Upload training and testing datasets

data_registration.py

@@ -0,0 +1,33 @@
+from huggingface_hub.utils import validate_repo_id, HfHubHTTPError,RepositoryNotFoundError
+from huggingface_hub import HfApi
+from huggingface_hub import create_repo
+import os
+
+repo_id = "grkavi0912/engine1"
+repo_type = "dataset" # Corrected from "Datasets" to "dataset"
+private = False
+token = "HFTOKEN" # Placeholder, will be replaced by userdata.get() later
+#Initialize API client
+api = HfApi(token=os.getenv("HFTOKEN")) # Corrected missing parenthesis and used os.getenv as in original notebook
+
+#step 1:check if the space exists
+try:
+    api.repo_info(repo_id=repo_id,repo_type=repo_type)
+    print(f"Repo {repo_id} already exists")
+except RepositoryNotFoundError:
+    print(f"Repo {repo_id} not found")
+    create_repo(repo_id=repo_id, repo_type=repo_type)
+    print(f"Repo {repo_id} created")
+
+#api.upload_folder(
+    #folder_path="mlops/data",
+    #repo_id=repo_id,
+    #repo_type=repo_type,
+#)
+api.upload_folder(
+    folder_path="engine1/data",
+    repo_id=repo_id,
+    repo_type=repo_type,
+    commit_message="Initial dataset upload",
+    ignore_patterns=["*.py", "__pycache__/*"],
+)