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Currently, predictors and preprocessors manually call into dataset.dataset_format() to determine what batch format to use that results in zero copy, and thus allowing preprocessors/predictors to delegate to format-specific optimized implementations of their transformation functions
However, this triggers execution of the dataset. Instead, we should introduce a "zero-copy" batch format in datasets that can pick the best batch format during runtime.
This will also allow us to deprecate dataset_format.
The text was updated successfully, but these errors were encountered:
amogkam
changed the title
[P1] Add a new "zero_copy" batch format that allows preprocessors/predictors to delegate to format-specific optimized implementations of their transformation functions
Add a new "zero_copy" batch format that allows preprocessors/predictors to delegate to format-specific optimized implementations of their transformation functions
Feb 17, 2023
amogkam
changed the title
Add a new "zero_copy" batch format that allows preprocessors/predictors to delegate to format-specific optimized implementations of their transformation functions
Add a new "zero_copy" batch format
Feb 17, 2023
Currently, predictors and preprocessors manually call into
dataset.dataset_format()
to determine what batch format to use that results in zero copy, and thus allowing preprocessors/predictors to delegate to format-specific optimized implementations of their transformation functionsHowever, this triggers execution of the dataset. Instead, we should introduce a "zero-copy" batch format in datasets that can pick the best batch format during runtime.
This will also allow us to deprecate
dataset_format
.The text was updated successfully, but these errors were encountered: