updated dmc and atari

hsuanwuhub/datasets/atari_100k.py

@@ -0,0 +1,26 @@
+from typing import Dict
+from huggingface_hub import hf_hub_download
+import pandas as pd
+import numpy as np
+
+
+class Atari_100k(object):
+    def __init__(self) -> None:
+        file = hf_hub_download(
+            repo_id="RLE-Foundation/HsuanwuHub",
+            repo_type="dataset",
+            filename="atari_100k.json",
+            subfolder="datasets"
+        )
+        self.atari_100k_data = pd.read_json(file)
+
+    def load_scores(self) -> Dict[str, np.ndarray]:
+        """Returns final performance"""
+        scores_dict = dict()
+        for algo in self.atari_100k_data.keys():
+            scores_dict[algo] = np.array([value for _, value in self.atari_100k_data[algo].items()]).T
+
+        return scores_dict
+
+    def load_curves(self) -> np.ndarray:
+        pass

hsuanwuhub/datasets/atari_200_iters.py

@@ -0,0 +1,27 @@
+from typing import Dict
+from huggingface_hub import hf_hub_download
+import numpy as np
+
+
+class Atari_200_iters(object):
+    def __init__(self) -> None:
+        file = hf_hub_download(
+            repo_id="RLE-Foundation/HsuanwuHub",
+            repo_type="dataset",
+            filename="atari_200_iters_normalized_scores.npy",
+            subfolder="datasets"
+        )
+
+        with open(file, 'rb') as f:
+            atari_200m_scores = np.load(f, allow_pickle=True)
+            atari_200m_scores = atari_200m_scores.tolist()
+        for key, val in atari_200m_scores.items():
+            atari_200m_scores[key] = np.transpose(val, axes=(1, 2, 0))
+        self.atari_200_iters_normalized_scores = atari_200m_scores
+
+    def load_scores(self) -> Dict[str, np.ndarray]:
+        """Returns final performance"""
+        return self.atari_200_iters_normalized_scores
+
+    def load_curves(self) -> np.ndarray:
+        pass

hsuanwuhub/datasets/dm_control.py

@@ -0,0 +1,26 @@
+from typing import Dict
+from huggingface_hub import hf_hub_download
+import pandas as pd
+import numpy as np
+
+
+class DM_Control(object):
+    def __init__(self) -> None:
+        file = hf_hub_download(
+            repo_id="RLE-Foundation/HsuanwuHub",
+            repo_type="dataset",
+            filename="dm_control.json", 
+            subfolder="datasets"
+        )
+        self.dm_control_data = pd.read_json(file)
+
+    def load_scores(self) -> Dict[str, np.ndarray]:
+        """Returns final performance"""
+        scores_dict = dict()
+        for algo in self.dm_control_data.keys():
+            scores_dict[algo] = np.array([value for _, value in self.dm_control_data[algo].items()]).T
+
+        return scores_dict
+
+    def load_curves(self) -> np.ndarray:
+        pass