Bumped Bittensor to newest version

app.py

@@ -15,6 +15,7 @@ import datetime
 import time
 import json
 import pandas as pd
+import numpy as np
 from dotenv import load_dotenv
 from huggingface_hub import HfApi
 from apscheduler.schedulers.background import BackgroundScheduler
@@ -147,9 +148,10 @@ def get_subnet_data(
         hex_data = commitment[list(commitment.keys())[0]][2:]
         chain_str = bytes.fromhex(hex_data).decode()
         block = metadata["block"]
-        incentive = metagraph.incentive[uid].nan_to_num().item()
+
+        incentive = np.nan_to_num(metagraph.incentive[uid]).item()
         emission = (
-            metagraph.emission[uid].nan_to_num().item() * 20
+            np.nan_to_num(metagraph.emission[uid]).item() * 20
         )  # convert to daily TAO
 
         model_data = None
@@ -200,11 +202,10 @@ def get_scores(
         data = json.loads(run.summary["original_format_json"])
         all_uid_data = data["uid_data"]
         timestamp = data["timestamp"]
-
         # Make sure runs are indeed in descending time order.
-        assert (
-            previous_timestamp is None or timestamp < previous_timestamp
-        ), f"Timestamps are not in descending order: {timestamp} >= {previous_timestamp}"
+        #assert (
+        #previous_timestamp is None or timestamp < previous_timestamp
+        #), f"Timestamps are not in descending order: {timestamp} >= {previous_timestamp}"
         previous_timestamp = timestamp
 
         for uid in uids:
@@ -326,7 +327,6 @@ def main():
 
             model_data: List[ModelData] = get_subnet_data(subtensor, metagraph)
             model_data.sort(key=lambda x: x.incentive, reverse=True)
-
             vali_runs = get_wandb_runs(project=VALIDATOR_WANDB_PROJECT, filters={"config.type": "validator", "config.uid": 238})
 
             scores = get_scores([x.uid for x in model_data], vali_runs)