assert_dim_in_range: Assert that a Dimension Exists

In mlr3torch: Deep Learning with 'mlr3'

Assert that a Dimension Exists

Description

Rejects a dim parameter that does not address a dimension of shape. Resolve negative indices with resolve_dim() first and pass both, so that the error message can report the value the user actually specified.

Usage

assert_dim_in_range(dim, true_dim, shape, id)

Arguments

dim	(integer(1)) The dimension as the user specified it: it may count back from the last dimension. Only used for the error message.
true_dim	(integer(1)) The same dimension resolved to a positive index, see resolve_dim().
shape	(integer()) The shape that true_dim addresses.
id	(character(1)) The id of the PipeOp, which the error message names.

Value

The resolved dimension, invisibly.

See Also

Other Shape Assertions: assert_known_dims(), assert_ndim(), assert_not_batch_dim(), assert_positive_extent(), assert_same_batch_size(), assert_same_ndim(), assert_shape(), assert_shapes()

Examples

shape = c(NA, 3, 8, 8)
assert_dim_in_range(-1L, resolve_dim(-1L, shape), shape, id = "nn_squeeze")
try(assert_dim_in_range(-5L, resolve_dim(-5L, shape), shape, id = "nn_squeeze"))

mlr3torch documentation built on Oct. 30, 2026, 5:10 p.m.