fix: function name 'requires_agumentation' to 'requires_augmentation'

plugins/accelerated-peft/src/fms_acceleration_peft/framework_plugin_autogptq.py

@@ -241,7 +241,7 @@ def requires_custom_loading(self):
         return True
 
     @property
-    def requires_agumentation(self):
+    def requires_augmentation(self):
         return True
 
     def augmentation(

plugins/accelerated-peft/src/fms_acceleration_peft/framework_plugin_bnb.py

@@ -185,7 +185,7 @@ def requires_custom_loading(self):
         return True
 
     @property
-    def requires_agumentation(self):
+    def requires_augmentation(self):
         # will skip the augmentation if _no_peft_model == True
         return not self._no_peft_model
 

plugins/accelerated-peft/tests/test_peft_plugins.py

@@ -54,7 +54,7 @@ def test_configure_gptq_plugin():
 
         # check flags and callbacks
         assert framework.requires_custom_loading
-        assert framework.requires_agumentation
+        assert framework.requires_augmentation
         assert len(framework.get_callbacks_and_ready_for_train()) == 0
 
     # attempt to activate plugin with configuration pointing to wrong path
@@ -171,7 +171,7 @@ def test_configure_bnb_plugin():
 
         # check flags and callbacks
         assert framework.requires_custom_loading
-        assert framework.requires_agumentation
+        assert framework.requires_augmentation
         assert len(framework.get_callbacks_and_ready_for_train()) == 0
 
     # test valid combinatinos
@@ -187,7 +187,7 @@ def test_configure_bnb_plugin():
         ):
             # check flags and callbacks
             assert framework.requires_custom_loading
-            assert framework.requires_agumentation
+            assert framework.requires_augmentation
             assert len(framework.get_callbacks_and_ready_for_train()) == 0
 
     # test no_peft_model is true skips plugin.augmentation
@@ -202,7 +202,7 @@ def test_configure_bnb_plugin():
             require_packages_check=False,
         ):
             # check flags and callbacks
-            assert (not correct_value) == framework.requires_agumentation
+            assert (not correct_value) == framework.requires_augmentation
 
     # attempt to activate plugin with configuration pointing to wrong path
     # - raise with message that no plugins can be configured

plugins/attention-and-distributed-packing/src/fms_acceleration_aadp/framework_plugin_multipack.py

@@ -61,7 +61,7 @@ def __init__(
             assert self._pad_token_id is not None, "need to get pad token id"
 
     @property
-    def requires_agumentation(self):
+    def requires_augmentation(self):
         return True
 
     def augmentation(

plugins/attention-and-distributed-packing/src/fms_acceleration_aadp/framework_plugin_padding_free.py

@@ -41,7 +41,7 @@ def __init__(self, configurations: Dict[str, Dict]):
         )
 
     @property
-    def requires_agumentation(self):
+    def requires_augmentation(self):
         return True
 
     def augmentation(

plugins/framework/README.md

@@ -45,7 +45,7 @@ model, (peft_config,) = framework.augmentation(
 )
 ```
 
-We also provide `framework.requires_agumentation` to check if augumentation is required by the plugins.
+We also provide `framework.requires_augmentation` to check if augumentation is required by the plugins.
 
 Finally pass the model to train:
 

plugins/framework/src/fms_acceleration/framework.py

@@ -199,10 +199,10 @@ def augmentation(
                 x in model_archs for x in plugin.restricted_model_archs
             ):
                 raise ValueError(
-                    f"Model architectures in '{model_archs}' are supported for '{plugin_name}'."
+                    f"Model architectures in '{model_archs}' are not supported for '{plugin_name}'."
                 )
 
-            if plugin.requires_agumentation:
+            if plugin.requires_augmentation:
                 model, modifiable_args = plugin.augmentation(
                     model, train_args, modifiable_args=modifiable_args
                 )
@@ -214,8 +214,8 @@ def requires_custom_loading(self):
         return len(self.plugins_require_custom_loading) > 0
 
     @property
-    def requires_agumentation(self):
-        return any(x.requires_agumentation for _, x in self.active_plugins)
+    def requires_augmentation(self):
+        return any(x.requires_augmentation for _, x in self.active_plugins)
 
     def get_callbacks_and_ready_for_train(
         self, model: torch.nn.Module = None, accelerator: Accelerator = None

plugins/framework/src/fms_acceleration/framework_plugin.py

@@ -171,7 +171,7 @@ def requires_custom_loading(self):
         return False
 
     @property
-    def requires_agumentation(self):
+    def requires_augmentation(self):
         return False
 
     def model_loader(self, model_name: str, **kwargs):

plugins/framework/src/fms_acceleration/utils/test_utils.py

@@ -159,8 +159,8 @@ def create_plugin_cls(
     restricted_models: Set = None,
     require_pkgs: Set = None,
     requires_custom_loading: bool = False,
-    requires_agumentation: bool = False,
-    agumentation: Callable = None,
+    requires_augmentation: bool = False,
+    augmentation: Callable = None,
     model_loader: Callable = None,
 ):
     "helper function to create plugin class"
@@ -174,11 +174,11 @@ def create_plugin_cls(
         "restricted_model_archs": restricted_models,
         "require_packages": require_pkgs,
         "requires_custom_loading": requires_custom_loading,
-        "requires_agumentation": requires_agumentation,
+        "requires_augmentation": requires_augmentation,
     }
 
-    if agumentation is not None:
-        attributes["augmentation"] = agumentation
+    if augmentation is not None:
+        attributes["augmentation"] = augmentation
 
     if model_loader is not None:
         attributes["model_loader"] = model_loader

plugins/framework/tests/test_framework.py

@@ -68,7 +68,7 @@ def test_model_with_no_config_raises():
 
     # create model and (incomplete) plugin with requires_augmentation = True
     model_no_config = torch.nn.Module()  # empty model
-    incomplete_plugin = create_plugin_cls(requires_agumentation=True)
+    incomplete_plugin = create_plugin_cls(requires_augmentation=True)
 
     # register and activate 1 incomplete plugin, and:
     # 1. test correct plugin registration and activation.
@@ -104,13 +104,13 @@ def test_single_plugin():
     empty_plugin = create_plugin_cls()
     incomplete_plugin = create_plugin_cls(
         restricted_models={"CausalLM"},
-        requires_agumentation=True,
+        requires_augmentation=True,
     )
     plugin = create_plugin_cls(
         restricted_models={"CausalLM"},
-        requires_agumentation=True,
+        requires_augmentation=True,
         requires_custom_loading=True,
-        agumentation=dummy_augmentation,
+        augmentation=dummy_augmentation,
         model_loader=dummy_custom_loader,
     )
     train_args = None  # dummy for now
@@ -175,32 +175,32 @@ def test_two_plugins():
 
     model = create_noop_model_with_archs(archs=["CausalLM"])
     incomp_plugin1 = create_plugin_cls(
-        restricted_models={"CausalLM"}, requires_agumentation=True
+        restricted_models={"CausalLM"}, requires_augmentation=True
     )
-    incomp_plugin2 = create_plugin_cls(requires_agumentation=True)
+    incomp_plugin2 = create_plugin_cls(requires_augmentation=True)
     incomp_plugin3 = create_plugin_cls(
-        class_name="PluginNoop2", requires_agumentation=True
+        class_name="PluginNoop2", requires_augmentation=True
     )
     plugin1 = create_plugin_cls(
         restricted_models={"CausalLM"},
-        requires_agumentation=True,
+        requires_augmentation=True,
         requires_custom_loading=True,
-        agumentation=dummy_augmentation,
+        augmentation=dummy_augmentation,
         model_loader=dummy_custom_loader,
     )
     plugin2 = create_plugin_cls(
         class_name="PluginNoop2",
         restricted_models={"CausalLM"},
-        requires_agumentation=True,
+        requires_augmentation=True,
         requires_custom_loading=True,
-        agumentation=dummy_augmentation,
+        augmentation=dummy_augmentation,
         model_loader=dummy_custom_loader,
     )
     plugin3_no_loader = create_plugin_cls(
         class_name="PluginNoop2",
         restricted_models={"CausalLM"},
-        requires_agumentation=True,
-        agumentation=dummy_augmentation,
+        requires_augmentation=True,
+        augmentation=dummy_augmentation,
     )
     train_args = None  # dummy for now
 
@@ -299,8 +299,8 @@ def _hook(
     for class_name in ["PluginDEF", "PluginABC"]:
         plugin = create_plugin_cls(
             class_name=class_name,
-            requires_agumentation=True,
-            agumentation=hook_builder(act_order=plugin_activation_order),
+            requires_augmentation=True,
+            augmentation=hook_builder(act_order=plugin_activation_order),
         )
         plugins_to_be_installed.append((class_name, plugin))
 
@@ -319,8 +319,8 @@ def test_plugin_registration_combination_logic():
 
     plugin = create_plugin_cls(
         restricted_models={"CausalLM"},
-        requires_agumentation=True,
-        agumentation=dummy_augmentation,
+        requires_augmentation=True,
+        augmentation=dummy_augmentation,
     )
 
     configuration_contents = {"existing1": {"key1": 1}, "existing2": {"key1": 1}}

plugins/fused-ops-and-kernels/src/fms_acceleration_foak/framework_plugin_fast_kernels.py

@@ -128,7 +128,7 @@ def __init__(self, configurations: Dict[str, Dict]):
         )
 
     @property
-    def requires_agumentation(self):
+    def requires_augmentation(self):
         return True
 
     def augmentation(

plugins/fused-ops-and-kernels/tests/test_foak_plugins.py

@@ -47,7 +47,7 @@ def test_configure_gptq_foak_plugin():
 
         # check flags and callbacks
         assert framework.requires_custom_loading is False
-        assert framework.requires_agumentation
+        assert framework.requires_augmentation
         assert len(framework.get_callbacks_and_ready_for_train()) == 0
 
     # attempt to activate plugin with configuration pointing to wrong path