chore: import upstream snapshot with attribution

2026-07-13 13:36:55 +08:00
commit c8a779b1bb
1887 changed files with 3245738 additions and 0 deletions
@@ -0,0 +1,107 @@
+#
+# SPDX-FileCopyrightText: Copyright (c) 1993-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import onnx_graphsurgeon as gs
+import onnx
+import numpy as np
+import json
+
+import sys, os
+
+sys.path.insert(1, os.path.join(sys.path[0], os.path.pardir))
+from downloader import getFilePath
+
+
+def drop_category_mapper_nodes(graph):
+    new_inputs = []
+    for org_input in graph.inputs:
+        # head node, simply disconnect it with others
+        assert len(org_input.outputs) == 1
+        category_mapper_node = org_input.outputs[0]
+        assert category_mapper_node.op == "CategoryMapper"
+        assert len(category_mapper_node.outputs) == 1
+        new_inputs.append(category_mapper_node.outputs[0])
+        category_mapper_node.inputs.clear()
+        category_mapper_node.outputs.clear()
+
+        # Save mapping info to preprocess inputs.
+        with open(category_mapper_node.name + ".json", "w") as fp:
+            json.dump(category_mapper_node.attrs, fp)
+
+    graph.inputs = new_inputs
+
+
+def replace_unsupported_ops(graph):
+    # replace hardmax with ArgMax
+    hardmaxes = [node for node in graph.nodes if node.op == "Hardmax"]
+    assert len(hardmaxes) == 1
+    hardmax = hardmaxes[0]
+    hardmax.op = "ArgMax"
+    hardmax.name = "ArgMax(org:" + hardmax.name + ")"
+    hardmax.attrs["axis"] = 1
+    hardmax.attrs["keepdims"] = 0
+
+    cast = hardmax.o()
+    reshape = cast.o()
+
+    hardmax.outputs = reshape.outputs
+    assert len(hardmax.outputs) == 1
+    hardmax.outputs[0].dtype = np.int64
+    hardmax.outputs[0].shape = [1]
+
+    compress = reshape.o()
+    compress.op = "Gather"
+    compress.name = "Gather(org:" + compress.name + ")"
+    compress.attrs["axis"] = 1
+
+    cast.outputs.clear()
+    reshape.outputs.clear()
+    # Remove the node from the graph completely
+    graph.cleanup().toposort()
+
+
+def save_weights_for_refitting(graph):
+    # Save weights for refitting
+    tmap = graph.tensors()
+    np.save("Parameter576_B_0.npy", tmap["Parameter576_B_0"].values)
+    np.save("W_0.npy", tmap["W_0"].values)
+
+
+def main():
+    org_model_file_path = getFilePath(
+        "samples/python/engine_refit_onnx_bidaf/bidaf-original.onnx"
+    )
+
+    print("Modifying the ONNX model ...")
+    original_model = onnx.load(org_model_file_path)
+    graph = gs.import_onnx(original_model)
+
+    drop_category_mapper_nodes(graph)
+    replace_unsupported_ops(graph)
+    save_weights_for_refitting(graph)
+
+    new_model = gs.export_onnx(graph)
+
+    modified_model_name = "bidaf-modified.onnx"
+    onnx.checker.check_model(new_model)
+    onnx.save(new_model, modified_model_name)
+    print("Modified ONNX model saved as {}".format(modified_model_name))
+    print("Done.")
+
+
+if __name__ == "__main__":
+    main()