Rename

app_training.py

@@ -48,9 +48,9 @@ def create_training_demo(trainer: Trainer,
                                                  label='Resolution',
                                                  visible=False)
 
-                    input_token = gr.Text(label='Hugging Face Write Token',
-                                          placeholder='',
-                                          visible=False if hf_token else True)
+                    input_hf_token = gr.Text(label='Hugging Face Write Token',
+                                             placeholder='',
+                                             visible=hf_token is None)
                     with gr.Accordion('Advanced settings', open=False):
                         num_training_steps = gr.Number(
                             label='Number of Training Steps',
@@ -150,7 +150,7 @@ def create_training_demo(trainer: Trainer,
                              delete_existing_repo,
                              upload_to,
                              remove_gpu_after_training,
-                             input_token,
+                             input_hf_token,
                          ])
     return demo
 

app_upload.py

@@ -20,7 +20,7 @@ class ModelUploader(Uploader):
         upload_to: str,
         private: bool,
         delete_existing_repo: bool,
-        input_token: str | None = None,
+        input_hf_token: str | None = None,
     ) -> str:
         if not folder_path:
             raise ValueError
@@ -40,7 +40,7 @@ class ModelUploader(Uploader):
                            organization=organization,
                            private=private,
                            delete_existing_repo=delete_existing_repo,
-                           input_token=input_token)
+                           input_hf_token=input_hf_token)
 
 
 def load_local_model_list() -> dict:
@@ -70,9 +70,9 @@ def create_upload_demo(hf_token: str | None) -> gr.Blocks:
                                  choices=[_.value for _ in UploadTarget],
                                  value=UploadTarget.MODEL_LIBRARY.value)
             model_name = gr.Textbox(label='Model Name')
-            input_token = gr.Text(label='Hugging Face Write Token',
-                                  placeholder='',
-                                  visible=False if hf_token else True)
+            input_hf_token = gr.Text(label='Hugging Face Write Token',
+                                     placeholder='',
+                                     visible=False if hf_token else True)
         upload_button = gr.Button('Upload')
         gr.Markdown(f'''
             - You can upload your trained model to your personal profile (i.e. https://huggingface.co/{{your_username}}/{{model_name}}) or to the public [Tune-A-Video Library](https://huggingface.co/{MODEL_LIBRARY_ORG_NAME}) (i.e. https://huggingface.co/{MODEL_LIBRARY_ORG_NAME}/{{model_name}}).
@@ -91,7 +91,7 @@ def create_upload_demo(hf_token: str | None) -> gr.Blocks:
                                 upload_to,
                                 use_private_repo,
                                 delete_existing_repo,
-                                input_token,
+                                input_hf_token,
                             ],
                             outputs=output_message)
 

trainer.py

@@ -72,7 +72,7 @@ class Trainer:
         delete_existing_repo: bool,
         upload_to: str,
         remove_gpu_after_training: bool,
-        input_token: str,
+        input_hf_token: str,
     ) -> None:
         if not torch.cuda.is_available():
             raise gr.Error('CUDA is not available.')
@@ -98,7 +98,7 @@ class Trainer:
 
         if upload_to_hub:
             self.join_model_library_org(
-                self.hf_token if self.hf_token else input_token)
+                self.hf_token if self.hf_token else input_hf_token)
 
         config = OmegaConf.load('Tune-A-Video/configs/man-surfing.yaml')
         config.pretrained_model_path = self.download_base_model(base_model)
@@ -152,14 +152,13 @@ class Trainer:
                 upload_to=upload_to,
                 private=use_private_repo,
                 delete_existing_repo=delete_existing_repo,
-                input_token=input_token)
+                input_hf_token=input_hf_token)
             with open(self.log_file, 'a') as f:
                 f.write(upload_message)
 
         if remove_gpu_after_training:
             space_id = os.getenv('SPACE_ID')
             if space_id:
-                api = HfApi(
-                    token=self.hf_token if self.hf_token else input_token)
+                api = HfApi(token=self.hf_token or input_hf_token)
                 api.request_space_hardware(repo_id=space_id,
                                            hardware='cpu-basic')

uploader.py

@@ -14,9 +14,9 @@ class Uploader:
                repo_type: str = 'model',
                private: bool = True,
                delete_existing_repo: bool = False,
-               input_token: str | None = None) -> str:
+               input_hf_token: str | None = None) -> str:
 
-        api = HfApi(token=self.hf_token if self.hf_token else input_token)
+        api = HfApi(token=self.hf_token or input_hf_token)
 
         if not folder_path:
             raise ValueError