add

update_almost_agi.py

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+#!/usr/bin/env python3
+import os
+
+from collections import Counter
+from datasets import load_dataset
+from huggingface_hub import HfApi, list_datasets
+
+
+api = HfApi(token=os.environ.get("HF_TOKEN", None))
+def restart_space():
+  api.restart_space(repo_id="OpenGenAI/parti-prompts-leaderboard")
+
+parti_prompt_results = []
+ORG = "diffusers-parti-prompts"
+SUBMISSIONS = {
+    "kand2": None,
+    "sdxl": None,
+    "wuerst": None,
+    "karlo": None,
+}
+LINKS = {
+    "kand2": "https://huggingface.co/kandinsky-community/kandinsky-2-2-decoder",
+    "sdxl": "https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0",
+    "wuerst": "https://huggingface.co/warp-ai/wuerstchen",
+    "karlo": "https://huggingface.co/kakaobrain/karlo-v1-alpha",
+}
+MODEL_KEYS = "-".join(SUBMISSIONS.keys())
+SUBMISSION_ORG = f"result-{MODEL_KEYS}"
+
+submission_names = list(SUBMISSIONS.keys())
+
+ORG = "diffusers-parti-prompts"
+SUBMISSIONS = {
+    "kand2": load_dataset(os.path.join(ORG, "kandinsky-2-2"))["train"],
+    "sdxl": load_dataset(os.path.join(ORG, "sdxl-1.0-refiner"))["train"],
+    "wuerst": load_dataset(os.path.join(ORG, "wuerstchen"))["train"],
+    "karlo": load_dataset(os.path.join(ORG, "karlo-v1"))["train"],
+}
+ds = load_dataset("nateraw/parti-prompts")["train"]
+
+parti_prompt_categories = ds["Category"]
+parti_prompt_challenge = ds["Challenge"]
+
+UPLOAD_ORG = "almost-agi-diff"
+
+def load_non_solved():
+    all_datasets = list_datasets(author=SUBMISSION_ORG)
+    relevant_ids = [d.id for d in all_datasets]
+    
+    all_non_solved_image_ids = []
+
+    for _id in relevant_ids[:5]:
+        try:
+            ds = load_dataset(_id)["train"]
+        except:
+            continue
+
+        for result, image_id in zip(ds["result"], ds["id"]):
+            if result == "":
+                all_non_solved_image_ids.append(image_id)
+
+    all_non_solved_image_ids_dict = Counter(all_non_solved_image_ids)
+    all_non_solved_image_ids = list(all_non_solved_image_ids_dict.keys())
+    all_non_solved_image_votes = list(all_non_solved_image_ids_dict.values())
+
+    return all_non_solved_image_ids, all_non_solved_image_votes
+
+def main():
+    non_solved_ids, upvotes = load_non_solved()
+
+    for name, ds in SUBMISSIONS.items():
+        ds_to_push = ds.select(non_solved_ids)
+
+        votes_column = upvotes
+
+        ds_to_push.add_column("upvotes", votes_column)
+        sorted_ds = ds_to_push.sort("upvotes", reverse=True)
+
+        import ipdb; ipdb.set_trace()
+        sorted_ds.push_to_hub(f"{UPLOAD_ORG}/{name}")