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Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError Message: The split names could not be parsed from the dataset config. Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 298, in get_dataset_config_info for split_generator in builder._split_generators( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 78, in _split_generators first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE)) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 52, in _get_pipeline_from_tar current_example[field_name] = cls.DECODERS[data_extension](current_example[field_name]) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 299, in npy_loads return numpy.lib.format.read_array(stream, allow_pickle=False) File "/src/services/worker/.venv/lib/python3.9/site-packages/numpy/lib/format.py", line 795, in read_array raise ValueError("Object arrays cannot be loaded when " ValueError: Object arrays cannot be loaded when allow_pickle=False 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/split_names.py", line 65, in compute_split_names_from_streaming_response for split in get_dataset_split_names( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 352, in get_dataset_split_names info = get_dataset_config_info( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 303, in get_dataset_config_info raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.
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ManipGen-PartNet
ManipGen-PartNet is used to train grasp handle, open, and close policies in ManipGen.
The dataset contains 2K+ cabinet assets (drawers and doors) for training robotic manipulation policies in simulation. We sample 1K+ handles from PartNet and assemble them with procedually generated cabinet bodies.
Structure
meshdata
: mesh and urdfgraspdata/
: pre-sampled grasp poses for Franka arm with UMI grippertrainset3419.txt
: the list of 2655 objects used to train grasp handle, open, and close policies in ManipGen
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