{ "cells": [ { "cell_type": "markdown", "id": "e484a4a7", "metadata": {}, "source": [ "### 【可选】下载已采集数据集\n" ] }, { "cell_type": "code", "execution_count": 1, "id": "4bf9c0ee", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "fatal: destination path 'datawhale_eai_pnp_language' already exists and is not an empty directory.\n" ] } ], "source": [ "'''\n", "If you want to use the collected dataset, please download it from Hugging Face.\n", "'''\n", "!git clone https://huggingface.co/datasets/Jeongeun/omy_pnp_language" ] }, { "cell_type": "markdown", "id": "baff685c", "metadata": {}, "source": [ "# 可视化你的数据\n", "\n", "\n", "\n", "基于重建后的仿真场景可视化你的动作。\n", "\n", "主窗口会回放动作。\n", "\n", "右上和右下叠加图像来自数据集。\n" ] }, { "cell_type": "code", "execution_count": null, "id": "fa9c3741", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/jeongeun/.pyenv/versions/3.10.2/envs/lerobot/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", " from .autonotebook import tqdm as notebook_tqdm\n", "Downloading data: 100%|██████████| 20/20 [00:00<00:00, 202623.38files/s]\n", "Generating train split: 2621 examples [00:00, 5670.23 examples/s]\n" ] } ], "source": [ "from lerobot.common.datasets.lerobot_dataset import LeRobotDataset, LeRobotDatasetMetadata\n", "import numpy as np\n", "from lerobot.common.datasets.utils import write_json, serialize_dict\n", "ROOT = \"./demo_data_language\" # The root directory to save the demonstrations \n", "# If you have downloaded the dataset from Hugging Face, you can set the root to the directory where the dataset is stored\n", "# ROOT = './datawhale_eai_pnp_language' # if you want to use the example data provided, root = './datawhale_eai_pnp_language' instead!\n", "dataset = LeRobotDataset('datawhale_eai_pnp_language', root=ROOT) # if youu want to use the example data provided, root = './datawhale_eai_pnp_language' instead!\n", "\n", "# If you want to use the collected dataset, please download it from Hugging Face.\n", "# dataset = LeRobotDataset('datawhale_eai_pnp_language', root='datawhale_eai_pnp_language')" ] }, { "cell_type": "markdown", "id": "a4ad4e59", "metadata": {}, "source": [ "## 加载数据集\n" ] }, { "cell_type": "code", "execution_count": 2, "id": "4aeafda1", "metadata": {}, "outputs": [], "source": [ "import torch\n", "\n", "class EpisodeSampler(torch.utils.data.Sampler):\n", " \"\"\"\n", " Sampler for a single episode\n", " \"\"\"\n", " def __init__(self, dataset: LeRobotDataset, episode_index: int):\n", " from_idx = dataset.episode_data_index[\"from\"][episode_index].item()\n", " to_idx = dataset.episode_data_index[\"to\"][episode_index].item()\n", " self.frame_ids = range(from_idx, to_idx)\n", "\n", " def __iter__(self):\n", " return iter(self.frame_ids)\n", "\n", " def __len__(self) -> int:\n", " return len(self.frame_ids)" ] }, { "cell_type": "code", "execution_count": 3, "id": "ad34e64c", "metadata": {}, "outputs": [], "source": [ "# Select an episode index that you want to visualize\n", "episode_index = 0\n", "\n", "episode_sampler = EpisodeSampler(dataset, episode_index)\n", "dataloader = torch.utils.data.DataLoader(\n", " dataset,\n", " num_workers=1,\n", " batch_size=1,\n", " sampler=episode_sampler,\n", ")\n" ] }, { "cell_type": "markdown", "id": "5f8bb337", "metadata": {}, "source": [ "## 在仿真中可视化数据集\n" ] }, { "cell_type": "code", "execution_count": 4, "id": "7d6c6e47", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "-----------------------------------------------------------------------------\n", "name:[Tabletop] dt:[0.002] HZ:[500]\n", " n_qpos:[31] n_qvel:[28] n_qacc:[28] n_ctrl:[10]\n", " integrator:[IMPLICITFAST]\n", "\n", "n_body:[23]\n", " [0/23] [world] mass:[0.00]kg\n", " [1/23] [front_object_table] mass:[1.00]kg\n", " [2/23] [camera] mass:[0.00]kg\n", " [3/23] [camera2] mass:[0.00]kg\n", " [4/23] [camera3] mass:[0.00]kg\n", " [5/23] [link1] mass:[2.06]kg\n", " [6/23] [link2] mass:[3.68]kg\n", " [7/23] [link3] mass:[2.39]kg\n", " [8/23] [link4] mass:[1.40]kg\n", " [9/23] [link5] mass:[1.40]kg\n", " [10/23] [link6] mass:[0.65]kg\n", " [11/23] [camera_center] mass:[0.00]kg\n", " [12/23] [tcp_link] mass:[0.32]kg\n", " [13/23] [rh_p12_rn_r1] mass:[0.07]kg\n", " [14/23] [rh_p12_rn_r2] mass:[0.02]kg\n", " [15/23] [rh_p12_rn_l1] mass:[0.07]kg\n", " [16/23] [rh_p12_rn_l2] mass:[0.02]kg\n", " [17/23] [body_obj_mug_5] mass:[0.00]kg\n", " [18/23] [object_mug_5] mass:[0.08]kg\n", " [19/23] [body_obj_plate_11] mass:[0.00]kg\n", " [20/23] [object_plate_11] mass:[0.10]kg\n", " [21/23] [body_obj_mug_6] mass:[0.00]kg\n", " [22/23] [object_mug_6] mass:[0.08]kg\n", "body_total_mass:[13.35]kg\n", "\n", "n_geom:[116]\n", "geom_names:['floor', None, 'front_object_table', None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None]\n", "\n", "n_mesh:[112]\n", "mesh_names:['base_unit', 'link1', 'link2', 'link3', 'link4', 'link5', 'link6', 'flange', 'base', 'r1', 'r2', 'l1', 'l2', 'mug_5_normalized_0_vis', 'mug_5_normalized_collision_22._coll', 'mug_5_normalized_collision_23._coll', 'mug_5_normalized_collision_21._coll', 'mug_5_normalized_collision_20._coll', 'mug_5_normalized_collision_24._coll', 'mug_5_normalized_collision_30._coll', 'mug_5_normalized_collision_18._coll', 'mug_5_normalized_collision_19._coll', 'mug_5_normalized_collision_31._coll', 'mug_5_normalized_collision_25._coll', 'mug_5_normalized_collision_27._coll', 'mug_5_normalized_collision_26._coll', 'mug_5_normalized_collision_9._coll', 'mug_5_normalized_collision_8._coll', 'mug_5_normalized_collision_6._coll', 'mug_5_normalized_collision_7._coll', 'mug_5_normalized_collision_5._coll', 'mug_5_normalized_collision_4._coll', 'mug_5_normalized_collision_0._coll', 'mug_5_normalized_collision_1._coll', 'mug_5_normalized_collision_3._coll', 'mug_5_normalized_collision_2._coll', 'mug_5_normalized_collision_17._coll', 'mug_5_normalized_collision_16._coll', 'mug_5_normalized_collision_28._coll', 'mug_5_normalized_collision_14._coll', 'mug_5_normalized_collision_15._coll', 'mug_5_normalized_collision_29._coll', 'mug_5_normalized_collision_11._coll', 'mug_5_normalized_collision_10._coll', 'mug_5_normalized_collision_12._coll', 'mug_5_normalized_collision_13._coll', 'plate_11_normalized_0_vis', 'plate_11_normalized_collision_22._coll', 'plate_11_normalized_collision_23._coll', 'plate_11_normalized_collision_21._coll', 'plate_11_normalized_collision_20._coll', 'plate_11_normalized_collision_24._coll', 'plate_11_normalized_collision_30._coll', 'plate_11_normalized_collision_18._coll', 'plate_11_normalized_collision_19._coll', 'plate_11_normalized_collision_31._coll', 'plate_11_normalized_collision_25._coll', 'plate_11_normalized_collision_27._coll', 'plate_11_normalized_collision_26._coll', 'plate_11_normalized_collision_9._coll', 'plate_11_normalized_collision_8._coll', 'plate_11_normalized_collision_6._coll', 'plate_11_normalized_collision_7._coll', 'plate_11_normalized_collision_5._coll', 'plate_11_normalized_collision_4._coll', 'plate_11_normalized_collision_0._coll', 'plate_11_normalized_collision_1._coll', 'plate_11_normalized_collision_3._coll', 'plate_11_normalized_collision_2._coll', 'plate_11_normalized_collision_17._coll', 'plate_11_normalized_collision_16._coll', 'plate_11_normalized_collision_28._coll', 'plate_11_normalized_collision_14._coll', 'plate_11_normalized_collision_15._coll', 'plate_11_normalized_collision_29._coll', 'plate_11_normalized_collision_11._coll', 'plate_11_normalized_collision_10._coll', 'plate_11_normalized_collision_12._coll', 'plate_11_normalized_collision_13._coll', 'mug_6_normalized_0_vis', 'mug_6_normalized_collision_22._coll', 'mug_6_normalized_collision_23._coll', 'mug_6_normalized_collision_21._coll', 'mug_6_normalized_collision_20._coll', 'mug_6_normalized_collision_24._coll', 'mug_6_normalized_collision_30._coll', 'mug_6_normalized_collision_18._coll', 'mug_6_normalized_collision_19._coll', 'mug_6_normalized_collision_31._coll', 'mug_6_normalized_collision_25._coll', 'mug_6_normalized_collision_27._coll', 'mug_6_normalized_collision_26._coll', 'mug_6_normalized_collision_9._coll', 'mug_6_normalized_collision_8._coll', 'mug_6_normalized_collision_6._coll', 'mug_6_normalized_collision_7._coll', 'mug_6_normalized_collision_5._coll', 'mug_6_normalized_collision_4._coll', 'mug_6_normalized_collision_0._coll', 'mug_6_normalized_collision_1._coll', 'mug_6_normalized_collision_3._coll', 'mug_6_normalized_collision_2._coll', 'mug_6_normalized_collision_17._coll', 'mug_6_normalized_collision_16._coll', 'mug_6_normalized_collision_28._coll', 'mug_6_normalized_collision_14._coll', 'mug_6_normalized_collision_15._coll', 'mug_6_normalized_collision_29._coll', 'mug_6_normalized_collision_11._coll', 'mug_6_normalized_collision_10._coll', 'mug_6_normalized_collision_12._coll', 'mug_6_normalized_collision_13._coll']\n", "\n", "n_joint:[13]\n", " [0/13] [joint1] axis:[0. 0. 1.]\n", " [1/13] [joint2] axis:[0. 1. 0.]\n", " [2/13] [joint3] axis:[0. 1. 0.]\n", " [3/13] [joint4] axis:[0. 1. 0.]\n", " [4/13] [joint5] axis:[0. 0. 1.]\n", " [5/13] [joint6] axis:[0. 1. 0.]\n", " [6/13] [rh_r1] axis:[1. 0. 0.]\n", " [7/13] [rh_r2] axis:[-1. 0. 0.]\n", " [8/13] [rh_l1] axis:[-1. 0. 0.]\n", " [9/13] [rh_l2] axis:[1. 0. 0.]\n", " [10/13] [None] axis:[0. 0. 1.]\n", " [11/13] [None] axis:[0. 0. 1.]\n", " [12/13] [None] axis:[0. 0. 1.]\n", "\n", "n_dof:[28] (=number of rows of Jacobian)\n", " [0/28] [None] attached joint:[joint1] body:[link1]\n", " [1/28] [None] attached joint:[joint2] body:[link2]\n", " [2/28] [None] attached joint:[joint3] body:[link3]\n", " [3/28] [None] attached joint:[joint4] body:[link4]\n", " [4/28] [None] attached joint:[joint5] body:[link5]\n", " [5/28] [None] attached joint:[joint6] body:[link6]\n", " [6/28] [None] attached joint:[rh_r1] body:[rh_p12_rn_r1]\n", " [7/28] [None] attached joint:[rh_r2] body:[rh_p12_rn_r2]\n", " [8/28] [None] attached joint:[rh_l1] body:[rh_p12_rn_l1]\n", " [9/28] [None] attached joint:[rh_l2] body:[rh_p12_rn_l2]\n", " [10/28] [None] attached joint:[None] body:[body_obj_mug_5]\n", " [11/28] [None] attached joint:[None] body:[body_obj_mug_5]\n", " [12/28] [None] attached joint:[None] body:[body_obj_mug_5]\n", " [13/28] [None] attached joint:[None] body:[body_obj_mug_5]\n", " [14/28] [None] attached joint:[None] body:[body_obj_mug_5]\n", " [15/28] [None] attached joint:[None] body:[body_obj_mug_5]\n", " [16/28] [None] attached joint:[None] body:[body_obj_plate_11]\n", " [17/28] [None] attached joint:[None] body:[body_obj_plate_11]\n", " [18/28] [None] attached joint:[None] body:[body_obj_plate_11]\n", " [19/28] [None] attached joint:[None] body:[body_obj_plate_11]\n", " [20/28] [None] attached joint:[None] body:[body_obj_plate_11]\n", " [21/28] [None] attached joint:[None] body:[body_obj_plate_11]\n", " [22/28] [None] attached joint:[None] body:[body_obj_mug_6]\n", " [23/28] [None] attached joint:[None] body:[body_obj_mug_6]\n", " [24/28] [None] attached joint:[None] body:[body_obj_mug_6]\n", " [25/28] [None] attached joint:[None] body:[body_obj_mug_6]\n", " [26/28] [None] attached joint:[None] body:[body_obj_mug_6]\n", " [27/28] [None] attached joint:[None] body:[body_obj_mug_6]\n", "\n", "Free joint information. n_free_joint:[3]\n", " [0/3] [None] body_name_attached:[body_obj_mug_5]\n", " [1/3] [None] body_name_attached:[body_obj_plate_11]\n", " [2/3] [None] body_name_attached:[body_obj_mug_6]\n", "\n", "Revolute joint information. n_rev_joint:[10]\n", " [0/10] [joint1] range:[-6.283]~[6.283]\n", " [1/10] [joint2] range:[-6.283]~[6.283]\n", " [2/10] [joint3] range:[-6.283]~[6.283]\n", " [3/10] [joint4] range:[-6.283]~[6.283]\n", " [4/10] [joint5] range:[-6.283]~[6.283]\n", " [5/10] [joint6] range:[-6.283]~[6.283]\n", " [6/10] [rh_r1] range:[0.000]~[1.100]\n", " [7/10] [rh_r2] range:[0.000]~[1.000]\n", " [8/10] [rh_l1] range:[0.000]~[1.100]\n", " [9/10] [rh_l2] range:[0.000]~[1.000]\n", "\n", "Prismatic joint information. n_pri_joint:[0]\n", "\n", "Control information. n_ctrl:[10]\n", " [0/10] [actuator_joint1] range:[-6.283]~[6.283] gear:[1.00] type:[JOINT]\n", " [1/10] [actuator_joint2] range:[-6.283]~[6.283] gear:[1.00] type:[JOINT]\n", " [2/10] [actuator_joint3] range:[-6.283]~[6.283] gear:[1.00] type:[JOINT]\n", " [3/10] [actuator_joint4] range:[-6.283]~[6.283] gear:[1.00] type:[JOINT]\n", " [4/10] [actuator_joint5] range:[-6.283]~[6.283] gear:[1.00] type:[JOINT]\n", " [5/10] [actuator_joint6] range:[-6.283]~[6.283] gear:[1.00] type:[JOINT]\n", " [6/10] [actuator_rh_r1] range:[0.000]~[1.100] gear:[1.00] type:[JOINT]\n", " [7/10] [actuator_rh_r2] range:[0.000]~[1.000] gear:[1.00] type:[JOINT]\n", " [8/10] [actuator_rh_l1] range:[0.000]~[1.100] gear:[1.00] type:[JOINT]\n", " [9/10] [actuator_rh_l2] range:[0.000]~[1.000] gear:[1.00] type:[JOINT]\n", "\n", "Camera information. n_cam:[4]\n", " [0/4] [agentview] fov:[60.0]\n", " [1/4] [topview] fov:[90.0]\n", " [2/4] [sideview] fov:[90.0]\n", " [3/4] [egocentric] fov:[90.0]\n", "\n", "n_sensor:[0]\n", "sensor_names:[]\n", "n_site:[9]\n", "site_names:['bottom_site_mug_5', 'top_site_mug_5', 'horizontal_radius_site_mug_5', 'bottom_site_plate_11', 'top_site_plate_11', 'horizontal_radius_site_plate_11', 'bottom_site_mug_6', 'top_site_mug_6', 'horizontal_radius_site_mug_6']\n", "-----------------------------------------------------------------------------\n", "env:[Tabletop] reset\n", "env:[Tabletop] reset\n", "env:[Tabletop] initalize viewer\n", "DONE INITIALIZATION\n" ] } ], "source": [ "from mujoco_env.y_env2 import SimpleEnv2\n", "xml_path = './asset/example_scene_y2.xml'\n", "PnPEnv = SimpleEnv2(xml_path, action_type='joint_angle')" ] }, { "cell_type": "code", "execution_count": 5, "id": "142cb7e6", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "DONE INITIALIZATION\n", "DONE INITIALIZATION\n", "DONE INITIALIZATION\n" ] } ], "source": [ "step = 0\n", "iter_dataloader = iter(dataloader)\n", "PnPEnv.reset()\n", "\n", "while PnPEnv.env.is_viewer_alive():\n", " PnPEnv.step_env()\n", " if PnPEnv.env.loop_every(HZ=20):\n", " # Get the action from dataset\n", " data = next(iter_dataloader)\n", " if step == 0:\n", " # Reset the object pose based on the dataset\n", " instruction = data['task'][0]\n", " PnPEnv.set_instruction(instruction)\n", " PnPEnv.set_obj_pose(data['obj_init'][0,:3], data['obj_init'][0,3:6], data['obj_init'][0,6:9])\n", " # Get the action from dataset\n", " action = data['action'].numpy()\n", " obs = PnPEnv.step(action[0])\n", "\n", " # Visualize the image from dataset to rgb_overlay\n", " PnPEnv.rgb_agent = data['observation.image'][0].numpy()*255\n", " PnPEnv.rgb_ego = data['observation.wrist_image'][0].numpy()*255\n", " PnPEnv.rgb_agent = PnPEnv.rgb_agent.astype(np.uint8)\n", " PnPEnv.rgb_ego = PnPEnv.rgb_ego.astype(np.uint8)\n", " # 3 256 256 -> 256 256 3\n", " PnPEnv.rgb_agent = np.transpose(PnPEnv.rgb_agent, (1,2,0))\n", " PnPEnv.rgb_ego = np.transpose(PnPEnv.rgb_ego, (1,2,0))\n", " PnPEnv.rgb_side = np.zeros((480, 640, 3), dtype=np.uint8)\n", " PnPEnv.render()\n", " step += 1\n", "\n", " if step == len(episode_sampler):\n", " # start from the beginning\n", " iter_dataloader = iter(dataloader)\n", " PnPEnv.reset()\n", " step = 0\n", " # PnPEnv" ] }, { "cell_type": "code", "execution_count": 6, "id": "3dbcb29d", "metadata": {}, "outputs": [], "source": [ "PnPEnv.env.close_viewer()" ] }, { "cell_type": "code", "execution_count": 7, "id": "161b4d3b", "metadata": { "scrolled": true }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Recovering from metadata files: 100%|██████████| 24/24 [00:00<00:00, 3053.92it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n", "\n", "---------- 2025-06-28 20:30:05 (0:00:00) ----------\n", "Files: hashed 1/24 (2.3K/382.2M) | pre-uploaded: 0/0 (0.0/382.2M) (+24 unsure) | committed: 0/24 (0.0/382.2M) | ignored: 0\n", "Workers: hashing: 22 | get upload mode: 0 | pre-uploading: 0 | committing: 0 | waiting: 0\n", "---------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "episode_000007.parquet: 0%| | 0.00/14.2M [00:00 409\u001b[0m \u001b[43mresponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mraise_for_status\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 410\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m HTTPError \u001b[38;5;28;01mas\u001b[39;00m e:\n", "File \u001b[0;32m~/.pyenv/versions/3.10.2/envs/lerobot/lib/python3.10/site-packages/requests/models.py:1024\u001b[0m, in \u001b[0;36mResponse.raise_for_status\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1023\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m http_error_msg:\n\u001b[0;32m-> 1024\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m HTTPError(http_error_msg, response\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m)\n", "\u001b[0;31mHTTPError\u001b[0m: 404 Client Error: Not Found for url: https://huggingface.co/api/datasets/datawhale_eai_pnp_language/preupload/main", "\nThe above exception was the direct cause of the following exception:\n", "\u001b[0;31mRepositoryNotFoundError\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[7], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mdataset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpush_to_hub\u001b[49m\u001b[43m(\u001b[49m\u001b[43mupload_large_folder\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m~/.pyenv/versions/3.10.2/envs/lerobot/lib/python3.10/site-packages/lerobot/common/datasets/lerobot_dataset.py:545\u001b[0m, in \u001b[0;36mLeRobotDataset.push_to_hub\u001b[0;34m(self, branch, tags, license, tag_version, push_videos, private, allow_patterns, upload_large_folder, **card_kwargs)\u001b[0m\n\u001b[1;32m 541\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m hub_api\u001b[38;5;241m.\u001b[39mfile_exists(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrepo_id, REPOCARD_NAME, repo_type\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdataset\u001b[39m\u001b[38;5;124m\"\u001b[39m, 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\u001b[0;32m~/.pyenv/versions/3.10.2/envs/lerobot/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py:114\u001b[0m, in \u001b[0;36mvalidate_hf_hub_args.._inner_fn\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 111\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m check_use_auth_token:\n\u001b[1;32m 112\u001b[0m kwargs \u001b[38;5;241m=\u001b[39m smoothly_deprecate_use_auth_token(fn_name\u001b[38;5;241m=\u001b[39mfn\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, has_token\u001b[38;5;241m=\u001b[39mhas_token, kwargs\u001b[38;5;241m=\u001b[39mkwargs)\n\u001b[0;32m--> 114\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m~/.pyenv/versions/3.10.2/envs/lerobot/lib/python3.10/site-packages/huggingface_hub/hf_api.py:1551\u001b[0m, in \u001b[0;36mfuture_compatible.._inner\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1548\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrun_as_future(fn, \u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 1550\u001b[0m \u001b[38;5;66;03m# Otherwise, call the function normally\u001b[39;00m\n\u001b[0;32m-> 1551\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m~/.pyenv/versions/3.10.2/envs/lerobot/lib/python3.10/site-packages/huggingface_hub/hf_api.py:3991\u001b[0m, in \u001b[0;36mHfApi.create_commit\u001b[0;34m(self, repo_id, operations, commit_message, commit_description, token, repo_type, revision, create_pr, num_threads, parent_commit, run_as_future)\u001b[0m\n\u001b[1;32m 3988\u001b[0m \u001b[38;5;66;03m# If updating twice the same file or update then delete a file in a single commit\u001b[39;00m\n\u001b[1;32m 3989\u001b[0m _warn_on_overwriting_operations(operations)\n\u001b[0;32m-> 3991\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpreupload_lfs_files\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 3992\u001b[0m \u001b[43m \u001b[49m\u001b[43mrepo_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrepo_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3993\u001b[0m \u001b[43m 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\u001b[49m\u001b[43mnum_threads\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnum_threads\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3999\u001b[0m \u001b[43m \u001b[49m\u001b[43mfree_memory\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# do not remove `CommitOperationAdd.path_or_fileobj` on LFS files for \"normal\" users\u001b[39;49;00m\n\u001b[1;32m 4000\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 4002\u001b[0m files_to_copy \u001b[38;5;241m=\u001b[39m _fetch_files_to_copy(\n\u001b[1;32m 4003\u001b[0m copies\u001b[38;5;241m=\u001b[39mcopies,\n\u001b[1;32m 4004\u001b[0m repo_type\u001b[38;5;241m=\u001b[39mrepo_type,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 4008\u001b[0m endpoint\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mendpoint,\n\u001b[1;32m 4009\u001b[0m )\n\u001b[1;32m 4010\u001b[0m \u001b[38;5;66;03m# Remove no-op operations (files that have not changed)\u001b[39;00m\n", "File \u001b[0;32m~/.pyenv/versions/3.10.2/envs/lerobot/lib/python3.10/site-packages/huggingface_hub/hf_api.py:4214\u001b[0m, in \u001b[0;36mHfApi.preupload_lfs_files\u001b[0;34m(self, repo_id, additions, token, repo_type, revision, create_pr, num_threads, free_memory, gitignore_content)\u001b[0m\n\u001b[1;32m 4212\u001b[0m \u001b[38;5;66;03m# Check which new files are LFS\u001b[39;00m\n\u001b[1;32m 4213\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 4214\u001b[0m \u001b[43m_fetch_upload_modes\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 4215\u001b[0m \u001b[43m \u001b[49m\u001b[43madditions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnew_additions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4216\u001b[0m \u001b[43m \u001b[49m\u001b[43mrepo_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrepo_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4217\u001b[0m \u001b[43m 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\u001b[49m\u001b[43mgitignore_content\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgitignore_content\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4223\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 4224\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m RepositoryNotFoundError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 4225\u001b[0m e\u001b[38;5;241m.\u001b[39mappend_to_message(_CREATE_COMMIT_NO_REPO_ERROR_MESSAGE)\n", "File \u001b[0;32m~/.pyenv/versions/3.10.2/envs/lerobot/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py:114\u001b[0m, in \u001b[0;36mvalidate_hf_hub_args.._inner_fn\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 111\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m check_use_auth_token:\n\u001b[1;32m 112\u001b[0m kwargs \u001b[38;5;241m=\u001b[39m smoothly_deprecate_use_auth_token(fn_name\u001b[38;5;241m=\u001b[39mfn\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, has_token\u001b[38;5;241m=\u001b[39mhas_token, kwargs\u001b[38;5;241m=\u001b[39mkwargs)\n\u001b[0;32m--> 114\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m~/.pyenv/versions/3.10.2/envs/lerobot/lib/python3.10/site-packages/huggingface_hub/_commit_api.py:542\u001b[0m, in \u001b[0;36m_fetch_upload_modes\u001b[0;34m(additions, repo_type, repo_id, headers, revision, endpoint, create_pr, gitignore_content)\u001b[0m\n\u001b[1;32m 534\u001b[0m payload[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgitIgnore\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m gitignore_content\n\u001b[1;32m 536\u001b[0m resp \u001b[38;5;241m=\u001b[39m get_session()\u001b[38;5;241m.\u001b[39mpost(\n\u001b[1;32m 537\u001b[0m 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)\n\u001b[0;32m--> 542\u001b[0m \u001b[43mhf_raise_for_status\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresp\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 543\u001b[0m preupload_info \u001b[38;5;241m=\u001b[39m _validate_preupload_info(resp\u001b[38;5;241m.\u001b[39mjson())\n\u001b[1;32m 544\u001b[0m upload_modes\u001b[38;5;241m.\u001b[39mupdate(\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m{file[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpath\u001b[39m\u001b[38;5;124m\"\u001b[39m]: file[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muploadMode\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;28;01mfor\u001b[39;00m file \u001b[38;5;129;01min\u001b[39;00m preupload_info[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfiles\u001b[39m\u001b[38;5;124m\"\u001b[39m]})\n", "File \u001b[0;32m~/.pyenv/versions/3.10.2/envs/lerobot/lib/python3.10/site-packages/huggingface_hub/utils/_http.py:458\u001b[0m, in \u001b[0;36mhf_raise_for_status\u001b[0;34m(response, endpoint_name)\u001b[0m\n\u001b[1;32m 438\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m error_code \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRepoNotFound\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m (\n\u001b[1;32m 439\u001b[0m response\u001b[38;5;241m.\u001b[39mstatus_code \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m401\u001b[39m\n\u001b[1;32m 440\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m error_message \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid credentials in Authorization header\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 448\u001b[0m \u001b[38;5;66;03m# => for now, we process them as `RepoNotFound` anyway.\u001b[39;00m\n\u001b[1;32m 449\u001b[0m \u001b[38;5;66;03m# See https://gist.github.com/Wauplin/46c27ad266b15998ce56a6603796f0b9\u001b[39;00m\n\u001b[1;32m 450\u001b[0m message \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 451\u001b[0m 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\u001b[38;5;241m400\u001b[39m:\n\u001b[1;32m 461\u001b[0m message \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 462\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124mBad request for \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mendpoint_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m endpoint:\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m endpoint_name \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124mBad request:\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 463\u001b[0m )\n", "\u001b[0;31mRepositoryNotFoundError\u001b[0m: 404 Client Error. (Request ID: Root=1-685fd26f-57fb9db57755896406046660;d0a22307-7fa7-4a09-8e35-72396bf34876)\n\nRepository Not Found for url: https://huggingface.co/api/datasets/datawhale_eai_pnp_language/preupload/main.\nPlease make sure you specified the correct `repo_id` and `repo_type`.\nIf you are trying to access a private or gated repo, make sure you are authenticated.\nNote: Creating a commit assumes that the repo already exists on the Huggingface Hub. Please use `create_repo` if it's not the case." ] } ], "source": [ "dataset.push_to_hub(upload_large_folder=True)" ] }, { "cell_type": "code", "execution_count": null, "id": "cc64b4a3", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.3" } }, "nbformat": 4, "nbformat_minor": 5 }