fix: validator introduced in #4132

[narendasan]

Description

For cases where the index is an attribute of the graph module, t…he validator should detect this and check that attribute val rather than pass through silently

Fixes # (issue)

Type of change

Please delete options that are not relevant and/or add your own.

• Bug fix (non-breaking change which fixes an issue)

Checklist:

• My code follows the style guidelines of this project (You can use the linters)
• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas and hacks
• I have made corresponding changes to the documentation
• I have added tests to verify my fix or my feature
• New and existing unit tests pass locally with my changes
• I have added the relevant labels to my PR in so that relevant reviewers are notified

[github-actions]

There are some changes that do not conform to Python style guidelines:

--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_index_bool_split_aten.py	2026-03-18 22:27:08.373651+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_index_bool_split_aten.py	2026-03-18 22:27:26.491036+00:00
@@ -4,10 +4,11 @@
1. `index_has_bool_indices` validator correctly distinguishes bool vs int indices.
2. Integer-indexed `aten.index.Tensor` routes to the converter WITHOUT output allocator.
3. Boolean-indexed `aten.index.Tensor` routes to the converter WITH output allocator.
4. Both paths produce correct results.
"""
+
import unittest
from unittest.mock import MagicMock

import torch
import torch.nn as nn
@@ -58,13 +59,11 @@
        node = _make_index_node([None, torch.tensor([True, False])])
        self.assertTrue(index_has_bool_indices(node))

    def test_mixed_int_and_bool_returns_true(self):
        """If any index is bool, the function should return True."""
-        node = _make_index_node(
-            [torch.tensor([0, 1]), torch.tensor([True, False])]
-        )
+        node = _make_index_node([torch.tensor([0, 1]), torch.tensor([True, False])])
        self.assertTrue(index_has_bool_indices(node))

    def test_all_none_returns_false(self):
        node = _make_index_node([None, None])
        self.assertFalse(index_has_bool_indices(node))

[github-actions]

There are some changes that do not conform to Python style guidelines:

--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_index_bool_split_aten.py	2026-03-18 22:27:34.043918+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_index_bool_split_aten.py	2026-03-18 22:27:53.739982+00:00
@@ -4,10 +4,11 @@
1. `index_has_bool_indices` validator correctly distinguishes bool vs int indices.
2. Integer-indexed `aten.index.Tensor` routes to the converter WITHOUT output allocator.
3. Boolean-indexed `aten.index.Tensor` routes to the converter WITH output allocator.
4. Both paths produce correct results.
"""
+
import unittest
from unittest.mock import MagicMock

import torch
import torch.nn as nn
@@ -58,13 +59,11 @@
        node = _make_index_node([None, torch.tensor([True, False])])
        self.assertTrue(index_has_bool_indices(node))

    def test_mixed_int_and_bool_returns_true(self):
        """If any index is bool, the function should return True."""
-        node = _make_index_node(
-            [torch.tensor([0, 1]), torch.tensor([True, False])]
-        )
+        node = _make_index_node([torch.tensor([0, 1]), torch.tensor([True, False])])
        self.assertTrue(index_has_bool_indices(node))

    def test_all_none_returns_false(self):
        node = _make_index_node([None, None])
        self.assertFalse(index_has_bool_indices(node))

[github-actions]

There are some changes that do not conform to Python style guidelines:

--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_index_bool_split_aten.py	2026-03-18 22:27:52.852046+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_index_bool_split_aten.py	2026-03-18 22:28:13.341265+00:00
@@ -4,10 +4,11 @@
1. `index_has_bool_indices` validator correctly distinguishes bool vs int indices.
2. Integer-indexed `aten.index.Tensor` routes to the converter WITHOUT output allocator.
3. Boolean-indexed `aten.index.Tensor` routes to the converter WITH output allocator.
4. Both paths produce correct results.
"""
+
import unittest
from unittest.mock import MagicMock

import torch
import torch.nn as nn
@@ -58,13 +59,11 @@
        node = _make_index_node([None, torch.tensor([True, False])])
        self.assertTrue(index_has_bool_indices(node))

    def test_mixed_int_and_bool_returns_true(self):
        """If any index is bool, the function should return True."""
-        node = _make_index_node(
-            [torch.tensor([0, 1]), torch.tensor([True, False])]
-        )
+        node = _make_index_node([torch.tensor([0, 1]), torch.tensor([True, False])])
        self.assertTrue(index_has_bool_indices(node))

    def test_all_none_returns_false(self):
        node = _make_index_node([None, None])
        self.assertFalse(index_has_bool_indices(node))

old

[zewenli98]

The L0 errors seem not related to this PR. LGTM.