chore: import upstream snapshot with attribution

samples/sampleNamedDimensions/create_model.py

@@ -0,0 +1,35 @@
+#
+# SPDX-FileCopyrightText: Copyright (c) 1993-2024 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 numpy as np
+import onnx
+import onnx_graphsurgeon as gs
+
+def main():
+    input0 = gs.Variable(name="input0", dtype=np.float32, shape=('n_rows', 8))
+    input1 = gs.Variable(name="input1", dtype=np.float32, shape=('n_rows', 8))
+    output = gs.Variable(name="output", dtype=np.float32, )
+
+    node = gs.Node(op="Concat", inputs=[input0, input1], outputs=[output], attrs={"axis": 0})
+
+    graph = gs.Graph(nodes=[node], inputs=[input0, input1], outputs=[output])
+
+    model = gs.export_onnx(graph)
+    onnx.save(model, "concat_layer.onnx")
+
+if __name__ == '__main__':
+    main()