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trt-replac
| Author | SHA1 | Date | |
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| 68d695d81d | |||
| 65788be1b3 |
2
.gitignore
vendored
2
.gitignore
vendored
@@ -132,3 +132,5 @@ Experiment/log
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*.0
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*.0
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ckpts/unifolm_wma_dual.ckpt.prepared.pt
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ckpts/unifolm_wma_dual.ckpt.prepared.pt
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trt_engines/video_backbone.engine
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trt_engines/video_backbone.onnx
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208
record.md
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208
record.md
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@@ -0,0 +1,208 @@
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好，下面是完整的 decode 优化讲解。
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---
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背景：原始 decode 流程的问题
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原始代码中，每轮迭代的 world model 交互会调用 image_guided_synthesis_sim_mode，内部对DDIM 采样得到的 latent 做全量 VAE decode：
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# ddpms.py decode_core, perframe_ae=True
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for index in range(z.shape[0]): # 逐帧循环，16帧就调16次
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frame_z = 1. / self.scale_factor * z[index:index+1]
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frame_result = self.first_stage_model.decode(frame_z)
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results.append(frame_result)
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假设 8 轮迭代、每轮 16 帧，WM 路径 decode 128 次，policy 路径再 decode 128 次，共 256 次 VAE decode。每次都是同步阻塞的。
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decode 完的视频还会被逐轮写成 mp4 + tensorboard，产生大量磁盘 I/O。最后还要把所有轮的 decoded video 在内存中torch.cat
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拼接，再写一次完整视频。
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---
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优化1：decode_video 开关——按需跳过 decode
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文件： world_model_interaction.py函数 image_guided_synthesis_sim_mode
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改动： 给函数加decode_video 参数（默认 False），返回值增加 raw samples：
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def image_guided_synthesis_sim_mode(...,
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decode_video: bool = False, # 新增
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...) -> tuple[Tensor | None, Tensor, Tensor, Tensor | None]:
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samples = None
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if ddim_sampler is not None:
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samples, actions, states, intermedia = ddim_sampler.sample(...)if decode_video: # 条件 decode
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batch_images = model.decode_first_stage(samples)
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batch_variants = batch_images
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return batch_variants, actions, states, samples# 多返回 samples
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调用侧：
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- Policy 路径：由 CLI 参数 --fast_policy_no_decode 控制，只需要 action 时可跳过 decode
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- WM 交互路径：传decode_video=False，只拿 raw latent
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效果： WM 路径每轮省掉 16 帧全量 decode。
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---
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优化2：只decode observation 需要的帧
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问题： WM 跳过了全量 decode，但下一轮的CLIP embedding 需要 pixel-space 图像做 observation。
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改动： 只decode exe_steps 帧（通常 1帧），而不是全部 16 帧：
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# WM 调用，不做全量 decode
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pred_videos_1, _, pred_states, wm_samples = image_guided_synthesis_sim_mode(
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..., decode_video=False)
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# 只 decode exe_steps 帧给 observation
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obs_pixels = model.decode_first_stage(
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wm_samples[:, :, :args.exe_steps, :, :])
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for idx in range(args.exe_steps):
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observation = {
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'observation.images.top':obs_pixels[0, :, idx:idx + 1].permute(1, 0, 2, 3),
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...
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}
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cond_obs_queues = populate_queues(cond_obs_queues, observation)
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关键细节： 必须逐帧填充 observation queue（idx:idx+1），不能全用最后一帧，否则 CLIP embedding 输入变了会影响精度。
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效果： 每轮从 decode 16 帧降到 decode exe_steps 帧（省15 帧/轮）。
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---
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优化3：decode stream——GPU 上并行 decode 和 UNet
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问题： 写入最终视频仍需要完整 segment 的 pixel，这部分 decode 还是要做。
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思路： 用独立 CUDA stream 做 segment decode，和下一轮 UNet 推断在 GPU 上并行。
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改动：
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初始化：
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decode_stream = torch.cuda.Stream(device=device)
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pending_decode = None
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循环尾部：
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# 收集上一轮 decode 结果
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if pending_decode is not None:
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decode_stream.synchronize()
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write_q.put(pending_decode.cpu())
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pending_decode = None
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# 在 decode stream 上启动当前轮 segment decode（不阻塞主线程）
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latent_slice = wm_samples[:, :, :args.exe_steps]
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decode_stream.wait_stream(torch.cuda.current_stream()) # 确保 latent 就绪
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with torch.cuda.stream(decode_stream):
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pending_decode = model.decode_first_stage(latent_slice)
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# 主线程立即进入下一轮 UNet
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循环结束后收集最后一轮：
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if pending_decode is not None:
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decode_stream.synchronize()
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write_q.put(pending_decode.cpu())
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原理： decode_stream.wait_stream() 建立 stream间依赖，确保 latent 产出后才开始 decode。两个 stream 的 kernel 可以被GPU
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调度器交错执行。
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效果： segment decode 时间被下一轮 UNet 推断掩盖。
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---
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优化4：Writer 进程——CPU 工作跨进程并行
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问题： decode 完的tensor 需要转numpy + cv2 编码写盘，这是 CPU 密集型操作，Python GIL 限制线程并行。
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改动：
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辅助函数（主进程和子进程都能调用）：
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def _video_tensor_to_frames(video: Tensor) -> np.ndarray:
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video = torch.clamp(video.float(), -1., 1.)
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n = video.shape[0]
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video = video.permute(2, 0, 1, 3, 4)
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frame_grids = [
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torchvision.utils.make_grid(f, nrow=int(n), padding=0) for f in video
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]
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grid = torch.stack(frame_grids, dim=0)
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grid = ((grid + 1.0) / 2.0 * 255).to(torch.uint8).permute(0, 2, 3, 1)
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return grid.numpy()[:, :, :, ::-1] # RGB → BGR
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Writer 进程：
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def _video_writer_process(q: mp.Queue, filename: str, fps: int):
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vwriter = None
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while True:
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item = q.get()
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if item is None: # sentinel，退出
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break
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frames = _video_tensor_to_frames(item)
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if vwriter is None:
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h, w = frames.shape[1], frames.shape[2]
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fourcc = cv2.VideoWriter_fourcc(*'mp4v')
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vwriter = cv2.VideoWriter(filename, fourcc, fps, (w, h))
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for f in frames:
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vwriter.write(f)
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if vwriter is not None:
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vwriter.release()
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主进程启动 writer：
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write_q = mp.Queue()
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writer_proc = mp.Process(target=_video_writer_process,
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args=(write_q, sample_full_video_file, args.save_fps))
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writer_proc.start()
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主进程通过 write_q.put(tensor.cpu()) 发送数据，循环结束发None sentinel 并join()。
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效果：
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- tensor→numpy 转换和cv2 编码不占主进程 CPU 时间
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- 不受 GIL 限制
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- cv2.VideoWriter 增量写入，不攒内存，不做最终 torch.cat
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- Queue 自带背压，writer 处理不过来时 put 自然阻塞，不会 OOM
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---
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同时删除的冗余 I/O
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- 每轮迭代的 WM 中间tensorboard log（log_to_tensorboard_async）
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- 每轮迭代的 WM 中间 mp4（save_results_async）
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- 每轮迭代的 policy 中间 mp4
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- 最终的 torch.cat + 一次性 save_results_async 写完整视频
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---
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总结：优化前后对比
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┌─────────────────────┬────────────────────────┬───────────────────────────┐
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│ │ 原始 │ 优化后 │
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├─────────────────────┼────────────────────────┼───────────────────────────┤
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│ WM decode帧数/轮 │ 16 │ exe_steps（通常1） │
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├─────────────────────┼────────────────────────┼───────────────────────────┤
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│ segment decode 阻塞 │ 同步阻塞主线程 │ decode stream，GPU并行 │
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├─────────────────────┼────────────────────────┼───────────────────────────┤
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│ tensor→numpy+写盘 │ 主线程同步/线程池(GIL) │ 独立进程，无GIL │
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├─────────────────────┼────────────────────────┼───────────────────────────┤
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│ 视频写入方式 │ 攒内存→cat→一次写 │ cv2增量追加写 │
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├─────────────────────┼────────────────────────┼───────────────────────────┤
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│ 中间I/O │ 每轮2×mp4+2×tb │ 无 │
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├─────────────────────┼────────────────────────┼───────────────────────────┤
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│ 内存占用 │ 随迭代数线性增长 │ 恒定（不攒decoded video） │
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└─────────────────────┴────────────────────────┴───────────────────────────┘
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✻ Cooked for 1m 31s
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❯ 目前哪些优化是默认开启的
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● 让我检查各个优化的开关状态。
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● Searched for 2 patterns (ctrl+o to expand)
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● 当前各优化的默认状态：
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┌───────────────────────────────────┬────────────┬────────────────────────────────────────────────────────┐
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│ 优化 │ 默认开启？ │ 控制方式 │
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├───────────────────────────────────┼────────────┼────────────────────────────────────────────────────────┤
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│ WM路径跳过全量decode │ ✅ 是 │ 硬编码 decode_video=False（789行） │
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├───────────────────────────────────┼────────────┼────────────────────────────────────────────────────────┤
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│ 只decode exe_steps帧给observation │ ✅ 是 │ 无开关，直接生效（792行） │
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├───────────────────────────────────┼────────────┼────────────────────────────────────────────────────────┤
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│ decode stream GPU并行 │ ✅ 是 │ 无开关，直接生效（824-827行） │
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├───────────────────────────────────┼────────────┼────────────────────────────────────────────────────────┤
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│ Writer进程增量写盘 │ ✅ 是 │ 无开关，直接生效（672-675行） │
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├───────────────────────────────────┼────────────┼────────────────────────────────────────────────────────┤
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│ 删除中间wm mp4/tb保存 │ ✅ 是 │ 代码已删除 │
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├───────────────────────────────────┼────────────┼────────────────────────────────────────────────────────┤
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│ Policy路径跳过decode │ ❌ 否 │ 需传--fast_policy_no_decode（默认False，即默认decode） │
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└───────────────────────────────────┴────────────┴────────────────────────────────────────────────────────┘
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114
run_all_case.sh
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114
run_all_case.sh
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#!/bin/bash
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# 自动执行所有场景的所有case
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# 总共5个场景，每个场景4个case，共20个case
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# 设置环境变量（离线模式）
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export HF_HUB_OFFLINE=1
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export TRANSFORMERS_OFFLINE=1
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# 颜色定义
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RED='\033[0;31m'
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GREEN='\033[0;32m'
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YELLOW='\033[1;33m'
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BLUE='\033[0;34m'
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NC='\033[0m' # No Color
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# 定义所有场景
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SCENARIOS=(
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"unitree_g1_pack_camera"
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"unitree_z1_dual_arm_cleanup_pencils"
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"unitree_z1_dual_arm_stackbox"
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"unitree_z1_dual_arm_stackbox_v2"
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"unitree_z1_stackbox"
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)
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# 定义case数量
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CASES=(1 2 3 4)
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# 记录开始时间
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START_TIME=$(date +%s)
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LOG_FILE="run_all_cases_$(date +%Y%m%d_%H%M%S).log"
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echo -e "${BLUE}========================================${NC}"
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echo -e "${BLUE}开始执行所有场景的case${NC}"
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echo -e "${BLUE}总共: ${#SCENARIOS[@]} 个场景 x ${#CASES[@]} 个case = $((${#SCENARIOS[@]} * ${#CASES[@]})) 个任务${NC}"
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echo -e "${BLUE}日志文件: ${LOG_FILE}${NC}"
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echo -e "${BLUE}========================================${NC}"
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echo ""
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# 初始化计数器
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TOTAL_CASES=$((${#SCENARIOS[@]} * ${#CASES[@]}))
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CURRENT_CASE=0
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SUCCESS_COUNT=0
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FAIL_COUNT=0
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# 记录失败的case
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declare -a FAILED_CASES
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# 遍历所有场景
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for scenario in "${SCENARIOS[@]}"; do
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echo -e "${YELLOW}>>> 场景: ${scenario}${NC}"
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# 遍历所有case
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for case_num in "${CASES[@]}"; do
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CURRENT_CASE=$((CURRENT_CASE + 1))
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case_dir="${scenario}/case${case_num}"
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script_path="${case_dir}/run_world_model_interaction.sh"
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echo -e "${BLUE}[${CURRENT_CASE}/${TOTAL_CASES}] 执行: ${case_dir}${NC}"
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# 检查脚本是否存在
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if [ ! -f "${script_path}" ]; then
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echo -e "${RED}错误: 脚本不存在 ${script_path}${NC}"
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FAIL_COUNT=$((FAIL_COUNT + 1))
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FAILED_CASES+=("${case_dir} (脚本不存在)")
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continue
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fi
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# 执行脚本
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echo "开始时间: $(date '+%Y-%m-%d %H:%M:%S')"
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if bash "${script_path}" >> "${LOG_FILE}" 2>&1; then
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echo -e "${GREEN}✓ 成功: ${case_dir}${NC}"
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SUCCESS_COUNT=$((SUCCESS_COUNT + 1))
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else
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echo -e "${RED}✗ 失败: ${case_dir}${NC}"
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FAIL_COUNT=$((FAIL_COUNT + 1))
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FAILED_CASES+=("${case_dir}")
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fi
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echo "结束时间: $(date '+%Y-%m-%d %H:%M:%S')"
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echo ""
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done
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||||||
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echo ""
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done
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||||||
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# 计算总耗时
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|
END_TIME=$(date +%s)
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|
DURATION=$((END_TIME - START_TIME))
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HOURS=$((DURATION / 3600))
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MINUTES=$(((DURATION % 3600) / 60))
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SECONDS=$((DURATION % 60))
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# 输出总结
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echo -e "${BLUE}========================================${NC}"
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echo -e "${BLUE}执行完成！${NC}"
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||||||
|
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}"
|
||||||
504
run_all_cases_20260218_190150.log
Normal file
504
run_all_cases_20260218_190150.log
Normal file
@@ -0,0 +1,504 @@
|
|||||||
|
2026-02-18 19:01:56.891895: 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`.
|
||||||
|
2026-02-18 19:01:56.940243: 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
|
||||||
|
2026-02-18 19:01:56.940285: 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
|
||||||
|
2026-02-18 19:01:56.941395: 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
|
||||||
|
2026-02-18 19:01:56.948327: 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.
|
||||||
|
2026-02-18 19:01:57.870809: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
|
||||||
|
Global seed set to 123
|
||||||
|
>>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
|
||||||
|
>>> Prepared model loaded.
|
||||||
|
INFO:root:***** Configing Data *****
|
||||||
|
>>> unitree_z1_stackbox: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_stackbox: data stats loaded.
|
||||||
|
>>> unitree_z1_stackbox: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: normalizer initiated.
|
||||||
|
>>> unitree_g1_pack_camera: 1 data samples loaded.
|
||||||
|
>>> unitree_g1_pack_camera: data stats loaded.
|
||||||
|
>>> unitree_g1_pack_camera: normalizer initiated.
|
||||||
|
>>> Dataset is successfully loaded ...
|
||||||
|
✓ KV fused: 66 attention layers
|
||||||
|
TRT output 'y': [1, 4, 16, 40, 64] torch.float32
|
||||||
|
TRT output 'hs_a_0': [1, 16, 320, 40, 64] torch.float32
|
||||||
|
TRT output 'hs_a_1': [1, 16, 640, 20, 32] torch.float32
|
||||||
|
TRT output 'hs_a_2': [1, 16, 1280, 10, 16] torch.float32
|
||||||
|
TRT output 'hs_a_3': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_4': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_5': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_6': [1, 16, 1280, 10, 16] torch.float32
|
||||||
|
TRT output 'hs_a_7': [1, 16, 640, 20, 32] torch.float32
|
||||||
|
TRT output 'hs_a_8': [1, 16, 320, 40, 64] torch.float32
|
||||||
|
>>> TRT backbone loaded from /home/qhy/unifolm-world-model-action/scripts/evaluation/../../trt_engines/video_backbone.engine
|
||||||
|
>>> 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][02/18/2026-19:02:10] [TRT] [W] Using default stream in enqueueV3() may lead to performance issues due to additional calls to cudaStreamSynchronize() by TensorRT to ensure correct synchronization. Please use non-default stream instead.
|
||||||
|
|
||||||
|
9%|▉ | 1/11 [00:17<02:51, 17.15s/it]>>> Step 0: generating actions ...
|
||||||
|
>>> Step 0: interacting with world model ...
|
||||||
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
|
>>> Step 1: generating actions ...
|
||||||
|
DEBUG:PIL.Image:Importing BlpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BlpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BmpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BufrStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BmpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BufrStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing CurImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing CurImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DdsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DdsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing EpsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing EpsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FliImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FliImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FpxImagePlugin
|
||||||
|
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 FtexImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GbrImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GbrImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GifImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GribStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GifImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GribStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcnsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcnsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImtImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImtImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IptcImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IptcImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing JpegImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing McIdasImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing JpegImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing McIdasImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MicImagePlugin
|
||||||
|
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 MpegImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MpoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MpoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MspImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MspImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PalmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PalmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PcdImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PcdImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PdfImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PdfImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PixarImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PixarImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PngImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PpmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PsdImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PngImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PpmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PsdImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing QoiImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing QoiImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SgiImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SgiImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SpiderImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SpiderImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SunImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SunImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing TgaImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing TgaImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing TiffImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing WebPImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing TiffImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing WebPImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing WmfImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing WmfImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XbmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XbmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XpmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XpmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XVThumbImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XVThumbImagePlugin
|
||||||
|
|
||||||
|
18%|█▊ | 2/11 [00:33<02:31, 16.87s/it]
|
||||||
|
27%|██▋ | 3/11 [00:50<02:14, 16.76s/it]
|
||||||
|
36%|███▋ | 4/11 [01:07<01:57, 16.81s/it]
|
||||||
|
45%|████▌ | 5/11 [01:24<01:41, 16.85s/it]
|
||||||
|
55%|█████▍ | 6/11 [01:41<01:24, 16.82s/it]
|
||||||
|
64%|██████▎ | 7/11 [01:57<01:07, 16.82s/it]
|
||||||
|
73%|███████▎ | 8/11 [02:14<00:50, 16.83s/it]
|
||||||
|
82%|████████▏ | 9/11 [02:31<00:33, 16.80s/it]
|
||||||
|
91%|█████████ | 10/11 [02:48<00:16, 16.81s/it]
|
||||||
|
100%|██████████| 11/11 [03:05<00:00, 16.81s/it]
|
||||||
|
100%|██████████| 11/11 [03:05<00:00, 16.83s/it]
|
||||||
|
>>> 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 ...
|
||||||
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
|
>>> Step 9: generating actions ...
|
||||||
|
>>> Step 9: interacting with world model ...
|
||||||
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
|
>>> Step 10: generating actions ...
|
||||||
|
>>> Step 10: interacting with world model ...
|
||||||
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
|
|
||||||
|
real 3m49.072s
|
||||||
|
user 4m16.055s
|
||||||
|
sys 0m44.636s
|
||||||
|
2026-02-18 19:05:45.956647: 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`.
|
||||||
|
2026-02-18 19:05:46.004149: 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
|
||||||
|
2026-02-18 19:05:46.004193: 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
|
||||||
|
2026-02-18 19:05:46.005265: 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
|
||||||
|
2026-02-18 19:05:46.012074: 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.
|
||||||
|
2026-02-18 19:05:46.932966: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
|
||||||
|
Global seed set to 123
|
||||||
|
>>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
|
||||||
|
>>> Prepared model loaded.
|
||||||
|
INFO:root:***** Configing Data *****
|
||||||
|
>>> unitree_z1_stackbox: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_stackbox: data stats loaded.
|
||||||
|
>>> unitree_z1_stackbox: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: normalizer initiated.
|
||||||
|
>>> unitree_g1_pack_camera: 1 data samples loaded.
|
||||||
|
>>> unitree_g1_pack_camera: data stats loaded.
|
||||||
|
>>> unitree_g1_pack_camera: normalizer initiated.
|
||||||
|
>>> Dataset is successfully loaded ...
|
||||||
|
✓ KV fused: 66 attention layers
|
||||||
|
TRT output 'y': [1, 4, 16, 40, 64] torch.float32
|
||||||
|
TRT output 'hs_a_0': [1, 16, 320, 40, 64] torch.float32
|
||||||
|
TRT output 'hs_a_1': [1, 16, 640, 20, 32] torch.float32
|
||||||
|
TRT output 'hs_a_2': [1, 16, 1280, 10, 16] torch.float32
|
||||||
|
TRT output 'hs_a_3': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_4': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_5': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_6': [1, 16, 1280, 10, 16] torch.float32
|
||||||
|
TRT output 'hs_a_7': [1, 16, 640, 20, 32] torch.float32
|
||||||
|
TRT output 'hs_a_8': [1, 16, 320, 40, 64] torch.float32
|
||||||
|
>>> TRT backbone loaded from /home/qhy/unifolm-world-model-action/scripts/evaluation/../../trt_engines/video_backbone.engine
|
||||||
|
>>> 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][02/18/2026-19:05:59] [TRT] [W] Using default stream in enqueueV3() may lead to performance issues due to additional calls to cudaStreamSynchronize() by TensorRT to ensure correct synchronization. Please use non-default stream instead.
|
||||||
|
|
||||||
|
9%|▉ | 1/11 [00:16<02:47, 16.71s/it]>>> Step 0: generating actions ...
|
||||||
|
>>> Step 0: interacting with world model ...
|
||||||
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
|
>>> Step 1: generating actions ...
|
||||||
|
DEBUG:PIL.Image:Importing BlpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BlpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BmpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BufrStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BmpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BufrStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing CurImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing CurImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DcxImagePlugin
|
||||||
|
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|
||||||
|
DEBUG:PIL.Image:Importing DdsImagePlugin
|
||||||
|
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|
||||||
|
DEBUG:PIL.Image:Importing EpsImagePlugin
|
||||||
|
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|
||||||
|
DEBUG:PIL.Image:Importing FitsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FliImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FliImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FpxImagePlugin
|
||||||
|
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 FtexImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GbrImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GbrImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GifImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GribStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GifImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GribStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
|
||||||
|
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|
||||||
|
DEBUG:PIL.Image:Importing IcnsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImtImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImtImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IptcImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IptcImagePlugin
|
||||||
|
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|
||||||
|
DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
|
||||||
|
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|
||||||
|
DEBUG:PIL.Image:Importing JpegImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
|
||||||
|
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|
||||||
|
DEBUG:PIL.Image:Importing MicImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MicImagePlugin
|
||||||
|
DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
|
||||||
|
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|
||||||
|
DEBUG:PIL.Image:Importing MpegImagePlugin
|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
DEBUG:PIL.Image:Importing XpmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XVThumbImagePlugin
|
||||||
|
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|
||||||
|
|
||||||
|
18%|█▊ | 2/11 [00:33<02:30, 16.75s/it]
|
||||||
|
27%|██▋ | 3/11 [00:50<02:15, 16.91s/it]
|
||||||
|
36%|███▋ | 4/11 [01:07<01:59, 17.02s/it]
|
||||||
|
45%|████▌ | 5/11 [01:24<01:41, 16.98s/it]
|
||||||
|
55%|█████▍ | 6/11 [01:41<01:24, 16.94s/it]
|
||||||
|
64%|██████▎ | 7/11 [01:58<01:07, 16.90s/it]
|
||||||
|
73%|███████▎ | 8/11 [02:15<00:50, 16.83s/it]
|
||||||
|
82%|████████▏ | 9/11 [02:31<00:33, 16.80s/it]
|
||||||
|
91%|█████████ | 10/11 [02:49<00:16, 16.94s/it]
|
||||||
|
100%|██████████| 11/11 [03:06<00:00, 16.97s/it]
|
||||||
|
100%|██████████| 11/11 [03:06<00:00, 16.91s/it]
|
||||||
|
>>> 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 ...
|
||||||
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
|
>>> Step 9: generating actions ...
|
||||||
|
>>> Step 9: interacting with world model ...
|
||||||
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
|
>>> Step 10: generating actions ...
|
||||||
|
>>> Step 10: interacting with world model ...
|
||||||
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
|
|
||||||
|
real 3m49.162s
|
||||||
|
user 4m12.814s
|
||||||
|
sys 0m45.565s
|
||||||
|
2026-02-18 19:09:35.113634: 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`.
|
||||||
|
2026-02-18 19:09:35.161428: 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
|
||||||
|
2026-02-18 19:09:35.161474: 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
|
||||||
|
2026-02-18 19:09:35.162551: 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
|
||||||
|
2026-02-18 19:09:35.169325: 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.
|
||||||
|
2026-02-18 19:09:36.089250: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
|
||||||
|
Global seed set to 123
|
||||||
|
>>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
|
||||||
|
>>> Prepared model loaded.
|
||||||
|
INFO:root:***** Configing Data *****
|
||||||
|
>>> unitree_z1_stackbox: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_stackbox: data stats loaded.
|
||||||
|
>>> unitree_z1_stackbox: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: normalizer initiated.
|
||||||
|
>>> unitree_g1_pack_camera: 1 data samples loaded.
|
||||||
|
>>> unitree_g1_pack_camera: data stats loaded.
|
||||||
|
>>> unitree_g1_pack_camera: normalizer initiated.
|
||||||
|
>>> Dataset is successfully loaded ...
|
||||||
|
✓ KV fused: 66 attention layers
|
||||||
|
TRT output 'y': [1, 4, 16, 40, 64] torch.float32
|
||||||
|
TRT output 'hs_a_0': [1, 16, 320, 40, 64] torch.float32
|
||||||
|
TRT output 'hs_a_1': [1, 16, 640, 20, 32] torch.float32
|
||||||
|
TRT output 'hs_a_2': [1, 16, 1280, 10, 16] torch.float32
|
||||||
|
TRT output 'hs_a_3': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_4': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_5': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_6': [1, 16, 1280, 10, 16] torch.float32
|
||||||
|
TRT output 'hs_a_7': [1, 16, 640, 20, 32] torch.float32
|
||||||
|
TRT output 'hs_a_8': [1, 16, 320, 40, 64] torch.float32
|
||||||
|
>>> TRT backbone loaded from /home/qhy/unifolm-world-model-action/scripts/evaluation/../../trt_engines/video_backbone.engine
|
||||||
|
>>> 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][02/18/2026-19:09:49] [TRT] [W] Using default stream in enqueueV3() may lead to performance issues due to additional calls to cudaStreamSynchronize() by TensorRT to ensure correct synchronization. Please use non-default stream instead.
|
||||||
|
|
||||||
|
9%|▉ | 1/11 [00:16<02:45, 16.53s/it]>>> Step 0: generating actions ...
|
||||||
|
>>> Step 0: interacting with world model ...
|
||||||
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
|
>>> Step 1: generating actions ...
|
||||||
|
DEBUG:PIL.Image:Importing BlpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BlpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BmpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BufrStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BmpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BufrStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing CurImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing CurImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DdsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DdsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing EpsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing EpsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FliImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FliImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FpxImagePlugin
|
||||||
|
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 FtexImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GbrImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GbrImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GifImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GribStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GifImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GribStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcnsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcnsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImtImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImtImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IptcImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IptcImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing JpegImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing McIdasImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing JpegImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing McIdasImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MicImagePlugin
|
||||||
|
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 MpegImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MpoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MpoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MspImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MspImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PalmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PalmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PcdImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PcdImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PdfImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PdfImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PixarImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PixarImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PngImagePlugin
|
||||||
61
run_all_psnr.sh
Normal file
61
run_all_psnr.sh
Normal file
@@ -0,0 +1,61 @@
|
|||||||
|
#!/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"
|
||||||
@@ -585,6 +585,11 @@ def run_inference(args: argparse.Namespace, gpu_num: int, gpu_no: int) -> None:
|
|||||||
if isinstance(m, CrossAttention) and m.fuse_kv())
|
if isinstance(m, CrossAttention) and m.fuse_kv())
|
||||||
print(f" ✓ KV fused: {kv_count} attention layers")
|
print(f" ✓ KV fused: {kv_count} attention layers")
|
||||||
|
|
||||||
|
# Load TRT backbone if engine exists
|
||||||
|
trt_engine_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), '..', '..', 'trt_engines', 'video_backbone.engine')
|
||||||
|
if os.path.exists(trt_engine_path):
|
||||||
|
model.model.diffusion_model.load_trt_backbone(trt_engine_path)
|
||||||
|
|
||||||
# Run over data
|
# Run over data
|
||||||
assert (args.height % 16 == 0) and (
|
assert (args.height % 16 == 0) and (
|
||||||
args.width % 16
|
args.width % 16
|
||||||
|
|||||||
87
scripts/export_trt.py
Normal file
87
scripts/export_trt.py
Normal file
@@ -0,0 +1,87 @@
|
|||||||
|
"""Export video UNet backbone to ONNX, then convert to TensorRT engine.
|
||||||
|
|
||||||
|
Usage:
|
||||||
|
python scripts/export_trt.py \
|
||||||
|
--ckpt ckpts/unifolm_wma_dual.ckpt.prepared.pt \
|
||||||
|
--config configs/inference/world_model_interaction.yaml \
|
||||||
|
--out_dir trt_engines
|
||||||
|
"""
|
||||||
|
|
||||||
|
import os
|
||||||
|
import sys
|
||||||
|
import argparse
|
||||||
|
|
||||||
|
import torch
|
||||||
|
import tensorrt as trt
|
||||||
|
from omegaconf import OmegaConf
|
||||||
|
|
||||||
|
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
|
||||||
|
from unifolm_wma.utils.utils import instantiate_from_config
|
||||||
|
from unifolm_wma.trt_utils import export_backbone_onnx
|
||||||
|
|
||||||
|
|
||||||
|
def load_model(config_path, ckpt_path):
|
||||||
|
if ckpt_path.endswith('.prepared.pt'):
|
||||||
|
model = torch.load(ckpt_path, map_location='cpu')
|
||||||
|
else:
|
||||||
|
config = OmegaConf.load(config_path)
|
||||||
|
model = instantiate_from_config(config.model)
|
||||||
|
state_dict = torch.load(ckpt_path, map_location='cpu')
|
||||||
|
if 'state_dict' in state_dict:
|
||||||
|
state_dict = state_dict['state_dict']
|
||||||
|
model.load_state_dict(state_dict, strict=False)
|
||||||
|
model.eval().cuda()
|
||||||
|
return model
|
||||||
|
|
||||||
|
|
||||||
|
def main():
|
||||||
|
parser = argparse.ArgumentParser()
|
||||||
|
parser.add_argument('--ckpt', required=True)
|
||||||
|
parser.add_argument('--config', default='configs/inference/world_model_interaction.yaml')
|
||||||
|
parser.add_argument('--out_dir', default='trt_engines')
|
||||||
|
parser.add_argument('--context_len', type=int, default=95)
|
||||||
|
parser.add_argument('--fp16', action='store_true', default=True)
|
||||||
|
args = parser.parse_args()
|
||||||
|
|
||||||
|
os.makedirs(args.out_dir, exist_ok=True)
|
||||||
|
onnx_path = os.path.join(args.out_dir, 'video_backbone.onnx')
|
||||||
|
engine_path = os.path.join(args.out_dir, 'video_backbone.engine')
|
||||||
|
|
||||||
|
if os.path.exists(onnx_path):
|
||||||
|
print(f">>> ONNX already exists at {onnx_path}, skipping export.")
|
||||||
|
n_outputs = 10
|
||||||
|
else:
|
||||||
|
print(">>> Loading model ...")
|
||||||
|
model = load_model(args.config, args.ckpt)
|
||||||
|
print(">>> Exporting ONNX ...")
|
||||||
|
with torch.no_grad():
|
||||||
|
n_outputs = export_backbone_onnx(model, onnx_path, context_len=args.context_len)
|
||||||
|
del model
|
||||||
|
torch.cuda.empty_cache()
|
||||||
|
|
||||||
|
print(">>> Converting ONNX -> TensorRT engine ...")
|
||||||
|
logger = trt.Logger(trt.Logger.WARNING)
|
||||||
|
builder = trt.Builder(logger)
|
||||||
|
network = builder.create_network(1 << int(trt.NetworkDefinitionCreationFlag.EXPLICIT_BATCH))
|
||||||
|
parser = trt.OnnxParser(network, logger)
|
||||||
|
|
||||||
|
if not parser.parse_from_file(os.path.abspath(onnx_path)):
|
||||||
|
for i in range(parser.num_errors):
|
||||||
|
print(f" ONNX parse error: {parser.get_error(i)}")
|
||||||
|
raise RuntimeError("ONNX parsing failed")
|
||||||
|
|
||||||
|
config = builder.create_builder_config()
|
||||||
|
config.set_memory_pool_limit(trt.MemoryPoolType.WORKSPACE, 16 << 30)
|
||||||
|
if args.fp16:
|
||||||
|
config.set_flag(trt.BuilderFlag.FP16)
|
||||||
|
|
||||||
|
engine_bytes = builder.build_serialized_network(network, config)
|
||||||
|
with open(engine_path, 'wb') as f:
|
||||||
|
f.write(engine_bytes)
|
||||||
|
|
||||||
|
print(f"\n>>> Done! Engine saved to {engine_path}")
|
||||||
|
print(f" Outputs: 1 y + {n_outputs - 1} hs_a tensors")
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == '__main__':
|
||||||
|
main()
|
||||||
@@ -688,6 +688,7 @@ class WMAModel(nn.Module):
|
|||||||
# Context precomputation cache
|
# Context precomputation cache
|
||||||
self._ctx_cache_enabled = False
|
self._ctx_cache_enabled = False
|
||||||
self._ctx_cache = {}
|
self._ctx_cache = {}
|
||||||
|
self._trt_backbone = None # TRT engine for video UNet backbone
|
||||||
# Reusable CUDA stream for parallel state_unet / action_unet
|
# Reusable CUDA stream for parallel state_unet / action_unet
|
||||||
self._state_stream = torch.cuda.Stream()
|
self._state_stream = torch.cuda.Stream()
|
||||||
|
|
||||||
@@ -700,6 +701,12 @@ class WMAModel(nn.Module):
|
|||||||
self.__dict__.update(state)
|
self.__dict__.update(state)
|
||||||
self._state_stream = torch.cuda.Stream()
|
self._state_stream = torch.cuda.Stream()
|
||||||
|
|
||||||
|
def load_trt_backbone(self, engine_path, n_hs_a=9):
|
||||||
|
"""Load a TensorRT engine for the video UNet backbone."""
|
||||||
|
from unifolm_wma.trt_utils import TRTBackbone
|
||||||
|
self._trt_backbone = TRTBackbone(engine_path, n_hs_a=n_hs_a)
|
||||||
|
print(f">>> TRT backbone loaded from {engine_path}")
|
||||||
|
|
||||||
def forward(self,
|
def forward(self,
|
||||||
x: Tensor,
|
x: Tensor,
|
||||||
x_action: Tensor,
|
x_action: Tensor,
|
||||||
@@ -812,6 +819,12 @@ class WMAModel(nn.Module):
|
|||||||
fs_embed = fs_embed.repeat_interleave(repeats=t, dim=0)
|
fs_embed = fs_embed.repeat_interleave(repeats=t, dim=0)
|
||||||
emb = emb + fs_embed
|
emb = emb + fs_embed
|
||||||
|
|
||||||
|
if self._trt_backbone is not None:
|
||||||
|
# TRT path: run backbone via TensorRT engine
|
||||||
|
h_in = x.type(self.dtype).contiguous()
|
||||||
|
y, hs_a = self._trt_backbone(h_in, emb.contiguous(), context.contiguous())
|
||||||
|
else:
|
||||||
|
# PyTorch path: original backbone
|
||||||
h = x.type(self.dtype)
|
h = x.type(self.dtype)
|
||||||
adapter_idx = 0
|
adapter_idx = 0
|
||||||
hs = []
|
hs = []
|
||||||
|
|||||||
151
src/unifolm_wma/trt_utils.py
Normal file
151
src/unifolm_wma/trt_utils.py
Normal file
@@ -0,0 +1,151 @@
|
|||||||
|
"""TensorRT acceleration utilities for the video UNet backbone."""
|
||||||
|
|
||||||
|
import torch
|
||||||
|
import torch.nn as nn
|
||||||
|
from einops import rearrange
|
||||||
|
from unifolm_wma.modules.networks.wma_model import Downsample, Upsample
|
||||||
|
|
||||||
|
|
||||||
|
class VideoBackboneForExport(nn.Module):
|
||||||
|
"""Wrapper that isolates the video UNet backbone for ONNX export.
|
||||||
|
|
||||||
|
Takes already-preprocessed inputs (after context/time embedding prep)
|
||||||
|
and returns y + hs_a as a flat tuple.
|
||||||
|
"""
|
||||||
|
|
||||||
|
def __init__(self, wma_model):
|
||||||
|
super().__init__()
|
||||||
|
self.input_blocks = wma_model.input_blocks
|
||||||
|
self.middle_block = wma_model.middle_block
|
||||||
|
self.output_blocks = wma_model.output_blocks
|
||||||
|
self.out = wma_model.out
|
||||||
|
self.addition_attention = wma_model.addition_attention
|
||||||
|
if self.addition_attention:
|
||||||
|
self.init_attn = wma_model.init_attn
|
||||||
|
self.dtype = wma_model.dtype
|
||||||
|
|
||||||
|
def forward(self, h, emb, context):
|
||||||
|
t = 16
|
||||||
|
b = 1
|
||||||
|
|
||||||
|
hs = []
|
||||||
|
hs_a = []
|
||||||
|
h = h.type(self.dtype)
|
||||||
|
for id, module in enumerate(self.input_blocks):
|
||||||
|
h = module(h, emb, context=context, batch_size=b)
|
||||||
|
if id == 0 and self.addition_attention:
|
||||||
|
h = self.init_attn(h, emb, context=context, batch_size=b)
|
||||||
|
if id != 0:
|
||||||
|
if isinstance(module[0], Downsample):
|
||||||
|
hs_a.append(rearrange(hs[-1], '(b t) c h w -> b t c h w', t=t))
|
||||||
|
hs.append(h)
|
||||||
|
hs_a.append(rearrange(h, '(b t) c h w -> b t c h w', t=t))
|
||||||
|
|
||||||
|
h = self.middle_block(h, emb, context=context, batch_size=b)
|
||||||
|
hs_a.append(rearrange(h, '(b t) c h w -> b t c h w', t=t))
|
||||||
|
|
||||||
|
hs_out = []
|
||||||
|
for module in self.output_blocks:
|
||||||
|
h = torch.cat([h, hs.pop()], dim=1)
|
||||||
|
h = module(h, emb, context=context, batch_size=b)
|
||||||
|
if isinstance(module[-1], Upsample):
|
||||||
|
hs_a.append(rearrange(hs_out[-1], '(b t) c h w -> b t c h w', t=t))
|
||||||
|
hs_out.append(h)
|
||||||
|
hs_a.append(rearrange(hs_out[-1], '(b t) c h w -> b t c h w', t=t))
|
||||||
|
|
||||||
|
y = self.out(h.type(h.dtype))
|
||||||
|
y = rearrange(y, '(b t) c h w -> b c t h w', b=b)
|
||||||
|
return (y, *hs_a)
|
||||||
|
|
||||||
|
|
||||||
|
def export_backbone_onnx(model, save_path, context_len=95):
|
||||||
|
wma = model.model.diffusion_model
|
||||||
|
wrapper = VideoBackboneForExport(wma)
|
||||||
|
wrapper.eval().cuda()
|
||||||
|
|
||||||
|
for m in wrapper.modules():
|
||||||
|
if hasattr(m, 'checkpoint'):
|
||||||
|
m.checkpoint = False
|
||||||
|
if hasattr(m, 'use_checkpoint'):
|
||||||
|
m.use_checkpoint = False
|
||||||
|
|
||||||
|
import xformers.ops
|
||||||
|
_orig_mea = xformers.ops.memory_efficient_attention
|
||||||
|
def _sdpa_replacement(q, k, v, attn_bias=None, op=None, **kw):
|
||||||
|
return torch.nn.functional.scaled_dot_product_attention(q, k, v, attn_mask=attn_bias)
|
||||||
|
xformers.ops.memory_efficient_attention = _sdpa_replacement
|
||||||
|
|
||||||
|
BT = 16
|
||||||
|
emb_dim = wma.model_channels * 4
|
||||||
|
ctx_dim = 1024
|
||||||
|
in_ch = wma.in_channels
|
||||||
|
|
||||||
|
dummy_h = torch.randn(BT, in_ch, 40, 64, device='cuda', dtype=torch.float32)
|
||||||
|
dummy_emb = torch.randn(BT, emb_dim, device='cuda', dtype=torch.float32)
|
||||||
|
dummy_ctx = torch.randn(BT, context_len, ctx_dim, device='cuda', dtype=torch.float32)
|
||||||
|
|
||||||
|
with torch.no_grad():
|
||||||
|
outputs = wrapper(dummy_h, dummy_emb, dummy_ctx)
|
||||||
|
n_outputs = len(outputs)
|
||||||
|
print(f">>> Backbone has {n_outputs} outputs (1 y + {n_outputs-1} hs_a)")
|
||||||
|
for i, o in enumerate(outputs):
|
||||||
|
print(f" output[{i}]: {o.shape} {o.dtype}")
|
||||||
|
|
||||||
|
output_names = ['y'] + [f'hs_a_{i}' for i in range(n_outputs - 1)]
|
||||||
|
|
||||||
|
torch.onnx.export(
|
||||||
|
wrapper,
|
||||||
|
(dummy_h, dummy_emb, dummy_ctx),
|
||||||
|
save_path,
|
||||||
|
input_names=['h', 'emb', 'context'],
|
||||||
|
output_names=output_names,
|
||||||
|
opset_version=17,
|
||||||
|
do_constant_folding=True,
|
||||||
|
)
|
||||||
|
print(f">>> ONNX exported to {save_path}")
|
||||||
|
xformers.ops.memory_efficient_attention = _orig_mea
|
||||||
|
return n_outputs
|
||||||
|
|
||||||
|
|
||||||
|
class TRTBackbone:
|
||||||
|
"""TensorRT runtime wrapper for the video UNet backbone."""
|
||||||
|
|
||||||
|
def __init__(self, engine_path, n_hs_a=9):
|
||||||
|
import tensorrt as trt
|
||||||
|
|
||||||
|
self.logger = trt.Logger(trt.Logger.WARNING)
|
||||||
|
with open(engine_path, 'rb') as f:
|
||||||
|
runtime = trt.Runtime(self.logger)
|
||||||
|
self.engine = runtime.deserialize_cuda_engine(f.read())
|
||||||
|
self.context = self.engine.create_execution_context()
|
||||||
|
self.n_hs_a = n_hs_a
|
||||||
|
|
||||||
|
import numpy as np
|
||||||
|
self.output_buffers = {}
|
||||||
|
for i in range(self.engine.num_io_tensors):
|
||||||
|
name = self.engine.get_tensor_name(i)
|
||||||
|
if self.engine.get_tensor_mode(name) == trt.TensorIOMode.OUTPUT:
|
||||||
|
shape = self.engine.get_tensor_shape(name)
|
||||||
|
np_dtype = trt.nptype(self.engine.get_tensor_dtype(name))
|
||||||
|
buf = torch.empty(list(shape), dtype=torch.from_numpy(np.empty(0, dtype=np_dtype)).dtype, device='cuda')
|
||||||
|
self.output_buffers[name] = buf
|
||||||
|
print(f" TRT output '{name}': {list(shape)} {buf.dtype}")
|
||||||
|
|
||||||
|
def __call__(self, h, emb, context):
|
||||||
|
import tensorrt as trt
|
||||||
|
for name, tensor in [('h', h), ('emb', emb), ('context', context)]:
|
||||||
|
expected_dtype = trt.nptype(self.engine.get_tensor_dtype(name))
|
||||||
|
torch_expected = torch.from_numpy(__import__('numpy').empty(0, dtype=expected_dtype)).dtype
|
||||||
|
if tensor.dtype != torch_expected:
|
||||||
|
tensor = tensor.to(torch_expected)
|
||||||
|
self.context.set_tensor_address(name, tensor.contiguous().data_ptr())
|
||||||
|
|
||||||
|
for name, buf in self.output_buffers.items():
|
||||||
|
self.context.set_tensor_address(name, buf.data_ptr())
|
||||||
|
|
||||||
|
self.context.execute_async_v3(torch.cuda.current_stream().cuda_stream)
|
||||||
|
torch.cuda.synchronize()
|
||||||
|
|
||||||
|
y = self.output_buffers['y']
|
||||||
|
hs_a = [self.output_buffers[f'hs_a_{i}'] for i in range(self.n_hs_a)]
|
||||||
|
return y, hs_a
|
||||||
179
unitree_g1_pack_camera/case1/output.log
Normal file
179
unitree_g1_pack_camera/case1/output.log
Normal file
@@ -0,0 +1,179 @@
|
|||||||
|
2026-02-18 19:01:56.891895: 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`.
|
||||||
|
2026-02-18 19:01:56.940243: 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
|
||||||
|
2026-02-18 19:01:56.940285: 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
|
||||||
|
2026-02-18 19:01:56.941395: 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
|
||||||
|
2026-02-18 19:01:56.948327: 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.
|
||||||
|
2026-02-18 19:01:57.870809: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
|
||||||
|
Global seed set to 123
|
||||||
|
>>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
|
||||||
|
>>> Prepared model loaded.
|
||||||
|
INFO:root:***** Configing Data *****
|
||||||
|
>>> unitree_z1_stackbox: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_stackbox: data stats loaded.
|
||||||
|
>>> unitree_z1_stackbox: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: normalizer initiated.
|
||||||
|
>>> unitree_g1_pack_camera: 1 data samples loaded.
|
||||||
|
>>> unitree_g1_pack_camera: data stats loaded.
|
||||||
|
>>> unitree_g1_pack_camera: normalizer initiated.
|
||||||
|
>>> Dataset is successfully loaded ...
|
||||||
|
✓ KV fused: 66 attention layers
|
||||||
|
TRT output 'y': [1, 4, 16, 40, 64] torch.float32
|
||||||
|
TRT output 'hs_a_0': [1, 16, 320, 40, 64] torch.float32
|
||||||
|
TRT output 'hs_a_1': [1, 16, 640, 20, 32] torch.float32
|
||||||
|
TRT output 'hs_a_2': [1, 16, 1280, 10, 16] torch.float32
|
||||||
|
TRT output 'hs_a_3': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_4': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_5': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_6': [1, 16, 1280, 10, 16] torch.float32
|
||||||
|
TRT output 'hs_a_7': [1, 16, 640, 20, 32] torch.float32
|
||||||
|
TRT output 'hs_a_8': [1, 16, 320, 40, 64] torch.float32
|
||||||
|
>>> TRT backbone loaded from /home/qhy/unifolm-world-model-action/scripts/evaluation/../../trt_engines/video_backbone.engine
|
||||||
|
>>> 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][02/18/2026-19:02:10] [TRT] [W] Using default stream in enqueueV3() may lead to performance issues due to additional calls to cudaStreamSynchronize() by TensorRT to ensure correct synchronization. Please use non-default stream instead.
|
||||||
|
|
||||||
|
9%|▉ | 1/11 [00:17<02:51, 17.15s/it]>>> Step 0: generating actions ...
|
||||||
|
>>> Step 0: interacting with world model ...
|
||||||
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
|
>>> Step 1: generating actions ...
|
||||||
|
DEBUG:PIL.Image:Importing BlpImagePlugin
|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
|
||||||
|
18%|█▊ | 2/11 [00:33<02:31, 16.87s/it]
|
||||||
|
27%|██▋ | 3/11 [00:50<02:14, 16.76s/it]
|
||||||
|
36%|███▋ | 4/11 [01:07<01:57, 16.81s/it]
|
||||||
|
45%|████▌ | 5/11 [01:24<01:41, 16.85s/it]
|
||||||
|
55%|█████▍ | 6/11 [01:41<01:24, 16.82s/it]
|
||||||
|
64%|██████▎ | 7/11 [01:57<01:07, 16.82s/it]
|
||||||
|
73%|███████▎ | 8/11 [02:14<00:50, 16.83s/it]
|
||||||
|
82%|████████▏ | 9/11 [02:31<00:33, 16.80s/it]
|
||||||
|
91%|█████████ | 10/11 [02:48<00:16, 16.81s/it]
|
||||||
|
100%|██████████| 11/11 [03:05<00:00, 16.81s/it]
|
||||||
|
100%|██████████| 11/11 [03:05<00:00, 16.83s/it]
|
||||||
|
>>> 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 ...
|
||||||
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
5
unitree_g1_pack_camera/case1/psnr_result.json
Normal file
5
unitree_g1_pack_camera/case1/psnr_result.json
Normal file
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_g1_pack_camera/case1/unitree_g1_pack_camera_case1.mp4",
|
||||||
|
"pred_video": "unitree_g1_pack_camera/case1/output/inference/0_full_fs6.mp4",
|
||||||
|
"psnr": 35.615362167470806
|
||||||
|
}
|
||||||
179
unitree_g1_pack_camera/case2/output.log
Normal file
179
unitree_g1_pack_camera/case2/output.log
Normal file
@@ -0,0 +1,179 @@
|
|||||||
|
2026-02-18 19:05:45.956647: 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`.
|
||||||
|
2026-02-18 19:05:46.004149: 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
|
||||||
|
2026-02-18 19:05:46.004193: 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
|
||||||
|
2026-02-18 19:05:46.005265: 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
|
||||||
|
2026-02-18 19:05:46.012074: 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.
|
||||||
|
2026-02-18 19:05:46.932966: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
|
||||||
|
Global seed set to 123
|
||||||
|
>>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
|
||||||
|
>>> Prepared model loaded.
|
||||||
|
INFO:root:***** Configing Data *****
|
||||||
|
>>> unitree_z1_stackbox: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_stackbox: data stats loaded.
|
||||||
|
>>> unitree_z1_stackbox: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: normalizer initiated.
|
||||||
|
>>> unitree_g1_pack_camera: 1 data samples loaded.
|
||||||
|
>>> unitree_g1_pack_camera: data stats loaded.
|
||||||
|
>>> unitree_g1_pack_camera: normalizer initiated.
|
||||||
|
>>> Dataset is successfully loaded ...
|
||||||
|
✓ KV fused: 66 attention layers
|
||||||
|
TRT output 'y': [1, 4, 16, 40, 64] torch.float32
|
||||||
|
TRT output 'hs_a_0': [1, 16, 320, 40, 64] torch.float32
|
||||||
|
TRT output 'hs_a_1': [1, 16, 640, 20, 32] torch.float32
|
||||||
|
TRT output 'hs_a_2': [1, 16, 1280, 10, 16] torch.float32
|
||||||
|
TRT output 'hs_a_3': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_4': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_5': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_6': [1, 16, 1280, 10, 16] torch.float32
|
||||||
|
TRT output 'hs_a_7': [1, 16, 640, 20, 32] torch.float32
|
||||||
|
TRT output 'hs_a_8': [1, 16, 320, 40, 64] torch.float32
|
||||||
|
>>> TRT backbone loaded from /home/qhy/unifolm-world-model-action/scripts/evaluation/../../trt_engines/video_backbone.engine
|
||||||
|
>>> 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][02/18/2026-19:05:59] [TRT] [W] Using default stream in enqueueV3() may lead to performance issues due to additional calls to cudaStreamSynchronize() by TensorRT to ensure correct synchronization. Please use non-default stream instead.
|
||||||
|
|
||||||
|
9%|▉ | 1/11 [00:16<02:47, 16.71s/it]>>> Step 0: generating actions ...
|
||||||
|
>>> Step 0: interacting with world model ...
|
||||||
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
|
>>> Step 1: generating actions ...
|
||||||
|
DEBUG:PIL.Image:Importing BlpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BlpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BmpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BufrStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BmpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BufrStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing CurImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing CurImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DdsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DdsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing EpsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing EpsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FliImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FliImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FpxImagePlugin
|
||||||
|
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 FtexImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GbrImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GbrImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GifImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GribStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GifImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GribStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcnsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcnsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImtImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImtImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IptcImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IptcImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing JpegImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
|
||||||
|
18%|█▊ | 2/11 [00:33<02:30, 16.75s/it]
|
||||||
|
27%|██▋ | 3/11 [00:50<02:15, 16.91s/it]
|
||||||
|
36%|███▋ | 4/11 [01:07<01:59, 17.02s/it]
|
||||||
|
45%|████▌ | 5/11 [01:24<01:41, 16.98s/it]
|
||||||
|
55%|█████▍ | 6/11 [01:41<01:24, 16.94s/it]
|
||||||
|
64%|██████▎ | 7/11 [01:58<01:07, 16.90s/it]
|
||||||
|
73%|███████▎ | 8/11 [02:15<00:50, 16.83s/it]
|
||||||
|
82%|████████▏ | 9/11 [02:31<00:33, 16.80s/it]
|
||||||
|
91%|█████████ | 10/11 [02:49<00:16, 16.94s/it]
|
||||||
|
100%|██████████| 11/11 [03:06<00:00, 16.97s/it]
|
||||||
|
100%|██████████| 11/11 [03:06<00:00, 16.91s/it]
|
||||||
|
>>> 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 ...
|
||||||
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
5
unitree_g1_pack_camera/case2/psnr_result.json
Normal file
5
unitree_g1_pack_camera/case2/psnr_result.json
Normal file
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_g1_pack_camera/case2/unitree_g1_pack_camera_case2.mp4",
|
||||||
|
"pred_video": "unitree_g1_pack_camera/case2/output/inference/50_full_fs6.mp4",
|
||||||
|
"psnr": 34.61979248212279
|
||||||
|
}
|
||||||
146
unitree_g1_pack_camera/case3/output.log
Normal file
146
unitree_g1_pack_camera/case3/output.log
Normal file
@@ -0,0 +1,146 @@
|
|||||||
|
2026-02-18 19:09:35.113634: 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`.
|
||||||
|
2026-02-18 19:09:35.161428: 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
|
||||||
|
2026-02-18 19:09:35.161474: 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
|
||||||
|
2026-02-18 19:09:35.162551: 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
|
||||||
|
2026-02-18 19:09:35.169325: 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.
|
||||||
|
2026-02-18 19:09:36.089250: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
|
||||||
|
Global seed set to 123
|
||||||
|
>>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
|
||||||
|
>>> Prepared model loaded.
|
||||||
|
INFO:root:***** Configing Data *****
|
||||||
|
>>> unitree_z1_stackbox: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_stackbox: data stats loaded.
|
||||||
|
>>> unitree_z1_stackbox: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: normalizer initiated.
|
||||||
|
>>> unitree_g1_pack_camera: 1 data samples loaded.
|
||||||
|
>>> unitree_g1_pack_camera: data stats loaded.
|
||||||
|
>>> unitree_g1_pack_camera: normalizer initiated.
|
||||||
|
>>> Dataset is successfully loaded ...
|
||||||
|
✓ KV fused: 66 attention layers
|
||||||
|
TRT output 'y': [1, 4, 16, 40, 64] torch.float32
|
||||||
|
TRT output 'hs_a_0': [1, 16, 320, 40, 64] torch.float32
|
||||||
|
TRT output 'hs_a_1': [1, 16, 640, 20, 32] torch.float32
|
||||||
|
TRT output 'hs_a_2': [1, 16, 1280, 10, 16] torch.float32
|
||||||
|
TRT output 'hs_a_3': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_4': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_5': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_6': [1, 16, 1280, 10, 16] torch.float32
|
||||||
|
TRT output 'hs_a_7': [1, 16, 640, 20, 32] torch.float32
|
||||||
|
TRT output 'hs_a_8': [1, 16, 320, 40, 64] torch.float32
|
||||||
|
>>> TRT backbone loaded from /home/qhy/unifolm-world-model-action/scripts/evaluation/../../trt_engines/video_backbone.engine
|
||||||
|
>>> 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][02/18/2026-19:09:49] [TRT] [W] Using default stream in enqueueV3() may lead to performance issues due to additional calls to cudaStreamSynchronize() by TensorRT to ensure correct synchronization. Please use non-default stream instead.
|
||||||
|
|
||||||
|
9%|▉ | 1/11 [00:16<02:45, 16.53s/it]>>> Step 0: generating actions ...
|
||||||
|
>>> Step 0: interacting with world model ...
|
||||||
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
|
>>> Step 1: generating actions ...
|
||||||
|
DEBUG:PIL.Image:Importing BlpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BlpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BmpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BufrStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BmpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BufrStubImagePlugin
|
||||||
|
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|
||||||
|
DEBUG:PIL.Image:Importing CurImagePlugin
|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
DEBUG:PIL.Image:Importing FitsStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FliImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FliImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FpxImagePlugin
|
||||||
|
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 FtexImagePlugin
|
||||||
|
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|
||||||
|
DEBUG:PIL.Image:Importing GbrImagePlugin
|
||||||
|
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|
||||||
|
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|
||||||
|
DEBUG:PIL.Image:Importing GifImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GribStubImagePlugin
|
||||||
|
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|
||||||
|
DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcnsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcnsImagePlugin
|
||||||
|
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|
||||||
|
DEBUG:PIL.Image:Importing IcoImagePlugin
|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing McIdasImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing JpegImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing McIdasImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MicImagePlugin
|
||||||
|
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 MpegImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MpoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MpoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MspImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MspImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PalmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PalmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PcdImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PcdImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PdfImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PdfImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PixarImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PixarImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PngImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PpmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PsdImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PngImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PpmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PsdImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing QoiImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing QoiImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SgiImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SgiImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SpiderImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SpiderImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SunImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SunImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing TgaImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing TgaImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing TiffImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing WebPImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing TiffImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing WebPImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing WmfImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing WmfImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XbmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XbmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XpmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XpmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XVThumbImagePlugin
|
||||||
5
unitree_g1_pack_camera/case3/psnr_result.json
Normal file
5
unitree_g1_pack_camera/case3/psnr_result.json
Normal file
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_g1_pack_camera/case3/unitree_g1_pack_camera_case3.mp4",
|
||||||
|
"pred_video": "unitree_g1_pack_camera/case3/output/inference/100_full_fs6.mp4",
|
||||||
|
"psnr": 37.034952654534486
|
||||||
|
}
|
||||||
5
unitree_g1_pack_camera/case4/psnr_result.json
Normal file
5
unitree_g1_pack_camera/case4/psnr_result.json
Normal file
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_g1_pack_camera/case4/unitree_g1_pack_camera_case4.mp4",
|
||||||
|
"pred_video": "unitree_g1_pack_camera/case4/output/inference/200_full_fs6.mp4",
|
||||||
|
"psnr": 31.43390896360405
|
||||||
|
}
|
||||||
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_z1_dual_arm_cleanup_pencils/case2/unitree_z1_dual_arm_cleanup_pencils_case2.mp4",
|
||||||
|
"pred_video": "unitree_z1_dual_arm_cleanup_pencils/case2/output/inference/50_full_fs4.mp4",
|
||||||
|
"psnr": 48.344571927558974
|
||||||
|
}
|
||||||
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_z1_dual_arm_cleanup_pencils/case3/unitree_z1_dual_arm_cleanup_pencils_case3.mp4",
|
||||||
|
"pred_video": "unitree_z1_dual_arm_cleanup_pencils/case3/output/inference/100_full_fs4.mp4",
|
||||||
|
"psnr": 41.152374490134825
|
||||||
|
}
|
||||||
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_z1_dual_arm_cleanup_pencils/case4/unitree_z1_dual_arm_cleanup_pencils_case4.mp4",
|
||||||
|
"pred_video": "unitree_z1_dual_arm_cleanup_pencils/case4/output/inference/200_full_fs4.mp4",
|
||||||
|
"psnr": 46.025723557253855
|
||||||
|
}
|
||||||
5
unitree_z1_dual_arm_stackbox/case1/psnr_result.json
Normal file
5
unitree_z1_dual_arm_stackbox/case1/psnr_result.json
Normal file
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_z1_dual_arm_stackbox/case1/unitree_z1_dual_arm_stackbox_case1.mp4",
|
||||||
|
"pred_video": "unitree_z1_dual_arm_stackbox/case1/output/inference/5_full_fs4.mp4",
|
||||||
|
"psnr": 44.3480149502738
|
||||||
|
}
|
||||||
5
unitree_z1_dual_arm_stackbox/case2/psnr_result.json
Normal file
5
unitree_z1_dual_arm_stackbox/case2/psnr_result.json
Normal file
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_z1_dual_arm_stackbox/case2/unitree_z1_dual_arm_stackbox_case2.mp4",
|
||||||
|
"pred_video": "unitree_z1_dual_arm_stackbox/case2/output/inference/15_full_fs4.mp4",
|
||||||
|
"psnr": 39.867728254007716
|
||||||
|
}
|
||||||
5
unitree_z1_dual_arm_stackbox/case3/psnr_result.json
Normal file
5
unitree_z1_dual_arm_stackbox/case3/psnr_result.json
Normal file
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_z1_dual_arm_stackbox/case3/unitree_z1_dual_arm_stackbox_case3.mp4",
|
||||||
|
"pred_video": "unitree_z1_dual_arm_stackbox/case3/output/inference/25_full_fs4.mp4",
|
||||||
|
"psnr": 39.19101039445159
|
||||||
|
}
|
||||||
5
unitree_z1_dual_arm_stackbox/case4/psnr_result.json
Normal file
5
unitree_z1_dual_arm_stackbox/case4/psnr_result.json
Normal file
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_z1_dual_arm_stackbox/case4/unitree_z1_dual_arm_stackbox_case4.mp4",
|
||||||
|
"pred_video": "unitree_z1_dual_arm_stackbox/case4/output/inference/35_full_fs4.mp4",
|
||||||
|
"psnr": 40.29563315341769
|
||||||
|
}
|
||||||
@@ -1,10 +1,10 @@
|
|||||||
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`.
|
2026-02-18 18:49:49.117856: 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 11:59:27.291755: 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
|
2026-02-18 18:49:49.165270: 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 11:59:27.291807: 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
|
2026-02-18 18:49:49.165322: 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 11:59:27.293169: 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
|
2026-02-18 18:49:49.166382: 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 11:59:27.300838: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
|
2026-02-18 18:49:49.173299: 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.
|
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
|
||||||
2026-02-11 11:59:28.228009: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
|
2026-02-18 18:49:50.090214: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
|
||||||
Global seed set to 123
|
Global seed set to 123
|
||||||
>>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
|
>>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
|
||||||
>>> Prepared model loaded.
|
>>> Prepared model loaded.
|
||||||
@@ -26,12 +26,24 @@ INFO:root:***** Configing Data *****
|
|||||||
>>> unitree_g1_pack_camera: normalizer initiated.
|
>>> unitree_g1_pack_camera: normalizer initiated.
|
||||||
>>> Dataset is successfully loaded ...
|
>>> Dataset is successfully loaded ...
|
||||||
✓ KV fused: 66 attention layers
|
✓ KV fused: 66 attention layers
|
||||||
|
TRT output 'y': [1, 4, 16, 40, 64] torch.float32
|
||||||
|
TRT output 'hs_a_0': [1, 16, 320, 40, 64] torch.float32
|
||||||
|
TRT output 'hs_a_1': [1, 16, 640, 20, 32] torch.float32
|
||||||
|
TRT output 'hs_a_2': [1, 16, 1280, 10, 16] torch.float32
|
||||||
|
TRT output 'hs_a_3': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_4': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_5': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_6': [1, 16, 1280, 10, 16] torch.float32
|
||||||
|
TRT output 'hs_a_7': [1, 16, 640, 20, 32] torch.float32
|
||||||
|
TRT output 'hs_a_8': [1, 16, 320, 40, 64] torch.float32
|
||||||
|
>>> TRT backbone loaded from /home/qhy/unifolm-world-model-action/scripts/evaluation/../../trt_engines/video_backbone.engine
|
||||||
>>> Generate 16 frames under each generation ...
|
>>> Generate 16 frames under each generation ...
|
||||||
DEBUG:h5py._conv:Creating converter from 3 to 5
|
DEBUG:h5py._conv:Creating converter from 3 to 5
|
||||||
DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
|
DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
|
||||||
DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
|
DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
|
||||||
DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
|
DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
|
||||||
|
|
||||||
|
0%| | 0/11 [00:00<?, ?it/s][02/18/2026-18:50:03] [TRT] [W] Using default stream in enqueueV3() may lead to performance issues due to additional calls to cudaStreamSynchronize() by TensorRT to ensure correct synchronization. Please use non-default stream instead.
|
||||||
|
|
||||||
9%|▉ | 1/11 [00:15<02:38, 15.88s/it]>>> Step 0: generating actions ...
|
9%|▉ | 1/11 [00:15<02:38, 15.88s/it]>>> Step 0: generating actions ...
|
||||||
>>> Step 0: interacting with world model ...
|
>>> Step 0: interacting with world model ...
|
||||||
@@ -84,7 +96,7 @@ DEBUG:PIL.Image:Importing WmfImagePlugin
|
|||||||
DEBUG:PIL.Image:Importing WebPImagePlugin
|
DEBUG:PIL.Image:Importing WebPImagePlugin
|
||||||
DEBUG:PIL.Image:Importing WmfImagePlugin
|
DEBUG:PIL.Image:Importing WmfImagePlugin
|
||||||
DEBUG:PIL.Image:Importing XbmImagePlugin
|
DEBUG:PIL.Image:Importing XbmImagePlugin
|
||||||
DEBUG:PIL.Image:Importing XpmImagePlugin
|
DEBUG:PIL.Image:Importing XpmImagePlugin
|
||||||
DEBUG:PIL.Image:Importing XVThumbImagePlugin
|
DEBUG:PIL.Image:Importing XVThumbImagePlugin
|
||||||
|
|
||||||
18%|█▊ | 2/11 [00:31<02:21, 15.71s/it]
|
18%|█▊ | 2/11 [00:31<02:21, 15.71s/it]
|
||||||
@@ -115,6 +127,6 @@ DEBUG:PIL.Image:Importing XVThumbImagePlugin
|
|||||||
>>> Step 6: generating actions ...
|
>>> Step 6: generating actions ...
|
||||||
>>> Step 6: interacting with world model ...
|
>>> 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 ...
|
||||||
>>>>>>>>>>>>>>>>>>>>>>>>
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
|
|||||||
@@ -1,5 +1,5 @@
|
|||||||
{
|
{
|
||||||
"gt_video": "/home/qhy/unifolm-world-model-action/unitree_z1_dual_arm_stackbox_v2/case1/unitree_z1_dual_arm_stackbox_v2_case1.mp4",
|
"gt_video": "unitree_z1_dual_arm_stackbox_v2/case1/unitree_z1_dual_arm_stackbox_v2_case1.mp4",
|
||||||
"pred_video": "/home/qhy/unifolm-world-model-action/unitree_z1_dual_arm_stackbox_v2/case1/output/inference/5_full_fs4.mp4",
|
"pred_video": "unitree_z1_dual_arm_stackbox_v2/case1/output/inference/5_full_fs4.mp4",
|
||||||
"psnr": 28.167025381705358
|
"psnr": 27.62636266067224
|
||||||
}
|
}
|
||||||
5
unitree_z1_dual_arm_stackbox_v2/case2/psnr_result.json
Normal file
5
unitree_z1_dual_arm_stackbox_v2/case2/psnr_result.json
Normal file
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_z1_dual_arm_stackbox_v2/case2/unitree_z1_dual_arm_stackbox_v2_case2.mp4",
|
||||||
|
"pred_video": "unitree_z1_dual_arm_stackbox_v2/case2/output/inference/15_full_fs4.mp4",
|
||||||
|
"psnr": 33.90444714332389
|
||||||
|
}
|
||||||
5
unitree_z1_dual_arm_stackbox_v2/case3/psnr_result.json
Normal file
5
unitree_z1_dual_arm_stackbox_v2/case3/psnr_result.json
Normal file
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_z1_dual_arm_stackbox_v2/case3/unitree_z1_dual_arm_stackbox_v2_case3.mp4",
|
||||||
|
"pred_video": "unitree_z1_dual_arm_stackbox_v2/case3/output/inference/25_full_fs4.mp4",
|
||||||
|
"psnr": 34.50192428908007
|
||||||
|
}
|
||||||
179
unitree_z1_dual_arm_stackbox_v2/case4/output.log
Normal file
179
unitree_z1_dual_arm_stackbox_v2/case4/output.log
Normal file
@@ -0,0 +1,179 @@
|
|||||||
|
2026-02-18 18:54:56.403136: 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`.
|
||||||
|
2026-02-18 18:54:56.451144: 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
|
||||||
|
2026-02-18 18:54:56.451189: 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
|
||||||
|
2026-02-18 18:54:56.452312: 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
|
||||||
|
2026-02-18 18:54:56.459281: 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.
|
||||||
|
2026-02-18 18:54:57.381032: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
|
||||||
|
Global seed set to 123
|
||||||
|
>>> Loading prepared model from ckpts/unifolm_wma_dual.ckpt.prepared.pt ...
|
||||||
|
>>> Prepared model loaded.
|
||||||
|
INFO:root:***** Configing Data *****
|
||||||
|
>>> unitree_z1_stackbox: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_stackbox: data stats loaded.
|
||||||
|
>>> unitree_z1_stackbox: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_stackbox_v2: normalizer initiated.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: 1 data samples loaded.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: data stats loaded.
|
||||||
|
>>> unitree_z1_dual_arm_cleanup_pencils: normalizer initiated.
|
||||||
|
>>> unitree_g1_pack_camera: 1 data samples loaded.
|
||||||
|
>>> unitree_g1_pack_camera: data stats loaded.
|
||||||
|
>>> unitree_g1_pack_camera: normalizer initiated.
|
||||||
|
>>> Dataset is successfully loaded ...
|
||||||
|
✓ KV fused: 66 attention layers
|
||||||
|
TRT output 'y': [1, 4, 16, 40, 64] torch.float32
|
||||||
|
TRT output 'hs_a_0': [1, 16, 320, 40, 64] torch.float32
|
||||||
|
TRT output 'hs_a_1': [1, 16, 640, 20, 32] torch.float32
|
||||||
|
TRT output 'hs_a_2': [1, 16, 1280, 10, 16] torch.float32
|
||||||
|
TRT output 'hs_a_3': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_4': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_5': [1, 16, 1280, 5, 8] torch.float32
|
||||||
|
TRT output 'hs_a_6': [1, 16, 1280, 10, 16] torch.float32
|
||||||
|
TRT output 'hs_a_7': [1, 16, 640, 20, 32] torch.float32
|
||||||
|
TRT output 'hs_a_8': [1, 16, 320, 40, 64] torch.float32
|
||||||
|
>>> TRT backbone loaded from /home/qhy/unifolm-world-model-action/scripts/evaluation/../../trt_engines/video_backbone.engine
|
||||||
|
>>> 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][02/18/2026-18:55:10] [TRT] [W] Using default stream in enqueueV3() may lead to performance issues due to additional calls to cudaStreamSynchronize() by TensorRT to ensure correct synchronization. Please use non-default stream instead.
|
||||||
|
|
||||||
|
9%|▉ | 1/11 [00:16<02:45, 16.53s/it]>>> Step 0: generating actions ...
|
||||||
|
>>> Step 0: interacting with world model ...
|
||||||
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
|
>>> Step 1: generating actions ...
|
||||||
|
DEBUG:PIL.Image:Importing BlpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BlpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BmpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BufrStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BmpImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing BufrStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing CurImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing CurImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DdsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing DdsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing EpsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing EpsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FitsStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FliImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FliImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing FpxImagePlugin
|
||||||
|
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 FtexImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GbrImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GbrImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GifImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GribStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GifImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing GribStubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcnsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcnsImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IcoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImtImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing ImtImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IptcImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing IptcImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing JpegImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing McIdasImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing JpegImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing McIdasImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MicImagePlugin
|
||||||
|
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 MpegImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MpoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MpoImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MspImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing MspImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PalmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PalmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PcdImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PcdImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PdfImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PcxImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PdfImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PixarImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PixarImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PngImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PpmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PsdImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PngImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PpmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing PsdImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing QoiImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing QoiImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SgiImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SgiImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SpiderImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SpiderImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SunImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing SunImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing TgaImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing TgaImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing TiffImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing WebPImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing TiffImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing WebPImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing WmfImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing WmfImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XbmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XbmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XpmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XpmImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XVThumbImagePlugin
|
||||||
|
DEBUG:PIL.Image:Importing XVThumbImagePlugin
|
||||||
|
|
||||||
|
18%|█▊ | 2/11 [00:33<02:28, 16.52s/it]
|
||||||
|
27%|██▋ | 3/11 [00:49<02:12, 16.53s/it]
|
||||||
|
36%|███▋ | 4/11 [01:06<01:56, 16.64s/it]
|
||||||
|
45%|████▌ | 5/11 [01:23<01:40, 16.69s/it]
|
||||||
|
55%|█████▍ | 6/11 [01:39<01:23, 16.71s/it]
|
||||||
|
64%|██████▎ | 7/11 [01:56<01:06, 16.68s/it]
|
||||||
|
73%|███████▎ | 8/11 [02:13<00:50, 16.68s/it]
|
||||||
|
82%|████████▏ | 9/11 [02:29<00:33, 16.71s/it]
|
||||||
|
91%|█████████ | 10/11 [02:46<00:16, 16.72s/it]
|
||||||
|
100%|██████████| 11/11 [03:03<00:00, 16.69s/it]
|
||||||
|
100%|██████████| 11/11 [03:03<00:00, 16.67s/it]
|
||||||
|
>>> 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 ...
|
||||||
|
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||||
5
unitree_z1_dual_arm_stackbox_v2/case4/psnr_result.json
Normal file
5
unitree_z1_dual_arm_stackbox_v2/case4/psnr_result.json
Normal file
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_z1_dual_arm_stackbox_v2/case4/unitree_z1_dual_arm_stackbox_v2_case4.mp4",
|
||||||
|
"pred_video": "unitree_z1_dual_arm_stackbox_v2/case4/output/inference/35_full_fs4.mp4",
|
||||||
|
"psnr": 25.49270910031428
|
||||||
|
}
|
||||||
5
unitree_z1_stackbox/case1/psnr_result.json
Normal file
5
unitree_z1_stackbox/case1/psnr_result.json
Normal file
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_z1_stackbox/case1/unitree_z1_stackbox_case1.mp4",
|
||||||
|
"pred_video": "unitree_z1_stackbox/case1/output/inference/5_full_fs4.mp4",
|
||||||
|
"psnr": 42.83913947323794
|
||||||
|
}
|
||||||
5
unitree_z1_stackbox/case2/psnr_result.json
Normal file
5
unitree_z1_stackbox/case2/psnr_result.json
Normal file
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_z1_stackbox/case2/unitree_z1_stackbox_case2.mp4",
|
||||||
|
"pred_video": "unitree_z1_stackbox/case2/output/inference/15_full_fs4.mp4",
|
||||||
|
"psnr": 48.64571989587276
|
||||||
|
}
|
||||||
5
unitree_z1_stackbox/case3/psnr_result.json
Normal file
5
unitree_z1_stackbox/case3/psnr_result.json
Normal file
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_z1_stackbox/case3/unitree_z1_stackbox_case3.mp4",
|
||||||
|
"pred_video": "unitree_z1_stackbox/case3/output/inference/25_full_fs4.mp4",
|
||||||
|
"psnr": 45.127553229898034
|
||||||
|
}
|
||||||
5
unitree_z1_stackbox/case4/psnr_result.json
Normal file
5
unitree_z1_stackbox/case4/psnr_result.json
Normal file
@@ -0,0 +1,5 @@
|
|||||||
|
{
|
||||||
|
"gt_video": "unitree_z1_stackbox/case4/unitree_z1_stackbox_case4.mp4",
|
||||||
|
"pred_video": "unitree_z1_stackbox/case4/output/inference/35_full_fs4.mp4",
|
||||||
|
"psnr": 50.642542240144444
|
||||||
|
}
|
||||||
Reference in New Issue
Block a user