Accera v1.2 Reference

accera.Array.slice(sliced_dims, sliced_offsets)

Creates a sliced view of reduced rank from an array. The view is created from elements at specified offsets of the sliced dimensions of the original array.

Arguments

argument	description	type/default
sliced_dims	The dimension indices of the original array to slice on.	Tuple[int]
sliced_offsets	The offsets of the corresponding dliced dimensions.	Tuple[Scalar]

Examples

Clear a slice of size 5 from an array of size 5x5 at dimension 0 with offset 2:

import numpy as np
import accera as acc

N = 5
slice_dim = 0
slice_offset = 2

matrix = np.random.rand(N, N)
Arr = Array(role=Role.INPUT, data=matrix)

# Zero out a slice of size [5] such that the resulting array looks like this:
# xxxxx
# xxxxx
# 00000
# xxxxx
# xxxxx

nest = Nest(shape=(N,))
i, = nest.get_indices()

@nest.iteration_logic
def _():
    SliceArr = Arr.slice([slice_dim], [slice_offset])
    SliceArr[i] = 0.0

schedule = nest.create_schedule()

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Last update: 2023-04-17