Advanced(Inc)Subtensor text representation

[ricardoV94]

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...)

[10ge6]

Hey! Would like to work on this. I'm new to the PyTensor codebase but have experience with Python and am looking to contribute. I'll look at the Subtensor implementation and apply the same format.

[aman-coder03]

Hi @ricardoV94 i would like to work on this. I will look at how Subtensor.__str__ formats idx_list and apply the same logic to AdvancedSubtensor and AdvancedIncSubtensor. I'll also investigate the TensorFromScalar issue mentioned at the end