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https://github.com/luxfi/onnx-source-snapshot.git
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43 lines
1.2 KiB
Python
43 lines
1.2 KiB
Python
# Copyright (c) ONNX Project Contributors
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# SPDX-License-Identifier: Apache-2.0
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from __future__ import annotations
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import numpy as np
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import onnx
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from onnx.backend.test.case.base import Base
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from onnx.backend.test.case.model import expect
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class ShrinkTest(Base):
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@staticmethod
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def export() -> None:
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node = onnx.helper.make_node(
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"Shrink",
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["x"],
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["y"],
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lambd=1.5,
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bias=1.5,
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)
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graph = onnx.helper.make_graph(
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nodes=[node],
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name="Shrink",
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inputs=[
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onnx.helper.make_tensor_value_info("x", onnx.TensorProto.FLOAT, [5])
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],
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outputs=[
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onnx.helper.make_tensor_value_info("y", onnx.TensorProto.FLOAT, [5])
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],
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)
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model = onnx.helper.make_model_gen_version(
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graph,
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producer_name="backend-test",
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opset_imports=[onnx.helper.make_opsetid("", 10)],
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)
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x = np.array([-2.0, -1.0, 0.0, 1.0, 2.0], dtype=np.float32)
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y = np.array([-0.5, 0.0, 0.0, 0.0, 0.5], dtype=np.float32)
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expect(model, inputs=[x], outputs=[y], name="test_shrink")
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