56/500 [01:25<11:22,  1.54s/it, loss=2176.0000, t=972]
Attacking:  11%|█▏        | 57/500 [01:26<11:15,  1.52s/it, loss=2176.0000, t=972]
Attacking:  11%|█▏        | 57/500 [01:27<11:15,  1.52s/it, loss=2240.0000, t=1e+3]
Attacking:  12%|█▏        | 58/500 [01:27<11:15,  1.53s/it, loss=2240.0000, t=1e+3]
Attacking:  12%|█▏        | 58/500 [01:28<11:15,  1.53s/it, loss=2160.0000, t=912] 
Attacking:  12%|█▏        | 59/500 [01:29<11:44,  1.60s/it, loss=2160.0000, t=912]
Attacking:  12%|█▏        | 59/500 [01:30<11:44,  1.60s/it, loss=2192.0000, t=984]
Attacking:  12%|█▏        | 60/500 [01:31<11:38,  1.59s/it, loss=2192.0000, t=984]
Attacking:  12%|█▏        | 60/500 [01:31<11:38,  1.59s/it, loss=2144.0000, t=928]
Attacking:  12%|█▏        | 61/500 [01:32<11:26,  1.56s/it, loss=2144.0000, t=928]
Attacking:  12%|█▏        | 61/500 [01:33<11:26,  1.56s/it, loss=2144.0000, t=952]
Attacking:  12%|█▏        | 62/500 [01:34<11:15,  1.54s/it, loss=2144.0000, t=952]
Attacking:  12%|█▏        | 62/500 [01:34<11:15,  1.54s/it, loss=2144.0000, t=900]
Attacking:  13%|█▎        | 63/500 [01:35<11:02,  1.52s/it, loss=2144.0000, t=900]
Attacking:  13%|█▎        | 63/500 [01:36<11:02,  1.52s/it, loss=2144.0000, t=964]
Attacking:  13%|█▎        | 64/500 [01:37<10:48,  1.49s/it, loss=2144.0000, t=964]
Attacking:  13%|█▎        | 64/500 [01:37<10:48,  1.49s/it, loss=2144.0000, t=928]
Attacking:  13%|█▎        | 65/500 [01:38<10:47,  1.49s/it, loss=2144.0000, t=928]
Attacking:  13%|█▎        | 65/500 [01:39<10:47,  1.49s/it, loss=2144.0000, t=900]
Attacking:  13%|█▎        | 66/500 [01:40<10:45,  1.49s/it, loss=2144.0000, t=900]
Attacking:  13%|█▎        | 66/500 [01:40<10:45,  1.49s/it, loss=2144.0000, t=912]
Attacking:  13%|█▎        | 67/500 [01:41<10:57,  1.52s/it, loss=2144.0000, t=912]
Attacking:  13%|█▎        | 67/500 [01:42<10:57,  1.52s/it, loss=2224.0000, t=1e+3]
Attacking:  14%|█▎        | 68/500 [01:43<11:04,  1.54s/it, loss=2224.0000, t=1e+3]
Attacking:  14%|█▎        | 68/500 [01:43<11:04,  1.54s/it, loss=2144.0000, t=940] 
Attacking:  14%|█▍        | 69/500 [01:44<10:57,  1.53s/it, loss=2144.0000, t=940]
Attacking:  14%|█▍        | 69/500 [01:45<10:57,  1.53s/it, loss=2128.0000, t=912]
Attacking:  14%|█▍        | 70/500 [01:46<10:44,  1.50s/it, loss=2128.0000, t=912]
Attacking:  14%|█▍        | 70/500 [01:46<10:44,  1.50s/it, loss=2128.0000, t=928]
Attacking:  14%|█▍        | 71/500 [01:47<10:42,  1.50s/it, loss=2128.0000, t=928]
Attacking:  14%|█▍        | 71/500 [01:48<10:42,  1.50s/it, loss=2144.0000, t=928]
Attacking:  14%|█▍        | 72/500 [01:49<10:45,  1.51s/it, loss=2144.0000, t=928]
Attacking:  14%|█▍        | 72/500 [01:49<10:45,  1.51s/it, loss=2128.0000, t=900]
Attacking:  15%|█▍        | 73/500 [01:50<10:46,  1.51s/it, loss=2128.0000, t=900]
Attacking:  15%|█▍        | 73/500 [01:51<10:46,  1.51s/it, loss=2144.0000, t=952]
Attacking:  15%|█▍        | 74/500 [01:52<10:33,  1.49s/it, loss=2144.0000, t=952]
Attacking:  15%|█▍        | 74/500 [01:52<10:33,  1.49s/it, loss=2128.0000, t=928]
Attacking:  15%|█▌        | 75/500 [01:53<10:26,  1.47s/it, loss=2128.0000, t=928]
Attacking:  15%|█▌        | 75/500 [01:54<10:26,  1.47s/it, loss=2208.0000, t=992]
Attacking:  15%|█▌        | 76/500 [01:55<10:19,  1.46s/it, loss=2208.0000, t=992]
Attacking:  15%|█▌        | 76/500 [01:55<10:19,  1.46s/it, loss=2128.0000, t=900]
Attacking:  15%|█▌        | 77/500 [01:56<10:17,  1.46s/it, loss=2128.0000, t=900]
Attacking:  15%|█▌        | 77/500 [01:57<10:17,  1.46s/it, loss=2176.0000, t=984]
Attacking:  16%|█▌        | 78/500 [01:58<10:19,  1.47s/it, loss=2176.0000, t=984]
Attacking:  16%|█▌        | 78/500 [01:58<10:19,  1.47s/it, loss=2112.0000, t=900]
Attacking:  16%|█▌        | 79/500 [01:59<10:20,  1.47s/it, loss=2112.0000, t=900]
Attacking:  16%|█▌        | 79/500 [02:00<10:20,  1.47s/it, loss=2128.0000, t=940]
Attacking:  16%|█▌        | 80/500 [02:00<10:20,  1.48s/it, loss=2128.0000, t=940]
Attacking:  16%|█▌        | 80/500 [02:01<10:20,  1.48s/it, loss=2128.0000, t=952]
Attacking:  16%|█▌        | 81/500 [02:02<10:33,  1.51s/it, loss=2128.0000, t=952]
Attacking:  16%|█▌        | 81/500 [02:03<10:33,  1.51s/it, loss=2144.0000, t=972]
Attacking:  16%|█▋        | 82/500 [02:04<10:47,  1.55s/it, loss=2144.0000, t=972]
Attacking:  16%|█▋        | 82/500 [02:04<10:47,  1.55s/it, loss=2112.0000, t=912]
Attacking:  17%|█▋        | 83/500 [02:05<10:53,  1.57s/it, loss=2112.0000, t=912]
Attacking:  17%|█▋        | 83/500 [02:06<10:53,  1.57s/it, loss=2208.0000, t=992]
Attacking:  17%|█▋        | 84/500 [02:07<10:50,  1.56s/it, loss=2208.0000, t=992]
Attacking:  17%|█▋        | 84/500 [02:08<10:50,  1.56s/it, loss=2128.0000, t=952]
Attacking:  17%|█▋        | 85/500 [02:08<10:39,  1.54s/it, loss=2128.0000, t=952]
Attacking:  17%|█▋        | 85/500 [02:09<10:39,  1.54s/it, loss=2144.0000, t=952]
Attacking:  17%|█▋        | 86/500 [02:10<10:36,  1.54s/it, loss=2144.0000, t=952]
Attacking:  17%|█▋        | 86/500 [02:11<10:36,  1.54s/it, loss=2192.0000, t=992]
Attacking:  17%|█▋        | 87/500 [02:11<10:37,  1.54s/it, loss=2192.0000, t=992]
Attacking:  17%|█▋        | 87/500 [02:12<10:37,  1.54s/it, loss=2128.0000, t=952]
Attacking:  18%|█▊        | 88/500 [02:13<10:40,  1.55s/it, loss=2128.0000, t=952]
Attacking:  18%|█▊        | 88/500 [02:14<10:40,  1.55s/it, loss=2160.0000, t=984]
Attacking:  18%|█▊        | 89/500 [02:15<10:43,  1.57s/it, loss=2160.0000, t=984]
Attacking:  18%|█▊        | 89/500 [02:15<10:43,  1.57s/it, loss=2128.0000, t=952]
Attacking:  18%|█▊        | 90/500 [02:16<10:34,  1.55s/it, loss=2128.0000, t=952]
Attacking:  18%|█▊        | 90/500 [02:17<10:34,  1.55s/it, loss=2128.0000, t=952]
Attacking:  18%|█▊        | 91/500 [02:18<10:34,  1.55s/it, loss=2128.0000, t=952]
Attacking:  18%|█▊        | 91/500 [02:18<10:34,  1.55s/it, loss=2128.0000, t=972]
Attacking:  18%|█▊        | 92/500 [02:19<10:34,  1.56s/it, loss=2128.0000, t=972]
Attacking:  18%|█▊        | 92/500 [02:20<10:34,  1.56s/it, loss=2128.0000, t=952]
Attacking:  19%|█▊        | 93/500 [02:21<10:43,  1.58s/it, loss=2128.0000, t=952]
Attacking:  19%|█▊        | 93/500 [02:22<10:43,  1.58s/it, loss=2192.0000, t=992]
Attacking:  19%|█▉        | 94/500 [02:22<10:32,  1.56s/it, loss=2192.0000, t=992]
Attacking:  19%|█▉        | 94/500 [02:23<10:32,  1.56s/it, loss=2144.0000, t=984]
Attacking:  19%|█▉        | 95/500 [02:24<10:27,  1.55s/it, loss=2144.0000, t=984]
Attacking:  19%|█▉        | 95/500 [02:25<10:27,  1.55s/it, loss=2192.0000, t=1e+3]
Attacking:  19%|█▉        | 96/500 [02:25<10:14,  1.52s/it, loss=2192.0000, t=1e+3]
Attacking:  19%|█▉        | 96/500 [02:26<10:14,  1.52s/it, loss=2144.0000, t=984] 
Attacking:  19%|█▉        | 97/500 [02:27<10:10,  1.52s/it, loss=2144.0000, t=984]
Attacking:  19%|█▉        | 97/500 [02:28<10:10,  1.52s/it, loss=2128.0000, t=952]
Attacking:  20%|█▉        | 98/500 [02:28<10:17,  1.54s/it, loss=2128.0000, t=952]
Attacking:  20%|█▉        | 98/500 [02:29<10:17,  1.54s/it, loss=2112.0000, t=952]
Attacking:  20%|█▉        | 99/500 [02:30<10:16,  1.54s/it, loss=2112.0000, t=952]
Attacking:  20%|█▉        | 99/500 [02:31<10:16,  1.54s/it, loss=2112.0000, t=952]
Attacking:  20%|██        | 100/500 [02:32<10:17,  1.54s/it, loss=2112.0000, t=952]
Attacking:  20%|██        | 100/500 [02:32<10:17,  1.54s/it, loss=2160.0000, t=984]
Attacking:  20%|██        | 101/500 [02:33<10:12,  1.54s/it, loss=2160.0000, t=984]
Attacking:  20%|██        | 101/500 [02:34<10:12,  1.54s/it, loss=2112.0000, t=900]
Attacking:  20%|██        | 102/500 [02:35<10:11,  1.54s/it, loss=2112.0000, t=900]
Attacking:  20%|██        | 102/500 [02:35<10:11,  1.54s/it, loss=2160.0000, t=984]
Attacking:  21%|██        | 103/500 [02:36<10:09,  1.53s/it, loss=2160.0000, t=984]
Attacking:  21%|██        | 103/500 [02:37<10:09,  1.53s/it, loss=2112.0000, t=928]
Attacking:  21%|██        | 104/500 [02:38<10:14,  1.55s/it, loss=2112.0000, t=928]
Attacking:  21%|██        | 104/500 [02:38<10:14,  1.55s/it, loss=2096.0000, t=940]
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+Max Diff: 0.501961
+Mean Diff: 0.256086
+Saved adversarial image to attacked/images/swing.jpg
+Saved loss curve to attacked/loss_curve/swing_loss.png
+[GPU 6] Stage 3/3: Test
+Loading models for testing swing...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for swing...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 87.18it/s]
+Saved video to attacked/videos/swing.mp4
+Saved frames to attacked/frames/swing
+[GPU 6] Finished swing.jpg
+======================================
+[GPU 6] Processing tandem.jpg (Image 46/50)
+======================================
+[GPU 6] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 6] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  12%|█▏        | 62/500 [01:36<11:19,  1.55s/it, loss=2112.0000, t=992]
Attacking:  13%|█▎        | 63/500 [01:37<11:27,  1.57s/it, loss=2112.0000, t=992]
Attacking:  13%|█▎        | 63/500 [01:37<11:27,  1.57s/it, loss=2040.0000, t=900]
Attacking:  13%|█▎        | 64/500 [01:38<11:33,  1.59s/it, loss=2040.0000, t=900]
Attacking:  13%|█▎        | 64/500 [01:39<11:33,  1.59s/it, loss=2112.0000, t=984]
Attacking:  13%|█▎        | 65/500 [01:40<11:36,  1.60s/it, loss=2112.0000, t=984]
Attacking:  13%|█▎        | 65/500 [01:41<11:36,  1.60s/it, loss=2032.0000, t=912]
Attacking:  13%|█▎        | 66/500 [01:41<11:29,  1.59s/it, loss=2032.0000, t=912]
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Attacking:  13%|█▎        | 67/500 [01:43<11:20,  1.57s/it, loss=2016.0000, t=900]
Attacking:  13%|█▎        | 67/500 [01:44<11:20,  1.57s/it, loss=2080.0000, t=964]
Attacking:  14%|█▎        | 68/500 [01:45<11:15,  1.56s/it, loss=2080.0000, t=964]
Attacking:  14%|█▎        | 68/500 [01:45<11:15,  1.56s/it, loss=2048.0000, t=952]
Attacking:  14%|█▍        | 69/500 [01:46<11:07,  1.55s/it, loss=2048.0000, t=952]
Attacking:  14%|█▍        | 69/500 [01:47<11:07,  1.55s/it, loss=2112.0000, t=992]
Attacking:  14%|█▍        | 70/500 [01:48<11:10,  1.56s/it, loss=2112.0000, t=992]
Attacking:  14%|█▍        | 70/500 [01:48<11:10,  1.56s/it, loss=2096.0000, t=992]
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Attacking:  15%|█▌        | 76/500 [01:57<10:43,  1.52s/it, loss=2008.0000, t=900]
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Attacking:  15%|█▌        | 77/500 [01:58<10:39,  1.51s/it, loss=2040.0000, t=928]
Attacking:  15%|█▌        | 77/500 [01:59<10:39,  1.51s/it, loss=2096.0000, t=992]
Attacking:  16%|█▌        | 78/500 [02:00<10:29,  1.49s/it, loss=2096.0000, t=992]
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Attacking:  16%|█▌        | 79/500 [02:01<10:37,  1.51s/it, loss=2016.0000, t=912]
Attacking:  16%|█▌        | 79/500 [02:02<10:37,  1.51s/it, loss=2040.0000, t=952]
Attacking:  16%|█▌        | 80/500 [02:03<10:41,  1.53s/it, loss=2040.0000, t=952]
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Attacking:  16%|█▌        | 81/500 [02:05<10:41,  1.53s/it, loss=2024.0000, t=928]
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Attacking:  16%|█▋        | 82/500 [02:06<10:34,  1.52s/it, loss=2032.0000, t=928]
Attacking:  17%|█▋        | 83/500 [02:07<10:36,  1.53s/it, loss=2032.0000, t=928]
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Attacking:  17%|█▋        | 84/500 [02:09<10:18,  1.49s/it, loss=2096.0000, t=992]
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Attacking:  17%|█▋        | 85/500 [02:11<10:34,  1.53s/it, loss=2064.0000, t=1e+3]
Attacking:  17%|█▋        | 86/500 [02:12<10:43,  1.55s/it, loss=2064.0000, t=1e+3]
Attacking:  17%|█▋        | 86/500 [02:13<10:43,  1.55s/it, loss=2032.0000, t=952] 
Attacking:  17%|█▋        | 87/500 [02:14<10:42,  1.56s/it, loss=2032.0000, t=952]
Attacking:  17%|█▋        | 87/500 [02:14<10:42,  1.56s/it, loss=2008.0000, t=912]
Attacking:  18%|█▊        | 88/500 [02:15<10:30,  1.53s/it, loss=2008.0000, t=912]
Attacking:  18%|█▊        | 88/500 [02:16<10:30,  1.53s/it, loss=2016.0000, t=928]
Attacking:  18%|█▊        | 89/500 [02:16<10:24,  1.52s/it, loss=2016.0000, t=928]
Attacking:  18%|█▊        | 89/500 [02:17<10:24,  1.52s/it, loss=2064.0000, t=1e+3]
Attacking:  18%|█▊        | 90/500 [02:18<10:20,  1.51s/it, loss=2064.0000, t=1e+3]
Attacking:  18%|█▊        | 90/500 [02:19<10:20,  1.51s/it, loss=2080.0000, t=992] 
Attacking:  18%|█▊        | 91/500 [02:19<10:09,  1.49s/it, loss=2080.0000, t=992]
Attacking:  18%|█▊        | 91/500 [02:20<10:09,  1.49s/it, loss=2048.0000, t=972]
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Attacking:  18%|█▊        | 92/500 [02:22<10:04,  1.48s/it, loss=2064.0000, t=1e+3]
Attacking:  19%|█▊        | 93/500 [02:22<10:04,  1.49s/it, loss=2064.0000, t=1e+3]
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Attacking:  19%|█▉        | 94/500 [02:25<10:11,  1.51s/it, loss=2080.0000, t=992]
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Attacking:  19%|█▉        | 95/500 [02:26<10:07,  1.50s/it, loss=2048.0000, t=972]
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Attacking:  19%|█▉        | 96/500 [02:28<10:06,  1.50s/it, loss=2064.0000, t=984]
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Attacking:  20%|█▉        | 99/500 [02:32<10:18,  1.54s/it, loss=2008.0000, t=912]
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Attacking:  20%|██        | 100/500 [02:33<10:09,  1.52s/it, loss=2016.0000, t=940]
Attacking:  20%|██        | 100/500 [02:34<10:09,  1.52s/it, loss=2080.0000, t=984]
Attacking:  20%|██        | 101/500 [02:35<10:09,  1.53s/it, loss=2080.0000, t=984]
Attacking:  20%|██        | 101/500 [02:35<10:09,  1.53s/it, loss=2008.0000, t=928]
Attacking:  20%|██        | 102/500 [02:36<10:00,  1.51s/it, loss=2008.0000, t=928]
Attacking:  20%|██        | 102/500 [02:37<10:00,  1.51s/it, loss=1992.0000, t=900]
Attacking:  21%|██        | 103/500 [02:38<09:49,  1.49s/it, loss=1992.0000, t=900]
Attacking:  21%|██        | 103/500 [02:38<09:49,  1.49s/it, loss=2032.0000, t=964]
Attacking:  21%|██        | 104/500 [02:39<09:41,  1.47s/it, loss=2032.0000, t=964]
Attacking:  21%|██        | 104/500 [02:40<09:41,  1.47s/it, loss=1992.0000, t=900]
Attacking:  21%|██        | 105/500 [02:40<09:40,  1.47s/it, loss=1992.0000, t=900]
Attacking:  21%|██        | 105/500 [02:41<09:40,  1.47s/it, loss=1992.0000, t=900]
Attacking:  21%|██        | 106/500 [02:42<09:38,  1.47s/it, loss=1992.0000, t=900]
Attacking:  21%|██        | 106/500 [02:43<09:38,  1.47s/it, loss=1984.0000, t=900]
Attacking:  21%|██▏       | 107/500 [02:43<09:40,  1.48s/it, loss=1984.0000, t=900]
Attacking:  21%|██▏       | 107/500 [02:44<09:40,  1.48s/it, loss=1984.0000, t=912]
Attacking:  22%|██▏       | 108/500 [02:45<09:39,  1.48s/it, loss=1984.0000, t=912]
Attacking:  22%|██▏       | 108/500 [02:46<09:39,  1.48s/it, loss=2032.0000, t=972]
Attacking:  22%|██▏       | 109/500 [02:46<09:50,  1.51s/it, loss=2032.0000, t=972]
Attacking:  22%|██▏       | 109/500 [02:47<09:50,  1.51s/it, loss=2064.0000, t=984]
Attacking:  22%|██▏       | 110/500 [02:48<09:55,  1.53s/it, loss=2064.0000, t=984]
Attacking:  22%|██▏       | 110/500 [02:49<09:55,  1.53s/it, loss=1984.0000, t=900]
Attacking:  22%|██▏       | 111/500 [02:49<09:49,  1.51s/it, loss=1984.0000, t=900]
Attacking:  22%|██▏       | 111/500 [02:50<09:49,  1.51s/it, loss=2064.0000, t=984]
Attacking:  22%|██▏       | 112/500 [02:51<09:55,  1.53s/it, loss=2064.0000, t=984]
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Attacking:  23%|██▎       | 113/500 [02:53<10:08,  1.57s/it, loss=2008.0000, t=952]
Attacking:  23%|██▎       | 113/500 [02:53<10:08,  1.57s/it, loss=2000.0000, t=928]
Attacking:  23%|██▎       | 114/500 [02:54<10:06,  1.57s/it, loss=2000.0000, t=928]
Attacking:  23%|██▎       | 114/500 [02:55<10:06,  1.57s/it, loss=2032.0000, t=972]
Attacking:  23%|██▎       | 115/500 [02:56<10:05,  1.57s/it, loss=2032.0000, t=972]
Attacking:  23%|██▎       | 115/500 [02:57<10:05,  1.57s/it, loss=2024.0000, t=964]
Attacking:  23%|██▎       | 116/500 [02:57<10:03,  1.57s/it, loss=2024.0000, t=964]
Attacking:  23%|██▎       | 116/500 [02:58<10:03,  1.57s/it, loss=2032.0000, t=964]
Attacking:  23%|██▎       | 117/500 [02:59<09:49,  1.54s/it, loss=2032.0000, t=964]
Attacking:  23%|██▎       | 117/500 [03:00<09:49,  1.54s/it, loss=2024.0000, t=964]
Attacking:  24%|██▎       | 118/500 [03:00<09:50,  1.55s/it, loss=2024.0000, t=964]
Attacking:  24%|██▎       | 118/500 [03:01<09:50,  1.55s/it, loss=2008.0000, t=952]
Attacking:  24%|██▍       | 119/500 [03:02<09:51,  1.55s/it, loss=2008.0000, t=952]
Attacking:  24%|██▍       | 119/500 [03:03<09:51,  1.55s/it, loss=2064.0000, t=992]
Attacking:  24%|██▍       | 120/500 [03:04<09:59,  1.58s/it, loss=2064.0000, t=992]
Attacking:  24%|██▍       | 120/500 [03:04<09:59,  1.58s/it, loss=2000.0000, t=940]
Attacking:  24%|██▍       | 121/500 [03:05<09:47,  1.55s/it, loss=2000.0000, t=940]
Attacking:  24%|██▍       | 121/500 [03:06<09:47,  1.55s/it, loss=1976.0000, t=900]
Attacking:  24%|██▍       | 122/500 [03:07<09:35,  1.52s/it, loss=1976.0000, t=900]
Attacking:  24%|██▍       | 122/500 [03:07<09:35,  1.52s/it, loss=2016.0000, t=964]
Attacking:  25%|██▍       | 123/500 [03:08<09:34,  1.52s/it, loss=2016.0000, t=964]
Attacking:  25%|██▍       | 123/500 [03:09<09:34,  1.52s/it, loss=1984.0000, t=928]
Attacking:  25%|██▍       | 124/500 [03:10<09:39,  1.54s/it, loss=1984.0000, t=928]
Attacking:  25%|██▍       | 124/500 [03:10<09:39,  1.54s/it, loss=2032.0000, t=964]
Attacking:  25%|██▌       | 125/500 [03:11<09:36,  1.54s/it, loss=2032.0000, t=964]
Attacking:  25%|██▌       | 125/500 [03:12<09:36,  1.54s/it, loss=1976.0000, t=900]
Attacking:  25%|██▌       | 126/500 [03:13<09:40,  1.55s/it, loss=1976.0000, t=900]
Attacking:  25%|██▌       | 126/500 [03:13<09:40,  1.55s/it, loss=2064.0000, t=1e+3]
Attacking:  25%|██▌       | 127/500 [03:14<09:33,  1.54s/it, loss=2064.0000, t=1e+3]
Attacking:  25%|██▌       | 127/500 [03:15<09:33,  1.54s/it, loss=2040.0000, t=1e+3]
Attacking:  26%|██▌       | 128/500 [03:16<09:29,  1.53s/it, loss=2040.0000, t=1e+3]
Attacking:  26%|██▌       | 128/500 [03:17<09:29,  1.53s/it, loss=1984.0000, t=928] 
Attacking:  26%|██▌       | 129/500 [03:17<09:31,  1.54s/it, loss=1984.0000, t=928]
Attacking:  26%|██▌       | 129/500 [03:18<09:31,  1.54s/it, loss=1992.0000, t=928]
Attacking:  26%|██▌       | 130/500 [03:19<09:29,  1.54s/it, loss=1992.0000, t=928]
Attacking:  26%|██▌       | 130/500 [03:20<09:29,  1.54s/it, loss=2008.0000, t=940]
Attacking:  26%|██▌       | 131/500 [03:20<09:22,  1.52s/it, loss=2008.0000, t=940]
Attacking:  26%|██▌       | 131/500 [03:21<09:22,  1.52s/it, loss=1984.0000, t=900]
Attacking:  26%|██▋       | 132/500 [03:22<09:23,  1.53s/it, loss=1984.0000, t=900]
Attacking:  26%|██▋       | 132/500 [03:23<09:23,  1.53s/it, loss=2016.0000, t=952]
Attacking:  27%|██▋       | 133/500 [03:24<09:27,  1.55s/it, loss=2016.0000, t=952]
Attacking:  27%|██▋       | 133/500 [03:24<09:27,  1.55s/it, loss=2032.0000, t=1e+3]
Attacking:  27%|██▋       | 134/500 [03:25<09:24,  1.54s/it, loss=2032.0000, t=1e+3]
Attacking:  27%|██▋       | 134/500 [03:26<09:24,  1.54s/it, loss=2016.0000, t=972] 
Attacking:  27%|██▋       | 135/500 [03:27<09:20,  1.54s/it, loss=2016.0000, t=972]
Attacking:  27%|██▋       | 135/500 [03:27<09:20,  1.54s/it, loss=2032.0000, t=1e+3]
Attacking:  27%|██▋       | 136/500 [03:28<09:13,  1.52s/it, loss=2032.0000, t=1e+3]
Attacking:  27%|██▋       | 136/500 [03:29<09:13,  1.52s/it, loss=1976.0000, t=912] 
Attacking:  27%|██▋       | 137/500 [03:30<09:16,  1.53s/it, loss=1976.0000, t=912]
Attacking:  27%|██▋       | 137/500 [03:30<09:16,  1.53s/it, loss=1984.0000, t=928]
Attacking:  28%|██▊       | 138/500 [03:31<09:11,  1.52s/it, loss=1984.0000, t=928]
Attacking:  28%|██▊       | 138/500 [03:32<09:11,  1.52s/it, loss=1984.0000, t=940]
Attacking:  28%|██▊       | 139/500 [03:33<09:04,  1.51s/it, loss=1984.0000, t=940]
Attacking:  28%|██▊       | 139/500 [03:33<09:04,  1.51s/it, loss=1984.0000, t=940]
Attacking:  28%|██▊       | 140/500 [03:34<09:01,  1.50s/it, loss=1984.0000, t=940]
Attacking:  28%|██▊       | 140/500 [03:35<09:01,  1.50s/it, loss=1984.0000, t=940]
Attacking:  28%|██▊       | 141/500 [03:36<08:50,  1.48s/it, loss=1984.0000, t=940]
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Attacking:  28%|██▊       | 142/500 [03:38<09:03,  1.52s/it, loss=2048.0000, t=984]
Attacking:  29%|██▊       | 143/500 [03:39<09:13,  1.55s/it, loss=2048.0000, t=984]
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Attacking:  29%|██▉       | 144/500 [03:40<09:04,  1.53s/it, loss=2048.0000, t=992]
Attacking:  29%|██▉       | 144/500 [03:41<09:04,  1.53s/it, loss=1976.0000, t=900]
Attacking:  29%|██▉       | 145/500 [03:42<09:04,  1.53s/it, loss=1976.0000, t=900]
Attacking:  29%|██▉       | 145/500 [03:43<09:04,  1.53s/it, loss=2016.0000, t=964]
Attacking:  29%|██▉       | 146/500 [03:43<09:11,  1.56s/it, loss=2016.0000, t=964]
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Attacking:  30%|██▉       | 148/500 [03:46<08:50,  1.51s/it, loss=1984.0000, t=940]
Attacking:  30%|██▉       | 148/500 [03:47<08:50,  1.51s/it, loss=1960.0000, t=900]
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Attacking:  90%|█████████ | 450/500 [11:33<01:19,  1.59s/it, loss=2000.0000, t=992]
Attacking:  90%|█████████ | 451/500 [11:34<01:17,  1.57s/it, loss=2000.0000, t=992]
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Attacking:  91%|█████████ | 455/500 [11:40<01:09,  1.55s/it, loss=1936.0000, t=940]
Attacking:  91%|█████████ | 455/500 [11:41<01:09,  1.55s/it, loss=1968.0000, t=972]
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Attacking:  91%|█████████▏| 457/500 [11:44<01:05,  1.53s/it, loss=1928.0000, t=928]
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Attacking:  92%|█████████▏| 462/500 [11:51<00:57,  1.50s/it, loss=2000.0000, t=992]
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Attacking:  96%|█████████▌| 479/500 [12:19<00:34,  1.62s/it, loss=1952.0000, t=964]
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Attacking:  96%|█████████▌| 481/500 [12:22<00:30,  1.60s/it, loss=1904.0000, t=900]
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Attacking:  97%|█████████▋| 483/500 [12:24<00:28,  1.65s/it, loss=1984.0000, t=1e+3]
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Attacking:  97%|█████████▋| 487/500 [12:32<00:21,  1.65s/it, loss=2000.0000, t=992]
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+Max Diff: 0.501961
+Mean Diff: 0.231930
+Saved adversarial image to attacked/images/tandem.jpg
+Saved loss curve to attacked/loss_curve/tandem_loss.png
+[GPU 6] Stage 3/3: Test
+Loading models for testing tandem...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for tandem...
+
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+
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 39.68it/s]
+Saved video to attacked/videos/tandem.mp4
+Saved frames to attacked/frames/tandem
+[GPU 6] Finished tandem.jpg
+======================================
+[GPU 6] Processing tennis-vest.jpg (Image 47/50)
+======================================
+[GPU 6] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 6] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   5%|▍         | 24/500 [00:37<12:07,  1.53s/it, loss=2352.0000, t=972]
Attacking:   5%|▍         | 24/500 [00:38<12:07,  1.53s/it, loss=2400.0000, t=1e+3]
Attacking:   5%|▌         | 25/500 [00:38<11:54,  1.51s/it, loss=2400.0000, t=1e+3]
Attacking:   5%|▌         | 25/500 [00:39<11:54,  1.51s/it, loss=2288.0000, t=900] 
Attacking:   5%|▌         | 26/500 [00:40<11:50,  1.50s/it, loss=2288.0000, t=900]
Attacking:   5%|▌         | 26/500 [00:41<11:50,  1.50s/it, loss=2352.0000, t=984]
Attacking:   5%|▌         | 27/500 [00:41<11:40,  1.48s/it, loss=2352.0000, t=984]
Attacking:   5%|▌         | 27/500 [00:42<11:40,  1.48s/it, loss=2304.0000, t=940]
Attacking:   6%|▌         | 28/500 [00:43<11:35,  1.47s/it, loss=2304.0000, t=940]
Attacking:   6%|▌         | 28/500 [00:43<11:35,  1.47s/it, loss=2320.0000, t=952]
Attacking:   6%|▌         | 29/500 [00:44<11:25,  1.45s/it, loss=2320.0000, t=952]
Attacking:   6%|▌         | 29/500 [00:45<11:25,  1.45s/it, loss=2288.0000, t=912]
Attacking:   6%|▌         | 30/500 [00:46<11:29,  1.47s/it, loss=2288.0000, t=912]
Attacking:   6%|▌         | 30/500 [00:46<11:29,  1.47s/it, loss=2320.0000, t=952]
Attacking:   6%|▌         | 31/500 [00:47<11:30,  1.47s/it, loss=2320.0000, t=952]
Attacking:   6%|▌         | 31/500 [00:48<11:30,  1.47s/it, loss=2400.0000, t=1e+3]
Attacking:   6%|▋         | 32/500 [00:49<11:31,  1.48s/it, loss=2400.0000, t=1e+3]
Attacking:   6%|▋         | 32/500 [00:49<11:31,  1.48s/it, loss=2368.0000, t=1e+3]
Attacking:   7%|▋         | 33/500 [00:50<11:30,  1.48s/it, loss=2368.0000, t=1e+3]
Attacking:   7%|▋         | 33/500 [00:51<11:30,  1.48s/it, loss=2304.0000, t=952] 
Attacking:   7%|▋         | 34/500 [00:52<11:25,  1.47s/it, loss=2304.0000, t=952]
Attacking:   7%|▋         | 34/500 [00:52<11:25,  1.47s/it, loss=2304.0000, t=964]
Attacking:   7%|▋         | 35/500 [00:53<11:32,  1.49s/it, loss=2304.0000, t=964]
Attacking:   7%|▋         | 35/500 [00:54<11:32,  1.49s/it, loss=2288.0000, t=952]
Attacking:   7%|▋         | 36/500 [00:55<11:32,  1.49s/it, loss=2288.0000, t=952]
Attacking:   7%|▋         | 36/500 [00:55<11:32,  1.49s/it, loss=2320.0000, t=972]
Attacking:   7%|▋         | 37/500 [00:56<11:32,  1.50s/it, loss=2320.0000, t=972]
Attacking:   7%|▋         | 37/500 [00:57<11:32,  1.50s/it, loss=2320.0000, t=984]
Attacking:   8%|▊         | 38/500 [00:58<11:42,  1.52s/it, loss=2320.0000, t=984]
Attacking:   8%|▊         | 38/500 [00:58<11:42,  1.52s/it, loss=2320.0000, t=972]
Attacking:   8%|▊         | 39/500 [00:59<11:21,  1.48s/it, loss=2320.0000, t=972]
Attacking:   8%|▊         | 39/500 [01:00<11:21,  1.48s/it, loss=2320.0000, t=984]
Attacking:   8%|▊         | 40/500 [01:01<11:21,  1.48s/it, loss=2320.0000, t=984]
Attacking:   8%|▊         | 40/500 [01:01<11:21,  1.48s/it, loss=2336.0000, t=992]
Attacking:   8%|▊         | 41/500 [01:02<11:30,  1.50s/it, loss=2336.0000, t=992]
Attacking:   8%|▊         | 41/500 [01:03<11:30,  1.50s/it, loss=2240.0000, t=900]
Attacking:   8%|▊         | 42/500 [01:04<11:37,  1.52s/it, loss=2240.0000, t=900]
Attacking:   8%|▊         | 42/500 [01:04<11:37,  1.52s/it, loss=2272.0000, t=940]
Attacking:   9%|▊         | 43/500 [01:05<11:36,  1.53s/it, loss=2272.0000, t=940]
Attacking:   9%|▊         | 43/500 [01:06<11:36,  1.53s/it, loss=2240.0000, t=912]
Attacking:   9%|▉         | 44/500 [01:07<11:54,  1.57s/it, loss=2240.0000, t=912]
Attacking:   9%|▉         | 44/500 [01:08<11:54,  1.57s/it, loss=2320.0000, t=992]
Attacking:   9%|▉         | 45/500 [01:08<11:46,  1.55s/it, loss=2320.0000, t=992]
Attacking:   9%|▉         | 45/500 [01:09<11:46,  1.55s/it, loss=2288.0000, t=984]
Attacking:   9%|▉         | 46/500 [01:10<11:43,  1.55s/it, loss=2288.0000, t=984]
Attacking:   9%|▉         | 46/500 [01:11<11:43,  1.55s/it, loss=2336.0000, t=1e+3]
Attacking:   9%|▉         | 47/500 [01:12<11:38,  1.54s/it, loss=2336.0000, t=1e+3]
Attacking:   9%|▉         | 47/500 [01:12<11:38,  1.54s/it, loss=2304.0000, t=992] 
Attacking:  10%|▉         | 48/500 [01:13<11:23,  1.51s/it, loss=2304.0000, t=992]
Attacking:  10%|▉         | 48/500 [01:14<11:23,  1.51s/it, loss=2256.0000, t=900]
Attacking:  10%|▉         | 49/500 [01:15<11:29,  1.53s/it, loss=2256.0000, t=900]
Attacking:  10%|▉         | 49/500 [01:15<11:29,  1.53s/it, loss=2240.0000, t=912]
Attacking:  10%|█         | 50/500 [01:16<11:31,  1.54s/it, loss=2240.0000, t=912]
Attacking:  10%|█         | 50/500 [01:17<11:31,  1.54s/it, loss=2256.0000, t=952]
Attacking:  10%|█         | 51/500 [01:18<11:31,  1.54s/it, loss=2256.0000, t=952]
Attacking:  10%|█         | 51/500 [01:18<11:31,  1.54s/it, loss=2288.0000, t=984]
Attacking:  10%|█         | 52/500 [01:19<11:26,  1.53s/it, loss=2288.0000, t=984]
Attacking:  10%|█         | 52/500 [01:20<11:26,  1.53s/it, loss=2304.0000, t=992]
Attacking:  11%|█         | 53/500 [01:21<11:23,  1.53s/it, loss=2304.0000, t=992]
Attacking:  11%|█         | 53/500 [01:21<11:23,  1.53s/it, loss=2256.0000, t=952]
Attacking:  11%|█         | 54/500 [01:22<11:16,  1.52s/it, loss=2256.0000, t=952]
Attacking:  11%|█         | 54/500 [01:23<11:16,  1.52s/it, loss=2272.0000, t=984]
Attacking:  11%|█         | 55/500 [01:24<11:08,  1.50s/it, loss=2272.0000, t=984]
Attacking:  11%|█         | 55/500 [01:24<11:08,  1.50s/it, loss=2272.0000, t=984]
Attacking:  11%|█         | 56/500 [01:25<10:59,  1.48s/it, loss=2272.0000, t=984]
Attacking:  11%|█         | 56/500 [01:26<10:59,  1.48s/it, loss=2272.0000, t=972]
Attacking:  11%|█▏        | 57/500 [01:27<10:51,  1.47s/it, loss=2272.0000, t=972]
Attacking:  11%|█▏        | 57/500 [01:27<10:51,  1.47s/it, loss=2224.0000, t=928]
Attacking:  12%|█▏        | 58/500 [01:28<10:52,  1.48s/it, loss=2224.0000, t=928]
Attacking:  12%|█▏        | 58/500 [01:29<10:52,  1.48s/it, loss=2272.0000, t=972]
Attacking:  12%|█▏        | 59/500 [01:30<11:05,  1.51s/it, loss=2272.0000, t=972]
Attacking:  12%|█▏        | 59/500 [01:30<11:05,  1.51s/it, loss=2208.0000, t=900]
Attacking:  12%|█▏        | 60/500 [01:31<10:55,  1.49s/it, loss=2208.0000, t=900]
Attacking:  12%|█▏        | 60/500 [01:32<10:55,  1.49s/it, loss=2256.0000, t=964]
Attacking:  12%|█▏        | 61/500 [01:32<10:44,  1.47s/it, loss=2256.0000, t=964]
Attacking:  12%|█▏        | 61/500 [01:33<10:44,  1.47s/it, loss=2208.0000, t=912]
Attacking:  12%|█▏        | 62/500 [01:34<10:33,  1.45s/it, loss=2208.0000, t=912]
Attacking:  12%|█▏        | 62/500 [01:35<10:33,  1.45s/it, loss=2240.0000, t=952]
Attacking:  13%|█▎        | 63/500 [01:35<10:42,  1.47s/it, loss=2240.0000, t=952]
Attacking:  13%|█▎        | 63/500 [01:36<10:42,  1.47s/it, loss=2272.0000, t=992]
Attacking:  13%|█▎        | 64/500 [01:37<10:40,  1.47s/it, loss=2272.0000, t=992]
Attacking:  13%|█▎        | 64/500 [01:37<10:40,  1.47s/it, loss=2208.0000, t=928]
Attacking:  13%|█▎        | 65/500 [01:38<10:42,  1.48s/it, loss=2208.0000, t=928]
Attacking:  13%|█▎        | 65/500 [01:39<10:42,  1.48s/it, loss=2240.0000, t=964]
Attacking:  13%|█▎        | 66/500 [01:40<10:47,  1.49s/it, loss=2240.0000, t=964]
Attacking:  13%|█▎        | 66/500 [01:41<10:47,  1.49s/it, loss=2208.0000, t=928]
Attacking:  13%|█▎        | 67/500 [01:41<10:50,  1.50s/it, loss=2208.0000, t=928]
Attacking:  13%|█▎        | 67/500 [01:42<10:50,  1.50s/it, loss=2224.0000, t=952]
Attacking:  14%|█▎        | 68/500 [01:43<10:48,  1.50s/it, loss=2224.0000, t=952]
Attacking:  14%|█▎        | 68/500 [01:44<10:48,  1.50s/it, loss=2272.0000, t=992]
Attacking:  14%|█▍        | 69/500 [01:44<10:59,  1.53s/it, loss=2272.0000, t=992]
Attacking:  14%|█▍        | 69/500 [01:45<10:59,  1.53s/it, loss=2256.0000, t=972]
Attacking:  14%|█▍        | 70/500 [01:46<10:58,  1.53s/it, loss=2256.0000, t=972]
Attacking:  14%|█▍        | 70/500 [01:47<10:58,  1.53s/it, loss=2240.0000, t=964]
Attacking:  14%|█▍        | 71/500 [01:48<10:55,  1.53s/it, loss=2240.0000, t=964]
Attacking:  14%|█▍        | 71/500 [01:48<10:55,  1.53s/it, loss=2208.0000, t=940]
Attacking:  14%|█▍        | 72/500 [01:49<10:47,  1.51s/it, loss=2208.0000, t=940]
Attacking:  14%|█▍        | 72/500 [01:50<10:47,  1.51s/it, loss=2240.0000, t=964]
Attacking:  15%|█▍        | 73/500 [01:51<10:47,  1.52s/it, loss=2240.0000, t=964]
Attacking:  15%|█▍        | 73/500 [01:51<10:47,  1.52s/it, loss=2192.0000, t=928]
Attacking:  15%|█▍        | 74/500 [01:52<10:42,  1.51s/it, loss=2192.0000, t=928]
Attacking:  15%|█▍        | 74/500 [01:53<10:42,  1.51s/it, loss=2272.0000, t=1e+3]
Attacking:  15%|█▌        | 75/500 [01:54<10:45,  1.52s/it, loss=2272.0000, t=1e+3]
Attacking:  15%|█▌        | 75/500 [01:54<10:45,  1.52s/it, loss=2256.0000, t=992] 
Attacking:  15%|█▌        | 76/500 [01:55<10:52,  1.54s/it, loss=2256.0000, t=992]
Attacking:  15%|█▌        | 76/500 [01:56<10:52,  1.54s/it, loss=2208.0000, t=940]
Attacking:  15%|█▌        | 77/500 [01:57<11:03,  1.57s/it, loss=2208.0000, t=940]
Attacking:  15%|█▌        | 77/500 [01:58<11:03,  1.57s/it, loss=2240.0000, t=972]
Attacking:  16%|█▌        | 78/500 [01:58<11:00,  1.57s/it, loss=2240.0000, t=972]
Attacking:  16%|█▌        | 78/500 [01:59<11:00,  1.57s/it, loss=2192.0000, t=912]
Attacking:  16%|█▌        | 79/500 [02:00<10:44,  1.53s/it, loss=2192.0000, t=912]
Attacking:  16%|█▌        | 79/500 [02:00<10:44,  1.53s/it, loss=2272.0000, t=1e+3]
Attacking:  16%|█▌        | 80/500 [02:01<10:36,  1.52s/it, loss=2272.0000, t=1e+3]
Attacking:  16%|█▌        | 80/500 [02:02<10:36,  1.52s/it, loss=2192.0000, t=928] 
Attacking:  16%|█▌        | 81/500 [02:03<10:38,  1.52s/it, loss=2192.0000, t=928]
Attacking:  16%|█▌        | 81/500 [02:04<10:38,  1.52s/it, loss=2176.0000, t=912]
Attacking:  16%|█▋        | 82/500 [02:04<10:38,  1.53s/it, loss=2176.0000, t=912]
Attacking:  16%|█▋        | 82/500 [02:05<10:38,  1.53s/it, loss=2176.0000, t=900]
Attacking:  17%|█▋        | 83/500 [02:06<10:30,  1.51s/it, loss=2176.0000, t=900]
Attacking:  17%|█▋        | 83/500 [02:06<10:30,  1.51s/it, loss=2208.0000, t=964]
Attacking:  17%|█▋        | 84/500 [02:07<10:22,  1.50s/it, loss=2208.0000, t=964]
Attacking:  17%|█▋        | 84/500 [02:08<10:22,  1.50s/it, loss=2224.0000, t=964]
Attacking:  17%|█▋        | 85/500 [02:09<10:24,  1.51s/it, loss=2224.0000, t=964]
Attacking:  17%|█▋        | 85/500 [02:09<10:24,  1.51s/it, loss=2176.0000, t=900]
Attacking:  17%|█▋        | 86/500 [02:10<10:18,  1.49s/it, loss=2176.0000, t=900]
Attacking:  17%|█▋        | 86/500 [02:11<10:18,  1.49s/it, loss=2192.0000, t=912]
Attacking:  17%|█▋        | 87/500 [02:12<10:09,  1.48s/it, loss=2192.0000, t=912]
Attacking:  17%|█▋        | 87/500 [02:12<10:09,  1.48s/it, loss=2224.0000, t=984]
Attacking:  18%|█▊        | 88/500 [02:13<10:03,  1.46s/it, loss=2224.0000, t=984]
Attacking:  18%|█▊        | 88/500 [02:14<10:03,  1.46s/it, loss=2240.0000, t=992]
Attacking:  18%|█▊        | 89/500 [02:15<10:00,  1.46s/it, loss=2240.0000, t=992]
Attacking:  18%|█▊        | 89/500 [02:15<10:00,  1.46s/it, loss=2192.0000, t=952]
Attacking:  18%|█▊        | 90/500 [02:16<09:54,  1.45s/it, loss=2192.0000, t=952]
Attacking:  18%|█▊        | 90/500 [02:17<09:54,  1.45s/it, loss=2208.0000, t=952]
Attacking:  18%|█▊        | 91/500 [02:18<10:13,  1.50s/it, loss=2208.0000, t=952]
Attacking:  18%|█▊        | 91/500 [02:18<10:13,  1.50s/it, loss=2176.0000, t=928]
Attacking:  18%|█▊        | 92/500 [02:19<10:08,  1.49s/it, loss=2176.0000, t=928]
Attacking:  18%|█▊        | 92/500 [02:20<10:08,  1.49s/it, loss=2208.0000, t=952]
Attacking:  19%|█▊        | 93/500 [02:21<10:03,  1.48s/it, loss=2208.0000, t=952]
Attacking:  19%|█▊        | 93/500 [02:21<10:03,  1.48s/it, loss=2224.0000, t=984]
Attacking:  19%|█▉        | 94/500 [02:22<10:01,  1.48s/it, loss=2224.0000, t=984]
Attacking:  19%|█▉        | 94/500 [02:23<10:01,  1.48s/it, loss=2224.0000, t=972]
Attacking:  19%|█▉        | 95/500 [02:24<10:03,  1.49s/it, loss=2224.0000, t=972]
Attacking:  19%|█▉        | 95/500 [02:24<10:03,  1.49s/it, loss=2176.0000, t=912]
Attacking:  19%|█▉        | 96/500 [02:25<10:00,  1.49s/it, loss=2176.0000, t=912]
Attacking:  19%|█▉        | 96/500 [02:26<10:00,  1.49s/it, loss=2256.0000, t=1e+3]
Attacking:  19%|█▉        | 97/500 [02:27<10:01,  1.49s/it, loss=2256.0000, t=1e+3]
Attacking:  19%|█▉        | 97/500 [02:27<10:01,  1.49s/it, loss=2208.0000, t=972] 
Attacking:  20%|█▉        | 98/500 [02:28<09:50,  1.47s/it, loss=2208.0000, t=972]
Attacking:  20%|█▉        | 98/500 [02:29<09:50,  1.47s/it, loss=2208.0000, t=964]
Attacking:  20%|█▉        | 99/500 [02:29<09:49,  1.47s/it, loss=2208.0000, t=964]
Attacking:  20%|█▉        | 99/500 [02:30<09:49,  1.47s/it, loss=2160.0000, t=900]
Attacking:  20%|██        | 100/500 [02:31<09:54,  1.49s/it, loss=2160.0000, t=900]
Attacking:  20%|██        | 100/500 [02:32<09:54,  1.49s/it, loss=2176.0000, t=940]
Attacking:  20%|██        | 101/500 [02:33<10:00,  1.50s/it, loss=2176.0000, t=940]
Attacking:  20%|██        | 101/500 [02:33<10:00,  1.50s/it, loss=2240.0000, t=992]
Attacking:  20%|██        | 102/500 [02:34<10:11,  1.54s/it, loss=2240.0000, t=992]
Attacking:  20%|██        | 102/500 [02:35<10:11,  1.54s/it, loss=2192.0000, t=940]
Attacking:  21%|██        | 103/500 [02:36<10:13,  1.54s/it, loss=2192.0000, t=940]
Attacking:  21%|██        | 103/500 [02:37<10:13,  1.54s/it, loss=2160.0000, t=912]
Attacking:  21%|██        | 104/500 [02:37<10:24,  1.58s/it, loss=2160.0000, t=912]
Attacking:  21%|██        | 104/500 [02:38<10:24,  1.58s/it, loss=2192.0000, t=940]
Attacking:  21%|██        | 105/500 [02:39<10:21,  1.57s/it, loss=2192.0000, t=940]
Attacking:  21%|██        | 105/500 [02:40<10:21,  1.57s/it, loss=2160.0000, t=900]
Attacking:  21%|██        | 106/500 [02:41<10:35,  1.61s/it, loss=2160.0000, t=900]
Attacking:  21%|██        | 106/500 [02:41<10:35,  1.61s/it, loss=2208.0000, t=964]
Attacking:  21%|██▏       | 107/500 [02:42<10:34,  1.62s/it, loss=2208.0000, t=964]
Attacking:  21%|██▏       | 107/500 [02:43<10:34,  1.62s/it, loss=2208.0000, t=964]
Attacking:  22%|██▏       | 108/500 [02:44<10:23,  1.59s/it, loss=2208.0000, t=964]
Attacking:  22%|██▏       | 108/500 [02:44<10:23,  1.59s/it, loss=2192.0000, t=952]
Attacking:  22%|██▏       | 109/500 [02:45<10:16,  1.58s/it, loss=2192.0000, t=952]
Attacking:  22%|██▏       | 109/500 [02:46<10:16,  1.58s/it, loss=2192.0000, t=952]
Attacking:  22%|██▏       | 110/500 [02:47<10:18,  1.58s/it, loss=2192.0000, t=952]
Attacking:  22%|██▏       | 110/500 [02:48<10:18,  1.58s/it, loss=2160.0000, t=912]
Attacking:  22%|██▏       | 111/500 [02:48<10:12,  1.57s/it, loss=2160.0000, t=912]
Attacking:  22%|██▏       | 111/500 [02:49<10:12,  1.57s/it, loss=2256.0000, t=1e+3]
Attacking:  22%|██▏       | 112/500 [02:50<09:57,  1.54s/it, loss=2256.0000, t=1e+3]
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Attacking: 100%|██████████| 500/500 [12:48<00:00,  1.54s/it, loss=2112.0000, t=940]
+Max Diff: 0.501961
+Mean Diff: 0.246148
+Saved adversarial image to attacked/images/tennis-vest.jpg
+Saved loss curve to attacked/loss_curve/tennis-vest_loss.png
+[GPU 6] Stage 3/3: Test
+Loading models for testing tennis-vest...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for tennis-vest...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
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Saving video: 100%|██████████| 17/17 [00:00<00:00, 72.50it/s]
+Saved video to attacked/videos/tennis-vest.mp4
+Saved frames to attacked/frames/tennis-vest
+[GPU 6] Finished tennis-vest.jpg
+======================================
+[GPU 6] Processing train.jpg (Image 48/50)
+======================================
+[GPU 6] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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+Saved to cache/
+[GPU 6] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:  20%|██        | 100/500 [02:33<10:12,  1.53s/it, loss=1768.0000, t=952]
Attacking:  20%|██        | 100/500 [02:34<10:12,  1.53s/it, loss=1760.0000, t=940]
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Attacking:  23%|██▎       | 113/500 [02:53<09:32,  1.48s/it, loss=1736.0000, t=912]
Attacking:  23%|██▎       | 113/500 [02:53<09:32,  1.48s/it, loss=1728.0000, t=900]
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Attacking:  23%|██▎       | 115/500 [02:56<09:28,  1.48s/it, loss=1744.0000, t=940]
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Attacking:  23%|██▎       | 116/500 [02:58<09:19,  1.46s/it, loss=1736.0000, t=912]
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Attacking:  23%|██▎       | 117/500 [02:59<09:34,  1.50s/it, loss=1792.0000, t=992]
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Attacking:  25%|██▌       | 127/500 [03:15<09:39,  1.55s/it, loss=1776.0000, t=1e+3]
Attacking:  26%|██▌       | 128/500 [03:16<09:34,  1.55s/it, loss=1776.0000, t=1e+3]
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Attacking:  27%|██▋       | 134/500 [03:26<09:24,  1.54s/it, loss=1760.0000, t=1e+3]
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Attacking:  27%|██▋       | 135/500 [03:27<09:14,  1.52s/it, loss=1760.0000, t=1e+3]
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\ No newline at end of file
diff --git a/experiments/cfg3_eps64/logs/gpu_7.log b/experiments/cfg3_eps64/logs/gpu_7.log
new file mode 100644
index 0000000000000000000000000000000000000000..d18beb54d16844dfb0553a9e810c8dd160105cdd
--- /dev/null
+++ b/experiments/cfg3_eps64/logs/gpu_7.log
@@ -0,0 +1,75 @@
+[GPU 7] Starting work on images 49 to 49
+======================================
+[GPU 7] Processing violin.jpg (Image 49/50)
+======================================
+[GPU 7] Stage 1/3: Preprocess
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+
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100%|██████████| 25/25 [00:34<00:00,  1.36s/it]
+Saved to cache/
+[GPU 7] Stage 2/3: Attack
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Loading cached data...
+Loaded successfully!
+
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Attacking:   9%|▉         | 45/500 [01:14<12:43,  1.68s/it, loss=2256.0000, t=928]
Attacking:   9%|▉         | 45/500 [01:15<12:43,  1.68s/it, loss=2256.0000, t=928]
Attacking:   9%|▉         | 46/500 [01:16<12:51,  1.70s/it, loss=2256.0000, t=928]
Attacking:   9%|▉         | 46/500 [01:17<12:51,  1.70s/it, loss=2320.0000, t=992]
Attacking:   9%|▉         | 47/500 [01:18<12:41,  1.68s/it, loss=2320.0000, t=992]
Attacking:   9%|▉         | 47/500 [01:19<12:41,  1.68s/it, loss=2272.0000, t=952]
Attacking:  10%|▉         | 48/500 [01:19<12:30,  1.66s/it, loss=2272.0000, t=952]
Attacking:  10%|▉         | 48/500 [01:20<12:30,  1.66s/it, loss=2320.0000, t=1e+3]
Attacking:  10%|▉         | 49/500 [01:21<12:23,  1.65s/it, loss=2320.0000, t=1e+3]
Attacking:  10%|▉         | 49/500 [01:22<12:23,  1.65s/it, loss=2304.0000, t=1e+3]
Attacking:  10%|█         | 50/500 [01:23<12:06,  1.61s/it, loss=2304.0000, t=1e+3]
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Attacking:  10%|█         | 51/500 [01:24<12:08,  1.62s/it, loss=2256.0000, t=912]
Attacking:  10%|█         | 51/500 [01:25<12:08,  1.62s/it, loss=2224.0000, t=900]
Attacking:  10%|█         | 52/500 [01:26<12:13,  1.64s/it, loss=2224.0000, t=900]
Attacking:  10%|█         | 52/500 [01:27<12:13,  1.64s/it, loss=2256.0000, t=940]
Attacking:  11%|█         | 53/500 [01:28<12:14,  1.64s/it, loss=2256.0000, t=940]
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Attacking:  11%|█         | 54/500 [01:29<12:16,  1.65s/it, loss=2224.0000, t=912]
Attacking:  11%|█         | 54/500 [01:30<12:16,  1.65s/it, loss=2272.0000, t=984]
Attacking:  11%|█         | 55/500 [01:31<12:17,  1.66s/it, loss=2272.0000, t=984]
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Attacking:  11%|█▏        | 57/500 [01:35<11:46,  1.59s/it, loss=2272.0000, t=972]
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Attacking:  12%|█▏        | 59/500 [01:37<12:16,  1.67s/it, loss=2256.0000, t=952]
Attacking:  12%|█▏        | 59/500 [01:38<12:16,  1.67s/it, loss=2224.0000, t=900]
Attacking:  12%|█▏        | 60/500 [01:39<11:52,  1.62s/it, loss=2224.0000, t=900]
Attacking:  12%|█▏        | 60/500 [01:40<11:52,  1.62s/it, loss=2240.0000, t=952]
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Attacking:  12%|█▏        | 62/500 [01:43<12:03,  1.65s/it, loss=2224.0000, t=928]
Attacking:  13%|█▎        | 63/500 [01:44<12:04,  1.66s/it, loss=2224.0000, t=928]
Attacking:  13%|█▎        | 63/500 [01:45<12:04,  1.66s/it, loss=2304.0000, t=992]
Attacking:  13%|█▎        | 64/500 [01:46<12:11,  1.68s/it, loss=2304.0000, t=992]
Attacking:  13%|█▎        | 64/500 [01:46<12:11,  1.68s/it, loss=2256.0000, t=984]
Attacking:  13%|█▎        | 65/500 [01:47<12:01,  1.66s/it, loss=2256.0000, t=984]
Attacking:  13%|█▎        | 65/500 [01:48<12:01,  1.66s/it, loss=2224.0000, t=912]
Attacking:  13%|█▎        | 66/500 [01:49<12:07,  1.68s/it, loss=2224.0000, t=912]
Attacking:  13%|█▎        | 66/500 [01:50<12:07,  1.68s/it, loss=2208.0000, t=912]
Attacking:  13%|█▎        | 67/500 [01:51<12:08,  1.68s/it, loss=2208.0000, t=912]
Attacking:  13%|█▎        | 67/500 [01:52<12:08,  1.68s/it, loss=2240.0000, t=964]
Attacking:  14%|█▎        | 68/500 [01:53<12:22,  1.72s/it, loss=2240.0000, t=964]
Attacking:  14%|█▎        | 68/500 [01:53<12:22,  1.72s/it, loss=2240.0000, t=984]
Attacking:  14%|█▍        | 69/500 [01:54<12:38,  1.76s/it, loss=2240.0000, t=984]
Attacking:  14%|█▍        | 69/500 [01:55<12:38,  1.76s/it, loss=2208.0000, t=912]
Attacking:  14%|█▍        | 70/500 [01:56<12:24,  1.73s/it, loss=2208.0000, t=912]
Attacking:  14%|█▍        | 70/500 [01:57<12:24,  1.73s/it, loss=2272.0000, t=1e+3]
Attacking:  14%|█▍        | 71/500 [01:58<12:21,  1.73s/it, loss=2272.0000, t=1e+3]
Attacking:  14%|█▍        | 71/500 [01:58<12:21,  1.73s/it, loss=2208.0000, t=900] 
Attacking:  14%|█▍        | 72/500 [01:59<12:04,  1.69s/it, loss=2208.0000, t=900]
Attacking:  14%|█▍        | 72/500 [02:00<12:04,  1.69s/it, loss=2240.0000, t=984]
Attacking:  15%|█▍        | 73/500 [02:01<11:30,  1.62s/it, loss=2240.0000, t=984]
Attacking:  15%|█▍        | 73/500 [02:02<11:30,  1.62s/it, loss=2240.0000, t=964]
Attacking:  15%|█▍        | 74/500 [02:03<11:40,  1.64s/it, loss=2240.0000, t=964]
Attacking:  15%|█▍        | 74/500 [02:03<11:40,  1.64s/it, loss=2288.0000, t=1e+3]
Attacking:  15%|█▌        | 75/500 [02:04<11:21,  1.60s/it, loss=2288.0000, t=1e+3]
Attacking:  15%|█▌        | 75/500 [02:05<11:21,  1.60s/it, loss=2224.0000, t=952] 
Attacking:  15%|█▌        | 76/500 [02:06<11:06,  1.57s/it, loss=2224.0000, t=952]
Attacking:  15%|█▌        | 76/500 [02:06<11:06,  1.57s/it, loss=2240.0000, t=964]
Attacking:  15%|█▌        | 77/500 [02:07<11:13,  1.59s/it, loss=2240.0000, t=964]
Attacking:  15%|█▌        | 77/500 [02:08<11:13,  1.59s/it, loss=2272.0000, t=1e+3]
Attacking:  16%|█▌        | 78/500 [02:09<11:10,  1.59s/it, loss=2272.0000, t=1e+3]
Attacking:  16%|█▌        | 78/500 [02:10<11:10,  1.59s/it, loss=2256.0000, t=992] 
Attacking:  16%|█▌        | 79/500 [02:10<11:14,  1.60s/it, loss=2256.0000, t=992]
Attacking:  16%|█▌        | 79/500 [02:11<11:14,  1.60s/it, loss=2240.0000, t=992]
Attacking:  16%|█▌        | 80/500 [02:12<11:05,  1.58s/it, loss=2240.0000, t=992]
Attacking:  16%|█▌        | 80/500 [02:13<11:05,  1.58s/it, loss=2240.0000, t=984]
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Attacking:  16%|█▌        | 81/500 [02:14<11:07,  1.59s/it, loss=2240.0000, t=972]
Attacking:  16%|█▋        | 82/500 [02:15<11:21,  1.63s/it, loss=2240.0000, t=972]
Attacking:  16%|█▋        | 82/500 [02:16<11:21,  1.63s/it, loss=2256.0000, t=1e+3]
Attacking:  17%|█▋        | 83/500 [02:17<11:10,  1.61s/it, loss=2256.0000, t=1e+3]
Attacking:  17%|█▋        | 83/500 [02:18<11:10,  1.61s/it, loss=2224.0000, t=984] 
Attacking:  17%|█▋        | 84/500 [02:18<11:12,  1.62s/it, loss=2224.0000, t=984]
Attacking:  17%|█▋        | 84/500 [02:19<11:12,  1.62s/it, loss=2192.0000, t=900]
Attacking:  17%|█▋        | 85/500 [02:20<10:51,  1.57s/it, loss=2192.0000, t=900]
Attacking:  17%|█▋        | 85/500 [02:21<10:51,  1.57s/it, loss=2256.0000, t=1e+3]
Attacking:  17%|█▋        | 86/500 [02:21<10:42,  1.55s/it, loss=2256.0000, t=1e+3]
Attacking:  17%|█▋        | 86/500 [02:22<10:42,  1.55s/it, loss=2240.0000, t=1e+3]
Attacking:  17%|█▋        | 87/500 [02:23<10:57,  1.59s/it, loss=2240.0000, t=1e+3]
Attacking:  17%|█▋        | 87/500 [02:24<10:57,  1.59s/it, loss=2240.0000, t=992] 
Attacking:  18%|█▊        | 88/500 [02:25<11:01,  1.60s/it, loss=2240.0000, t=992]
Attacking:  18%|█▊        | 88/500 [02:25<11:01,  1.60s/it, loss=2192.0000, t=912]
Attacking:  18%|█▊        | 89/500 [02:26<10:54,  1.59s/it, loss=2192.0000, t=912]
Attacking:  18%|█▊        | 89/500 [02:27<10:54,  1.59s/it, loss=2224.0000, t=972]
Attacking:  18%|█▊        | 90/500 [02:28<10:58,  1.61s/it, loss=2224.0000, t=972]
Attacking:  18%|█▊        | 90/500 [02:29<10:58,  1.61s/it, loss=2192.0000, t=912]
Attacking:  18%|█▊        | 91/500 [02:30<11:02,  1.62s/it, loss=2192.0000, t=912]
Attacking:  18%|█▊        | 91/500 [02:30<11:02,  1.62s/it, loss=2240.0000, t=992]
Attacking:  18%|█▊        | 92/500 [02:31<10:56,  1.61s/it, loss=2240.0000, t=992]
Attacking:  18%|█▊        | 92/500 [02:32<10:56,  1.61s/it, loss=2192.0000, t=900]
Attacking:  19%|█▊        | 93/500 [02:33<10:44,  1.58s/it, loss=2192.0000, t=900]
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Attacking:  19%|█▉        | 94/500 [02:35<10:53,  1.61s/it, loss=2208.0000, t=964]
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Attacking:  19%|█▉        | 96/500 [02:38<11:06,  1.65s/it, loss=2224.0000, t=972]
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Attacking:  19%|█▉        | 97/500 [02:40<11:00,  1.64s/it, loss=2224.0000, t=964]
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Attacking:  20%|█▉        | 99/500 [02:43<10:44,  1.61s/it, loss=2176.0000, t=900]
Attacking:  20%|██        | 100/500 [02:44<10:29,  1.57s/it, loss=2176.0000, t=900]
Attacking:  20%|██        | 100/500 [02:45<10:29,  1.57s/it, loss=2208.0000, t=964]
Attacking:  20%|██        | 101/500 [02:46<10:32,  1.59s/it, loss=2208.0000, t=964]
Attacking:  20%|██        | 101/500 [02:46<10:32,  1.59s/it, loss=2176.0000, t=900]
Attacking:  20%|██        | 102/500 [02:47<10:46,  1.62s/it, loss=2176.0000, t=900]
Attacking:  20%|██        | 102/500 [02:48<10:46,  1.62s/it, loss=2192.0000, t=928]
Attacking:  21%|██        | 103/500 [02:49<10:31,  1.59s/it, loss=2192.0000, t=928]
Attacking:  21%|██        | 103/500 [02:50<10:31,  1.59s/it, loss=2192.0000, t=928]
Attacking:  21%|██        | 104/500 [02:50<10:25,  1.58s/it, loss=2192.0000, t=928]
Attacking:  21%|██        | 104/500 [02:51<10:25,  1.58s/it, loss=2208.0000, t=964]
Attacking:  21%|██        | 105/500 [02:52<10:24,  1.58s/it, loss=2208.0000, t=964]
Attacking:  21%|██        | 105/500 [02:53<10:24,  1.58s/it, loss=2192.0000, t=928]
Attacking:  21%|██        | 106/500 [02:54<10:35,  1.61s/it, loss=2192.0000, t=928]
Attacking:  21%|██        | 106/500 [02:54<10:35,  1.61s/it, loss=2224.0000, t=984]
Attacking:  21%|██▏       | 107/500 [02:55<10:38,  1.62s/it, loss=2224.0000, t=984]
Attacking:  21%|██▏       | 107/500 [02:56<10:38,  1.62s/it, loss=2224.0000, t=992]
Attacking:  22%|██▏       | 108/500 [02:57<10:36,  1.62s/it, loss=2224.0000, t=992]
Attacking:  22%|██▏       | 108/500 [02:58<10:36,  1.62s/it, loss=2224.0000, t=992]
Attacking:  22%|██▏       | 109/500 [02:59<10:32,  1.62s/it, loss=2224.0000, t=992]
Attacking:  22%|██▏       | 109/500 [02:59<10:32,  1.62s/it, loss=2192.0000, t=928]
Attacking:  22%|██▏       | 110/500 [03:00<10:36,  1.63s/it, loss=2192.0000, t=928]
Attacking:  22%|██▏       | 110/500 [03:01<10:36,  1.63s/it, loss=2208.0000, t=964]
Attacking:  22%|██▏       | 111/500 [03:02<10:40,  1.65s/it, loss=2208.0000, t=964]
Attacking:  22%|██▏       | 111/500 [03:03<10:40,  1.65s/it, loss=2176.0000, t=912]
Attacking:  22%|██▏       | 112/500 [03:03<10:28,  1.62s/it, loss=2176.0000, t=912]
Attacking:  22%|██▏       | 112/500 [03:04<10:28,  1.62s/it, loss=2208.0000, t=964]
Attacking:  23%|██▎       | 113/500 [03:05<10:38,  1.65s/it, loss=2208.0000, t=964]
Attacking:  23%|██▎       | 113/500 [03:06<10:38,  1.65s/it, loss=2176.0000, t=912]
Attacking:  23%|██▎       | 114/500 [03:07<10:38,  1.65s/it, loss=2176.0000, t=912]
Attacking:  23%|██▎       | 114/500 [03:08<10:38,  1.65s/it, loss=2240.0000, t=1e+3]
Attacking:  23%|██▎       | 115/500 [03:08<10:41,  1.67s/it, loss=2240.0000, t=1e+3]
Attacking:  23%|██▎       | 115/500 [03:09<10:41,  1.67s/it, loss=2208.0000, t=984] 
Attacking:  23%|██▎       | 116/500 [03:10<10:42,  1.67s/it, loss=2208.0000, t=984]
Attacking:  23%|██▎       | 116/500 [03:11<10:42,  1.67s/it, loss=2192.0000, t=952]
Attacking:  23%|██▎       | 117/500 [03:12<10:39,  1.67s/it, loss=2192.0000, t=952]
Attacking:  23%|██▎       | 117/500 [03:13<10:39,  1.67s/it, loss=2176.0000, t=928]
Attacking:  24%|██▎       | 118/500 [03:14<10:42,  1.68s/it, loss=2176.0000, t=928]
Attacking:  24%|██▎       | 118/500 [03:14<10:42,  1.68s/it, loss=2224.0000, t=972]
Attacking:  24%|██▍       | 119/500 [03:15<10:29,  1.65s/it, loss=2224.0000, t=972]
Attacking:  24%|██▍       | 119/500 [03:16<10:29,  1.65s/it, loss=2192.0000, t=952]
Attacking:  24%|██▍       | 120/500 [03:17<10:41,  1.69s/it, loss=2192.0000, t=952]
Attacking:  24%|██▍       | 120/500 [03:18<10:41,  1.69s/it, loss=2240.0000, t=992]
Attacking:  24%|██▍       | 121/500 [03:18<10:23,  1.64s/it, loss=2240.0000, t=992]
Attacking:  24%|██▍       | 121/500 [03:19<10:23,  1.64s/it, loss=2176.0000, t=912]
Attacking:  24%|██▍       | 122/500 [03:20<10:16,  1.63s/it, loss=2176.0000, t=912]
Attacking:  24%|██▍       | 122/500 [03:21<10:16,  1.63s/it, loss=2240.0000, t=1e+3]
Attacking:  25%|██▍       | 123/500 [03:22<10:13,  1.63s/it, loss=2240.0000, t=1e+3]
Attacking:  25%|██▍       | 123/500 [03:22<10:13,  1.63s/it, loss=2240.0000, t=1e+3]
Attacking:  25%|██▍       | 124/500 [03:23<10:11,  1.63s/it, loss=2240.0000, t=1e+3]
Attacking:  25%|██▍       | 124/500 [03:24<10:11,  1.63s/it, loss=2192.0000, t=928] 
Attacking:  25%|██▌       | 125/500 [03:25<10:16,  1.64s/it, loss=2192.0000, t=928]
Attacking:  25%|██▌       | 125/500 [03:26<10:16,  1.64s/it, loss=2176.0000, t=940]
Attacking:  25%|██▌       | 126/500 [03:27<10:24,  1.67s/it, loss=2176.0000, t=940]
Attacking:  25%|██▌       | 126/500 [03:27<10:24,  1.67s/it, loss=2176.0000, t=912]
Attacking:  25%|██▌       | 127/500 [03:28<10:17,  1.66s/it, loss=2176.0000, t=912]
Attacking:  25%|██▌       | 127/500 [03:29<10:17,  1.66s/it, loss=2208.0000, t=992]
Attacking:  26%|██▌       | 128/500 [03:30<10:09,  1.64s/it, loss=2208.0000, t=992]
Attacking:  26%|██▌       | 128/500 [03:31<10:09,  1.64s/it, loss=2192.0000, t=984]
Attacking:  26%|██▌       | 129/500 [03:32<10:17,  1.66s/it, loss=2192.0000, t=984]
Attacking:  26%|██▌       | 129/500 [03:32<10:17,  1.66s/it, loss=2192.0000, t=928]
Attacking:  26%|██▌       | 130/500 [03:33<10:15,  1.66s/it, loss=2192.0000, t=928]
Attacking:  26%|██▌       | 130/500 [03:34<10:15,  1.66s/it, loss=2176.0000, t=928]
Attacking:  26%|██▌       | 131/500 [03:35<10:21,  1.68s/it, loss=2176.0000, t=928]
Attacking:  26%|██▌       | 131/500 [03:36<10:21,  1.68s/it, loss=2192.0000, t=972]
Attacking:  26%|██▋       | 132/500 [03:37<10:17,  1.68s/it, loss=2192.0000, t=972]
Attacking:  26%|██▋       | 132/500 [03:37<10:17,  1.68s/it, loss=2224.0000, t=1e+3]
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+Max Diff: 0.501961
+Mean Diff: 0.213443
+Saved adversarial image to attacked/images/violin.jpg
+Saved loss curve to attacked/loss_curve/violin_loss.png
+[GPU 7] Stage 3/3: Test
+Loading models for testing violin...
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+    model_name: wan_video_image_encoder model_class: WanImageEncoder
+    The following models are loaded: ['wan_video_image_encoder'].
+Loading models from: ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors']
+    model_name: wan_video_dit model_class: WanModel
+        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}
+    The following models are loaded: ['wan_video_dit'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
+    model_name: wan_video_text_encoder model_class: WanTextEncoder
+    The following models are loaded: ['wan_video_text_encoder'].
+Loading models from: models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
+    model_name: wan_video_vae model_class: WanVideoVAE
+    The following models are loaded: ['wan_video_vae'].
+Using wan_video_text_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth.
+Using wan_video_dit from ['models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00001-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00002-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00003-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00004-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00005-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00006-of-00007.safetensors', 'models/Wan-AI/Wan2.1-I2V-14B-480P/diffusion_pytorch_model-00007-of-00007.safetensors'].
+Using wan_video_vae from models/Wan-AI/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth.
+Using wan_video_image_encoder from models/Wan-AI/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth.
+Generating video for violin...
+
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+
Saving video:   0%|          | 0/17 [00:00<?, ?it/s]
Saving video:   6%|▌         | 1/17 [00:00<00:05,  2.97it/s]
Saving video: 100%|██████████| 17/17 [00:00<00:00, 39.12it/s]
+Saved video to attacked/videos/violin.mp4
+Saved frames to attacked/frames/violin
+[GPU 7] Finished violin.jpg
+[GPU 7] All assigned tasks completed.
diff --git a/experiments/cfg3_eps64/logs/progress.txt b/experiments/cfg3_eps64/logs/progress.txt
new file mode 100644
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+++ b/experiments/cfg3_eps64/logs/progress.txt
@@ -0,0 +1,46 @@
+camel.jpg
+bear.jpg
+dance-twirl.jpg
+golf.jpg
+lucia.jpg
+parkour.jpg
+ship.jpg
+violin.jpg
+blackswan.jpg
+car-roundabout.jpg
+deer.jpg
+hike.jpg
+mallard-fly.jpg
+picking.jpg
+sportsfield.jpg
+bmx-bumps.jpg
+car-shadow.jpg
+dog.jpg
+hockey.jpg
+man-talking.jpg
+picnic.jpg
+stroller.jpg
+bmx-trees.jpg
+car-turn.jpg
+elephant.jpg
+horsejump-high.jpg
+marllard-water.jpg
+rhino.jpg
+swing.jpg
+boat.jpg
+carousel.jpg
+flamingo.jpg
+horsejump-low.jpg
+motocross-jump.jpg
+rollerblade.jpg
+tandem.jpg
+breakdance-flare.jpg
+cow.jpg
+girl.jpg
+hoverboard.jpg
+motorbike.jpg
+scooter-black.jpg
+tennis-vest.jpg
+bus.jpg
+dance-jump.jpg
+goat.jpg
diff --git a/experiments/cfg3_eps64/loss_curve/bear_loss.png b/experiments/cfg3_eps64/loss_curve/bear_loss.png
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