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Error code: DatasetGenerationError Exception: ArrowNotImplementedError Message: Unsupported cast from double to halffloat using function cast_half_float Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1766, in _prepare_split_single writer.write(example, key) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 500, in write self.write_examples_on_file() File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 458, in write_examples_on_file self.write_batch(batch_examples=batch_examples) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 568, in write_batch arrays.append(pa.array(typed_sequence)) File "pyarrow/array.pxi", line 247, in pyarrow.lib.array File "pyarrow/array.pxi", line 112, in pyarrow.lib._handle_arrow_array_protocol File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 208, in __arrow_array__ out = cast_array_to_feature( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper return func(array, *args, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2075, in cast_array_to_feature casted_array_values = _c(array.values, feature.feature) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper return func(array, *args, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2075, in cast_array_to_feature casted_array_values = _c(array.values, feature.feature) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper return func(array, *args, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2075, in cast_array_to_feature casted_array_values = _c(array.values, feature.feature) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper return func(array, *args, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2116, in cast_array_to_feature return array_cast( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper return func(array, *args, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1963, in array_cast return array.cast(pa_type) File "pyarrow/array.pxi", line 996, in pyarrow.lib.Array.cast File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/compute.py", line 404, in cast return call_function("cast", [arr], options, memory_pool) File "pyarrow/_compute.pyx", line 590, in pyarrow._compute.call_function File "pyarrow/_compute.pyx", line 385, in pyarrow._compute.Function.call File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowNotImplementedError: Unsupported cast from double to halffloat using function cast_half_float During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1775, in _prepare_split_single num_examples, num_bytes = writer.finalize() File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 599, in finalize self.write_examples_on_file() File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 458, in write_examples_on_file self.write_batch(batch_examples=batch_examples) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 568, in write_batch arrays.append(pa.array(typed_sequence)) File "pyarrow/array.pxi", line 247, in pyarrow.lib.array File "pyarrow/array.pxi", line 112, in pyarrow.lib._handle_arrow_array_protocol File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 208, in __arrow_array__ out = cast_array_to_feature( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper return func(array, *args, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2075, in cast_array_to_feature casted_array_values = _c(array.values, feature.feature) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper return func(array, *args, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2075, in cast_array_to_feature casted_array_values = _c(array.values, feature.feature) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper return func(array, *args, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2075, in cast_array_to_feature casted_array_values = _c(array.values, feature.feature) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper return func(array, *args, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2116, in cast_array_to_feature return array_cast( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper return func(array, *args, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1963, in array_cast return array.cast(pa_type) File "pyarrow/array.pxi", line 996, in pyarrow.lib.Array.cast File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/compute.py", line 404, in cast return call_function("cast", [arr], options, memory_pool) File "pyarrow/_compute.pyx", line 590, in pyarrow._compute.call_function File "pyarrow/_compute.pyx", line 385, in pyarrow._compute.Function.call File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowNotImplementedError: Unsupported cast from double to halffloat using function cast_half_float 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 1524, 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 1099, in stream_convert_to_parquet builder._prepare_split( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1627, 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 1784, 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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__key__
string | __url__
string | cls.txt
string | img.png
image | latent.pth
sequence |
---|---|---|---|---|
0 | hf://datasets/Birchlabs/sdxl-latents-artbench@53461857cdf2ba7ccf8033a6ba6cdb7285d8e0cd/train/00000.tar | 0 | [
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|
4 | "hf://datasets/Birchlabs/sdxl-latents-artbench@53461857cdf2ba7ccf8033a6ba6cdb7285d8e0cd/train/00000.(...TRUNCATED) | 0 | [[[-2.13671875,-3.84765625,-7.16015625,-5.1484375,-6.203125,-2.796875,-5.9453125,-6.39453125,-4.8593(...TRUNCATED) |
|
5 | "hf://datasets/Birchlabs/sdxl-latents-artbench@53461857cdf2ba7ccf8033a6ba6cdb7285d8e0cd/train/00000.(...TRUNCATED) | 0 | [[[-7.140625,-7.30859375,-8.4609375,-8.46875,-5.5078125,-5.66796875,-9.2265625,-4.8828125,-5.6328125(...TRUNCATED) |
|
6 | "hf://datasets/Birchlabs/sdxl-latents-artbench@53461857cdf2ba7ccf8033a6ba6cdb7285d8e0cd/train/00000.(...TRUNCATED) | 0 | [[[12.140625,11.046875,10.1171875,10.109375,10.578125,14.9375,13.8046875,16.09375,12.0,12.578125,11.(...TRUNCATED) |
|
7 | "hf://datasets/Birchlabs/sdxl-latents-artbench@53461857cdf2ba7ccf8033a6ba6cdb7285d8e0cd/train/00000.(...TRUNCATED) | 0 | [[[1.90625,6.171875,4.609375,0.48779296875,11.03125,5.62890625,7.7421875,6.87109375,4.62109375,6.738(...TRUNCATED) |
|
8 | "hf://datasets/Birchlabs/sdxl-latents-artbench@53461857cdf2ba7ccf8033a6ba6cdb7285d8e0cd/train/00000.(...TRUNCATED) | 0 | [[[7.37109375,3.693359375,7.33203125,0.3134765625,8.5859375,3.923828125,12.3515625,7.44921875,6.1484(...TRUNCATED) |
|
9 | "hf://datasets/Birchlabs/sdxl-latents-artbench@53461857cdf2ba7ccf8033a6ba6cdb7285d8e0cd/train/00000.(...TRUNCATED) | 0 | [[[4.85546875,2.720703125,2.869140625,7.203125,7.03125,5.49609375,7.0390625,6.8125,3.69921875,6.8398(...TRUNCATED) |
https://github.com/liaopeiyuan/artbench samples encoded to float16 SDXL latents via Ollin VAE.
Dataset created using this script.
Didn't bother saving mean & logvar, because variance is low enough it's not worth the doubling of filesize to retain.
Sampled from diagonal gaussian distribution, saved the resulting latents.
Also kept the original image.
Schema/usage:
from typing import TypedDict, Iterator
from webdataset import WebDataset
Sample = TypedDict('Sample', {
'__key__': str,
'__url__': str,
'cls.txt': bytes, # UTF-8 encoded class id from 0 to 9 inclusive
'img.png': bytes, # PIL image, serialized. 256*256px
'latent.pth': bytes, # FloatTensor, serialized. 32*32 latents
})
it: Iterator[Sample] = WebDataset('train/{00000..00004}.tar')
for sample in it:
pass
The data sources of ArtBench-10 is released under a Fair Use license, as requested by WikiArt, Ukiyo-e.org database and The Surrealism Website.
For more information, see https://www.wikiart.org/en/terms-of-use, https://ukiyo-e.org/about and https://surrealism.website/
train: 50000 samples
test: 10000 samples
# test/avg/val.pt (mean):
[-0.11362826824188232, -0.7059057950973511, 0.4819808006286621, 2.2327630519866943]
# test/avg/sq.pt:
[52.59075927734375, 30.115631103515625, 44.977020263671875, 30.228885650634766]
# std
# (sq - val**2)**.5
[7.251058578491211, 5.442180633544922, 6.689148902893066, 5.024306297302246]
# 1/std
[0.1379109025001526, 0.18374986946582794, 0.14949584007263184, 0.19903245568275452]
# train/avg/val.pt (mean):
[-0.1536690890789032, -0.7142514586448669, 0.4706766605377197, 2.24863600730896]
# train/avg/sq.pt:
[51.99677276611328, 30.184646606445312, 44.909732818603516, 30.234216690063477]
# std
# (sq - val**2)**.5
[7.2092413902282715, 5.447429656982422, 6.68492317199707, 5.017753601074219]
# 1/std
[0.1387108564376831, 0.18357281386852264, 0.14959034323692322, 0.1992923617362976]
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