Description
Hi , Thanks for your repo.
I've followed your tutorial to create my dataset, and converted it into zarr .
the training stage went well, but when i load data to prediction, the oom shows:
(umi2) fusion@fusion-1013:~/PycharmProjects/universal_manipulation_interface$ ~/miniforge3/envs/umi2/bin/python load_checkpoint_eval.py -i data/outputs/2024.07.15/10.33.31_train_diffusion_unet_timm_umi/checkpoints/latest.ckpt -o wipe/ model_name: vit_base_patch16_clip_224.openai dataset_path: /home/fusion/PycharmProjects/universal_manipulation_interface/wipe/dataset.zarr.zip steps_per_inference: 6 Waiting for camera match dataset :wipe/videos/20240708140122 match_video_path:wipe/videos/20240708140122/raw_videos.mp4 Loaded initial frame for 1 episodes {'name': 'train_diffusion_unet_timm', '_target_': 'diffusion_policy.workspace.train_diffusion_unet_image_workspace.TrainDiffusionUnetImageWorkspace', 'task_name': 'umi', 'shape_meta': {'obs': {'camera0_rgb': {'shape': [3, 224, 224], 'horizon': 2, 'latency_steps': 0, 'down_sample_steps': 3, 'type': 'rgb', 'ignore_by_policy': False}, 'robot0_eef_pos': {'shape': [3], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'ignore_by_policy': False}, 'robot0_eef_rot_axis_angle': {'raw_shape': [3], 'shape': [6], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'rotation_rep': 'rotation_6d', 'ignore_by_policy': False}, 'robot0_gripper_width': {'shape': [1], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'ignore_by_policy': False}, 'robot0_eef_rot_axis_angle_wrt_start': {'raw_shape': [3], 'shape': [6], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'ignore_by_policy': False}}, 'action': {'shape': [10], 'horizon': 16, 'latency_steps': 0, 'down_sample_steps': 3, 'rotation_rep': 'rotation_6d'}}, 'exp_name': 'default', 'n_action_steps': 8, 'policy': {'_target_': 'diffusion_policy.policy.diffusion_unet_timm_policy.DiffusionUnetTimmPolicy', 'shape_meta': {'obs': {'camera0_rgb': {'shape': [3, 224, 224], 'horizon': 2, 'latency_steps': 0, 'down_sample_steps': 3, 'type': 'rgb', 'ignore_by_policy': False}, 'robot0_eef_pos': {'shape': [3], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'ignore_by_policy': False}, 'robot0_eef_rot_axis_angle': {'raw_shape': [3], 'shape': [6], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'rotation_rep': 'rotation_6d', 'ignore_by_policy': False}, 'robot0_gripper_width': {'shape': [1], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'ignore_by_policy': False}, 'robot0_eef_rot_axis_angle_wrt_start': {'raw_shape': [3], 'shape': [6], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'ignore_by_policy': False}}, 'action': {'shape': [10], 'horizon': 16, 'latency_steps': 0, 'down_sample_steps': 3, 'rotation_rep': 'rotation_6d'}}, 'noise_scheduler': {'_target_': 'diffusers.DDIMScheduler', 'num_train_timesteps': 50, 'beta_start': 0.0001, 'beta_end': 0.02, 'beta_schedule': 'squaredcos_cap_v2', 'clip_sample': True, 'set_alpha_to_one': True, 'steps_offset': 0, 'prediction_type': 'epsilon'}, 'obs_encoder': {'_target_': 'diffusion_policy.model.vision.timm_obs_encoder.TimmObsEncoder', 'shape_meta': {'obs': {'camera0_rgb': {'shape': [3, 224, 224], 'horizon': 2, 'latency_steps': 0, 'down_sample_steps': 3, 'type': 'rgb', 'ignore_by_policy': False}, 'robot0_eef_pos': {'shape': [3], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'ignore_by_policy': False}, 'robot0_eef_rot_axis_angle': {'raw_shape': [3], 'shape': [6], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'rotation_rep': 'rotation_6d', 'ignore_by_policy': False}, 'robot0_gripper_width': {'shape': [1], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'ignore_by_policy': False}, 'robot0_eef_rot_axis_angle_wrt_start': {'raw_shape': [3], 'shape': [6], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'ignore_by_policy': False}}, 'action': {'shape': [10], 'horizon': 16, 'latency_steps': 0, 'down_sample_steps': 3, 'rotation_rep': 'rotation_6d'}}, 'model_name': 'vit_base_patch16_clip_224.openai', 'pretrained': True, 'frozen': False, 'global_pool': '', 'feature_aggregation': 'attention_pool_2d', 'position_encording': 'sinusoidal', 'downsample_ratio': 32, 'transforms': [{'type': 'RandomCrop', 'ratio': 0.95}, {'_target_': 'torchvision.transforms.ColorJitter', 'brightness': 0.3, 'contrast': 0.4, 'saturation': 0.5, 'hue': 0.08}], 'use_group_norm': True, 'share_rgb_model': False, 'imagenet_norm': True}, 'num_inference_steps': 16, 'obs_as_global_cond': True, 'diffusion_step_embed_dim': 128, 'down_dims': [256, 512, 1024], 'kernel_size': 5, 'n_groups': 8, 'cond_predict_scale': True, 'input_pertub': 0.1, 'train_diffusion_n_samples': 1}, 'ema': {'_target_': 'diffusion_policy.model.diffusion.ema_model.EMAModel', 'update_after_step': 0, 'inv_gamma': 1.0, 'power': 0.75, 'min_value': 0.0, 'max_value': 0.9999}, 'dataloader': {'batch_size': 8, 'num_workers': 8, 'shuffle': True, 'pin_memory': True, 'persistent_workers': True}, 'val_dataloader': {'batch_size': 8, 'num_workers': 8, 'shuffle': False, 'pin_memory': True, 'persistent_workers': True}, 'optimizer': {'_target_': 'torch.optim.AdamW', 'lr': 0.0003, 'betas': [0.95, 0.999], 'eps': 1e-08, 'weight_decay': 1e-06}, 'training': {'device': 'cuda:0', 'seed': 42, 'debug': False, 'resume': False, 'lr_scheduler': 'cosine', 'lr_warmup_steps': 2000, 'num_epochs': 120, 'gradient_accumulate_every': 1, 'use_ema': True, 'freeze_encoder': False, 'rollout_every': 10, 'checkpoint_every': 10, 'val_every': 1, 'sample_every': 5, 'max_train_steps': None, 'max_val_steps': None, 'tqdm_interval_sec': 1.0}, 'logging': {'project': 'umi', 'resume': False, 'mode': 'online', 'name': '2024.07.10-14.08.26_train_diffusion_unet_timm_umi', 'tags': ['train_diffusion_unet_timm', 'umi', 'default'], 'id': None, 'group': None}, 'checkpoint': {'topk': {'monitor_key': 'train_loss', 'mode': 'min', 'k': 20, 'format_str': 'epoch={epoch:04d}-train_loss={train_loss:.3f}.ckpt'}, 'save_last_ckpt': True, 'save_last_snapshot': False}, 'multi_run': {'run_dir': 'data/outputs/2024.07.10/14.08.26_train_diffusion_unet_timm_umi', 'wandb_name_base': '2024.07.10-14.08.26_train_diffusion_unet_timm_umi'}, 'task': {'name': 'umi', 'camera_obs_latency': 0.125, 'robot_obs_latency': 0.0001, 'gripper_obs_latency': 0.02, 'dataset_frequeny': 0, 'obs_down_sample_steps': 3, 'low_dim_obs_horizon': 2, 'img_obs_horizon': 2, 'action_horizon': 16, 'ignore_proprioception': False, 'shape_meta': {'obs': {'camera0_rgb': {'shape': [3, 224, 224], 'horizon': 2, 'latency_steps': 0, 'down_sample_steps': 3, 'type': 'rgb', 'ignore_by_policy': False}, 'robot0_eef_pos': {'shape': [3], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'ignore_by_policy': False}, 'robot0_eef_rot_axis_angle': {'raw_shape': [3], 'shape': [6], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'rotation_rep': 'rotation_6d', 'ignore_by_policy': False}, 'robot0_gripper_width': {'shape': [1], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'ignore_by_policy': False}, 'robot0_eef_rot_axis_angle_wrt_start': {'raw_shape': [3], 'shape': [6], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'ignore_by_policy': False}}, 'action': {'shape': [10], 'horizon': 16, 'latency_steps': 0, 'down_sample_steps': 3, 'rotation_rep': 'rotation_6d'}}, 'task_name': 'umi', 'dataset_path': '/home/fusion/PycharmProjects/universal_manipulation_interface/wipe/dataset.zarr.zip', 'pose_repr': {'obs_pose_repr': 'relative', 'action_pose_repr': 'relative'}, 'env_runner': {'_target_': 'diffusion_policy.env_runner.real_pusht_image_runner.RealPushTImageRunner'}, 'dataset': {'_target_': 'diffusion_policy.dataset.umi_dataset.UmiDataset', 'shape_meta': {'obs': {'camera0_rgb': {'shape': [3, 224, 224], 'horizon': 2, 'latency_steps': 0, 'down_sample_steps': 3, 'type': 'rgb', 'ignore_by_policy': False}, 'robot0_eef_pos': {'shape': [3], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'ignore_by_policy': False}, 'robot0_eef_rot_axis_angle': {'raw_shape': [3], 'shape': [6], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'rotation_rep': 'rotation_6d', 'ignore_by_policy': False}, 'robot0_gripper_width': {'shape': [1], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'ignore_by_policy': False}, 'robot0_eef_rot_axis_angle_wrt_start': {'raw_shape': [3], 'shape': [6], 'horizon': 2, 'latency_steps': 0.0, 'down_sample_steps': 3, 'type': 'low_dim', 'ignore_by_policy': False}}, 'action': {'shape': [10], 'horizon': 16, 'latency_steps': 0, 'down_sample_steps': 3, 'rotation_rep': 'rotation_6d'}}, 'dataset_path': '/home/fusion/PycharmProjects/universal_manipulation_interface/wipe/dataset.zarr.zip', 'cache_dir': None, 'pose_repr': {'obs_pose_repr': 'relative', 'action_pose_repr': 'relative'}, 'action_padding': False, 'temporally_independent_normalization': False, 'repeat_frame_prob': 0.0, 'max_duration': None, 'seed': 42, 'val_ratio': 0.05}}} rgb keys: ['camera0_rgb'] low_dim_keys keys: ['robot0_eef_pos', 'robot0_eef_rot_axis_angle', 'robot0_eef_rot_axis_angle_wrt_start', 'robot0_gripper_width'] vit will use the CLS token. feature_aggregation (attention_pool_2d) is ignored! ==> reduce pretrained obs_encorder's lr obs_encorder params: 151 Warming up policy inference Traceback (most recent call last): File "/home/fusion/PycharmProjects/universal_manipulation_interface/load_checkpoint_eval.py", line 322, in <module> main() File "/home/fusion/miniforge3/envs/umi2/lib/python3.9/site-packages/click/core.py", line 1157, in __call__ return self.main(*args, **kwargs) File "/home/fusion/miniforge3/envs/umi2/lib/python3.9/site-packages/click/core.py", line 1078, in main rv = self.invoke(ctx) File "/home/fusion/miniforge3/envs/umi2/lib/python3.9/site-packages/click/core.py", line 1434, in invoke return ctx.invoke(self.callback, **ctx.params) File "/home/fusion/miniforge3/envs/umi2/lib/python3.9/site-packages/click/core.py", line 783, in invoke return __callback(*args, **kwargs) File "/home/fusion/PycharmProjects/universal_manipulation_interface/load_checkpoint_eval.py", line 266, in main result = policy.predict_action(obs_dict) File "/home/fusion/PycharmProjects/universal_manipulation_interface/diffusion_policy/policy/diffusion_unet_timm_policy.py", line 129, in predict_action nobs = self.normalizer.normalize(obs_dict) File "/home/fusion/PycharmProjects/universal_manipulation_interface/diffusion_policy/model/common/normalizer.py", line 68, in normalize return self._normalize_impl(x, forward=True) File "/home/fusion/PycharmProjects/universal_manipulation_interface/diffusion_policy/model/common/normalizer.py", line 59, in _normalize_impl result[key] = _normalize(value, params, forward=forward) File "/home/fusion/PycharmProjects/universal_manipulation_interface/diffusion_policy/model/common/normalizer.py", line 272, in _normalize x = x * scale + offset torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 1.95 GiB (GPU 0; 7.78 GiB total capacity; 6.50 GiB already allocated; 917.81 MiB free; 6.53 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
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The paper used 8 pcs of A100 , but i'm poor~ I have tried RTX3070(8G), V100(25G), A6000(51G), but all out of memory.
Actually, The trained model has 170 million parameters, 170*10^7 *4 /1024^3=0.64GB , why always show OUT OF MEMORY OOM. T_T~~~
Can somebody tell me the most minimum Gpu memory the inference stage, huge thanks~ ^o^