setted hf token

api/model/environment.yml

@@ -22,6 +22,7 @@ dependencies:
   - wheel=0.38.4=py39h06a4308_0
   - xz=5.4.2=h5eee18b_0
   - zlib=1.2.13=h5eee18b_0
+  - huggingface_hub
   - pip:
       - accelerate==0.15.0
       - certifi==2023.7.22

api/model/src/eval.py

@@ -1,6 +1,5 @@
 import os
 import io
-import subprocess
 
 #  external libraries
 import torch
@@ -22,6 +21,7 @@ from model.src.utils.arg_parser import eval_parse_args
 from model.src.utils.image_from_pipe import generate_images_from_mgd_pipe
 from model.src.utils.set_seeds import set_seed
 from PIL import Image
+from huggingface_hub import HfApi, HfFolder
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
 check_min_version("0.10.0.dev0")
@@ -30,10 +30,12 @@ logger = get_logger(__name__, log_level="INFO")
 os.environ["TOKENIZERS_PARALLELISM"] = "true"
 os.environ["WANDB_START_METHOD"] = "thread"
 
+hf_token = os.getenv("HF_TOKEN")
+api = HfApi()
+api.set_access_token(hf_token)
+HfFolder.save_token(hf_token)
 
 def main(json_from_req: dict) -> None:
-    hf_token = os.getenv("HF_TOKEN")
-    subprocess.run(['huggingface-cli', 'login'], input=f'{hf_token}\n'.encode('utf-8'))
     args = eval_parse_args()
     accelerator = Accelerator(
         mixed_precision=args.mixed_precision,
@@ -45,14 +47,7 @@ def main(json_from_req: dict) -> None:
         set_seed(args.seed)
 
     # Load scheduler, tokenizer and models.
-    #val_scheduler = DDIMScheduler.from_pretrained(args.pretrained_model_name_or_path, subfolder="scheduler", use_auth_token=True)
-    #hf_token = os.getenv("HF_TOKEN")
-    print(hf_token)
-    val_scheduler = DDIMScheduler.from_pretrained(
-        "benjamin-paine/stable-diffusion-v1-5-inpainting",
-        subfolder="scheduler",
-        use_auth_token=True
-    )
+    val_scheduler = DDIMScheduler.from_pretrained(args.pretrained_model_name_or_path, subfolder="scheduler")
     val_scheduler.set_timesteps(50, device=device)
 
     tokenizer = CLIPTokenizer.from_pretrained(