organized adding envs + added more envs

.gitignore

@@ -0,0 +1 @@
+__pycache__/*

app.py

@@ -1,81 +1,42 @@
 import requests
 import pandas as pd
 from tqdm.auto import tqdm
-
+from utils import *
 import gradio as gr
 from huggingface_hub import HfApi, hf_hub_download
 from huggingface_hub.repocard import metadata_load
 
 
-RL_ENVS = ['LunarLander-v2','CarRacing-v0','MountainCar-v0',
- 'BipedalWalker-v3','FrozenLake-v1','FrozenLake-v1-no_slippery',
- 'Taxi-v3','Cliffwalker-v0']
+class DeepRL_Leaderboard:
+    def __init__(self) -> None:
+        self.leaderboard= {} 
 
-with open('app.css','r') as f:
-    BLOCK_CSS = f.read() 
+    def add_leaderboad(self,id=None, title=None):
+        if id is not None and title is not None:
+            id = id.strip()
+            title = title.strip()
+            self.leaderboard.update({id:{'title':title,'data':get_data_per_env(id)}})
+    def get_data(self):
+        return self.leaderboard
 
-LOADED_MODEL_IDS = {rl_env:[] for rl_env in RL_ENVS}
+    def get_ids(self):
+        return list(self.leaderboard.keys())
 
+          
 
-# Based on Omar Sanseviero work
-# Make model clickable link
-def make_clickable_model(model_name):
-    # remove user from model name
-    model_name_show = ' '.join(model_name.split('/')[1:])
+# CSS file for the
+with open('app.css','r') as f:
+    BLOCK_CSS = f.read() 
 
-    link = "https://huggingface.co/" + model_name
-    return f'<a target="_blank" href="{link}">{model_name_show}</a>'
 
-# Make user clickable link
-def make_clickable_user(user_id):
-    link = "https://huggingface.co/" + user_id
-    return f'<a  target="_blank" href="{link}">{user_id}</a>'
-    
-def get_model_ids(rl_env):
-    api = HfApi()
-    models = api.list_models(filter=rl_env)
-    model_ids = [x.modelId for x in models]
-    return model_ids
-    
-def get_metadata(model_id):
-    try:
-        readme_path = hf_hub_download(model_id, filename="README.md")
-        return metadata_load(readme_path)
-    except requests.exceptions.HTTPError:
-        # 404 README.md not found
-        return None
-        
-def parse_metrics_accuracy(meta):
-    if "model-index" not in meta:
-        return None
-    result = meta["model-index"][0]["results"]
-    metrics = result[0]["metrics"]
-    accuracy = metrics[0]["value"]
-    return accuracy
-
-# We keep the worst case episode
-def parse_rewards(accuracy):
-    default_std = -1000
-    default_reward=-1000
-    if accuracy !=  None:
-        parsed =  accuracy.split(' +/- ')
-        if len(parsed)>1:
-            mean_reward = float(parsed[0])
-            std_reward =  float(parsed[1])
-        else: 
-            mean_reward = default_std
-            std_reward = default_reward
 
-    else:
-        mean_reward = default_std
-        std_reward = default_reward
-    return mean_reward, std_reward
+LOADED_MODEL_IDS = {}
 
 def get_data(rl_env):
     global LOADED_MODEL_IDS 
     data = []
     model_ids = get_model_ids(rl_env)
-    LOADED_MODEL_IDS[rl_env]+=model_ids
+    LOADED_MODEL_IDS[rl_env]=model_ids
 
     for model_id in tqdm(model_ids):
         meta = get_metadata(model_id)
@@ -93,6 +54,47 @@ def get_data(rl_env):
         data.append(row)
     return pd.DataFrame.from_records(data)
 
+def get_data_per_env(rl_env):
+    dataframe = get_data(rl_env)
+    dataframe = dataframe.fillna("")
+
+    if not dataframe.empty:
+        # turn the model ids into clickable links
+        dataframe["User"] = dataframe["User"].apply(make_clickable_user)
+        dataframe["Model"] = dataframe["Model"].apply(make_clickable_model)
+        dataframe = dataframe.sort_values(by=['Results'], ascending=False)
+        if not 'Ranking' in dataframe.columns:
+            dataframe.insert(0, 'Ranking', [i for i in range(1,len(dataframe)+1)])
+        else:
+           dataframe['Ranking'] =   [i for i in range(1,len(dataframe)+1)]   
+        table_html = dataframe.to_html(escape=False, index=False,justify = 'left')
+        return table_html,dataframe,dataframe.empty
+    else: 
+        html = """<div style="color: green">
+                <p> ⌛ Please wait. Results will be out soon... </p>
+                </div>
+               """
+        return html,dataframe,dataframe.empty   
+
+
+
+rl_leaderboard = DeepRL_Leaderboard()
+rl_leaderboard.add_leaderboad('CarRacing-v0'," The Car Racing 🏎️ Leaderboard 🚀")
+rl_leaderboard.add_leaderboad('MountainCar-v0',"The Mountain Car ⛰️ 🚗 Leaderboard 🚀")
+rl_leaderboard.add_leaderboad('LunarLander-v2',"The Lunar Lander 🌕 Leaderboard 🚀")
+rl_leaderboard.add_leaderboad('BipedalWalker-v3',"The BipedalWalker Leaderboard 🚀")
+rl_leaderboard.add_leaderboad('Taxi-v3','The Taxi-v3🚖 Leaderboard 🚀')
+rl_leaderboard.add_leaderboad('FrozenLake-v1-4x4-no_slippery','The FrozenLake-v1-4x4-no_slippery Leaderboard 🚀')
+rl_leaderboard.add_leaderboad('FrozenLake-v1-8x8-no_slippery','The FrozenLake-v1-8x8-no_slippery Leaderboard 🚀')
+rl_leaderboard.add_leaderboad('FrozenLake-v1-4x4','The FrozenLake-v1-4x4 Leaderboard 🚀')
+rl_leaderboard.add_leaderboad('FrozenLake-v1-8x8','The FrozenLake-v1-8x8 Leaderboard 🚀')
+
+RL_ENVS = rl_leaderboard.get_ids()
+RL_DETAILS = rl_leaderboard.get_data()
+
+
+
+
 
 
 def update_data(rl_env):
@@ -149,27 +151,6 @@ def update_data_per_env(rl_env):
         return html,dataframe,dataframe.empty   
 
 
-def get_data_per_env(rl_env):
-    dataframe = get_data(rl_env)
-    dataframe = dataframe.fillna("")
-
-    if not dataframe.empty:
-        # turn the model ids into clickable links
-        dataframe["User"] = dataframe["User"].apply(make_clickable_user)
-        dataframe["Model"] = dataframe["Model"].apply(make_clickable_model)
-        dataframe = dataframe.sort_values(by=['Results'], ascending=False)
-        if not 'Ranking' in dataframe.columns:
-            dataframe.insert(0, 'Ranking', [i for i in range(1,len(dataframe)+1)])
-        else:
-           dataframe['Ranking'] =   [i for i in range(1,len(dataframe)+1)]   
-        table_html = dataframe.to_html(escape=False, index=False,justify = 'left')
-        return table_html,dataframe,dataframe.empty
-    else: 
-        html = """<div style="color: green">
-                <p> ⌛ Please wait. Results will be out soon... </p>
-                </div>
-               """
-        return html,dataframe,dataframe.empty   
 
 
 
@@ -225,15 +206,6 @@ def reload_leaderboard(rl_env):
             
 
            
-RL_DETAILS ={'CarRacing-v0':{'title':" The Car Racing 🏎️ Leaderboard 🚀",'data':get_data_per_env('CarRacing-v0')},
-            'MountainCar-v0':{'title':"The Mountain Car ⛰️ 🚗 Leaderboard 🚀",'data':get_data_per_env('MountainCar-v0')},
-            'LunarLander-v2':{'title':"The Lunar Lander 🌕 Leaderboard 🚀",'data':get_data_per_env('LunarLander-v2')},
-            'BipedalWalker-v3':{'title':"The BipedalWalker Leaderboard 🚀",'data':get_data_per_env('BipedalWalker-v3')},
-            'FrozenLake-v1':{'title':"The FrozenLake Leaderboard 🚀",'data':get_data_per_env('FrozenLake-v1')},
-            'FrozenLake-v1-no_slippery':{'title':'The FrozenLake-v1-no_slippery Leaderboard 🚀','data':get_data_per_env('FrozenLake-v1-no_slippery')},
-            'Taxi-v3':{'title':'The Taxi-v3🚖 Leaderboard 🚀','data':get_data_per_env('Taxi-v3')},
-            'Cliffwalker-v0':{'title':'The Cliffwalker-v0 Leaderboard 🚀','data':get_data_per_env('Cliffwalker-v0')},
-            }
 
 
 

utils.py

@@ -0,0 +1,63 @@
+import pandas as pd
+import requests
+from tqdm.auto import tqdm
+from huggingface_hub import HfApi, hf_hub_download
+from huggingface_hub.repocard import metadata_load
+
+
+# Based on Omar Sanseviero work
+# Make model clickable link
+def make_clickable_model(model_name):
+    # remove user from model name
+    model_name_show = ' '.join(model_name.split('/')[1:])
+
+    link = "https://huggingface.co/" + model_name
+    return f'<a target="_blank" href="{link}">{model_name_show}</a>'
+
+# Make user clickable link
+def make_clickable_user(user_id):
+    link = "https://huggingface.co/" + user_id
+    return f'<a  target="_blank" href="{link}">{user_id}</a>'
+    
+
+
+def get_model_ids(rl_env):
+    api = HfApi()
+    models = api.list_models(filter=rl_env)
+    model_ids = [x.modelId for x in models]
+    return model_ids
+    
+def get_metadata(model_id):
+    try:
+        readme_path = hf_hub_download(model_id, filename="README.md")
+        return metadata_load(readme_path)
+    except requests.exceptions.HTTPError:
+        # 404 README.md not found
+        return None
+        
+def parse_metrics_accuracy(meta):
+    if "model-index" not in meta:
+        return None
+    result = meta["model-index"][0]["results"]
+    metrics = result[0]["metrics"]
+    accuracy = metrics[0]["value"]
+    return accuracy
+
+# We keep the worst case episode
+def parse_rewards(accuracy):
+    default_std = -1000
+    default_reward=-1000
+    if accuracy !=  None:
+        parsed =  accuracy.split(' +/- ')
+        if len(parsed)>1:
+            mean_reward = float(parsed[0])
+            std_reward =  float(parsed[1])
+        else: 
+            mean_reward = default_std
+            std_reward = default_reward
+
+    else:
+        mean_reward = default_std
+        std_reward = default_reward
+    return mean_reward, std_reward
+