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39 lines
1.1 KiB
Python
39 lines
1.1 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 Tile(Base):
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@staticmethod
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def export_tile() -> None:
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node = onnx.helper.make_node("Tile", inputs=["x", "y"], outputs=["z"])
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x = np.random.rand(2, 3, 4, 5).astype(np.float32)
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repeats = np.random.randint(low=1, high=10, size=(np.ndim(x),)).astype(np.int64)
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z = np.tile(x, repeats)
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expect(node, inputs=[x, repeats], outputs=[z], name="test_tile")
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@staticmethod
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def export_tile_precomputed() -> None:
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node = onnx.helper.make_node("Tile", inputs=["x", "y"], outputs=["z"])
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x = np.array([[0, 1], [2, 3]], dtype=np.float32)
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repeats = np.array([2, 2], dtype=np.int64)
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z = np.array(
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[[0, 1, 0, 1], [2, 3, 2, 3], [0, 1, 0, 1], [2, 3, 2, 3]], dtype=np.float32
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)
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expect(node, inputs=[x, repeats], outputs=[z], name="test_tile_precomputed")
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