Add GPU types

app.py

@@ -36,6 +36,7 @@ from src.display.utils import (
     fields,
     WeightType,
     Precision,
+    GPUType
 )
 
 from src.envs import API, EVAL_REQUESTS_PATH, EVAL_RESULTS_PATH, H4_TOKEN, IS_PUBLIC, \
@@ -155,47 +156,47 @@ shown_columns = None
 dataset_df, original_df, finished_eval_queue_df, running_eval_queue_df, pending_eval_queue_df = init_space()
 leaderboard_df = original_df.copy()
 
-def update_leaderboard_table():
-    global leaderboard_df, shown_columns
-    print("Updating leaderboard table")
-    return leaderboard_df[
-                [c.name for c in fields(AutoEvalColumn) if c.never_hidden]
-                + shown_columns.value
-                + [AutoEvalColumn.dummy.name]
-            ] if not leaderboard_df.empty else leaderboard_df
+# def update_leaderboard_table():
+#     global leaderboard_df, shown_columns
+#     print("Updating leaderboard table")
+#     return leaderboard_df[
+#                 [c.name for c in fields(AutoEvalColumn) if c.never_hidden]
+#                 + shown_columns.value
+#                 + [AutoEvalColumn.dummy.name]
+#             ] if not leaderboard_df.empty else leaderboard_df
         
 
-def update_hidden_leaderboard_table():
-    global original_df
-    return original_df[COLS] if original_df.empty is False else original_df
+# def update_hidden_leaderboard_table():
+#     global original_df
+#     return original_df[COLS] if original_df.empty is False else original_df
 
-def update_dataset_table():
-    global dataset_df
-    return dataset_df
+# def update_dataset_table():
+#     global dataset_df
+#     return dataset_df
 
-def update_finish_table():
-    global finished_eval_queue_df
-    return finished_eval_queue_df
+# def update_finish_table():
+#     global finished_eval_queue_df
+#     return finished_eval_queue_df
 
-def update_running_table():
-    global running_eval_queue_df
-    return running_eval_queue_df
+# def update_running_table():
+#     global running_eval_queue_df
+#     return running_eval_queue_df
 
-def update_pending_table():
-    global pending_eval_queue_df
-    return pending_eval_queue_df
+# def update_pending_table():
+#     global pending_eval_queue_df
+#     return pending_eval_queue_df
 
-def update_finish_num():
-    global finished_eval_queue_df
-    return len(finished_eval_queue_df)
+# def update_finish_num():
+#     global finished_eval_queue_df
+#     return len(finished_eval_queue_df)
 
-def update_running_num():
-    global running_eval_queue_df
-    return len(running_eval_queue_df)
+# def update_running_num():
+#     global running_eval_queue_df
+#     return len(running_eval_queue_df)
 
-def update_pending_num():
-    global pending_eval_queue_df
-    return len(pending_eval_queue_df)
+# def update_pending_num():
+#     global pending_eval_queue_df
+#     return len(pending_eval_queue_df)
 
 # triggered only once at startup => read query parameter if it exists
 def load_query(request: gr.Request):
@@ -377,6 +378,15 @@ with demo:
                     value=None,
                     interactive=True,
                 )
+                
+                gpu_type = gr.Dropdown(
+                    choices=[t.to_str() for t in GPUType],
+                    label="GPU type",
+                    multiselect=False,
+                    value=None,
+                    interactive=True,
+                )
+                
 
             with gr.Row():
                 with gr.Column():
@@ -412,6 +422,7 @@ with demo:
 
             submit_button = gr.Button("Submit Eval")
             submission_result = gr.Markdown()
+            debug = gr.Textbox(label=args.debug, placeholder="main", visible=False)
             submit_button.click(
                 add_new_eval,
                 [
@@ -448,9 +459,9 @@ def launch_backend():
     if DEVICE not in {"cpu"}:
         _ = subprocess.run(["python", "backend-cli.py"])
 
-Thread(target=periodic_init, daemon=True).start()
+# Thread(target=periodic_init, daemon=True).start()
 # scheduler.add_job(launch_backend, "interval", seconds=120)
 if __name__ == "__main__":
     scheduler.start()
-    block_launch()
+    demo.queue(default_concurrency_limit=40).launch()
     

src/display/utils.py

@@ -190,7 +190,25 @@ class InferenceFramework(Enum):
             return InferenceFramework.HF_Chat
         return InferenceFramework.Unknown
 
+class GPUType(Enum):
+    H100_pcie = ModelDetails("NVIDIA H100 PCIe")
+    A100_pcie = ModelDetails("NVIDIA A100 PCIe")
+    A5000 = ModelDetails("NVIDIA A5000")
+    Unknown = ModelDetails("?")
 
+    def to_str(self):
+        return self.value.name
+
+    @staticmethod
+    def from_str(gpu_type: str):
+        if gpu_type in ["NVIDIA A100 PCIe"]:
+            return GPUType.A100_pcie
+        if gpu_type in ["NVIDIA H100 PCIe"]:
+            return GPUType.H100_pcie
+        if gpu_type in ["NVIDIA A5000"]:
+            return GPUType.A5000
+        return GPUType.Unknown
+    
 class WeightType(Enum):
     Adapter = ModelDetails("Adapter")
     Original = ModelDetails("Original")