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A `torch.LongTensor` seems to always be created on the CPU.
The result is not great with 32 epochs, either.
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## [0.29.0](v0.28.1...v0.29.0) (2024-11-26) ### Features * remove `Image.__array__` ([#964](#964)) ([d2f59c9](d2f59c9)) * rename `count_row_if` to `count_rows_if` ([#960](#960)) ([f5d6324](f5d6324)) * rename `epoch_size` to `epoch_count` ([#962](#962)) ([fa62e9b](fa62e9b)) * rename `flip_vertically` and `flip_horizontally` methods ([#946](#946)) ([a3607d7](a3607d7)), closes [#945](#945) * rename `load_pretrained_model` to `from_pretrained_model` ([#957](#957)) ([5b32acc](5b32acc)) * rename `Row.get_value` to `Row.get_cell` ([#947](#947)) ([e77cb6c](e77cb6c)) ### Bug Fixes * avoid performance warning when accessing `column_count` ([#949](#949)) ([c24b6d5](c24b6d5)) * handle deprecations in third-party libraries ([#963](#963)) ([e10e6bb](e10e6bb)) * index tensor on cpu ([#961](#961)) ([afafd43](afafd43))
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Summary of Changes
The index tensor of an
ImageDatasetsometimes ended up on the CPU, instead of the default device, which led to runtime errors. This PR fixes this.