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Allow usage of generator-like objects instead of numpy arrays for training #7

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profjsb opened this issue Aug 2, 2019 · 2 comments
Open

Allow usage of generator-like objects instead of numpy arrays for training #7

profjsb opened this issue Aug 2, 2019 · 2 comments
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@kmzzhang
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enhancement New feature or request
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0.2

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@profjsb
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profjsb commented Aug 2, 2019

By using a single numpy array at train time, the user is currently limited to building models on dataset sizes that fit in RAM. Instead, we should allow the user to train on a generator (akin to fit_generator in keras), which can read data as needed from disk. Perhaps the user can pass a pytorch.Dataset instead of a numpy array.
@profjsb profjsb added the enhancement New feature or request label Aug 2, 2019
@profjsb profjsb added this to the 0.2 milestone Aug 2, 2019
@kmzzhang
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This is currently being developed and expected to be released soon.

@kmzzhang
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kmzzhang commented Oct 6, 2019 •
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Implemented and release as part of v.0.2.0 in DatasetSim.
For HST style dataset I will implement that when the generic HST model is made

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