Apply isort and black reformatting

Signed-off-by: akoumpa <[email protected]>

nemo/collections/llm/gpt/model/auto_model.py

@@ -12,24 +12,24 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from pathlib import Path
 from typing import Callable, Optional
 
 from torch import nn
-from nemo.lightning.pytorch.optim import OptimizerModule
-from pathlib import Path
 
+from nemo.collections.llm.gpt.model.baichuan import Baichuan2Model
 from nemo.collections.llm.gpt.model.base import GPTModel
 from nemo.collections.llm.gpt.model.chatglm import ChatGLMModel
-from nemo.collections.llm.gpt.model.phi3mini import Phi3Model
-from nemo.collections.llm.gpt.model.mixtral import MixtralModel
-from nemo.collections.llm.gpt.model.mistral import MistralModel
 from nemo.collections.llm.gpt.model.gemma import GemmaModel
 from nemo.collections.llm.gpt.model.gemma2 import Gemma2Model
 from nemo.collections.llm.gpt.model.llama import LlamaModel
-from nemo.collections.llm.gpt.model.baichuan import Baichuan2Model
+from nemo.collections.llm.gpt.model.mistral import MistralModel
+from nemo.collections.llm.gpt.model.mixtral import MixtralModel
+from nemo.collections.llm.gpt.model.phi3mini import Phi3Model
 from nemo.collections.llm.gpt.model.qwen2 import Qwen2Model
 from nemo.collections.llm.gpt.model.starcoder import StarcoderModel
 from nemo.collections.llm.gpt.model.starcoder2 import Starcoder2Model
+from nemo.lightning.pytorch.optim import OptimizerModule
 
 HF_TO_MCORE_REGISTRY = {
     'ChatGLMForCausalLM': ChatGLMModel,
@@ -67,6 +67,7 @@ def __init__(
 
         # Get model class from registry
         from transformers import AutoConfig
+
         architectures = AutoConfig.from_pretrained(model_name_or_path, trust_remote_code=True).architectures
         assert isinstance(architectures, list), "Expected architectures to be a list"
         assert len(architectures) == 1, "Expected architectures to contain one item"
@@ -84,13 +85,12 @@ def __init__(
         config = model_cls.importer(import_path).config
 
         # Init class
-        super().__init__(
-            config, optim=optim, tokenizer=tokenizer, model_transform=model_transform
-        )
+        super().__init__(config, optim=optim, tokenizer=tokenizer, model_transform=model_transform)
 
         # Change self's class to model_cls
         self.__class__ = model_cls
 
+
 __all__ = [
     "AutoModel",
 ]