DDIM loop 内小张量分配优化，attention mask 缓存到 GPU
This commit is contained in:
1
.gitignore
vendored
1
.gitignore
vendored
@@ -55,7 +55,6 @@ coverage.xml
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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@@ -67,11 +67,12 @@ class DDIMSampler(object):
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ddim_timesteps=self.ddim_timesteps,
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eta=ddim_eta,
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verbose=verbose)
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self.register_buffer('ddim_sigmas', ddim_sigmas)
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self.register_buffer('ddim_alphas', ddim_alphas)
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self.register_buffer('ddim_alphas_prev', ddim_alphas_prev)
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# Ensure tensors are on correct device for efficient indexing
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self.register_buffer('ddim_sigmas', to_torch(torch.as_tensor(ddim_sigmas)))
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self.register_buffer('ddim_alphas', to_torch(torch.as_tensor(ddim_alphas)))
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self.register_buffer('ddim_alphas_prev', to_torch(torch.as_tensor(ddim_alphas_prev)))
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self.register_buffer('ddim_sqrt_one_minus_alphas',
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np.sqrt(1. - ddim_alphas))
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to_torch(torch.as_tensor(np.sqrt(1. - ddim_alphas))))
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sigmas_for_original_sampling_steps = ddim_eta * torch.sqrt(
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(1 - self.alphas_cumprod_prev) / (1 - self.alphas_cumprod) *
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(1 - self.alphas_cumprod / self.alphas_cumprod_prev))
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@@ -241,9 +242,10 @@ class DDIMSampler(object):
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dp_ddim_scheduler_action.set_timesteps(len(timesteps))
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dp_ddim_scheduler_state.set_timesteps(len(timesteps))
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ts = torch.empty((b, ), device=device, dtype=torch.long)
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for i, step in enumerate(iterator):
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index = total_steps - i - 1
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ts = torch.full((b, ), step, device=device, dtype=torch.long)
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ts.fill_(step)
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# Use mask to blend noised original latent (img_orig) & new sampled latent (img)
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if mask is not None:
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@@ -325,10 +327,6 @@ class DDIMSampler(object):
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guidance_rescale=0.0,
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**kwargs):
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b, *_, device = *x.shape, x.device
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if x.dim() == 5:
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is_video = True
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else:
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is_video = False
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if unconditional_conditioning is None or unconditional_guidance_scale == 1.:
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model_output, model_output_action, model_output_state = self.model.apply_model(
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@@ -377,17 +375,11 @@ class DDIMSampler(object):
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sqrt_one_minus_alphas = self.model.sqrt_one_minus_alphas_cumprod if use_original_steps else self.ddim_sqrt_one_minus_alphas
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sigmas = self.ddim_sigmas_for_original_num_steps if use_original_steps else self.ddim_sigmas
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if is_video:
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size = (b, 1, 1, 1, 1)
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else:
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size = (b, 1, 1, 1)
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a_t = torch.full(size, alphas[index], device=device)
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a_prev = torch.full(size, alphas_prev[index], device=device)
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sigma_t = torch.full(size, sigmas[index], device=device)
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sqrt_one_minus_at = torch.full(size,
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sqrt_one_minus_alphas[index],
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device=device)
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# Use 0-d tensors directly (already on device); broadcasting handles shape
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a_t = alphas[index]
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a_prev = alphas_prev[index]
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sigma_t = sigmas[index]
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sqrt_one_minus_at = sqrt_one_minus_alphas[index]
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if self.model.parameterization != "v":
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pred_x0 = (x - sqrt_one_minus_at * e_t) / a_t.sqrt()
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@@ -395,12 +387,8 @@ class DDIMSampler(object):
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pred_x0 = self.model.predict_start_from_z_and_v(x, t, model_output)
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if self.model.use_dynamic_rescale:
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scale_t = torch.full(size,
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self.ddim_scale_arr[index],
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device=device)
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prev_scale_t = torch.full(size,
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self.ddim_scale_arr_prev[index],
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device=device)
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scale_t = self.ddim_scale_arr[index]
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prev_scale_t = self.ddim_scale_arr_prev[index]
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rescale = (prev_scale_t / scale_t)
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pred_x0 *= rescale
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@@ -275,7 +275,8 @@ class CrossAttention(nn.Module):
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attn_mask_aa = self._get_attn_mask_aa(x.shape[0],
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q.shape[1],
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k_aa.shape[1],
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block_size=16).to(k_aa.device)
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block_size=16,
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device=k_aa.device)
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else:
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if not spatial_self_attn:
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assert 1 > 2, ">>> ERROR: you should never go into here ..."
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@@ -386,14 +387,26 @@ class CrossAttention(nn.Module):
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return self.to_out(out)
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def _get_attn_mask_aa(self, b, l1, l2, block_size=16):
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def _get_attn_mask_aa(self, b, l1, l2, block_size=16, device=None):
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cache_key = (b, l1, l2, block_size)
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if hasattr(self, '_attn_mask_aa_cache_key') and self._attn_mask_aa_cache_key == cache_key:
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cached = self._attn_mask_aa_cache
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if device is not None and cached.device != torch.device(device):
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cached = cached.to(device)
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self._attn_mask_aa_cache = cached
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return cached
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target_device = device if device is not None else 'cpu'
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num_token = l2 // block_size
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start_positions = ((torch.arange(b) % block_size) + 1) * num_token
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col_indices = torch.arange(l2)
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start_positions = ((torch.arange(b, device=target_device) % block_size) + 1) * num_token
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col_indices = torch.arange(l2, device=target_device)
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mask_2d = col_indices.unsqueeze(0) >= start_positions.unsqueeze(1)
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mask = mask_2d.unsqueeze(1).expand(b, l1, l2)
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attn_mask = torch.zeros_like(mask, dtype=torch.float)
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attn_mask = torch.zeros(b, l1, l2, dtype=torch.float, device=target_device)
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attn_mask[mask] = float('-inf')
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self._attn_mask_aa_cache_key = cache_key
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self._attn_mask_aa_cache = attn_mask
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return attn_mask
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121
unitree_z1_dual_arm_cleanup_pencils/case1/output.log
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121
unitree_z1_dual_arm_cleanup_pencils/case1/output.log
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@@ -0,0 +1,121 @@
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2026-02-10 15:38:28.973314: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
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2026-02-10 15:38:29.023024: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
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2026-02-10 15:38:29.023070: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
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2026-02-10 15:38:29.024393: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
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2026-02-10 15:38:29.031901: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
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To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
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2026-02-10 15:38:29.955454: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
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Global seed set to 123
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INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
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INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
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INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
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AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
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INFO:root:Loaded ViT-H-14 model config.
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DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): hf-mirror.com:443
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DEBUG:urllib3.connectionpool:https://hf-mirror.com:443 "HEAD /laion/CLIP-ViT-H-14-laion2B-s32B-b79K/resolve/main/open_clip_pytorch_model.bin HTTP/1.1" 302 0
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INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
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INFO:root:Loaded ViT-H-14 model config.
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DEBUG:urllib3.connectionpool:https://hf-mirror.com:443 "HEAD /laion/CLIP-ViT-H-14-laion2B-s32B-b79K/resolve/main/open_clip_pytorch_model.bin HTTP/1.1" 302 0
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INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
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>>> model checkpoint loaded.
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>>> Load pre-trained model ...
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INFO:root:***** Configing Data *****
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>>> unitree_z1_stackbox: 1 data samples loaded.
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>>> unitree_z1_stackbox: data stats loaded.
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>>> unitree_z1_stackbox: normalizer initiated.
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>>> unitree_z1_dual_arm_stackbox: 1 data samples loaded.
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>>> unitree_z1_dual_arm_stackbox: data stats loaded.
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>>> unitree_z1_dual_arm_stackbox: normalizer initiated.
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>>> unitree_z1_dual_arm_stackbox_v2: 1 data samples loaded.
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>>> unitree_z1_dual_arm_stackbox_v2: data stats loaded.
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>>> unitree_z1_dual_arm_stackbox_v2: normalizer initiated.
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>>> unitree_z1_dual_arm_cleanup_pencils: 1 data samples loaded.
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>>> unitree_z1_dual_arm_cleanup_pencils: data stats loaded.
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>>> unitree_z1_dual_arm_cleanup_pencils: normalizer initiated.
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>>> unitree_g1_pack_camera: 1 data samples loaded.
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>>> unitree_g1_pack_camera: data stats loaded.
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>>> unitree_g1_pack_camera: normalizer initiated.
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>>> Dataset is successfully loaded ...
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>>> Generate 16 frames under each generation ...
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DEBUG:h5py._conv:Creating converter from 3 to 5
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DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
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DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
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DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
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0%| | 0/8 [00:00<?, ?it/s]>>> Step 0: generating actions ...
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>>> Step 0: interacting with world model ...
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DEBUG:PIL.Image:Importing BlpImagePlugin
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DEBUG:PIL.Image:Importing BmpImagePlugin
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DEBUG:PIL.Image:Importing BufrStubImagePlugin
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DEBUG:PIL.Image:Importing CurImagePlugin
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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
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DEBUG:PIL.Image:Importing FitsStubImagePlugin
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DEBUG:PIL.Image:Importing FliImagePlugin
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DEBUG:PIL.Image:Importing FpxImagePlugin
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DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
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DEBUG:PIL.Image:Importing FtexImagePlugin
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DEBUG:PIL.Image:Importing GbrImagePlugin
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DEBUG:PIL.Image:Importing GifImagePlugin
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DEBUG:PIL.Image:Importing GribStubImagePlugin
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DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
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DEBUG:PIL.Image:Importing IcnsImagePlugin
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DEBUG:PIL.Image:Importing IcoImagePlugin
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DEBUG:PIL.Image:Importing ImImagePlugin
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DEBUG:PIL.Image:Importing ImtImagePlugin
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DEBUG:PIL.Image:Importing IptcImagePlugin
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DEBUG:PIL.Image:Importing JpegImagePlugin
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DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
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DEBUG:PIL.Image:Importing McIdasImagePlugin
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DEBUG:PIL.Image:Importing MicImagePlugin
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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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DEBUG:PIL.Image:Importing MpoImagePlugin
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DEBUG:PIL.Image:Importing MspImagePlugin
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DEBUG:PIL.Image:Importing PalmImagePlugin
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DEBUG:PIL.Image:Importing PcdImagePlugin
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DEBUG:PIL.Image:Importing PcxImagePlugin
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DEBUG:PIL.Image:Importing PdfImagePlugin
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DEBUG:PIL.Image:Importing PixarImagePlugin
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DEBUG:PIL.Image:Importing PngImagePlugin
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DEBUG:PIL.Image:Importing PpmImagePlugin
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DEBUG:PIL.Image:Importing PsdImagePlugin
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DEBUG:PIL.Image:Importing QoiImagePlugin
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DEBUG:PIL.Image:Importing SgiImagePlugin
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DEBUG:PIL.Image:Importing SpiderImagePlugin
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DEBUG:PIL.Image:Importing SunImagePlugin
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DEBUG:PIL.Image:Importing TgaImagePlugin
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DEBUG:PIL.Image:Importing TiffImagePlugin
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DEBUG:PIL.Image:Importing WebPImagePlugin
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DEBUG:PIL.Image:Importing WmfImagePlugin
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DEBUG:PIL.Image:Importing XbmImagePlugin
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DEBUG:PIL.Image:Importing XpmImagePlugin
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DEBUG:PIL.Image:Importing XVThumbImagePlugin
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12%|█▎ | 1/8 [01:14<08:41, 74.51s/it]
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25%|██▌ | 2/8 [02:29<07:28, 74.79s/it]
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75%|███████▌ | 6/8 [07:28<02:29, 74.66s/it]
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100%|██████████| 8/8 [09:56<00:00, 74.62s/it]
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>>>>>>>>>>>>>>>>>>>>>>>>
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>>> Step 1: generating actions ...
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>>> Step 1: interacting with world model ...
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>>>>>>>>>>>>>>>>>>>>>>>>
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>>> Step 2: generating actions ...
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>>> Step 2: interacting with world model ...
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>>>>>>>>>>>>>>>>>>>>>>>>
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>>> Step 3: generating actions ...
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>>> Step 3: interacting with world model ...
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>>>>>>>>>>>>>>>>>>>>>>>>
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>>> Step 4: generating actions ...
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>>> Step 4: interacting with world model ...
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>>>>>>>>>>>>>>>>>>>>>>>>
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>>> Step 5: generating actions ...
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>>> Step 5: interacting with world model ...
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>>>>>>>>>>>>>>>>>>>>>>>>
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130
unitree_z1_dual_arm_stackbox_v2/case1/output.log
Normal file
130
unitree_z1_dual_arm_stackbox_v2/case1/output.log
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@@ -0,0 +1,130 @@
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2026-02-10 16:42:59.052755: 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`.
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||||
2026-02-10 16:42:59.102749: 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
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2026-02-10 16:42:59.102803: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
|
||||
2026-02-10 16:42:59.104125: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
|
||||
2026-02-10 16:42:59.111711: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
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To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
|
||||
2026-02-10 16:43:00.040735: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
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Global seed set to 123
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INFO:mainlogger:LatentVisualDiffusion: Running in v-prediction mode
|
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INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
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INFO:unifolm_wma.models.diffusion_head.conditional_unet1d:number of parameters: 5.010531e+08
|
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AE working on z of shape (1, 4, 32, 32) = 4096 dimensions.
|
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INFO:root:Loaded ViT-H-14 model config.
|
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DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): hf-mirror.com:443
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DEBUG:urllib3.connectionpool:https://hf-mirror.com:443 "HEAD /laion/CLIP-ViT-H-14-laion2B-s32B-b79K/resolve/main/open_clip_pytorch_model.bin HTTP/1.1" 302 0
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INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
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INFO:root:Loaded ViT-H-14 model config.
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DEBUG:urllib3.connectionpool:https://hf-mirror.com:443 "HEAD /laion/CLIP-ViT-H-14-laion2B-s32B-b79K/resolve/main/open_clip_pytorch_model.bin HTTP/1.1" 302 0
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INFO:root:Loading pretrained ViT-H-14 weights (laion2b_s32b_b79k).
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>>> model checkpoint loaded.
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>>> Load pre-trained model ...
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INFO:root:***** Configing Data *****
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>>> unitree_z1_stackbox: 1 data samples loaded.
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>>> unitree_z1_stackbox: data stats loaded.
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>>> unitree_z1_stackbox: normalizer initiated.
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>>> unitree_z1_dual_arm_stackbox: 1 data samples loaded.
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>>> unitree_z1_dual_arm_stackbox: data stats loaded.
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>>> unitree_z1_dual_arm_stackbox: normalizer initiated.
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>>> unitree_z1_dual_arm_stackbox_v2: 1 data samples loaded.
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>>> unitree_z1_dual_arm_stackbox_v2: data stats loaded.
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>>> unitree_z1_dual_arm_stackbox_v2: normalizer initiated.
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>>> unitree_z1_dual_arm_cleanup_pencils: 1 data samples loaded.
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>>> unitree_z1_dual_arm_cleanup_pencils: data stats loaded.
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>>> unitree_z1_dual_arm_cleanup_pencils: normalizer initiated.
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>>> unitree_g1_pack_camera: 1 data samples loaded.
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>>> unitree_g1_pack_camera: data stats loaded.
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>>> unitree_g1_pack_camera: normalizer initiated.
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>>> Dataset is successfully loaded ...
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>>> Generate 16 frames under each generation ...
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DEBUG:h5py._conv:Creating converter from 3 to 5
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DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13
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DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 41 9
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DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 62 4096
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0%| | 0/11 [00:00<?, ?it/s]>>> Step 0: generating actions ...
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>>> Step 0: interacting with world model ...
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DEBUG:PIL.Image:Importing BlpImagePlugin
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DEBUG:PIL.Image:Importing BmpImagePlugin
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DEBUG:PIL.Image:Importing BufrStubImagePlugin
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DEBUG:PIL.Image:Importing CurImagePlugin
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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
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DEBUG:PIL.Image:Importing FitsStubImagePlugin
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DEBUG:PIL.Image:Importing FliImagePlugin
|
||||
DEBUG:PIL.Image:Importing FpxImagePlugin
|
||||
DEBUG:PIL.Image:Image: failed to import FpxImagePlugin: No module named 'olefile'
|
||||
DEBUG:PIL.Image:Importing FtexImagePlugin
|
||||
DEBUG:PIL.Image:Importing GbrImagePlugin
|
||||
DEBUG:PIL.Image:Importing GifImagePlugin
|
||||
DEBUG:PIL.Image:Importing GribStubImagePlugin
|
||||
DEBUG:PIL.Image:Importing Hdf5StubImagePlugin
|
||||
DEBUG:PIL.Image:Importing IcnsImagePlugin
|
||||
DEBUG:PIL.Image:Importing IcoImagePlugin
|
||||
DEBUG:PIL.Image:Importing ImImagePlugin
|
||||
DEBUG:PIL.Image:Importing ImtImagePlugin
|
||||
DEBUG:PIL.Image:Importing IptcImagePlugin
|
||||
DEBUG:PIL.Image:Importing JpegImagePlugin
|
||||
DEBUG:PIL.Image:Importing Jpeg2KImagePlugin
|
||||
DEBUG:PIL.Image:Importing McIdasImagePlugin
|
||||
DEBUG:PIL.Image:Importing MicImagePlugin
|
||||
DEBUG:PIL.Image:Image: failed to import MicImagePlugin: No module named 'olefile'
|
||||
DEBUG:PIL.Image:Importing MpegImagePlugin
|
||||
DEBUG:PIL.Image:Importing MpoImagePlugin
|
||||
DEBUG:PIL.Image:Importing MspImagePlugin
|
||||
DEBUG:PIL.Image:Importing PalmImagePlugin
|
||||
DEBUG:PIL.Image:Importing PcdImagePlugin
|
||||
DEBUG:PIL.Image:Importing PcxImagePlugin
|
||||
DEBUG:PIL.Image:Importing PdfImagePlugin
|
||||
DEBUG:PIL.Image:Importing PixarImagePlugin
|
||||
DEBUG:PIL.Image:Importing PngImagePlugin
|
||||
DEBUG:PIL.Image:Importing PpmImagePlugin
|
||||
DEBUG:PIL.Image:Importing PsdImagePlugin
|
||||
DEBUG:PIL.Image:Importing QoiImagePlugin
|
||||
DEBUG:PIL.Image:Importing SgiImagePlugin
|
||||
DEBUG:PIL.Image:Importing SpiderImagePlugin
|
||||
DEBUG:PIL.Image:Importing SunImagePlugin
|
||||
DEBUG:PIL.Image:Importing TgaImagePlugin
|
||||
DEBUG:PIL.Image:Importing TiffImagePlugin
|
||||
DEBUG:PIL.Image:Importing WebPImagePlugin
|
||||
DEBUG:PIL.Image:Importing WmfImagePlugin
|
||||
DEBUG:PIL.Image:Importing XbmImagePlugin
|
||||
DEBUG:PIL.Image:Importing XpmImagePlugin
|
||||
DEBUG:PIL.Image:Importing XVThumbImagePlugin
|
||||
|
||||
9%|▉ | 1/11 [00:40<06:41, 40.19s/it]
|
||||
18%|█▊ | 2/11 [01:20<06:04, 40.45s/it]
|
||||
27%|██▋ | 3/11 [02:01<05:25, 40.72s/it]
|
||||
36%|███▋ | 4/11 [02:42<04:45, 40.81s/it]
|
||||
45%|████▌ | 5/11 [03:23<04:04, 40.76s/it]
|
||||
55%|█████▍ | 6/11 [04:03<03:22, 40.57s/it]
|
||||
64%|██████▎ | 7/11 [04:43<02:41, 40.48s/it]
|
||||
73%|███████▎ | 8/11 [05:24<02:01, 40.44s/it]
|
||||
82%|████████▏ | 9/11 [06:04<01:20, 40.41s/it]
|
||||
91%|█████████ | 10/11 [06:45<00:40, 40.44s/it]
|
||||
100%|██████████| 11/11 [07:25<00:00, 40.45s/it]
|
||||
100%|██████████| 11/11 [07:25<00:00, 40.51s/it]
|
||||
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||
>>> Step 1: generating actions ...
|
||||
>>> Step 1: interacting with world model ...
|
||||
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||
>>> Step 2: generating actions ...
|
||||
>>> Step 2: interacting with world model ...
|
||||
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||
>>> Step 3: generating actions ...
|
||||
>>> Step 3: interacting with world model ...
|
||||
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||
>>> Step 4: generating actions ...
|
||||
>>> Step 4: interacting with world model ...
|
||||
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||
>>> Step 5: generating actions ...
|
||||
>>> Step 5: interacting with world model ...
|
||||
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||
>>> Step 6: generating actions ...
|
||||
>>> Step 6: interacting with world model ...
|
||||
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||
>>> Step 7: generating actions ...
|
||||
>>> Step 7: interacting with world model ...
|
||||
>>>>>>>>>>>>>>>>>>>>>>>>
|
||||
Reference in New Issue
Block a user