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https://github.com/luxfi/onnx-source-snapshot.git
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40 lines
1.2 KiB
Python
40 lines
1.2 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 LeakyRelu(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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"LeakyRelu", inputs=["x"], outputs=["y"], alpha=0.1
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)
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x = np.array([-1, 0, 1]).astype(np.float32)
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# expected output [-0.1, 0., 1.]
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y = np.clip(x, 0, np.inf) + np.clip(x, -np.inf, 0) * 0.1
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expect(node, inputs=[x], outputs=[y], name="test_leakyrelu_example")
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x = np.random.randn(3, 4, 5).astype(np.float32)
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y = np.clip(x, 0, np.inf) + np.clip(x, -np.inf, 0) * 0.1
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expect(node, inputs=[x], outputs=[y], name="test_leakyrelu")
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@staticmethod
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def export_leakyrelu_default() -> None:
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default_alpha = 0.01
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node = onnx.helper.make_node(
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"LeakyRelu",
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inputs=["x"],
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outputs=["y"],
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)
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x = np.random.randn(3, 4, 5).astype(np.float32)
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y = np.clip(x, 0, np.inf) + np.clip(x, -np.inf, 0) * default_alpha
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expect(node, inputs=[x], outputs=[y], name="test_leakyrelu_default")
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