/home/ubuntu/Isaac-GR00T/.venv/lib/python3.10/site-packages/albumentations/__init__.py:13: UserWarning: A new version of Albumentations is available: 2.0.8 (you have 1.4.18). Upgrade using: pip install -U albumentations. To disable automatic update checks, set the environment variable NO_ALBUMENTATIONS_UPDATE to 1. check_for_updates() /home/ubuntu/Isaac-GR00T/gr00t/experiment/experiment.py:98: UserWarning: image_crop_size and image_target_size will be deprecated in the future. Please use shortest_image_edge and crop_fraction instead. warnings.warn( 05/28/2026 10:18:32 - INFO - Saved config to /home/ubuntu/groot-files/checkpoints/run-2026-05-28-101824/groot-wbc-8/experiment_cfg wandb: Currently logged in as: lucafrat (lucafrat-microsoft) to https://api.wandb.ai. Use `wandb login --relogin` to force relogin wandb: Tracking run with wandb version 0.23.0 wandb: Run data is saved locally in /home/ubuntu/Isaac-GR00T/wandb/run-20260528_101832-7coniw77 wandb: Run `wandb offline` to turn off syncing. wandb: Syncing run groot-wbc-8 wandb: ⭐️ View project at https://wandb.ai/lucafrat-microsoft/groot-wbc wandb: 🚀 View run at https://wandb.ai/lucafrat-microsoft/groot-wbc/runs/7coniw77 Flash Attention 2 only supports torch.float16 and torch.bfloat16 dtypes, but the current dype in Qwen3VLForConditionalGeneration is torch.float32. You should run training or inference using Automatic Mixed-Precision via the `with torch.autocast(device_type='torch_device'):` decorator, or load the model with the `dtype` argument. Example: `model = AutoModel.from_pretrained("openai/whisper-tiny", attn_implementation="flash_attention_2", dtype=torch.float16)` Flash Attention 2 only supports torch.float16 and torch.bfloat16 dtypes, but the current dype in Qwen3VLModel is torch.float32. You should run training or inference using Automatic Mixed-Precision via the `with torch.autocast(device_type='torch_device'):` decorator, or load the model with the `dtype` argument. Example: `model = AutoModel.from_pretrained("openai/whisper-tiny", attn_implementation="flash_attention_2", dtype=torch.float16)` Flash Attention 2 only supports torch.float16 and torch.bfloat16 dtypes, but the current dype in Qwen3VLVisionModel is torch.float32. You should run training or inference using Automatic Mixed-Precision via the `with torch.autocast(device_type='torch_device'):` decorator, or load the model with the `dtype` argument. Example: `model = AutoModel.from_pretrained("openai/whisper-tiny", attn_implementation="flash_attention_2", dtype=torch.float16)` Flash Attention 2 only supports torch.float16 and torch.bfloat16 dtypes, but the current dype in Qwen3VLTextModel is torch.float32. You should run training or inference using Automatic Mixed-Precision via the `with torch.autocast(device_type='torch_device'):` decorator, or load the model with the `dtype` argument. Example: `model = AutoModel.from_pretrained("openai/whisper-tiny", attn_implementation="flash_attention_2", dtype=torch.float16)` /home/ubuntu/Isaac-GR00T/gr00t/model/modules/dit.py:255: FutureWarning: Accessing config attribute `compute_dtype` directly via 'AlternateVLDiT' object attribute is deprecated. Please access 'compute_dtype' over 'AlternateVLDiT's config object instead, e.g. 'unet.config.compute_dtype'. embedding_dim=self.inner_dim, compute_dtype=self.compute_dtype /home/ubuntu/Isaac-GR00T/gr00t/model/modules/dit.py:286: FutureWarning: Accessing config attribute `output_dim` directly via 'AlternateVLDiT' object attribute is deprecated. Please access 'output_dim' over 'AlternateVLDiT's config object instead, e.g. 'unet.config.output_dim'. self.proj_out_2 = nn.Linear(self.inner_dim, self.output_dim) Total number of DiT parameters: 1091722240 05/28/2026 10:18:34 - INFO - Using AlternateVLDiT for diffusion model Total number of SelfAttentionTransformer parameters: 201433088 Loading checkpoint shards: 0%| | 0/2 [00:00