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# Copyright (c) ONNX Project Contributors | |
# | |
# SPDX-License-Identifier: Apache-2.0 | |
import numpy as np | |
import onnx | |
from onnx.backend.test.case.base import Base | |
from onnx.backend.test.case.node import expect | |
class And(Base): | |
def export() -> None: | |
node = onnx.helper.make_node( | |
"And", | |
inputs=["x", "y"], | |
outputs=["and"], | |
) | |
# 2d | |
x = (np.random.randn(3, 4) > 0).astype(bool) | |
y = (np.random.randn(3, 4) > 0).astype(bool) | |
z = np.logical_and(x, y) | |
expect(node, inputs=[x, y], outputs=[z], name="test_and2d") | |
# 3d | |
x = (np.random.randn(3, 4, 5) > 0).astype(bool) | |
y = (np.random.randn(3, 4, 5) > 0).astype(bool) | |
z = np.logical_and(x, y) | |
expect(node, inputs=[x, y], outputs=[z], name="test_and3d") | |
# 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_and(x, y) | |
expect(node, inputs=[x, y], outputs=[z], name="test_and4d") | |
def export_and_broadcast() -> None: | |
node = onnx.helper.make_node( | |
"And", | |
inputs=["x", "y"], | |
outputs=["and"], | |
) | |
# 3d vs 1d | |
x = (np.random.randn(3, 4, 5) > 0).astype(bool) | |
y = (np.random.randn(5) > 0).astype(bool) | |
z = np.logical_and(x, y) | |
expect(node, inputs=[x, y], outputs=[z], name="test_and_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_and(x, y) | |
expect(node, inputs=[x, y], outputs=[z], name="test_and_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_and(x, y) | |
expect(node, inputs=[x, y], outputs=[z], name="test_and_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_and(x, y) | |
expect(node, inputs=[x, y], outputs=[z], name="test_and_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_and(x, y) | |
expect(node, inputs=[x, y], outputs=[z], name="test_and_bcast4v4d") | |