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31 lines
853 B
Python
31 lines
853 B
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 Sigmoid(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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"Sigmoid",
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inputs=["x"],
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outputs=["y"],
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)
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x = np.array([-1, 0, 1]).astype(np.float32)
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y = 1.0 / (
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1.0 + np.exp(np.negative(x))
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) # expected output [0.26894143, 0.5, 0.7310586]
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expect(node, inputs=[x], outputs=[y], name="test_sigmoid_example")
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x = np.random.randn(3, 4, 5).astype(np.float32)
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y = 1.0 / (1.0 + np.exp(np.negative(x)))
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expect(node, inputs=[x], outputs=[y], name="test_sigmoid")
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