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https://github.com/luxfi/onnx-source-snapshot.git
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63 lines
1.3 KiB
Python
63 lines
1.3 KiB
Python
# Copyright (c) ONNX Project Contributors
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#
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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.node import expect
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class Round(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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"Round",
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inputs=["x"],
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outputs=["y"],
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)
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x = np.array(
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[
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0.1,
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0.5,
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0.9,
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1.2,
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1.5,
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1.8,
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2.3,
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2.5,
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2.7,
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-1.1,
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-1.5,
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-1.9,
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-2.2,
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-2.5,
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-2.8,
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]
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).astype(np.float32)
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# expected output
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y = np.array(
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[
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0.0,
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0.0,
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1.0,
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1.0,
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2.0,
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2.0,
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2.0,
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2.0,
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3.0,
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-1.0,
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-2.0,
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-2.0,
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-2.0,
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-2.0,
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-3.0,
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]
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).astype(np.float32)
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expect(node, inputs=[x], outputs=[y], name="test_round")
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