Fix (graph/quant): Bugfix in blacklist matching in find_module

src/brevitas/graph/quantize_impl.py

@@ -516,7 +516,7 @@ def find_module(
     else:
         for name, module in model.named_children():
             full_name = prefix + '.' + name if prefix != '' else name
-            if name_blacklist is not None and name in name_blacklist:
+            if name_blacklist is not None and full_name in name_blacklist:
                 continue
             find_module(module, layer_map, module_to_replace, name_blacklist, full_name)
 

tests/brevitas/graph/test_quantize.py

@@ -0,0 +1,39 @@
+import pytest_cases
+import torch.nn as nn
+
+from brevitas.graph.quantize import layerwise_quantize
+
+
+@pytest_cases.parametrize(
+    'kwargs',
+    [
+        {
+            'model': nn.Sequential(nn.Linear(2, 3)),
+            'name_blacklist': [],
+            'key': '0',
+            'expected': "<class 'brevitas.nn.quant_linear.QuantLinear'>"},
+        {
+            'model': nn.Sequential(nn.Linear(2, 3)),
+            'name_blacklist': ['0'],
+            'key': '0',
+            'expected': "<class 'torch.nn.modules.linear.Linear'>"},
+        {
+            'model': nn.Sequential(nn.Sequential(nn.Linear(2, 3))),
+            'name_blacklist': ['0.0'],
+            'key': '0.0',
+            'expected': "<class 'torch.nn.modules.linear.Linear'>"},])
+def test_layerwise_quantize_blacklist(kwargs):
+    key = kwargs['key']
+    exp = kwargs['expected']
+    del kwargs['key']
+    del kwargs['expected']
+    qmodel = layerwise_quantize(**kwargs)
+    checked = False
+    found_names = []
+    for n, m in qmodel.named_modules():
+        found_names.append(n)
+        if n == key:
+            mt = str(type(m))
+            assert mt == exp, f"Expect module {n} to be type: {exp}, found type {mt}"
+            checked = True
+    assert checked, f"Layer named {key} not found. Layer names are: {found_names}"