Files
zeekayandHanzo Dev f84fe1fd15 snapshot slice 1
Co-authored-by: Hanzo Dev <[email protected]>
2026-07-28 15:29:05 -07:00

59 lines
1.3 KiB
Python

# Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx import helper
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class Upsample(Base):
@staticmethod
def export_nearest() -> None:
node = onnx.helper.make_node(
"Upsample",
inputs=["X", "scales"],
outputs=["Y"],
mode="nearest",
)
data = np.array(
[
[
[
[1, 2],
[3, 4],
]
]
],
dtype=np.float32,
)
scales = np.array([1.0, 1.0, 2.0, 3.0], dtype=np.float32)
output = np.array(
[
[
[
[1, 1, 1, 2, 2, 2],
[1, 1, 1, 2, 2, 2],
[3, 3, 3, 4, 4, 4],
[3, 3, 3, 4, 4, 4],
]
]
],
dtype=np.float32,
)
expect(
node,
inputs=[data, scales],
outputs=[output],
name="test_upsample_nearest",
opset_imports=[helper.make_opsetid("", 9)],
)