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Aim to facilitate batch size selection for stochastic gradient method when fitting very large dataset. Especially useful as a lower bound when estimating the GPU resources necessary by model fitting.
This method will be part of Basis, and can use the num_output_features parameter to estimate the size of the output array that the basis generates, given the number of samples in a batch and, optionally, the dtype of the array.
The text was updated successfully, but these errors were encountered:
Aim to facilitate batch size selection for stochastic gradient method when fitting very large dataset. Especially useful as a lower bound when estimating the GPU resources necessary by model fitting.
This method will be part of Basis, and can use the num_output_features parameter to estimate the size of the output array that the basis generates, given the number of samples in a batch and, optionally, the dtype of the array.
The text was updated successfully, but these errors were encountered: