Search for both basic and bottleneck blocks (to fix "no known network structure detected" warning with ResNet-50 and other similar models)

README.md

@@ -48,7 +48,7 @@ See the [Annealing](http://dev.fast.ai/callback.schedule#Annealing) section of f
 `ManifoldMixup` tries to establish a sensible list of modules on which to apply mixup:
 - it uses a user provided `module_list` if possible
 - otherwise it uses only the modules wrapped with `ManifoldMixupModule`
-- if none are found, it defaults to modules with `Block` in their name (targetting mostly resblocks)
+- if none are found, it defaults to modules with `Block` or `Bottleneck` in their name (targetting mostly resblocks)
 - finaly, if needed, it defaults to all modules that are not included in the `non_mixable_module_types` list
 
 The `non_mixable_module_types` list contains mostly recurrent layers but you can add elements to it in order to define module classes that should not be used for mixup (*do not hesitate to create an issue or start a PR to add common modules to the default list*).

manifold_mixup.py

@@ -39,8 +39,9 @@ def _is_mixable(m):
     return not any(isinstance(m, non_mixable_class) for non_mixable_class in non_mixable_module_types)
 
 def _is_block_module(m):
-    "Checks wether a module is a Block (typically a kind of resBlock)"
-    return "block" in str(type(m)).lower()
+    "Checks whether a module is a Block or Bottleneck (typically a kind of resBlock)"
+    m = str(type(m)).lower()
+    return "block" in m or "bottleneck" in m
 
 def _get_mixup_module_list(model):
     "returns all the modules that can be used for mixup"