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https://github.com/luxfi/onnx-source-snapshot.git
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38 lines
1.0 KiB
Python
38 lines
1.0 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 Shrink(Base):
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@staticmethod
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def export_hard_shrink() -> None:
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node = onnx.helper.make_node(
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"Shrink",
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inputs=["x"],
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outputs=["y"],
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lambd=1.5,
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)
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X = np.arange(-2.0, 2.1, dtype=np.float32)
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Y = np.array([-2, 0, 0, 0, 2], dtype=np.float32)
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expect(node, inputs=[X], outputs=[Y], name="test_shrink_hard")
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@staticmethod
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def export_soft_shrink() -> None:
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node = onnx.helper.make_node(
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"Shrink",
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inputs=["x"],
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outputs=["y"],
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lambd=1.5,
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bias=1.5,
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)
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X = np.arange(-2.0, 2.1, dtype=np.float32)
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Y = np.array([-0.5, 0, 0, 0, 0.5], dtype=np.float32)
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expect(node, inputs=[X], outputs=[Y], name="test_shrink_soft")
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