第一次baseline测试，补充psnr测定

.claude/settings.local.json

@@ -1,21 +0,0 @@
-{
-  "permissions": {
-    "allow": [
-      "Bash(conda env list:*)",
-      "Bash(mamba env:*)",
-      "Bash(micromamba env list:*)",
-      "Bash(echo:*)",
-      "Bash(git show:*)",
-      "Bash(nvidia-smi:*)",
-      "Bash(conda activate unifolm-wma)",
-      "Bash(conda info:*)",
-      "Bash(direnv allow:*)",
-      "Bash(ls:*)",
-      "Bash(for scenario in unitree_g1_pack_camera unitree_z1_dual_arm_cleanup_pencils unitree_z1_dual_arm_stackbox unitree_z1_dual_arm_stackbox_v2 unitree_z1_stackbox)",
-      "Bash(do for case in case1 case2 case3 case4)",
-      "Bash(done)",
-      "Bash(chmod:*)",
-      "Bash(ln:*)"
-    ]
-  }
-}

.envrc

@@ -1,2 +0,0 @@
-eval "$(conda shell.bash hook 2>/dev/null)"
-conda activate unifolm-wma

.gitignore

@@ -55,6 +55,7 @@ coverage.xml
 *.pot
 
 # Django stuff:
+
 local_settings.py
 db.sqlite3
 
@@ -120,15 +121,11 @@ localTest/
 fig/
 figure/
 *.mp4
-
 Data/ControlVAE.yml
 Data/Misc
 Data/Pretrained
 Data/utils.py
 Experiment/checkpoint
 Experiment/log
-
+ckpts/unifolm_wma_dual.ckpt
-*.ckpt
-
 *.0
-ckpts/unifolm_wma_dual.ckpt.prepared.pt

ckpts/LICENSE

@@ -1,439 +0,0 @@
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ckpts/README.md

@@ -1,38 +0,0 @@
----
-tags:
-- robotics
----
-
-# UnifoLM-WMA-0: A World-Model-Action (WMA) Framework under UnifoLM Family
-<p style="font-size: 1.2em;">
-    <a href="https://unigen-x.github.io/unifolm-world-model-action.github.io"><strong>Project Page</strong></a> | 
-    <a href="https://github.com/unitreerobotics/unifolm-world-model-action"><strong>Code</strong></a> |
-    <a href="https://huggingface.co/unitreerobotics/datasets"><strong>Dataset</strong></a> 
-  </p>
-<div align="center">
-  <div align="justify">
-    <b>UnifoLM-WMA-0</b> is Unitree‘s first open-source world-model–action architecture spanning multiple types of robotic embodiments, designed specifically for general-purpose robot learning. Its core component is a world-model capable of understanding the physical interactions between robots and the environments. This world-model provides two key functions: (a) <b>Simulation Engine</b> – operates as an interactive simulator to generate synthetic data for robot learning; (b) <b>Policy Enhancement</b> – connects with an action head and, by predicting future interaction processes with the world-model, further optimizes decision-making performance.
-  </div>
-</div>
-
-## 🦾 Real Robot Deployment
-| <img src="assets/real_z1_stackbox.gif" style="border:none;box-shadow:none;margin:0;padding:0;" /> | <img src="assets/real_dual_stackbox.gif" style="border:none;box-shadow:none;margin:0;padding:0;" /> |
-|:---:|:---:|
-| <img src="assets/real_cleanup_pencils.gif" style="border:none;box-shadow:none;margin:0;padding:0;" /> | <img src="assets/real_g1_pack_camera.gif" style="border:none;box-shadow:none;margin:0;padding:0;" /> |
-
-**Note: the top-right window shows the world model’s prediction of future environmental changes.**
-
-## License
-The model is released under the CC BY-NC-SA 4.0 license as found in the [LICENSE](https://huggingface.co/unitreerobotics/UnifoLM-WMA-0/blob/main/LICENSE). You are responsible for ensuring that your use of Unitree AI Models complies with all applicable laws.
-
-## Model Architecture
-![Demo](assets/world_model_interaction.gif)
-
-## Citation
-```
-@misc{unifolm-wma-0,
-  author = {Unitree},
-  title  = {UnifoLM-WMA-0: A World-Model-Action (WMA) Framework under UnifoLM Family},
-  year   = {2025},
-}
-```

pyproject.toml

@@ -19,13 +19,13 @@ dependencies = [
     "pytorch-lightning==1.9.3",
     "pyyaml==6.0",
     "setuptools==65.6.3",
-    #"torch==2.3.1",
+    "torch==2.3.1",
-    #"torchvision==0.18.1",
+    "torchvision==0.18.1",
     "tqdm==4.66.5",
     "transformers==4.40.1",
     "moviepy==1.0.3",
     "av==12.3.0",
-    #"xformers==0.0.27",
+    "xformers==0.0.27",
     "gradio==4.39.0",
     "timm==0.9.10",
     "scikit-learn==1.5.1",

run_all_cases_20260211_173422.log

@@ -1,37 +0,0 @@
-2026-02-11 17:34:29.188470: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 17:34:29.238296: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 17:34:29.238342: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 17:34:29.239649: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 17:34:29.247152: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
-To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 17:34:30.172640: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
-Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
->>> Prepared model loaded.
->>> Diffusion backbone (model.model) converted to FP16.
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
-INFO:root:***** Configing Data *****
->>> unitree_z1_stackbox: 1 data samples loaded.
->>> unitree_z1_stackbox: data stats loaded.
->>> unitree_z1_stackbox: normalizer initiated.
->>> unitree_z1_dual_arm_stackbox: 1 data samples loaded.
->>> unitree_z1_dual_arm_stackbox: data stats loaded.
->>> unitree_z1_dual_arm_stackbox: normalizer initiated.
->>> unitree_z1_dual_arm_stackbox_v2: 1 data samples loaded.
->>> unitree_z1_dual_arm_stackbox_v2: data stats loaded.
->>> unitree_z1_dual_arm_stackbox_v2: normalizer initiated.
->>> unitree_z1_dual_arm_cleanup_pencils: 1 data samples loaded.
->>> unitree_z1_dual_arm_cleanup_pencils: data stats loaded.
->>> unitree_z1_dual_arm_cleanup_pencils: normalizer initiated.
->>> unitree_g1_pack_camera: 1 data samples loaded.
->>> unitree_g1_pack_camera: data stats loaded.
->>> unitree_g1_pack_camera: normalizer initiated.
->>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
->>> Generate 16 frames under each generation ...
-DEBUG:h5py._conv:Creating converter from 3 to 5
-DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
-DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
-DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-

scripts/evaluation/base_model_inference.py

@@ -16,9 +16,6 @@ from collections import OrderedDict
 from unifolm_wma.models.samplers.ddim import DDIMSampler
 from unifolm_wma.utils.utils import instantiate_from_config
 
-torch.backends.cuda.matmul.allow_tf32 = True
-torch.backends.cudnn.allow_tf32 = True
-
 
 def get_filelist(data_dir: str, postfixes: list[str]) -> list[str]:
     """

scripts/evaluation/real_eval_server.py

@@ -19,9 +19,6 @@ from fastapi.responses import JSONResponse
 from typing import Any, Dict, Optional, Tuple, List
 from datetime import datetime
 
-torch.backends.cuda.matmul.allow_tf32 = True
-torch.backends.cudnn.allow_tf32 = True
-
 from unifolm_wma.utils.utils import instantiate_from_config
 from unifolm_wma.models.samplers.ddim import DDIMSampler
 

scripts/evaluation/world_model_interaction.py

@@ -9,8 +9,6 @@ import logging
 import einops
 import warnings
 import imageio
-import atexit
-from concurrent.futures import ThreadPoolExecutor
 
 from pytorch_lightning import seed_everything
 from omegaconf import OmegaConf
@@ -18,12 +16,8 @@ from tqdm import tqdm
 from einops import rearrange, repeat
 from collections import OrderedDict
 from torch import nn
-from eval_utils import populate_queues
+from eval_utils import populate_queues, log_to_tensorboard
 from collections import deque
-from typing import Optional, List, Any
-
-torch.backends.cuda.matmul.allow_tf32 = True
-torch.backends.cudnn.allow_tf32 = True
 from torch import Tensor
 from torch.utils.tensorboard import SummaryWriter
 from PIL import Image
@@ -156,81 +150,6 @@ def save_results(video: Tensor, filename: str, fps: int = 8) -> None:
                                options={'crf': '10'})
 
 
-# ========== Async I/O ==========
-_io_executor: Optional[ThreadPoolExecutor] = None
-_io_futures: List[Any] = []
-
-
-def _get_io_executor() -> ThreadPoolExecutor:
-    global _io_executor
-    if _io_executor is None:
-        _io_executor = ThreadPoolExecutor(max_workers=2)
-    return _io_executor
-
-
-def _flush_io():
-    """Wait for all pending async I/O to finish."""
-    global _io_futures
-    for fut in _io_futures:
-        try:
-            fut.result()
-        except Exception as e:
-            print(f">>> [async I/O] error: {e}")
-    _io_futures.clear()
-
-
-atexit.register(_flush_io)
-
-
-def _save_results_sync(video_cpu: Tensor, filename: str, fps: int) -> None:
-    """Synchronous save on CPU tensor (runs in background thread)."""
-    video = torch.clamp(video_cpu.float(), -1., 1.)
-    n = video.shape[0]
-    video = video.permute(2, 0, 1, 3, 4)
-    frame_grids = [
-        torchvision.utils.make_grid(framesheet, nrow=int(n), padding=0)
-        for framesheet in video
-    ]
-    grid = torch.stack(frame_grids, dim=0)
-    grid = (grid + 1.0) / 2.0
-    grid = (grid * 255).to(torch.uint8).permute(0, 2, 3, 1)
-    torchvision.io.write_video(filename,
-                               grid,
-                               fps=fps,
-                               video_codec='h264',
-                               options={'crf': '10'})
-
-
-def save_results_async(video: Tensor, filename: str, fps: int = 8) -> None:
-    """Submit video saving to background thread pool."""
-    video_cpu = video.detach().cpu()
-    fut = _get_io_executor().submit(_save_results_sync, video_cpu, filename, fps)
-    _io_futures.append(fut)
-
-
-def _log_to_tb_sync(writer, video_cpu: Tensor, tag: str, fps: int) -> None:
-    """Synchronous TensorBoard log on CPU tensor (runs in background thread)."""
-    if video_cpu.dim() == 5:
-        n = video_cpu.shape[0]
-        video = video_cpu.permute(2, 0, 1, 3, 4)
-        frame_grids = [
-            torchvision.utils.make_grid(framesheet, nrow=int(n), padding=0)
-            for framesheet in video
-        ]
-        grid = torch.stack(frame_grids, dim=0)
-        grid = (grid + 1.0) / 2.0
-        grid = grid.unsqueeze(dim=0)
-        writer.add_video(tag, grid, fps=fps)
-
-
-def log_to_tensorboard_async(writer, data: Tensor, tag: str, fps: int = 10) -> None:
-    """Submit TensorBoard logging to background thread pool."""
-    if isinstance(data, torch.Tensor) and data.dim() == 5:
-        data_cpu = data.detach().cpu()
-        fut = _get_io_executor().submit(_log_to_tb_sync, writer, data_cpu, tag, fps)
-        _io_futures.append(fut)
-
-
 def get_init_frame_path(data_dir: str, sample: dict) -> str:
     """Construct the init_frame path from directory and sample metadata.
 
@@ -408,8 +327,7 @@ def image_guided_synthesis_sim_mode(
         timestep_spacing: str = 'uniform',
         guidance_rescale: float = 0.0,
         sim_mode: bool = True,
-        decode_video: bool = True,
+        **kwargs) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
-        **kwargs) -> tuple[torch.Tensor | None, torch.Tensor, torch.Tensor]:
     """
     Performs image-guided video generation in a simulation-style mode with optional multimodal guidance (image, state, action, text).
 
@@ -432,13 +350,10 @@ def image_guided_synthesis_sim_mode(
         timestep_spacing (str): Timestep sampling method in DDIM sampler. Typically "uniform" or "linspace".
         guidance_rescale (float): Guidance rescaling factor to mitigate overexposure from classifier-free guidance.
         sim_mode (bool): Whether to perform world-model interaction or decision-making using the world-model.
-        decode_video (bool): Whether to decode latent samples to pixel-space video.
-            Set to False to skip VAE decode for speed when only actions/states are needed.
         **kwargs: Additional arguments passed to the DDIM sampler.
 
     Returns:
-        batch_variants (torch.Tensor | None): Predicted pixel-space video frames [B, C, T, H, W],
+        batch_variants (torch.Tensor): Predicted pixel-space video frames [B, C, T, H, W].
-            or None when decode_video=False.
         actions (torch.Tensor): Predicted action sequences [B, T, D] from diffusion decoding.
         states (torch.Tensor): Predicted state sequences [B, T, D] from diffusion decoding.
     """
@@ -450,7 +365,6 @@ def image_guided_synthesis_sim_mode(
 
     img = observation['observation.images.top'].permute(0, 2, 1, 3, 4)
     cond_img = rearrange(img, 'b o c h w -> (b o) c h w')[-1:]
-    with torch.cuda.amp.autocast(dtype=torch.float16):
     cond_img_emb = model.embedder(cond_img)
     cond_img_emb = model.image_proj_model(cond_img_emb)
 
@@ -466,7 +380,6 @@ def image_guided_synthesis_sim_mode(
         prompts = [""] * batch_size
     cond_ins_emb = model.get_learned_conditioning(prompts)
 
-    with torch.cuda.amp.autocast(dtype=torch.float16):
     cond_state_emb = model.state_projector(observation['observation.state'])
     cond_state_emb = cond_state_emb + model.agent_state_pos_emb
 
@@ -493,8 +406,6 @@ def image_guided_synthesis_sim_mode(
     kwargs.update({"unconditional_conditioning_img_nonetext": None})
     cond_mask = None
     cond_z0 = None
-    batch_variants = None
-    samples = None
     if ddim_sampler is not None:
         samples, actions, states, intermedia = ddim_sampler.sample(
             S=ddim_steps,
@@ -513,12 +424,11 @@ def image_guided_synthesis_sim_mode(
             guidance_rescale=guidance_rescale,
             **kwargs)
 
-        if decode_video:
         # Reconstruct from latent to pixel space
         batch_images = model.decode_first_stage(samples)
         batch_variants = batch_images
 
-    return batch_variants, actions, states, samples
+    return batch_variants, actions, states
 
 
 def run_inference(args: argparse.Namespace, gpu_num: int, gpu_no: int) -> None:
@@ -543,67 +453,26 @@ def run_inference(args: argparse.Namespace, gpu_num: int, gpu_no: int) -> None:
     csv_path = os.path.join(args.prompt_dir, f"{args.dataset}.csv")
     df = pd.read_csv(csv_path)
 
-    # Load config (always needed for data setup)
+    # Load config
     config = OmegaConf.load(args.config)
-
-    prepared_path = args.ckpt_path + ".prepared.pt"
-    if os.path.exists(prepared_path):
-        # ---- Fast path: load the fully-prepared model ----
-        print(f">>> Loading prepared model from {prepared_path} ...")
-        model = torch.load(prepared_path,
-                           map_location=f"cuda:{gpu_no}",
-                           weights_only=False,
-                           mmap=True)
-        model.eval()
-        print(f">>> Prepared model loaded.")
-    else:
-        # ---- Normal path: construct + load checkpoint ----
     config['model']['params']['wma_config']['params'][
         'use_checkpoint'] = False
     model = instantiate_from_config(config.model)
     model.perframe_ae = args.perframe_ae
-
     assert os.path.exists(args.ckpt_path), "Error: checkpoint Not Found!"
     model = load_model_checkpoint(model, args.ckpt_path)
     model.eval()
-        model = model.cuda(gpu_no)
     print(f'>>> Load pre-trained model ...')
 
-        # Save prepared model for fast loading next time
+    # Build unnomalizer
-        print(f">>> Saving prepared model to {prepared_path} ...")
-        torch.save(model, prepared_path)
-        print(f">>> Prepared model saved ({os.path.getsize(prepared_path) / 1024**3:.1f} GB).")
-
-    # ---- FP16: convert diffusion backbone + conditioning modules ----
-    model.model.to(torch.float16)
-    model.model.diffusion_model.dtype = torch.float16
-    print(">>> Diffusion backbone (model.model) converted to FP16.")
-
-    # Projectors / MLP → FP16
-    model.image_proj_model.half()
-    model.state_projector.half()
-    model.action_projector.half()
-    print(">>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.")
-
-    # Text/image encoders → FP16
-    model.cond_stage_model.half()
-    model.embedder.half()
-    print(">>> Encoders (cond_stage_model, embedder) converted to FP16.")
-
-    # Build normalizer (always needed, independent of model loading path)
     logging.info("***** Configing Data *****")
     data = instantiate_from_config(config.data)
     data.setup()
     print(">>> Dataset is successfully loaded ...")
 
+    model = model.cuda(gpu_no)
     device = get_device_from_parameters(model)
 
-    # Fuse KV projections in attention layers (to_k + to_v → to_kv)
-    from unifolm_wma.modules.attention import CrossAttention
-    kv_count = sum(1 for m in model.modules()
-                   if isinstance(m, CrossAttention) and m.fuse_kv())
-    print(f"    ✓ KV fused: {kv_count} attention layers")
-
     # Run over data
     assert (args.height % 16 == 0) and (
         args.width % 16
@@ -649,7 +518,7 @@ def run_inference(args: argparse.Namespace, gpu_num: int, gpu_no: int) -> None:
             sample_save_dir = f'{video_save_dir}/wm/{fs}'
             os.makedirs(sample_save_dir, exist_ok=True)
             # For collecting interaction videos
-            wm_latent = []
+            wm_video = []
             # Initialize observation queues
             cond_obs_queues = {
                 "observation.images.top":
@@ -705,7 +574,7 @@ def run_inference(args: argparse.Namespace, gpu_num: int, gpu_no: int) -> None:
 
                 # Use world-model in policy to generate action
                 print(f'>>> Step {itr}: generating actions ...')
-                pred_videos_0, pred_actions, _, _ = image_guided_synthesis_sim_mode(
+                pred_videos_0, pred_actions, _ = image_guided_synthesis_sim_mode(
                     model,
                     sample['instruction'],
                     observation,
@@ -718,8 +587,7 @@ def run_inference(args: argparse.Namespace, gpu_num: int, gpu_no: int) -> None:
                     fs=model_input_fs,
                     timestep_spacing=args.timestep_spacing,
                     guidance_rescale=args.guidance_rescale,
-                    sim_mode=False,
+                    sim_mode=False)
-                    decode_video=not args.fast_policy_no_decode)
 
                 # Update future actions in the observation queues
                 for idx in range(len(pred_actions[0])):
@@ -747,7 +615,7 @@ def run_inference(args: argparse.Namespace, gpu_num: int, gpu_no: int) -> None:
 
                 # Interaction with the world-model
                 print(f'>>> Step {itr}: interacting with world model ...')
-                pred_videos_1, _, pred_states, wm_samples = image_guided_synthesis_sim_mode(
+                pred_videos_1, _, pred_states = image_guided_synthesis_sim_mode(
                     model,
                     "",
                     observation,
@@ -760,16 +628,12 @@ def run_inference(args: argparse.Namespace, gpu_num: int, gpu_no: int) -> None:
                     fs=model_input_fs,
                     text_input=False,
                     timestep_spacing=args.timestep_spacing,
-                    guidance_rescale=args.guidance_rescale,
+                    guidance_rescale=args.guidance_rescale)
-                    decode_video=False)
-
-                # Decode only the last frame for CLIP embedding in next iteration
-                last_frame_pixel = model.decode_first_stage(wm_samples[:, :, -1:, :, :])
 
                 for idx in range(args.exe_steps):
                     observation = {
                         'observation.images.top':
-                        last_frame_pixel[0, :, 0:1].permute(1, 0, 2, 3),
+                        pred_videos_1[0][:, idx:idx + 1].permute(1, 0, 2, 3),
                         'observation.state':
                         torch.zeros_like(pred_states[0][idx:idx + 1]) if
                         args.zero_pred_state else pred_states[0][idx:idx + 1],
@@ -780,31 +644,42 @@ def run_inference(args: argparse.Namespace, gpu_num: int, gpu_no: int) -> None:
                     cond_obs_queues = populate_queues(cond_obs_queues,
                                                       observation)
 
-                # Save the imagen videos for decision-making (async)
+                # Save the imagen videos for decision-making
-                if pred_videos_0 is not None:
                 sample_tag = f"{args.dataset}-vid{sample['videoid']}-dm-fs-{fs}/itr-{itr}"
-                    log_to_tensorboard_async(writer,
+                log_to_tensorboard(writer,
                                    pred_videos_0,
                                    sample_tag,
                                    fps=args.save_fps)
+                # Save videos environment changes via world-model interaction
+                sample_tag = f"{args.dataset}-vid{sample['videoid']}-wd-fs-{fs}/itr-{itr}"
+                log_to_tensorboard(writer,
+                                   pred_videos_1,
+                                   sample_tag,
+                                   fps=args.save_fps)
+
+                # Save the imagen videos for decision-making
+                sample_video_file = f'{video_save_dir}/dm/{fs}/itr-{itr}.mp4'
+                save_results(pred_videos_0.cpu(),
+                             sample_video_file,
+                             fps=args.save_fps)
+                # Save videos environment changes via world-model interaction
+                sample_video_file = f'{video_save_dir}/wm/{fs}/itr-{itr}.mp4'
+                save_results(pred_videos_1.cpu(),
+                             sample_video_file,
+                             fps=args.save_fps)
 
                 print('>' * 24)
-                # Store raw latent for deferred decode
+                # Collect the result of world-model interactions
-                wm_latent.append(wm_samples[:, :, :args.exe_steps].cpu())
+                wm_video.append(pred_videos_1[:, :, :args.exe_steps].cpu())
 
-            # Deferred decode: batch decode all stored latents
+            full_video = torch.cat(wm_video, dim=2)
-            full_latent = torch.cat(wm_latent, dim=2).to(device)
-            full_video = model.decode_first_stage(full_latent).cpu()
             sample_tag = f"{args.dataset}-vid{sample['videoid']}-wd-fs-{fs}/full"
-            log_to_tensorboard_async(writer,
+            log_to_tensorboard(writer,
                                full_video,
                                sample_tag,
                                fps=args.save_fps)
             sample_full_video_file = f"{video_save_dir}/../{sample['videoid']}_full_fs{fs}.mp4"
-            save_results_async(full_video, sample_full_video_file, fps=args.save_fps)
+            save_results(full_video, sample_full_video_file, fps=args.save_fps)
-
-    # Wait for all async I/O to complete
-    _flush_io()
 
 
 def get_parser():
@@ -919,11 +794,6 @@ def get_parser():
                         action='store_true',
                         default=False,
                         help="not using the predicted states as comparison")
-    parser.add_argument(
-        "--fast_policy_no_decode",
-        action='store_true',
-        default=True,
-        help="Speed mode: policy pass only predicts actions, skip policy video decode/log/save.")
     parser.add_argument("--save_fps",
                         type=int,
                         default=8,

scripts/trainer.py

@@ -11,9 +11,6 @@ from unifolm_wma.utils.utils import instantiate_from_config
 from unifolm_wma.utils.train import get_trainer_callbacks, get_trainer_logger, get_trainer_strategy
 from unifolm_wma.utils.train import set_logger, init_workspace, load_checkpoints, get_num_parameters
 
-torch.backends.cuda.matmul.allow_tf32 = True
-torch.backends.cudnn.allow_tf32 = True
-
 
 def get_parser(**parser_kwargs):
     parser = argparse.ArgumentParser(**parser_kwargs)

src/unifolm_wma/models/ddpms.py

@@ -988,7 +988,7 @@ class LatentDiffusion(DDPM):
 
     def instantiate_cond_stage(self, config: OmegaConf) -> None:
         """
-        Build the conditioning stage model. Frozen models are converted to FP16.
+        Build the conditioning stage model.
 
         Args:
             config: OmegaConf config describing the conditioning model to instantiate.
@@ -1000,7 +1000,6 @@ class LatentDiffusion(DDPM):
             self.cond_stage_model.train = disabled_train
             for param in self.cond_stage_model.parameters():
                 param.requires_grad = False
-            self.cond_stage_model.half()
         else:
             model = instantiate_from_config(config)
             self.cond_stage_model = model
@@ -1015,7 +1014,6 @@ class LatentDiffusion(DDPM):
         Returns:
             Conditioning embedding as a tensor (shape depends on cond model).
         """
-        with torch.cuda.amp.autocast(dtype=torch.float16):
         if self.cond_stage_forward is None:
             if hasattr(self.cond_stage_model, 'encode') and callable(
                     self.cond_stage_model.encode):
@@ -1959,7 +1957,6 @@ class LatentVisualDiffusion(LatentDiffusion):
             self.image_proj_model.train = disabled_train
             for param in self.image_proj_model.parameters():
                 param.requires_grad = False
-            self.image_proj_model.half()
 
     def _init_embedder(self, config: OmegaConf, freeze: bool = True) -> None:
         """
@@ -1975,7 +1972,6 @@ class LatentVisualDiffusion(LatentDiffusion):
             self.embedder.train = disabled_train
             for param in self.embedder.parameters():
                 param.requires_grad = False
-            self.embedder.half()
 
     def init_normalizers(self, normalize_config: OmegaConf,
                          dataset_stats: Mapping[str, Any]) -> None:
@@ -2179,7 +2175,6 @@ class LatentVisualDiffusion(LatentDiffusion):
             (random_num < 3 * self.uncond_prob).float(), "n -> n 1 1 1")
 
         cond_img = input_mask * img
-        with torch.cuda.amp.autocast(dtype=torch.float16):
         cond_img_emb = self.embedder(cond_img)
         cond_img_emb = self.image_proj_model(cond_img_emb)
 
@@ -2196,7 +2191,6 @@ class LatentVisualDiffusion(LatentDiffusion):
                                       repeat=z.shape[2])
             cond["c_concat"] = [img_cat_cond]
 
-        with torch.cuda.amp.autocast(dtype=torch.float16):
         cond_action = self.action_projector(action)
         cond_action_emb = self.agent_action_pos_emb + cond_action
         # Get conditioning states
@@ -2463,17 +2457,7 @@ class DiffusionWrapper(pl.LightningModule):
         Returns:
             Output from the inner diffusion model (tensor or tuple, depending on the model).
         """
-        with torch.cuda.amp.autocast(dtype=torch.float16):
-            return self._forward_impl(x, x_action, x_state, t,
-                                      c_concat, c_crossattn, c_crossattn_action,
-                                      c_adm, s, mask, **kwargs)
 
-    def _forward_impl(
-        self,
-        x, x_action, x_state, t,
-        c_concat=None, c_crossattn=None, c_crossattn_action=None,
-        c_adm=None, s=None, mask=None, **kwargs,
-    ):
         if self.conditioning_key is None:
             out = self.diffusion_model(x, t)
         elif self.conditioning_key == 'concat':

src/unifolm_wma/models/diffusion_head/conditional_unet1d.py

@@ -501,10 +501,6 @@ class ConditionalUnet1D(nn.Module):
         self.last_frame_only = last_frame_only
         self.horizon = horizon
 
-        # Context precomputation cache
-        self._global_cond_cache_enabled = False
-        self._global_cond_cache = {}
-
     def forward(self,
                 sample: torch.Tensor,
                 timestep: Union[torch.Tensor, float, int],
@@ -534,10 +530,6 @@ class ConditionalUnet1D(nn.Module):
         B, T, D = sample.shape
         if self.use_linear_act_proj:
             sample = self.proj_in_action(sample.unsqueeze(-1))
-            _gc_key = (cond['image'].data_ptr(), cond['agent_pos'].data_ptr())
-            if self._global_cond_cache_enabled and _gc_key in self._global_cond_cache:
-                global_cond = self._global_cond_cache[_gc_key]
-            else:
             global_cond = self.obs_encoder(cond)
             global_cond = rearrange(global_cond,
                                     '(b t) d -> b 1 (t d)',
@@ -546,8 +538,6 @@ class ConditionalUnet1D(nn.Module):
             global_cond = repeat(global_cond,
                                  'b c d -> b (repeat c) d',
                                  repeat=T)
-                if self._global_cond_cache_enabled:
-                    self._global_cond_cache[_gc_key] = global_cond
         else:
             sample = einops.rearrange(sample, 'b h t -> b t h')
             sample = self.proj_in_horizon(sample)

src/unifolm_wma/models/samplers/ddim.py

@@ -6,8 +6,6 @@ from unifolm_wma.utils.diffusion import make_ddim_sampling_parameters, make_ddim
 from unifolm_wma.utils.common import noise_like
 from unifolm_wma.utils.common import extract_into_tensor
 from tqdm import tqdm
-from unifolm_wma.modules.attention import enable_cross_attn_kv_cache, disable_cross_attn_kv_cache
-from unifolm_wma.modules.networks.wma_model import enable_ctx_cache, disable_ctx_cache
 
 
 class DDIMSampler(object):
@@ -69,12 +67,11 @@ class DDIMSampler(object):
             ddim_timesteps=self.ddim_timesteps,
             eta=ddim_eta,
             verbose=verbose)
-        # Ensure tensors are on correct device for efficient indexing
+        self.register_buffer('ddim_sigmas', ddim_sigmas)
-        self.register_buffer('ddim_sigmas', to_torch(torch.as_tensor(ddim_sigmas)))
+        self.register_buffer('ddim_alphas', ddim_alphas)
-        self.register_buffer('ddim_alphas', to_torch(torch.as_tensor(ddim_alphas)))
+        self.register_buffer('ddim_alphas_prev', ddim_alphas_prev)
-        self.register_buffer('ddim_alphas_prev', to_torch(torch.as_tensor(ddim_alphas_prev)))
         self.register_buffer('ddim_sqrt_one_minus_alphas',
-                             to_torch(torch.as_tensor(np.sqrt(1. - ddim_alphas))))
+                             np.sqrt(1. - ddim_alphas))
         sigmas_for_original_sampling_steps = ddim_eta * torch.sqrt(
             (1 - self.alphas_cumprod_prev) / (1 - self.alphas_cumprod) *
             (1 - self.alphas_cumprod / self.alphas_cumprod_prev))
@@ -244,13 +241,9 @@ class DDIMSampler(object):
 
         dp_ddim_scheduler_action.set_timesteps(len(timesteps))
         dp_ddim_scheduler_state.set_timesteps(len(timesteps))
-        ts = torch.empty((b, ), device=device, dtype=torch.long)
-        enable_cross_attn_kv_cache(self.model)
-        enable_ctx_cache(self.model)
-        try:
         for i, step in enumerate(iterator):
             index = total_steps - i - 1
-                ts.fill_(step)
+            ts = torch.full((b, ), step, device=device, dtype=torch.long)
 
             # Use mask to blend noised original latent (img_orig) & new sampled latent (img)
             if mask is not None:
@@ -305,9 +298,6 @@ class DDIMSampler(object):
                 intermediates['pred_x0'].append(pred_x0)
                 intermediates['x_inter_action'].append(action)
                 intermediates['x_inter_state'].append(state)
-        finally:
-            disable_cross_attn_kv_cache(self.model)
-            disable_ctx_cache(self.model)
 
         return img, action, state, intermediates
 
@@ -335,6 +325,10 @@ class DDIMSampler(object):
                       guidance_rescale=0.0,
                       **kwargs):
         b, *_, device = *x.shape, x.device
+        if x.dim() == 5:
+            is_video = True
+        else:
+            is_video = False
 
         if unconditional_conditioning is None or unconditional_guidance_scale == 1.:
             model_output, model_output_action, model_output_state = self.model.apply_model(
@@ -383,11 +377,17 @@ class DDIMSampler(object):
         sqrt_one_minus_alphas = self.model.sqrt_one_minus_alphas_cumprod if use_original_steps else self.ddim_sqrt_one_minus_alphas
         sigmas = self.ddim_sigmas_for_original_num_steps if use_original_steps else self.ddim_sigmas
 
-        # Use 0-d tensors directly (already on device); broadcasting handles shape
+        if is_video:
-        a_t = alphas[index]
+            size = (b, 1, 1, 1, 1)
-        a_prev = alphas_prev[index]
+        else:
-        sigma_t = sigmas[index]
+            size = (b, 1, 1, 1)
-        sqrt_one_minus_at = sqrt_one_minus_alphas[index]
+
+        a_t = torch.full(size, alphas[index], device=device)
+        a_prev = torch.full(size, alphas_prev[index], device=device)
+        sigma_t = torch.full(size, sigmas[index], device=device)
+        sqrt_one_minus_at = torch.full(size,
+                                       sqrt_one_minus_alphas[index],
+                                       device=device)
 
         if self.model.parameterization != "v":
             pred_x0 = (x - sqrt_one_minus_at * e_t) / a_t.sqrt()
@@ -395,8 +395,12 @@ class DDIMSampler(object):
             pred_x0 = self.model.predict_start_from_z_and_v(x, t, model_output)
 
         if self.model.use_dynamic_rescale:
-            scale_t = self.ddim_scale_arr[index]
+            scale_t = torch.full(size,
-            prev_scale_t = self.ddim_scale_arr_prev[index]
+                                 self.ddim_scale_arr[index],
+                                 device=device)
+            prev_scale_t = torch.full(size,
+                                      self.ddim_scale_arr_prev[index],
+                                      device=device)
             rescale = (prev_scale_t / scale_t)
             pred_x0 *= rescale
 

src/unifolm_wma/modules/attention.py

@@ -98,10 +98,6 @@ class CrossAttention(nn.Module):
         self.text_context_len = text_context_len
         self.agent_state_context_len = agent_state_context_len
         self.agent_action_context_len = agent_action_context_len
-        self._kv_cache = {}
-        self._kv_cache_enabled = False
-        self._kv_fused = False
-
         self.cross_attention_scale_learnable = cross_attention_scale_learnable
         if self.image_cross_attention:
             self.to_k_ip = nn.Linear(context_dim, inner_dim, bias=False)
@@ -118,27 +114,6 @@ class CrossAttention(nn.Module):
                 self.register_parameter('alpha_caa',
                                         nn.Parameter(torch.tensor(0.)))
 
-    def fuse_kv(self):
-        """Fuse to_k/to_v into to_kv (2 Linear → 1). Works for all layers."""
-        k_w = self.to_k.weight  # (inner_dim, context_dim)
-        v_w = self.to_v.weight
-        self.to_kv = nn.Linear(k_w.shape[1], k_w.shape[0] * 2, bias=False)
-        self.to_kv.weight = nn.Parameter(torch.cat([k_w, v_w], dim=0))
-        del self.to_k, self.to_v
-        if self.image_cross_attention:
-            for suffix in ('_ip', '_as', '_aa'):
-                k_attr = f'to_k{suffix}'
-                v_attr = f'to_v{suffix}'
-                kw = getattr(self, k_attr).weight
-                vw = getattr(self, v_attr).weight
-                fused = nn.Linear(kw.shape[1], kw.shape[0] * 2, bias=False)
-                fused.weight = nn.Parameter(torch.cat([kw, vw], dim=0))
-                setattr(self, f'to_kv{suffix}', fused)
-                delattr(self, k_attr)
-                delattr(self, v_attr)
-        self._kv_fused = True
-        return True
-
     def forward(self, x, context=None, mask=None):
         spatial_self_attn = (context is None)
         k_ip, v_ip, out_ip = None, None, None
@@ -165,12 +140,6 @@ class CrossAttention(nn.Module):
                                     self.agent_action_context_len +
                                     self.text_context_len:, :]
 
-            if self._kv_fused:
-                k, v = self.to_kv(context_ins).chunk(2, dim=-1)
-                k_ip, v_ip = self.to_kv_ip(context_image).chunk(2, dim=-1)
-                k_as, v_as = self.to_kv_as(context_agent_state).chunk(2, dim=-1)
-                k_aa, v_aa = self.to_kv_aa(context_agent_action).chunk(2, dim=-1)
-            else:
             k = self.to_k(context_ins)
             v = self.to_v(context_ins)
             k_ip = self.to_k_ip(context_image)
@@ -182,9 +151,6 @@ class CrossAttention(nn.Module):
         else:
             if not spatial_self_attn:
                 context = context[:, :self.text_context_len, :]
-            if self._kv_fused:
-                k, v = self.to_kv(context).chunk(2, dim=-1)
-            else:
             k = self.to_k(context)
             v = self.to_v(context)
 
@@ -270,78 +236,33 @@ class CrossAttention(nn.Module):
         k_ip, v_ip, out_ip = None, None, None
         k_as, v_as, out_as = None, None, None
         k_aa, v_aa, out_aa = None, None, None
-        attn_mask_aa = None
 
-        h = self.heads
         q = self.to_q(x)
         context = default(context, x)
 
-        b, _, _ = q.shape
+        if self.image_cross_attention and not spatial_self_attn:
-        q = q.unsqueeze(3).reshape(b, q.shape[1], h, self.dim_head).permute(0, 2, 1, 3).reshape(b * h, q.shape[1], self.dim_head).contiguous()
-
-        def _reshape_kv(t):
-            return t.unsqueeze(3).reshape(b, t.shape[1], h, self.dim_head).permute(0, 2, 1, 3).reshape(b * h, t.shape[1], self.dim_head).contiguous()
-
-        use_cache = self._kv_cache_enabled and not spatial_self_attn
-        cache_hit = use_cache and len(self._kv_cache) > 0
-
-        if cache_hit:
-            k = self._kv_cache['k']
-            v = self._kv_cache['v']
-            k_ip = self._kv_cache.get('k_ip')
-            v_ip = self._kv_cache.get('v_ip')
-            k_as = self._kv_cache.get('k_as')
-            v_as = self._kv_cache.get('v_as')
-            k_aa = self._kv_cache.get('k_aa')
-            v_aa = self._kv_cache.get('v_aa')
-            attn_mask_aa = self._kv_cache.get('attn_mask_aa')
-        elif self.image_cross_attention and not spatial_self_attn:
             if context.shape[1] == self.text_context_len + self.video_length:
                 context_ins, context_image = context[:, :self.text_context_len, :], context[:,self.text_context_len:, :]
-                if self._kv_fused:
-                    k, v = self.to_kv(context).chunk(2, dim=-1)
-                    k_ip, v_ip = self.to_kv_ip(context_image).chunk(2, dim=-1)
-                else:
                 k = self.to_k(context)
                 v = self.to_v(context)
                 k_ip = self.to_k_ip(context_image)
                 v_ip = self.to_v_ip(context_image)
-                k, v = map(_reshape_kv, (k, v))
-                k_ip, v_ip = map(_reshape_kv, (k_ip, v_ip))
-                if use_cache:
-                    self._kv_cache = {'k': k, 'v': v, 'k_ip': k_ip, 'v_ip': v_ip}
             elif context.shape[1] == self.agent_state_context_len + self.text_context_len + self.video_length:
                 context_agent_state = context[:, :self.agent_state_context_len, :]
                 context_ins = context[:, self.agent_state_context_len:self.agent_state_context_len+self.text_context_len, :]
                 context_image = context[:, self.agent_state_context_len+self.text_context_len:, :]
-                if self._kv_fused:
-                    k, v = self.to_kv(context_ins).chunk(2, dim=-1)
-                    k_ip, v_ip = self.to_kv_ip(context_image).chunk(2, dim=-1)
-                    k_as, v_as = self.to_kv_as(context_agent_state).chunk(2, dim=-1)
-                else:
                 k = self.to_k(context_ins)
                 v = self.to_v(context_ins)
                 k_ip = self.to_k_ip(context_image)
                 v_ip = self.to_v_ip(context_image)
                 k_as = self.to_k_as(context_agent_state)
                 v_as = self.to_v_as(context_agent_state)
-                k, v = map(_reshape_kv, (k, v))
-                k_ip, v_ip = map(_reshape_kv, (k_ip, v_ip))
-                k_as, v_as = map(_reshape_kv, (k_as, v_as))
-                if use_cache:
-                    self._kv_cache = {'k': k, 'v': v, 'k_ip': k_ip, 'v_ip': v_ip, 'k_as': k_as, 'v_as': v_as}
             else:
                 context_agent_state = context[:, :self.agent_state_context_len, :]
                 context_agent_action = context[:, self.agent_state_context_len:self.agent_state_context_len+self.agent_action_context_len, :]
                 context_ins = context[:, self.agent_state_context_len+self.agent_action_context_len:self.agent_state_context_len+self.agent_action_context_len+self.text_context_len, :]
                 context_image = context[:, self.agent_state_context_len+self.agent_action_context_len+self.text_context_len:, :]
 
-                if self._kv_fused:
-                    k, v = self.to_kv(context_ins).chunk(2, dim=-1)
-                    k_ip, v_ip = self.to_kv_ip(context_image).chunk(2, dim=-1)
-                    k_as, v_as = self.to_kv_as(context_agent_state).chunk(2, dim=-1)
-                    k_aa, v_aa = self.to_kv_aa(context_agent_action).chunk(2, dim=-1)
-                else:
                 k = self.to_k(context_ins)
                 v = self.to_v(context_ins)
                 k_ip = self.to_k_ip(context_image)
@@ -351,81 +272,98 @@ class CrossAttention(nn.Module):
                 k_aa = self.to_k_aa(context_agent_action)
                 v_aa = self.to_v_aa(context_agent_action)
 
-                k, v = map(_reshape_kv, (k, v))
+                attn_mask_aa = self._get_attn_mask_aa(x.shape[0],
-                k_ip, v_ip = map(_reshape_kv, (k_ip, v_ip))
-                k_as, v_as = map(_reshape_kv, (k_as, v_as))
-                k_aa, v_aa = map(_reshape_kv, (k_aa, v_aa))
-
-                attn_mask_aa_raw = self._get_attn_mask_aa(x.shape[0],
                                                       q.shape[1],
                                                       k_aa.shape[1],
-                                                          block_size=16,
+                                                      block_size=16).to(k_aa.device)
-                                                          device=k_aa.device)
-                attn_mask_aa = attn_mask_aa_raw.unsqueeze(1).repeat(1, h, 1, 1).reshape(
-                    b * h, attn_mask_aa_raw.shape[1], attn_mask_aa_raw.shape[2]).to(q.dtype)
-
-                if use_cache:
-                    self._kv_cache = {
-                        'k': k, 'v': v, 'k_ip': k_ip, 'v_ip': v_ip,
-                        'k_as': k_as, 'v_as': v_as, 'k_aa': k_aa, 'v_aa': v_aa,
-                        'attn_mask_aa': attn_mask_aa,
-                    }
         else:
             if not spatial_self_attn:
                 assert 1 > 2, ">>> ERROR: you should never go into here ..."
                 context = context[:, :self.text_context_len, :]
-            if self._kv_fused:
-                k, v = self.to_kv(context).chunk(2, dim=-1)
-            else:
             k = self.to_k(context)
             v = self.to_v(context)
-            k, v = map(_reshape_kv, (k, v))
+
-            if use_cache:
+        b, _, _ = q.shape
-                self._kv_cache = {'k': k, 'v': v}
+        q = q.unsqueeze(3).reshape(b, q.shape[1], self.heads, self.dim_head).permute(0, 2, 1, 3).reshape(b * self.heads, q.shape[1], self.dim_head).contiguous()
         if k is not None:
+            k, v = map(
+                lambda t: t.unsqueeze(3).reshape(b, t.shape[
+                    1], self.heads, self.dim_head).permute(0, 2, 1, 3).reshape(
+                        b * self.heads, t.shape[1], self.dim_head).contiguous(),
+                (k, v),
+            )
             out = xformers.ops.memory_efficient_attention(q,
                                                           k,
                                                           v,
                                                           attn_bias=None,
                                                           op=None)
             out = (out.unsqueeze(0).reshape(
-                b, h, out.shape[1],
+                b, self.heads, out.shape[1],
                 self.dim_head).permute(0, 2, 1,
                                        3).reshape(b, out.shape[1],
-                                                  h * self.dim_head))
+                                                  self.heads * self.dim_head))
 
         if k_ip is not None:
+            # For image cross-attention
+            k_ip, v_ip = map(
+                lambda t: t.unsqueeze(3).reshape(b, t.shape[
+                    1], self.heads, self.dim_head).permute(0, 2, 1, 3).reshape(
+                        b * self.heads, t.shape[1], self.dim_head).contiguous(
+                        ),
+                (k_ip, v_ip),
+            )
             out_ip = xformers.ops.memory_efficient_attention(q,
                                                              k_ip,
                                                              v_ip,
                                                              attn_bias=None,
                                                              op=None)
             out_ip = (out_ip.unsqueeze(0).reshape(
-                b, h, out_ip.shape[1],
+                b, self.heads, out_ip.shape[1],
                 self.dim_head).permute(0, 2, 1,
                                        3).reshape(b, out_ip.shape[1],
-                                                  h * self.dim_head))
+                                                  self.heads * self.dim_head))
 
         if k_as is not None:
+            # For agent state cross-attention
+            k_as, v_as = map(
+                lambda t: t.unsqueeze(3).reshape(b, t.shape[
+                    1], self.heads, self.dim_head).permute(0, 2, 1, 3).reshape(
+                        b * self.heads, t.shape[1], self.dim_head).contiguous(
+                        ),
+                (k_as, v_as),
+            )
             out_as = xformers.ops.memory_efficient_attention(q,
                                                              k_as,
                                                              v_as,
                                                              attn_bias=None,
                                                              op=None)
             out_as = (out_as.unsqueeze(0).reshape(
-                b, h, out_as.shape[1],
+                b, self.heads, out_as.shape[1],
                 self.dim_head).permute(0, 2, 1,
                                        3).reshape(b, out_as.shape[1],
-                                                  h * self.dim_head))
+                                                  self.heads * self.dim_head))
-
         if k_aa is not None:
+            # For agent action cross-attention
+            k_aa, v_aa = map(
+                lambda t: t.unsqueeze(3).reshape(b, t.shape[
+                    1], self.heads, self.dim_head).permute(0, 2, 1, 3).reshape(
+                        b * self.heads, t.shape[1], self.dim_head).contiguous(
+                        ),
+                (k_aa, v_aa),
+            )
+
+            attn_mask_aa = attn_mask_aa.unsqueeze(1).repeat(1,self.heads,1,1).reshape(
+                    b * self.heads, attn_mask_aa.shape[1], attn_mask_aa.shape[2])
+            attn_mask_aa = attn_mask_aa.to(q.dtype)
+
             out_aa = xformers.ops.memory_efficient_attention(
                 q, k_aa, v_aa, attn_bias=attn_mask_aa, op=None)
+
             out_aa = (out_aa.unsqueeze(0).reshape(
-                b, h, out_aa.shape[1],
+                b, self.heads, out_aa.shape[1],
                 self.dim_head).permute(0, 2, 1,
                                        3).reshape(b, out_aa.shape[1],
-                                                  h * self.dim_head))
+                                                  self.heads * self.dim_head))
         if exists(mask):
             raise NotImplementedError
 
@@ -448,43 +386,17 @@ class CrossAttention(nn.Module):
 
         return self.to_out(out)
 
-    def _get_attn_mask_aa(self, b, l1, l2, block_size=16, device=None):
+    def _get_attn_mask_aa(self, b, l1, l2, block_size=16):
-        cache_key = (b, l1, l2, block_size)
-        if hasattr(self, '_attn_mask_aa_cache_key') and self._attn_mask_aa_cache_key == cache_key:
-            cached = self._attn_mask_aa_cache
-            if device is not None and cached.device != torch.device(device):
-                cached = cached.to(device)
-                self._attn_mask_aa_cache = cached
-            return cached
-
-        target_device = device if device is not None else 'cpu'
         num_token = l2 // block_size
-        start_positions = ((torch.arange(b, device=target_device) % block_size) + 1) * num_token
+        start_positions = ((torch.arange(b) % block_size) + 1) * num_token
-        col_indices = torch.arange(l2, device=target_device)
+        col_indices = torch.arange(l2)
         mask_2d = col_indices.unsqueeze(0) >= start_positions.unsqueeze(1)
         mask = mask_2d.unsqueeze(1).expand(b, l1, l2)
-        attn_mask = torch.zeros(b, l1, l2, dtype=torch.float, device=target_device)
+        attn_mask = torch.zeros_like(mask, dtype=torch.float)
         attn_mask[mask] = float('-inf')
-
-        self._attn_mask_aa_cache_key = cache_key
-        self._attn_mask_aa_cache = attn_mask
         return attn_mask
 
 
-def enable_cross_attn_kv_cache(module):
-    for m in module.modules():
-        if isinstance(m, CrossAttention):
-            m._kv_cache_enabled = True
-            m._kv_cache = {}
-
-
-def disable_cross_attn_kv_cache(module):
-    for m in module.modules():
-        if isinstance(m, CrossAttention):
-            m._kv_cache_enabled = False
-            m._kv_cache = {}
-
-
 class BasicTransformerBlock(nn.Module):
 
     def __init__(self,

src/unifolm_wma/modules/networks/wma_model.py

@@ -685,21 +685,6 @@ class WMAModel(nn.Module):
         self.action_token_projector = instantiate_from_config(
             stem_process_config)
 
-        # Context precomputation cache
-        self._ctx_cache_enabled = False
-        self._ctx_cache = {}
-        # Reusable CUDA stream for parallel state_unet / action_unet
-        self._state_stream = torch.cuda.Stream()
-
-    def __getstate__(self):
-        state = self.__dict__.copy()
-        state.pop('_state_stream', None)
-        return state
-
-    def __setstate__(self, state):
-        self.__dict__.update(state)
-        self._state_stream = torch.cuda.Stream()
-
     def forward(self,
                 x: Tensor,
                 x_action: Tensor,
@@ -735,10 +720,6 @@ class WMAModel(nn.Module):
                                    repeat_only=False).type(x.dtype)
         emb = self.time_embed(t_emb)
 
-        _ctx_key = context.data_ptr()
-        if self._ctx_cache_enabled and _ctx_key in self._ctx_cache:
-            context = self._ctx_cache[_ctx_key]
-        else:
         bt, l_context, _ = context.shape
         if self.base_model_gen_only:
             assert l_context == 77 + self.n_obs_steps * 16, ">>> ERROR Context dim 1 ..."  ## NOTE HANDCODE
@@ -791,8 +772,6 @@ class WMAModel(nn.Module):
                     context_img
                 ],
                                     dim=1)
-            if self._ctx_cache_enabled:
-                self._ctx_cache[_ctx_key] = context
 
         emb = emb.repeat_interleave(repeats=t, dim=0)
 
@@ -853,45 +832,17 @@ class WMAModel(nn.Module):
 
         if not self.base_model_gen_only:
             ba, _, _ = x_action.shape
-            ts_state = timesteps[:ba] if b > 1 else timesteps
-            # Run action_unet and state_unet in parallel via CUDA streams
-            s_stream = self._state_stream
-            s_stream.wait_stream(torch.cuda.current_stream())
-            with torch.cuda.stream(s_stream):
-                s_y = self.state_unet(x_state, ts_state, hs_a,
-                                      context_action[:2], **kwargs)
             a_y = self.action_unet(x_action, timesteps[:ba], hs_a,
                                    context_action[:2], **kwargs)
-            torch.cuda.current_stream().wait_stream(s_stream)
+            # Predict state
+            if b > 1:
+                s_y = self.state_unet(x_state, timesteps[:ba], hs_a,
+                                      context_action[:2], **kwargs)
+            else:
+                s_y = self.state_unet(x_state, timesteps, hs_a,
+                                      context_action[:2], **kwargs)
         else:
             a_y = torch.zeros_like(x_action)
             s_y = torch.zeros_like(x_state)
 
         return y, a_y, s_y
-
-
-def enable_ctx_cache(model):
-    """Enable context precomputation cache on WMAModel and its action/state UNets."""
-    for m in model.modules():
-        if isinstance(m, WMAModel):
-            m._ctx_cache_enabled = True
-            m._ctx_cache = {}
-    # conditional_unet1d cache
-    from unifolm_wma.models.diffusion_head.conditional_unet1d import ConditionalUnet1D
-    for m in model.modules():
-        if isinstance(m, ConditionalUnet1D):
-            m._global_cond_cache_enabled = True
-            m._global_cond_cache = {}
-
-
-def disable_ctx_cache(model):
-    """Disable and clear context precomputation cache."""
-    for m in model.modules():
-        if isinstance(m, WMAModel):
-            m._ctx_cache_enabled = False
-            m._ctx_cache = {}
-    from unifolm_wma.models.diffusion_head.conditional_unet1d import ConditionalUnet1D
-    for m in model.modules():
-        if isinstance(m, ConditionalUnet1D):
-            m._global_cond_cache_enabled = False
-            m._global_cond_cache = {}

unitree_g1_pack_camera/case1/output.log

@@ -1,16 +1,21 @@
-2026-02-11 19:14:09.599811: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 19:49:03.885238: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 19:14:09.649058: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 19:49:03.934263: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 19:14:09.649103: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 19:49:03.934309: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 19:14:09.650392: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 19:49:03.935622: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 19:14:09.657857: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 19:49:03.943041: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 19:14:10.584900: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 19:49:04.852993: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,46 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/11 [00:00<?, ?it/s]
   0%|          | 0/11 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 18%|█▊        | 2/11 [00:45<03:22, 22.52s/it]
- 27%|██▋       | 3/11 [01:07<03:00, 22.52s/it]
- 36%|███▋      | 4/11 [01:30<02:38, 22.60s/it]
- 45%|████▌     | 5/11 [01:53<02:16, 22.70s/it]
- 55%|█████▍    | 6/11 [02:16<01:53, 22.74s/it]
- 64%|██████▎   | 7/11 [02:38<01:31, 22.76s/it]
- 73%|███████▎  | 8/11 [03:01<01:08, 22.77s/it]
- 82%|████████▏ | 9/11 [03:24<00:45, 22.76s/it]
- 91%|█████████ | 10/11 [03:47<00:22, 22.76s/it]
-100%|██████████| 11/11 [04:09<00:00, 22.77s/it]
-100%|██████████| 11/11 [04:09<00:00, 22.73s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 4: generating actions ...
->>> Step 4: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...
->>> Step 5: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 6: generating actions ...
->>> Step 6: interacting with world model ...
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -117,7 +89,39 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+  9%|▉         | 1/11 [01:12<12:09, 72.95s/it]
+ 18%|█▊        | 2/11 [02:26<10:58, 73.19s/it]
+ 27%|██▋       | 3/11 [03:39<09:45, 73.21s/it]
+ 36%|███▋      | 4/11 [04:52<08:32, 73.21s/it]
+ 45%|████▌     | 5/11 [06:05<07:19, 73.22s/it]
+ 55%|█████▍    | 6/11 [07:19<06:06, 73.20s/it]
+ 64%|██████▎   | 7/11 [08:32<04:52, 73.16s/it]
+ 73%|███████▎  | 8/11 [09:45<03:39, 73.14s/it]
+ 82%|████████▏ | 9/11 [10:58<02:26, 73.13s/it]
+ 91%|█████████ | 10/11 [12:11<01:13, 73.15s/it]
+100%|██████████| 11/11 [13:24<00:00, 73.18s/it]
+100%|██████████| 11/11 [13:24<00:00, 73.17s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 4: generating actions ...
+>>> Step 4: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 5: generating actions ...
+>>> Step 5: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 6: generating actions ...
+>>> Step 6: interacting with world model ...
 >>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing PsdImagePlugin
+>>> Step 7: generating actions ...
-DEBUG:PIL.Image:Importing QoiImagePlugin
+>>> Step 7: interacting with world model ...
-DEBUG:PIL.Image:Importing SgiImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>

unitree_g1_pack_camera/case1/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_g1_pack_camera/case1/unitree_g1_pack_camera_case1.mp4",
     "pred_video": "unitree_g1_pack_camera/case1/output/inference/0_full_fs6.mp4",
-    "psnr": 32.340256576190384
+    "psnr": 35.615362167470806
 }

unitree_g1_pack_camera/case1/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_g1_pack_camera"
         --n_iter 11 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_g1_pack_camera/case2/output.log

@@ -1,16 +1,21 @@
-2026-02-11 17:41:30.163933: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 20:04:06.049535: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 17:41:30.213409: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 20:04:06.099186: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 17:41:30.213453: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 20:04:06.099232: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 17:41:30.214760: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 20:04:06.100544: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 17:41:30.222233: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 20:04:06.108023: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 17:41:31.146811: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 20:04:07.025500: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,46 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/11 [00:00<?, ?it/s]
   0%|          | 0/11 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 18%|█▊        | 2/11 [00:46<03:26, 23.00s/it]
- 27%|██▋       | 3/11 [01:08<03:03, 22.93s/it]
- 36%|███▋      | 4/11 [01:31<02:40, 22.88s/it]
- 45%|████▌     | 5/11 [01:54<02:17, 22.86s/it]
- 55%|█████▍    | 6/11 [02:17<01:54, 22.84s/it]
- 64%|██████▎   | 7/11 [02:40<01:31, 22.82s/it]
- 73%|███████▎  | 8/11 [03:02<01:08, 22.80s/it]
- 82%|████████▏ | 9/11 [03:25<00:45, 22.78s/it]
- 91%|█████████ | 10/11 [03:48<00:22, 22.77s/it]
-100%|██████████| 11/11 [04:11<00:00, 22.76s/it]
-100%|██████████| 11/11 [04:11<00:00, 22.83s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 4: generating actions ...
->>> Step 4: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...
->>> Step 5: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 6: generating actions ...
->>> Step 6: interacting with world model ...
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -117,7 +89,39 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+  9%|▉         | 1/11 [01:14<12:22, 74.22s/it]
+ 18%|█▊        | 2/11 [02:28<11:09, 74.33s/it]
+ 27%|██▋       | 3/11 [03:42<09:54, 74.32s/it]
+ 36%|███▋      | 4/11 [04:57<08:40, 74.32s/it]
+ 45%|████▌     | 5/11 [06:11<07:25, 74.28s/it]
+ 55%|█████▍    | 6/11 [07:25<06:10, 74.19s/it]
+ 64%|██████▎   | 7/11 [08:39<04:56, 74.11s/it]
+ 73%|███████▎  | 8/11 [09:53<03:42, 74.07s/it]
+ 82%|████████▏ | 9/11 [11:07<02:28, 74.06s/it]
+ 91%|█████████ | 10/11 [12:21<01:14, 74.01s/it]
+100%|██████████| 11/11 [13:35<00:00, 73.98s/it]
+100%|██████████| 11/11 [13:35<00:00, 74.12s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 4: generating actions ...
+>>> Step 4: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 5: generating actions ...
+>>> Step 5: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 6: generating actions ...
+>>> Step 6: interacting with world model ...
 >>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing PsdImagePlugin
+>>> Step 7: generating actions ...
-DEBUG:PIL.Image:Importing QoiImagePlugin
+>>> Step 7: interacting with world model ...
-DEBUG:PIL.Image:Importing SgiImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>

unitree_g1_pack_camera/case2/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_g1_pack_camera/case2/unitree_g1_pack_camera_case2.mp4",
     "pred_video": "unitree_g1_pack_camera/case2/output/inference/50_full_fs6.mp4",
-    "psnr": 37.49178506869336
+    "psnr": 34.61979248212279
 }

unitree_g1_pack_camera/case2/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_g1_pack_camera"
         --n_iter 11 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_g1_pack_camera/case3/output.log

@@ -1,16 +1,21 @@
-2026-02-11 17:46:20.925463: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 20:19:19.271045: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 17:46:20.976293: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 20:19:19.320688: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 17:46:20.976338: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 20:19:19.320734: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 17:46:20.977650: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 20:19:19.322059: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 17:46:20.985133: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 20:19:19.329606: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 17:46:21.909964: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 20:19:20.248938: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,46 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/11 [00:00<?, ?it/s]
   0%|          | 0/11 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 18%|█▊        | 2/11 [00:46<03:27, 23.07s/it]
- 27%|██▋       | 3/11 [01:09<03:03, 22.99s/it]
- 36%|███▋      | 4/11 [01:32<02:40, 22.94s/it]
- 45%|████▌     | 5/11 [01:54<02:17, 22.90s/it]
- 55%|█████▍    | 6/11 [02:17<01:54, 22.87s/it]
- 64%|██████▎   | 7/11 [02:40<01:31, 22.85s/it]
- 73%|███████▎  | 8/11 [03:03<01:08, 22.83s/it]
- 82%|████████▏ | 9/11 [03:26<00:45, 22.81s/it]
- 91%|█████████ | 10/11 [03:48<00:22, 22.78s/it]
-100%|██████████| 11/11 [04:11<00:00, 22.76s/it]
-100%|██████████| 11/11 [04:11<00:00, 22.86s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 4: generating actions ...
->>> Step 4: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...
->>> Step 5: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 6: generating actions ...
->>> Step 6: interacting with world model ...
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -117,7 +89,39 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+  9%|▉         | 1/11 [01:14<12:22, 74.28s/it]
+ 18%|█▊        | 2/11 [02:28<11:09, 74.38s/it]
+ 27%|██▋       | 3/11 [03:43<09:55, 74.45s/it]
+ 36%|███▋      | 4/11 [04:57<08:41, 74.43s/it]
+ 45%|████▌     | 5/11 [06:11<07:25, 74.25s/it]
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+ 64%|██████▎   | 7/11 [08:40<04:57, 74.26s/it]
+ 73%|███████▎  | 8/11 [09:54<03:43, 74.34s/it]
+ 82%|████████▏ | 9/11 [11:08<02:28, 74.29s/it]
+ 91%|█████████ | 10/11 [12:23<01:14, 74.26s/it]
+100%|██████████| 11/11 [13:37<00:00, 74.39s/it]
+100%|██████████| 11/11 [13:37<00:00, 74.34s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 4: generating actions ...
+>>> Step 4: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 5: generating actions ...
+>>> Step 5: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 6: generating actions ...
+>>> Step 6: interacting with world model ...
 >>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing PsdImagePlugin
+>>> Step 7: generating actions ...
-DEBUG:PIL.Image:Importing QoiImagePlugin
+>>> Step 7: interacting with world model ...
-DEBUG:PIL.Image:Importing SgiImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>

unitree_g1_pack_camera/case3/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_g1_pack_camera/case3/unitree_g1_pack_camera_case3.mp4",
     "pred_video": "unitree_g1_pack_camera/case3/output/inference/100_full_fs6.mp4",
-    "psnr": 29.88155122131729
+    "psnr": 37.034952654534486
 }

unitree_g1_pack_camera/case3/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_g1_pack_camera"
         --n_iter 11 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_g1_pack_camera/case4/output.log

@@ -1,16 +1,21 @@
-2026-02-11 17:51:11.566934: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 20:34:34.563818: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 17:51:11.616260: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 20:34:34.613426: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 17:51:11.616305: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 20:34:34.613485: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 17:51:11.617626: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 20:34:34.614802: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 17:51:11.625103: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 20:34:34.622286: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 17:51:12.538539: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 20:34:35.540506: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,46 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/11 [00:00<?, ?it/s]
   0%|          | 0/11 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 18%|█▊        | 2/11 [00:46<03:26, 22.96s/it]
- 27%|██▋       | 3/11 [01:08<03:03, 22.89s/it]
- 36%|███▋      | 4/11 [01:31<02:40, 22.86s/it]
- 45%|████▌     | 5/11 [01:54<02:16, 22.82s/it]
- 55%|█████▍    | 6/11 [02:17<01:54, 22.80s/it]
- 64%|██████▎   | 7/11 [02:39<01:31, 22.77s/it]
- 73%|███████▎  | 8/11 [03:02<01:08, 22.75s/it]
- 82%|████████▏ | 9/11 [03:25<00:45, 22.73s/it]
- 91%|█████████ | 10/11 [03:47<00:22, 22.72s/it]
-100%|██████████| 11/11 [04:10<00:00, 22.73s/it]
-100%|██████████| 11/11 [04:10<00:00, 22.79s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 4: generating actions ...
->>> Step 4: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...
->>> Step 5: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 6: generating actions ...
->>> Step 6: interacting with world model ...
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -117,7 +89,39 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+  9%|▉         | 1/11 [01:14<12:25, 74.52s/it]
+ 18%|█▊        | 2/11 [02:29<11:15, 75.00s/it]
+ 27%|██▋       | 3/11 [03:44<09:59, 74.99s/it]
+ 36%|███▋      | 4/11 [04:59<08:43, 74.74s/it]
+ 45%|████▌     | 5/11 [06:13<07:26, 74.48s/it]
+ 55%|█████▍    | 6/11 [07:27<06:12, 74.56s/it]
+ 64%|██████▎   | 7/11 [08:42<04:57, 74.46s/it]
+ 73%|███████▎  | 8/11 [09:56<03:43, 74.48s/it]
+ 82%|████████▏ | 9/11 [11:10<02:28, 74.32s/it]
+ 91%|█████████ | 10/11 [12:23<01:13, 73.94s/it]
+100%|██████████| 11/11 [13:36<00:00, 73.64s/it]
+100%|██████████| 11/11 [13:36<00:00, 74.25s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 4: generating actions ...
+>>> Step 4: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 5: generating actions ...
+>>> Step 5: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 6: generating actions ...
+>>> Step 6: interacting with world model ...
 >>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing PsdImagePlugin
+>>> Step 7: generating actions ...
-DEBUG:PIL.Image:Importing QoiImagePlugin
+>>> Step 7: interacting with world model ...
-DEBUG:PIL.Image:Importing SgiImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>

unitree_g1_pack_camera/case4/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_g1_pack_camera/case4/unitree_g1_pack_camera_case4.mp4",
     "pred_video": "unitree_g1_pack_camera/case4/output/inference/200_full_fs6.mp4",
-    "psnr": 35.62512454155058
+    "psnr": 31.43390896360405
 }

unitree_g1_pack_camera/case4/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_g1_pack_camera"
         --n_iter 11 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_z1_dual_arm_cleanup_pencils/case1/output.log

@@ -1,16 +1,21 @@
-2026-02-11 17:56:01.170137: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 20:49:47.965949: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 17:56:01.219541: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 20:49:48.015942: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 17:56:01.219584: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 20:49:48.015997: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 17:56:01.220897: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 20:49:48.017330: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 17:56:01.228350: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 20:49:48.024854: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 17:56:02.145344: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 20:49:48.943205: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,37 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/8 [00:00<?, ?it/s]
   0%|          | 0/8 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 25%|██▌       | 2/8 [00:46<02:17, 22.96s/it]
- 38%|███▊      | 3/8 [01:08<01:54, 22.88s/it]
- 50%|█████     | 4/8 [01:31<01:31, 22.82s/it]
- 62%|██████▎   | 5/8 [01:54<01:08, 22.78s/it]
- 75%|███████▌  | 6/8 [02:16<00:45, 22.76s/it]
- 88%|████████▊ | 7/8 [02:39<00:22, 22.73s/it]
-100%|██████████| 8/8 [03:02<00:00, 22.72s/it]
-100%|██████████| 8/8 [03:02<00:00, 22.79s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 4: generating actions ...
->>> Step 4: interacting with world model ...
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -108,7 +89,30 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+ 12%|█▎        | 1/8 [01:15<08:48, 75.51s/it]
+ 25%|██▌       | 2/8 [02:30<07:32, 75.39s/it]
+ 38%|███▊      | 3/8 [03:46<06:16, 75.35s/it]
+ 50%|█████     | 4/8 [05:00<05:00, 75.01s/it]
+ 62%|██████▎   | 5/8 [06:14<03:44, 74.68s/it]
+ 75%|███████▌  | 6/8 [07:28<02:28, 74.40s/it]
+ 88%|████████▊ | 7/8 [08:42<01:14, 74.19s/it]
+100%|██████████| 8/8 [09:55<00:00, 73.95s/it]
+100%|██████████| 8/8 [09:55<00:00, 74.47s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 4: generating actions ...
+>>> Step 4: interacting with world model ...
 >>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing SpiderImagePlugin
+>>> Step 5: generating actions ...
-DEBUG:PIL.Image:Importing SunImagePlugin
+>>> Step 5: interacting with world model ...
-DEBUG:PIL.Image:Importing TgaImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>

unitree_z1_dual_arm_cleanup_pencils/case1/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_z1_dual_arm_cleanup_pencils/case1/unitree_z1_dual_arm_cleanup_pencils_case1.mp4",
     "pred_video": "unitree_z1_dual_arm_cleanup_pencils/case1/output/inference/0_full_fs4.mp4",
-    "psnr": 38.269577028444445
+    "psnr": 47.911564449209735
 }

unitree_z1_dual_arm_cleanup_pencils/case1/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_z1_dual_arm_cleanup_pencils"
         --n_iter 8 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_z1_dual_arm_cleanup_pencils/case2/output.log

@@ -1,16 +1,21 @@
-2026-02-11 17:59:40.132715: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 21:01:19.535243: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 17:59:40.183410: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 21:01:19.585230: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 17:59:40.183456: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 21:01:19.585275: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 17:59:40.184784: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 21:01:19.586600: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 17:59:40.192307: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 21:01:19.594107: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 17:59:41.105025: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 21:01:20.510688: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,37 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/8 [00:00<?, ?it/s]
   0%|          | 0/8 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 25%|██▌       | 2/8 [00:46<02:18, 23.00s/it]
- 38%|███▊      | 3/8 [01:08<01:54, 22.94s/it]
- 50%|█████     | 4/8 [01:31<01:31, 22.86s/it]
- 62%|██████▎   | 5/8 [01:54<01:08, 22.82s/it]
- 75%|███████▌  | 6/8 [02:17<00:45, 22.78s/it]
- 88%|████████▊ | 7/8 [02:39<00:22, 22.77s/it]
-100%|██████████| 8/8 [03:02<00:00, 22.75s/it]
-100%|██████████| 8/8 [03:02<00:00, 22.83s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 4: generating actions ...
->>> Step 4: interacting with world model ...
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -108,7 +89,30 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+ 12%|█▎        | 1/8 [01:16<08:54, 76.34s/it]
+ 25%|██▌       | 2/8 [02:32<07:37, 76.28s/it]
+ 38%|███▊      | 3/8 [03:48<06:21, 76.24s/it]
+ 50%|█████     | 4/8 [05:04<05:04, 76.15s/it]
+ 62%|██████▎   | 5/8 [06:21<03:48, 76.24s/it]
+ 75%|███████▌  | 6/8 [07:36<02:32, 76.08s/it]
+ 88%|████████▊ | 7/8 [08:52<01:15, 75.93s/it]
+100%|██████████| 8/8 [10:09<00:00, 76.12s/it]
+100%|██████████| 8/8 [10:09<00:00, 76.14s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 4: generating actions ...
+>>> Step 4: interacting with world model ...
 >>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing SpiderImagePlugin
+>>> Step 5: generating actions ...
-DEBUG:PIL.Image:Importing SunImagePlugin
+>>> Step 5: interacting with world model ...
-DEBUG:PIL.Image:Importing TgaImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>

unitree_z1_dual_arm_cleanup_pencils/case2/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_z1_dual_arm_cleanup_pencils/case2/unitree_z1_dual_arm_cleanup_pencils_case2.mp4",
     "pred_video": "unitree_z1_dual_arm_cleanup_pencils/case2/output/inference/50_full_fs4.mp4",
-    "psnr": 44.38754096950435
+    "psnr": 48.344571927558974
 }

unitree_z1_dual_arm_cleanup_pencils/case2/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_z1_dual_arm_cleanup_pencils"
         --n_iter 8 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_z1_dual_arm_cleanup_pencils/case3/output.log

@@ -1,16 +1,21 @@
-2026-02-11 18:03:19.373691: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 21:13:04.812376: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 18:03:19.423144: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 21:13:04.862167: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 18:03:19.423201: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 21:13:04.862223: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 18:03:19.424504: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 21:13:04.863549: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 18:03:19.431968: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 21:13:04.871078: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 18:03:20.342432: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 21:13:05.785070: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,37 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/8 [00:00<?, ?it/s]
   0%|          | 0/8 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 25%|██▌       | 2/8 [00:46<02:17, 22.99s/it]
- 38%|███▊      | 3/8 [01:09<01:54, 22.94s/it]
- 50%|█████     | 4/8 [01:31<01:31, 22.89s/it]
- 62%|██████▎   | 5/8 [01:54<01:08, 22.84s/it]
- 75%|███████▌  | 6/8 [02:17<00:45, 22.82s/it]
- 88%|████████▊ | 7/8 [02:40<00:22, 22.81s/it]
-100%|██████████| 8/8 [03:02<00:00, 22.79s/it]
-100%|██████████| 8/8 [03:02<00:00, 22.86s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 4: generating actions ...
->>> Step 4: interacting with world model ...
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -108,7 +89,30 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+ 12%|█▎        | 1/8 [01:15<08:45, 75.11s/it]
+ 25%|██▌       | 2/8 [02:30<07:31, 75.30s/it]
+ 38%|███▊      | 3/8 [03:45<06:16, 75.32s/it]
+ 50%|█████     | 4/8 [05:01<05:01, 75.29s/it]
+ 62%|██████▎   | 5/8 [06:16<03:46, 75.38s/it]
+ 75%|███████▌  | 6/8 [07:32<02:30, 75.48s/it]
+ 88%|████████▊ | 7/8 [08:47<01:15, 75.39s/it]
+100%|██████████| 8/8 [10:02<00:00, 75.30s/it]
+100%|██████████| 8/8 [10:02<00:00, 75.33s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 4: generating actions ...
+>>> Step 4: interacting with world model ...
 >>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing SpiderImagePlugin
+>>> Step 5: generating actions ...
-DEBUG:PIL.Image:Importing SunImagePlugin
+>>> Step 5: interacting with world model ...
-DEBUG:PIL.Image:Importing TgaImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>

unitree_z1_dual_arm_cleanup_pencils/case3/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_z1_dual_arm_cleanup_pencils/case3/unitree_z1_dual_arm_cleanup_pencils_case3.mp4",
     "pred_video": "unitree_z1_dual_arm_cleanup_pencils/case3/output/inference/100_full_fs4.mp4",
-    "psnr": 32.29959078097713
+    "psnr": 41.152374490134825
 }

unitree_z1_dual_arm_cleanup_pencils/case3/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_z1_dual_arm_cleanup_pencils"
         --n_iter 8 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_z1_dual_arm_cleanup_pencils/case4/output.log

@@ -1,16 +1,21 @@
-2026-02-11 18:06:58.863806: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 21:24:42.443699: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 18:06:58.913518: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 21:24:42.494143: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 18:06:58.913565: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 21:24:42.494201: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 18:06:58.914918: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 21:24:42.495506: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 18:06:58.922497: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 21:24:42.503003: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 18:06:59.840461: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 21:24:43.415898: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,37 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/8 [00:00<?, ?it/s]
   0%|          | 0/8 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 25%|██▌       | 2/8 [00:46<02:18, 23.01s/it]
- 38%|███▊      | 3/8 [01:09<01:54, 22.94s/it]
- 50%|█████     | 4/8 [01:31<01:31, 22.89s/it]
- 62%|██████▎   | 5/8 [01:54<01:08, 22.85s/it]
- 75%|███████▌  | 6/8 [02:17<00:45, 22.81s/it]
- 88%|████████▊ | 7/8 [02:40<00:22, 22.79s/it]
-100%|██████████| 8/8 [03:02<00:00, 22.77s/it]
-100%|██████████| 8/8 [03:02<00:00, 22.85s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 4: generating actions ...
->>> Step 4: interacting with world model ...
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -108,7 +89,30 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+ 12%|█▎        | 1/8 [01:15<08:46, 75.28s/it]
+ 25%|██▌       | 2/8 [02:30<07:32, 75.34s/it]
+ 38%|███▊      | 3/8 [03:45<06:15, 75.08s/it]
+ 50%|█████     | 4/8 [04:59<04:58, 74.69s/it]
+ 62%|██████▎   | 5/8 [06:13<03:43, 74.43s/it]
+ 75%|███████▌  | 6/8 [07:27<02:28, 74.27s/it]
+ 88%|████████▊ | 7/8 [08:41<01:14, 74.21s/it]
+100%|██████████| 8/8 [09:55<00:00, 74.13s/it]
+100%|██████████| 8/8 [09:55<00:00, 74.43s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 4: generating actions ...
+>>> Step 4: interacting with world model ...
 >>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing SpiderImagePlugin
+>>> Step 5: generating actions ...
-DEBUG:PIL.Image:Importing SunImagePlugin
+>>> Step 5: interacting with world model ...
-DEBUG:PIL.Image:Importing TgaImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>

unitree_z1_dual_arm_cleanup_pencils/case4/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_z1_dual_arm_cleanup_pencils/case4/unitree_z1_dual_arm_cleanup_pencils_case4.mp4",
     "pred_video": "unitree_z1_dual_arm_cleanup_pencils/case4/output/inference/200_full_fs4.mp4",
-    "psnr": 45.051241961122535
+    "psnr": 46.025723557253855
 }

unitree_z1_dual_arm_cleanup_pencils/case4/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_z1_dual_arm_cleanup_pencils"
         --n_iter 8 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_z1_dual_arm_stackbox/case1/output.log

@@ -1,16 +1,21 @@
-2026-02-11 18:10:38.361867: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 21:36:14.761055: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 18:10:38.412126: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 21:36:14.811056: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 18:10:38.412182: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 21:36:14.811115: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 18:10:38.413493: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 21:36:14.812480: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 18:10:38.420963: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 21:36:14.820115: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 18:10:39.335981: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 21:36:15.736583: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,34 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/7 [00:00<?, ?it/s]
   0%|          | 0/7 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 29%|██▊       | 2/7 [00:46<01:54, 22.99s/it]
- 43%|████▎     | 3/7 [01:08<01:31, 22.92s/it]
- 57%|█████▋    | 4/7 [01:31<01:08, 22.88s/it]
- 71%|███████▏  | 5/7 [01:54<00:45, 22.82s/it]
- 86%|████████▌ | 6/7 [02:17<00:22, 22.79s/it]
-100%|██████████| 7/7 [02:39<00:00, 22.75s/it]
-100%|██████████| 7/7 [02:39<00:00, 22.84s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -105,7 +89,27 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+ 14%|█▍        | 1/7 [01:15<07:34, 75.70s/it]
+ 29%|██▊       | 2/7 [02:31<06:18, 75.65s/it]
+ 43%|████▎     | 3/7 [03:46<05:02, 75.52s/it]
+ 57%|█████▋    | 4/7 [05:02<03:46, 75.47s/it]
+ 71%|███████▏  | 5/7 [06:17<02:30, 75.40s/it]
+ 86%|████████▌ | 6/7 [07:32<01:15, 75.37s/it]
+100%|██████████| 7/7 [08:48<00:00, 75.38s/it]
+100%|██████████| 7/7 [08:48<00:00, 75.44s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
 >>> Step 4: generating actions ...
-DEBUG:PIL.Image:Importing SunImagePlugin
+>>> Step 4: interacting with world model ...
-DEBUG:PIL.Image:Importing TgaImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing TiffImagePlugin
+>>> Step 5: generating actions ...

unitree_z1_dual_arm_stackbox/case1/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_z1_dual_arm_stackbox/case1/unitree_z1_dual_arm_stackbox_case1.mp4",
     "pred_video": "unitree_z1_dual_arm_stackbox/case1/output/inference/5_full_fs4.mp4",
-    "psnr": 42.717688631296596
+    "psnr": 44.3480149502738
 }

unitree_z1_dual_arm_stackbox/case1/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_z1_dual_arm_stackbox"
         --n_iter 7 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_z1_dual_arm_stackbox/case2/output.log

@@ -1,16 +1,21 @@
-2026-02-11 18:13:57.132827: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 21:46:41.375935: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 18:13:57.182101: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 21:46:41.426557: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 18:13:57.182156: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 21:46:41.426614: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 18:13:57.183471: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 21:46:41.427937: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 18:13:57.190931: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 21:46:41.435507: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 18:13:58.104923: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 21:46:42.361310: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,34 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/7 [00:00<?, ?it/s]
   0%|          | 0/7 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 29%|██▊       | 2/7 [00:46<01:54, 22.98s/it]
- 43%|████▎     | 3/7 [01:08<01:31, 22.91s/it]
- 57%|█████▋    | 4/7 [01:31<01:08, 22.87s/it]
- 71%|███████▏  | 5/7 [01:54<00:45, 22.84s/it]
- 86%|████████▌ | 6/7 [02:17<00:22, 22.80s/it]
-100%|██████████| 7/7 [02:39<00:00, 22.77s/it]
-100%|██████████| 7/7 [02:39<00:00, 22.84s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -105,7 +89,27 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+ 14%|█▍        | 1/7 [01:16<07:38, 76.39s/it]
+ 29%|██▊       | 2/7 [02:33<06:23, 76.69s/it]
+ 43%|████▎     | 3/7 [03:50<05:07, 76.87s/it]
+ 57%|█████▋    | 4/7 [05:07<03:50, 76.91s/it]
+ 71%|███████▏  | 5/7 [06:23<02:33, 76.80s/it]
+ 86%|████████▌ | 6/7 [07:40<01:16, 76.77s/it]
+100%|██████████| 7/7 [08:57<00:00, 76.85s/it]
+100%|██████████| 7/7 [08:57<00:00, 76.81s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
 >>> Step 4: generating actions ...
-DEBUG:PIL.Image:Importing SunImagePlugin
+>>> Step 4: interacting with world model ...
-DEBUG:PIL.Image:Importing TgaImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing TiffImagePlugin
+>>> Step 5: generating actions ...

unitree_z1_dual_arm_stackbox/case2/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_z1_dual_arm_stackbox/case2/unitree_z1_dual_arm_stackbox_case2.mp4",
     "pred_video": "unitree_z1_dual_arm_stackbox/case2/output/inference/15_full_fs4.mp4",
-    "psnr": 44.90750363879194
+    "psnr": 39.867728254007716
 }

unitree_z1_dual_arm_stackbox/case2/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_z1_dual_arm_stackbox"
         --n_iter 7 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_z1_dual_arm_stackbox/case3/output.log

@@ -1,16 +1,21 @@
-2026-02-11 18:17:16.023670: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 21:57:17.623993: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 18:17:16.073206: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 21:57:17.673835: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 18:17:16.073251: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 21:57:17.673891: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 18:17:16.074552: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 21:57:17.675211: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 18:17:16.082033: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 21:57:17.682716: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 18:17:16.997362: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 21:57:18.593525: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,34 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/7 [00:00<?, ?it/s]
   0%|          | 0/7 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 29%|██▊       | 2/7 [00:46<01:55, 23.03s/it]
- 43%|████▎     | 3/7 [01:09<01:31, 22.95s/it]
- 57%|█████▋    | 4/7 [01:31<01:08, 22.91s/it]
- 71%|███████▏  | 5/7 [01:54<00:45, 22.87s/it]
- 86%|████████▌ | 6/7 [02:17<00:22, 22.84s/it]
-100%|██████████| 7/7 [02:40<00:00, 22.82s/it]
-100%|██████████| 7/7 [02:40<00:00, 22.89s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -105,7 +89,27 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+ 14%|█▍        | 1/7 [01:15<07:33, 75.59s/it]
+ 29%|██▊       | 2/7 [02:31<06:17, 75.59s/it]
+ 43%|████▎     | 3/7 [03:46<05:01, 75.44s/it]
+ 57%|█████▋    | 4/7 [05:01<03:46, 75.39s/it]
+ 71%|███████▏  | 5/7 [06:17<02:30, 75.35s/it]
+ 86%|████████▌ | 6/7 [07:32<01:15, 75.32s/it]
+100%|██████████| 7/7 [08:47<00:00, 75.24s/it]
+100%|██████████| 7/7 [08:47<00:00, 75.34s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
 >>> Step 4: generating actions ...
-DEBUG:PIL.Image:Importing SunImagePlugin
+>>> Step 4: interacting with world model ...
-DEBUG:PIL.Image:Importing TgaImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing TiffImagePlugin
+>>> Step 5: generating actions ...

unitree_z1_dual_arm_stackbox/case3/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_z1_dual_arm_stackbox/case3/unitree_z1_dual_arm_stackbox_case3.mp4",
     "pred_video": "unitree_z1_dual_arm_stackbox/case3/output/inference/25_full_fs4.mp4",
-    "psnr": 39.63695040491171
+    "psnr": 39.19101039445159
 }

unitree_z1_dual_arm_stackbox/case3/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_z1_dual_arm_stackbox"
         --n_iter 7 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_z1_dual_arm_stackbox/case4/output.log

@@ -1,16 +1,21 @@
-2026-02-11 18:20:35.210324: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 22:07:43.398736: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 18:20:35.259487: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 22:07:43.448264: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 18:20:35.259530: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 22:07:43.448321: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 18:20:35.260816: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 22:07:43.449636: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 18:20:35.268252: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 22:07:43.457127: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 18:20:36.181189: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 22:07:44.370935: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,34 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/7 [00:00<?, ?it/s]
   0%|          | 0/7 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 29%|██▊       | 2/7 [00:46<01:55, 23.03s/it]
- 43%|████▎     | 3/7 [01:09<01:31, 22.96s/it]
- 57%|█████▋    | 4/7 [01:31<01:08, 22.92s/it]
- 71%|███████▏  | 5/7 [01:54<00:45, 22.89s/it]
- 86%|████████▌ | 6/7 [02:17<00:22, 22.86s/it]
-100%|██████████| 7/7 [02:40<00:00, 22.84s/it]
-100%|██████████| 7/7 [02:40<00:00, 22.91s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -105,7 +89,27 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+ 14%|█▍        | 1/7 [01:17<07:42, 77.04s/it]
+ 29%|██▊       | 2/7 [02:33<06:24, 76.95s/it]
+ 43%|████▎     | 3/7 [03:50<05:07, 76.87s/it]
+ 57%|█████▋    | 4/7 [05:06<03:49, 76.59s/it]
+ 71%|███████▏  | 5/7 [06:24<02:33, 76.82s/it]
+ 86%|████████▌ | 6/7 [07:39<01:16, 76.43s/it]
+100%|██████████| 7/7 [08:55<00:00, 76.06s/it]
+100%|██████████| 7/7 [08:55<00:00, 76.44s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
 >>> Step 4: generating actions ...
-DEBUG:PIL.Image:Importing SunImagePlugin
+>>> Step 4: interacting with world model ...
-DEBUG:PIL.Image:Importing TgaImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing TiffImagePlugin
+>>> Step 5: generating actions ...

unitree_z1_dual_arm_stackbox/case4/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_z1_dual_arm_stackbox/case4/unitree_z1_dual_arm_stackbox_case4.mp4",
     "pred_video": "unitree_z1_dual_arm_stackbox/case4/output/inference/35_full_fs4.mp4",
-    "psnr": 42.34177660061245
+    "psnr": 40.29563315341769
 }

unitree_z1_dual_arm_stackbox/case4/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_z1_dual_arm_stackbox"
         --n_iter 7 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_z1_dual_arm_stackbox_v2/case1/output.log

@@ -1,16 +1,21 @@
-2026-02-11 18:23:54.635983: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 22:18:17.396072: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 18:23:54.685542: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 22:18:17.446095: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 18:23:54.685587: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 22:18:17.446154: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 18:23:54.686907: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 22:18:17.447480: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 18:23:54.694405: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 22:18:17.455025: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 18:23:55.620959: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 22:18:18.367007: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,46 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/11 [00:00<?, ?it/s]
   0%|          | 0/11 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 18%|█▊        | 2/11 [00:46<03:26, 22.96s/it]
- 27%|██▋       | 3/11 [01:08<03:03, 22.91s/it]
- 36%|███▋      | 4/11 [01:31<02:40, 22.86s/it]
- 45%|████▌     | 5/11 [01:54<02:16, 22.83s/it]
- 55%|█████▍    | 6/11 [02:17<01:54, 22.80s/it]
- 64%|██████▎   | 7/11 [02:39<01:31, 22.79s/it]
- 73%|███████▎  | 8/11 [03:02<01:08, 22.79s/it]
- 82%|████████▏ | 9/11 [03:25<00:45, 22.78s/it]
- 91%|█████████ | 10/11 [03:48<00:22, 22.76s/it]
-100%|██████████| 11/11 [04:10<00:00, 22.75s/it]
-100%|██████████| 11/11 [04:10<00:00, 22.82s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 4: generating actions ...
->>> Step 4: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...
->>> Step 5: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 6: generating actions ...
->>> Step 6: interacting with world model ...
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -117,7 +89,39 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+  9%|▉         | 1/11 [01:15<12:35, 75.53s/it]
+ 18%|█▊        | 2/11 [02:30<11:18, 75.39s/it]
+ 27%|██▋       | 3/11 [03:46<10:03, 75.38s/it]
+ 36%|███▋      | 4/11 [05:01<08:48, 75.47s/it]
+ 45%|████▌     | 5/11 [06:16<07:31, 75.32s/it]
+ 55%|█████▍    | 6/11 [07:31<06:15, 75.08s/it]
+ 64%|██████▎   | 7/11 [08:46<05:00, 75.07s/it]
+ 73%|███████▎  | 8/11 [10:00<03:44, 74.76s/it]
+ 82%|████████▏ | 9/11 [11:15<02:29, 74.87s/it]
+ 91%|█████████ | 10/11 [12:30<01:14, 74.79s/it]
+100%|██████████| 11/11 [13:45<00:00, 74.80s/it]
+100%|██████████| 11/11 [13:45<00:00, 75.02s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 4: generating actions ...
+>>> Step 4: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 5: generating actions ...
+>>> Step 5: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 6: generating actions ...
+>>> Step 6: interacting with world model ...
 >>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing PsdImagePlugin
+>>> Step 7: generating actions ...
-DEBUG:PIL.Image:Importing QoiImagePlugin
+>>> Step 7: interacting with world model ...
-DEBUG:PIL.Image:Importing SgiImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>

unitree_z1_dual_arm_stackbox_v2/case1/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_z1_dual_arm_stackbox_v2/case1/unitree_z1_dual_arm_stackbox_v2_case1.mp4",
     "pred_video": "unitree_z1_dual_arm_stackbox_v2/case1/output/inference/5_full_fs4.mp4",
-    "psnr": 26.683000215343522
+    "psnr": 25.812741419225095
 }

unitree_z1_dual_arm_stackbox_v2/case1/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_z1_dual_arm_stackbox_v2"
         --n_iter 11 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_z1_dual_arm_stackbox_v2/case2/output.log

@@ -1,16 +1,21 @@
-2026-02-11 18:28:48.801743: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 22:33:42.261398: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 18:28:48.852069: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 22:33:42.310786: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 18:28:48.852128: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 22:33:42.310845: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 18:28:48.853466: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 22:33:42.312191: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 18:28:48.861133: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 22:33:42.319738: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 18:28:49.784354: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 22:33:43.232517: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,46 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/11 [00:00<?, ?it/s]
   0%|          | 0/11 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 18%|█▊        | 2/11 [00:46<03:28, 23.13s/it]
- 27%|██▋       | 3/11 [01:09<03:04, 23.02s/it]
- 36%|███▋      | 4/11 [01:32<02:40, 22.96s/it]
- 45%|████▌     | 5/11 [01:55<02:17, 22.92s/it]
- 55%|█████▍    | 6/11 [02:17<01:54, 22.88s/it]
- 64%|██████▎   | 7/11 [02:40<01:31, 22.84s/it]
- 73%|███████▎  | 8/11 [03:03<01:08, 22.81s/it]
- 82%|████████▏ | 9/11 [03:26<00:45, 22.81s/it]
- 91%|█████████ | 10/11 [03:48<00:22, 22.80s/it]
-100%|██████████| 11/11 [04:11<00:00, 22.80s/it]
-100%|██████████| 11/11 [04:11<00:00, 22.88s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 4: generating actions ...
->>> Step 4: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...
->>> Step 5: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 6: generating actions ...
->>> Step 6: interacting with world model ...
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -117,7 +89,39 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+  9%|▉         | 1/11 [01:13<12:18, 73.90s/it]
+ 18%|█▊        | 2/11 [02:27<11:05, 73.99s/it]
+ 27%|██▋       | 3/11 [03:41<09:50, 73.86s/it]
+ 36%|███▋      | 4/11 [04:55<08:35, 73.70s/it]
+ 45%|████▌     | 5/11 [06:08<07:20, 73.48s/it]
+ 55%|█████▍    | 6/11 [07:21<06:06, 73.39s/it]
+ 64%|██████▎   | 7/11 [08:34<04:53, 73.28s/it]
+ 73%|███████▎  | 8/11 [09:47<03:39, 73.11s/it]
+ 82%|████████▏ | 9/11 [11:00<02:26, 73.21s/it]
+ 91%|█████████ | 10/11 [12:14<01:13, 73.49s/it]
+100%|██████████| 11/11 [13:28<00:00, 73.55s/it]
+100%|██████████| 11/11 [13:28<00:00, 73.50s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 4: generating actions ...
+>>> Step 4: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 5: generating actions ...
+>>> Step 5: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 6: generating actions ...
+>>> Step 6: interacting with world model ...
 >>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing PsdImagePlugin
+>>> Step 7: generating actions ...
-DEBUG:PIL.Image:Importing QoiImagePlugin
+>>> Step 7: interacting with world model ...
-DEBUG:PIL.Image:Importing SgiImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>

unitree_z1_dual_arm_stackbox_v2/case2/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_z1_dual_arm_stackbox_v2/case2/unitree_z1_dual_arm_stackbox_v2_case2.mp4",
     "pred_video": "unitree_z1_dual_arm_stackbox_v2/case2/output/inference/15_full_fs4.mp4",
-    "psnr": 27.46347145461597
+    "psnr": 33.90444714332389
 }

unitree_z1_dual_arm_stackbox_v2/case2/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_z1_dual_arm_stackbox_v2"
         --n_iter 11 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_z1_dual_arm_stackbox_v2/case3/output.log

@@ -1,16 +1,21 @@
-2026-02-11 18:33:43.119091: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 22:48:49.761688: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 18:33:43.169099: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 22:48:49.811395: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 18:33:43.169143: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 22:48:49.811456: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 18:33:43.170444: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 22:48:49.812798: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 18:33:43.177944: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 22:48:49.820307: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 18:33:44.102499: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 22:48:50.732941: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,46 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/11 [00:00<?, ?it/s]
   0%|          | 0/11 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 18%|█▊        | 2/11 [00:46<03:26, 22.99s/it]
- 27%|██▋       | 3/11 [01:08<03:03, 22.93s/it]
- 36%|███▋      | 4/11 [01:31<02:40, 22.87s/it]
- 45%|████▌     | 5/11 [01:54<02:17, 22.85s/it]
- 55%|█████▍    | 6/11 [02:17<01:54, 22.80s/it]
- 64%|██████▎   | 7/11 [02:40<01:31, 22.79s/it]
- 73%|███████▎  | 8/11 [03:02<01:08, 22.78s/it]
- 82%|████████▏ | 9/11 [03:25<00:45, 22.76s/it]
- 91%|█████████ | 10/11 [03:48<00:22, 22.74s/it]
-100%|██████████| 11/11 [04:10<00:00, 22.73s/it]
-100%|██████████| 11/11 [04:10<00:00, 22.81s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 4: generating actions ...
->>> Step 4: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...
->>> Step 5: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 6: generating actions ...
->>> Step 6: interacting with world model ...
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -117,7 +89,39 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+  9%|▉         | 1/11 [01:14<12:29, 74.99s/it]
+ 18%|█▊        | 2/11 [02:30<11:18, 75.44s/it]
+ 27%|██▋       | 3/11 [03:46<10:03, 75.49s/it]
+ 36%|███▋      | 4/11 [05:01<08:47, 75.30s/it]
+ 45%|████▌     | 5/11 [06:15<07:30, 75.02s/it]
+ 55%|█████▍    | 6/11 [07:30<06:14, 74.84s/it]
+ 64%|██████▎   | 7/11 [08:44<04:59, 74.79s/it]
+ 73%|███████▎  | 8/11 [10:00<03:44, 74.94s/it]
+ 82%|████████▏ | 9/11 [11:15<02:29, 74.89s/it]
+ 91%|█████████ | 10/11 [12:30<01:14, 74.95s/it]
+100%|██████████| 11/11 [13:45<00:00, 74.95s/it]
+100%|██████████| 11/11 [13:45<00:00, 75.01s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 4: generating actions ...
+>>> Step 4: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 5: generating actions ...
+>>> Step 5: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 6: generating actions ...
+>>> Step 6: interacting with world model ...
 >>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing PsdImagePlugin
+>>> Step 7: generating actions ...
-DEBUG:PIL.Image:Importing QoiImagePlugin
+>>> Step 7: interacting with world model ...
-DEBUG:PIL.Image:Importing SgiImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>

unitree_z1_dual_arm_stackbox_v2/case3/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_z1_dual_arm_stackbox_v2/case3/unitree_z1_dual_arm_stackbox_v2_case3.mp4",
     "pred_video": "unitree_z1_dual_arm_stackbox_v2/case3/output/inference/25_full_fs4.mp4",
-    "psnr": 28.604047286947512
+    "psnr": 34.50192428908007
 }

unitree_z1_dual_arm_stackbox_v2/case3/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_z1_dual_arm_stackbox_v2"
         --n_iter 11 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_z1_dual_arm_stackbox_v2/case4/output.log

@@ -1,16 +1,21 @@
-2026-02-11 18:38:37.252690: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 23:04:15.762959: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 18:38:37.301897: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 23:04:15.814243: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 18:38:37.301950: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 23:04:15.814301: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 18:38:37.303254: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 23:04:15.815653: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 18:38:37.310679: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 23:04:15.823287: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 18:38:38.237893: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 23:04:16.742609: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,46 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/11 [00:00<?, ?it/s]
   0%|          | 0/11 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 18%|█▊        | 2/11 [00:46<03:26, 22.99s/it]
- 27%|██▋       | 3/11 [01:08<03:03, 22.91s/it]
- 36%|███▋      | 4/11 [01:31<02:40, 22.86s/it]
- 45%|████▌     | 5/11 [01:54<02:16, 22.83s/it]
- 55%|█████▍    | 6/11 [02:17<01:54, 22.82s/it]
- 64%|██████▎   | 7/11 [02:40<01:31, 22.81s/it]
- 73%|███████▎  | 8/11 [03:02<01:08, 22.80s/it]
- 82%|████████▏ | 9/11 [03:25<00:45, 22.78s/it]
- 91%|█████████ | 10/11 [03:48<00:22, 22.77s/it]
-100%|██████████| 11/11 [04:11<00:00, 22.77s/it]
-100%|██████████| 11/11 [04:11<00:00, 22.83s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 4: generating actions ...
->>> Step 4: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...
->>> Step 5: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 6: generating actions ...
->>> Step 6: interacting with world model ...
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -117,7 +89,39 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+  9%|▉         | 1/11 [01:14<12:25, 74.55s/it]
+ 18%|█▊        | 2/11 [02:29<11:13, 74.83s/it]
+ 27%|██▋       | 3/11 [03:44<09:58, 74.77s/it]
+ 36%|███▋      | 4/11 [04:59<08:43, 74.78s/it]
+ 45%|████▌     | 5/11 [06:13<07:28, 74.83s/it]
+ 55%|█████▍    | 6/11 [07:28<06:13, 74.62s/it]
+ 64%|██████▎   | 7/11 [08:42<04:57, 74.37s/it]
+ 73%|███████▎  | 8/11 [09:56<03:42, 74.28s/it]
+ 82%|████████▏ | 9/11 [11:10<02:28, 74.26s/it]
+ 91%|█████████ | 10/11 [12:24<01:14, 74.31s/it]
+100%|██████████| 11/11 [13:39<00:00, 74.38s/it]
+100%|██████████| 11/11 [13:39<00:00, 74.48s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 4: generating actions ...
+>>> Step 4: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 5: generating actions ...
+>>> Step 5: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 6: generating actions ...
+>>> Step 6: interacting with world model ...
 >>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing PsdImagePlugin
+>>> Step 7: generating actions ...
-DEBUG:PIL.Image:Importing QoiImagePlugin
+>>> Step 7: interacting with world model ...
-DEBUG:PIL.Image:Importing SgiImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>

unitree_z1_dual_arm_stackbox_v2/case4/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_z1_dual_arm_stackbox_v2/case4/unitree_z1_dual_arm_stackbox_v2_case4.mp4",
     "pred_video": "unitree_z1_dual_arm_stackbox_v2/case4/output/inference/35_full_fs4.mp4",
-    "psnr": 25.578498826379903
+    "psnr": 38.797893493652516
 }

unitree_z1_dual_arm_stackbox_v2/case4/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_z1_dual_arm_stackbox_v2"
         --n_iter 11 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_z1_stackbox/case1/output.log

@@ -1,16 +1,21 @@
-2026-02-11 18:43:31.592464: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 23:19:36.475817: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 18:43:31.641865: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 23:19:36.525118: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 18:43:31.641908: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 23:19:36.525172: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 18:43:31.643209: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 23:19:36.526479: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 18:43:31.650663: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 23:19:36.533981: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 18:43:32.564662: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 23:19:37.461985: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,49 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/12 [00:00<?, ?it/s]
   0%|          | 0/12 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 17%|█▋        | 2/12 [00:46<03:50, 23.03s/it]
- 25%|██▌       | 3/12 [01:09<03:26, 22.97s/it]
- 33%|███▎      | 4/12 [01:31<03:03, 22.92s/it]
- 42%|████▏     | 5/12 [01:54<02:40, 22.88s/it]
- 50%|█████     | 6/12 [02:17<02:17, 22.84s/it]
- 58%|█████▊    | 7/12 [02:40<01:54, 22.80s/it]
- 67%|██████▋   | 8/12 [03:02<01:31, 22.78s/it]
- 75%|███████▌  | 9/12 [03:25<01:08, 22.78s/it]
- 83%|████████▎ | 10/12 [03:48<00:45, 22.78s/it]
- 92%|█████████▏| 11/12 [04:11<00:22, 22.77s/it]
-100%|██████████| 12/12 [04:34<00:00, 22.77s/it]
-100%|██████████| 12/12 [04:34<00:00, 22.83s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 4: generating actions ...
->>> Step 4: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...
->>> Step 5: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 6: generating actions ...
->>> Step 6: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 7: generating actions ...
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -120,7 +89,42 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+  8%|▊         | 1/12 [01:14<13:38, 74.37s/it]
+ 17%|█▋        | 2/12 [02:28<12:21, 74.13s/it]
+ 25%|██▌       | 3/12 [03:42<11:05, 73.97s/it]
+ 33%|███▎      | 4/12 [04:55<09:51, 73.92s/it]
+ 42%|████▏     | 5/12 [06:09<08:35, 73.70s/it]
+ 50%|█████     | 6/12 [07:22<07:21, 73.58s/it]
+ 58%|█████▊    | 7/12 [08:35<06:07, 73.49s/it]
+ 67%|██████▋   | 8/12 [09:49<04:53, 73.46s/it]
+ 75%|███████▌  | 9/12 [11:02<03:40, 73.42s/it]
+ 83%|████████▎ | 10/12 [12:16<02:26, 73.44s/it]
+ 92%|█████████▏| 11/12 [13:29<01:13, 73.40s/it]
+100%|██████████| 12/12 [14:42<00:00, 73.32s/it]
+100%|██████████| 12/12 [14:42<00:00, 73.55s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 4: generating actions ...
+>>> Step 4: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 5: generating actions ...
+>>> Step 5: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 6: generating actions ...
+>>> Step 6: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 7: generating actions ...
 >>> Step 7: interacting with world model ...
-DEBUG:PIL.Image:Importing PpmImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing PsdImagePlugin
+>>> Step 8: generating actions ...
-DEBUG:PIL.Image:Importing QoiImagePlugin
+>>> Step 8: interacting with world model ...

unitree_z1_stackbox/case1/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_z1_stackbox/case1/unitree_z1_stackbox_case1.mp4",
     "pred_video": "unitree_z1_stackbox/case1/output/inference/5_full_fs4.mp4",
-    "psnr": 46.05271283048069
+    "psnr": 42.83913947323794
 }

unitree_z1_stackbox/case1/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_z1_stackbox"
         --n_iter 12 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_z1_stackbox/case2/output.log

@@ -1,16 +1,21 @@
-2026-02-11 18:48:44.235405: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 23:35:52.961572: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 18:48:44.285138: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 23:35:53.011562: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 18:48:44.285181: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 23:35:53.011622: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 18:48:44.286531: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 23:35:53.012961: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 18:48:44.294141: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 23:35:53.020520: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 18:48:45.209453: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 23:35:53.953177: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,49 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/12 [00:00<?, ?it/s]
   0%|          | 0/12 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 17%|█▋        | 2/12 [00:46<03:49, 22.97s/it]
- 25%|██▌       | 3/12 [01:08<03:26, 22.91s/it]
- 33%|███▎      | 4/12 [01:31<03:02, 22.86s/it]
- 42%|████▏     | 5/12 [01:54<02:39, 22.82s/it]
- 50%|█████     | 6/12 [02:17<02:16, 22.81s/it]
- 58%|█████▊    | 7/12 [02:39<01:53, 22.79s/it]
- 67%|██████▋   | 8/12 [03:02<01:31, 22.78s/it]
- 75%|███████▌  | 9/12 [03:25<01:08, 22.76s/it]
- 83%|████████▎ | 10/12 [03:48<00:45, 22.75s/it]
- 92%|█████████▏| 11/12 [04:10<00:22, 22.74s/it]
-100%|██████████| 12/12 [04:33<00:00, 22.72s/it]
-100%|██████████| 12/12 [04:33<00:00, 22.80s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 4: generating actions ...
->>> Step 4: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...
->>> Step 5: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 6: generating actions ...
->>> Step 6: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 7: generating actions ...
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -120,7 +89,42 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+  8%|▊         | 1/12 [01:13<13:33, 73.92s/it]
+ 17%|█▋        | 2/12 [02:28<12:22, 74.25s/it]
+ 25%|██▌       | 3/12 [03:41<11:01, 73.53s/it]
+ 33%|███▎      | 4/12 [04:53<09:45, 73.17s/it]
+ 42%|████▏     | 5/12 [06:06<08:30, 72.96s/it]
+ 50%|█████     | 6/12 [07:18<07:16, 72.80s/it]
+ 58%|█████▊    | 7/12 [08:31<06:03, 72.71s/it]
+ 67%|██████▋   | 8/12 [09:43<04:50, 72.64s/it]
+ 75%|███████▌  | 9/12 [10:56<03:37, 72.61s/it]
+ 83%|████████▎ | 10/12 [12:08<02:25, 72.56s/it]
+ 92%|█████████▏| 11/12 [13:21<01:12, 72.53s/it]
+100%|██████████| 12/12 [14:33<00:00, 72.48s/it]
+100%|██████████| 12/12 [14:33<00:00, 72.80s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 4: generating actions ...
+>>> Step 4: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 5: generating actions ...
+>>> Step 5: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 6: generating actions ...
+>>> Step 6: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 7: generating actions ...
 >>> Step 7: interacting with world model ...
-DEBUG:PIL.Image:Importing PpmImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing PsdImagePlugin
+>>> Step 8: generating actions ...
-DEBUG:PIL.Image:Importing QoiImagePlugin
+>>> Step 8: interacting with world model ...

unitree_z1_stackbox/case2/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_z1_stackbox/case2/unitree_z1_stackbox_case2.mp4",
     "pred_video": "unitree_z1_stackbox/case2/output/inference/15_full_fs4.mp4",
-    "psnr": 38.94694381287429
+    "psnr": 48.64571989587276
 }

unitree_z1_stackbox/case2/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_z1_stackbox"
         --n_iter 12 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_z1_stackbox/case3/output.log

@@ -1,16 +1,21 @@
-2026-02-11 18:53:57.068615: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-11 23:51:59.440508: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 18:53:57.118271: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-11 23:51:59.489849: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 18:53:57.118312: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-11 23:51:59.489897: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 18:53:57.119665: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-11 23:51:59.491194: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 18:53:57.127266: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-11 23:51:59.498659: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 18:53:58.042116: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 23:52:00.422248: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,49 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/12 [00:00<?, ?it/s]
   0%|          | 0/12 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 17%|█▋        | 2/12 [00:46<03:50, 23.02s/it]
- 25%|██▌       | 3/12 [01:09<03:26, 22.96s/it]
- 33%|███▎      | 4/12 [01:31<03:03, 22.92s/it]
- 42%|████▏     | 5/12 [01:54<02:40, 22.87s/it]
- 50%|█████     | 6/12 [02:17<02:17, 22.85s/it]
- 58%|█████▊    | 7/12 [02:40<01:54, 22.83s/it]
- 67%|██████▋   | 8/12 [03:03<01:31, 22.80s/it]
- 75%|███████▌  | 9/12 [03:25<01:08, 22.78s/it]
- 83%|████████▎ | 10/12 [03:48<00:45, 22.77s/it]
- 92%|█████████▏| 11/12 [04:11<00:22, 22.76s/it]
-100%|██████████| 12/12 [04:33<00:00, 22.75s/it]
-100%|██████████| 12/12 [04:33<00:00, 22.83s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 4: generating actions ...
->>> Step 4: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...
->>> Step 5: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 6: generating actions ...
->>> Step 6: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 7: generating actions ...
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -120,7 +89,42 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+  8%|▊         | 1/12 [01:14<13:34, 74.06s/it]
+ 17%|█▋        | 2/12 [02:27<12:17, 73.74s/it]
+ 25%|██▌       | 3/12 [03:40<10:59, 73.23s/it]
+ 33%|███▎      | 4/12 [04:52<09:43, 72.94s/it]
+ 42%|████▏     | 5/12 [06:05<08:29, 72.81s/it]
+ 50%|█████     | 6/12 [07:17<07:16, 72.74s/it]
+ 58%|█████▊    | 7/12 [08:30<06:03, 72.68s/it]
+ 67%|██████▋   | 8/12 [09:42<04:50, 72.63s/it]
+ 75%|███████▌  | 9/12 [10:55<03:38, 72.72s/it]
+ 83%|████████▎ | 10/12 [12:09<02:25, 72.86s/it]
+ 92%|█████████▏| 11/12 [13:21<01:12, 72.75s/it]
+100%|██████████| 12/12 [14:33<00:00, 72.66s/it]
+100%|██████████| 12/12 [14:33<00:00, 72.83s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 4: generating actions ...
+>>> Step 4: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 5: generating actions ...
+>>> Step 5: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 6: generating actions ...
+>>> Step 6: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 7: generating actions ...
 >>> Step 7: interacting with world model ...
-DEBUG:PIL.Image:Importing PpmImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing PsdImagePlugin
+>>> Step 8: generating actions ...
-DEBUG:PIL.Image:Importing QoiImagePlugin
+>>> Step 8: interacting with world model ...

unitree_z1_stackbox/case3/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_z1_stackbox/case3/unitree_z1_stackbox_case3.mp4",
     "pred_video": "unitree_z1_stackbox/case3/output/inference/25_full_fs4.mp4",
-    "psnr": 49.489774674892764
+    "psnr": 45.127553229898034
 }

unitree_z1_stackbox/case3/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_z1_stackbox"
         --n_iter 12 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"

unitree_z1_stackbox/case4/output.log

@@ -1,16 +1,21 @@
-2026-02-11 18:59:09.688302: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+2026-02-12 00:08:05.532356: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-2026-02-11 18:59:09.737473: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
+2026-02-12 00:08:05.582134: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
-2026-02-11 18:59:09.737518: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
+2026-02-12 00:08:05.582180: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
-2026-02-11 18:59:09.738835: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
+2026-02-12 00:08:05.583503: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
-2026-02-11 18:59:09.746322: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-12 00:08:05.591049: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2026-02-11 18:59:10.660940: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-12 00:08:06.523218: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
->>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
+INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
->>> Prepared model loaded.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Diffusion backbone (model.model) converted to FP16.
+INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
->>> Projectors (image_proj_model, state_projector, action_projector) converted to FP16.
+AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
->>> Encoders (cond_stage_model, embedder) converted to FP16.
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+INFO:root:Loaded ViT-H-14 model config.
+INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
+>>> model checkpoint loaded.
+>>> Load pre-trained model ...
 INFO:root:***** Configing Data *****
 >>> unitree_z1_stackbox: 1 data samples loaded.
 >>> unitree_z1_stackbox: data stats loaded.
@@ -28,49 +33,13 @@ INFO:root:***** Configing Data *****
 >>> unitree_g1_pack_camera: data stats loaded.
 >>> unitree_g1_pack_camera: normalizer initiated.
 >>> Dataset is successfully loaded ...
-    ✓ KV fused: 66 attention layers
 >>> Generate 16 frames under each generation ...
 DEBUG:h5py._conv:Creating converter from 3 to 5
 DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
 DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
 DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
-
+
-  0%|          | 0/12 [00:00<?, ?it/s]
   0%|          | 0/12 [00:00<?, ?it/s]>>> Step 0: generating actions ...
- 17%|█▋        | 2/12 [00:46<03:50, 23.01s/it]
- 25%|██▌       | 3/12 [01:09<03:26, 22.96s/it]
- 33%|███▎      | 4/12 [01:31<03:03, 22.92s/it]
- 42%|████▏     | 5/12 [01:54<02:40, 22.86s/it]
- 50%|█████     | 6/12 [02:17<02:16, 22.82s/it]
- 58%|█████▊    | 7/12 [02:40<01:53, 22.79s/it]
- 67%|██████▋   | 8/12 [03:02<01:31, 22.77s/it]
- 75%|███████▌  | 9/12 [03:25<01:08, 22.77s/it]
- 83%|████████▎ | 10/12 [03:48<00:45, 22.78s/it]
- 92%|█████████▏| 11/12 [04:11<00:22, 22.77s/it]
-100%|██████████| 12/12 [04:33<00:00, 22.77s/it]
-100%|██████████| 12/12 [04:33<00:00, 22.83s/it]
->>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 1: generating actions ...
->>> Step 1: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 2: generating actions ...
->>> Step 2: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 3: generating actions ...
->>> Step 3: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 4: generating actions ...
->>> Step 4: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...
->>> Step 5: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 6: generating actions ...
->>> Step 6: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 7: generating actions ...
 >>> Step 0: interacting with world model ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
 DEBUG:PIL.Image:Importing BmpImagePlugin
@@ -120,7 +89,42 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
 DEBUG:PIL.Image:Importing XpmImagePlugin
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
+
+  8%|▊         | 1/12 [01:13<13:30, 73.69s/it]
+ 17%|█▋        | 2/12 [02:26<12:12, 73.23s/it]
+ 25%|██▌       | 3/12 [03:40<11:02, 73.59s/it]
+ 33%|███▎      | 4/12 [04:54<09:50, 73.76s/it]
+ 42%|████▏     | 5/12 [06:07<08:34, 73.51s/it]
+ 50%|█████     | 6/12 [07:20<07:19, 73.19s/it]
+ 58%|█████▊    | 7/12 [08:32<06:04, 72.98s/it]
+ 67%|██████▋   | 8/12 [09:45<04:51, 72.85s/it]
+ 75%|███████▌  | 9/12 [10:57<03:38, 72.76s/it]
+ 83%|████████▎ | 10/12 [12:10<02:25, 72.69s/it]
+ 92%|█████████▏| 11/12 [13:23<01:12, 72.66s/it]
+100%|██████████| 12/12 [14:35<00:00, 72.63s/it]
+100%|██████████| 12/12 [14:35<00:00, 72.97s/it]
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 1: generating actions ...
+>>> Step 1: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 2: generating actions ...
+>>> Step 2: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 3: generating actions ...
+>>> Step 3: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 4: generating actions ...
+>>> Step 4: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 5: generating actions ...
+>>> Step 5: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 6: generating actions ...
+>>> Step 6: interacting with world model ...
+>>>>>>>>>>>>>>>>>>>>>>>>
+>>> Step 7: generating actions ...
 >>> Step 7: interacting with world model ...
-DEBUG:PIL.Image:Importing PpmImagePlugin
+>>>>>>>>>>>>>>>>>>>>>>>>
-DEBUG:PIL.Image:Importing PsdImagePlugin
+>>> Step 8: generating actions ...
-DEBUG:PIL.Image:Importing QoiImagePlugin
+>>> Step 8: interacting with world model ...

unitree_z1_stackbox/case4/psnr_result.json

@@ -1,5 +1,5 @@
 {
     "gt_video": "unitree_z1_stackbox/case4/unitree_z1_stackbox_case4.mp4",
     "pred_video": "unitree_z1_stackbox/case4/output/inference/35_full_fs4.mp4",
-    "psnr": 47.18724378194084
+    "psnr": 50.642542240144444
 }

unitree_z1_stackbox/case4/run_world_model_interaction.sh

@@ -20,6 +20,5 @@ dataset="unitree_z1_stackbox"
         --n_iter 12 \
         --timestep_spacing 'uniform_trailing' \
         --guidance_rescale 0.7 \
-        --perframe_ae \
+        --perframe_ae
-        --fast_policy_no_decode
 } 2>&1 | tee "${res_dir}/output.log"