Advanced(Inc)Subtensor text representation

Description

After #1756 Advanced and IncSubtensor take idx_list (just like Subtensor did). It would be nice to use the same string representation we used for Subtensor to make dprint more readable.

import pytensor.tensor as pt

x = pt.zeros((2, 3, 4, 5))

basic_sub = x[0, :, :1, 1]
basic_sub.dprint()
# Subtensor{i, :, :stop, j} [id A]
#  ├─ Alloc [id B]
#  │  ├─ 0.0 [id C]
#  │  ├─ 2 [id D]
#  │  ├─ 3 [id E]
#  │  ├─ 4 [id F]
#  │  └─ 5 [id G]
#  ├─ 0 [id H]
#  ├─ 1 [id I]
#  └─ 1 [id J]

adv_sub = x[[0], :, :1, 1]
adv_sub.dprint()
# AdvancedSubtensor{idx_list=(0, slice(None, None, None), slice(None, 1, None), 2)} [id A]
#  ├─ Alloc [id B]
#  │  ├─ 0.0 [id C]
#  │  ├─ 2 [id D]
#  │  ├─ 3 [id E]
#  │  ├─ 4 [id F]
#  │  └─ 5 [id G]
#  ├─ [0] [id H]
#  ├─ TensorFromScalar [id I]
#  │  └─ 1 [id J]
#  └─ TensorFromScalar [id K]
#     └─ 1 [id L]

(We should also check what's going on with those TensorFromScalar in AdvancedSubtensor...)

Start with the Subtensor, AdvancedSubtensor, and IncSubtensor entry points and compare their current string representations with the dprint examples in the issue. Check the AdvancedSubtensor TensorFromScalar output as noted; done means Advanced and IncSubtensor use the readable idx_list-style representation and the related output is understood.