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  1. 02c97dc5bf4ec64f0a8a17d3c48a37d0/input0.jpg +3 -0
  2. 02c97dc5bf4ec64f0a8a17d3c48a37d0/run.log +31 -0
  3. 02c97dc5bf4ec64f0a8a17d3c48a37d0/video2world_2B.mp4 +3 -0
  4. 02c97dc5bf4ec64f0a8a17d3c48a37d0/video2world_2B.txt +6 -0
  5. 02c97dc5bf4ec64f0a8a17d3c48a37d0/video2world_2B.yaml +390 -0
  6. 072ae5a4543eee1ed73e95bc93d8c243/input0.jpg +3 -0
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  8. 072ae5a4543eee1ed73e95bc93d8c243/video2world_2B.mp4 +3 -0
  9. 072ae5a4543eee1ed73e95bc93d8c243/video2world_2B.txt +6 -0
  10. 072ae5a4543eee1ed73e95bc93d8c243/video2world_2B.yaml +390 -0
  11. 0766fe2271f1c36b2a8d73885c913731/input0.jpg +3 -0
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  13. 0766fe2271f1c36b2a8d73885c913731/video2world_2B.mp4 +3 -0
  14. 0766fe2271f1c36b2a8d73885c913731/video2world_2B.txt +6 -0
  15. 0766fe2271f1c36b2a8d73885c913731/video2world_2B.yaml +390 -0
  16. 0856a3f1d05e3aa70d8284d5c67d5f03/input0.jpg +3 -0
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  18. 0856a3f1d05e3aa70d8284d5c67d5f03/video2world_2B.mp4 +3 -0
  19. 0856a3f1d05e3aa70d8284d5c67d5f03/video2world_2B.txt +6 -0
  20. 0856a3f1d05e3aa70d8284d5c67d5f03/video2world_2B.yaml +390 -0
  21. 08a0e63da36bd3fade24514337eca65c/input0.jpg +3 -0
  22. 08a0e63da36bd3fade24514337eca65c/run.log +31 -0
  23. 08a0e63da36bd3fade24514337eca65c/video2world_2B.mp4 +3 -0
  24. 08a0e63da36bd3fade24514337eca65c/video2world_2B.txt +6 -0
  25. 08a0e63da36bd3fade24514337eca65c/video2world_2B.yaml +390 -0
  26. 16b4eef5d7a47892e2342e6a83f5929f/input0.jpg +3 -0
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  28. 16b4eef5d7a47892e2342e6a83f5929f/video2world_2B.mp4 +3 -0
  29. 16b4eef5d7a47892e2342e6a83f5929f/video2world_2B.txt +6 -0
  30. 16b4eef5d7a47892e2342e6a83f5929f/video2world_2B.yaml +390 -0
  31. 191ed6f62a0f4d1c23107f8f4939f153/input0.jpg +3 -0
  32. 191ed6f62a0f4d1c23107f8f4939f153/run.log +31 -0
  33. 191ed6f62a0f4d1c23107f8f4939f153/video2world_2B.mp4 +3 -0
  34. 191ed6f62a0f4d1c23107f8f4939f153/video2world_2B.txt +6 -0
  35. 191ed6f62a0f4d1c23107f8f4939f153/video2world_2B.yaml +390 -0
  36. 1c3d50949247baa54eae139fdddb9c53/input0.jpg +3 -0
  37. 1c3d50949247baa54eae139fdddb9c53/run.log +31 -0
  38. 1c3d50949247baa54eae139fdddb9c53/video2world_2B.mp4 +3 -0
  39. 1c3d50949247baa54eae139fdddb9c53/video2world_2B.txt +6 -0
  40. 1c3d50949247baa54eae139fdddb9c53/video2world_2B.yaml +390 -0
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  43. 1dc0dd10757270c34b550f09a383c5f4/video2world_2B.mp4 +3 -0
  44. 1dc0dd10757270c34b550f09a383c5f4/video2world_2B.txt +6 -0
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  48. 2357fa0df9e84b61a1fbe8e6c80efee9/video2world_2B.mp4 +3 -0
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  50. 2357fa0df9e84b61a1fbe8e6c80efee9/video2world_2B.yaml +390 -0
02c97dc5bf4ec64f0a8a17d3c48a37d0/input0.jpg ADDED

Git LFS Details

  • SHA256: 5ffeb7935ad3cb5c35a3ea96a6d09637694f36d7edfbfb29084f172932fab94a
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02c97dc5bf4ec64f0a8a17d3c48a37d0/run.log ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0
 
 
 
 
 
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+ fatal: detected dubious ownership in repository at '/workspace'
2
+ To add an exception for this directory, call:
3
+
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+ git config --global --add safe.directory /workspace
5
+ [01-15 17:42:33|INFO|imaginaire/constants.py:39:print_environment_info] imaginaire.constants: Namespace(checkpoints='checkpoints', text_encoder=<TextEncoderClass.T5: 't5'>)
6
+ [01-15 17:42:33|INFO|imaginaire/constants.py:40:print_environment_info] sys.argv: ['/workspace/examples/video2world.py', '--model_size', '2B', '--input_path', '/workspace/video2world_out/02c97dc5bf4ec64f0a8a17d3c48a37d0/input0.jpg', '--num_conditional_frames', '1', '--prompt', 'The video depicts a vehicle driving through a calm urban residential area during early morning or late afternoon, with soft, warm lighting suggesting dawn or dusk. The road is lined with parked cars, trees, and occasional traffic cones or barriers, possibly indicating temporary roadwork. Tall apartment buildings are visible in the background, and the sky has a pale purple hue. As the vehicle moves forward, it passes by various street elements like utility poles, residential homes, and sparse traffic (including a few parked or slowly moving cars). No pedestrians or cyclists are visible, and the vehicle maintains a steady pace on the straight road, with no significant turns or stops. The environment feels quiet and orderly, with no notable events like near-misses or lane changes.', '--save_path', '/workspace/video2world_out/02c97dc5bf4ec64f0a8a17d3c48a37d0/video2world_2B.mp4', '--disable_guardrail']
7
+ [01-15 17:42:33|INFO|imaginaire/constants.py:41:print_environment_info] args: Namespace(model_size='2B', resolution='720', fps=16, dit_path='', load_ema=False, prompt='The video depicts a vehicle driving through a calm urban residential area during early morning or late afternoon, with soft, warm lighting suggesting dawn or dusk. The road is lined with parked cars, trees, and occasional traffic cones or barriers, possibly indicating temporary roadwork. Tall apartment buildings are visible in the background, and the sky has a pale purple hue. As the vehicle moves forward, it passes by various street elements like utility poles, residential homes, and sparse traffic (including a few parked or slowly moving cars). No pedestrians or cyclists are visible, and the vehicle maintains a steady pace on the straight road, with no significant turns or stops. The environment feels quiet and orderly, with no notable events like near-misses or lane changes.', input_path='/workspace/video2world_out/02c97dc5bf4ec64f0a8a17d3c48a37d0/input0.jpg', negative_prompt='The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.', aspect_ratio='16:9', num_conditional_frames=1, batch_input_json=None, guidance=7, seed=0, save_path='/workspace/video2world_out/02c97dc5bf4ec64f0a8a17d3c48a37d0/video2world_2B.mp4', num_gpus=1, disable_guardrail=True, offload_guardrail=False, disable_prompt_refiner=False, offload_prompt_refiner=False, offload_text_encoder=False, downcast_text_encoder=False, benchmark=False, use_cuda_graphs=False, natten=False)
8
+ [01-15 17:42:33|INFO|examples/video2world.py:210:setup_pipeline] Using dit_path: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
9
+ [01-15 17:42:33|INFO|imaginaire/utils/misc.py:139:set_random_seed] Using random seed 0.
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+ [01-15 17:42:33|WARNING|examples/video2world.py:241:setup_pipeline] Guardrail checks are disabled
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+ [01-15 17:42:33|WARNING|imaginaire/lazy_config/lazy.py:441:save_yaml] Config is saved using omegaconf at /workspace/video2world_out/02c97dc5bf4ec64f0a8a17d3c48a37d0/video2world_2B.yaml.
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+ [01-15 17:42:33|INFO|examples/video2world.py:259:setup_pipeline] Initializing Video2WorldPipeline with model size: 2B
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+ [01-15 17:42:33|WARNING|cosmos_predict2/pipelines/video2world.py:292:from_config] precision torch.bfloat16
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+ [01-15 17:42:36|INFO|cosmos_predict2/tokenizers/tokenizer.py:599:_video_vae] Loading checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
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+ [01-15 17:42:36|SUCCESS|cosmos_predict2/tokenizers/tokenizer.py:601:_video_vae] Successfully loaded checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
16
+ [01-15 17:45:30|INFO|imaginaire/auxiliary/text_encoder.py:345:__init__] T5 Text encoder model instantiated
17
+
18
+ [01-15 17:46:46|INFO|cosmos_predict2/pipelines/video2world.py:354:from_config] Loading DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
19
+ [01-15 17:46:52|SUCCESS|cosmos_predict2/pipelines/video2world.py:373:from_config] Successfully loaded DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
20
+ [01-15 17:46:53|INFO|examples/video2world.py:297:process_single_generation] Running Video2WorldPipeline
21
+ input: /workspace/video2world_out/02c97dc5bf4ec64f0a8a17d3c48a37d0/input0.jpg
22
+ prompt: The video depicts a vehicle driving through a calm urban residential area during early morning or late afternoon, with soft, warm lighting suggesting dawn or dusk. The road is lined with parked cars, trees, and occasional traffic cones or barriers, possibly indicating temporary roadwork. Tall apartment buildings are visible in the background, and the sky has a pale purple hue. As the vehicle moves forward, it passes by various street elements like utility poles, residential homes, and sparse traffic (including a few parked or slowly moving cars). No pedestrians or cyclists are visible, and the vehicle maintains a steady pace on the straight road, with no significant turns or stops. The environment feels quiet and orderly, with no notable events like near-misses or lane changes.
23
+ [01-15 17:46:53|WARNING|cosmos_predict2/pipelines/video2world.py:821:__call__] Guardrail checks on prompt are disabled
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+ [01-15 17:46:53|INFO|cosmos_predict2/pipelines/video2world.py:830:__call__] Starting prompt refinement...
25
+ [01-15 17:47:03|INFO|cosmos_predict2/pipelines/video2world.py:832:__call__] Finished prompt refinement
26
+ [01-15 17:47:03|WARNING|cosmos_predict2/pipelines/video2world.py:845:__call__] Guardrail checks on refined prompt are disabled
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+ [01-15 17:47:18|INFO|cosmos_predict2/pipelines/video2world.py:898:__call__] Starting video generation...
28
+
29
 
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+ [01-15 17:57:19|INFO|examples/video2world.py:330:process_single_generation] Saving the generated video to: /workspace/video2world_out/02c97dc5bf4ec64f0a8a17d3c48a37d0/video2world_2B.mp4
31
+ [01-15 17:57:22|SUCCESS|examples/video2world.py:336:process_single_generation] Successfully saved video to: /workspace/video2world_out/02c97dc5bf4ec64f0a8a17d3c48a37d0/video2world_2B.mp4
32
+ [01-15 17:57:22|SUCCESS|examples/video2world.py:347:process_single_generation] Successfully saved prompt file to: /workspace/video2world_out/02c97dc5bf4ec64f0a8a17d3c48a37d0/video2world_2B.txt
02c97dc5bf4ec64f0a8a17d3c48a37d0/video2world_2B.mp4 ADDED
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+ size 6292670
02c97dc5bf4ec64f0a8a17d3c48a37d0/video2world_2B.txt ADDED
@@ -0,0 +1,6 @@
 
 
 
 
 
 
 
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+ [Prompt]
2
+ The video depicts a vehicle driving through a calm urban residential area during early morning or late afternoon, with soft, warm lighting suggesting dawn or dusk. The road is lined with parked cars, trees, and occasional traffic cones or barriers, possibly indicating temporary roadwork. Tall apartment buildings are visible in the background, and the sky has a pale purple hue. As the vehicle moves forward, it passes by various street elements like utility poles, residential homes, and sparse traffic (including a few parked or slowly moving cars). No pedestrians or cyclists are visible, and the vehicle maintains a steady pace on the straight road, with no significant turns or stops. The environment feels quiet and orderly, with no notable events like near-misses or lane changes.
3
+ [Negative Prompt]
4
+ The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.
5
+ [Refined Prompt]
6
+ A vehicle drives steadily through a serene urban residential area during early morning or late afternoon, bathed in soft, warm lighting that suggests dawn or dusk. The road is lined with parked cars, trees, and occasional traffic cones or barriers, hinting at ongoing roadwork. Tall apartment buildings rise in the background, and the sky displays a pale purple hue. As the vehicle progresses, it navigates past utility poles, residential homes, and sparse traffic, including a few parked or slowly moving cars. The environment remains quiet and orderly, with no pedestrians or cyclists in sight, and the vehicle maintains a consistent pace on the straight road, avoiding any significant turns or stops. The overall atmosphere feels calm and methodical.
02c97dc5bf4ec64f0a8a17d3c48a37d0/video2world_2B.yaml ADDED
@@ -0,0 +1,390 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ adjust_video_noise: 'True'
2
+ conditioner:
3
+ _target_: <class 'cosmos_predict2.conditioner.VideoConditioner'>
4
+ fps:
5
+ _target_: <class 'cosmos_predict2.conditioner.ReMapkey'>
6
+ dropout_rate: '0.0'
7
+ dtype: null
8
+ input_key: fps
9
+ output_key: fps
10
+ padding_mask:
11
+ _target_: <class 'cosmos_predict2.conditioner.ReMapkey'>
12
+ dropout_rate: '0.0'
13
+ dtype: null
14
+ input_key: padding_mask
15
+ output_key: padding_mask
16
+ text:
17
+ _target_: <class 'cosmos_predict2.conditioner.TextAttr'>
18
+ dropout_rate: '0.2'
19
+ input_key:
20
+ - t5_text_embeddings
21
+ use_video_condition:
22
+ _target_: <class 'cosmos_predict2.conditioner.BooleanFlag'>
23
+ dropout_rate: '0.0'
24
+ input_key: fps
25
+ output_key: use_video_condition
26
+ conditioning_strategy: frame_replace
27
+ ema:
28
+ _target_: cosmos_predict2.configs.base.defaults.ema.EMAConfig
29
+ enabled: 'False'
30
+ iteration_shift: '0'
31
+ rate: '0.1'
32
+ guardrail_config:
33
+ checkpoint_dir: checkpoints
34
+ enabled: 'False'
35
+ offload_model_to_cpu: 'False'
36
+ input_image_key: images
37
+ input_video_key: video
38
+ max_num_conditional_frames: '2'
39
+ min_num_conditional_frames: '1'
40
+ net:
41
+ _target_: <class 'cosmos_predict2.models.video2world_dit.MinimalV1LVGDiT'>
42
+ adaln_lora_dim: '256'
43
+ atten_backend: minimal_a2a
44
+ concat_padding_mask: 'True'
45
+ extra_per_block_abs_pos_emb: 'False'
46
+ in_channels: '16'
47
+ max_frames: '128'
48
+ max_img_h: '240'
49
+ max_img_w: '240'
50
+ model_channels: '2048'
51
+ num_blocks: '28'
52
+ num_heads: '16'
53
+ out_channels: '16'
54
+ patch_spatial: '2'
55
+ patch_temporal: '1'
56
+ pos_emb_cls: rope3d
57
+ pos_emb_interpolation: crop
58
+ pos_emb_learnable: 'True'
59
+ rope_enable_fps_modulation: 'False'
60
+ rope_h_extrapolation_ratio: '3.0'
61
+ rope_t_extrapolation_ratio: '1.0'
62
+ rope_w_extrapolation_ratio: '3.0'
63
+ sac_config:
64
+ _target_: cosmos_predict2.models.text2image_dit.SACConfig
65
+ every_n_blocks: '1'
66
+ mode: predict2_2b_720
67
+ use_adaln_lora: 'True'
68
+ precision: bfloat16
69
+ prompt_refiner_config:
70
+ checkpoint_dir: checkpoints/nvidia/Cosmos-Reason1-7B
71
+ enabled: 'True'
72
+ offload_model_to_cpu: 'False'
73
+ rectified_flow_loss_weight_uniform: 'True'
74
+ rectified_flow_t_scaling_factor: '1.0'
75
+ resize_online: 'True'
76
+ resolution: '720'
77
+ sigma_conditional: '0.0001'
78
+ sigma_data: '1.0'
79
+ state_ch: '16'
80
+ state_t: '24'
81
+ text_encoder:
82
+ cls: TextEncoderClass.T5
83
+ cosmos_reason1:
84
+ ckpt_path: checkpoints/nvidia/Cosmos-Reason1-Private/reason1_internal_real.pt
85
+ compute_online: 'True'
86
+ embed_dim: '100352'
87
+ embedding_concat_strategy: full_concat
88
+ model_config:
89
+ _target_: <class 'imaginaire.models.vlm_qwen_omni.QwenVLBaseModel'>
90
+ model_config:
91
+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenModelConfig
92
+ activation_checkpoint:
93
+ mode: selective
94
+ models: vlm
95
+ selective_ac_option: op
96
+ add_answer_tag: 'True'
97
+ add_cross_attention: 'False'
98
+ add_image_start_end_tag: 'False'
99
+ add_tile_tag: 'False'
100
+ architectures:
101
+ - Qwen2_5_VLForConditionalGeneration
102
+ attention_dropout: '0.0'
103
+ attn_implementation: flash_attention_2
104
+ attn_implementation_autoset: 'True'
105
+ aux_loss_coeff: '0.0'
106
+ bad_words_ids: null
107
+ begin_suppress_tokens: null
108
+ bos_token_id: '151643'
109
+ cache_dir: null
110
+ checkpoint:
111
+ async_mode: disabled
112
+ create_seed_checkpoint: false
113
+ enable_checkpoint: false
114
+ export_dtype: float32
115
+ folder: checkpoint
116
+ interval: 500
117
+ interval_type: steps
118
+ model_weights_only: false
119
+ chunk_size_feed_forward: '0'
120
+ ckpt_dir: null
121
+ ckpt_path: null
122
+ comm:
123
+ init_timeout_seconds: 300
124
+ trace_buf_size: 20000
125
+ train_timeout_seconds: 100
126
+ cp_size: null
127
+ cross_attention_hidden_size: null
128
+ decoder_start_token_id: null
129
+ deterministic: 'False'
130
+ diversity_penalty: '0.0'
131
+ do_sample: 'False'
132
+ early_stopping: 'False'
133
+ encoder_no_repeat_ngram_size: '0'
134
+ eos_token_id: '151645'
135
+ ep_size: null
136
+ experimental:
137
+ enable_async_tensor_parallel: false
138
+ enable_compiled_autograd: false
139
+ pipeline_parallel_degree: 1
140
+ exponential_decay_length_penalty: null
141
+ finetuning_task: null
142
+ float8:
143
+ enable_float8_linear: false
144
+ forced_bos_token_id: null
145
+ forced_eos_token_id: null
146
+ freeze_llm: 'False'
147
+ freeze_mm_projector: 'False'
148
+ freeze_vision_encoder: 'False'
149
+ fsdp_enabled: 'False'
150
+ hidden_act: silu
151
+ hidden_size: '3584'
152
+ id2label:
153
+ 0: LABEL_0
154
+ 1: LABEL_1
155
+ image_token_id: '151655'
156
+ initializer_range: '0.02'
157
+ intermediate_size: '18944'
158
+ is_decoder: 'False'
159
+ is_encoder_decoder: 'False'
160
+ label2id:
161
+ LABEL_0: '0'
162
+ LABEL_1: '1'
163
+ length_penalty: '1.0'
164
+ loss_per_token: 'True'
165
+ max_batch_size: '1'
166
+ max_length: '20'
167
+ max_position_embeddings: '128000'
168
+ max_seq_len: '128000'
169
+ max_window_layers: '28'
170
+ min_length: '0'
171
+ mm_projector: null
172
+ model_type: qwen2_5_vl
173
+ name_or_path: Qwen/Qwen2.5-VL-7B-Instruct
174
+ no_repeat_ngram_size: '0'
175
+ num_attention_heads: '28'
176
+ num_beam_groups: '1'
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+ name: AdamW
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+ rms_norm_eps: 1e-06
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+ tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct
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+ top_k: '50'
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+ torch_dtype: bfloat16
229
+ torchscript: 'False'
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+ training:
231
+ compile: false
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+ context_parallel_degree: 1
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+ data_parallel_replicate_degree: 1
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+ data_parallel_shard_degree: -1
235
+ disable_loss_parallel: false
236
+ enable_cpu_offload: false
237
+ fsdp_reshard_after_forward: default
238
+ mixed_precision_param: bfloat16
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+ mixed_precision_reduce: float32
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+ steps: 400000
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+ tensor_parallel_degree: 1
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+ use_cosine_decay: false
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+ use_linear_decay: true
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+ warmup_steps: 1000
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+ training_seq_len: '4096'
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+ transformers_version: 4.51.0.dev0
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253
+ use_sliding_window: 'False'
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+ video_token_id: '151656'
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+ vision_config:
256
+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenVisionConfig
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+ add_cross_attention: 'False'
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+ architectures: null
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+ attn_implementation: flash_attention_2
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+ temperature: '1.0'
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+ typical_p: '1.0'
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+ _target_: <function build_tokenizer at 0x735f7d2de520>
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+ cache_dir: checkpoints/nvidia/Cosmos-Reason1-Private/tokenizer
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+ tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct
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+ n_layers_per_group: '5'
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+ num_tokens: '512'
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+ t5:
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+ ckpt_path: checkpoints/google-t5/t5-11b
376
+ embed_dim: '1024'
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+ num_tokens: '512'
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+ timestamps:
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+ is_forward: 'False'
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+ _target_: <class 'cosmos_predict2.tokenizers.tokenizer.TokenizerInterface'>
386
+ chunk_duration: '81'
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+ load_mean_std: 'False'
388
+ name: tokenizer
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+ temporal_window: '16'
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+ vae_pth: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
072ae5a4543eee1ed73e95bc93d8c243/input0.jpg ADDED

Git LFS Details

  • SHA256: 82b5dc25b5c3c9f6842a1ac736ec1e357b32eef45e34aee1cd9a4ed9e28f2076
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072ae5a4543eee1ed73e95bc93d8c243/run.log ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0
 
 
 
 
 
1
+ fatal: detected dubious ownership in repository at '/workspace'
2
+ To add an exception for this directory, call:
3
+
4
+ git config --global --add safe.directory /workspace
5
+ [01-15 17:42:33|INFO|imaginaire/constants.py:39:print_environment_info] imaginaire.constants: Namespace(checkpoints='checkpoints', text_encoder=<TextEncoderClass.T5: 't5'>)
6
+ [01-15 17:42:33|INFO|imaginaire/constants.py:40:print_environment_info] sys.argv: ['/workspace/examples/video2world.py', '--model_size', '2B', '--input_path', '/workspace/video2world_out/072ae5a4543eee1ed73e95bc93d8c243/input0.jpg', '--num_conditional_frames', '1', '--prompt', 'A vehicle drives through a quiet suburban neighborhood on an overcast day, navigating paved streets lined with houses, trees, and parked cars. The lighting is diffused, indicating cloudy conditions. The car moves straight along residential roads, passing intersections where it stops at a stop sign. No pedestrians, cyclists, or significant traffic events are visible; the scene remains calm with consistent, slow movement. The environment features single-family homes, streetlights, and occasional utility poles, with no notable near-misses or abrupt actions', '--save_path', '/workspace/video2world_out/072ae5a4543eee1ed73e95bc93d8c243/video2world_2B.mp4', '--disable_guardrail']
7
+ [01-15 17:42:33|INFO|imaginaire/constants.py:41:print_environment_info] args: Namespace(model_size='2B', resolution='720', fps=16, dit_path='', load_ema=False, prompt='A vehicle drives through a quiet suburban neighborhood on an overcast day, navigating paved streets lined with houses, trees, and parked cars. The lighting is diffused, indicating cloudy conditions. The car moves straight along residential roads, passing intersections where it stops at a stop sign. No pedestrians, cyclists, or significant traffic events are visible; the scene remains calm with consistent, slow movement. The environment features single-family homes, streetlights, and occasional utility poles, with no notable near-misses or abrupt actions', input_path='/workspace/video2world_out/072ae5a4543eee1ed73e95bc93d8c243/input0.jpg', negative_prompt='The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.', aspect_ratio='16:9', num_conditional_frames=1, batch_input_json=None, guidance=7, seed=0, save_path='/workspace/video2world_out/072ae5a4543eee1ed73e95bc93d8c243/video2world_2B.mp4', num_gpus=1, disable_guardrail=True, offload_guardrail=False, disable_prompt_refiner=False, offload_prompt_refiner=False, offload_text_encoder=False, downcast_text_encoder=False, benchmark=False, use_cuda_graphs=False, natten=False)
8
+ [01-15 17:42:33|INFO|examples/video2world.py:210:setup_pipeline] Using dit_path: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
9
+ [01-15 17:42:33|INFO|imaginaire/utils/misc.py:139:set_random_seed] Using random seed 0.
10
+ [01-15 17:42:33|WARNING|examples/video2world.py:241:setup_pipeline] Guardrail checks are disabled
11
+ [01-15 17:42:33|WARNING|imaginaire/lazy_config/lazy.py:441:save_yaml] Config is saved using omegaconf at /workspace/video2world_out/072ae5a4543eee1ed73e95bc93d8c243/video2world_2B.yaml.
12
+ [01-15 17:42:33|INFO|examples/video2world.py:259:setup_pipeline] Initializing Video2WorldPipeline with model size: 2B
13
+ [01-15 17:42:33|WARNING|cosmos_predict2/pipelines/video2world.py:292:from_config] precision torch.bfloat16
14
+ [01-15 17:42:36|INFO|cosmos_predict2/tokenizers/tokenizer.py:599:_video_vae] Loading checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
15
+ [01-15 17:42:36|SUCCESS|cosmos_predict2/tokenizers/tokenizer.py:601:_video_vae] Successfully loaded checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
16
+ [01-15 17:45:42|INFO|imaginaire/auxiliary/text_encoder.py:345:__init__] T5 Text encoder model instantiated
17
+
18
+ [01-15 17:46:46|INFO|cosmos_predict2/pipelines/video2world.py:354:from_config] Loading DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
19
+ [01-15 17:46:52|SUCCESS|cosmos_predict2/pipelines/video2world.py:373:from_config] Successfully loaded DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
20
+ [01-15 17:46:53|INFO|examples/video2world.py:297:process_single_generation] Running Video2WorldPipeline
21
+ input: /workspace/video2world_out/072ae5a4543eee1ed73e95bc93d8c243/input0.jpg
22
+ prompt: A vehicle drives through a quiet suburban neighborhood on an overcast day, navigating paved streets lined with houses, trees, and parked cars. The lighting is diffused, indicating cloudy conditions. The car moves straight along residential roads, passing intersections where it stops at a stop sign. No pedestrians, cyclists, or significant traffic events are visible; the scene remains calm with consistent, slow movement. The environment features single-family homes, streetlights, and occasional utility poles, with no notable near-misses or abrupt actions
23
+ [01-15 17:46:53|WARNING|cosmos_predict2/pipelines/video2world.py:821:__call__] Guardrail checks on prompt are disabled
24
+ [01-15 17:46:53|INFO|cosmos_predict2/pipelines/video2world.py:830:__call__] Starting prompt refinement...
25
+ [01-15 17:47:02|INFO|cosmos_predict2/pipelines/video2world.py:832:__call__] Finished prompt refinement
26
+ [01-15 17:47:02|WARNING|cosmos_predict2/pipelines/video2world.py:845:__call__] Guardrail checks on refined prompt are disabled
27
+ [01-15 17:47:17|INFO|cosmos_predict2/pipelines/video2world.py:898:__call__] Starting video generation...
28
+
29
 
30
+ [01-15 17:57:06|INFO|examples/video2world.py:330:process_single_generation] Saving the generated video to: /workspace/video2world_out/072ae5a4543eee1ed73e95bc93d8c243/video2world_2B.mp4
31
+ [01-15 17:57:10|SUCCESS|examples/video2world.py:336:process_single_generation] Successfully saved video to: /workspace/video2world_out/072ae5a4543eee1ed73e95bc93d8c243/video2world_2B.mp4
32
+ [01-15 17:57:10|SUCCESS|examples/video2world.py:347:process_single_generation] Successfully saved prompt file to: /workspace/video2world_out/072ae5a4543eee1ed73e95bc93d8c243/video2world_2B.txt
072ae5a4543eee1ed73e95bc93d8c243/video2world_2B.mp4 ADDED
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072ae5a4543eee1ed73e95bc93d8c243/video2world_2B.txt ADDED
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+ [Prompt]
2
+ A vehicle drives through a quiet suburban neighborhood on an overcast day, navigating paved streets lined with houses, trees, and parked cars. The lighting is diffused, indicating cloudy conditions. The car moves straight along residential roads, passing intersections where it stops at a stop sign. No pedestrians, cyclists, or significant traffic events are visible; the scene remains calm with consistent, slow movement. The environment features single-family homes, streetlights, and occasional utility poles, with no notable near-misses or abrupt actions
3
+ [Negative Prompt]
4
+ The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.
5
+ [Refined Prompt]
6
+ A vehicle drives through a quiet suburban neighborhood on an overcast day, navigating paved streets lined with houses, trees, and parked cars. The lighting is diffused, indicating cloudy conditions. The car moves straight along residential roads, passing intersections where it stops at a stop sign. No pedestrians, cyclists, or significant traffic events are visible; the scene remains calm with consistent, slow movement. The environment features single-family homes, streetlights, and occasional utility poles, with no notable near-misses or abrupt actions. A steady tracking shot following the vehicle from behind, capturing the serene suburban landscape.
072ae5a4543eee1ed73e95bc93d8c243/video2world_2B.yaml ADDED
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1
+ adjust_video_noise: 'True'
2
+ conditioner:
3
+ _target_: <class 'cosmos_predict2.conditioner.VideoConditioner'>
4
+ fps:
5
+ _target_: <class 'cosmos_predict2.conditioner.ReMapkey'>
6
+ dropout_rate: '0.0'
7
+ dtype: null
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+ input_key: fps
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+ output_key: fps
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+ padding_mask:
11
+ _target_: <class 'cosmos_predict2.conditioner.ReMapkey'>
12
+ dropout_rate: '0.0'
13
+ dtype: null
14
+ input_key: padding_mask
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+ output_key: padding_mask
16
+ text:
17
+ _target_: <class 'cosmos_predict2.conditioner.TextAttr'>
18
+ dropout_rate: '0.2'
19
+ input_key:
20
+ - t5_text_embeddings
21
+ use_video_condition:
22
+ _target_: <class 'cosmos_predict2.conditioner.BooleanFlag'>
23
+ dropout_rate: '0.0'
24
+ input_key: fps
25
+ output_key: use_video_condition
26
+ conditioning_strategy: frame_replace
27
+ ema:
28
+ _target_: cosmos_predict2.configs.base.defaults.ema.EMAConfig
29
+ enabled: 'False'
30
+ iteration_shift: '0'
31
+ rate: '0.1'
32
+ guardrail_config:
33
+ checkpoint_dir: checkpoints
34
+ enabled: 'False'
35
+ offload_model_to_cpu: 'False'
36
+ input_image_key: images
37
+ input_video_key: video
38
+ max_num_conditional_frames: '2'
39
+ min_num_conditional_frames: '1'
40
+ net:
41
+ _target_: <class 'cosmos_predict2.models.video2world_dit.MinimalV1LVGDiT'>
42
+ adaln_lora_dim: '256'
43
+ atten_backend: minimal_a2a
44
+ concat_padding_mask: 'True'
45
+ extra_per_block_abs_pos_emb: 'False'
46
+ in_channels: '16'
47
+ max_frames: '128'
48
+ max_img_h: '240'
49
+ max_img_w: '240'
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+ model_channels: '2048'
51
+ num_blocks: '28'
52
+ num_heads: '16'
53
+ out_channels: '16'
54
+ patch_spatial: '2'
55
+ patch_temporal: '1'
56
+ pos_emb_cls: rope3d
57
+ pos_emb_interpolation: crop
58
+ pos_emb_learnable: 'True'
59
+ rope_enable_fps_modulation: 'False'
60
+ rope_h_extrapolation_ratio: '3.0'
61
+ rope_t_extrapolation_ratio: '1.0'
62
+ rope_w_extrapolation_ratio: '3.0'
63
+ sac_config:
64
+ _target_: cosmos_predict2.models.text2image_dit.SACConfig
65
+ every_n_blocks: '1'
66
+ mode: predict2_2b_720
67
+ use_adaln_lora: 'True'
68
+ precision: bfloat16
69
+ prompt_refiner_config:
70
+ checkpoint_dir: checkpoints/nvidia/Cosmos-Reason1-7B
71
+ enabled: 'True'
72
+ offload_model_to_cpu: 'False'
73
+ rectified_flow_loss_weight_uniform: 'True'
74
+ rectified_flow_t_scaling_factor: '1.0'
75
+ resize_online: 'True'
76
+ resolution: '720'
77
+ sigma_conditional: '0.0001'
78
+ sigma_data: '1.0'
79
+ state_ch: '16'
80
+ state_t: '24'
81
+ text_encoder:
82
+ cls: TextEncoderClass.T5
83
+ cosmos_reason1:
84
+ ckpt_path: checkpoints/nvidia/Cosmos-Reason1-Private/reason1_internal_real.pt
85
+ compute_online: 'True'
86
+ embed_dim: '100352'
87
+ embedding_concat_strategy: full_concat
88
+ model_config:
89
+ _target_: <class 'imaginaire.models.vlm_qwen_omni.QwenVLBaseModel'>
90
+ model_config:
91
+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenModelConfig
92
+ activation_checkpoint:
93
+ mode: selective
94
+ models: vlm
95
+ selective_ac_option: op
96
+ add_answer_tag: 'True'
97
+ add_cross_attention: 'False'
98
+ add_image_start_end_tag: 'False'
99
+ add_tile_tag: 'False'
100
+ architectures:
101
+ - Qwen2_5_VLForConditionalGeneration
102
+ attention_dropout: '0.0'
103
+ attn_implementation: flash_attention_2
104
+ attn_implementation_autoset: 'True'
105
+ aux_loss_coeff: '0.0'
106
+ bad_words_ids: null
107
+ begin_suppress_tokens: null
108
+ bos_token_id: '151643'
109
+ cache_dir: null
110
+ checkpoint:
111
+ async_mode: disabled
112
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224
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226
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229
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230
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231
+ compile: false
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237
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253
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254
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256
+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenVisionConfig
257
+ add_cross_attention: 'False'
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+ n_layers_per_group: '5'
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+ num_tokens: '512'
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+ t5:
375
+ ckpt_path: checkpoints/google-t5/t5-11b
376
+ embed_dim: '1024'
377
+ num_tokens: '512'
378
+ timestamps:
379
+ is_forward: 'False'
380
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+ _target_: <class 'cosmos_predict2.tokenizers.tokenizer.TokenizerInterface'>
386
+ chunk_duration: '81'
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+ load_mean_std: 'False'
388
+ name: tokenizer
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+ temporal_window: '16'
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+ vae_pth: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
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Git LFS Details

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0766fe2271f1c36b2a8d73885c913731/run.log ADDED
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0
 
 
 
 
 
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+ fatal: detected dubious ownership in repository at '/workspace'
2
+ To add an exception for this directory, call:
3
+
4
+ git config --global --add safe.directory /workspace
5
+ [01-15 17:42:33|INFO|imaginaire/constants.py:39:print_environment_info] imaginaire.constants: Namespace(checkpoints='checkpoints', text_encoder=<TextEncoderClass.T5: 't5'>)
6
+ [01-15 17:42:33|INFO|imaginaire/constants.py:40:print_environment_info] sys.argv: ['/workspace/examples/video2world.py', '--model_size', '2B', '--input_path', '/workspace/video2world_out/0766fe2271f1c36b2a8d73885c913731/input0.jpg', '--num_conditional_frames', '1', '--prompt', 'The video depicts a car', '--save_path', '/workspace/video2world_out/0766fe2271f1c36b2a8d73885c913731/video2world_2B.mp4', '--disable_guardrail']
7
+ [01-15 17:42:33|INFO|imaginaire/constants.py:41:print_environment_info] args: Namespace(model_size='2B', resolution='720', fps=16, dit_path='', load_ema=False, prompt='The video depicts a car', input_path='/workspace/video2world_out/0766fe2271f1c36b2a8d73885c913731/input0.jpg', negative_prompt='The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.', aspect_ratio='16:9', num_conditional_frames=1, batch_input_json=None, guidance=7, seed=0, save_path='/workspace/video2world_out/0766fe2271f1c36b2a8d73885c913731/video2world_2B.mp4', num_gpus=1, disable_guardrail=True, offload_guardrail=False, disable_prompt_refiner=False, offload_prompt_refiner=False, offload_text_encoder=False, downcast_text_encoder=False, benchmark=False, use_cuda_graphs=False, natten=False)
8
+ [01-15 17:42:33|INFO|examples/video2world.py:210:setup_pipeline] Using dit_path: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
9
+ [01-15 17:42:33|INFO|imaginaire/utils/misc.py:139:set_random_seed] Using random seed 0.
10
+ [01-15 17:42:33|WARNING|examples/video2world.py:241:setup_pipeline] Guardrail checks are disabled
11
+ [01-15 17:42:33|WARNING|imaginaire/lazy_config/lazy.py:441:save_yaml] Config is saved using omegaconf at /workspace/video2world_out/0766fe2271f1c36b2a8d73885c913731/video2world_2B.yaml.
12
+ [01-15 17:42:33|INFO|examples/video2world.py:259:setup_pipeline] Initializing Video2WorldPipeline with model size: 2B
13
+ [01-15 17:42:33|WARNING|cosmos_predict2/pipelines/video2world.py:292:from_config] precision torch.bfloat16
14
+ [01-15 17:42:36|INFO|cosmos_predict2/tokenizers/tokenizer.py:599:_video_vae] Loading checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
15
+ [01-15 17:42:36|SUCCESS|cosmos_predict2/tokenizers/tokenizer.py:601:_video_vae] Successfully loaded checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
16
+ [01-15 17:45:36|INFO|imaginaire/auxiliary/text_encoder.py:345:__init__] T5 Text encoder model instantiated
17
+
18
+ [01-15 17:46:46|INFO|cosmos_predict2/pipelines/video2world.py:354:from_config] Loading DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
19
+ [01-15 17:46:52|SUCCESS|cosmos_predict2/pipelines/video2world.py:373:from_config] Successfully loaded DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
20
+ [01-15 17:46:53|INFO|examples/video2world.py:297:process_single_generation] Running Video2WorldPipeline
21
+ input: /workspace/video2world_out/0766fe2271f1c36b2a8d73885c913731/input0.jpg
22
+ prompt: The video depicts a car
23
+ [01-15 17:46:53|WARNING|cosmos_predict2/pipelines/video2world.py:821:__call__] Guardrail checks on prompt are disabled
24
+ [01-15 17:46:53|INFO|cosmos_predict2/pipelines/video2world.py:830:__call__] Starting prompt refinement...
25
+ [01-15 17:47:02|INFO|cosmos_predict2/pipelines/video2world.py:832:__call__] Finished prompt refinement
26
+ [01-15 17:47:02|WARNING|cosmos_predict2/pipelines/video2world.py:845:__call__] Guardrail checks on refined prompt are disabled
27
+ [01-15 17:47:18|INFO|cosmos_predict2/pipelines/video2world.py:898:__call__] Starting video generation...
28
+
29
 
30
+ [01-15 17:57:21|INFO|examples/video2world.py:330:process_single_generation] Saving the generated video to: /workspace/video2world_out/0766fe2271f1c36b2a8d73885c913731/video2world_2B.mp4
31
+ [01-15 17:57:25|SUCCESS|examples/video2world.py:336:process_single_generation] Successfully saved video to: /workspace/video2world_out/0766fe2271f1c36b2a8d73885c913731/video2world_2B.mp4
32
+ [01-15 17:57:25|SUCCESS|examples/video2world.py:347:process_single_generation] Successfully saved prompt file to: /workspace/video2world_out/0766fe2271f1c36b2a8d73885c913731/video2world_2B.txt
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0766fe2271f1c36b2a8d73885c913731/video2world_2B.txt ADDED
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+ [Prompt]
2
+ The video depicts a car
3
+ [Negative Prompt]
4
+ The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.
5
+ [Refined Prompt]
6
+ A wide-angle shot captures a quiet urban street lined with modern apartment buildings under a bright blue sky dotted with fluffy clouds. Palm trees sway gently along the sidewalk, adding a touch of greenery to the concrete surroundings. A stop sign stands prominently near the intersection, marking the boundary between the residential area and the road. The scene is bathed in sunlight, casting soft shadows across the pavement. A billboard is visible in the distance, partially obscured by the palm trees. The overall atmosphere is calm and serene, typical of a sunny day in a suburban neighborhood.
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+ adjust_video_noise: 'True'
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+ conditioner:
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+ _target_: <class 'cosmos_predict2.conditioner.VideoConditioner'>
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+ fps:
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+ _target_: <class 'cosmos_predict2.conditioner.ReMapkey'>
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+ dropout_rate: '0.0'
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+ dtype: null
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+ input_key: fps
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+ output_key: fps
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+ padding_mask:
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+ _target_: <class 'cosmos_predict2.conditioner.ReMapkey'>
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+ dropout_rate: '0.0'
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+ dtype: null
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+ input_key: padding_mask
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+ output_key: padding_mask
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+ text:
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+ _target_: <class 'cosmos_predict2.conditioner.TextAttr'>
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+ dropout_rate: '0.2'
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+ input_key:
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+ - t5_text_embeddings
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+ use_video_condition:
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+ _target_: <class 'cosmos_predict2.conditioner.BooleanFlag'>
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+ dropout_rate: '0.0'
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+ input_key: fps
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+ output_key: use_video_condition
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+ conditioning_strategy: frame_replace
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+ ema:
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+ _target_: cosmos_predict2.configs.base.defaults.ema.EMAConfig
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+ enabled: 'False'
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+ iteration_shift: '0'
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+ rate: '0.1'
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+ guardrail_config:
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+ checkpoint_dir: checkpoints
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+ enabled: 'False'
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+ offload_model_to_cpu: 'False'
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+ input_image_key: images
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+ input_video_key: video
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+ max_num_conditional_frames: '2'
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+ min_num_conditional_frames: '1'
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+ net:
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+ _target_: <class 'cosmos_predict2.models.video2world_dit.MinimalV1LVGDiT'>
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+ adaln_lora_dim: '256'
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+ atten_backend: minimal_a2a
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+ concat_padding_mask: 'True'
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+ extra_per_block_abs_pos_emb: 'False'
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+ in_channels: '16'
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+ max_frames: '128'
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+ max_img_h: '240'
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+ max_img_w: '240'
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+ model_channels: '2048'
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+ num_blocks: '28'
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+ num_heads: '16'
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+ out_channels: '16'
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+ patch_spatial: '2'
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+ patch_temporal: '1'
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+ pos_emb_cls: rope3d
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+ pos_emb_interpolation: crop
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+ pos_emb_learnable: 'True'
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+ rope_enable_fps_modulation: 'False'
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+ rope_h_extrapolation_ratio: '3.0'
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+ rope_t_extrapolation_ratio: '1.0'
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+ rope_w_extrapolation_ratio: '3.0'
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+ sac_config:
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+ _target_: cosmos_predict2.models.text2image_dit.SACConfig
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+ every_n_blocks: '1'
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+ mode: predict2_2b_720
67
+ use_adaln_lora: 'True'
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+ precision: bfloat16
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+ prompt_refiner_config:
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+ checkpoint_dir: checkpoints/nvidia/Cosmos-Reason1-7B
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+ enabled: 'True'
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+ offload_model_to_cpu: 'False'
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+ rectified_flow_loss_weight_uniform: 'True'
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+ rectified_flow_t_scaling_factor: '1.0'
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+ resize_online: 'True'
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+ resolution: '720'
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+ sigma_conditional: '0.0001'
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+ sigma_data: '1.0'
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80
+ state_t: '24'
81
+ text_encoder:
82
+ cls: TextEncoderClass.T5
83
+ cosmos_reason1:
84
+ ckpt_path: checkpoints/nvidia/Cosmos-Reason1-Private/reason1_internal_real.pt
85
+ compute_online: 'True'
86
+ embed_dim: '100352'
87
+ embedding_concat_strategy: full_concat
88
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89
+ _target_: <class 'imaginaire.models.vlm_qwen_omni.QwenVLBaseModel'>
90
+ model_config:
91
+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenModelConfig
92
+ activation_checkpoint:
93
+ mode: selective
94
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95
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96
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97
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98
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99
+ add_tile_tag: 'False'
100
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101
+ - Qwen2_5_VLForConditionalGeneration
102
+ attention_dropout: '0.0'
103
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104
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105
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106
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111
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113
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114
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115
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116
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117
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118
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119
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120
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121
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123
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124
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125
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137
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138
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139
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143
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144
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147
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148
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149
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150
+ hidden_act: silu
151
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152
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153
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161
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165
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168
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169
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170
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171
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172
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173
+ name_or_path: Qwen/Qwen2.5-VL-7B-Instruct
174
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175
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176
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179
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180
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181
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182
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183
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184
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185
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186
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187
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188
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190
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191
+ name: AdamW
192
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193
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194
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195
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197
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198
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199
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200
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201
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202
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203
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204
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205
+ rms_norm_eps: 1e-06
206
+ rope_scaling:
207
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208
+ - '16'
209
+ - '24'
210
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211
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212
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214
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215
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216
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217
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218
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219
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220
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221
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222
+ tie_word_embeddings: 'False'
223
+ tile_tag_type: space_separated
224
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225
+ tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct
226
+ top_k: '50'
227
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228
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229
+ torchscript: 'False'
230
+ training:
231
+ compile: false
232
+ context_parallel_degree: 1
233
+ data_parallel_replicate_degree: 1
234
+ data_parallel_shard_degree: -1
235
+ disable_loss_parallel: false
236
+ enable_cpu_offload: false
237
+ fsdp_reshard_after_forward: default
238
+ mixed_precision_param: bfloat16
239
+ mixed_precision_reduce: float32
240
+ steps: 400000
241
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242
+ use_cosine_decay: false
243
+ use_linear_decay: true
244
+ warmup_steps: 1000
245
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+ typical_p: '1.0'
248
+ use_bfloat16: 'False'
249
+ use_cache: 'False'
250
+ use_fsdp2: 'True'
251
+ use_return_dict: 'True'
252
+ use_rope_from_torchtitan: 'False'
253
+ use_sliding_window: 'False'
254
+ video_token_id: '151656'
255
+ vision_config:
256
+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenVisionConfig
257
+ add_cross_attention: 'False'
258
+ architectures: null
259
+ attn_implementation: flash_attention_2
260
+ attn_implementation_autoset: 'True'
261
+ bad_words_ids: null
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+ fullatt_block_indexes:
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+ - '7'
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+ - '15'
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+ - '23'
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+ - '31'
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+ max_length: '20'
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+ output_scores: 'False'
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+ tf_legacy_loss: 'False'
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+ tokens_per_second: '2'
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+ _target_: <function build_tokenizer at 0x78b587d12520>
370
+ cache_dir: checkpoints/nvidia/Cosmos-Reason1-Private/tokenizer
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+ tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct
372
+ n_layers_per_group: '5'
373
+ num_tokens: '512'
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+ t5:
375
+ ckpt_path: checkpoints/google-t5/t5-11b
376
+ embed_dim: '1024'
377
+ num_tokens: '512'
378
+ timestamps:
379
+ is_forward: 'False'
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+ nfe: '35'
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+ order: '7.0'
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+ t_max: '80.0'
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+ t_min: '0.002'
384
+ tokenizer:
385
+ _target_: <class 'cosmos_predict2.tokenizers.tokenizer.TokenizerInterface'>
386
+ chunk_duration: '81'
387
+ load_mean_std: 'False'
388
+ name: tokenizer
389
+ temporal_window: '16'
390
+ vae_pth: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
0856a3f1d05e3aa70d8284d5c67d5f03/input0.jpg ADDED

Git LFS Details

  • SHA256: 0b7cbe9a535c869f2c12b1066056f7ecc2f579a460dcc72d3d31edfded43120e
  • Pointer size: 130 Bytes
  • Size of remote file: 50.7 kB
0856a3f1d05e3aa70d8284d5c67d5f03/run.log ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0
 
 
 
 
 
1
+ fatal: detected dubious ownership in repository at '/workspace'
2
+ To add an exception for this directory, call:
3
+
4
+ git config --global --add safe.directory /workspace
5
+ [01-15 17:42:33|INFO|imaginaire/constants.py:39:print_environment_info] imaginaire.constants: Namespace(checkpoints='checkpoints', text_encoder=<TextEncoderClass.T5: 't5'>)
6
+ [01-15 17:42:33|INFO|imaginaire/constants.py:40:print_environment_info] sys.argv: ['/workspace/examples/video2world.py', '--model_size', '2B', '--input_path', '/workspace/video2world_out/0856a3f1d05e3aa70d8284d5c67d5f03/input0.jpg', '--num_conditional_frames', '1', '--prompt', 'A car drives through a sunny urban city center, navigating multi-lane streets lined with tall buildings, palm trees, and street signs like “1st Ave.” The road is busy with other vehicles, including a white sedan ahead, a white pickup truck, and a silver sedan. Pedestrians walk on sidewalks, and construction barriers appear in later segments. The car stops at traffic lights, then proceeds through intersections, passing storefronts, parking signs, and a “No Turn on Red” sign. Bright midday sunlight illuminates the scene, with clear blue skies overhead. The vehicle maintains a steady pace, avoiding near-misses while maneuvering through the bustling city environment.', '--save_path', '/workspace/video2world_out/0856a3f1d05e3aa70d8284d5c67d5f03/video2world_2B.mp4', '--disable_guardrail']
7
+ [01-15 17:42:33|INFO|imaginaire/constants.py:41:print_environment_info] args: Namespace(model_size='2B', resolution='720', fps=16, dit_path='', load_ema=False, prompt='A car drives through a sunny urban city center, navigating multi-lane streets lined with tall buildings, palm trees, and street signs like “1st Ave.” The road is busy with other vehicles, including a white sedan ahead, a white pickup truck, and a silver sedan. Pedestrians walk on sidewalks, and construction barriers appear in later segments. The car stops at traffic lights, then proceeds through intersections, passing storefronts, parking signs, and a “No Turn on Red” sign. Bright midday sunlight illuminates the scene, with clear blue skies overhead. The vehicle maintains a steady pace, avoiding near-misses while maneuvering through the bustling city environment.', input_path='/workspace/video2world_out/0856a3f1d05e3aa70d8284d5c67d5f03/input0.jpg', negative_prompt='The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.', aspect_ratio='16:9', num_conditional_frames=1, batch_input_json=None, guidance=7, seed=0, save_path='/workspace/video2world_out/0856a3f1d05e3aa70d8284d5c67d5f03/video2world_2B.mp4', num_gpus=1, disable_guardrail=True, offload_guardrail=False, disable_prompt_refiner=False, offload_prompt_refiner=False, offload_text_encoder=False, downcast_text_encoder=False, benchmark=False, use_cuda_graphs=False, natten=False)
8
+ [01-15 17:42:33|INFO|examples/video2world.py:210:setup_pipeline] Using dit_path: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
9
+ [01-15 17:42:33|INFO|imaginaire/utils/misc.py:139:set_random_seed] Using random seed 0.
10
+ [01-15 17:42:33|WARNING|examples/video2world.py:241:setup_pipeline] Guardrail checks are disabled
11
+ [01-15 17:42:33|WARNING|imaginaire/lazy_config/lazy.py:441:save_yaml] Config is saved using omegaconf at /workspace/video2world_out/0856a3f1d05e3aa70d8284d5c67d5f03/video2world_2B.yaml.
12
+ [01-15 17:42:33|INFO|examples/video2world.py:259:setup_pipeline] Initializing Video2WorldPipeline with model size: 2B
13
+ [01-15 17:42:33|WARNING|cosmos_predict2/pipelines/video2world.py:292:from_config] precision torch.bfloat16
14
+ [01-15 17:42:36|INFO|cosmos_predict2/tokenizers/tokenizer.py:599:_video_vae] Loading checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
15
+ [01-15 17:42:36|SUCCESS|cosmos_predict2/tokenizers/tokenizer.py:601:_video_vae] Successfully loaded checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
16
+ [01-15 17:45:42|INFO|imaginaire/auxiliary/text_encoder.py:345:__init__] T5 Text encoder model instantiated
17
+
18
+ [01-15 17:46:46|INFO|cosmos_predict2/pipelines/video2world.py:354:from_config] Loading DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
19
+ [01-15 17:46:52|SUCCESS|cosmos_predict2/pipelines/video2world.py:373:from_config] Successfully loaded DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
20
+ [01-15 17:46:53|INFO|examples/video2world.py:297:process_single_generation] Running Video2WorldPipeline
21
+ input: /workspace/video2world_out/0856a3f1d05e3aa70d8284d5c67d5f03/input0.jpg
22
+ prompt: A car drives through a sunny urban city center, navigating multi-lane streets lined with tall buildings, palm trees, and street signs like “1st Ave.” The road is busy with other vehicles, including a white sedan ahead, a white pickup truck, and a silver sedan. Pedestrians walk on sidewalks, and construction barriers appear in later segments. The car stops at traffic lights, then proceeds through intersections, passing storefronts, parking signs, and a “No Turn on Red” sign. Bright midday sunlight illuminates the scene, with clear blue skies overhead. The vehicle maintains a steady pace, avoiding near-misses while maneuvering through the bustling city environment.
23
+ [01-15 17:46:53|WARNING|cosmos_predict2/pipelines/video2world.py:821:__call__] Guardrail checks on prompt are disabled
24
+ [01-15 17:46:53|INFO|cosmos_predict2/pipelines/video2world.py:830:__call__] Starting prompt refinement...
25
+ [01-15 17:47:03|INFO|cosmos_predict2/pipelines/video2world.py:832:__call__] Finished prompt refinement
26
+ [01-15 17:47:03|WARNING|cosmos_predict2/pipelines/video2world.py:845:__call__] Guardrail checks on refined prompt are disabled
27
+ [01-15 17:47:18|INFO|cosmos_predict2/pipelines/video2world.py:898:__call__] Starting video generation...
28
+
29
 
30
+ [01-15 17:57:19|INFO|examples/video2world.py:330:process_single_generation] Saving the generated video to: /workspace/video2world_out/0856a3f1d05e3aa70d8284d5c67d5f03/video2world_2B.mp4
31
+ [01-15 17:57:23|SUCCESS|examples/video2world.py:336:process_single_generation] Successfully saved video to: /workspace/video2world_out/0856a3f1d05e3aa70d8284d5c67d5f03/video2world_2B.mp4
32
+ [01-15 17:57:23|SUCCESS|examples/video2world.py:347:process_single_generation] Successfully saved prompt file to: /workspace/video2world_out/0856a3f1d05e3aa70d8284d5c67d5f03/video2world_2B.txt
0856a3f1d05e3aa70d8284d5c67d5f03/video2world_2B.mp4 ADDED
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0856a3f1d05e3aa70d8284d5c67d5f03/video2world_2B.txt ADDED
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+ [Prompt]
2
+ A car drives through a sunny urban city center, navigating multi-lane streets lined with tall buildings, palm trees, and street signs like “1st Ave.” The road is busy with other vehicles, including a white sedan ahead, a white pickup truck, and a silver sedan. Pedestrians walk on sidewalks, and construction barriers appear in later segments. The car stops at traffic lights, then proceeds through intersections, passing storefronts, parking signs, and a “No Turn on Red” sign. Bright midday sunlight illuminates the scene, with clear blue skies overhead. The vehicle maintains a steady pace, avoiding near-misses while maneuvering through the bustling city environment.
3
+ [Negative Prompt]
4
+ The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.
5
+ [Refined Prompt]
6
+ A car drives through a sunny urban city center, navigating multi-lane streets lined with tall buildings, palm trees, and street signs like "1st Ave." The road is busy with other vehicles, including a white sedan ahead, a white pickup truck, and a silver sedan. Pedestrians walk on sidewalks, and construction barriers appear in later segments. The car stops at traffic lights, then proceeds through intersections, passing storefronts, parking signs, and a "No Turn on Red" sign. Bright midday sunlight illuminates the scene, with clear blue skies overhead. The vehicle maintains a steady pace, avoiding near-misses while maneuvering through the bustling city environment. A dynamic medium shot captures the car's journey, emphasizing the lively urban atmosphere and the interplay between the vehicle and its surroundings.
0856a3f1d05e3aa70d8284d5c67d5f03/video2world_2B.yaml ADDED
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1
+ adjust_video_noise: 'True'
2
+ conditioner:
3
+ _target_: <class 'cosmos_predict2.conditioner.VideoConditioner'>
4
+ fps:
5
+ _target_: <class 'cosmos_predict2.conditioner.ReMapkey'>
6
+ dropout_rate: '0.0'
7
+ dtype: null
8
+ input_key: fps
9
+ output_key: fps
10
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11
+ _target_: <class 'cosmos_predict2.conditioner.ReMapkey'>
12
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13
+ dtype: null
14
+ input_key: padding_mask
15
+ output_key: padding_mask
16
+ text:
17
+ _target_: <class 'cosmos_predict2.conditioner.TextAttr'>
18
+ dropout_rate: '0.2'
19
+ input_key:
20
+ - t5_text_embeddings
21
+ use_video_condition:
22
+ _target_: <class 'cosmos_predict2.conditioner.BooleanFlag'>
23
+ dropout_rate: '0.0'
24
+ input_key: fps
25
+ output_key: use_video_condition
26
+ conditioning_strategy: frame_replace
27
+ ema:
28
+ _target_: cosmos_predict2.configs.base.defaults.ema.EMAConfig
29
+ enabled: 'False'
30
+ iteration_shift: '0'
31
+ rate: '0.1'
32
+ guardrail_config:
33
+ checkpoint_dir: checkpoints
34
+ enabled: 'False'
35
+ offload_model_to_cpu: 'False'
36
+ input_image_key: images
37
+ input_video_key: video
38
+ max_num_conditional_frames: '2'
39
+ min_num_conditional_frames: '1'
40
+ net:
41
+ _target_: <class 'cosmos_predict2.models.video2world_dit.MinimalV1LVGDiT'>
42
+ adaln_lora_dim: '256'
43
+ atten_backend: minimal_a2a
44
+ concat_padding_mask: 'True'
45
+ extra_per_block_abs_pos_emb: 'False'
46
+ in_channels: '16'
47
+ max_frames: '128'
48
+ max_img_h: '240'
49
+ max_img_w: '240'
50
+ model_channels: '2048'
51
+ num_blocks: '28'
52
+ num_heads: '16'
53
+ out_channels: '16'
54
+ patch_spatial: '2'
55
+ patch_temporal: '1'
56
+ pos_emb_cls: rope3d
57
+ pos_emb_interpolation: crop
58
+ pos_emb_learnable: 'True'
59
+ rope_enable_fps_modulation: 'False'
60
+ rope_h_extrapolation_ratio: '3.0'
61
+ rope_t_extrapolation_ratio: '1.0'
62
+ rope_w_extrapolation_ratio: '3.0'
63
+ sac_config:
64
+ _target_: cosmos_predict2.models.text2image_dit.SACConfig
65
+ every_n_blocks: '1'
66
+ mode: predict2_2b_720
67
+ use_adaln_lora: 'True'
68
+ precision: bfloat16
69
+ prompt_refiner_config:
70
+ checkpoint_dir: checkpoints/nvidia/Cosmos-Reason1-7B
71
+ enabled: 'True'
72
+ offload_model_to_cpu: 'False'
73
+ rectified_flow_loss_weight_uniform: 'True'
74
+ rectified_flow_t_scaling_factor: '1.0'
75
+ resize_online: 'True'
76
+ resolution: '720'
77
+ sigma_conditional: '0.0001'
78
+ sigma_data: '1.0'
79
+ state_ch: '16'
80
+ state_t: '24'
81
+ text_encoder:
82
+ cls: TextEncoderClass.T5
83
+ cosmos_reason1:
84
+ ckpt_path: checkpoints/nvidia/Cosmos-Reason1-Private/reason1_internal_real.pt
85
+ compute_online: 'True'
86
+ embed_dim: '100352'
87
+ embedding_concat_strategy: full_concat
88
+ model_config:
89
+ _target_: <class 'imaginaire.models.vlm_qwen_omni.QwenVLBaseModel'>
90
+ model_config:
91
+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenModelConfig
92
+ activation_checkpoint:
93
+ mode: selective
94
+ models: vlm
95
+ selective_ac_option: op
96
+ add_answer_tag: 'True'
97
+ add_cross_attention: 'False'
98
+ add_image_start_end_tag: 'False'
99
+ add_tile_tag: 'False'
100
+ architectures:
101
+ - Qwen2_5_VLForConditionalGeneration
102
+ attention_dropout: '0.0'
103
+ attn_implementation: flash_attention_2
104
+ attn_implementation_autoset: 'True'
105
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106
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111
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113
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114
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115
+ folder: checkpoint
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117
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119
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120
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121
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122
+ comm:
123
+ init_timeout_seconds: 300
124
+ trace_buf_size: 20000
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126
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130
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131
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132
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133
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134
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137
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138
+ enable_compiled_autograd: false
139
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140
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141
+ finetuning_task: null
142
+ float8:
143
+ enable_float8_linear: false
144
+ forced_bos_token_id: null
145
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146
+ freeze_llm: 'False'
147
+ freeze_mm_projector: 'False'
148
+ freeze_vision_encoder: 'False'
149
+ fsdp_enabled: 'False'
150
+ hidden_act: silu
151
+ hidden_size: '3584'
152
+ id2label:
153
+ 0: LABEL_0
154
+ 1: LABEL_1
155
+ image_token_id: '151655'
156
+ initializer_range: '0.02'
157
+ intermediate_size: '18944'
158
+ is_decoder: 'False'
159
+ is_encoder_decoder: 'False'
160
+ label2id:
161
+ LABEL_0: '0'
162
+ LABEL_1: '1'
163
+ length_penalty: '1.0'
164
+ loss_per_token: 'True'
165
+ max_batch_size: '1'
166
+ max_length: '20'
167
+ max_position_embeddings: '128000'
168
+ max_seq_len: '128000'
169
+ max_window_layers: '28'
170
+ min_length: '0'
171
+ mm_projector: null
172
+ model_type: qwen2_5_vl
173
+ name_or_path: Qwen/Qwen2.5-VL-7B-Instruct
174
+ no_repeat_ngram_size: '0'
175
+ num_attention_heads: '28'
176
+ num_beam_groups: '1'
177
+ num_beams: '1'
178
+ num_hidden_layers: '28'
179
+ num_key_value_heads: '4'
180
+ num_return_sequences: '1'
181
+ num_tiles: '1'
182
+ optimizer:
183
+ early_step_in_backward: false
184
+ end_lr: 2.5e-05
185
+ fused: false
186
+ init_lr: 1.0e-05
187
+ lr: 0.0003
188
+ lr_multiplier_llm: 1.0
189
+ lr_multiplier_mm_projector: 1.0
190
+ lr_multiplier_vision_encoder: 0.1
191
+ name: AdamW
192
+ output_attentions: 'False'
193
+ output_hidden_states: 'True'
194
+ output_scores: 'False'
195
+ pad_token_id: null
196
+ precision: bfloat16
197
+ prefix: null
198
+ prepend_padding: 'False'
199
+ problem_type: null
200
+ pruned_heads: _Nothing.NOTHING
201
+ remove_invalid_values: 'False'
202
+ repetition_penalty: '1.0'
203
+ return_dict: 'True'
204
+ return_dict_in_generate: 'False'
205
+ rms_norm_eps: 1e-06
206
+ rope_scaling:
207
+ mrope_section:
208
+ - '16'
209
+ - '24'
210
+ - '24'
211
+ rope_type: default
212
+ type: default
213
+ rope_theta: '1000000.0'
214
+ seed: '0'
215
+ sep_token_id: null
216
+ sliding_window: '32768'
217
+ suppress_tokens: null
218
+ task_specific_params: null
219
+ temperature: '1.0'
220
+ tf_legacy_loss: 'False'
221
+ tie_encoder_decoder: 'False'
222
+ tie_word_embeddings: 'False'
223
+ tile_tag_type: space_separated
224
+ tokenizer_class: null
225
+ tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct
226
+ top_k: '50'
227
+ top_p: '1.0'
228
+ torch_dtype: bfloat16
229
+ torchscript: 'False'
230
+ training:
231
+ compile: false
232
+ context_parallel_degree: 1
233
+ data_parallel_replicate_degree: 1
234
+ data_parallel_shard_degree: -1
235
+ disable_loss_parallel: false
236
+ enable_cpu_offload: false
237
+ fsdp_reshard_after_forward: default
238
+ mixed_precision_param: bfloat16
239
+ mixed_precision_reduce: float32
240
+ steps: 400000
241
+ tensor_parallel_degree: 1
242
+ use_cosine_decay: false
243
+ use_linear_decay: true
244
+ warmup_steps: 1000
245
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246
+ transformers_version: 4.51.0.dev0
247
+ typical_p: '1.0'
248
+ use_bfloat16: 'False'
249
+ use_cache: 'False'
250
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251
+ use_return_dict: 'True'
252
+ use_rope_from_torchtitan: 'False'
253
+ use_sliding_window: 'False'
254
+ video_token_id: '151656'
255
+ vision_config:
256
+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenVisionConfig
257
+ add_cross_attention: 'False'
258
+ architectures: null
259
+ attn_implementation: flash_attention_2
260
+ attn_implementation_autoset: 'True'
261
+ bad_words_ids: null
262
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268
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269
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270
+ early_stopping: 'False'
271
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278
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279
+ - '7'
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+ - '15'
281
+ - '23'
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+ - '31'
283
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322
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323
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324
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325
+ temperature: '1.0'
326
+ temporal_patch_size: '2'
327
+ tf_legacy_loss: 'False'
328
+ tie_encoder_decoder: 'False'
329
+ tie_word_embeddings: 'True'
330
+ tokenizer_class: null
331
+ tokens_per_second: '2'
332
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333
+ top_p: '1.0'
334
+ torch_dtype: bfloat16
335
+ torchscript: 'False'
336
+ typical_p: '1.0'
337
+ use_bfloat16: 'False'
338
+ window_size: '112'
339
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340
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341
+ depth_init: true
342
+ dim: 1024
343
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+ head_dim: null
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353
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+ norm_type: rmsnorm
355
+ num_channels: 3
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+ vision_start_token_id: '151652'
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+ tokenizer:
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+ _target_: <function build_tokenizer at 0x7e6f5c296520>
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+ cache_dir: checkpoints/nvidia/Cosmos-Reason1-Private/tokenizer
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+ tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct
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+ n_layers_per_group: '5'
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+ num_tokens: '512'
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+ t5:
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+ ckpt_path: checkpoints/google-t5/t5-11b
376
+ embed_dim: '1024'
377
+ num_tokens: '512'
378
+ timestamps:
379
+ is_forward: 'False'
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+ nfe: '35'
381
+ order: '7.0'
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+ t_max: '80.0'
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+ t_min: '0.002'
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+ tokenizer:
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+ _target_: <class 'cosmos_predict2.tokenizers.tokenizer.TokenizerInterface'>
386
+ chunk_duration: '81'
387
+ load_mean_std: 'False'
388
+ name: tokenizer
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+ temporal_window: '16'
390
+ vae_pth: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
08a0e63da36bd3fade24514337eca65c/input0.jpg ADDED

Git LFS Details

  • SHA256: c76d007424b550e495a50721fdab96d344b99a7c3cd0694602a836d61661f76c
  • Pointer size: 130 Bytes
  • Size of remote file: 18.8 kB
08a0e63da36bd3fade24514337eca65c/run.log ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0
 
 
 
 
 
1
+ fatal: detected dubious ownership in repository at '/workspace'
2
+ To add an exception for this directory, call:
3
+
4
+ git config --global --add safe.directory /workspace
5
+ [01-15 17:42:33|INFO|imaginaire/constants.py:39:print_environment_info] imaginaire.constants: Namespace(checkpoints='checkpoints', text_encoder=<TextEncoderClass.T5: 't5'>)
6
+ [01-15 17:42:33|INFO|imaginaire/constants.py:40:print_environment_info] sys.argv: ['/workspace/examples/video2world.py', '--model_size', '2B', '--input_path', '/workspace/video2world_out/08a0e63da36bd3fade24514337eca65c/input0.jpg', '--num_conditional_frames', '1', '--prompt', 'The video depicts a nighttime urban driving scene on a multi - lane road. The road is illuminated by streetlights and vehicle headlights, with dark surroundings indicating it is night. Multiple cars, including a white pickup truck, a silver sedan, and a red SUV, are present, moving slowly in what appears to be heavy traffic. Construction workers in reflective gear and signs like “KEEP RIGHT” suggest lane - related traffic control. Vehicles maintain a slow pace, likely due to congestion or roadwork. No pedestrians or cyclists are visible. The road surface shows signs of wear, and the overall environment is characterized by artificial lighting from streetlights and vehicle lights.', '--save_path', '/workspace/video2world_out/08a0e63da36bd3fade24514337eca65c/video2world_2B.mp4', '--disable_guardrail']
7
+ [01-15 17:42:33|INFO|imaginaire/constants.py:41:print_environment_info] args: Namespace(model_size='2B', resolution='720', fps=16, dit_path='', load_ema=False, prompt='The video depicts a nighttime urban driving scene on a multi - lane road. The road is illuminated by streetlights and vehicle headlights, with dark surroundings indicating it is night. Multiple cars, including a white pickup truck, a silver sedan, and a red SUV, are present, moving slowly in what appears to be heavy traffic. Construction workers in reflective gear and signs like “KEEP RIGHT” suggest lane - related traffic control. Vehicles maintain a slow pace, likely due to congestion or roadwork. No pedestrians or cyclists are visible. The road surface shows signs of wear, and the overall environment is characterized by artificial lighting from streetlights and vehicle lights.', input_path='/workspace/video2world_out/08a0e63da36bd3fade24514337eca65c/input0.jpg', negative_prompt='The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.', aspect_ratio='16:9', num_conditional_frames=1, batch_input_json=None, guidance=7, seed=0, save_path='/workspace/video2world_out/08a0e63da36bd3fade24514337eca65c/video2world_2B.mp4', num_gpus=1, disable_guardrail=True, offload_guardrail=False, disable_prompt_refiner=False, offload_prompt_refiner=False, offload_text_encoder=False, downcast_text_encoder=False, benchmark=False, use_cuda_graphs=False, natten=False)
8
+ [01-15 17:42:33|INFO|examples/video2world.py:210:setup_pipeline] Using dit_path: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
9
+ [01-15 17:42:33|INFO|imaginaire/utils/misc.py:139:set_random_seed] Using random seed 0.
10
+ [01-15 17:42:33|WARNING|examples/video2world.py:241:setup_pipeline] Guardrail checks are disabled
11
+ [01-15 17:42:33|WARNING|imaginaire/lazy_config/lazy.py:441:save_yaml] Config is saved using omegaconf at /workspace/video2world_out/08a0e63da36bd3fade24514337eca65c/video2world_2B.yaml.
12
+ [01-15 17:42:33|INFO|examples/video2world.py:259:setup_pipeline] Initializing Video2WorldPipeline with model size: 2B
13
+ [01-15 17:42:33|WARNING|cosmos_predict2/pipelines/video2world.py:292:from_config] precision torch.bfloat16
14
+ [01-15 17:42:36|INFO|cosmos_predict2/tokenizers/tokenizer.py:599:_video_vae] Loading checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
15
+ [01-15 17:42:36|SUCCESS|cosmos_predict2/tokenizers/tokenizer.py:601:_video_vae] Successfully loaded checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
16
+ [01-15 17:45:39|INFO|imaginaire/auxiliary/text_encoder.py:345:__init__] T5 Text encoder model instantiated
17
+
18
+ [01-15 17:46:46|INFO|cosmos_predict2/pipelines/video2world.py:354:from_config] Loading DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
19
+ [01-15 17:46:52|SUCCESS|cosmos_predict2/pipelines/video2world.py:373:from_config] Successfully loaded DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
20
+ [01-15 17:46:53|INFO|examples/video2world.py:297:process_single_generation] Running Video2WorldPipeline
21
+ input: /workspace/video2world_out/08a0e63da36bd3fade24514337eca65c/input0.jpg
22
+ prompt: The video depicts a nighttime urban driving scene on a multi - lane road. The road is illuminated by streetlights and vehicle headlights, with dark surroundings indicating it is night. Multiple cars, including a white pickup truck, a silver sedan, and a red SUV, are present, moving slowly in what appears to be heavy traffic. Construction workers in reflective gear and signs like “KEEP RIGHT” suggest lane - related traffic control. Vehicles maintain a slow pace, likely due to congestion or roadwork. No pedestrians or cyclists are visible. The road surface shows signs of wear, and the overall environment is characterized by artificial lighting from streetlights and vehicle lights.
23
+ [01-15 17:46:53|WARNING|cosmos_predict2/pipelines/video2world.py:821:__call__] Guardrail checks on prompt are disabled
24
+ [01-15 17:46:53|INFO|cosmos_predict2/pipelines/video2world.py:830:__call__] Starting prompt refinement...
25
+ [01-15 17:47:02|INFO|cosmos_predict2/pipelines/video2world.py:832:__call__] Finished prompt refinement
26
+ [01-15 17:47:02|WARNING|cosmos_predict2/pipelines/video2world.py:845:__call__] Guardrail checks on refined prompt are disabled
27
+ [01-15 17:47:18|INFO|cosmos_predict2/pipelines/video2world.py:898:__call__] Starting video generation...
28
+
29
 
30
+ [01-15 17:57:22|INFO|examples/video2world.py:330:process_single_generation] Saving the generated video to: /workspace/video2world_out/08a0e63da36bd3fade24514337eca65c/video2world_2B.mp4
31
+ [01-15 17:57:26|SUCCESS|examples/video2world.py:336:process_single_generation] Successfully saved video to: /workspace/video2world_out/08a0e63da36bd3fade24514337eca65c/video2world_2B.mp4
32
+ [01-15 17:57:26|SUCCESS|examples/video2world.py:347:process_single_generation] Successfully saved prompt file to: /workspace/video2world_out/08a0e63da36bd3fade24514337eca65c/video2world_2B.txt
08a0e63da36bd3fade24514337eca65c/video2world_2B.mp4 ADDED
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08a0e63da36bd3fade24514337eca65c/video2world_2B.txt ADDED
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+ [Prompt]
2
+ The video depicts a nighttime urban driving scene on a multi - lane road. The road is illuminated by streetlights and vehicle headlights, with dark surroundings indicating it is night. Multiple cars, including a white pickup truck, a silver sedan, and a red SUV, are present, moving slowly in what appears to be heavy traffic. Construction workers in reflective gear and signs like “KEEP RIGHT” suggest lane - related traffic control. Vehicles maintain a slow pace, likely due to congestion or roadwork. No pedestrians or cyclists are visible. The road surface shows signs of wear, and the overall environment is characterized by artificial lighting from streetlights and vehicle lights.
3
+ [Negative Prompt]
4
+ The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.
5
+ [Refined Prompt]
6
+ A nighttime urban driving scene captures a multi-lane road illuminated by streetlights and vehicle headlights. The dark surroundings indicate it is night, with multiple cars, including a white pickup truck, a silver sedan, and a red SUV, moving slowly in heavy traffic. Construction workers in reflective gear and signs like "KEEP RIGHT" suggest lane-related traffic control. Vehicles maintain a slow pace, likely due to congestion or roadwork. The road surface shows signs of wear, and the overall environment is characterized by artificial lighting from streetlights and vehicle lights. A wide-angle shot from a slightly elevated perspective.
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+ _target_: <class 'cosmos_predict2.models.video2world_dit.MinimalV1LVGDiT'>
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+ return_dict: 'True'
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+ return_dict_in_generate: 'False'
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+ - '16'
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226
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+ training:
231
+ compile: false
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+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenVisionConfig
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+ architectures: null
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+ n_layers_per_group: '5'
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+ num_tokens: '512'
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+ ckpt_path: checkpoints/google-t5/t5-11b
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+ embed_dim: '1024'
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+ num_tokens: '512'
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+ timestamps:
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+ order: '7.0'
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+ t_min: '0.002'
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+ _target_: <class 'cosmos_predict2.tokenizers.tokenizer.TokenizerInterface'>
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+ chunk_duration: '81'
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+ load_mean_std: 'False'
388
+ name: tokenizer
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+ temporal_window: '16'
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+ vae_pth: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
16b4eef5d7a47892e2342e6a83f5929f/input0.jpg ADDED

Git LFS Details

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  • Pointer size: 130 Bytes
  • Size of remote file: 28.9 kB
16b4eef5d7a47892e2342e6a83f5929f/run.log ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0
 
 
 
 
 
1
+ fatal: detected dubious ownership in repository at '/workspace'
2
+ To add an exception for this directory, call:
3
+
4
+ git config --global --add safe.directory /workspace
5
+ [01-15 17:42:33|INFO|imaginaire/constants.py:39:print_environment_info] imaginaire.constants: Namespace(checkpoints='checkpoints', text_encoder=<TextEncoderClass.T5: 't5'>)
6
+ [01-15 17:42:33|INFO|imaginaire/constants.py:40:print_environment_info] sys.argv: ['/workspace/examples/video2world.py', '--model_size', '2B', '--input_path', '/workspace/video2world_out/16b4eef5d7a47892e2342e6a83f5929f/input0.jpg', '--num_conditional_frames', '1', '--prompt', 'A vehicle drives through a sunny urban intersection, starting at a red light before proceeding as the light turns green. The road is a multi-lane street with buildings, trees, and utility poles lining the sides. Several cars are visible, including a black SUV turning left and other vehicles moving straight or parked along the curb. The sky is clear and bright, indicating a sunny day. As the vehicle continues forward, it travels past more parked cars, commercial buildings, and dense foliage, maintaining a steady pace on the relatively straight road. No pedestrians or cyclists are seen, and the scene remains calm with no notable stops or lane changes beyond the initial intersection.', '--save_path', '/workspace/video2world_out/16b4eef5d7a47892e2342e6a83f5929f/video2world_2B.mp4', '--disable_guardrail']
7
+ [01-15 17:42:33|INFO|imaginaire/constants.py:41:print_environment_info] args: Namespace(model_size='2B', resolution='720', fps=16, dit_path='', load_ema=False, prompt='A vehicle drives through a sunny urban intersection, starting at a red light before proceeding as the light turns green. The road is a multi-lane street with buildings, trees, and utility poles lining the sides. Several cars are visible, including a black SUV turning left and other vehicles moving straight or parked along the curb. The sky is clear and bright, indicating a sunny day. As the vehicle continues forward, it travels past more parked cars, commercial buildings, and dense foliage, maintaining a steady pace on the relatively straight road. No pedestrians or cyclists are seen, and the scene remains calm with no notable stops or lane changes beyond the initial intersection.', input_path='/workspace/video2world_out/16b4eef5d7a47892e2342e6a83f5929f/input0.jpg', negative_prompt='The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.', aspect_ratio='16:9', num_conditional_frames=1, batch_input_json=None, guidance=7, seed=0, save_path='/workspace/video2world_out/16b4eef5d7a47892e2342e6a83f5929f/video2world_2B.mp4', num_gpus=1, disable_guardrail=True, offload_guardrail=False, disable_prompt_refiner=False, offload_prompt_refiner=False, offload_text_encoder=False, downcast_text_encoder=False, benchmark=False, use_cuda_graphs=False, natten=False)
8
+ [01-15 17:42:33|INFO|examples/video2world.py:210:setup_pipeline] Using dit_path: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
9
+ [01-15 17:42:33|INFO|imaginaire/utils/misc.py:139:set_random_seed] Using random seed 0.
10
+ [01-15 17:42:33|WARNING|examples/video2world.py:241:setup_pipeline] Guardrail checks are disabled
11
+ [01-15 17:42:33|WARNING|imaginaire/lazy_config/lazy.py:441:save_yaml] Config is saved using omegaconf at /workspace/video2world_out/16b4eef5d7a47892e2342e6a83f5929f/video2world_2B.yaml.
12
+ [01-15 17:42:33|INFO|examples/video2world.py:259:setup_pipeline] Initializing Video2WorldPipeline with model size: 2B
13
+ [01-15 17:42:33|WARNING|cosmos_predict2/pipelines/video2world.py:292:from_config] precision torch.bfloat16
14
+ [01-15 17:42:36|INFO|cosmos_predict2/tokenizers/tokenizer.py:599:_video_vae] Loading checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
15
+ [01-15 17:42:36|SUCCESS|cosmos_predict2/tokenizers/tokenizer.py:601:_video_vae] Successfully loaded checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
16
+ [01-15 17:45:40|INFO|imaginaire/auxiliary/text_encoder.py:345:__init__] T5 Text encoder model instantiated
17
+
18
+ [01-15 17:46:46|INFO|cosmos_predict2/pipelines/video2world.py:354:from_config] Loading DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
19
+ [01-15 17:46:52|SUCCESS|cosmos_predict2/pipelines/video2world.py:373:from_config] Successfully loaded DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
20
+ [01-15 17:46:53|INFO|examples/video2world.py:297:process_single_generation] Running Video2WorldPipeline
21
+ input: /workspace/video2world_out/16b4eef5d7a47892e2342e6a83f5929f/input0.jpg
22
+ prompt: A vehicle drives through a sunny urban intersection, starting at a red light before proceeding as the light turns green. The road is a multi-lane street with buildings, trees, and utility poles lining the sides. Several cars are visible, including a black SUV turning left and other vehicles moving straight or parked along the curb. The sky is clear and bright, indicating a sunny day. As the vehicle continues forward, it travels past more parked cars, commercial buildings, and dense foliage, maintaining a steady pace on the relatively straight road. No pedestrians or cyclists are seen, and the scene remains calm with no notable stops or lane changes beyond the initial intersection.
23
+ [01-15 17:46:53|WARNING|cosmos_predict2/pipelines/video2world.py:821:__call__] Guardrail checks on prompt are disabled
24
+ [01-15 17:46:53|INFO|cosmos_predict2/pipelines/video2world.py:830:__call__] Starting prompt refinement...
25
+ [01-15 17:47:03|INFO|cosmos_predict2/pipelines/video2world.py:832:__call__] Finished prompt refinement
26
+ [01-15 17:47:03|WARNING|cosmos_predict2/pipelines/video2world.py:845:__call__] Guardrail checks on refined prompt are disabled
27
+ [01-15 17:47:17|INFO|cosmos_predict2/pipelines/video2world.py:898:__call__] Starting video generation...
28
+
29
 
30
+ [01-15 17:57:07|INFO|examples/video2world.py:330:process_single_generation] Saving the generated video to: /workspace/video2world_out/16b4eef5d7a47892e2342e6a83f5929f/video2world_2B.mp4
31
+ [01-15 17:57:11|SUCCESS|examples/video2world.py:336:process_single_generation] Successfully saved video to: /workspace/video2world_out/16b4eef5d7a47892e2342e6a83f5929f/video2world_2B.mp4
32
+ [01-15 17:57:11|SUCCESS|examples/video2world.py:347:process_single_generation] Successfully saved prompt file to: /workspace/video2world_out/16b4eef5d7a47892e2342e6a83f5929f/video2world_2B.txt
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+ [Prompt]
2
+ A vehicle drives through a sunny urban intersection, starting at a red light before proceeding as the light turns green. The road is a multi-lane street with buildings, trees, and utility poles lining the sides. Several cars are visible, including a black SUV turning left and other vehicles moving straight or parked along the curb. The sky is clear and bright, indicating a sunny day. As the vehicle continues forward, it travels past more parked cars, commercial buildings, and dense foliage, maintaining a steady pace on the relatively straight road. No pedestrians or cyclists are seen, and the scene remains calm with no notable stops or lane changes beyond the initial intersection.
3
+ [Negative Prompt]
4
+ The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.
5
+ [Refined Prompt]
6
+ A vehicle drives through a sunny urban intersection, starting at a red light before proceeding as the light turns green. The road is a multi-lane street with buildings, trees, and utility poles lining the sides. Several cars are visible, including a black SUV turning left and other vehicles moving straight or parked along the curb. The sky is clear and bright, indicating a sunny day. As the vehicle continues forward, it travels past more parked cars, commercial buildings, and dense foliage, maintaining a steady pace on the relatively straight road. No pedestrians or cyclists are seen, and the scene remains calm with no notable stops or lane changes beyond the initial intersection. A dynamic medium shot captures the vehicle's journey through the bustling cityscape.
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+ adjust_video_noise: 'True'
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+ conditioner:
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+ _target_: <class 'cosmos_predict2.conditioner.VideoConditioner'>
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+ _target_: <class 'cosmos_predict2.conditioner.ReMapkey'>
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+ dropout_rate: '0.0'
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+ - t5_text_embeddings
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+ use_video_condition:
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+ _target_: <class 'cosmos_predict2.conditioner.BooleanFlag'>
23
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+ _target_: cosmos_predict2.configs.base.defaults.ema.EMAConfig
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+ enabled: 'False'
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+ iteration_shift: '0'
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+ rate: '0.1'
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+ guardrail_config:
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+ input_video_key: video
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+ max_num_conditional_frames: '2'
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+ net:
41
+ _target_: <class 'cosmos_predict2.models.video2world_dit.MinimalV1LVGDiT'>
42
+ adaln_lora_dim: '256'
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+ atten_backend: minimal_a2a
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+ concat_padding_mask: 'True'
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+ in_channels: '16'
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+ max_frames: '128'
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+ pos_emb_cls: rope3d
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+ rope_enable_fps_modulation: 'False'
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+ rope_h_extrapolation_ratio: '3.0'
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+ rope_w_extrapolation_ratio: '3.0'
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+ sac_config:
64
+ _target_: cosmos_predict2.models.text2image_dit.SACConfig
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+ mode: predict2_2b_720
67
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70
+ checkpoint_dir: checkpoints/nvidia/Cosmos-Reason1-7B
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+ enabled: 'True'
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73
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77
+ sigma_conditional: '0.0001'
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84
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85
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86
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89
+ _target_: <class 'imaginaire.models.vlm_qwen_omni.QwenVLBaseModel'>
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+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenModelConfig
92
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93
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+ add_tile_tag: 'False'
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101
+ - Qwen2_5_VLForConditionalGeneration
102
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206
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+ name: tokenizer
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Git LFS Details

  • SHA256: 05bdd2860faeb3697f89046c56ac9aaa05d7e7aff3cab6ffcfd5d1beb0a9096c
  • Pointer size: 130 Bytes
  • Size of remote file: 53.8 kB
191ed6f62a0f4d1c23107f8f4939f153/run.log ADDED
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0
 
 
 
 
 
1
+ fatal: detected dubious ownership in repository at '/workspace'
2
+ To add an exception for this directory, call:
3
+
4
+ git config --global --add safe.directory /workspace
5
+ [01-15 17:42:33|INFO|imaginaire/constants.py:39:print_environment_info] imaginaire.constants: Namespace(checkpoints='checkpoints', text_encoder=<TextEncoderClass.T5: 't5'>)
6
+ [01-15 17:42:33|INFO|imaginaire/constants.py:40:print_environment_info] sys.argv: ['/workspace/examples/video2world.py', '--model_size', '2B', '--input_path', '/workspace/video2world_out/191ed6f62a0f4d1c23107f8f4939f153/input0.jpg', '--num_conditional_frames', '1', '--prompt', 'The video depicts a sunny day in an urban area, with a vehicle driving along a multi - lane street flanked by tall residential and commercial buildings. Several cars, including a black SUV in the center lane, navigate the road, stopping at red traffic lights and proceeding when they turn green. Pedestrians are visible on sidewalks, and trees line the street, adding greenery to the cityscape. Traffic signs, such as no - parking and street name markers, are present. The scene shows typical city driving dynamics, with vehicles maintaining their lanes, stopping at intersections, and moving through the urban environment without any notable incidents like near - misses.', '--save_path', '/workspace/video2world_out/191ed6f62a0f4d1c23107f8f4939f153/video2world_2B.mp4', '--disable_guardrail']
7
+ [01-15 17:42:33|INFO|imaginaire/constants.py:41:print_environment_info] args: Namespace(model_size='2B', resolution='720', fps=16, dit_path='', load_ema=False, prompt='The video depicts a sunny day in an urban area, with a vehicle driving along a multi - lane street flanked by tall residential and commercial buildings. Several cars, including a black SUV in the center lane, navigate the road, stopping at red traffic lights and proceeding when they turn green. Pedestrians are visible on sidewalks, and trees line the street, adding greenery to the cityscape. Traffic signs, such as no - parking and street name markers, are present. The scene shows typical city driving dynamics, with vehicles maintaining their lanes, stopping at intersections, and moving through the urban environment without any notable incidents like near - misses.', input_path='/workspace/video2world_out/191ed6f62a0f4d1c23107f8f4939f153/input0.jpg', negative_prompt='The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.', aspect_ratio='16:9', num_conditional_frames=1, batch_input_json=None, guidance=7, seed=0, save_path='/workspace/video2world_out/191ed6f62a0f4d1c23107f8f4939f153/video2world_2B.mp4', num_gpus=1, disable_guardrail=True, offload_guardrail=False, disable_prompt_refiner=False, offload_prompt_refiner=False, offload_text_encoder=False, downcast_text_encoder=False, benchmark=False, use_cuda_graphs=False, natten=False)
8
+ [01-15 17:42:33|INFO|examples/video2world.py:210:setup_pipeline] Using dit_path: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
9
+ [01-15 17:42:33|INFO|imaginaire/utils/misc.py:139:set_random_seed] Using random seed 0.
10
+ [01-15 17:42:33|WARNING|examples/video2world.py:241:setup_pipeline] Guardrail checks are disabled
11
+ [01-15 17:42:33|WARNING|imaginaire/lazy_config/lazy.py:441:save_yaml] Config is saved using omegaconf at /workspace/video2world_out/191ed6f62a0f4d1c23107f8f4939f153/video2world_2B.yaml.
12
+ [01-15 17:42:33|INFO|examples/video2world.py:259:setup_pipeline] Initializing Video2WorldPipeline with model size: 2B
13
+ [01-15 17:42:33|WARNING|cosmos_predict2/pipelines/video2world.py:292:from_config] precision torch.bfloat16
14
+ [01-15 17:42:36|INFO|cosmos_predict2/tokenizers/tokenizer.py:599:_video_vae] Loading checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
15
+ [01-15 17:42:36|SUCCESS|cosmos_predict2/tokenizers/tokenizer.py:601:_video_vae] Successfully loaded checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
16
+ [01-15 17:45:36|INFO|imaginaire/auxiliary/text_encoder.py:345:__init__] T5 Text encoder model instantiated
17
+
18
+ [01-15 17:46:46|INFO|cosmos_predict2/pipelines/video2world.py:354:from_config] Loading DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
19
+ [01-15 17:46:52|SUCCESS|cosmos_predict2/pipelines/video2world.py:373:from_config] Successfully loaded DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
20
+ [01-15 17:46:53|INFO|examples/video2world.py:297:process_single_generation] Running Video2WorldPipeline
21
+ input: /workspace/video2world_out/191ed6f62a0f4d1c23107f8f4939f153/input0.jpg
22
+ prompt: The video depicts a sunny day in an urban area, with a vehicle driving along a multi - lane street flanked by tall residential and commercial buildings. Several cars, including a black SUV in the center lane, navigate the road, stopping at red traffic lights and proceeding when they turn green. Pedestrians are visible on sidewalks, and trees line the street, adding greenery to the cityscape. Traffic signs, such as no - parking and street name markers, are present. The scene shows typical city driving dynamics, with vehicles maintaining their lanes, stopping at intersections, and moving through the urban environment without any notable incidents like near - misses.
23
+ [01-15 17:46:53|WARNING|cosmos_predict2/pipelines/video2world.py:821:__call__] Guardrail checks on prompt are disabled
24
+ [01-15 17:46:53|INFO|cosmos_predict2/pipelines/video2world.py:830:__call__] Starting prompt refinement...
25
+ [01-15 17:47:03|INFO|cosmos_predict2/pipelines/video2world.py:832:__call__] Finished prompt refinement
26
+ [01-15 17:47:03|WARNING|cosmos_predict2/pipelines/video2world.py:845:__call__] Guardrail checks on refined prompt are disabled
27
+ [01-15 17:47:18|INFO|cosmos_predict2/pipelines/video2world.py:898:__call__] Starting video generation...
28
+
29
 
30
+ [01-15 17:57:21|INFO|examples/video2world.py:330:process_single_generation] Saving the generated video to: /workspace/video2world_out/191ed6f62a0f4d1c23107f8f4939f153/video2world_2B.mp4
31
+ [01-15 17:57:24|SUCCESS|examples/video2world.py:336:process_single_generation] Successfully saved video to: /workspace/video2world_out/191ed6f62a0f4d1c23107f8f4939f153/video2world_2B.mp4
32
+ [01-15 17:57:24|SUCCESS|examples/video2world.py:347:process_single_generation] Successfully saved prompt file to: /workspace/video2world_out/191ed6f62a0f4d1c23107f8f4939f153/video2world_2B.txt
191ed6f62a0f4d1c23107f8f4939f153/video2world_2B.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:4145e755359aacd0f1cc3c552b4db7219acdbf16923e1ee9c8aecfd965876295
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+ size 6673165
191ed6f62a0f4d1c23107f8f4939f153/video2world_2B.txt ADDED
@@ -0,0 +1,6 @@
 
 
 
 
 
 
 
1
+ [Prompt]
2
+ The video depicts a sunny day in an urban area, with a vehicle driving along a multi - lane street flanked by tall residential and commercial buildings. Several cars, including a black SUV in the center lane, navigate the road, stopping at red traffic lights and proceeding when they turn green. Pedestrians are visible on sidewalks, and trees line the street, adding greenery to the cityscape. Traffic signs, such as no - parking and street name markers, are present. The scene shows typical city driving dynamics, with vehicles maintaining their lanes, stopping at intersections, and moving through the urban environment without any notable incidents like near - misses.
3
+ [Negative Prompt]
4
+ The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.
5
+ [Refined Prompt]
6
+ A sunny day captures a bustling urban street scene with multiple lanes of traffic. A black SUV is prominently positioned in the center lane, navigating through the flow of vehicles. Surrounding it are various cars, including sedans and hatchbacks, all adhering to traffic signals and maintaining their respective lanes. Pedestrians can be seen walking along the sidewalks, adding life to the urban landscape. Tall residential and commercial buildings flank both sides of the street, with trees lining the sidewalks, providing patches of greenery amidst the concrete structures. Traffic signs, such as no-parking zones and street name markers, are clearly visible, guiding the flow of traffic. The scene portrays typical city driving dynamics, with vehicles smoothly transitioning between stops and go phases at intersections, creating a sense of organized movement within the urban environment.
191ed6f62a0f4d1c23107f8f4939f153/video2world_2B.yaml ADDED
@@ -0,0 +1,390 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ adjust_video_noise: 'True'
2
+ conditioner:
3
+ _target_: <class 'cosmos_predict2.conditioner.VideoConditioner'>
4
+ fps:
5
+ _target_: <class 'cosmos_predict2.conditioner.ReMapkey'>
6
+ dropout_rate: '0.0'
7
+ dtype: null
8
+ input_key: fps
9
+ output_key: fps
10
+ padding_mask:
11
+ _target_: <class 'cosmos_predict2.conditioner.ReMapkey'>
12
+ dropout_rate: '0.0'
13
+ dtype: null
14
+ input_key: padding_mask
15
+ output_key: padding_mask
16
+ text:
17
+ _target_: <class 'cosmos_predict2.conditioner.TextAttr'>
18
+ dropout_rate: '0.2'
19
+ input_key:
20
+ - t5_text_embeddings
21
+ use_video_condition:
22
+ _target_: <class 'cosmos_predict2.conditioner.BooleanFlag'>
23
+ dropout_rate: '0.0'
24
+ input_key: fps
25
+ output_key: use_video_condition
26
+ conditioning_strategy: frame_replace
27
+ ema:
28
+ _target_: cosmos_predict2.configs.base.defaults.ema.EMAConfig
29
+ enabled: 'False'
30
+ iteration_shift: '0'
31
+ rate: '0.1'
32
+ guardrail_config:
33
+ checkpoint_dir: checkpoints
34
+ enabled: 'False'
35
+ offload_model_to_cpu: 'False'
36
+ input_image_key: images
37
+ input_video_key: video
38
+ max_num_conditional_frames: '2'
39
+ min_num_conditional_frames: '1'
40
+ net:
41
+ _target_: <class 'cosmos_predict2.models.video2world_dit.MinimalV1LVGDiT'>
42
+ adaln_lora_dim: '256'
43
+ atten_backend: minimal_a2a
44
+ concat_padding_mask: 'True'
45
+ extra_per_block_abs_pos_emb: 'False'
46
+ in_channels: '16'
47
+ max_frames: '128'
48
+ max_img_h: '240'
49
+ max_img_w: '240'
50
+ model_channels: '2048'
51
+ num_blocks: '28'
52
+ num_heads: '16'
53
+ out_channels: '16'
54
+ patch_spatial: '2'
55
+ patch_temporal: '1'
56
+ pos_emb_cls: rope3d
57
+ pos_emb_interpolation: crop
58
+ pos_emb_learnable: 'True'
59
+ rope_enable_fps_modulation: 'False'
60
+ rope_h_extrapolation_ratio: '3.0'
61
+ rope_t_extrapolation_ratio: '1.0'
62
+ rope_w_extrapolation_ratio: '3.0'
63
+ sac_config:
64
+ _target_: cosmos_predict2.models.text2image_dit.SACConfig
65
+ every_n_blocks: '1'
66
+ mode: predict2_2b_720
67
+ use_adaln_lora: 'True'
68
+ precision: bfloat16
69
+ prompt_refiner_config:
70
+ checkpoint_dir: checkpoints/nvidia/Cosmos-Reason1-7B
71
+ enabled: 'True'
72
+ offload_model_to_cpu: 'False'
73
+ rectified_flow_loss_weight_uniform: 'True'
74
+ rectified_flow_t_scaling_factor: '1.0'
75
+ resize_online: 'True'
76
+ resolution: '720'
77
+ sigma_conditional: '0.0001'
78
+ sigma_data: '1.0'
79
+ state_ch: '16'
80
+ state_t: '24'
81
+ text_encoder:
82
+ cls: TextEncoderClass.T5
83
+ cosmos_reason1:
84
+ ckpt_path: checkpoints/nvidia/Cosmos-Reason1-Private/reason1_internal_real.pt
85
+ compute_online: 'True'
86
+ embed_dim: '100352'
87
+ embedding_concat_strategy: full_concat
88
+ model_config:
89
+ _target_: <class 'imaginaire.models.vlm_qwen_omni.QwenVLBaseModel'>
90
+ model_config:
91
+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenModelConfig
92
+ activation_checkpoint:
93
+ mode: selective
94
+ models: vlm
95
+ selective_ac_option: op
96
+ add_answer_tag: 'True'
97
+ add_cross_attention: 'False'
98
+ add_image_start_end_tag: 'False'
99
+ add_tile_tag: 'False'
100
+ architectures:
101
+ - Qwen2_5_VLForConditionalGeneration
102
+ attention_dropout: '0.0'
103
+ attn_implementation: flash_attention_2
104
+ attn_implementation_autoset: 'True'
105
+ aux_loss_coeff: '0.0'
106
+ bad_words_ids: null
107
+ begin_suppress_tokens: null
108
+ bos_token_id: '151643'
109
+ cache_dir: null
110
+ checkpoint:
111
+ async_mode: disabled
112
+ create_seed_checkpoint: false
113
+ enable_checkpoint: false
114
+ export_dtype: float32
115
+ folder: checkpoint
116
+ interval: 500
117
+ interval_type: steps
118
+ model_weights_only: false
119
+ chunk_size_feed_forward: '0'
120
+ ckpt_dir: null
121
+ ckpt_path: null
122
+ comm:
123
+ init_timeout_seconds: 300
124
+ trace_buf_size: 20000
125
+ train_timeout_seconds: 100
126
+ cp_size: null
127
+ cross_attention_hidden_size: null
128
+ decoder_start_token_id: null
129
+ deterministic: 'False'
130
+ diversity_penalty: '0.0'
131
+ do_sample: 'False'
132
+ early_stopping: 'False'
133
+ encoder_no_repeat_ngram_size: '0'
134
+ eos_token_id: '151645'
135
+ ep_size: null
136
+ experimental:
137
+ enable_async_tensor_parallel: false
138
+ enable_compiled_autograd: false
139
+ pipeline_parallel_degree: 1
140
+ exponential_decay_length_penalty: null
141
+ finetuning_task: null
142
+ float8:
143
+ enable_float8_linear: false
144
+ forced_bos_token_id: null
145
+ forced_eos_token_id: null
146
+ freeze_llm: 'False'
147
+ freeze_mm_projector: 'False'
148
+ freeze_vision_encoder: 'False'
149
+ fsdp_enabled: 'False'
150
+ hidden_act: silu
151
+ hidden_size: '3584'
152
+ id2label:
153
+ 0: LABEL_0
154
+ 1: LABEL_1
155
+ image_token_id: '151655'
156
+ initializer_range: '0.02'
157
+ intermediate_size: '18944'
158
+ is_decoder: 'False'
159
+ is_encoder_decoder: 'False'
160
+ label2id:
161
+ LABEL_0: '0'
162
+ LABEL_1: '1'
163
+ length_penalty: '1.0'
164
+ loss_per_token: 'True'
165
+ max_batch_size: '1'
166
+ max_length: '20'
167
+ max_position_embeddings: '128000'
168
+ max_seq_len: '128000'
169
+ max_window_layers: '28'
170
+ min_length: '0'
171
+ mm_projector: null
172
+ model_type: qwen2_5_vl
173
+ name_or_path: Qwen/Qwen2.5-VL-7B-Instruct
174
+ no_repeat_ngram_size: '0'
175
+ num_attention_heads: '28'
176
+ num_beam_groups: '1'
177
+ num_beams: '1'
178
+ num_hidden_layers: '28'
179
+ num_key_value_heads: '4'
180
+ num_return_sequences: '1'
181
+ num_tiles: '1'
182
+ optimizer:
183
+ early_step_in_backward: false
184
+ end_lr: 2.5e-05
185
+ fused: false
186
+ init_lr: 1.0e-05
187
+ lr: 0.0003
188
+ lr_multiplier_llm: 1.0
189
+ lr_multiplier_mm_projector: 1.0
190
+ lr_multiplier_vision_encoder: 0.1
191
+ name: AdamW
192
+ output_attentions: 'False'
193
+ output_hidden_states: 'True'
194
+ output_scores: 'False'
195
+ pad_token_id: null
196
+ precision: bfloat16
197
+ prefix: null
198
+ prepend_padding: 'False'
199
+ problem_type: null
200
+ pruned_heads: _Nothing.NOTHING
201
+ remove_invalid_values: 'False'
202
+ repetition_penalty: '1.0'
203
+ return_dict: 'True'
204
+ return_dict_in_generate: 'False'
205
+ rms_norm_eps: 1e-06
206
+ rope_scaling:
207
+ mrope_section:
208
+ - '16'
209
+ - '24'
210
+ - '24'
211
+ rope_type: default
212
+ type: default
213
+ rope_theta: '1000000.0'
214
+ seed: '0'
215
+ sep_token_id: null
216
+ sliding_window: '32768'
217
+ suppress_tokens: null
218
+ task_specific_params: null
219
+ temperature: '1.0'
220
+ tf_legacy_loss: 'False'
221
+ tie_encoder_decoder: 'False'
222
+ tie_word_embeddings: 'False'
223
+ tile_tag_type: space_separated
224
+ tokenizer_class: null
225
+ tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct
226
+ top_k: '50'
227
+ top_p: '1.0'
228
+ torch_dtype: bfloat16
229
+ torchscript: 'False'
230
+ training:
231
+ compile: false
232
+ context_parallel_degree: 1
233
+ data_parallel_replicate_degree: 1
234
+ data_parallel_shard_degree: -1
235
+ disable_loss_parallel: false
236
+ enable_cpu_offload: false
237
+ fsdp_reshard_after_forward: default
238
+ mixed_precision_param: bfloat16
239
+ mixed_precision_reduce: float32
240
+ steps: 400000
241
+ tensor_parallel_degree: 1
242
+ use_cosine_decay: false
243
+ use_linear_decay: true
244
+ warmup_steps: 1000
245
+ training_seq_len: '4096'
246
+ transformers_version: 4.51.0.dev0
247
+ typical_p: '1.0'
248
+ use_bfloat16: 'False'
249
+ use_cache: 'False'
250
+ use_fsdp2: 'True'
251
+ use_return_dict: 'True'
252
+ use_rope_from_torchtitan: 'False'
253
+ use_sliding_window: 'False'
254
+ video_token_id: '151656'
255
+ vision_config:
256
+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenVisionConfig
257
+ add_cross_attention: 'False'
258
+ architectures: null
259
+ attn_implementation: flash_attention_2
260
+ attn_implementation_autoset: 'True'
261
+ bad_words_ids: null
262
+ begin_suppress_tokens: null
263
+ bos_token_id: null
264
+ chunk_size_feed_forward: '0'
265
+ cross_attention_hidden_size: null
266
+ decoder_start_token_id: null
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+ depth: '32'
268
+ diversity_penalty: '0.0'
269
+ do_sample: 'False'
270
+ early_stopping: 'False'
271
+ embed_dim: null
272
+ encoder_no_repeat_ngram_size: '0'
273
+ eos_token_id: null
274
+ exponential_decay_length_penalty: null
275
+ finetuning_task: null
276
+ forced_bos_token_id: null
277
+ forced_eos_token_id: null
278
+ fullatt_block_indexes:
279
+ - '7'
280
+ - '15'
281
+ - '23'
282
+ - '31'
283
+ hidden_act: silu
284
+ hidden_size: '1280'
285
+ id2label:
286
+ 0: LABEL_0
287
+ 1: LABEL_1
288
+ in_channels: '3'
289
+ in_chans: '3'
290
+ intermediate_size: '3420'
291
+ is_decoder: 'False'
292
+ is_encoder_decoder: 'False'
293
+ label2id:
294
+ LABEL_0: '0'
295
+ LABEL_1: '1'
296
+ length_penalty: '1.0'
297
+ max_length: '20'
298
+ min_length: '0'
299
+ mlp_ratio: null
300
+ model_type: qwen2_5_vl
301
+ name_or_path: ''
302
+ no_repeat_ngram_size: '0'
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+ num_beam_groups: '1'
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+ num_beams: '1'
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+ num_heads: '16'
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+ num_return_sequences: '1'
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+ out_hidden_size: '3584'
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+ output_attentions: 'False'
309
+ output_hidden_states: 'False'
310
+ output_scores: 'False'
311
+ pad_token_id: null
312
+ patch_size: '14'
313
+ prefix: null
314
+ problem_type: null
315
+ pruned_heads: _Nothing.NOTHING
316
+ remove_invalid_values: 'False'
317
+ repetition_penalty: '1.0'
318
+ return_dict: 'True'
319
+ return_dict_in_generate: 'False'
320
+ sep_token_id: null
321
+ spatial_merge_size: '2'
322
+ spatial_patch_size: '14'
323
+ suppress_tokens: null
324
+ task_specific_params: null
325
+ temperature: '1.0'
326
+ temporal_patch_size: '2'
327
+ tf_legacy_loss: 'False'
328
+ tie_encoder_decoder: 'False'
329
+ tie_word_embeddings: 'True'
330
+ tokenizer_class: null
331
+ tokens_per_second: '2'
332
+ top_k: '50'
333
+ top_p: '1.0'
334
+ torch_dtype: bfloat16
335
+ torchscript: 'False'
336
+ typical_p: '1.0'
337
+ use_bfloat16: 'False'
338
+ window_size: '112'
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+ vision_encoder: openai/clip-vit-base-patch32
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+ vision_encoder_config:
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+ depth_init: true
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+ dim: 1024
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+ ffn_dim_multiplier: null
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+ norm_type: rmsnorm
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+ num_channels: 3
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+ patch_size: 16
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+ proj_bias: null
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+ qkv_bias: null
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+ rope_theta: 10000.0
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+ use_cache: false
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+ use_rope_from_torchtitan: false
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+ vision_token_id: '151654'
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+ vocab_size: '152064'
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+ z_loss_coeff: '0.0'
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+ tokenizer:
369
+ _target_: <function build_tokenizer at 0x73af79a2a520>
370
+ cache_dir: checkpoints/nvidia/Cosmos-Reason1-Private/tokenizer
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+ tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct
372
+ n_layers_per_group: '5'
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+ num_tokens: '512'
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+ t5:
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+ ckpt_path: checkpoints/google-t5/t5-11b
376
+ embed_dim: '1024'
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+ num_tokens: '512'
378
+ timestamps:
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+ is_forward: 'False'
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+ nfe: '35'
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+ order: '7.0'
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+ t_max: '80.0'
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+ t_min: '0.002'
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+ tokenizer:
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+ _target_: <class 'cosmos_predict2.tokenizers.tokenizer.TokenizerInterface'>
386
+ chunk_duration: '81'
387
+ load_mean_std: 'False'
388
+ name: tokenizer
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+ temporal_window: '16'
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+ vae_pth: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
1c3d50949247baa54eae139fdddb9c53/input0.jpg ADDED

Git LFS Details

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  • Pointer size: 130 Bytes
  • Size of remote file: 30.5 kB
1c3d50949247baa54eae139fdddb9c53/run.log ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0
 
 
 
 
 
1
+ fatal: detected dubious ownership in repository at '/workspace'
2
+ To add an exception for this directory, call:
3
+
4
+ git config --global --add safe.directory /workspace
5
+ [01-15 17:42:33|INFO|imaginaire/constants.py:39:print_environment_info] imaginaire.constants: Namespace(checkpoints='checkpoints', text_encoder=<TextEncoderClass.T5: 't5'>)
6
+ [01-15 17:42:33|INFO|imaginaire/constants.py:40:print_environment_info] sys.argv: ['/workspace/examples/video2world.py', '--model_size', '2B', '--input_path', '/workspace/video2world_out/1c3d50949247baa54eae139fdddb9c53/input0.jpg', '--num_conditional_frames', '1', '--prompt', 'The video depicts a multi - lane highway scene during the daytime under partly cloudy skies. Several cars, including sedans and SUVs, travel forward in their respective lanes, with a white sedan often visible in the center lane. The road is flanked by tall trees on the right and open space with scattered vegetation on the left. A green road sign appears briefly on the right side of the highway. There are no pedestrians or cyclists; the only notable activity is the steady flow of traffic with no sudden turns, stops, or lane changes. The lighting is bright, indicating clear daytime conditions, and the overall environment is calm with no near - misses or significant events.', '--save_path', '/workspace/video2world_out/1c3d50949247baa54eae139fdddb9c53/video2world_2B.mp4', '--disable_guardrail']
7
+ [01-15 17:42:33|INFO|imaginaire/constants.py:41:print_environment_info] args: Namespace(model_size='2B', resolution='720', fps=16, dit_path='', load_ema=False, prompt='The video depicts a multi - lane highway scene during the daytime under partly cloudy skies. Several cars, including sedans and SUVs, travel forward in their respective lanes, with a white sedan often visible in the center lane. The road is flanked by tall trees on the right and open space with scattered vegetation on the left. A green road sign appears briefly on the right side of the highway. There are no pedestrians or cyclists; the only notable activity is the steady flow of traffic with no sudden turns, stops, or lane changes. The lighting is bright, indicating clear daytime conditions, and the overall environment is calm with no near - misses or significant events.', input_path='/workspace/video2world_out/1c3d50949247baa54eae139fdddb9c53/input0.jpg', negative_prompt='The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.', aspect_ratio='16:9', num_conditional_frames=1, batch_input_json=None, guidance=7, seed=0, save_path='/workspace/video2world_out/1c3d50949247baa54eae139fdddb9c53/video2world_2B.mp4', num_gpus=1, disable_guardrail=True, offload_guardrail=False, disable_prompt_refiner=False, offload_prompt_refiner=False, offload_text_encoder=False, downcast_text_encoder=False, benchmark=False, use_cuda_graphs=False, natten=False)
8
+ [01-15 17:42:33|INFO|examples/video2world.py:210:setup_pipeline] Using dit_path: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
9
+ [01-15 17:42:33|INFO|imaginaire/utils/misc.py:139:set_random_seed] Using random seed 0.
10
+ [01-15 17:42:33|WARNING|examples/video2world.py:241:setup_pipeline] Guardrail checks are disabled
11
+ [01-15 17:42:33|WARNING|imaginaire/lazy_config/lazy.py:441:save_yaml] Config is saved using omegaconf at /workspace/video2world_out/1c3d50949247baa54eae139fdddb9c53/video2world_2B.yaml.
12
+ [01-15 17:42:33|INFO|examples/video2world.py:259:setup_pipeline] Initializing Video2WorldPipeline with model size: 2B
13
+ [01-15 17:42:33|WARNING|cosmos_predict2/pipelines/video2world.py:292:from_config] precision torch.bfloat16
14
+ [01-15 17:42:36|INFO|cosmos_predict2/tokenizers/tokenizer.py:599:_video_vae] Loading checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
15
+ [01-15 17:42:36|SUCCESS|cosmos_predict2/tokenizers/tokenizer.py:601:_video_vae] Successfully loaded checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
16
+ [01-15 17:45:36|INFO|imaginaire/auxiliary/text_encoder.py:345:__init__] T5 Text encoder model instantiated
17
+
18
+ [01-15 17:46:46|INFO|cosmos_predict2/pipelines/video2world.py:354:from_config] Loading DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
19
+ [01-15 17:46:52|SUCCESS|cosmos_predict2/pipelines/video2world.py:373:from_config] Successfully loaded DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
20
+ [01-15 17:46:53|INFO|examples/video2world.py:297:process_single_generation] Running Video2WorldPipeline
21
+ input: /workspace/video2world_out/1c3d50949247baa54eae139fdddb9c53/input0.jpg
22
+ prompt: The video depicts a multi - lane highway scene during the daytime under partly cloudy skies. Several cars, including sedans and SUVs, travel forward in their respective lanes, with a white sedan often visible in the center lane. The road is flanked by tall trees on the right and open space with scattered vegetation on the left. A green road sign appears briefly on the right side of the highway. There are no pedestrians or cyclists; the only notable activity is the steady flow of traffic with no sudden turns, stops, or lane changes. The lighting is bright, indicating clear daytime conditions, and the overall environment is calm with no near - misses or significant events.
23
+ [01-15 17:46:53|WARNING|cosmos_predict2/pipelines/video2world.py:821:__call__] Guardrail checks on prompt are disabled
24
+ [01-15 17:46:53|INFO|cosmos_predict2/pipelines/video2world.py:830:__call__] Starting prompt refinement...
25
+ [01-15 17:47:03|INFO|cosmos_predict2/pipelines/video2world.py:832:__call__] Finished prompt refinement
26
+ [01-15 17:47:03|WARNING|cosmos_predict2/pipelines/video2world.py:845:__call__] Guardrail checks on refined prompt are disabled
27
+ [01-15 17:47:17|INFO|cosmos_predict2/pipelines/video2world.py:898:__call__] Starting video generation...
28
+
29
 
30
+ [01-15 17:57:02|INFO|examples/video2world.py:330:process_single_generation] Saving the generated video to: /workspace/video2world_out/1c3d50949247baa54eae139fdddb9c53/video2world_2B.mp4
31
+ [01-15 17:57:06|SUCCESS|examples/video2world.py:336:process_single_generation] Successfully saved video to: /workspace/video2world_out/1c3d50949247baa54eae139fdddb9c53/video2world_2B.mp4
32
+ [01-15 17:57:06|SUCCESS|examples/video2world.py:347:process_single_generation] Successfully saved prompt file to: /workspace/video2world_out/1c3d50949247baa54eae139fdddb9c53/video2world_2B.txt
1c3d50949247baa54eae139fdddb9c53/video2world_2B.mp4 ADDED
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1c3d50949247baa54eae139fdddb9c53/video2world_2B.txt ADDED
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+ [Prompt]
2
+ The video depicts a multi - lane highway scene during the daytime under partly cloudy skies. Several cars, including sedans and SUVs, travel forward in their respective lanes, with a white sedan often visible in the center lane. The road is flanked by tall trees on the right and open space with scattered vegetation on the left. A green road sign appears briefly on the right side of the highway. There are no pedestrians or cyclists; the only notable activity is the steady flow of traffic with no sudden turns, stops, or lane changes. The lighting is bright, indicating clear daytime conditions, and the overall environment is calm with no near - misses or significant events.
3
+ [Negative Prompt]
4
+ The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.
5
+ [Refined Prompt]
6
+ A daytime video capturing a multi-lane highway scene with a steady flow of traffic. Several vehicles, including sedans and SUVs, move smoothly in their designated lanes, with a white sedan frequently seen in the central lane. The road is bordered by tall trees on the right and open spaces with scattered vegetation on the left. A green road sign briefly appears on the right side of the highway. The scene is calm, with no pedestrians, cyclists, or abrupt movements. The lighting is bright, suggesting clear daytime conditions, and the overall atmosphere is serene with no near-misses or significant events. A wide-angle shot taken from a moving vehicle, providing a comprehensive view of the highway and its surroundings.
1c3d50949247baa54eae139fdddb9c53/video2world_2B.yaml ADDED
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1
+ adjust_video_noise: 'True'
2
+ conditioner:
3
+ _target_: <class 'cosmos_predict2.conditioner.VideoConditioner'>
4
+ fps:
5
+ _target_: <class 'cosmos_predict2.conditioner.ReMapkey'>
6
+ dropout_rate: '0.0'
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+ dtype: null
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+ input_key: fps
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+ output_key: fps
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+ padding_mask:
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+ _target_: <class 'cosmos_predict2.conditioner.ReMapkey'>
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+ dropout_rate: '0.0'
13
+ dtype: null
14
+ input_key: padding_mask
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+ output_key: padding_mask
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+ text:
17
+ _target_: <class 'cosmos_predict2.conditioner.TextAttr'>
18
+ dropout_rate: '0.2'
19
+ input_key:
20
+ - t5_text_embeddings
21
+ use_video_condition:
22
+ _target_: <class 'cosmos_predict2.conditioner.BooleanFlag'>
23
+ dropout_rate: '0.0'
24
+ input_key: fps
25
+ output_key: use_video_condition
26
+ conditioning_strategy: frame_replace
27
+ ema:
28
+ _target_: cosmos_predict2.configs.base.defaults.ema.EMAConfig
29
+ enabled: 'False'
30
+ iteration_shift: '0'
31
+ rate: '0.1'
32
+ guardrail_config:
33
+ checkpoint_dir: checkpoints
34
+ enabled: 'False'
35
+ offload_model_to_cpu: 'False'
36
+ input_image_key: images
37
+ input_video_key: video
38
+ max_num_conditional_frames: '2'
39
+ min_num_conditional_frames: '1'
40
+ net:
41
+ _target_: <class 'cosmos_predict2.models.video2world_dit.MinimalV1LVGDiT'>
42
+ adaln_lora_dim: '256'
43
+ atten_backend: minimal_a2a
44
+ concat_padding_mask: 'True'
45
+ extra_per_block_abs_pos_emb: 'False'
46
+ in_channels: '16'
47
+ max_frames: '128'
48
+ max_img_h: '240'
49
+ max_img_w: '240'
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+ model_channels: '2048'
51
+ num_blocks: '28'
52
+ num_heads: '16'
53
+ out_channels: '16'
54
+ patch_spatial: '2'
55
+ patch_temporal: '1'
56
+ pos_emb_cls: rope3d
57
+ pos_emb_interpolation: crop
58
+ pos_emb_learnable: 'True'
59
+ rope_enable_fps_modulation: 'False'
60
+ rope_h_extrapolation_ratio: '3.0'
61
+ rope_t_extrapolation_ratio: '1.0'
62
+ rope_w_extrapolation_ratio: '3.0'
63
+ sac_config:
64
+ _target_: cosmos_predict2.models.text2image_dit.SACConfig
65
+ every_n_blocks: '1'
66
+ mode: predict2_2b_720
67
+ use_adaln_lora: 'True'
68
+ precision: bfloat16
69
+ prompt_refiner_config:
70
+ checkpoint_dir: checkpoints/nvidia/Cosmos-Reason1-7B
71
+ enabled: 'True'
72
+ offload_model_to_cpu: 'False'
73
+ rectified_flow_loss_weight_uniform: 'True'
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+ rectified_flow_t_scaling_factor: '1.0'
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+ resize_online: 'True'
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+ resolution: '720'
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+ sigma_conditional: '0.0001'
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+ sigma_data: '1.0'
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+ state_ch: '16'
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+ state_t: '24'
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+ text_encoder:
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+ cls: TextEncoderClass.T5
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+ cosmos_reason1:
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+ ckpt_path: checkpoints/nvidia/Cosmos-Reason1-Private/reason1_internal_real.pt
85
+ compute_online: 'True'
86
+ embed_dim: '100352'
87
+ embedding_concat_strategy: full_concat
88
+ model_config:
89
+ _target_: <class 'imaginaire.models.vlm_qwen_omni.QwenVLBaseModel'>
90
+ model_config:
91
+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenModelConfig
92
+ activation_checkpoint:
93
+ mode: selective
94
+ models: vlm
95
+ selective_ac_option: op
96
+ add_answer_tag: 'True'
97
+ add_cross_attention: 'False'
98
+ add_image_start_end_tag: 'False'
99
+ add_tile_tag: 'False'
100
+ architectures:
101
+ - Qwen2_5_VLForConditionalGeneration
102
+ attention_dropout: '0.0'
103
+ attn_implementation: flash_attention_2
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+ attn_implementation_autoset: 'True'
105
+ aux_loss_coeff: '0.0'
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+ bad_words_ids: null
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+ begin_suppress_tokens: null
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+ bos_token_id: '151643'
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+ cache_dir: null
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+ checkpoint:
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+ async_mode: disabled
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+ create_seed_checkpoint: false
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+ enable_checkpoint: false
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+ export_dtype: float32
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+ folder: checkpoint
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+ interval: 500
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+ interval_type: steps
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+ model_weights_only: false
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+ chunk_size_feed_forward: '0'
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+ ckpt_dir: null
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+ ckpt_path: null
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+ comm:
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+ init_timeout_seconds: 300
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+ trace_buf_size: 20000
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+ train_timeout_seconds: 100
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+ cp_size: null
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+ decoder_start_token_id: null
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+ deterministic: 'False'
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+ diversity_penalty: '0.0'
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+ do_sample: 'False'
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+ early_stopping: 'False'
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+ encoder_no_repeat_ngram_size: '0'
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+ ep_size: null
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+ experimental:
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+ enable_async_tensor_parallel: false
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+ enable_compiled_autograd: false
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+ pipeline_parallel_degree: 1
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+ exponential_decay_length_penalty: null
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+ finetuning_task: null
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+ float8:
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+ enable_float8_linear: false
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+ forced_bos_token_id: null
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+ forced_eos_token_id: null
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+ freeze_llm: 'False'
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+ freeze_mm_projector: 'False'
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+ freeze_vision_encoder: 'False'
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+ fsdp_enabled: 'False'
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+ hidden_act: silu
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+ hidden_size: '3584'
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+ id2label:
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+ 0: LABEL_0
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+ 1: LABEL_1
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+ image_token_id: '151655'
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+ initializer_range: '0.02'
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+ intermediate_size: '18944'
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+ is_decoder: 'False'
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+ is_encoder_decoder: 'False'
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+ label2id:
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+ LABEL_0: '0'
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+ LABEL_1: '1'
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+ length_penalty: '1.0'
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+ loss_per_token: 'True'
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+ max_batch_size: '1'
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+ max_length: '20'
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+ max_position_embeddings: '128000'
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+ max_seq_len: '128000'
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+ max_window_layers: '28'
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+ min_length: '0'
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+ mm_projector: null
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+ model_type: qwen2_5_vl
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+ name_or_path: Qwen/Qwen2.5-VL-7B-Instruct
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+ no_repeat_ngram_size: '0'
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+ num_attention_heads: '28'
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+ num_beam_groups: '1'
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+ num_beams: '1'
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+ num_hidden_layers: '28'
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+ num_key_value_heads: '4'
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+ num_return_sequences: '1'
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+ num_tiles: '1'
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+ optimizer:
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+ early_step_in_backward: false
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+ end_lr: 2.5e-05
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+ fused: false
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+ init_lr: 1.0e-05
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+ lr: 0.0003
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+ lr_multiplier_llm: 1.0
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+ lr_multiplier_mm_projector: 1.0
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+ lr_multiplier_vision_encoder: 0.1
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+ name: AdamW
192
+ output_attentions: 'False'
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+ output_hidden_states: 'True'
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+ output_scores: 'False'
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+ pad_token_id: null
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+ precision: bfloat16
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+ prefix: null
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+ prepend_padding: 'False'
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+ problem_type: null
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+ pruned_heads: _Nothing.NOTHING
201
+ remove_invalid_values: 'False'
202
+ repetition_penalty: '1.0'
203
+ return_dict: 'True'
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+ return_dict_in_generate: 'False'
205
+ rms_norm_eps: 1e-06
206
+ rope_scaling:
207
+ mrope_section:
208
+ - '16'
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+ - '24'
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+ - '24'
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+ rope_type: default
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+ type: default
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+ rope_theta: '1000000.0'
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+ seed: '0'
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+ sep_token_id: null
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+ sliding_window: '32768'
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+ suppress_tokens: null
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+ task_specific_params: null
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+ temperature: '1.0'
220
+ tf_legacy_loss: 'False'
221
+ tie_encoder_decoder: 'False'
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+ tie_word_embeddings: 'False'
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+ tile_tag_type: space_separated
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+ tokenizer_class: null
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+ tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct
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+ top_k: '50'
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+ top_p: '1.0'
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+ torch_dtype: bfloat16
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+ torchscript: 'False'
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+ training:
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+ compile: false
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+ context_parallel_degree: 1
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+ data_parallel_replicate_degree: 1
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+ data_parallel_shard_degree: -1
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+ disable_loss_parallel: false
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+ enable_cpu_offload: false
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+ fsdp_reshard_after_forward: default
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+ mixed_precision_param: bfloat16
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+ mixed_precision_reduce: float32
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+ steps: 400000
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+ tensor_parallel_degree: 1
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+ use_cosine_decay: false
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+ use_linear_decay: true
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+ warmup_steps: 1000
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+ training_seq_len: '4096'
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+ transformers_version: 4.51.0.dev0
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+ typical_p: '1.0'
248
+ use_bfloat16: 'False'
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+ use_cache: 'False'
250
+ use_fsdp2: 'True'
251
+ use_return_dict: 'True'
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+ use_rope_from_torchtitan: 'False'
253
+ use_sliding_window: 'False'
254
+ video_token_id: '151656'
255
+ vision_config:
256
+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenVisionConfig
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+ add_cross_attention: 'False'
258
+ architectures: null
259
+ attn_implementation: flash_attention_2
260
+ attn_implementation_autoset: 'True'
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+ bad_words_ids: null
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+ begin_suppress_tokens: null
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+ tf_legacy_loss: 'False'
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+ ckpt_path: checkpoints/google-t5/t5-11b
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+ embed_dim: '1024'
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+ _target_: <class 'cosmos_predict2.tokenizers.tokenizer.TokenizerInterface'>
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+ chunk_duration: '81'
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+ load_mean_std: 'False'
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+ name: tokenizer
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+ temporal_window: '16'
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+ vae_pth: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
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1dc0dd10757270c34b550f09a383c5f4/run.log ADDED
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0
 
 
 
 
 
1
+ fatal: detected dubious ownership in repository at '/workspace'
2
+ To add an exception for this directory, call:
3
+
4
+ git config --global --add safe.directory /workspace
5
+ [01-15 17:57:20|INFO|imaginaire/constants.py:39:print_environment_info] imaginaire.constants: Namespace(checkpoints='checkpoints', text_encoder=<TextEncoderClass.T5: 't5'>)
6
+ [01-15 17:57:20|INFO|imaginaire/constants.py:40:print_environment_info] sys.argv: ['/workspace/examples/video2world.py', '--model_size', '2B', '--input_path', '/workspace/video2world_out/1dc0dd10757270c34b550f09a383c5f4/input0.jpg', '--num_conditional_frames', '1', '--prompt', '[ERROR] RuntimeError: Empty response from model. Hint: {"done": true, "done_reason": "length", "eval_count": 350}', '--save_path', '/workspace/video2world_out/1dc0dd10757270c34b550f09a383c5f4/video2world_2B.mp4', '--disable_guardrail']
7
+ [01-15 17:57:20|INFO|imaginaire/constants.py:41:print_environment_info] args: Namespace(model_size='2B', resolution='720', fps=16, dit_path='', load_ema=False, prompt='[ERROR] RuntimeError: Empty response from model. Hint: {"done": true, "done_reason": "length", "eval_count": 350}', input_path='/workspace/video2world_out/1dc0dd10757270c34b550f09a383c5f4/input0.jpg', negative_prompt='The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.', aspect_ratio='16:9', num_conditional_frames=1, batch_input_json=None, guidance=7, seed=0, save_path='/workspace/video2world_out/1dc0dd10757270c34b550f09a383c5f4/video2world_2B.mp4', num_gpus=1, disable_guardrail=True, offload_guardrail=False, disable_prompt_refiner=False, offload_prompt_refiner=False, offload_text_encoder=False, downcast_text_encoder=False, benchmark=False, use_cuda_graphs=False, natten=False)
8
+ [01-15 17:57:20|INFO|examples/video2world.py:210:setup_pipeline] Using dit_path: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
9
+ [01-15 17:57:20|INFO|imaginaire/utils/misc.py:139:set_random_seed] Using random seed 0.
10
+ [01-15 17:57:20|WARNING|examples/video2world.py:241:setup_pipeline] Guardrail checks are disabled
11
+ [01-15 17:57:20|WARNING|imaginaire/lazy_config/lazy.py:441:save_yaml] Config is saved using omegaconf at /workspace/video2world_out/1dc0dd10757270c34b550f09a383c5f4/video2world_2B.yaml.
12
+ [01-15 17:57:20|INFO|examples/video2world.py:259:setup_pipeline] Initializing Video2WorldPipeline with model size: 2B
13
+ [01-15 17:57:20|WARNING|cosmos_predict2/pipelines/video2world.py:292:from_config] precision torch.bfloat16
14
+ [01-15 17:57:21|INFO|cosmos_predict2/tokenizers/tokenizer.py:599:_video_vae] Loading checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
15
+ [01-15 17:57:21|SUCCESS|cosmos_predict2/tokenizers/tokenizer.py:601:_video_vae] Successfully loaded checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
16
+ [01-15 17:59:39|INFO|imaginaire/auxiliary/text_encoder.py:345:__init__] T5 Text encoder model instantiated
17
+
18
+ [01-15 17:59:44|INFO|cosmos_predict2/pipelines/video2world.py:354:from_config] Loading DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
19
+ [01-15 17:59:50|SUCCESS|cosmos_predict2/pipelines/video2world.py:373:from_config] Successfully loaded DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
20
+ [01-15 17:59:50|INFO|examples/video2world.py:297:process_single_generation] Running Video2WorldPipeline
21
+ input: /workspace/video2world_out/1dc0dd10757270c34b550f09a383c5f4/input0.jpg
22
+ prompt: [ERROR] RuntimeError: Empty response from model. Hint: {"done": true, "done_reason": "length", "eval_count": 350}
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+ [01-15 17:59:50|WARNING|cosmos_predict2/pipelines/video2world.py:821:__call__] Guardrail checks on prompt are disabled
24
+ [01-15 17:59:50|INFO|cosmos_predict2/pipelines/video2world.py:830:__call__] Starting prompt refinement...
25
+ [01-15 17:59:55|INFO|cosmos_predict2/pipelines/video2world.py:832:__call__] Finished prompt refinement
26
+ [01-15 17:59:55|WARNING|cosmos_predict2/pipelines/video2world.py:845:__call__] Guardrail checks on refined prompt are disabled
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+ [01-15 18:00:10|INFO|cosmos_predict2/pipelines/video2world.py:898:__call__] Starting video generation...
28
+
29
 
30
+ [01-15 18:10:11|INFO|examples/video2world.py:330:process_single_generation] Saving the generated video to: /workspace/video2world_out/1dc0dd10757270c34b550f09a383c5f4/video2world_2B.mp4
31
+ [01-15 18:10:15|SUCCESS|examples/video2world.py:336:process_single_generation] Successfully saved video to: /workspace/video2world_out/1dc0dd10757270c34b550f09a383c5f4/video2world_2B.mp4
32
+ [01-15 18:10:15|SUCCESS|examples/video2world.py:347:process_single_generation] Successfully saved prompt file to: /workspace/video2world_out/1dc0dd10757270c34b550f09a383c5f4/video2world_2B.txt
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1dc0dd10757270c34b550f09a383c5f4/video2world_2B.txt ADDED
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+ [Prompt]
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+ [ERROR] RuntimeError: Empty response from model. Hint: {"done": true, "done_reason": "length", "eval_count": 350}
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+ [Negative Prompt]
4
+ The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.
5
+ [Refined Prompt]
6
+ A serene highway scene with a single car driving away into the distance, framed by tall, dense trees on both sides. The road stretches forward, marked by clear lane lines, and the overcast sky casts a soft, diffused light across the landscape. The surrounding forest appears lush and green, with mist gently hovering near the ground, adding a sense of tranquility and depth to the scene. A wide-angle shot captures the expansive view of the road and its natural surroundings.
1dc0dd10757270c34b550f09a383c5f4/video2world_2B.yaml ADDED
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+ adjust_video_noise: 'True'
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+ conditioner:
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+ _target_: <class 'cosmos_predict2.conditioner.VideoConditioner'>
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+ fps:
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+ _target_: <class 'cosmos_predict2.conditioner.ReMapkey'>
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+ dropout_rate: '0.0'
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+ dtype: null
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+ input_key: fps
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+ output_key: fps
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+ dtype: null
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+ input_key: padding_mask
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+ output_key: padding_mask
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+ text:
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+ _target_: <class 'cosmos_predict2.conditioner.TextAttr'>
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+ dropout_rate: '0.2'
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+ input_key:
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+ - t5_text_embeddings
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+ use_video_condition:
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+ _target_: <class 'cosmos_predict2.conditioner.BooleanFlag'>
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+ dropout_rate: '0.0'
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+ input_key: fps
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+ output_key: use_video_condition
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+ conditioning_strategy: frame_replace
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+ ema:
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+ _target_: cosmos_predict2.configs.base.defaults.ema.EMAConfig
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+ enabled: 'False'
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+ iteration_shift: '0'
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+ rate: '0.1'
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+ guardrail_config:
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+ checkpoint_dir: checkpoints
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+ enabled: 'False'
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+ offload_model_to_cpu: 'False'
36
+ input_image_key: images
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+ input_video_key: video
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+ max_num_conditional_frames: '2'
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+ min_num_conditional_frames: '1'
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+ net:
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+ _target_: <class 'cosmos_predict2.models.video2world_dit.MinimalV1LVGDiT'>
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+ adaln_lora_dim: '256'
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+ atten_backend: minimal_a2a
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+ concat_padding_mask: 'True'
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+ extra_per_block_abs_pos_emb: 'False'
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+ in_channels: '16'
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+ max_frames: '128'
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+ max_img_h: '240'
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+ max_img_w: '240'
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+ model_channels: '2048'
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+ num_blocks: '28'
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+ num_heads: '16'
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+ out_channels: '16'
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+ patch_spatial: '2'
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+ patch_temporal: '1'
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+ pos_emb_cls: rope3d
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+ pos_emb_interpolation: crop
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+ pos_emb_learnable: 'True'
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+ rope_enable_fps_modulation: 'False'
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+ rope_h_extrapolation_ratio: '3.0'
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+ rope_t_extrapolation_ratio: '1.0'
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+ rope_w_extrapolation_ratio: '3.0'
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+ sac_config:
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+ _target_: cosmos_predict2.models.text2image_dit.SACConfig
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+ every_n_blocks: '1'
66
+ mode: predict2_2b_720
67
+ use_adaln_lora: 'True'
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+ precision: bfloat16
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+ prompt_refiner_config:
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+ checkpoint_dir: checkpoints/nvidia/Cosmos-Reason1-7B
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+ enabled: 'True'
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+ offload_model_to_cpu: 'False'
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+ rectified_flow_loss_weight_uniform: 'True'
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+ rectified_flow_t_scaling_factor: '1.0'
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+ resize_online: 'True'
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+ resolution: '720'
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+ sigma_conditional: '0.0001'
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+ sigma_data: '1.0'
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+ state_ch: '16'
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+ state_t: '24'
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+ text_encoder:
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+ cls: TextEncoderClass.T5
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+ cosmos_reason1:
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+ ckpt_path: checkpoints/nvidia/Cosmos-Reason1-Private/reason1_internal_real.pt
85
+ compute_online: 'True'
86
+ embed_dim: '100352'
87
+ embedding_concat_strategy: full_concat
88
+ model_config:
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+ _target_: <class 'imaginaire.models.vlm_qwen_omni.QwenVLBaseModel'>
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+ model_config:
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+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenModelConfig
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+ activation_checkpoint:
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+ mode: selective
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+ models: vlm
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+ selective_ac_option: op
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+ add_answer_tag: 'True'
97
+ add_cross_attention: 'False'
98
+ add_image_start_end_tag: 'False'
99
+ add_tile_tag: 'False'
100
+ architectures:
101
+ - Qwen2_5_VLForConditionalGeneration
102
+ attention_dropout: '0.0'
103
+ attn_implementation: flash_attention_2
104
+ attn_implementation_autoset: 'True'
105
+ aux_loss_coeff: '0.0'
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+ bad_words_ids: null
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+ begin_suppress_tokens: null
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+ bos_token_id: '151643'
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+ cache_dir: null
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+ checkpoint:
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+ async_mode: disabled
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+ create_seed_checkpoint: false
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+ enable_checkpoint: false
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+ export_dtype: float32
115
+ folder: checkpoint
116
+ interval: 500
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+ interval_type: steps
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+ model_weights_only: false
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+ chunk_size_feed_forward: '0'
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+ ckpt_dir: null
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+ ckpt_path: null
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+ comm:
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+ init_timeout_seconds: 300
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+ trace_buf_size: 20000
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+ train_timeout_seconds: 100
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+ cp_size: null
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+ deterministic: 'False'
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+ do_sample: 'False'
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+ early_stopping: 'False'
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+ ep_size: null
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+ enable_compiled_autograd: false
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+ pipeline_parallel_degree: 1
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+ exponential_decay_length_penalty: null
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+ finetuning_task: null
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+ float8:
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+ enable_float8_linear: false
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+ forced_bos_token_id: null
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+ forced_eos_token_id: null
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+ freeze_llm: 'False'
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+ freeze_mm_projector: 'False'
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+ freeze_vision_encoder: 'False'
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+ fsdp_enabled: 'False'
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+ hidden_act: silu
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+ hidden_size: '3584'
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+ id2label:
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+ 0: LABEL_0
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+ 1: LABEL_1
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+ image_token_id: '151655'
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+ initializer_range: '0.02'
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+ intermediate_size: '18944'
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+ is_decoder: 'False'
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+ is_encoder_decoder: 'False'
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+ label2id:
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+ LABEL_0: '0'
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+ LABEL_1: '1'
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+ length_penalty: '1.0'
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+ loss_per_token: 'True'
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+ max_batch_size: '1'
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+ max_length: '20'
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+ max_position_embeddings: '128000'
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+ max_seq_len: '128000'
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+ max_window_layers: '28'
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+ min_length: '0'
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+ mm_projector: null
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+ model_type: qwen2_5_vl
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+ name_or_path: Qwen/Qwen2.5-VL-7B-Instruct
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+ no_repeat_ngram_size: '0'
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+ num_attention_heads: '28'
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+ num_beam_groups: '1'
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+ num_beams: '1'
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+ num_hidden_layers: '28'
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+ num_key_value_heads: '4'
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+ num_return_sequences: '1'
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+ num_tiles: '1'
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+ optimizer:
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+ early_step_in_backward: false
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+ end_lr: 2.5e-05
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+ fused: false
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+ init_lr: 1.0e-05
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+ lr: 0.0003
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+ lr_multiplier_llm: 1.0
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+ lr_multiplier_mm_projector: 1.0
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+ lr_multiplier_vision_encoder: 0.1
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+ name: AdamW
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+ output_attentions: 'False'
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+ output_hidden_states: 'True'
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+ output_scores: 'False'
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+ pad_token_id: null
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+ precision: bfloat16
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+ prefix: null
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+ prepend_padding: 'False'
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+ problem_type: null
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+ pruned_heads: _Nothing.NOTHING
201
+ remove_invalid_values: 'False'
202
+ repetition_penalty: '1.0'
203
+ return_dict: 'True'
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+ return_dict_in_generate: 'False'
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+ rms_norm_eps: 1e-06
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+ rope_scaling:
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+ mrope_section:
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+ - '16'
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+ - '24'
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+ - '24'
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+ rope_type: default
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+ type: default
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+ rope_theta: '1000000.0'
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+ seed: '0'
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+ sep_token_id: null
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+ sliding_window: '32768'
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+ suppress_tokens: null
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+ task_specific_params: null
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+ temperature: '1.0'
220
+ tf_legacy_loss: 'False'
221
+ tie_encoder_decoder: 'False'
222
+ tie_word_embeddings: 'False'
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+ tile_tag_type: space_separated
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+ tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct
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+ top_k: '50'
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+ torch_dtype: bfloat16
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+ torchscript: 'False'
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+ training:
231
+ compile: false
232
+ context_parallel_degree: 1
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+ data_parallel_replicate_degree: 1
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+ data_parallel_shard_degree: -1
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+ disable_loss_parallel: false
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+ enable_cpu_offload: false
237
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+ mixed_precision_param: bfloat16
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+ mixed_precision_reduce: float32
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+ steps: 400000
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256
+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenVisionConfig
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+ attn_implementation: flash_attention_2
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+ _target_: <function build_tokenizer at 0x7553d0672480>
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+ cache_dir: checkpoints/nvidia/Cosmos-Reason1-Private/tokenizer
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+ tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct
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+ n_layers_per_group: '5'
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+ num_tokens: '512'
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+ t5:
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+ ckpt_path: checkpoints/google-t5/t5-11b
376
+ embed_dim: '1024'
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+ num_tokens: '512'
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+ timestamps:
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+ is_forward: 'False'
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+ order: '7.0'
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+ t_max: '80.0'
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+ t_min: '0.002'
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+ tokenizer:
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+ _target_: <class 'cosmos_predict2.tokenizers.tokenizer.TokenizerInterface'>
386
+ chunk_duration: '81'
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+ load_mean_std: 'False'
388
+ name: tokenizer
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+ temporal_window: '16'
390
+ vae_pth: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
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2357fa0df9e84b61a1fbe8e6c80efee9/run.log ADDED
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0
 
 
 
 
 
1
+ fatal: detected dubious ownership in repository at '/workspace'
2
+ To add an exception for this directory, call:
3
+
4
+ git config --global --add safe.directory /workspace
5
+ [01-15 17:57:21|INFO|imaginaire/constants.py:39:print_environment_info] imaginaire.constants: Namespace(checkpoints='checkpoints', text_encoder=<TextEncoderClass.T5: 't5'>)
6
+ [01-15 17:57:21|INFO|imaginaire/constants.py:40:print_environment_info] sys.argv: ['/workspace/examples/video2world.py', '--model_size', '2B', '--input_path', '/workspace/video2world_out/2357fa0df9e84b61a1fbe8e6c80efee9/input0.jpg', '--num_conditional_frames', '1', '--prompt', '[ERROR] RuntimeError: Empty response from model. Hint: {"done": true, "done_reason": "length", "eval_count": 350}', '--save_path', '/workspace/video2world_out/2357fa0df9e84b61a1fbe8e6c80efee9/video2world_2B.mp4', '--disable_guardrail']
7
+ [01-15 17:57:21|INFO|imaginaire/constants.py:41:print_environment_info] args: Namespace(model_size='2B', resolution='720', fps=16, dit_path='', load_ema=False, prompt='[ERROR] RuntimeError: Empty response from model. Hint: {"done": true, "done_reason": "length", "eval_count": 350}', input_path='/workspace/video2world_out/2357fa0df9e84b61a1fbe8e6c80efee9/input0.jpg', negative_prompt='The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.', aspect_ratio='16:9', num_conditional_frames=1, batch_input_json=None, guidance=7, seed=0, save_path='/workspace/video2world_out/2357fa0df9e84b61a1fbe8e6c80efee9/video2world_2B.mp4', num_gpus=1, disable_guardrail=True, offload_guardrail=False, disable_prompt_refiner=False, offload_prompt_refiner=False, offload_text_encoder=False, downcast_text_encoder=False, benchmark=False, use_cuda_graphs=False, natten=False)
8
+ [01-15 17:57:21|INFO|examples/video2world.py:210:setup_pipeline] Using dit_path: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
9
+ [01-15 17:57:21|INFO|imaginaire/utils/misc.py:139:set_random_seed] Using random seed 0.
10
+ [01-15 17:57:21|WARNING|examples/video2world.py:241:setup_pipeline] Guardrail checks are disabled
11
+ [01-15 17:57:21|WARNING|imaginaire/lazy_config/lazy.py:441:save_yaml] Config is saved using omegaconf at /workspace/video2world_out/2357fa0df9e84b61a1fbe8e6c80efee9/video2world_2B.yaml.
12
+ [01-15 17:57:21|INFO|examples/video2world.py:259:setup_pipeline] Initializing Video2WorldPipeline with model size: 2B
13
+ [01-15 17:57:21|WARNING|cosmos_predict2/pipelines/video2world.py:292:from_config] precision torch.bfloat16
14
+ [01-15 17:57:22|INFO|cosmos_predict2/tokenizers/tokenizer.py:599:_video_vae] Loading checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
15
+ [01-15 17:57:22|SUCCESS|cosmos_predict2/tokenizers/tokenizer.py:601:_video_vae] Successfully loaded checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth
16
+ [01-15 17:59:40|INFO|imaginaire/auxiliary/text_encoder.py:345:__init__] T5 Text encoder model instantiated
17
+
18
+ [01-15 17:59:45|INFO|cosmos_predict2/pipelines/video2world.py:354:from_config] Loading DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
19
+ [01-15 17:59:51|SUCCESS|cosmos_predict2/pipelines/video2world.py:373:from_config] Successfully loaded DiT from checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/model-720p-16fps.pt
20
+ [01-15 17:59:51|INFO|examples/video2world.py:297:process_single_generation] Running Video2WorldPipeline
21
+ input: /workspace/video2world_out/2357fa0df9e84b61a1fbe8e6c80efee9/input0.jpg
22
+ prompt: [ERROR] RuntimeError: Empty response from model. Hint: {"done": true, "done_reason": "length", "eval_count": 350}
23
+ [01-15 17:59:51|WARNING|cosmos_predict2/pipelines/video2world.py:821:__call__] Guardrail checks on prompt are disabled
24
+ [01-15 17:59:51|INFO|cosmos_predict2/pipelines/video2world.py:830:__call__] Starting prompt refinement...
25
+ [01-15 17:59:56|INFO|cosmos_predict2/pipelines/video2world.py:832:__call__] Finished prompt refinement
26
+ [01-15 17:59:56|WARNING|cosmos_predict2/pipelines/video2world.py:845:__call__] Guardrail checks on refined prompt are disabled
27
+ [01-15 18:00:10|INFO|cosmos_predict2/pipelines/video2world.py:898:__call__] Starting video generation...
28
+
29
 
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+ [01-15 18:09:59|INFO|examples/video2world.py:330:process_single_generation] Saving the generated video to: /workspace/video2world_out/2357fa0df9e84b61a1fbe8e6c80efee9/video2world_2B.mp4
31
+ [01-15 18:10:03|SUCCESS|examples/video2world.py:336:process_single_generation] Successfully saved video to: /workspace/video2world_out/2357fa0df9e84b61a1fbe8e6c80efee9/video2world_2B.mp4
32
+ [01-15 18:10:03|SUCCESS|examples/video2world.py:347:process_single_generation] Successfully saved prompt file to: /workspace/video2world_out/2357fa0df9e84b61a1fbe8e6c80efee9/video2world_2B.txt
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2357fa0df9e84b61a1fbe8e6c80efee9/video2world_2B.txt ADDED
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+ [Prompt]
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+ [ERROR] RuntimeError: Empty response from model. Hint: {"done": true, "done_reason": "length", "eval_count": 350}
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+ [Negative Prompt]
4
+ The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.
5
+ [Refined Prompt]
6
+ A nighttime urban street scene captured from inside a vehicle, showcasing a wet road reflecting the red taillights of several cars ahead. The traffic lights are red, indicating a stop, and the street is lined with construction cones and barriers, suggesting ongoing work. The surroundings include illuminated streetlights casting a warm glow over the scene, with buildings and signs faintly visible in the background. The atmosphere is quiet and somewhat eerie due to the darkness and the reflective wet pavement. A low-angle shot taken from within the vehicle, emphasizing the view towards the stopped traffic.
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+ adjust_video_noise: 'True'
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+ conditioner:
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+ _target_: <class 'cosmos_predict2.conditioner.VideoConditioner'>
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+ fps:
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+ _target_: <class 'cosmos_predict2.conditioner.ReMapkey'>
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+ dropout_rate: '0.0'
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+ dtype: null
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+ input_key: fps
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+ output_key: fps
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+ dropout_rate: '0.0'
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+ dtype: null
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+ input_key: padding_mask
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+ output_key: padding_mask
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+ text:
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+ _target_: <class 'cosmos_predict2.conditioner.TextAttr'>
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+ dropout_rate: '0.2'
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+ input_key:
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+ - t5_text_embeddings
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+ use_video_condition:
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+ _target_: <class 'cosmos_predict2.conditioner.BooleanFlag'>
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+ dropout_rate: '0.0'
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+ input_key: fps
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+ output_key: use_video_condition
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+ conditioning_strategy: frame_replace
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+ ema:
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+ _target_: cosmos_predict2.configs.base.defaults.ema.EMAConfig
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+ enabled: 'False'
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+ iteration_shift: '0'
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+ rate: '0.1'
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+ guardrail_config:
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+ checkpoint_dir: checkpoints
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+ enabled: 'False'
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+ offload_model_to_cpu: 'False'
36
+ input_image_key: images
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+ input_video_key: video
38
+ max_num_conditional_frames: '2'
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+ min_num_conditional_frames: '1'
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+ net:
41
+ _target_: <class 'cosmos_predict2.models.video2world_dit.MinimalV1LVGDiT'>
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+ adaln_lora_dim: '256'
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+ atten_backend: minimal_a2a
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+ concat_padding_mask: 'True'
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+ extra_per_block_abs_pos_emb: 'False'
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+ in_channels: '16'
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+ max_frames: '128'
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+ max_img_h: '240'
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+ max_img_w: '240'
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+ model_channels: '2048'
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+ num_blocks: '28'
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+ num_heads: '16'
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+ out_channels: '16'
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+ patch_spatial: '2'
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+ patch_temporal: '1'
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+ pos_emb_cls: rope3d
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+ pos_emb_interpolation: crop
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+ pos_emb_learnable: 'True'
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+ rope_enable_fps_modulation: 'False'
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+ rope_h_extrapolation_ratio: '3.0'
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+ rope_t_extrapolation_ratio: '1.0'
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+ rope_w_extrapolation_ratio: '3.0'
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+ sac_config:
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+ _target_: cosmos_predict2.models.text2image_dit.SACConfig
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+ every_n_blocks: '1'
66
+ mode: predict2_2b_720
67
+ use_adaln_lora: 'True'
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+ precision: bfloat16
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+ prompt_refiner_config:
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+ checkpoint_dir: checkpoints/nvidia/Cosmos-Reason1-7B
71
+ enabled: 'True'
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+ offload_model_to_cpu: 'False'
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+ rectified_flow_loss_weight_uniform: 'True'
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+ rectified_flow_t_scaling_factor: '1.0'
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+ resize_online: 'True'
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+ resolution: '720'
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+ sigma_conditional: '0.0001'
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+ sigma_data: '1.0'
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+ state_ch: '16'
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+ state_t: '24'
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+ text_encoder:
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+ cls: TextEncoderClass.T5
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+ cosmos_reason1:
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+ ckpt_path: checkpoints/nvidia/Cosmos-Reason1-Private/reason1_internal_real.pt
85
+ compute_online: 'True'
86
+ embed_dim: '100352'
87
+ embedding_concat_strategy: full_concat
88
+ model_config:
89
+ _target_: <class 'imaginaire.models.vlm_qwen_omni.QwenVLBaseModel'>
90
+ model_config:
91
+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenModelConfig
92
+ activation_checkpoint:
93
+ mode: selective
94
+ models: vlm
95
+ selective_ac_option: op
96
+ add_answer_tag: 'True'
97
+ add_cross_attention: 'False'
98
+ add_image_start_end_tag: 'False'
99
+ add_tile_tag: 'False'
100
+ architectures:
101
+ - Qwen2_5_VLForConditionalGeneration
102
+ attention_dropout: '0.0'
103
+ attn_implementation: flash_attention_2
104
+ attn_implementation_autoset: 'True'
105
+ aux_loss_coeff: '0.0'
106
+ bad_words_ids: null
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+ begin_suppress_tokens: null
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+ bos_token_id: '151643'
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+ cache_dir: null
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+ checkpoint:
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+ async_mode: disabled
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+ create_seed_checkpoint: false
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+ enable_checkpoint: false
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+ export_dtype: float32
115
+ folder: checkpoint
116
+ interval: 500
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+ interval_type: steps
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+ model_weights_only: false
119
+ chunk_size_feed_forward: '0'
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+ ckpt_dir: null
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+ ckpt_path: null
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+ comm:
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+ init_timeout_seconds: 300
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+ trace_buf_size: 20000
125
+ train_timeout_seconds: 100
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+ cp_size: null
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+ cross_attention_hidden_size: null
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+ decoder_start_token_id: null
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+ deterministic: 'False'
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+ diversity_penalty: '0.0'
131
+ do_sample: 'False'
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+ early_stopping: 'False'
133
+ encoder_no_repeat_ngram_size: '0'
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+ eos_token_id: '151645'
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+ ep_size: null
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+ experimental:
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+ enable_async_tensor_parallel: false
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+ enable_compiled_autograd: false
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+ pipeline_parallel_degree: 1
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+ finetuning_task: null
142
+ float8:
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+ enable_float8_linear: false
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+ freeze_llm: 'False'
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+ freeze_mm_projector: 'False'
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+ freeze_vision_encoder: 'False'
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+ fsdp_enabled: 'False'
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+ hidden_act: silu
151
+ hidden_size: '3584'
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+ id2label:
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+ 0: LABEL_0
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+ 1: LABEL_1
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+ image_token_id: '151655'
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+ initializer_range: '0.02'
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+ intermediate_size: '18944'
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+ is_decoder: 'False'
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+ is_encoder_decoder: 'False'
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+ label2id:
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+ LABEL_0: '0'
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+ LABEL_1: '1'
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+ length_penalty: '1.0'
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+ loss_per_token: 'True'
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+ max_batch_size: '1'
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+ max_length: '20'
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+ max_position_embeddings: '128000'
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+ max_seq_len: '128000'
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+ max_window_layers: '28'
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+ min_length: '0'
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+ mm_projector: null
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+ model_type: qwen2_5_vl
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+ name_or_path: Qwen/Qwen2.5-VL-7B-Instruct
174
+ no_repeat_ngram_size: '0'
175
+ num_attention_heads: '28'
176
+ num_beam_groups: '1'
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+ early_step_in_backward: false
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+ end_lr: 2.5e-05
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+ fused: false
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+ init_lr: 1.0e-05
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+ lr: 0.0003
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+ lr_multiplier_llm: 1.0
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+ lr_multiplier_mm_projector: 1.0
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+ lr_multiplier_vision_encoder: 0.1
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+ name: AdamW
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+ output_attentions: 'False'
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+ output_hidden_states: 'True'
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+ output_scores: 'False'
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+ pad_token_id: null
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+ precision: bfloat16
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+ prefix: null
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+ prepend_padding: 'False'
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+ problem_type: null
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+ pruned_heads: _Nothing.NOTHING
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+ remove_invalid_values: 'False'
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+ repetition_penalty: '1.0'
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+ return_dict: 'True'
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+ return_dict_in_generate: 'False'
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+ rms_norm_eps: 1e-06
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+ rope_scaling:
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+ mrope_section:
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+ - '16'
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+ - '24'
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+ - '24'
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+ rope_type: default
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+ type: default
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+ rope_theta: '1000000.0'
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+ seed: '0'
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+ sep_token_id: null
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+ sliding_window: '32768'
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+ suppress_tokens: null
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+ task_specific_params: null
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+ temperature: '1.0'
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+ tf_legacy_loss: 'False'
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+ tie_encoder_decoder: 'False'
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+ tie_word_embeddings: 'False'
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+ tile_tag_type: space_separated
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+ tokenizer_class: null
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+ tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct
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+ top_k: '50'
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+ top_p: '1.0'
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+ torch_dtype: bfloat16
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+ torchscript: 'False'
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+ training:
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+ compile: false
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+ context_parallel_degree: 1
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+ data_parallel_replicate_degree: 1
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+ data_parallel_shard_degree: -1
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+ disable_loss_parallel: false
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+ enable_cpu_offload: false
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+ fsdp_reshard_after_forward: default
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+ mixed_precision_param: bfloat16
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+ mixed_precision_reduce: float32
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+ steps: 400000
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+ tensor_parallel_degree: 1
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+ use_cosine_decay: false
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+ use_linear_decay: true
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+ typical_p: '1.0'
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+ use_bfloat16: 'False'
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+ use_cache: 'False'
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+ use_fsdp2: 'True'
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+ use_return_dict: 'True'
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+ use_rope_from_torchtitan: 'False'
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+ use_sliding_window: 'False'
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+ video_token_id: '151656'
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+ vision_config:
256
+ _target_: imaginaire.configs.reason1.model_config_qwen.QwenVisionConfig
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+ add_cross_attention: 'False'
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+ architectures: null
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+ attn_implementation: flash_attention_2
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+ attn_implementation_autoset: 'True'
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+ bad_words_ids: null
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+ begin_suppress_tokens: null
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+ bos_token_id: null
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+ depth: '32'
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+ diversity_penalty: '0.0'
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+ do_sample: 'False'
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+ early_stopping: 'False'
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+ embed_dim: null
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+ encoder_no_repeat_ngram_size: '0'
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+ eos_token_id: null
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+ exponential_decay_length_penalty: null
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+ finetuning_task: null
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+ forced_bos_token_id: null
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+ forced_eos_token_id: null
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+ fullatt_block_indexes:
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+ - '7'
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+ - '15'
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+ - '23'
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+ - '31'
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+ hidden_act: silu
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+ hidden_size: '1280'
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+ 0: LABEL_0
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+ 1: LABEL_1
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+ in_channels: '3'
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+ in_chans: '3'
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+ intermediate_size: '3420'
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+ is_decoder: 'False'
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+ is_encoder_decoder: 'False'
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+ label2id:
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+ LABEL_0: '0'
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+ LABEL_1: '1'
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+ length_penalty: '1.0'
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+ max_length: '20'
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+ min_length: '0'
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+ mlp_ratio: null
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+ model_type: qwen2_5_vl
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+ name_or_path: ''
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+ no_repeat_ngram_size: '0'
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+ num_beam_groups: '1'
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+ out_hidden_size: '3584'
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+ output_attentions: 'False'
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+ output_hidden_states: 'False'
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+ output_scores: 'False'
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+ pad_token_id: null
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+ patch_size: '14'
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+ prefix: null
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+ problem_type: null
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+ pruned_heads: _Nothing.NOTHING
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+ remove_invalid_values: 'False'
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+ repetition_penalty: '1.0'
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+ return_dict: 'True'
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+ return_dict_in_generate: 'False'
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+ sep_token_id: null
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+ spatial_merge_size: '2'
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+ spatial_patch_size: '14'
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+ suppress_tokens: null
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+ task_specific_params: null
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+ temperature: '1.0'
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+ temporal_patch_size: '2'
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+ tf_legacy_loss: 'False'
328
+ tie_encoder_decoder: 'False'
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+ tie_word_embeddings: 'True'
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+ tokenizer_class: null
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+ tokens_per_second: '2'
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+ top_k: '50'
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+ top_p: '1.0'
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+ torch_dtype: bfloat16
335
+ torchscript: 'False'
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+ typical_p: '1.0'
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+ use_bfloat16: 'False'
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+ window_size: '112'
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+ vision_encoder: openai/clip-vit-base-patch32
340
+ vision_encoder_config:
341
+ depth_init: true
342
+ dim: 1024
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+ ffn_dim_multiplier: null
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+ head_dim: null
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+ hidden_act: null
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+ hidden_dim: 4096
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+ image_size: 1024
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+ image_token_id: null
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+ multiple_of: null
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+ n_heads: 16
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+ n_kv_heads: null
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+ n_layers: 24
353
+ norm_eps: 1.0e-05
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+ norm_type: rmsnorm
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+ num_channels: 3
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+ patch_size: 16
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+ proj_bias: null
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+ qkv_bias: null
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+ rope_theta: 10000.0
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+ use_cache: false
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+ use_rope_from_torchtitan: false
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+ vision_encoder_in_channels: '3'
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+ vision_end_token_id: '151653'
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+ vision_start_token_id: '151652'
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+ vision_token_id: '151654'
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+ vocab_size: '152064'
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+ z_loss_coeff: '0.0'
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+ tokenizer:
369
+ _target_: <function build_tokenizer at 0x79e865a8e480>
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+ cache_dir: checkpoints/nvidia/Cosmos-Reason1-Private/tokenizer
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+ tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct
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+ n_layers_per_group: '5'
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+ num_tokens: '512'
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+ t5:
375
+ ckpt_path: checkpoints/google-t5/t5-11b
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+ embed_dim: '1024'
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+ num_tokens: '512'
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+ timestamps:
379
+ is_forward: 'False'
380
+ nfe: '35'
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+ order: '7.0'
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+ t_max: '80.0'
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+ t_min: '0.002'
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+ tokenizer:
385
+ _target_: <class 'cosmos_predict2.tokenizers.tokenizer.TokenizerInterface'>
386
+ chunk_duration: '81'
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+ load_mean_std: 'False'
388
+ name: tokenizer
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+ temporal_window: '16'
390
+ vae_pth: checkpoints/nvidia/Cosmos-Predict2-2B-Video2World/tokenizer/tokenizer.pth