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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 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.
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 | {
"0": [
1,
1
],
"1": [
2,
1
],
"2": [
3,
2
],
"3": [
5,
4
],
"4": [
9,
7
],
"5": [
17,
13
],
"6": [
33,
26
],
"7": [
66,
52
],
"8": [
132,
103
],
"9": [
264,
206
],
"10": [
528,
412
],
... | {
"0": 59690.1888,
"1": 29845.0944,
"2": 14922.5472,
"3": 7461.2736,
"4": 3730.6368,
"5": 1865.3184,
"6": 932.6592,
"7": 466.3296,
"8": 233.1648,
"9": 116.5824,
"10": 58.2912,
"11": 29.1456,
"12": 14.5728,
"13": 7.2864,
"14": 3.6432,
"15": 1.8216,
"16": 0.9108,
"17": 0.4554,
"18": ... | {
"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_... | 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 | [
118784,
93440
] | 0.9108 | {
"0": [
1,
1
],
"1": [
2,
2
],
"2": [
4,
3
],
"3": [
8,
6
],
"4": [
15,
12
],
"5": [
29,
23
],
"6": [
58,
46
],
"7": [
116,
92
],
"8": [
232,
183
],
"9": [
464,
365
],
"10": [
928,
730
],... | {
"0": 29845.0944,
"1": 14922.5472,
"2": 7461.2736,
"3": 3730.6368,
"4": 1865.3184,
"5": 932.6592,
"6": 466.3296,
"7": 233.1648,
"8": 116.5824,
"9": 58.2912,
"10": 29.1456,
"11": 14.5728,
"12": 7.2864,
"13": 3.6432,
"14": 1.8216,
"15": 0.9108,
"16": 0.4554,
"17": 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_... | 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": [
2,
2
],
"2": [
4,
4
],
"3": [
7,
7
],
"4": [
14,
13
],
"5": [
27,
26
],
"6": [
54,
51
],
"7": [
108,
102
],
"8": [
216,
204
],
"9": [
432,
408
],
"10": [
864,
816
]... | {
"0": 29845.0944,
"1": 14922.5472,
"2": 7461.2736,
"3": 3730.6368,
"4": 1865.3184,
"5": 932.6592,
"6": 466.3296,
"7": 233.1648,
"8": 116.5824,
"9": 58.2912,
"10": 29.1456,
"11": 14.5728,
"12": 7.2864,
"13": 3.6432,
"14": 1.8216,
"15": 0.9108,
"16": 0.4554,
"17": 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_... | 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": [
2,
2
],
"2": [
4,
3
],
"3": [
7,
5
],
"4": [
14,
10
],
"5": [
27,
19
],
"6": [
54,
38
],
"7": [
108,
76
],
"8": [
216,
151
],
"9": [
432,
302
],
"10": [
864,
604
],... | {
"0": 29845.0944,
"1": 14922.5472,
"2": 7461.2736,
"3": 3730.6368,
"4": 1865.3184,
"5": 932.6592,
"6": 466.3296,
"7": 233.1648,
"8": 116.5824,
"9": 58.2912,
"10": 29.1456,
"11": 14.5728,
"12": 7.2864,
"13": 3.6432,
"14": 1.8216,
"15": 0.9108,
"16": 0.4554,
"17": 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_... | 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 | {
"0": [
1,
1
],
"1": [
2,
2
],
"2": [
4,
4
],
"3": [
8,
7
],
"4": [
15,
13
],
"5": [
30,
26
],
"6": [
60,
51
],
"7": [
120,
101
],
"8": [
240,
202
],
"9": [
480,
403
],
"10": [
960,
806
]... | {
"0": 29845.0944,
"1": 14922.5472,
"2": 7461.2736,
"3": 3730.6368,
"4": 1865.3184,
"5": 932.6592,
"6": 466.3296,
"7": 233.1648,
"8": 116.5824,
"9": 58.2912,
"10": 29.1456,
"11": 14.5728,
"12": 7.2864,
"13": 3.6432,
"14": 1.8216,
"15": 0.9108,
"16": 0.4554,
"17": 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_... | 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 | {
"0": [
1,
1
],
"1": [
2,
2
],
"2": [
4,
4
],
"3": [
8,
7
],
"4": [
16,
13
],
"5": [
32,
26
],
"6": [
64,
51
],
"7": [
128,
102
],
"8": [
256,
204
],
"9": [
512,
407
],
"10": [
1024,
814
... | {
"0": 29845.0944,
"1": 14922.5472,
"2": 7461.2736,
"3": 3730.6368,
"4": 1865.3184,
"5": 932.6592,
"6": 466.3296,
"7": 233.1648,
"8": 116.5824,
"9": 58.2912,
"10": 29.1456,
"11": 14.5728,
"12": 7.2864,
"13": 3.6432,
"14": 1.8216,
"15": 0.9108,
"16": 0.4554,
"17": 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_... | 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 | {
"0": [
1,
1
],
"1": [
2,
2
],
"2": [
4,
4
],
"3": [
8,
7
],
"4": [
16,
13
],
"5": [
32,
26
],
"6": [
64,
51
],
"7": [
128,
101
],
"8": [
256,
201
],
"9": [
512,
402
],
"10": [
1024,
804
... | {
"0": 29845.0944,
"1": 14922.5472,
"2": 7461.2736,
"3": 3730.6368,
"4": 1865.3184,
"5": 932.6592,
"6": 466.3296,
"7": 233.1648,
"8": 116.5824,
"9": 58.2912,
"10": 29.1456,
"11": 14.5728,
"12": 7.2864,
"13": 3.6432,
"14": 1.8216,
"15": 0.9108,
"16": 0.4554,
"17": 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_... | 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,
108032
] | 0.9108 | {
"0": [
1,
1
],
"1": [
2,
1
],
"2": [
3,
2
],
"3": [
5,
4
],
"4": [
9,
7
],
"5": [
17,
14
],
"6": [
33,
27
],
"7": [
66,
53
],
"8": [
132,
106
],
"9": [
264,
211
],
"10": [
528,
422
],
... | {
"0": 59690.1888,
"1": 29845.0944,
"2": 14922.5472,
"3": 7461.2736,
"4": 3730.6368,
"5": 1865.3184,
"6": 932.6592,
"7": 466.3296,
"8": 233.1648,
"9": 116.5824,
"10": 58.2912,
"11": 29.1456,
"12": 14.5728,
"13": 7.2864,
"14": 3.6432,
"15": 1.8216,
"16": 0.9108,
"17": 0.4554,
"18": ... | {
"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_... | dcc04411d1fca532cd3657d28e152bfe591b4478255afcc3da572d7d128794ca |
3.0.0 | 11.6.0 | 4,344 | 4,344 | {
"mode": "random",
"seed": 0
} | {
"name": "BUNet",
"dilatation": 1,
"threshold": 0.5
} | iBOTViTGiant | 15 | 224 | 896 | [
90112,
91392
] | 0.9108 | {
"0": [
1,
1
],
"1": [
2,
2
],
"2": [
3,
3
],
"3": [
6,
6
],
"4": [
11,
12
],
"5": [
22,
23
],
"6": [
44,
45
],
"7": [
88,
90
],
"8": [
176,
179
],
"9": [
352,
357
],
"10": [
704,
714
],
... | {
"0": 29845.0944,
"1": 14922.5472,
"2": 7461.2736,
"3": 3730.6368,
"4": 1865.3184,
"5": 932.6592,
"6": 466.3296,
"7": 233.1648,
"8": 116.5824,
"9": 58.2912,
"10": 29.1456,
"11": 14.5728,
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