wehub-resource-sync
50 lines
1.9 KiB
Python
50 lines
1.9 KiB
Python
#!/usr/bin/env python3
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#
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# SPDX-FileCopyrightText: Copyright (c) 1993-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import onnx_graphsurgeon as gs
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import numpy as np
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import onnx
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graph = gs.import_onnx(onnx.load("model.onnx"))
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# 1. Remove the `b` input of the add node
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first_add = [node for node in graph.nodes if node.op == "Add"][0]
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first_add.inputs = [inp for inp in first_add.inputs if inp.name != "b"]
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# 2. Change the Add to a LeakyRelu
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first_add.op = "LeakyRelu"
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first_add.attrs["alpha"] = 0.02
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# 3. Add an identity after the add node
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identity_out = gs.Variable("identity_out", dtype=np.float32)
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identity = gs.Node(op="Identity", inputs=first_add.outputs, outputs=[identity_out])
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graph.nodes.append(identity)
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# 4. Modify the graph output to be the identity output
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graph.outputs = [identity_out]
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# 5. Remove unused nodes/tensors, and topologically sort the graph
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# ONNX requires nodes to be topologically sorted to be considered valid.
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# Therefore, you should only need to sort the graph when you have added new nodes out-of-order.
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# In this case, the identity node is already in the correct spot (it is the last node,
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# and was appended to the end of the list), but to be on the safer side, we can sort anyway.
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graph.cleanup(remove_unused_graph_inputs=True).toposort()
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model = onnx.shape_inference.infer_shapes(gs.export_onnx(graph))
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onnx.save(model, "modified.onnx")
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