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The dataset generation failed
Error code: DatasetGenerationError Exception: TypeError Message: Couldn't cast array of type struct<0: list<item: int64>, 1: list<item: int64>, 2: list<item: int64>, 3: list<item: int64>, 4: list<item: int64>, 5: list<item: int64>, 6: list<item: int64>, 7: list<item: int64>, 8: list<item: int64>, 9: list<item: int64>, 10: list<item: int64>, 11: list<item: int64>, 12: list<item: int64>, 13: list<item: int64>, 14: list<item: int64>, 15: list<item: int64>, 16: list<item: int64>, 17: list<item: int64>> to {'0': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '1': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '2': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '3': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '4': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '5': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '6': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '7': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '8': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '9': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '10': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '11': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '12': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '13': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '14': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '15': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '16': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '17': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '18': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None)} Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single writer.write_table(table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table pa_table = table_cast(pa_table, self._schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast return cast_table_to_schema(table, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in cast_table_to_schema arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()] File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in <listcomp> arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()] File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1802, in wrapper return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks]) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1802, in <listcomp> return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks]) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2122, in cast_array_to_feature raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}") TypeError: Couldn't cast array of type struct<0: list<item: int64>, 1: list<item: int64>, 2: list<item: int64>, 3: list<item: int64>, 4: list<item: int64>, 5: list<item: int64>, 6: list<item: int64>, 7: list<item: int64>, 8: list<item: int64>, 9: list<item: int64>, 10: list<item: int64>, 11: list<item: int64>, 12: list<item: int64>, 13: list<item: int64>, 14: list<item: int64>, 15: list<item: int64>, 16: list<item: int64>, 17: list<item: int64>> to {'0': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '1': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '2': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '3': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '4': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '5': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '6': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '7': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '8': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '9': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '10': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '11': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '12': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '13': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '14': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '15': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '16': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '17': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), '18': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None)} 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 1391, in compute_config_parquet_and_info_response parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet( File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 990, in stream_convert_to_parquet builder._prepare_split( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1884, in _prepare_split for job_id, done, content in self._prepare_split_single( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2040, in _prepare_split_single raise DatasetGenerationError("An error occurred while generating the dataset") from e datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset
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version
string | tiling_tool_version
string | nb_tiles
int64 | total_number_of_tiles
int64 | sampling_mode
dict | matter_detector
dict | features_extractor
string | level
int64 | tile_size
int64 | absolute_tile_size
int64 | slide_size
sequence | tile_mpp
float64 | level_dimensions
dict | level_mpp_mapping
dict | environment
dict | slide_hash
string |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
3.0.0 | 11.6.0 | 5,561 | 5,561 | {
"mode": "random",
"seed": 0
} | {
"name": "BUNet",
"dilatation": 1,
"threshold": 0.5
} | iBOTViTGiant | 16 | 224 | 896 | [
135168,
105472
] | 0.9108 | {
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"5": [
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],
"6": [
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],
"7": [
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],
"8": [
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],
"9": [
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],
"10": [
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],
"11": [
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],
"12": [
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],
"13": [
4224,
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],
"14": [
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],
"15": [
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],
"16": [
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],
"17": [
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],
"18": [
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]
} | {
"0": 59690.1888,
"1": 29845.0944,
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"13": 7.2864,
"14": 3.6432,
"15": 1.8216,
"16": 0.9108,
"17": 0.4554,
"18": 0.2277
} | {
"python_version": "3.9.19 | packaged by conda-forge | (main, Mar 20 2024, 12:50:21) \n[GCC 12.3.0]",
"pixman_version": "0.38.4",
"openslide_version": "3.4.1",
"classic_algos_version": "1.19.0",
"torch_version": "2.0.1+cu117",
"openslide_python_version": "1.3.1",
"platform": "Linux-5.4.0-152-generic-x86_64-with-glibc2.31"
} | 97816938bcfac54f2f32ac2ae42d225201760d70ac45654a33a386fc4b071d72 |
3.0.0 | 11.6.0 | 7,981 | 7,981 | {
"mode": "random",
"seed": 0
} | {
"name": "BUNet",
"dilatation": 1,
"threshold": 0.5
} | iBOTViTGiant | 15 | 224 | 896 | [
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} | {
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} | {
"python_version": "3.9.19 | packaged by conda-forge | (main, Mar 20 2024, 12:50:21) \n[GCC 12.3.0]",
"pixman_version": "0.38.4",
"openslide_version": "3.4.1",
"classic_algos_version": "1.19.0",
"torch_version": "2.0.1+cu117",
"openslide_python_version": "1.3.1",
"platform": "Linux-5.4.0-152-generic-x86_64-with-glibc2.31"
} | f0a26aa8b96a21f3c66ccfb163bb40f630ac1591aca693f0b5bbb5ca5195938c |
3.0.0 | 11.6.0 | 8,005 | 8,005 | {
"mode": "random",
"seed": 0
} | {
"name": "BUNet",
"dilatation": 1,
"threshold": 0.5
} | iBOTViTGiant | 15 | 224 | 896 | [
110592,
104448
] | 0.9108 | {
"0": [
1,
1
],
"1": [
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],
"2": [
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],
"3": [
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],
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} | {
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} | {
"python_version": "3.9.19 | packaged by conda-forge | (main, Mar 20 2024, 12:50:21) \n[GCC 12.3.0]",
"pixman_version": "0.38.4",
"openslide_version": "3.4.1",
"classic_algos_version": "1.19.0",
"torch_version": "2.0.1+cu117",
"openslide_python_version": "1.3.1",
"platform": "Linux-5.4.0-152-generic-x86_64-with-glibc2.31"
} | bc9c4b913a7a338793b785bf073fdd81ed042aa71067a5bea60496dc0e870fdd |
3.0.0 | 11.6.0 | 4,125 | 4,125 | {
"mode": "random",
"seed": 0
} | {
"name": "BUNet",
"dilatation": 1,
"threshold": 0.5
} | iBOTViTGiant | 15 | 224 | 896 | [
110592,
77312
] | 0.9108 | {
"0": [
1,
1
],
"1": [
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],
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],
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],
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],
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]
} | {
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} | {
"python_version": "3.9.19 | packaged by conda-forge | (main, Mar 20 2024, 12:50:21) \n[GCC 12.3.0]",
"pixman_version": "0.38.4",
"openslide_version": "3.4.1",
"classic_algos_version": "1.19.0",
"torch_version": "2.0.1+cu117",
"openslide_python_version": "1.3.1",
"platform": "Linux-5.4.0-152-generic-x86_64-with-glibc2.31"
} | 636ae4618bac90b25576e75f82fdc0eea978683f4dbbbd9d23ebfb3fbfb0467e |
3.0.0 | 11.6.0 | 9,497 | 9,497 | {
"mode": "random",
"seed": 0
} | {
"name": "BUNet",
"dilatation": 1,
"threshold": 0.5
} | iBOTViTGiant | 15 | 224 | 896 | [
122880,
103168
] | 0.9108 | {
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],
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],
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],
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],
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],
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],
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]
} | {
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} | {
"python_version": "3.9.19 | packaged by conda-forge | (main, Mar 20 2024, 12:50:21) \n[GCC 12.3.0]",
"pixman_version": "0.38.4",
"openslide_version": "3.4.1",
"classic_algos_version": "1.19.0",
"torch_version": "2.0.1+cu117",
"openslide_python_version": "1.3.1",
"platform": "Linux-5.4.0-152-generic-x86_64-with-glibc2.31"
} | b42d17bb0c4373235e8d460918c667abc872a925786de1f5a613987e8c30a535 |
3.0.0 | 11.6.0 | 11,335 | 11,335 | {
"mode": "random",
"seed": 0
} | {
"name": "BUNet",
"dilatation": 1,
"threshold": 0.5
} | iBOTViTGiant | 15 | 224 | 896 | [
131072,
104192
] | 0.9108 | {
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} | {
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} | {
"python_version": "3.9.19 | packaged by conda-forge | (main, Mar 20 2024, 12:50:21) \n[GCC 12.3.0]",
"pixman_version": "0.38.4",
"openslide_version": "3.4.1",
"classic_algos_version": "1.19.0",
"torch_version": "2.0.1+cu117",
"openslide_python_version": "1.3.1",
"platform": "Linux-5.4.0-152-generic-x86_64-with-glibc2.31"
} | 1d43f33d38e28b01f8201fce812c48a882ba2a096b0a02f82d29bc215cff7d90 |
3.0.0 | 11.6.0 | 12,003 | 12,003 | {
"mode": "random",
"seed": 0
} | {
"name": "BUNet",
"dilatation": 1,
"threshold": 0.5
} | iBOTViTGiant | 15 | 224 | 896 | [
131072,
102912
] | 0.9108 | {
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],
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],
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],
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],
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],
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],
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],
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],
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],
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],
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]
} | {
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} | {
"python_version": "3.9.19 | packaged by conda-forge | (main, Mar 20 2024, 12:50:21) \n[GCC 12.3.0]",
"pixman_version": "0.38.4",
"openslide_version": "3.4.1",
"classic_algos_version": "1.19.0",
"torch_version": "2.0.1+cu117",
"openslide_python_version": "1.3.1",
"platform": "Linux-5.4.0-152-generic-x86_64-with-glibc2.31"
} | 0b6d96a17aea7df2170e706bda6b97ccedc1f8d02d2a026a4a898b09ec935942 |
3.0.0 | 11.6.0 | 9,041 | 9,041 | {
"mode": "random",
"seed": 0
} | {
"name": "BUNet",
"dilatation": 1,
"threshold": 0.5
} | iBOTViTGiant | 16 | 224 | 896 | [
135168,
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"classic_algos_version": "1.19.0",
"torch_version": "2.0.1+cu117",
"openslide_python_version": "1.3.1",
"platform": "Linux-5.4.0-152-generic-x86_64-with-glibc2.31"
} | e6d1925096fac543bc34ae684ea07e1e |
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