heat.memory

This module changes the internal memory of an array.

Module Contents

copy(x: heat.core.dndarray.DNDarray) → heat.core.dndarray.DNDarray

Return a deep copy of the given object.

Parameters:

x (DNDarray) – Input array to be copied.

Examples

>>> a = ht.array([1,2,3])
>>> b = ht.copy(a)
>>> b
DNDarray([1, 2, 3], dtype=ht.int64, device=cpu:0, split=None)
>>> a[0] = 4
>>> a
DNDarray([4, 2, 3], dtype=ht.int64, device=cpu:0, split=None)
>>> b
DNDarray([1, 2, 3], dtype=ht.int64, device=cpu:0, split=None)

sanitize_memory_layout(x: torch.Tensor, order: str = 'C') → torch.Tensor

Return the given object with memory layout as defined below. The default memory distribution is assumed.

Parameters:

• x (torch.Tensor) – Input data

• order (str, optional.) – Default is 'C' as in C-like (row-major) memory layout. The array is stored first dimension first (rows first if ndim=2). Alternative is 'F', as in Fortran-like (column-major) memory layout. The array is stored last dimension first (columns first if ndim=2).