KV 融合实现完成。改动总结： 速度微弱提升psnr略微上升

attention.py — 3处改动：
  1. __init__ 添加 _kv_fused = False 标志
  2.新增 fuse_kv() 方法：将 to_k + to_v → to_kv，同时处理 _ip/_as/_aa 辅助 KV 对
  2. bmm_forward 两个分支加_kv_fused 判断，用to_kv().chunk(2, dim=-1) 替代分别调用

.claude/settings.local.json

@@ -0,0 +1,15 @@
+{
+  "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:*)"
+    ]
+  }
+}

.envrc

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

.gitignore

@@ -55,7 +55,6 @@ coverage.xml
 *.pot
 
 # Django stuff:
-
 local_settings.py
 db.sqlite3
 
@@ -121,11 +120,15 @@ 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

@@ -0,0 +1,439 @@
+Attribution-NonCommercial-ShareAlike 4.0 International
+
+Copyright (c) 2016-2025 HangZhou YuShu TECHNOLOGY CO.,LTD. ("Unitree Robotics")
+
+=======================================================================
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ckpts/README.md

@@ -0,0 +1,38 @@
+---
+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_case.sh

@@ -1,114 +0,0 @@
-#!/bin/bash
-
-# 自动执行所有场景的所有case
-# 总共5个场景，每个场景4个case，共20个case
-# 设置环境变量（离线模式）
-export HF_HUB_OFFLINE=1
-export TRANSFORMERS_OFFLINE=1
-
-# 颜色定义
-RED='\033[0;31m'
-GREEN='\033[0;32m'
-YELLOW='\033[1;33m'
-BLUE='\033[0;34m'
-NC='\033[0m' # No Color
-
-# 定义所有场景
-SCENARIOS=(
-    "unitree_g1_pack_camera"
-    "unitree_z1_dual_arm_cleanup_pencils"
-    "unitree_z1_dual_arm_stackbox"
-    "unitree_z1_dual_arm_stackbox_v2"
-    "unitree_z1_stackbox"
-)
-
-# 定义case数量
-CASES=(1 2 3 4)
-
-# 记录开始时间
-START_TIME=$(date +%s)
-LOG_FILE="run_all_cases_$(date +%Y%m%d_%H%M%S).log"
-
-echo -e "${BLUE}========================================${NC}"
-echo -e "${BLUE}开始执行所有场景的case${NC}"
-echo -e "${BLUE}总共: ${#SCENARIOS[@]} 个场景 x ${#CASES[@]} 个case = $((${#SCENARIOS[@]} * ${#CASES[@]})) 个任务${NC}"
-echo -e "${BLUE}日志文件: ${LOG_FILE}${NC}"
-echo -e "${BLUE}========================================${NC}"
-echo ""
-
-# 初始化计数器
-TOTAL_CASES=$((${#SCENARIOS[@]} * ${#CASES[@]}))
-CURRENT_CASE=0
-SUCCESS_COUNT=0
-FAIL_COUNT=0
-
-# 记录失败的case
-declare -a FAILED_CASES
-
-# 遍历所有场景
-for scenario in "${SCENARIOS[@]}"; do
-    echo -e "${YELLOW}>>> 场景: ${scenario}${NC}"
-
-    # 遍历所有case
-    for case_num in "${CASES[@]}"; do
-        CURRENT_CASE=$((CURRENT_CASE + 1))
-        case_dir="${scenario}/case${case_num}"
-        script_path="${case_dir}/run_world_model_interaction.sh"
-
-        echo -e "${BLUE}[${CURRENT_CASE}/${TOTAL_CASES}] 执行: ${case_dir}${NC}"
-
-        # 检查脚本是否存在
-        if [ ! -f "${script_path}" ]; then
-            echo -e "${RED}错误: 脚本不存在 ${script_path}${NC}"
-            FAIL_COUNT=$((FAIL_COUNT + 1))
-            FAILED_CASES+=("${case_dir} (脚本不存在)")
-            continue
-        fi
-
-        # 执行脚本
-        echo "开始时间: $(date '+%Y-%m-%d %H:%M:%S')"
-
-        if bash "${script_path}" >> "${LOG_FILE}" 2>&1; then
-            echo -e "${GREEN}✓ 成功: ${case_dir}${NC}"
-            SUCCESS_COUNT=$((SUCCESS_COUNT + 1))
-        else
-            echo -e "${RED}✗ 失败: ${case_dir}${NC}"
-            FAIL_COUNT=$((FAIL_COUNT + 1))
-            FAILED_CASES+=("${case_dir}")
-        fi
-
-        echo "结束时间: $(date '+%Y-%m-%d %H:%M:%S')"
-        echo ""
-    done
-
-    echo ""
-done
-
-# 计算总耗时
-END_TIME=$(date +%s)
-DURATION=$((END_TIME - START_TIME))
-HOURS=$((DURATION / 3600))
-MINUTES=$(((DURATION % 3600) / 60))
-SECONDS=$((DURATION % 60))
-
-# 输出总结
-echo -e "${BLUE}========================================${NC}"
-echo -e "${BLUE}执行完成！${NC}"
-echo -e "${BLUE}========================================${NC}"
-echo -e "总任务数: ${TOTAL_CASES}"
-echo -e "${GREEN}成功: ${SUCCESS_COUNT}${NC}"
-echo -e "${RED}失败: ${FAIL_COUNT}${NC}"
-echo -e "总耗时: ${HOURS}小时 ${MINUTES}分钟 ${SECONDS}秒"
-echo -e "详细日志: ${LOG_FILE}"
-echo ""
-
-# 如果有失败的case，列出来
-if [ ${FAIL_COUNT} -gt 0 ]; then
-    echo -e "${RED}失败的case列表:${NC}"
-    for failed_case in "${FAILED_CASES[@]}"; do
-        echo -e "${RED}  - ${failed_case}${NC}"
-    done
-    echo ""
-fi
-
-echo -e "${BLUE}========================================${NC}"

run_all_psnr.sh

@@ -1,61 +0,0 @@
-#!/bin/bash
-set -e
-
-SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
-cd "$SCRIPT_DIR"
-
-SCENARIOS=(
-    unitree_g1_pack_camera
-    unitree_z1_dual_arm_cleanup_pencils
-    unitree_z1_dual_arm_stackbox
-    unitree_z1_dual_arm_stackbox_v2
-    unitree_z1_stackbox
-)
-
-CASES=(case1 case2 case3 case4)
-
-total=0
-success=0
-fail=0
-
-for scenario in "${SCENARIOS[@]}"; do
-    for case in "${CASES[@]}"; do
-        case_dir="${scenario}/${case}"
-        gt_video="${case_dir}/${scenario}_${case}.mp4"
-        pred_video=$(ls "${case_dir}"/output/inference/*_full_fs*.mp4 2>/dev/null | head -1)
-        output_file="${case_dir}/psnr_result.json"
-
-        total=$((total + 1))
-        echo "=========================================="
-        echo "[${total}/20] ${case_dir}"
-
-        if [ ! -f "$gt_video" ]; then
-            echo "  SKIP: GT video not found: $gt_video"
-            fail=$((fail + 1))
-            continue
-        fi
-        if [ -z "$pred_video" ]; then
-            echo "  SKIP: pred video not found in ${case_dir}/output/inference/"
-            fail=$((fail + 1))
-            continue
-        fi
-
-        echo "  GT:   $gt_video"
-        echo "  Pred: $pred_video"
-        echo "  Out:  $output_file"
-
-        if python3 psnr_score_for_challenge.py \
-            --gt_video "$gt_video" \
-            --pred_video "$pred_video" \
-            --output_file "$output_file"; then
-            success=$((success + 1))
-            echo "  DONE"
-        else
-            fail=$((fail + 1))
-            echo "  FAILED"
-        fi
-    done
-done
-
-echo "=========================================="
-echo "Finished: ${success} success, ${fail} fail, ${total} total"

scripts/evaluation/base_model_inference.py

@@ -16,6 +16,9 @@ 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

@@ -19,6 +19,9 @@ 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

@@ -9,6 +9,8 @@ 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
@@ -16,8 +18,12 @@ from tqdm import tqdm
 from einops import rearrange, repeat
 from collections import OrderedDict
 from torch import nn
-from eval_utils import populate_queues, log_to_tensorboard
+from eval_utils import populate_queues
 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
@@ -150,6 +156,81 @@ 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.
 
@@ -327,7 +408,8 @@ def image_guided_synthesis_sim_mode(
         timestep_spacing: str = 'uniform',
         guidance_rescale: float = 0.0,
         sim_mode: bool = True,
-        **kwargs) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+        decode_video: bool = True,
+        **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).
 
@@ -350,10 +432,13 @@ 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): Predicted pixel-space video frames [B, C, T, H, W].
+        batch_variants (torch.Tensor | None): 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.
     """
@@ -406,6 +491,7 @@ def image_guided_synthesis_sim_mode(
     kwargs.update({"unconditional_conditioning_img_nonetext": None})
     cond_mask = None
     cond_z0 = None
+    batch_variants = None
     if ddim_sampler is not None:
         samples, actions, states, intermedia = ddim_sampler.sample(
             S=ddim_steps,
@@ -424,9 +510,10 @@ def image_guided_synthesis_sim_mode(
             guidance_rescale=guidance_rescale,
             **kwargs)
 
-        # Reconstruct from latent to pixel space
+        if decode_video:
-        batch_images = model.decode_first_stage(samples)
+            # Reconstruct from latent to pixel space
-        batch_variants = batch_images
+            batch_images = model.decode_first_stage(samples)
+            batch_variants = batch_images
 
     return batch_variants, actions, states
 
@@ -453,26 +540,51 @@ 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
+    # Load config (always needed for data setup)
     config = OmegaConf.load(args.config)
-    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()
-    print(f'>>> Load pre-trained model ...')
 
-    # Build unnomalizer
+    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
+        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).")
+
+    # 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
@@ -587,7 +699,8 @@ 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])):
@@ -644,29 +757,31 @@ 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
+                # Save the imagen videos for decision-making (async)
-                sample_tag = f"{args.dataset}-vid{sample['videoid']}-dm-fs-{fs}/itr-{itr}"
+                if pred_videos_0 is not None:
-                log_to_tensorboard(writer,
+                    sample_tag = f"{args.dataset}-vid{sample['videoid']}-dm-fs-{fs}/itr-{itr}"
-                                   pred_videos_0,
+                    log_to_tensorboard_async(writer,
-                                   sample_tag,
+                                             pred_videos_0,
-                                   fps=args.save_fps)
+                                             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,
+                log_to_tensorboard_async(writer,
-                                   pred_videos_1,
+                                         pred_videos_1,
-                                   sample_tag,
+                                         sample_tag,
-                                   fps=args.save_fps)
+                                         fps=args.save_fps)
 
                 # Save the imagen videos for decision-making
-                sample_video_file = f'{video_save_dir}/dm/{fs}/itr-{itr}.mp4'
+                if pred_videos_0 is not None:
-                save_results(pred_videos_0.cpu(),
+                    sample_video_file = f'{video_save_dir}/dm/{fs}/itr-{itr}.mp4'
-                             sample_video_file,
+                    save_results_async(pred_videos_0,
-                             fps=args.save_fps)
+                                       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(),
+                save_results_async(pred_videos_1,
-                             sample_video_file,
+                                   sample_video_file,
-                             fps=args.save_fps)
+                                   fps=args.save_fps)
 
                 print('>' * 24)
                 # Collect the result of world-model interactions
@@ -674,12 +789,15 @@ def run_inference(args: argparse.Namespace, gpu_num: int, gpu_no: int) -> None:
 
             full_video = torch.cat(wm_video, dim=2)
             sample_tag = f"{args.dataset}-vid{sample['videoid']}-wd-fs-{fs}/full"
-            log_to_tensorboard(writer,
+            log_to_tensorboard_async(writer,
-                               full_video,
+                                     full_video,
-                               sample_tag,
+                                     sample_tag,
-                               fps=args.save_fps)
+                                     fps=args.save_fps)
             sample_full_video_file = f"{video_save_dir}/../{sample['videoid']}_full_fs{fs}.mp4"
-            save_results(full_video, sample_full_video_file, fps=args.save_fps)
+            save_results_async(full_video, sample_full_video_file, fps=args.save_fps)
+
+    # Wait for all async I/O to complete
+    _flush_io()
 
 
 def get_parser():
@@ -794,6 +912,11 @@ 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=False,
+        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

@@ -11,6 +11,9 @@ 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/diffusion_head/conditional_unet1d.py

@@ -501,6 +501,10 @@ 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],
@@ -530,14 +534,20 @@ class ConditionalUnet1D(nn.Module):
         B, T, D = sample.shape
         if self.use_linear_act_proj:
             sample = self.proj_in_action(sample.unsqueeze(-1))
-            global_cond = self.obs_encoder(cond)
+            _gc_key = (cond['image'].data_ptr(), cond['agent_pos'].data_ptr())
-            global_cond = rearrange(global_cond,
+            if self._global_cond_cache_enabled and _gc_key in self._global_cond_cache:
-                                    '(b t) d -> b 1 (t d)',
+                global_cond = self._global_cond_cache[_gc_key]
-                                    b=B,
+            else:
-                                    t=self.n_obs_steps)
+                global_cond = self.obs_encoder(cond)
-            global_cond = repeat(global_cond,
+                global_cond = rearrange(global_cond,
-                                 'b c d -> b (repeat c) d',
+                                        '(b t) d -> b 1 (t d)',
-                                 repeat=T)
+                                        b=B,
+                                        t=self.n_obs_steps)
+                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

@@ -6,6 +6,8 @@ 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):
@@ -67,11 +69,12 @@ class DDIMSampler(object):
             ddim_timesteps=self.ddim_timesteps,
             eta=ddim_eta,
             verbose=verbose)
-        self.register_buffer('ddim_sigmas', ddim_sigmas)
+        # Ensure tensors are on correct device for efficient indexing
-        self.register_buffer('ddim_alphas', ddim_alphas)
+        self.register_buffer('ddim_sigmas', to_torch(torch.as_tensor(ddim_sigmas)))
-        self.register_buffer('ddim_alphas_prev', ddim_alphas_prev)
+        self.register_buffer('ddim_alphas', to_torch(torch.as_tensor(ddim_alphas)))
+        self.register_buffer('ddim_alphas_prev', to_torch(torch.as_tensor(ddim_alphas_prev)))
         self.register_buffer('ddim_sqrt_one_minus_alphas',
-                             np.sqrt(1. - ddim_alphas))
+                             to_torch(torch.as_tensor(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))
@@ -241,63 +244,70 @@ class DDIMSampler(object):
 
         dp_ddim_scheduler_action.set_timesteps(len(timesteps))
         dp_ddim_scheduler_state.set_timesteps(len(timesteps))
-        for i, step in enumerate(iterator):
+        ts = torch.empty((b, ), device=device, dtype=torch.long)
-            index = total_steps - i - 1
+        enable_cross_attn_kv_cache(self.model)
-            ts = torch.full((b, ), step, device=device, dtype=torch.long)
+        enable_ctx_cache(self.model)
+        try:
+            for i, step in enumerate(iterator):
+                index = total_steps - i - 1
+                ts.fill_(step)
 
-            # Use mask to blend noised original latent (img_orig) & new sampled latent (img)
+                # Use mask to blend noised original latent (img_orig) & new sampled latent (img)
-            if mask is not None:
+                if mask is not None:
-                assert x0 is not None
+                    assert x0 is not None
-                if clean_cond:
+                    if clean_cond:
-                    img_orig = x0
+                        img_orig = x0
-                else:
+                    else:
-                    img_orig = self.model.q_sample(x0, ts)
+                        img_orig = self.model.q_sample(x0, ts)
-                img = img_orig * mask + (1. - mask) * img
+                    img = img_orig * mask + (1. - mask) * img
 
-            outs = self.p_sample_ddim(
+                outs = self.p_sample_ddim(
-                img,
+                    img,
-                action,
+                    action,
-                state,
+                    state,
-                cond,
+                    cond,
-                ts,
+                    ts,
-                index=index,
+                    index=index,
-                use_original_steps=ddim_use_original_steps,
+                    use_original_steps=ddim_use_original_steps,
-                quantize_denoised=quantize_denoised,
+                    quantize_denoised=quantize_denoised,
-                temperature=temperature,
+                    temperature=temperature,
-                noise_dropout=noise_dropout,
+                    noise_dropout=noise_dropout,
-                score_corrector=score_corrector,
+                    score_corrector=score_corrector,
-                corrector_kwargs=corrector_kwargs,
+                    corrector_kwargs=corrector_kwargs,
-                unconditional_guidance_scale=unconditional_guidance_scale,
+                    unconditional_guidance_scale=unconditional_guidance_scale,
-                unconditional_conditioning=unconditional_conditioning,
+                    unconditional_conditioning=unconditional_conditioning,
-                mask=mask,
+                    mask=mask,
-                x0=x0,
+                    x0=x0,
-                fs=fs,
+                    fs=fs,
-                guidance_rescale=guidance_rescale,
+                    guidance_rescale=guidance_rescale,
-                **kwargs)
+                    **kwargs)
 
-            img, pred_x0, model_output_action, model_output_state = outs
+                img, pred_x0, model_output_action, model_output_state = outs
 
-            action = dp_ddim_scheduler_action.step(
+                action = dp_ddim_scheduler_action.step(
-                model_output_action,
+                    model_output_action,
-                step,
+                    step,
-                action,
+                    action,
-                generator=None,
+                    generator=None,
-            ).prev_sample
+                ).prev_sample
-            state = dp_ddim_scheduler_state.step(
+                state = dp_ddim_scheduler_state.step(
-                model_output_state,
+                    model_output_state,
-                step,
+                    step,
-                state,
+                    state,
-                generator=None,
+                    generator=None,
-            ).prev_sample
+                ).prev_sample
 
-            if callback: callback(i)
+                if callback: callback(i)
-            if img_callback: img_callback(pred_x0, i)
+                if img_callback: img_callback(pred_x0, i)
 
-            if index % log_every_t == 0 or index == total_steps - 1:
+                if index % log_every_t == 0 or index == total_steps - 1:
-                intermediates['x_inter'].append(img)
+                    intermediates['x_inter'].append(img)
-                intermediates['pred_x0'].append(pred_x0)
+                    intermediates['pred_x0'].append(pred_x0)
-                intermediates['x_inter_action'].append(action)
+                    intermediates['x_inter_action'].append(action)
-                intermediates['x_inter_state'].append(state)
+                    intermediates['x_inter_state'].append(state)
+        finally:
+            disable_cross_attn_kv_cache(self.model)
+            disable_ctx_cache(self.model)
 
         return img, action, state, intermediates
 
@@ -325,10 +335,6 @@ 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(
@@ -377,17 +383,11 @@ 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
 
-        if is_video:
+        # Use 0-d tensors directly (already on device); broadcasting handles shape
-            size = (b, 1, 1, 1, 1)
+        a_t = alphas[index]
-        else:
+        a_prev = alphas_prev[index]
-            size = (b, 1, 1, 1)
+        sigma_t = sigmas[index]
-
+        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()
@@ -395,12 +395,8 @@ 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 = torch.full(size,
+            scale_t = self.ddim_scale_arr[index]
-                                 self.ddim_scale_arr[index],
+            prev_scale_t = self.ddim_scale_arr_prev[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

@@ -98,6 +98,10 @@ 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)
@@ -114,6 +118,27 @@ 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
@@ -140,19 +165,28 @@ class CrossAttention(nn.Module):
                                     self.agent_action_context_len +
                                     self.text_context_len:, :]
 
-            k = self.to_k(context_ins)
+            if self._kv_fused:
-            v = self.to_v(context_ins)
+                k, v = self.to_kv(context_ins).chunk(2, dim=-1)
-            k_ip = self.to_k_ip(context_image)
+                k_ip, v_ip = self.to_kv_ip(context_image).chunk(2, dim=-1)
-            v_ip = self.to_v_ip(context_image)
+                k_as, v_as = self.to_kv_as(context_agent_state).chunk(2, dim=-1)
-            k_as = self.to_k_as(context_agent_state)
+                k_aa, v_aa = self.to_kv_aa(context_agent_action).chunk(2, dim=-1)
-            v_as = self.to_v_as(context_agent_state)
+            else:
-            k_aa = self.to_k_aa(context_agent_action)
+                k = self.to_k(context_ins)
-            v_aa = self.to_v_aa(context_agent_action)
+                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_aa = self.to_k_aa(context_agent_action)
+                v_aa = self.to_v_aa(context_agent_action)
         else:
             if not spatial_self_attn:
                 context = context[:, :self.text_context_len, :]
-            k = self.to_k(context)
+            if self._kv_fused:
-            v = self.to_v(context)
+                k, v = self.to_kv(context).chunk(2, dim=-1)
+            else:
+                k = self.to_k(context)
+                v = self.to_v(context)
 
         q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h),
                       (q, k, v))
@@ -236,134 +270,162 @@ 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)
 
-        if self.image_cross_attention and not spatial_self_attn:
+        b, _, _ = q.shape
+        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:, :]
-                k = self.to_k(context)
+                if self._kv_fused:
-                v = self.to_v(context)
+                    k, v = self.to_kv(context).chunk(2, dim=-1)
-                k_ip = self.to_k_ip(context_image)
+                    k_ip, v_ip = self.to_kv_ip(context_image).chunk(2, dim=-1)
-                v_ip = self.to_v_ip(context_image)
+                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:, :]
-                k = self.to_k(context_ins)
+                if self._kv_fused:
-                v = self.to_v(context_ins)
+                    k, v = self.to_kv(context_ins).chunk(2, dim=-1)
-                k_ip = self.to_k_ip(context_image)
+                    k_ip, v_ip = self.to_kv_ip(context_image).chunk(2, dim=-1)
-                v_ip = self.to_v_ip(context_image)
+                    k_as, v_as = self.to_kv_as(context_agent_state).chunk(2, dim=-1)
-                k_as = self.to_k_as(context_agent_state)
+                else:
-                v_as = self.to_v_as(context_agent_state)
+                    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:, :]
 
-                k = self.to_k(context_ins)
+                if self._kv_fused:
-                v = self.to_v(context_ins)
+                    k, v = self.to_kv(context_ins).chunk(2, dim=-1)
-                k_ip = self.to_k_ip(context_image)
+                    k_ip, v_ip = self.to_kv_ip(context_image).chunk(2, dim=-1)
-                v_ip = self.to_v_ip(context_image)
+                    k_as, v_as = self.to_kv_as(context_agent_state).chunk(2, dim=-1)
-                k_as = self.to_k_as(context_agent_state)
+                    k_aa, v_aa = self.to_kv_aa(context_agent_action).chunk(2, dim=-1)
-                v_as = self.to_v_as(context_agent_state)
+                else:
-                k_aa = self.to_k_aa(context_agent_action)
+                    k = self.to_k(context_ins)
-                v_aa = self.to_v_aa(context_agent_action)
+                    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_aa = self.to_k_aa(context_agent_action)
+                    v_aa = self.to_v_aa(context_agent_action)
 
-                attn_mask_aa = self._get_attn_mask_aa(x.shape[0],
+                k, v = map(_reshape_kv, (k, v))
-                                                      q.shape[1],
+                k_ip, v_ip = map(_reshape_kv, (k_ip, v_ip))
-                                                      k_aa.shape[1],
+                k_as, v_as = map(_reshape_kv, (k_as, v_as))
-                                                      block_size=16).to(k_aa.device)
+                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,
+                                                          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, :]
-            k = self.to_k(context)
+            if self._kv_fused:
-            v = self.to_v(context)
+                k, v = self.to_kv(context).chunk(2, dim=-1)
-
+            else:
-        b, _, _ = q.shape
+                k = self.to_k(context)
-        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()
+                v = self.to_v(context)
+            k, v = map(_reshape_kv, (k, v))
+            if use_cache:
+                self._kv_cache = {'k': k, 'v': v}
         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, self.heads, out.shape[1],
+                b, h, out.shape[1],
                 self.dim_head).permute(0, 2, 1,
                                        3).reshape(b, out.shape[1],
-                                                  self.heads * self.dim_head))
+                                                  h * 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, self.heads, out_ip.shape[1],
+                b, h, out_ip.shape[1],
                 self.dim_head).permute(0, 2, 1,
                                        3).reshape(b, out_ip.shape[1],
-                                                  self.heads * self.dim_head))
+                                                  h * 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, self.heads, out_as.shape[1],
+                b, h, out_as.shape[1],
                 self.dim_head).permute(0, 2, 1,
                                        3).reshape(b, out_as.shape[1],
-                                                  self.heads * self.dim_head))
+                                                  h * 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, self.heads, out_aa.shape[1],
+                b, h, out_aa.shape[1],
                 self.dim_head).permute(0, 2, 1,
                                        3).reshape(b, out_aa.shape[1],
-                                                  self.heads * self.dim_head))
+                                                  h * self.dim_head))
         if exists(mask):
             raise NotImplementedError
 
@@ -386,17 +448,43 @@ class CrossAttention(nn.Module):
 
         return self.to_out(out)
 
-    def _get_attn_mask_aa(self, b, l1, l2, block_size=16):
+    def _get_attn_mask_aa(self, b, l1, l2, block_size=16, device=None):
+        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) % block_size) + 1) * num_token
+        start_positions = ((torch.arange(b, device=target_device) % block_size) + 1) * num_token
-        col_indices = torch.arange(l2)
+        col_indices = torch.arange(l2, device=target_device)
         mask_2d = col_indices.unsqueeze(0) >= start_positions.unsqueeze(1)
         mask = mask_2d.unsqueeze(1).expand(b, l1, l2)
-        attn_mask = torch.zeros_like(mask, dtype=torch.float)
+        attn_mask = torch.zeros(b, l1, l2, dtype=torch.float, device=target_device)
         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

@@ -685,6 +685,21 @@ 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,
@@ -720,58 +735,64 @@ class WMAModel(nn.Module):
                                    repeat_only=False).type(x.dtype)
         emb = self.time_embed(t_emb)
 
-        bt, l_context, _ = context.shape
+        _ctx_key = context.data_ptr()
-        if self.base_model_gen_only:
+        if self._ctx_cache_enabled and _ctx_key in self._ctx_cache:
-            assert l_context == 77 + self.n_obs_steps * 16, ">>> ERROR Context dim 1 ..."  ## NOTE HANDCODE
+            context = self._ctx_cache[_ctx_key]
         else:
-            if l_context == self.n_obs_steps + 77 + t * 16:
+            bt, l_context, _ = context.shape
-                context_agent_state = context[:, :self.n_obs_steps]
+            if self.base_model_gen_only:
-                context_text = context[:, self.n_obs_steps:self.n_obs_steps +
+                assert l_context == 77 + self.n_obs_steps * 16, ">>> ERROR Context dim 1 ..."  ## NOTE HANDCODE
-                                       77, :]
+            else:
-                context_img = context[:, self.n_obs_steps + 77:, :]
+                if l_context == self.n_obs_steps + 77 + t * 16:
-                context_agent_state = context_agent_state.repeat_interleave(
+                    context_agent_state = context[:, :self.n_obs_steps]
-                    repeats=t, dim=0)
+                    context_text = context[:, self.n_obs_steps:self.n_obs_steps +
-                context_text = context_text.repeat_interleave(repeats=t, dim=0)
+                                           77, :]
-                context_img = rearrange(context_img,
+                    context_img = context[:, self.n_obs_steps + 77:, :]
-                                        'b (t l) c -> (b t) l c',
+                    context_agent_state = context_agent_state.repeat_interleave(
-                                        t=t)
+                        repeats=t, dim=0)
-                context = torch.cat(
+                    context_text = context_text.repeat_interleave(repeats=t, dim=0)
-                    [context_agent_state, context_text, context_img], dim=1)
+                    context_img = rearrange(context_img,
-            elif l_context == self.n_obs_steps + 16 + 77 + t * 16:
+                                            'b (t l) c -> (b t) l c',
-                context_agent_state = context[:, :self.n_obs_steps]
+                                            t=t)
-                context_agent_action = context[:, self.
+                    context = torch.cat(
-                                               n_obs_steps:self.n_obs_steps +
+                        [context_agent_state, context_text, context_img], dim=1)
-                                               16, :]
+                elif l_context == self.n_obs_steps + 16 + 77 + t * 16:
-                context_agent_action = rearrange(
+                    context_agent_state = context[:, :self.n_obs_steps]
-                    context_agent_action.unsqueeze(2), 'b t l d -> (b t) l d')
+                    context_agent_action = context[:, self.
-                context_agent_action = self.action_token_projector(
+                                                   n_obs_steps:self.n_obs_steps +
-                    context_agent_action)
+                                                   16, :]
-                context_agent_action = rearrange(context_agent_action,
+                    context_agent_action = rearrange(
-                                                 '(b o) l d -> b o l d',
+                        context_agent_action.unsqueeze(2), 'b t l d -> (b t) l d')
-                                                 o=t)
+                    context_agent_action = self.action_token_projector(
-                context_agent_action = rearrange(context_agent_action,
+                        context_agent_action)
-                                                 'b o (t l) d -> b o t l d',
+                    context_agent_action = rearrange(context_agent_action,
-                                                 t=t)
+                                                     '(b o) l d -> b o l d',
-                context_agent_action = context_agent_action.permute(
+                                                     o=t)
-                    0, 2, 1, 3, 4)
+                    context_agent_action = rearrange(context_agent_action,
-                context_agent_action = rearrange(context_agent_action,
+                                                     'b o (t l) d -> b o t l d',
-                                                 'b t o l d -> (b t) (o l) d')
+                                                     t=t)
+                    context_agent_action = context_agent_action.permute(
+                        0, 2, 1, 3, 4)
+                    context_agent_action = rearrange(context_agent_action,
+                                                     'b t o l d -> (b t) (o l) d')
 
-                context_text = context[:, self.n_obs_steps +
+                    context_text = context[:, self.n_obs_steps +
-                                       16:self.n_obs_steps + 16 + 77, :]
+                                           16:self.n_obs_steps + 16 + 77, :]
-                context_text = context_text.repeat_interleave(repeats=t, dim=0)
+                    context_text = context_text.repeat_interleave(repeats=t, dim=0)
 
-                context_img = context[:, self.n_obs_steps + 16 + 77:, :]
+                    context_img = context[:, self.n_obs_steps + 16 + 77:, :]
-                context_img = rearrange(context_img,
+                    context_img = rearrange(context_img,
-                                        'b (t l) c -> (b t) l c',
+                                            'b (t l) c -> (b t) l c',
-                                        t=t)
+                                            t=t)
-                context_agent_state = context_agent_state.repeat_interleave(
+                    context_agent_state = context_agent_state.repeat_interleave(
-                    repeats=t, dim=0)
+                        repeats=t, dim=0)
-                context = torch.cat([
+                    context = torch.cat([
-                    context_agent_state, context_agent_action, context_text,
+                        context_agent_state, context_agent_action, context_text,
-                    context_img
+                        context_img
-                ],
+                    ],
-                                    dim=1)
+                                        dim=1)
+            if self._ctx_cache_enabled:
+                self._ctx_cache[_ctx_key] = context
 
         emb = emb.repeat_interleave(repeats=t, dim=0)
 
@@ -832,17 +853,45 @@ 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)
-            # Predict state
+            torch.cuda.current_stream().wait_stream(s_stream)
-            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

@@ -1,127 +0,0 @@
-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 19:49:03.934263: 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 19:49:03.934309: 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 19:49:03.935622: 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 19:49:03.943041: 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 19:49:04.852993: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
-Global seed set to 123
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-DEBUG:PIL.Image:Importing WmfImagePlugin
-DEBUG:PIL.Image:Importing XbmImagePlugin
-DEBUG:PIL.Image:Importing XpmImagePlugin
-DEBUG:PIL.Image:Importing XVThumbImagePlugin
-
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->>>>>>>>>>>>>>>>>>>>>>>>
->>> 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 ...
->>>>>>>>>>>>>>>>>>>>>>>>

unitree_g1_pack_camera/case1/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "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": 35.615362167470806
-}

unitree_g1_pack_camera/case2/output.log

@@ -1,127 +0,0 @@
-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 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 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 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 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 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-DEBUG:PIL.Image:Importing WmfImagePlugin
-DEBUG:PIL.Image:Importing XbmImagePlugin
-DEBUG:PIL.Image:Importing XpmImagePlugin
-DEBUG:PIL.Image:Importing XVThumbImagePlugin
-
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->>>>>>>>>>>>>>>>>>>>>>>>
->>> 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 ...
->>>>>>>>>>>>>>>>>>>>>>>>

unitree_g1_pack_camera/case2/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "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": 34.61979248212279
-}

unitree_g1_pack_camera/case3/output.log

@@ -1,127 +0,0 @@
-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 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 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 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 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 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-DEBUG:PIL.Image:Importing WmfImagePlugin
-DEBUG:PIL.Image:Importing XbmImagePlugin
-DEBUG:PIL.Image:Importing XpmImagePlugin
-DEBUG:PIL.Image:Importing XVThumbImagePlugin
-
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->>>>>>>>>>>>>>>>>>>>>>>>
->>> 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 ...
->>>>>>>>>>>>>>>>>>>>>>>>

unitree_g1_pack_camera/case3/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "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": 37.034952654534486
-}

unitree_g1_pack_camera/case4/output.log

@@ -1,127 +0,0 @@
-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 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 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 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 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 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-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]
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->>>>>>>>>>>>>>>>>>>>>>>>
->>> 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 ...
->>>>>>>>>>>>>>>>>>>>>>>>

unitree_g1_pack_camera/case4/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "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": 31.43390896360405
-}

unitree_z1_dual_arm_cleanup_pencils/case1/output.log

@@ -1,18 +1,21 @@
-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`.
+2026-02-10 15:38:28.973314: 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 20:49:48.015942: 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
+2026-02-10 15:38:29.023024: 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 20:49:48.015997: 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
+2026-02-10 15:38:29.023070: 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 20:49:48.017330: 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
+2026-02-10 15:38:29.024393: 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 20:49:48.024854: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+2026-02-10 15:38:29.031901: 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 20:49:48.943205: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-10 15:38:29.955454: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
 INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
 INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
 INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
 AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
 INFO:root:Loaded ViT-H-14 model config.
+DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): hf-mirror.com:443
+DEBUG:urllib3.connectionpool:https://hf-mirror.com:443 "HEAD /laion/CLIP-ViT-H-14-laion2B-s32B-b79K/resolve/main/open_clip_pytorch_model.bin HTTP/1.1" 302 0
 INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
 INFO:root:Loaded ViT-H-14 model config.
+DEBUG:urllib3.connectionpool:https://hf-mirror.com:443 "HEAD /laion/CLIP-ViT-H-14-laion2B-s32B-b79K/resolve/main/open_clip_pytorch_model.bin HTTP/1.1" 302 0
 INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
 >>> model checkpoint loaded.
 >>> Load pre-trained model ...
@@ -89,7 +92,7 @@ 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
+DEBUG:PIL.Image:Importing XVThumbImagePlugin
 
  12%|█▎        | 1/8 [01:14<08:41, 74.51s/it]
  25%|██▌       | 2/8 [02:29<07:28, 74.79s/it]
@@ -113,6 +116,6 @@ DEBUG:PIL.Image:Importing XVThumbImagePlugin
 >>> Step 4: generating actions ...
 >>> Step 4: interacting with world model ...
 >>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...
+>>> Step 5: generating actions ...
->>> Step 5: interacting with world model ...
+>>> Step 5: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
+>>>>>>>>>>>>>>>>>>>>>>>>

unitree_z1_dual_arm_cleanup_pencils/case2/output.log

@@ -1,118 +0,0 @@
-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 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 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 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 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 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-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]
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->>>>>>>>>>>>>>>>>>>>>>>>
->>> 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 ...
->>>>>>>>>>>>>>>>>>>>>>>>

unitree_z1_dual_arm_cleanup_pencils/case2/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "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": 48.344571927558974
-}

unitree_z1_dual_arm_cleanup_pencils/case3/output.log

@@ -1,118 +0,0 @@
-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 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 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 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 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 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-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]
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-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 ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...
->>> Step 5: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>

unitree_z1_dual_arm_cleanup_pencils/case3/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "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": 41.152374490134825
-}

unitree_z1_dual_arm_cleanup_pencils/case4/output.log

@@ -1,118 +0,0 @@
-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 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 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 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 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 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-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]
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-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 ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...
->>> Step 5: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>

unitree_z1_dual_arm_cleanup_pencils/case4/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "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": 46.025723557253855
-}

unitree_z1_dual_arm_stackbox/case1/output.log

@@ -1,115 +0,0 @@
-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 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 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 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 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 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-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]
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->>>>>>>>>>>>>>>>>>>>>>>>
->>> 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 ...

unitree_z1_dual_arm_stackbox/case1/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "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": 44.3480149502738
-}

unitree_z1_dual_arm_stackbox/case2/output.log

@@ -1,115 +0,0 @@
-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 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 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 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 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 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-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]
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->>>>>>>>>>>>>>>>>>>>>>>>
->>> 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 ...

unitree_z1_dual_arm_stackbox/case2/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "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": 39.867728254007716
-}

unitree_z1_dual_arm_stackbox/case3/output.log

@@ -1,115 +0,0 @@
-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 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 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 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 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 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-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 ...
->>> Step 4: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...

unitree_z1_dual_arm_stackbox/case3/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "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": 39.19101039445159
-}

unitree_z1_dual_arm_stackbox/case4/output.log

@@ -1,115 +0,0 @@
-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 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 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 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 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 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-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]
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-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 ...
->>> Step 4: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 5: generating actions ...

unitree_z1_dual_arm_stackbox/case4/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "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": 40.29563315341769
-}

unitree_z1_dual_arm_stackbox_v2/case1/output.log

@@ -1,21 +1,13 @@
-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 11:59:27.241485: 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 22:18:17.446095: 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 11:59:27.291755: 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 22:18:17.446154: 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 11:59:27.291807: 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 22:18:17.447480: 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 11:59:27.293169: 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 22:18:17.455025: 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 11:59:27.300838: 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 22:18:18.367007: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2026-02-11 11:59:28.228009: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 Global seed set to 123
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
+>>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
+>>> Prepared model loaded.
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
@@ -33,13 +25,16 @@ 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]
+  9%|▉         | 1/11 [00:34<05:40, 34.05s/it]>>> Step 0: generating actions ...
+>>> Step 0: interacting with world model ...
 >>>>>>>>>>>>>>>>>>>>>>>>
 >>> Step 1: generating actions ...
 DEBUG:PIL.Image:Importing BlpImagePlugin
@@ -89,9 +84,7 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing WebPImagePlugin
 DEBUG:PIL.Image:Importing WmfImagePlugin
 DEBUG:PIL.Image:Importing XbmImagePlugin
-DEBUG:PIL.Image:Importing XVThumbImagePlugin
+DEBUG:PIL.Image:Importing XpmImagePlugin
-
-  9%|▉         | 1/11 [01:15<12:35, 75.53s/it]
 DEBUG:PIL.Image:Importing XVThumbImagePlugin
 
  18%|█▊        | 2/11 [01:08<05:07, 34.17s/it]
@@ -122,6 +115,6 @@ DEBUG:PIL.Image:Importing XVThumbImagePlugin
 >>> Step 6: generating actions ...
 >>> Step 6: interacting with world model ...
 >>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 7: generating actions ...
+>>> Step 7: generating actions ...
->>> Step 7: interacting with world model ...
+>>> Step 7: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>
+>>>>>>>>>>>>>>>>>>>>>>>>

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",
+    "gt_video": "/home/qhy/unifolm-world-model-action/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",
+    "pred_video": "/home/qhy/unifolm-world-model-action/unitree_z1_dual_arm_stackbox_v2/case1/output/inference/5_full_fs4.mp4",
-    "psnr": 25.812741419225095
+    "psnr": 28.167025381705358
 }

unitree_z1_dual_arm_stackbox_v2/case1/run_world_model_interaction.sh

@@ -20,5 +20,6 @@ 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

@@ -1,127 +0,0 @@
-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 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 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 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 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 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-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]
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-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 ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 7: generating actions ...
->>> Step 7: interacting with world model ...
->>>>>>>>>>>>>>>>>>>>>>>>

unitree_z1_dual_arm_stackbox_v2/case2/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "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": 33.90444714332389
-}

unitree_z1_dual_arm_stackbox_v2/case3/output.log

@@ -1,127 +0,0 @@
-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 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 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 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 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 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-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]
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->>>>>>>>>>>>>>>>>>>>>>>>
->>> 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 ...
->>>>>>>>>>>>>>>>>>>>>>>>

unitree_z1_dual_arm_stackbox_v2/case3/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "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": 34.50192428908007
-}

unitree_z1_dual_arm_stackbox_v2/case4/output.log

@@ -1,127 +0,0 @@
-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 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 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 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 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 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-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]
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->>>>>>>>>>>>>>>>>>>>>>>>
->>> 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 ...
->>>>>>>>>>>>>>>>>>>>>>>>

unitree_z1_dual_arm_stackbox_v2/case4/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "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": 38.797893493652516
-}

unitree_z1_stackbox/case1/output.log

@@ -1,130 +0,0 @@
-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 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 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 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 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 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-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]
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->>>>>>>>>>>>>>>>>>>>>>>>
->>> 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 ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 8: generating actions ...
->>> Step 8: interacting with world model ...

unitree_z1_stackbox/case1/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "gt_video": "unitree_z1_stackbox/case1/unitree_z1_stackbox_case1.mp4",
-    "pred_video": "unitree_z1_stackbox/case1/output/inference/5_full_fs4.mp4",
-    "psnr": 42.83913947323794
-}

unitree_z1_stackbox/case2/output.log

@@ -1,130 +0,0 @@
-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 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 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 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 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 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-DEBUG:PIL.Image:Importing WmfImagePlugin
-DEBUG:PIL.Image:Importing XbmImagePlugin
-DEBUG:PIL.Image:Importing XpmImagePlugin
-DEBUG:PIL.Image:Importing XVThumbImagePlugin
-
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->>>>>>>>>>>>>>>>>>>>>>>>
->>> 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 ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 8: generating actions ...
->>> Step 8: interacting with world model ...

unitree_z1_stackbox/case2/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "gt_video": "unitree_z1_stackbox/case2/unitree_z1_stackbox_case2.mp4",
-    "pred_video": "unitree_z1_stackbox/case2/output/inference/15_full_fs4.mp4",
-    "psnr": 48.64571989587276
-}

unitree_z1_stackbox/case3/output.log

@@ -1,130 +0,0 @@
-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 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 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 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 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 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-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]
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->>>>>>>>>>>>>>>>>>>>>>>>
->>> 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 ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 8: generating actions ...
->>> Step 8: interacting with world model ...

unitree_z1_stackbox/case3/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "gt_video": "unitree_z1_stackbox/case3/unitree_z1_stackbox_case3.mp4",
-    "pred_video": "unitree_z1_stackbox/case3/output/inference/25_full_fs4.mp4",
-    "psnr": 45.127553229898034
-}

unitree_z1_stackbox/case4/output.log

@@ -1,130 +0,0 @@
-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`.
-2026-02-12 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
-2026-02-12 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
-2026-02-12 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
-2026-02-12 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.
-2026-02-12 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
-INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
-AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
-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.
->>> 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 ...
->>> 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]>>> Step 0: generating actions ...
->>> Step 0: interacting with world model ...
-DEBUG:PIL.Image:Importing BlpImagePlugin
-DEBUG:PIL.Image:Importing BmpImagePlugin
-DEBUG:PIL.Image:Importing BufrStubImagePlugin
-DEBUG:PIL.Image:Importing CurImagePlugin
-DEBUG:PIL.Image:Importing DcxImagePlugin
-DEBUG:PIL.Image:Importing DdsImagePlugin
-DEBUG:PIL.Image:Importing EpsImagePlugin
-DEBUG:PIL.Image:Importing FitsImagePlugin
-DEBUG:PIL.Image:Importing FitsStubImagePlugin
-DEBUG:PIL.Image:Importing FliImagePlugin
-DEBUG:PIL.Image:Importing FpxImagePlugin
-DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing FtexImagePlugin
-DEBUG:PIL.Image:Importing GbrImagePlugin
-DEBUG:PIL.Image:Importing GifImagePlugin
-DEBUG:PIL.Image:Importing GribStubImagePlugin
-DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
-DEBUG:PIL.Image:Importing IcnsImagePlugin
-DEBUG:PIL.Image:Importing IcoImagePlugin
-DEBUG:PIL.Image:Importing ImImagePlugin
-DEBUG:PIL.Image:Importing ImtImagePlugin
-DEBUG:PIL.Image:Importing IptcImagePlugin
-DEBUG:PIL.Image:Importing JpegImagePlugin
-DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
-DEBUG:PIL.Image:Importing McIdasImagePlugin
-DEBUG:PIL.Image:Importing MicImagePlugin
-DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
-DEBUG:PIL.Image:Importing MpegImagePlugin
-DEBUG:PIL.Image:Importing MpoImagePlugin
-DEBUG:PIL.Image:Importing MspImagePlugin
-DEBUG:PIL.Image:Importing PalmImagePlugin
-DEBUG:PIL.Image:Importing PcdImagePlugin
-DEBUG:PIL.Image:Importing PcxImagePlugin
-DEBUG:PIL.Image:Importing PdfImagePlugin
-DEBUG:PIL.Image:Importing PixarImagePlugin
-DEBUG:PIL.Image:Importing PngImagePlugin
-DEBUG:PIL.Image:Importing PpmImagePlugin
-DEBUG:PIL.Image:Importing PsdImagePlugin
-DEBUG:PIL.Image:Importing QoiImagePlugin
-DEBUG:PIL.Image:Importing SgiImagePlugin
-DEBUG:PIL.Image:Importing SpiderImagePlugin
-DEBUG:PIL.Image:Importing SunImagePlugin
-DEBUG:PIL.Image:Importing TgaImagePlugin
-DEBUG:PIL.Image:Importing TiffImagePlugin
-DEBUG:PIL.Image:Importing WebPImagePlugin
-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]
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-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 ...
->>>>>>>>>>>>>>>>>>>>>>>>
->>> Step 8: generating actions ...
->>> Step 8: interacting with world model ...

unitree_z1_stackbox/case4/psnr_result.json

@@ -1,5 +0,0 @@
-{
-    "gt_video": "unitree_z1_stackbox/case4/unitree_z1_stackbox_case4.mp4",
-    "pred_video": "unitree_z1_stackbox/case4/output/inference/35_full_fs4.mp4",
-    "psnr": 50.642542240144444
-}