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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: object of type 'numpy.float32' has no len()
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1593, in _prepare_split_single
example = self.info.features.encode_example(record) if self.info.features is not None else record
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2152, in encode_example
return encode_nested_example(self, example)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1437, in encode_nested_example
{k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1451, in encode_nested_example
changed = bool(encode_nested_example(sub_schema, first_elmt, level=level + 1) != first_elmt)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1445, in encode_nested_example
if len(obj) > 0:
^^^^^^^^
TypeError: object of type 'numpy.float32' has no len()
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1633, in _download_and_prepare
super()._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1438, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1616, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
npy list | __key__ string | __url__ string |
|---|---|---|
[
[
0.010289706289768219,
-0.05859002098441124,
0.01464750524610281,
-0.014200126752257347,
-0.004722329322248697,
-0.06654341518878937,
0.010679091326892376,
-0.02500349096953869,
-0.030206337571144104,
0.08583040535449982,
-0.019088150933384895,
-0.018276242539286613,... | pretrain/text_emb/M004939 | hf://datasets/yonful/gem-analysis-pretrain@020bda5ff7a38aea3b998770b94ef7953909343d/pretrain.tar.gz |
[[0.00048487947788089514,0.0038557732477784157,0.0004490163119044155,0.002337889513000846,0.00146166(...TRUNCATED) | pretrain/text_emb/M002390 | "hf://datasets/yonful/gem-analysis-pretrain@020bda5ff7a38aea3b998770b94ef7953909343d/pretrain.tar.gz(...TRUNCATED) |
[[0.031663257628679276,-0.055627863854169846,0.04561280459165573,-0.020370768383145332,-0.0217333603(...TRUNCATED) | pretrain/text_emb/M012183 | "hf://datasets/yonful/gem-analysis-pretrain@020bda5ff7a38aea3b998770b94ef7953909343d/pretrain.tar.gz(...TRUNCATED) |
[[-0.04690122604370117,-0.025874163955450058,0.037867989391088486,-0.020200850442051888,-0.002490680(...TRUNCATED) | pretrain/text_emb/009280 | "hf://datasets/yonful/gem-analysis-pretrain@020bda5ff7a38aea3b998770b94ef7953909343d/pretrain.tar.gz(...TRUNCATED) |
[[-0.04107790067791939,-0.035654135048389435,0.032999344170093536,-0.02609117701649666,-0.0076575032(...TRUNCATED) | pretrain/text_emb/010909 | "hf://datasets/yonful/gem-analysis-pretrain@020bda5ff7a38aea3b998770b94ef7953909343d/pretrain.tar.gz(...TRUNCATED) |
[[0.030201861634850502,-0.007010035682469606,-0.051663536578416824,-0.06581579893827438,0.0032192510(...TRUNCATED) | pretrain/text_emb/M001699 | "hf://datasets/yonful/gem-analysis-pretrain@020bda5ff7a38aea3b998770b94ef7953909343d/pretrain.tar.gz(...TRUNCATED) |
[[0.014363846741616726,-0.027245067059993744,0.07692034542560577,0.007772771175950766,0.005200196988(...TRUNCATED) | pretrain/text_emb/M000587 | "hf://datasets/yonful/gem-analysis-pretrain@020bda5ff7a38aea3b998770b94ef7953909343d/pretrain.tar.gz(...TRUNCATED) |
[[0.02863164432346821,-0.009746942669153214,-0.02912479266524315,0.02098783664405346,0.0490248017013(...TRUNCATED) | pretrain/text_emb/M010794 | "hf://datasets/yonful/gem-analysis-pretrain@020bda5ff7a38aea3b998770b94ef7953909343d/pretrain.tar.gz(...TRUNCATED) |
[[0.03654216229915619,-0.05496913939714432,0.021248705685138702,0.002276090206578374,-0.031647007912(...TRUNCATED) | pretrain/text_emb/001804 | "hf://datasets/yonful/gem-analysis-pretrain@020bda5ff7a38aea3b998770b94ef7953909343d/pretrain.tar.gz(...TRUNCATED) |
[[-0.030492931604385376,0.005477571859955788,0.06000414118170738,-0.0124649154022336,-0.014101121574(...TRUNCATED) | pretrain/text_emb/M006848 | "hf://datasets/yonful/gem-analysis-pretrain@020bda5ff7a38aea3b998770b94ef7953909343d/pretrain.tar.gz(...TRUNCATED) |
End of preview.
YAML Metadata Warning: The task_categories "time-series-classification" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
gem-analysis-pretrain
UniMTS pretrain dataset built from HumanML3D
数据集信息
- 来源路径:
datasets/pretrain - 数据大小: 6.4 GB
- 用途: 健身动作识别模型训练
使用方法
from huggingface_hub import snapshot_download
# 下载数据集
snapshot_download(
repo_id="yonful/gem-analysis-pretrain",
repo_type="dataset",
local_dir="./datasets/pretrain"
)
或使用项目中的下载脚本:
python scripts/download_datasets.py --dataset pretrain
许可证
请参考原始数据源的许可证要求。
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