diff --git a/.gitattributes b/.gitattributes index e5b5961d385b4642f81fdd06cfdadc25d2293d30..e3cf4186fbf2ac06524ae6255b9a7c58bf6e1892 100644 --- a/.gitattributes +++ b/.gitattributes @@ -46,3 +46,4 @@ static/videos/shiba.mp4 filter=lfs diff=lfs merge=lfs -text static/videos/steve.mp4 filter=lfs diff=lfs merge=lfs -text static/videos/teaser.mp4 filter=lfs diff=lfs merge=lfs -text static/videos/toby.mp4 filter=lfs diff=lfs merge=lfs -text +*.png filter=lfs diff=lfs merge=lfs -text diff --git a/index.html b/index.html index 88951116f7ed81764f0d75616b9f4c60892b9a30..01035410521228ab41880b0668c4d2ede797c4a8 100644 --- a/index.html +++ b/index.html @@ -2,29 +2,170 @@ - - + + - Nerfies: Deformable Neural Radiance Fields - - + RTC Experiments: Flow Matching Steps & Sigma Analysis + - - - + - - - + + @@ -33,86 +174,10 @@
-

Nerfies: Deformable Neural Radiance Fields

-
- - Keunhong Park1, - - Utkarsh Sinha2, - - Jonathan T. Barron2, - - - Sofien Bouaziz2, - - - Dan B Goldman2, - - - Steven M. Seitz1,2, - - - Ricardo Martin-Brualla2 - -
- +

Real-Time Chunking Experiments

+

Flow Matching Steps & Sigma_d Parameter Analysis

- 1University of Washington, - 2Google Research -
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- - - - - - - Paper - - - - - - - - arXiv - - - - - - - - - Video - - - - - - - - - Code - - - - - - - - - Data - -
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- Nerfies turns selfie videos from your phone into - free-viewpoint - portraits. -

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Experiment Overview

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+ This page presents comprehensive results from Real-Time Chunking (RTC) experiments across different models, + flow matching steps, and sigma_d values. The experiments demonstrate how these parameters affect the + denoising process and final action predictions. +

+

+ Models tested: PI0.5, SmolVLA
+ Flow matching steps: 2, 5, 10, 20, 50, 100 (varies by model)
+ Sigma_d values: 0.1, 0.2, 0.5, 0.8, 1.0, 1.2, 1.5 +

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PI0.5 Model
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SmolVLA Model
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PI0.5 Model Results

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Abstract

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- We present the first method capable of photorealistically reconstructing a non-rigidly - deforming scene using photos/videos captured casually from mobile phones. -

-

- Our approach augments neural radiance fields - (NeRF) by optimizing an - additional continuous volumetric deformation field that warps each observed point into a - canonical 5D NeRF. - We observe that these NeRF-like deformation fields are prone to local minima, and - propose a coarse-to-fine optimization method for coordinate-based models that allows for - more robust optimization. - By adapting principles from geometry processing and physical simulation to NeRF-like - models, we propose an elastic regularization of the deformation field that further - improves robustness. -

-

- We show that Nerfies can turn casually captured selfie - photos/videos into deformable NeRF - models that allow for photorealistic renderings of the subject from arbitrary - viewpoints, which we dub "nerfies". We evaluate our method by collecting data - using a - rig with two mobile phones that take time-synchronized photos, yielding train/validation - images of the same pose at different viewpoints. We show that our method faithfully - reconstructs non-rigidly deforming scenes and reproduces unseen views with high - fidelity. -

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Flow Matching Steps: 2

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Video

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Flow Matching Steps: 5

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Flow Matching Steps: 10

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Flow Matching Steps: 20

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Flow Matching Steps: 50

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BibTeX

- 
@article{park2021nerfies,
-  author    = {Park, Keunhong and Sinha, Utkarsh and Barron, Jonathan T. and Bouaziz, Sofien and Goldman, Dan B and Seitz, Steven M. and Martin-Brualla, Ricardo},
-  title     = {Nerfies: Deformable Neural Radiance Fields},
-  journal   = {ICCV},
-  year      = {2021},
-}
+ +
+

Flow Matching Steps: 100

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+
+ +
+ × + +
+ + diff --git a/static/experiments/experiment_log.txt b/static/experiments/experiment_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..6028766bcbfafed7dd1ae0192fa42a20f2015c26 --- /dev/null +++ b/static/experiments/experiment_log.txt @@ -0,0 +1,378 @@ +RTC Evaluation Experiments - Sat Nov 22 23:39:40 +07 2025 +====================================== +Sat Nov 22 23:39:40 +07 2025: Starting pi05 steps=10 sigma_d=0.1 +WARNING:lerobot.configs.policies:Device 'cuda' is not available. Switching to 'mps'. +WARNING:lerobot.configs.policies:Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:39:46 _dataset.py:959 ================================================================================ +INFO 2025-11-22 23:39:46 _dataset.py:960 RTC Dataset Evaluation +INFO 2025-11-22 23:39:46 _dataset.py:961 Config: RTCEvalConfig(policy=PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path='lerobot/pi05_libero_finetuned', paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=None, image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': , 'STATE': , 'VISUAL': }, gradient_checkpointing=True, compile_model=True, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06), dataset=DatasetConfig(repo_id='HuggingFaceVLA/libero', root=None, episodes=None, image_transforms=ImageTransformsConfig(enable=False, max_num_transforms=3, random_order=False, tfs={'brightness': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'brightness': (0.8, 1.2)}), 'contrast': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'contrast': (0.8, 1.2)}), 'saturation': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'saturation': (0.5, 1.5)}), 'hue': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'hue': (-0.05, 0.05)}), 'sharpness': ImageTransformConfig(weight=1.0, type='SharpnessJitter', kwargs={'sharpness': (0.5, 1.5)}), 'affine': ImageTransformConfig(weight=1.0, type='RandomAffine', kwargs={'degrees': (-5.0, 5.0), 'translate': (0.05, 0.05)})}), revision=None, use_imagenet_stats=True, video_backend='torchcodec', streaming=False), rtc=RTCConfig(enabled=False, prefix_attention_schedule=, max_guidance_weight=None, execution_horizon=8, sigma_d=0.1, debug=False, debug_maxlen=100), device='mps', output_dir='rtc_experiments_results/pi05_steps_10_sigma_0.1', seed=10, inference_delay=4, num_inference_steps=10, use_torch_compile=False, torch_compile_backend='inductor', torch_compile_mode='default', torch_compile_disable_cudagraphs=True) +INFO 2025-11-22 23:39:46 _dataset.py:962 ================================================================================ +INFO 2025-11-22 23:39:46 _dataset.py:256 Loading dataset: HuggingFaceVLA/libero +INFO 2025-11-22 23:39:46 _dataset.py:269 Dataset loaded: 273465 samples, 1693 episodes +INFO 2025-11-22 23:39:49 _dataset.py:280 ================================================================================ +INFO 2025-11-22 23:39:49 _dataset.py:281 Ready to run evaluation with sequential policy loading: +INFO 2025-11-22 23:39:49 _dataset.py:282 1. policy_prev_chunk - Generate reference chunk, then destroy +INFO 2025-11-22 23:39:49 _dataset.py:283 2. policy_no_rtc - Generate without RTC, then destroy +INFO 2025-11-22 23:39:49 _dataset.py:284 3. policy_rtc - Generate with RTC, then destroy +INFO 2025-11-22 23:39:49 _dataset.py:285 Note: Only one policy in memory at a time for efficient memory usage +INFO 2025-11-22 23:39:49 _dataset.py:286 ================================================================================ +INFO 2025-11-22 23:39:49 _dataset.py:445 Output directory: rtc_experiments_results/pi05_steps_10_sigma_0.1 +INFO 2025-11-22 23:39:49 _dataset.py:447 ================================================================================ +INFO 2025-11-22 23:39:49 _dataset.py:448 Starting RTC evaluation +INFO 2025-11-22 23:39:49 _dataset.py:449 Inference delay: 4 +INFO 2025-11-22 23:39:49 _dataset.py:451 Number of flow matching steps: 10 +INFO 2025-11-22 23:39:49 _dataset.py:454 ================================================================================ +INFO 2025-11-22 23:39:49 _dataset.py:469 ================================================================================ +INFO 2025-11-22 23:39:49 _dataset.py:470 Step 1: Generating previous chunk with policy_prev_chunk +INFO 2025-11-22 23:39:49 _dataset.py:471 ================================================================================ +INFO 2025-11-22 23:39:49 _dataset.py:299 Initializing policy_prev_chunk... +INFO 2025-11-22 23:39:49 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:39:49 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:39:49 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:39:49 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:39:49 _dataset.py:316 Overriding num_inference_steps for pi05: 10 +INFO 2025-11-22 23:40:58 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model +WARNING 2025-11-22 23:41:01 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias +WARNING 2025-11-22 23:41:01 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight +INFO 2025-11-22 23:41:02 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC +INFO 2025-11-22 23:41:02 _dataset.py:336 RTC enabled: False +INFO 2025-11-22 23:41:02 _dataset.py:337 RTC debug: False +INFO 2025-11-22 23:41:02 _dataset.py:338 Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=False, prefix_attention_schedule=, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=False, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': , 'STATE': , 'VISUAL': }, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06) +INFO 2025-11-22 23:41:02 _dataset.py:344 ✓ policy_prev_chunk initialized successfully +INFO 2025-11-22 23:41:04 _dataset.py:483 Generated prev_chunk shape: torch.Size([25, 7]) +INFO 2025-11-22 23:41:04 _dataset.py:410 Destroying policy_prev_chunk and freeing memory... +INFO 2025-11-22 23:41:05 _dataset.py:430 ✓ policy_prev_chunk destroyed and memory freed +INFO 2025-11-22 23:41:05 _dataset.py:491 ================================================================================ +INFO 2025-11-22 23:41:05 _dataset.py:492 Step 2: Generating actions WITHOUT RTC with policy_no_rtc +INFO 2025-11-22 23:41:05 _dataset.py:493 ================================================================================ +INFO 2025-11-22 23:41:05 _dataset.py:299 Initializing policy_no_rtc... +INFO 2025-11-22 23:41:07 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:41:07 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:41:07 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:41:07 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:41:07 _dataset.py:316 Overriding num_inference_steps for pi05: 10 +INFO 2025-11-22 23:42:17 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model +WARNING 2025-11-22 23:42:19 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias +WARNING 2025-11-22 23:42:19 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight +INFO 2025-11-22 23:42:25 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC +INFO 2025-11-22 23:42:25 _dataset.py:336 RTC enabled: False +INFO 2025-11-22 23:42:25 _dataset.py:337 RTC debug: True +INFO 2025-11-22 23:42:25 _dataset.py:338 Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=False, prefix_attention_schedule=, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=True, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': , 'STATE': , 'VISUAL': }, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06) +INFO 2025-11-22 23:42:25 _dataset.py:344 ✓ policy_no_rtc initialized successfully +INFO 2025-11-22 23:42:28 _dataset.py:515 Tracked 10 steps without RTC +INFO 2025-11-22 23:42:28 _dataset.py:516 Generated no_rtc_actions shape: torch.Size([1, 50, 7]) +INFO 2025-11-22 23:42:28 _dataset.py:410 Destroying policy_no_rtc and freeing memory... +INFO 2025-11-22 23:42:30 _dataset.py:430 ✓ policy_no_rtc destroyed and memory freed +INFO 2025-11-22 23:42:30 _dataset.py:524 ================================================================================ +INFO 2025-11-22 23:42:30 _dataset.py:525 Step 3: Generating actions WITH RTC with policy_rtc +INFO 2025-11-22 23:42:30 _dataset.py:526 ================================================================================ +INFO 2025-11-22 23:42:30 _dataset.py:299 Initializing policy_rtc... +INFO 2025-11-22 23:42:31 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:42:31 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:42:31 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:42:31 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:42:31 _dataset.py:316 Overriding num_inference_steps for pi05: 10 +INFO 2025-11-22 23:43:39 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model +WARNING 2025-11-22 23:43:41 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias +WARNING 2025-11-22 23:43:41 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight +INFO 2025-11-22 23:43:56 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC +INFO 2025-11-22 23:43:56 _dataset.py:336 RTC enabled: True +INFO 2025-11-22 23:43:56 _dataset.py:337 RTC debug: True +INFO 2025-11-22 23:43:56 _dataset.py:338 Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=True, prefix_attention_schedule=, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=True, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': , 'STATE': , 'VISUAL': }, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06) +INFO 2025-11-22 23:43:56 _dataset.py:344 ✓ policy_rtc initialized successfully +INFO 2025-11-22 23:43:59 _dataset.py:546 Tracked 10 steps with RTC +INFO 2025-11-22 23:43:59 _dataset.py:547 Generated rtc_actions shape: torch.Size([1, 50, 7]) +ERROR 2025-11-22 23:43:59 _dataset.py:553 Error getting num_steps: 'PI05Config' object has no attribute 'num_steps' +WARNING 2025-11-22 23:43:59 _dataset.py:555 Using num_inference_steps: 10 instead of num_steps +INFO 2025-11-22 23:43:59 _dataset.py:410 Destroying policy_rtc and freeing memory... +INFO 2025-11-22 23:44:01 _dataset.py:430 ✓ policy_rtc destroyed and memory freed +INFO 2025-11-22 23:44:01 _dataset.py:561 ================================================================================ +INFO 2025-11-22 23:44:01 _dataset.py:562 Plotting results... +INFO 2025-11-22 23:44:01 _dataset.py:818 ================================================================================ +INFO 2025-11-22 23:44:01 _dataset.py:819 Plotting 10 steps +INFO 2025-11-22 23:44:02 _dataset.py:818 ================================================================================ +INFO 2025-11-22 23:44:02 _dataset.py:819 Plotting 10 steps +INFO 2025-11-22 23:44:02 _dataset.py:905 Plotting final no-RTC x_t step as orange dashed reference +INFO 2025-11-22 23:44:03 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.1/denoising_xt_comparison.png +INFO 2025-11-22 23:44:03 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.1/denoising_vt_comparison.png +INFO 2025-11-22 23:44:04 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.1/denoising_correction_comparison.png +INFO 2025-11-22 23:44:05 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.1/denoising_x1t_comparison.png +INFO 2025-11-22 23:44:05 _dataset.py:566 ================================================================================ +INFO 2025-11-22 23:44:05 _dataset.py:567 Plotting final actions comparison... +INFO 2025-11-22 23:44:05 _dataset.py:687 Saved final actions comparison to rtc_experiments_results/pi05_steps_10_sigma_0.1/final_actions_comparison.png +INFO 2025-11-22 23:44:05 _dataset.py:570 ================================================================================ +INFO 2025-11-22 23:44:05 _dataset.py:571 Evaluation completed successfully +The PI05 model is a direct port of the OpenPI implementation. +This implementation follows the original OpenPI structure for compatibility. +Original implementation: https://github.com/Physical-Intelligence/openpi +Loading model from: lerobot/pi05_libero_finetuned +✓ Loaded state dict from model.safetensors +Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy: + Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight". +The PI05 model is a direct port of the OpenPI implementation. +This implementation follows the original OpenPI structure for compatibility. +Original implementation: https://github.com/Physical-Intelligence/openpi +Loading model from: lerobot/pi05_libero_finetuned +✓ Loaded state dict from model.safetensors +Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy: + Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight". +The PI05 model is a direct port of the OpenPI implementation. +This implementation follows the original OpenPI structure for compatibility. +Original implementation: https://github.com/Physical-Intelligence/openpi +Loading model from: lerobot/pi05_libero_finetuned +✓ Loaded state dict from model.safetensors +Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy: + Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight". +Sat Nov 22 23:44:08 +07 2025: SUCCESS pi05 steps=10 sigma_d=0.1 + +Sat Nov 22 23:44:08 +07 2025: Starting pi05 steps=10 sigma_d=0.2 +WARNING:lerobot.configs.policies:Device 'cuda' is not available. Switching to 'mps'. +WARNING:lerobot.configs.policies:Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:44:14 _dataset.py:959 ================================================================================ +INFO 2025-11-22 23:44:14 _dataset.py:960 RTC Dataset Evaluation +INFO 2025-11-22 23:44:14 _dataset.py:961 Config: RTCEvalConfig(policy=PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path='lerobot/pi05_libero_finetuned', paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=None, image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': , 'STATE': , 'VISUAL': }, gradient_checkpointing=True, compile_model=True, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06), dataset=DatasetConfig(repo_id='HuggingFaceVLA/libero', root=None, episodes=None, image_transforms=ImageTransformsConfig(enable=False, max_num_transforms=3, random_order=False, tfs={'brightness': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'brightness': (0.8, 1.2)}), 'contrast': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'contrast': (0.8, 1.2)}), 'saturation': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'saturation': (0.5, 1.5)}), 'hue': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'hue': (-0.05, 0.05)}), 'sharpness': ImageTransformConfig(weight=1.0, type='SharpnessJitter', kwargs={'sharpness': (0.5, 1.5)}), 'affine': ImageTransformConfig(weight=1.0, type='RandomAffine', kwargs={'degrees': (-5.0, 5.0), 'translate': (0.05, 0.05)})}), revision=None, use_imagenet_stats=True, video_backend='torchcodec', streaming=False), rtc=RTCConfig(enabled=False, prefix_attention_schedule=, max_guidance_weight=None, execution_horizon=8, sigma_d=0.2, debug=False, debug_maxlen=100), device='mps', output_dir='rtc_experiments_results/pi05_steps_10_sigma_0.2', seed=10, inference_delay=4, num_inference_steps=10, use_torch_compile=False, torch_compile_backend='inductor', torch_compile_mode='default', torch_compile_disable_cudagraphs=True) +INFO 2025-11-22 23:44:14 _dataset.py:962 ================================================================================ +INFO 2025-11-22 23:44:14 _dataset.py:256 Loading dataset: HuggingFaceVLA/libero +INFO 2025-11-22 23:44:15 _dataset.py:269 Dataset loaded: 273465 samples, 1693 episodes +INFO 2025-11-22 23:44:17 _dataset.py:280 ================================================================================ +INFO 2025-11-22 23:44:17 _dataset.py:281 Ready to run evaluation with sequential policy loading: +INFO 2025-11-22 23:44:17 _dataset.py:282 1. policy_prev_chunk - Generate reference chunk, then destroy +INFO 2025-11-22 23:44:17 _dataset.py:283 2. policy_no_rtc - Generate without RTC, then destroy +INFO 2025-11-22 23:44:17 _dataset.py:284 3. policy_rtc - Generate with RTC, then destroy +INFO 2025-11-22 23:44:17 _dataset.py:285 Note: Only one policy in memory at a time for efficient memory usage +INFO 2025-11-22 23:44:17 _dataset.py:286 ================================================================================ +INFO 2025-11-22 23:44:17 _dataset.py:445 Output directory: rtc_experiments_results/pi05_steps_10_sigma_0.2 +INFO 2025-11-22 23:44:17 _dataset.py:447 ================================================================================ +INFO 2025-11-22 23:44:17 _dataset.py:448 Starting RTC evaluation +INFO 2025-11-22 23:44:17 _dataset.py:449 Inference delay: 4 +INFO 2025-11-22 23:44:17 _dataset.py:451 Number of flow matching steps: 10 +INFO 2025-11-22 23:44:17 _dataset.py:454 ================================================================================ +INFO 2025-11-22 23:44:17 _dataset.py:469 ================================================================================ +INFO 2025-11-22 23:44:17 _dataset.py:470 Step 1: Generating previous chunk with policy_prev_chunk +INFO 2025-11-22 23:44:17 _dataset.py:471 ================================================================================ +INFO 2025-11-22 23:44:17 _dataset.py:299 Initializing policy_prev_chunk... +INFO 2025-11-22 23:44:17 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:44:17 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:44:17 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:44:17 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:44:17 _dataset.py:316 Overriding num_inference_steps for pi05: 10 +INFO 2025-11-22 23:45:26 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model +WARNING 2025-11-22 23:45:28 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias +WARNING 2025-11-22 23:45:28 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight +INFO 2025-11-22 23:45:31 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC +INFO 2025-11-22 23:45:31 _dataset.py:336 RTC enabled: False +INFO 2025-11-22 23:45:31 _dataset.py:337 RTC debug: False +INFO 2025-11-22 23:45:31 _dataset.py:338 Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=False, prefix_attention_schedule=, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=False, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': , 'STATE': , 'VISUAL': }, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06) +INFO 2025-11-22 23:45:31 _dataset.py:344 ✓ policy_prev_chunk initialized successfully +INFO 2025-11-22 23:45:33 _dataset.py:483 Generated prev_chunk shape: torch.Size([25, 7]) +INFO 2025-11-22 23:45:33 _dataset.py:410 Destroying policy_prev_chunk and freeing memory... +INFO 2025-11-22 23:45:34 _dataset.py:430 ✓ policy_prev_chunk destroyed and memory freed +INFO 2025-11-22 23:45:34 _dataset.py:491 ================================================================================ +INFO 2025-11-22 23:45:34 _dataset.py:492 Step 2: Generating actions WITHOUT RTC with policy_no_rtc +INFO 2025-11-22 23:45:34 _dataset.py:493 ================================================================================ +INFO 2025-11-22 23:45:34 _dataset.py:299 Initializing policy_no_rtc... +INFO 2025-11-22 23:45:34 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:45:34 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:45:35 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:45:35 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:45:35 _dataset.py:316 Overriding num_inference_steps for pi05: 10 +INFO 2025-11-22 23:46:43 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model +WARNING 2025-11-22 23:46:44 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias +WARNING 2025-11-22 23:46:44 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight +INFO 2025-11-22 23:46:46 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC +INFO 2025-11-22 23:46:46 _dataset.py:336 RTC enabled: False +INFO 2025-11-22 23:46:46 _dataset.py:337 RTC debug: True +INFO 2025-11-22 23:46:46 _dataset.py:338 Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=False, prefix_attention_schedule=, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=True, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': , 'STATE': , 'VISUAL': }, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06) +INFO 2025-11-22 23:46:46 _dataset.py:344 ✓ policy_no_rtc initialized successfully +INFO 2025-11-22 23:46:48 _dataset.py:515 Tracked 10 steps without RTC +INFO 2025-11-22 23:46:48 _dataset.py:516 Generated no_rtc_actions shape: torch.Size([1, 50, 7]) +INFO 2025-11-22 23:46:48 _dataset.py:410 Destroying policy_no_rtc and freeing memory... +INFO 2025-11-22 23:46:49 _dataset.py:430 ✓ policy_no_rtc destroyed and memory freed +INFO 2025-11-22 23:46:49 _dataset.py:524 ================================================================================ +INFO 2025-11-22 23:46:49 _dataset.py:525 Step 3: Generating actions WITH RTC with policy_rtc +INFO 2025-11-22 23:46:49 _dataset.py:526 ================================================================================ +INFO 2025-11-22 23:46:49 _dataset.py:299 Initializing policy_rtc... +INFO 2025-11-22 23:46:49 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:46:49 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:46:49 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:46:49 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:46:49 _dataset.py:316 Overriding num_inference_steps for pi05: 10 +INFO 2025-11-22 23:47:56 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model +WARNING 2025-11-22 23:47:58 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias +WARNING 2025-11-22 23:47:58 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight +INFO 2025-11-22 23:48:07 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC +INFO 2025-11-22 23:48:07 _dataset.py:336 RTC enabled: True +INFO 2025-11-22 23:48:07 _dataset.py:337 RTC debug: True +INFO 2025-11-22 23:48:07 _dataset.py:338 Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=True, prefix_attention_schedule=, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=True, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': , 'STATE': , 'VISUAL': }, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06) +INFO 2025-11-22 23:48:07 _dataset.py:344 ✓ policy_rtc initialized successfully +INFO 2025-11-22 23:48:10 _dataset.py:546 Tracked 10 steps with RTC +INFO 2025-11-22 23:48:10 _dataset.py:547 Generated rtc_actions shape: torch.Size([1, 50, 7]) +ERROR 2025-11-22 23:48:10 _dataset.py:553 Error getting num_steps: 'PI05Config' object has no attribute 'num_steps' +WARNING 2025-11-22 23:48:10 _dataset.py:555 Using num_inference_steps: 10 instead of num_steps +INFO 2025-11-22 23:48:10 _dataset.py:410 Destroying policy_rtc and freeing memory... +INFO 2025-11-22 23:48:12 _dataset.py:430 ✓ policy_rtc destroyed and memory freed +INFO 2025-11-22 23:48:12 _dataset.py:561 ================================================================================ +INFO 2025-11-22 23:48:12 _dataset.py:562 Plotting results... +INFO 2025-11-22 23:48:12 _dataset.py:818 ================================================================================ +INFO 2025-11-22 23:48:12 _dataset.py:819 Plotting 10 steps +INFO 2025-11-22 23:48:13 _dataset.py:818 ================================================================================ +INFO 2025-11-22 23:48:13 _dataset.py:819 Plotting 10 steps +INFO 2025-11-22 23:48:13 _dataset.py:905 Plotting final no-RTC x_t step as orange dashed reference +INFO 2025-11-22 23:48:14 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.2/denoising_xt_comparison.png +INFO 2025-11-22 23:48:15 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.2/denoising_vt_comparison.png +INFO 2025-11-22 23:48:15 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.2/denoising_correction_comparison.png +INFO 2025-11-22 23:48:16 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.2/denoising_x1t_comparison.png +INFO 2025-11-22 23:48:16 _dataset.py:566 ================================================================================ +INFO 2025-11-22 23:48:16 _dataset.py:567 Plotting final actions comparison... +INFO 2025-11-22 23:48:17 _dataset.py:687 Saved final actions comparison to rtc_experiments_results/pi05_steps_10_sigma_0.2/final_actions_comparison.png +INFO 2025-11-22 23:48:17 _dataset.py:570 ================================================================================ +INFO 2025-11-22 23:48:17 _dataset.py:571 Evaluation completed successfully +The PI05 model is a direct port of the OpenPI implementation. +This implementation follows the original OpenPI structure for compatibility. +Original implementation: https://github.com/Physical-Intelligence/openpi +Loading model from: lerobot/pi05_libero_finetuned +✓ Loaded state dict from model.safetensors +Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy: + Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight". +The PI05 model is a direct port of the OpenPI implementation. +This implementation follows the original OpenPI structure for compatibility. +Original implementation: https://github.com/Physical-Intelligence/openpi +Loading model from: lerobot/pi05_libero_finetuned +✓ Loaded state dict from model.safetensors +Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy: + Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight". +The PI05 model is a direct port of the OpenPI implementation. +This implementation follows the original OpenPI structure for compatibility. +Original implementation: https://github.com/Physical-Intelligence/openpi +Loading model from: lerobot/pi05_libero_finetuned +✓ Loaded state dict from model.safetensors +Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy: + Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight". +Sat Nov 22 23:48:19 +07 2025: SUCCESS pi05 steps=10 sigma_d=0.2 + +Sat Nov 22 23:48:19 +07 2025: Starting pi05 steps=10 sigma_d=0.5 +WARNING:lerobot.configs.policies:Device 'cuda' is not available. Switching to 'mps'. +WARNING:lerobot.configs.policies:Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:48:25 _dataset.py:959 ================================================================================ +INFO 2025-11-22 23:48:25 _dataset.py:960 RTC Dataset Evaluation +INFO 2025-11-22 23:48:25 _dataset.py:961 Config: RTCEvalConfig(policy=PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path='lerobot/pi05_libero_finetuned', paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=None, image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': , 'STATE': , 'VISUAL': }, gradient_checkpointing=True, compile_model=True, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06), dataset=DatasetConfig(repo_id='HuggingFaceVLA/libero', root=None, episodes=None, image_transforms=ImageTransformsConfig(enable=False, max_num_transforms=3, random_order=False, tfs={'brightness': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'brightness': (0.8, 1.2)}), 'contrast': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'contrast': (0.8, 1.2)}), 'saturation': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'saturation': (0.5, 1.5)}), 'hue': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'hue': (-0.05, 0.05)}), 'sharpness': ImageTransformConfig(weight=1.0, type='SharpnessJitter', kwargs={'sharpness': (0.5, 1.5)}), 'affine': ImageTransformConfig(weight=1.0, type='RandomAffine', kwargs={'degrees': (-5.0, 5.0), 'translate': (0.05, 0.05)})}), revision=None, use_imagenet_stats=True, video_backend='torchcodec', streaming=False), rtc=RTCConfig(enabled=False, prefix_attention_schedule=, max_guidance_weight=None, execution_horizon=8, sigma_d=0.5, debug=False, debug_maxlen=100), device='mps', output_dir='rtc_experiments_results/pi05_steps_10_sigma_0.5', seed=10, inference_delay=4, num_inference_steps=10, use_torch_compile=False, torch_compile_backend='inductor', torch_compile_mode='default', torch_compile_disable_cudagraphs=True) +INFO 2025-11-22 23:48:25 _dataset.py:962 ================================================================================ +INFO 2025-11-22 23:48:25 _dataset.py:256 Loading dataset: HuggingFaceVLA/libero +INFO 2025-11-22 23:48:26 _dataset.py:269 Dataset loaded: 273465 samples, 1693 episodes +INFO 2025-11-22 23:48:28 _dataset.py:280 ================================================================================ +INFO 2025-11-22 23:48:28 _dataset.py:281 Ready to run evaluation with sequential policy loading: +INFO 2025-11-22 23:48:28 _dataset.py:282 1. policy_prev_chunk - Generate reference chunk, then destroy +INFO 2025-11-22 23:48:28 _dataset.py:283 2. policy_no_rtc - Generate without RTC, then destroy +INFO 2025-11-22 23:48:28 _dataset.py:284 3. policy_rtc - Generate with RTC, then destroy +INFO 2025-11-22 23:48:28 _dataset.py:285 Note: Only one policy in memory at a time for efficient memory usage +INFO 2025-11-22 23:48:28 _dataset.py:286 ================================================================================ +INFO 2025-11-22 23:48:28 _dataset.py:445 Output directory: rtc_experiments_results/pi05_steps_10_sigma_0.5 +INFO 2025-11-22 23:48:28 _dataset.py:447 ================================================================================ +INFO 2025-11-22 23:48:28 _dataset.py:448 Starting RTC evaluation +INFO 2025-11-22 23:48:28 _dataset.py:449 Inference delay: 4 +INFO 2025-11-22 23:48:28 _dataset.py:451 Number of flow matching steps: 10 +INFO 2025-11-22 23:48:28 _dataset.py:454 ================================================================================ +INFO 2025-11-22 23:48:28 _dataset.py:469 ================================================================================ +INFO 2025-11-22 23:48:28 _dataset.py:470 Step 1: Generating previous chunk with policy_prev_chunk +INFO 2025-11-22 23:48:28 _dataset.py:471 ================================================================================ +INFO 2025-11-22 23:48:28 _dataset.py:299 Initializing policy_prev_chunk... +INFO 2025-11-22 23:48:28 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:48:28 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:48:28 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:48:28 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:48:28 _dataset.py:316 Overriding num_inference_steps for pi05: 10 +INFO 2025-11-22 23:49:37 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model +WARNING 2025-11-22 23:49:39 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias +WARNING 2025-11-22 23:49:39 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight +INFO 2025-11-22 23:49:42 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC +INFO 2025-11-22 23:49:42 _dataset.py:336 RTC enabled: False +INFO 2025-11-22 23:49:42 _dataset.py:337 RTC debug: False +INFO 2025-11-22 23:49:42 _dataset.py:338 Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=False, prefix_attention_schedule=, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=False, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': , 'STATE': , 'VISUAL': }, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06) +INFO 2025-11-22 23:49:42 _dataset.py:344 ✓ policy_prev_chunk initialized successfully +INFO 2025-11-22 23:49:44 _dataset.py:483 Generated prev_chunk shape: torch.Size([25, 7]) +INFO 2025-11-22 23:49:44 _dataset.py:410 Destroying policy_prev_chunk and freeing memory... +INFO 2025-11-22 23:49:45 _dataset.py:430 ✓ policy_prev_chunk destroyed and memory freed +INFO 2025-11-22 23:49:45 _dataset.py:491 ================================================================================ +INFO 2025-11-22 23:49:45 _dataset.py:492 Step 2: Generating actions WITHOUT RTC with policy_no_rtc +INFO 2025-11-22 23:49:45 _dataset.py:493 ================================================================================ +INFO 2025-11-22 23:49:45 _dataset.py:299 Initializing policy_no_rtc... +INFO 2025-11-22 23:49:46 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:49:46 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:49:46 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:49:46 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:49:46 _dataset.py:316 Overriding num_inference_steps for pi05: 10 +INFO 2025-11-22 23:50:55 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model +WARNING 2025-11-22 23:50:57 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias +WARNING 2025-11-22 23:50:57 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight +INFO 2025-11-22 23:50:58 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC +INFO 2025-11-22 23:50:58 _dataset.py:336 RTC enabled: False +INFO 2025-11-22 23:50:58 _dataset.py:337 RTC debug: True +INFO 2025-11-22 23:50:58 _dataset.py:338 Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=False, prefix_attention_schedule=, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=True, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': , 'STATE': , 'VISUAL': }, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06) +INFO 2025-11-22 23:50:58 _dataset.py:344 ✓ policy_no_rtc initialized successfully +INFO 2025-11-22 23:51:00 _dataset.py:515 Tracked 10 steps without RTC +INFO 2025-11-22 23:51:00 _dataset.py:516 Generated no_rtc_actions shape: torch.Size([1, 50, 7]) +INFO 2025-11-22 23:51:00 _dataset.py:410 Destroying policy_no_rtc and freeing memory... +INFO 2025-11-22 23:51:01 _dataset.py:430 ✓ policy_no_rtc destroyed and memory freed +INFO 2025-11-22 23:51:01 _dataset.py:524 ================================================================================ +INFO 2025-11-22 23:51:01 _dataset.py:525 Step 3: Generating actions WITH RTC with policy_rtc +INFO 2025-11-22 23:51:01 _dataset.py:526 ================================================================================ +INFO 2025-11-22 23:51:01 _dataset.py:299 Initializing policy_rtc... +INFO 2025-11-22 23:51:01 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:51:01 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:51:02 ils/utils.py:46 Metal backend detected, using mps. +WARNING 2025-11-22 23:51:02 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'. +INFO 2025-11-22 23:51:02 _dataset.py:316 Overriding num_inference_steps for pi05: 10 +INFO 2025-11-22 23:52:12 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model +WARNING 2025-11-22 23:52:13 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias +WARNING 2025-11-22 23:52:13 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight +INFO 2025-11-22 23:52:24 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC +INFO 2025-11-22 23:52:24 _dataset.py:336 RTC enabled: True +INFO 2025-11-22 23:52:24 _dataset.py:337 RTC debug: True +INFO 2025-11-22 23:52:24 _dataset.py:338 Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=True, prefix_attention_schedule=, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=True, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': , 'STATE': , 'VISUAL': }, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06) +INFO 2025-11-22 23:52:24 _dataset.py:344 ✓ policy_rtc initialized successfully +INFO 2025-11-22 23:52:27 _dataset.py:546 Tracked 10 steps with RTC +INFO 2025-11-22 23:52:27 _dataset.py:547 Generated rtc_actions shape: torch.Size([1, 50, 7]) +ERROR 2025-11-22 23:52:27 _dataset.py:553 Error getting num_steps: 'PI05Config' object has no attribute 'num_steps' +WARNING 2025-11-22 23:52:27 _dataset.py:555 Using num_inference_steps: 10 instead of num_steps +INFO 2025-11-22 23:52:27 _dataset.py:410 Destroying policy_rtc and freeing memory... +INFO 2025-11-22 23:52:29 _dataset.py:430 ✓ policy_rtc destroyed and memory freed +INFO 2025-11-22 23:52:29 _dataset.py:561 ================================================================================ +INFO 2025-11-22 23:52:29 _dataset.py:562 Plotting results... +INFO 2025-11-22 23:52:29 _dataset.py:818 ================================================================================ +INFO 2025-11-22 23:52:29 _dataset.py:819 Plotting 10 steps +INFO 2025-11-22 23:52:30 _dataset.py:818 ================================================================================ +INFO 2025-11-22 23:52:30 _dataset.py:819 Plotting 10 steps +INFO 2025-11-22 23:52:30 _dataset.py:905 Plotting final no-RTC x_t step as orange dashed reference +INFO 2025-11-22 23:52:31 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.5/denoising_xt_comparison.png +INFO 2025-11-22 23:52:32 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.5/denoising_vt_comparison.png +INFO 2025-11-22 23:52:32 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.5/denoising_correction_comparison.png +INFO 2025-11-22 23:52:33 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.5/denoising_x1t_comparison.png +INFO 2025-11-22 23:52:33 _dataset.py:566 ================================================================================ +INFO 2025-11-22 23:52:33 _dataset.py:567 Plotting final actions comparison... +INFO 2025-11-22 23:52:34 _dataset.py:687 Saved final actions comparison to rtc_experiments_results/pi05_steps_10_sigma_0.5/final_actions_comparison.png +INFO 2025-11-22 23:52:34 _dataset.py:570 ================================================================================ +INFO 2025-11-22 23:52:34 _dataset.py:571 Evaluation completed successfully +The PI05 model is a direct port of the OpenPI implementation. +This implementation follows the original OpenPI structure for compatibility. +Original implementation: https://github.com/Physical-Intelligence/openpi +Loading model from: lerobot/pi05_libero_finetuned +✓ Loaded state dict from model.safetensors +Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy: + Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight". +The PI05 model is a direct port of the OpenPI implementation. +This implementation follows the original OpenPI structure for compatibility. +Original implementation: https://github.com/Physical-Intelligence/openpi +Loading model from: lerobot/pi05_libero_finetuned +✓ Loaded state dict from model.safetensors +Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy: + Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight". +The PI05 model is a direct port of the OpenPI implementation. +This implementation follows the original OpenPI structure for compatibility. +Original implementation: https://github.com/Physical-Intelligence/openpi +Loading model from: lerobot/pi05_libero_finetuned +✓ Loaded state dict from model.safetensors +Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy: + Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight". +Sat Nov 22 23:52:36 +07 2025: SUCCESS pi05 steps=10 sigma_d=0.5 + +Sat Nov 22 23:52:36 +07 2025: Starting pi05 steps=10 sigma_d=1.0 diff --git a/static/experiments/pi05_steps_10_sigma_0.1/denoising_correction_comparison.png b/static/experiments/pi05_steps_10_sigma_0.1/denoising_correction_comparison.png new file mode 100644 index 0000000000000000000000000000000000000000..b519c5c52e4f31fdb2e82027b3cd5cf884107942 --- /dev/null +++ b/static/experiments/pi05_steps_10_sigma_0.1/denoising_correction_comparison.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8586b49d1e7489b52bc60b825b8ad3b51afa5f248b2f0ad6a32ed50803f2eabe 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