Generator to create n_packs
evenly spaced slices going up to n
.
If n_packs
does not divide n
, except for the first n % n_packs
slices, remaining slices may contain fewer elements.
Size of the sequence.
Number of slices to generate.
Number of samples. Pass n_samples
when the slices are to be used for sparse matrix indexing; slicing off-the-end raises an exception, while it works for NumPy arrays.
slice
representing a set of indices from 0 to n.
See also
gen_batches
Generator to create slices containing batch_size elements from 0 to n.
Examples
>>> from sklearn.utils import gen_even_slices >>> list(gen_even_slices(10, 1)) [slice(0, 10, None)] >>> list(gen_even_slices(10, 10)) [slice(0, 1, None), slice(1, 2, None), ..., slice(9, 10, None)] >>> list(gen_even_slices(10, 5)) [slice(0, 2, None), slice(2, 4, None), ..., slice(8, 10, None)] >>> list(gen_even_slices(10, 3)) [slice(0, 4, None), slice(4, 7, None), slice(7, 10, None)]
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