finale

Author: xadupre

_scripts/export_qwen25_vl_visual.py

@@ -364,6 +364,7 @@ def fprint(s):
             for i, feed in enumerate(tqdm.tqdm(feeds)):
                 if (
                     device == "cpu"
+                    and dtype == "float16"
                     and os.environ.get("QWEN25ATTENTION", "default") == "LOOPA23"
                     and i >= 2
                 ):
@@ -437,9 +438,27 @@ def fprint(s):
             "latency_torch",
             "latency_ort_n",
         ]
-        stat = df[[*index, *values]].groupby(index).max()
+        stat = (
+            df[[*index, *values]]
+            .groupby(index)
+            .agg(
+                {
+                    **{c: "max" for c in values if c != "speedup"},
+                    "speedup": "min",
+                }
+            )
+        )
         stat.to_excel(statistics + ".agg.xlsx")
-        stat = df[df.exporter == "onnx-dynamo"][[*index, *values]].groupby(index).max()
+        stat = (
+            df[df.exporter == "onnx-dynamo"][[*index, *values]]
+            .groupby(index)
+            .agg(
+                {
+                    **{c: "max" for c in values if c != "speedup"},
+                    "speedup": "min",
+                }
+            )
+        )
         stat.to_excel(statistics + ".agg.onnx-dynamo.xlsx")
 
     if make_zip:

_scripts/investigate.ipynb

@@ -161,7 +161,16 @@
     "    \"latency_ort_n\",\n",
     "]\n",
     "df = pandas.read_json(\"dump_models/collection_statistics.js\", lines=True)\n",
-    "stat = df[[*index, *values]].groupby(index).max()\n",
+    "stat = (\n",
+    "    df[[*index, *values]]\n",
+    "    .groupby(index)\n",
+    "    .agg(\n",
+    "        {\n",
+    "            **{c: \"max\" for c in values if c != \"speedup\"},\n",
+    "            \"speedup\": \"min\",\n",
+    "        }\n",
+    "    )\n",
+    ")\n",
     "stat"
    ]
   },
@@ -173,7 +182,16 @@
    "outputs": [],
    "source": [
     "df = pandas.read_json(\"dump_models/collection_statistics.js\", lines=True)\n",
-    "stat = df[df.exporter == \"onnx-dynamo\"][[*index, *values]].groupby(index).max()\n",
+    "stat = (\n",
+    "    df[df.exporter == \"onnx-dynamo\"][[*index, *values]]\n",
+    "    .groupby(index)\n",
+    "    .agg(\n",
+    "        {\n",
+    "            **{c: \"max\" for c in values if c != \"speedup\"},\n",
+    "            \"speedup\": \"min\",\n",
+    "        }\n",
+    "    )\n",
+    ")\n",
     "stat"
    ]
   },