Datasets:
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## WebDataset\n",
"\n",
"The dataset can be exported to a `.tar` archive and iterated with the `webdataset`\n",
"package.\n",
"\n",
"After building the WebDataset-formatted archives using `make webdataset`, the dataset can be iterated as follows."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Sample csvps-val/000030\n",
"['000000', '000001', '000002', '000003', '000004', '000005', '000006', '000007',\n",
" '000008', '000009', '000010', '000011', '000012', '000013', '000014', '000015',\n",
" '000016', '000017', '000018', '000019', '000020', '000021', '000022', '000023',\n",
" '000024', '000025', '000026', '000027', '000028', '000029']\n",
"Sample csvps-val/000031\n",
"['000000', '000001', '000002', '000003', '000004', '000005', '000006', '000007',\n",
" '000008', '000009', '000010', '000011', '000012', '000013', '000014', '000015',\n",
" '000016', '000017', '000018', '000019', '000020', '000021', '000022', '000023',\n",
" '000024', '000025', '000026', '000027', '000028', '000029']\n",
"Sample csvps-val/000032\n",
"['000000', '000001', '000002', '000003', '000004', '000005', '000006', '000007',\n",
" '000008', '000009', '000010', '000011', '000012', '000013', '000014', '000015',\n",
" '000016', '000017', '000018', '000019', '000020', '000021', '000022', '000023',\n",
" '000024', '000025', '000026', '000027', '000028', '000029']\n"
]
}
],
"source": [
"import webdataset as wds\n",
"import json\n",
"\n",
"from pprint import pformat\n",
"import os\n",
"\n",
"# Create iterable dataset\n",
"shard_dir = \"shards/val\"\n",
"ds = wds.WebDataset([os.path.join(shard_dir, shard_file) for shard_file in os.listdir(shard_dir)], shardshuffle=False, verbose=True)\n",
"\n",
"# Iterate over the dataset and print the keys and the first few samples\n",
"for i, sample in enumerate(ds):\n",
" if i > 2: \n",
" break\n",
" meta_data = json.loads(sample[\"frames.json\"].decode())\n",
" print(\"Sample \" + sample[\"__key__\"])\n",
" print(pformat(meta_data, compact=True))\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Sample frames\n",
"\n",
"We can use `webdataset`'s compose helper to split the sequences into individual (pairs of) frames."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"__key__ (<class 'str'>) csvps-val/000030/000000:000001\n",
"camera.json (<class 'bytes'>) ...\n",
"metadata.json (<class 'list'>) 2\n",
"vehicle.json (<class 'list'>) 2\n",
"image.png (<class 'list'>) 2\n",
"panoptic.png (<class 'list'>) 2\n",
"depth.tiff (<class 'list'>) 2\n"
]
}
],
"source": [
"import collections\n",
"import itertools\n",
"\n",
"def find_frame_keys(keys, frames):\n",
" r\"\"\"\n",
" Returns a mapping from frame number to the keys of the sample that correspond to \n",
" that frame.\n",
" \"\"\"\n",
" meta_keys = set()\n",
" frame_keys = collections.defaultdict(list)\n",
" for key in keys:\n",
" if key.startswith(\"__\"):\n",
" continue\n",
" if \".\" not in key:\n",
" meta_keys.add(key)\n",
" continue \n",
" stem, other = key.split(\".\", 1)\n",
" if stem in frames:\n",
" frame_keys[stem].append(other)\n",
" else:\n",
" meta_keys.add(key)\n",
" return dict(frame_keys), meta_keys\n",
"\n",
"\n",
"def generate_range(src, length: int = 2, *, missing_ok: bool =True):\n",
" for sample in src:\n",
" frames = json.loads(sample.pop(\"frames.json\").decode())\n",
" key = sample[\"__key__\"]\n",
" frame_keys, meta_keys = find_frame_keys(sample.keys(), frames) \n",
" \n",
" pair_keys = set(itertools.chain.from_iterable(frame_keys.values()))\n",
" meta_data = {key: sample[key] for key in meta_keys}\n",
"\n",
" frame_ids = list(frame_keys.keys())\n",
"\n",
" for i in range(0, len(frame_keys) - length):\n",
" ids = frame_ids[i:i + length]\n",
"\n",
" pair_data = {\n",
" \"__key__\": f\"{key}/{ids[0]}:{ids[-1]}\" if len(ids) > 1 else f\"{key}/{ids[0]}\",\n",
" **meta_data,\n",
" **{\n",
" source_key: [sample.get(f\"{frame}.{source_key}\", None) for frame in ids]\n",
" for source_key in pair_keys\n",
" }\n",
" }\n",
"\n",
" yield pair_data\n",
"\n",
"ds_per_frame = ds.compose(generate_range)\n",
"\n",
"sample = next(iter(ds_per_frame))\n",
"\n",
"for key, value in sample.items():\n",
" print(f\"{key} ({type(value)})\", end=\" \")\n",
" if isinstance(value, list):\n",
" print(len(value))\n",
" elif isinstance(value, bytes):\n",
" print(\"...\")\n",
" else:\n",
" print(value)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Hugging Face Datasets\n",
"\n",
"The WebDataset can be used directly in Hugging Face Datasets."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "86f83a11f89e4f37b4acc752f5316585",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Resolving data files: 0%| | 0/40 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "c2914d517b4e436388dbf345bbb856c5",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Downloading data: 0%| | 0/40 [00:00<?, ?files/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "0d2ca2ef894e49beae715e904168e870",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Generating train split: 0 examples [00:00, ? examples/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"ename": "DatasetGenerationError",
"evalue": "An error occurred while generating the dataset",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mOSError\u001b[0m Traceback (most recent call last)",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/datasets/builder.py:1625\u001b[0m, in \u001b[0;36mGeneratorBasedBuilder._prepare_split_single\u001b[0;34m(self, gen_kwargs, fpath, file_format, max_shard_size, split_info, check_duplicate_keys, job_id)\u001b[0m\n\u001b[1;32m 1624\u001b[0m example \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minfo\u001b[38;5;241m.\u001b[39mfeatures\u001b[38;5;241m.\u001b[39mencode_example(record) \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minfo\u001b[38;5;241m.\u001b[39mfeatures \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 record\n\u001b[0;32m-> 1625\u001b[0m \u001b[43mwriter\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite\u001b[49m\u001b[43m(\u001b[49m\u001b[43mexample\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1626\u001b[0m num_examples_progress_update \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/datasets/arrow_writer.py:537\u001b[0m, in \u001b[0;36mArrowWriter.write\u001b[0;34m(self, example, key, writer_batch_size)\u001b[0m\n\u001b[1;32m 535\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhkey_record \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m--> 537\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite_examples_on_file\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/datasets/arrow_writer.py:495\u001b[0m, in \u001b[0;36mArrowWriter.write_examples_on_file\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 491\u001b[0m batch_examples[col] \u001b[38;5;241m=\u001b[39m [\n\u001b[1;32m 492\u001b[0m row[\u001b[38;5;241m0\u001b[39m][col]\u001b[38;5;241m.\u001b[39mto_pylist()[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(row[\u001b[38;5;241m0\u001b[39m][col], (pa\u001b[38;5;241m.\u001b[39mArray, pa\u001b[38;5;241m.\u001b[39mChunkedArray)) \u001b[38;5;28;01melse\u001b[39;00m row[\u001b[38;5;241m0\u001b[39m][col]\n\u001b[1;32m 493\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m row \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcurrent_examples\n\u001b[1;32m 494\u001b[0m ]\n\u001b[0;32m--> 495\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite_batch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbatch_examples\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbatch_examples\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 496\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcurrent_examples \u001b[38;5;241m=\u001b[39m []\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/datasets/arrow_writer.py:609\u001b[0m, in \u001b[0;36mArrowWriter.write_batch\u001b[0;34m(self, batch_examples, writer_batch_size)\u001b[0m\n\u001b[1;32m 608\u001b[0m pa_table \u001b[38;5;241m=\u001b[39m pa\u001b[38;5;241m.\u001b[39mTable\u001b[38;5;241m.\u001b[39mfrom_arrays(arrays, schema\u001b[38;5;241m=\u001b[39mschema)\n\u001b[0;32m--> 609\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite_table\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpa_table\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mwriter_batch_size\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/datasets/arrow_writer.py:627\u001b[0m, in \u001b[0;36mArrowWriter.write_table\u001b[0;34m(self, pa_table, writer_batch_size)\u001b[0m\n\u001b[1;32m 626\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_num_examples \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m pa_table\u001b[38;5;241m.\u001b[39mnum_rows\n\u001b[0;32m--> 627\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpa_writer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite_table\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpa_table\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mwriter_batch_size\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/pyarrow/ipc.pxi:529\u001b[0m, in \u001b[0;36mpyarrow.lib._CRecordBatchWriter.write_table\u001b[0;34m()\u001b[0m\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/pyarrow/error.pxi:89\u001b[0m, in \u001b[0;36mpyarrow.lib.check_status\u001b[0;34m()\u001b[0m\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/fsspec/implementations/local.py:422\u001b[0m, in \u001b[0;36mLocalFileOpener.write\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 421\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrite\u001b[39m(\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[0;32m--> 422\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite\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",
"\u001b[0;31mOSError\u001b[0m: [Errno 122] Disk quota exceeded",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mOSError\u001b[0m Traceback (most recent call last)",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/datasets/builder.py:1634\u001b[0m, in \u001b[0;36mGeneratorBasedBuilder._prepare_split_single\u001b[0;34m(self, gen_kwargs, fpath, file_format, max_shard_size, split_info, check_duplicate_keys, job_id)\u001b[0m\n\u001b[1;32m 1633\u001b[0m num_shards \u001b[38;5;241m=\u001b[39m shard_id \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[0;32m-> 1634\u001b[0m num_examples, num_bytes \u001b[38;5;241m=\u001b[39m \u001b[43mwriter\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfinalize\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1635\u001b[0m writer\u001b[38;5;241m.\u001b[39mclose()\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/datasets/arrow_writer.py:636\u001b[0m, in \u001b[0;36mArrowWriter.finalize\u001b[0;34m(self, close_stream)\u001b[0m\n\u001b[1;32m 635\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhkey_record \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m--> 636\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite_examples_on_file\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 637\u001b[0m \u001b[38;5;66;03m# If schema is known, infer features even if no examples were written\u001b[39;00m\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/datasets/arrow_writer.py:495\u001b[0m, in \u001b[0;36mArrowWriter.write_examples_on_file\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 491\u001b[0m batch_examples[col] \u001b[38;5;241m=\u001b[39m [\n\u001b[1;32m 492\u001b[0m row[\u001b[38;5;241m0\u001b[39m][col]\u001b[38;5;241m.\u001b[39mto_pylist()[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(row[\u001b[38;5;241m0\u001b[39m][col], (pa\u001b[38;5;241m.\u001b[39mArray, pa\u001b[38;5;241m.\u001b[39mChunkedArray)) \u001b[38;5;28;01melse\u001b[39;00m row[\u001b[38;5;241m0\u001b[39m][col]\n\u001b[1;32m 493\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m row \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcurrent_examples\n\u001b[1;32m 494\u001b[0m ]\n\u001b[0;32m--> 495\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite_batch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbatch_examples\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbatch_examples\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 496\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcurrent_examples \u001b[38;5;241m=\u001b[39m []\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/datasets/arrow_writer.py:609\u001b[0m, in \u001b[0;36mArrowWriter.write_batch\u001b[0;34m(self, batch_examples, writer_batch_size)\u001b[0m\n\u001b[1;32m 608\u001b[0m pa_table \u001b[38;5;241m=\u001b[39m pa\u001b[38;5;241m.\u001b[39mTable\u001b[38;5;241m.\u001b[39mfrom_arrays(arrays, schema\u001b[38;5;241m=\u001b[39mschema)\n\u001b[0;32m--> 609\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite_table\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpa_table\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mwriter_batch_size\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/datasets/arrow_writer.py:627\u001b[0m, in \u001b[0;36mArrowWriter.write_table\u001b[0;34m(self, pa_table, writer_batch_size)\u001b[0m\n\u001b[1;32m 626\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_num_examples \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m pa_table\u001b[38;5;241m.\u001b[39mnum_rows\n\u001b[0;32m--> 627\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpa_writer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite_table\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpa_table\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mwriter_batch_size\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/pyarrow/ipc.pxi:529\u001b[0m, in \u001b[0;36mpyarrow.lib._CRecordBatchWriter.write_table\u001b[0;34m()\u001b[0m\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/pyarrow/error.pxi:89\u001b[0m, in \u001b[0;36mpyarrow.lib.check_status\u001b[0;34m()\u001b[0m\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/fsspec/implementations/local.py:422\u001b[0m, in \u001b[0;36mLocalFileOpener.write\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 421\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrite\u001b[39m(\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[0;32m--> 422\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite\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",
"\u001b[0;31mOSError\u001b[0m: [Errno 122] Disk quota exceeded",
"\nThe above exception was the direct cause of the following exception:\n",
"\u001b[0;31mDatasetGenerationError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[14], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mdatasets\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m dataset \u001b[38;5;241m=\u001b[39m \u001b[43mdatasets\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_dataset\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mwebdataset\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdata_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mshards\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msplit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtrain\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28mprint\u001b[39m(dataset)\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/datasets/load.py:2151\u001b[0m, in \u001b[0;36mload_dataset\u001b[0;34m(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, keep_in_memory, save_infos, revision, token, streaming, num_proc, storage_options, trust_remote_code, **config_kwargs)\u001b[0m\n\u001b[1;32m 2148\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m builder_instance\u001b[38;5;241m.\u001b[39mas_streaming_dataset(split\u001b[38;5;241m=\u001b[39msplit)\n\u001b[1;32m 2150\u001b[0m \u001b[38;5;66;03m# Download and prepare data\u001b[39;00m\n\u001b[0;32m-> 2151\u001b[0m \u001b[43mbuilder_instance\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdownload_and_prepare\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2152\u001b[0m \u001b[43m \u001b[49m\u001b[43mdownload_config\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_config\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2153\u001b[0m \u001b[43m \u001b[49m\u001b[43mdownload_mode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_mode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2154\u001b[0m \u001b[43m \u001b[49m\u001b[43mverification_mode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mverification_mode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2155\u001b[0m \u001b[43m \u001b[49m\u001b[43mnum_proc\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnum_proc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2156\u001b[0m \u001b[43m \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstorage_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2157\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2159\u001b[0m \u001b[38;5;66;03m# Build dataset for splits\u001b[39;00m\n\u001b[1;32m 2160\u001b[0m keep_in_memory \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 2161\u001b[0m keep_in_memory \u001b[38;5;28;01mif\u001b[39;00m keep_in_memory \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 is_small_dataset(builder_instance\u001b[38;5;241m.\u001b[39minfo\u001b[38;5;241m.\u001b[39mdataset_size)\n\u001b[1;32m 2162\u001b[0m )\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/datasets/builder.py:924\u001b[0m, in \u001b[0;36mDatasetBuilder.download_and_prepare\u001b[0;34m(self, output_dir, download_config, download_mode, verification_mode, dl_manager, base_path, file_format, max_shard_size, num_proc, storage_options, **download_and_prepare_kwargs)\u001b[0m\n\u001b[1;32m 922\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m num_proc \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 923\u001b[0m prepare_split_kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnum_proc\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m num_proc\n\u001b[0;32m--> 924\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_download_and_prepare\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 925\u001b[0m \u001b[43m \u001b[49m\u001b[43mdl_manager\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdl_manager\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 926\u001b[0m \u001b[43m \u001b[49m\u001b[43mverification_mode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mverification_mode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 927\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mprepare_split_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 928\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mdownload_and_prepare_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 929\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 930\u001b[0m \u001b[38;5;66;03m# Sync info\u001b[39;00m\n\u001b[1;32m 931\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minfo\u001b[38;5;241m.\u001b[39mdataset_size \u001b[38;5;241m=\u001b[39m \u001b[38;5;28msum\u001b[39m(split\u001b[38;5;241m.\u001b[39mnum_bytes \u001b[38;5;28;01mfor\u001b[39;00m split \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minfo\u001b[38;5;241m.\u001b[39msplits\u001b[38;5;241m.\u001b[39mvalues())\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/datasets/builder.py:1648\u001b[0m, in \u001b[0;36mGeneratorBasedBuilder._download_and_prepare\u001b[0;34m(self, dl_manager, verification_mode, **prepare_splits_kwargs)\u001b[0m\n\u001b[1;32m 1647\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_download_and_prepare\u001b[39m(\u001b[38;5;28mself\u001b[39m, dl_manager, verification_mode, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mprepare_splits_kwargs):\n\u001b[0;32m-> 1648\u001b[0m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_download_and_prepare\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1649\u001b[0m \u001b[43m \u001b[49m\u001b[43mdl_manager\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1650\u001b[0m \u001b[43m \u001b[49m\u001b[43mverification_mode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1651\u001b[0m \u001b[43m \u001b[49m\u001b[43mcheck_duplicate_keys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mverification_mode\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m==\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mVerificationMode\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mBASIC_CHECKS\u001b[49m\n\u001b[1;32m 1652\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mverification_mode\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m==\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mVerificationMode\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mALL_CHECKS\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1653\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mprepare_splits_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1654\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/datasets/builder.py:1000\u001b[0m, in \u001b[0;36mDatasetBuilder._download_and_prepare\u001b[0;34m(self, dl_manager, verification_mode, **prepare_split_kwargs)\u001b[0m\n\u001b[1;32m 996\u001b[0m split_dict\u001b[38;5;241m.\u001b[39madd(split_generator\u001b[38;5;241m.\u001b[39msplit_info)\n\u001b[1;32m 998\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 999\u001b[0m \u001b[38;5;66;03m# Prepare split will record examples associated to the split\u001b[39;00m\n\u001b[0;32m-> 1000\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_prepare_split\u001b[49m\u001b[43m(\u001b[49m\u001b[43msplit_generator\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[43mprepare_split_kwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1001\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 1002\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m(\n\u001b[1;32m 1003\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCannot find data file. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1004\u001b[0m \u001b[38;5;241m+\u001b[39m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmanual_download_instructions \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 1005\u001b[0m \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124mOriginal error:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1006\u001b[0m \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mstr\u001b[39m(e)\n\u001b[1;32m 1007\u001b[0m ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/datasets/builder.py:1486\u001b[0m, in \u001b[0;36mGeneratorBasedBuilder._prepare_split\u001b[0;34m(self, split_generator, check_duplicate_keys, file_format, num_proc, max_shard_size)\u001b[0m\n\u001b[1;32m 1484\u001b[0m job_id \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n\u001b[1;32m 1485\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m pbar:\n\u001b[0;32m-> 1486\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mjob_id\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdone\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcontent\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_prepare_split_single\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1487\u001b[0m \u001b[43m \u001b[49m\u001b[43mgen_kwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgen_kwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mjob_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mjob_id\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[43m_prepare_split_args\u001b[49m\n\u001b[1;32m 1488\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[1;32m 1489\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mdone\u001b[49m\u001b[43m:\u001b[49m\n\u001b[1;32m 1490\u001b[0m \u001b[43m \u001b[49m\u001b[43mresult\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mcontent\u001b[49m\n",
"File \u001b[0;32m/gpfs/home3/kstolle/.local/opt/miniconda3/envs/multidvps-py312/lib/python3.12/site-packages/datasets/builder.py:1643\u001b[0m, in \u001b[0;36mGeneratorBasedBuilder._prepare_split_single\u001b[0;34m(self, gen_kwargs, fpath, file_format, max_shard_size, split_info, check_duplicate_keys, job_id)\u001b[0m\n\u001b[1;32m 1641\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(e, SchemaInferenceError) \u001b[38;5;129;01mand\u001b[39;00m e\u001b[38;5;241m.\u001b[39m__context__ \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 1642\u001b[0m e \u001b[38;5;241m=\u001b[39m e\u001b[38;5;241m.\u001b[39m__context__\n\u001b[0;32m-> 1643\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m DatasetGenerationError(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAn error occurred while generating the dataset\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n\u001b[1;32m 1645\u001b[0m \u001b[38;5;28;01myield\u001b[39;00m job_id, \u001b[38;5;28;01mTrue\u001b[39;00m, (total_num_examples, total_num_bytes, writer\u001b[38;5;241m.\u001b[39m_features, num_shards, shard_lengths)\n",
"\u001b[0;31mDatasetGenerationError\u001b[0m: An error occurred while generating the dataset"
]
}
],
"source": [
"import datasets\n",
"\n",
"dataset = datasets.load_dataset(\"webdataset\", data_dir=\"shards\", split=\"train\")\n",
"print(dataset)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": []
}
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|