Update constants.py

constants.py

@@ -1,10 +1,37 @@
-LEADERBOARD_INTRODUCTION = """
-# DD-Ranking Leaderboard
+LEADERBOARD_HEADER = """
+<style>
+.header-gradient {
+    top: 40%;
+    bottom: 40%;
+    padding: 10px 0px;
+    font-weight: bold;
+    font-size: 40px;
+    font-family: Inter, Arial, Helvetica, sans-serif;
+    background: linear-gradient(to right, #5EA2EF, #0072F5);
+    -webkit-text-fill-color: transparent;
+    -webkit-background-clip: text;
+}
+
+.header-normal {
+    top: 40%;
+    bottom: 40%;
+    padding: 10px 0px;
+    font-weight: bold;
+    font-size: 40px;
+    font-family: Inter, Arial, Helvetica, sans-serif;
+}
+</style>
 
-</h3>
+<div align="center">
+    <span class="header-gradient"> DD-Ranking </span>
+    <span class="header-normal"> Leaderboard </span>
+</div>
 <p align="center">
 | <a href="https://nus-hpc-ai-lab.github.io/DD-Ranking/"><b>Documentation</b></a> | <a href="https://github.com/NUS-HPC-AI-Lab/DD-Ranking"><b>Github</b></a> | <a href=""><b>Paper </b> (Coming Soon)</a> | <a href=""><b>Twitter/X</b> (Coming Soon)</a> | <a href=""><b>Developer Slack</b> (Coming Soon)</a> |
-</p>
+</p>"""
+
+LEADERBOARD_INTRODUCTION = """
+# DD-Ranking Leaderboard
 
 🏆 Welcome to the leaderboard of the **DD-Ranking**! 
 
@@ -32,12 +59,17 @@ Hard labels are categorical, having the same format of the real dataset. Soft la
 """
 
 WEIGHT_ADJUSTMENT_INTRODUCTION = """
-The score for ranking in the following table is computed by $score = \sum w_i score_i$, where $w_i$ is the weight for the $i$-th metric.
+The score for ranking in the following table is computed by $score = w score_{HLR} - (1 - w) score_{IOR}$, where $w$ is the weight for the HLR metric.
 **You can specify the weights for each metric below.**
 """
 
 DATASET_LIST = ["CIFAR-10", "CIFAR-100", "Tiny-ImageNet"]
 IPC_LIST = ["IPC-1", "IPC-10", "IPC-50"]
+DATASET_IPC_LIST = {
+    "CIFAR-10": ["IPC-1", "IPC-10", "IPC-50"],
+    "CIFAR-100": ["IPC-1", "IPC-10", "IPC-50"],
+    "Tiny-ImageNet": ["IPC-10", "IPC-50"],
+}
 LABEL_TYPE_LIST = ["Hard Label", "Soft Label"]
 
 METRICS = ["HLR", "IOR"]