Replace deprecated hub utils in `train_unconditional_ort` (#1504)

* Replace deprecated hub utils in `train_unconditional_ort`

* typo

examples/unconditional_image_generation/train_unconditional_ort.py

 import argparse
 import math
 import os
+from pathlib import Path
+from typing import Optional
 
 import torch
 import torch.nn.functional as F
@@ -9,9 +11,9 @@ from accelerate import Accelerator
 from accelerate.logging import get_logger
 from datasets import load_dataset
 from diffusers import DDPMPipeline, DDPMScheduler, UNet2DModel
-from diffusers.hub_utils import init_git_repo, push_to_hub
 from diffusers.optimization import get_scheduler
 from diffusers.training_utils import EMAModel
+from huggingface_hub import HfFolder, Repository, whoami
 from onnxruntime.training.ortmodule import ORTModule
 from torchvision.transforms import (
     CenterCrop,
@@ -28,6 +30,16 @@ from tqdm.auto import tqdm
 logger = get_logger(__name__)
 
 
+def get_full_repo_name(model_id: str, organization: Optional[str] = None, token: Optional[str] = None):
+    if token is None:
+        token = HfFolder.get_token()
+    if organization is None:
+        username = whoami(token)["name"]
+        return f"{username}/{model_id}"
+    else:
+        return f"{organization}/{model_id}"
+
+
 def main(args):
     logging_dir = os.path.join(args.output_dir, args.logging_dir)
     accelerator = Accelerator(
@@ -113,8 +125,22 @@ def main(args):
 
     ema_model = EMAModel(model, inv_gamma=args.ema_inv_gamma, power=args.ema_power, max_value=args.ema_max_decay)
 
+    # Handle the repository creation
+    if accelerator.is_main_process:
         if args.push_to_hub:
-        repo = init_git_repo(args, at_init=True)
+            if args.hub_model_id is None:
+                repo_name = get_full_repo_name(Path(args.output_dir).name, token=args.hub_token)
+            else:
+                repo_name = args.hub_model_id
+            repo = Repository(args.output_dir, clone_from=repo_name)
+
+            with open(os.path.join(args.output_dir, ".gitignore"), "w+") as gitignore:
+                if "step_*" not in gitignore:
+                    gitignore.write("step_*\n")
+                if "epoch_*" not in gitignore:
+                    gitignore.write("epoch_*\n")
+        elif args.output_dir is not None:
+            os.makedirs(args.output_dir, exist_ok=True)
 
     if accelerator.is_main_process:
         run = os.path.split(__file__)[-1].split(".")[0]
@@ -186,10 +212,9 @@ def main(args):
 
             if epoch % args.save_model_epochs == 0 or epoch == args.num_epochs - 1:
                 # save the model
-                if args.push_to_hub:
-                    push_to_hub(args, pipeline, repo, commit_message=f"Epoch {epoch}", blocking=False)
-                else:
                 pipeline.save_pretrained(args.output_dir)
+                if args.push_to_hub:
+                    repo.push_to_hub(commit_message=f"Epoch {epoch}", blocking=False)
         accelerator.wait_for_everyone()
 
     accelerator.end_training()