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

48 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.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class Sum(Base):
@staticmethod
def export() -> None:
data_0 = np.array([3, 0, 2]).astype(np.float32)
data_1 = np.array([1, 3, 4]).astype(np.float32)
data_2 = np.array([2, 6, 6]).astype(np.float32)
result = np.array([6, 9, 12]).astype(np.float32)
node = onnx.helper.make_node(
"Sum",
inputs=["data_0", "data_1", "data_2"],
outputs=["result"],
)
expect(
node,
inputs=[data_0, data_1, data_2],
outputs=[result],
name="test_sum_example",
)
node = onnx.helper.make_node(
"Sum",
inputs=["data_0"],
outputs=["result"],
)
expect(node, inputs=[data_0], outputs=[data_0], name="test_sum_one_input")
result = np.add(data_0, data_1)
node = onnx.helper.make_node(
"Sum",
inputs=["data_0", "data_1"],
outputs=["result"],
)
expect(
node, inputs=[data_0, data_1], outputs=[result], name="test_sum_two_inputs"
)