# Copyright (c) ONNX Project Contributors # # SPDX-License-Identifier: Apache-2.0 from __future__ import annotations import numpy as np import onnx from onnx.backend.test.case.base import Base from onnx.backend.test.case.node import expect class Or(Base): @staticmethod def export() -> None: node = onnx.helper.make_node( "Or", inputs=["x", "y"], outputs=["or"], ) # 2d x = (np.random.randn(3, 4) > 0).astype(bool) y = (np.random.randn(3, 4) > 0).astype(bool) z = np.logical_or(x, y) expect(node, inputs=[x, y], outputs=[z], name="test_or2d") # 3d x = (np.random.randn(3, 4, 5) > 0).astype(bool) y = (np.random.randn(3, 4, 5) > 0).astype(bool) z = np.logical_or(x, y) expect(node, inputs=[x, y], outputs=[z], name="test_or3d") # 4d x = (np.random.randn(3, 4, 5, 6) > 0).astype(bool) y = (np.random.randn(3, 4, 5, 6) > 0).astype(bool) z = np.logical_or(x, y) expect(node, inputs=[x, y], outputs=[z], name="test_or4d") @staticmethod def export_or_broadcast() -> None: node = onnx.helper.make_node( "Or", inputs=["x", "y"], outputs=["or"], ) # 3d vs 1d x = (np.random.randn(3, 4, 5) > 0).astype(bool) y = (np.random.randn(5) > 0).astype(bool) z = np.logical_or(x, y) expect(node, inputs=[x, y], outputs=[z], name="test_or_bcast3v1d") # 3d vs 2d x = (np.random.randn(3, 4, 5) > 0).astype(bool) y = (np.random.randn(4, 5) > 0).astype(bool) z = np.logical_or(x, y) expect(node, inputs=[x, y], outputs=[z], name="test_or_bcast3v2d") # 4d vs 2d x = (np.random.randn(3, 4, 5, 6) > 0).astype(bool) y = (np.random.randn(5, 6) > 0).astype(bool) z = np.logical_or(x, y) expect(node, inputs=[x, y], outputs=[z], name="test_or_bcast4v2d") # 4d vs 3d x = (np.random.randn(3, 4, 5, 6) > 0).astype(bool) y = (np.random.randn(4, 5, 6) > 0).astype(bool) z = np.logical_or(x, y) expect(node, inputs=[x, y], outputs=[z], name="test_or_bcast4v3d") # 4d vs 4d x = (np.random.randn(1, 4, 1, 6) > 0).astype(bool) y = (np.random.randn(3, 1, 5, 6) > 0).astype(bool) z = np.logical_or(x, y) expect(node, inputs=[x, y], outputs=[z], name="test_or_bcast4v4d")