added optimizations to control panel

app.py

@@ -31,8 +31,8 @@ COLUMNS_MAPPING = {
     "backend.torch_dtype": "Load Dtype 📥",
     "optimizations": "Optimizations 🛠️",
     #
-    "forward.peak_memory(MB)": "Peak Memory (MB) ⬇️",
     "generate.throughput(tokens/s)": "Throughput (tokens/s) ⬆️",
+    "forward.peak_memory(MB)": "Peak Memory (MB) ⬇️",
     "average": "Average Open LLM Score ⬆️",
     #
     "num_parameters": "#️⃣ Parameters 📏",
@@ -67,11 +67,7 @@ def get_benchmark_df(benchmark="1xA100-80GB"):
     bench_df["optimizations"] = bench_df[
         ["backend.bettertransformer", "backend.load_in_8bit", "backend.load_in_4bit"]
     ].apply(
-        lambda x: "BetterTransformer 🤖"
-        if x[0] == True
-        else (
-            "LLM.int8 🗜️" if x[1] == True else ("NF4 🗜️" if x[2] == True else "")
-        ),
+        lambda x: ", ".join([opt for opt in x.index if x[opt] == True]),
         axis=1,
     )
 
@@ -151,13 +147,22 @@ def get_benchmark_plot(bench_df):
     return fig
 
 
-def filter_query(text, backends, datatypes, threshold, benchmark="1xA100-80GB"):
+def filter_query(
+    text, backends, datatypes, optimizations, threshold, benchmark="1xA100-80GB"
+):
     raw_df = get_benchmark_df(benchmark=benchmark)
 
     filtered_df = raw_df[
         raw_df["model"].str.lower().str.contains(text.lower())
         & raw_df["backend.name"].isin(backends)
         & raw_df["backend.torch_dtype"].isin(datatypes)
+        & pd.concat(
+            [
+                raw_df["optimizations"].str.contains(optimization)
+                for optimization in optimizations
+            ],
+            axis=1,
+        ).any(axis=1)
         & (raw_df["average"] >= threshold)
     ]
 
@@ -191,6 +196,8 @@ with demo:
             info="🔍 Search for a model name",
             elem_id="search-bar",
         )
+
+    with gr.Row():
         backend_checkboxes = gr.CheckboxGroup(
             label="Backends 🏭",
             choices=["pytorch", "onnxruntime"],
@@ -205,7 +212,16 @@ with demo:
             info="☑️ Select the load datatypes",
             elem_id="datatype-checkboxes",
         )
-        threshold_slider = gr.Slider(
+        optimizations_checkboxes = gr.CheckboxGroup(
+            label="Optimizations 🛠️",
+            choices=["BetterTransformer", "LLM.int8", "NF4"],
+            value=[],
+            info="☑️ Select the optimizations",
+            elem_id="optimizations-checkboxes",
+        )
+
+    with gr.Row():
+        score_slider = gr.Slider(
             label="Average Open LLM Score 📈",
             info="🎚️ Slide to minimum Average Open LLM score",
             value=0.0,
@@ -213,9 +229,9 @@ with demo:
         )
 
     with gr.Row():
-        submit_button = gr.Button(
+        filter_button = gr.Button(
             value="Filter 🚀",
-            elem_id="submit-button",
+            elem_id="filter-button",
         )
 
     # leaderboard tabs
@@ -242,9 +258,15 @@ with demo:
                 show_label=False,
             )
 
-        submit_button.click(
+        filter_button.click(
             filter_query,
-            [search_bar, backend_checkboxes, datatype_checkboxes, threshold_slider],
+            [
+                search_bar,
+                backend_checkboxes,
+                datatype_checkboxes,
+                optimizations_checkboxes,
+                score_slider,
+            ],
             [single_A100_leaderboard, single_A100_plotly],
         )