tiny modifications

_scripts/export_qwen25_vl_visual.py

@@ -97,6 +97,7 @@ def main(
     second_input: bool = True,
     make_zip: bool = False,
     output_folder: str = "dump_models",
+    existing_onnx: str | None = None,
 ):
     prefix = simplify_model_id_for_a_filename(model_id)
     if "QWEN25ATTENTION" in os.environ:
@@ -115,7 +116,7 @@ def main(
     print("------------------------------------------------------------------")
     print(f"-- export in {filename!r}")
 
-    if os.path.exists(stat_file):
+    if os.path.exists(stat_file) and not existing_onnx:
         print(f"-- skipping because {stat_file!r} already exists")
         return
 
@@ -278,55 +279,73 @@ def compute_expected():
         compute_expected() if not os.environ.get("STOPAT", "") else (None, None)
     )
 
-    print("-- ######")
-    print("-- EXPORT")
-    print("-- ######")
+    if existing_onnx and os.path.exists(existing_onnx):
+        exporter = existing_onnx
+        filename = existing_onnx
+        export_duration = None
+        target_opset = None
+    else:
+        print("-- ######")
+        print("-- EXPORT")
+        print("-- ######")
 
-    dynamic_shapes = dict(
-        hidden_states={0: "hidden_width", 1: "hidden_height"},
-        grid_thw={},  # {0: "n_images"}, # TODO: fix
-    )
+        dynamic_shapes = dict(
+            hidden_states={0: "hidden_width", 1: "hidden_height"},
+            grid_thw={},  # {0: "n_images"}, # TODO: fix
+        )
 
-    begin = time.perf_counter()
-
-    target_opset = 22
-    if exporter == "onnx-dynamo" and device == "cuda" and "QWEN25ATTENTION" not in os.environ:
-        os.environ["QWEN25ATTENTION"] = "PACKED"
-    elif "QWEN25ATTENTION" in os.environ and os.environ["QWEN25ATTENTION"] == "LOOPA23":
-        target_opset = 23
-
-    with torch_export_patches(
-        patch_torch=False,
-        patch_sympy=False,
-        patch_transformers=True,
-        verbose=1,
-        stop_if_static=2,
-    ):
-        if export_expected is None:
-            export_expected, other_expected, durations = compute_expected()
-        to_onnx(
-            model_to_export,
-            kwargs=export_inputs,
-            dynamic_shapes=dynamic_shapes,
-            filename=filename,
-            exporter=exporter,
+        begin = time.perf_counter()
+
+        target_opset = 22
+        if (
+            exporter == "onnx-dynamo"
+            and device == "cuda"
+            and "QWEN25ATTENTION" not in os.environ
+        ):
+            os.environ["QWEN25ATTENTION"] = "PACKED"
+        elif "QWEN25ATTENTION" in os.environ and os.environ["QWEN25ATTENTION"] == "LOOPA23":
+            target_opset = 23
+
+        with torch_export_patches(
+            patch_torch=False,
+            patch_sympy=False,
+            patch_transformers=True,
             verbose=1,
-            save_ep=None,
-            target_opset=target_opset,
-            optimize=True,
-            onnx_plugs=PLUGS,
-        )
-    export_duration = time.perf_counter() - begin
+            stop_if_static=2,
+        ):
+            if export_expected is None:
+                export_expected, other_expected, durations = compute_expected()
+            to_onnx(
+                model_to_export,
+                kwargs=export_inputs,
+                dynamic_shapes=dynamic_shapes,
+                filename=filename,
+                exporter=exporter,
+                verbose=1,
+                save_ep=None,
+                target_opset=target_opset,
+                optimize=True,
+                onnx_plugs=PLUGS,
+            )
+        export_duration = time.perf_counter() - begin
 
-    if exporter == "onnx-dynamo":
-        # onnx-dynamo fails at producing function body with sequences as input / output.
-        # They are replaced by tensor type one step in the model.
-        print("-- remove_body_last_input_output_for_loop")
-        remove_inplace_body_last_input_output_type_for_loop(filename)
-        print("-- done.")
+        if exporter == "onnx-dynamo":
+            # onnx-dynamo fails at producing function body with sequences as input / output.
+            # They are replaced by tensor type one step in the model.
+            print("-- remove_body_last_input_output_for_loop")
+            remove_inplace_body_last_input_output_type_for_loop(filename)
+            print("-- done.")
 
     with open(stat_file, "w") as f:
 
+        def _rename(k):
+            if rename_inputs:
+                if k == "hidden_states":
+                    return "pixel_values"
+                if k == "grid_thw":
+                    return "image_grid_thw"
+            return k
+
         def fprint(s):
             print(s)
             f.write(f"{s}\n")
@@ -337,21 +356,22 @@ def fprint(s):
             providers = providers[1:]
         fprint(f"-- checking discrepancies with providers={providers!r}")
         sess = onnxruntime.InferenceSession(filename, providers=providers)
+        rename_inputs = sess.get_inputs()[0].name != "hidden_states"
 
         fprint(
             f"-- export_inputs {string_type(export_inputs, with_shape=True, with_device=True)}"
         )
         fprint(
             f"-- export_expected {string_type(export_expected, with_shape=True, with_device=True)}"
         )
-        feeds = {k: v.detach().cpu().numpy() for k, v in export_inputs.items()}
+        feeds = {_rename(k): v.detach().cpu().numpy() for k, v in export_inputs.items()}
         small = sess.run(None, feeds)
         diff = max_diff(export_expected, small[0], hist=[0.1, 0.01])
         fprint(f"-- discrepancies={diff}")
 
         if second_input:
             feeds = [
-                {k: v.detach().cpu().numpy() for k, v in inputs.items()}
+                {_rename(k): v.detach().cpu().numpy() for k, v in inputs.items()}
                 for inputs in other_inputs
             ]
             fprint("")
@@ -440,7 +460,7 @@ def fprint(s):
         ]
         stat = (
             df[[*index, *values]]
-            .groupby(index)
+            .groupby(index, dropna=False)
             .agg(
                 {
                     **{c: "max" for c in values if c != "speedup"},
@@ -450,8 +470,8 @@ def fprint(s):
         )
         stat.to_excel(statistics + ".agg.xlsx")
         stat = (
-            df[df.exporter == "onnx-dynamo"][[*index, *values]]
-            .groupby(index)
+            df[df.exporter != "custom"][[*index, *values]]
+            .groupby(index, dropna=False)
             .agg(
                 {
                     **{c: "max" for c in values if c != "speedup"},
@@ -517,6 +537,12 @@ def get_parser() -> ArgumentParser:
         help="Folders where to put the results.",
         action=BooleanOptionalAction,
     )
+    parser.add_argument(
+        "-x",
+        "--existing-onnx",
+        default="",
+        help="If an onnx file exists, only measures the disrepancies.",
+    )
     return parser
 
 
@@ -532,4 +558,5 @@ def get_parser() -> ArgumentParser:
         second_input=args.second_input,
         make_zip=args.zip,
         output_folder=args.output_folder,
+        existing_onnx=args.existing_onnx,
     )