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

67 lines
2.0 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
from onnx.backend.test.case.utils import all_numeric_dtypes
class Max(Base):
@staticmethod
def export() -> None:
data_0 = np.array([3, 2, 1]).astype(np.float32)
data_1 = np.array([1, 4, 4]).astype(np.float32)
data_2 = np.array([2, 5, 3]).astype(np.float32)
result = np.array([3, 5, 4]).astype(np.float32)
node = onnx.helper.make_node(
"Max",
inputs=["data_0", "data_1", "data_2"],
outputs=["result"],
)
expect(
node,
inputs=[data_0, data_1, data_2],
outputs=[result],
name="test_max_example",
)
node = onnx.helper.make_node(
"Max",
inputs=["data_0"],
outputs=["result"],
)
expect(node, inputs=[data_0], outputs=[data_0], name="test_max_one_input")
result = np.maximum(data_0, data_1)
node = onnx.helper.make_node(
"Max",
inputs=["data_0", "data_1"],
outputs=["result"],
)
expect(
node, inputs=[data_0, data_1], outputs=[result], name="test_max_two_inputs"
)
@staticmethod
def export_max_all_numeric_types() -> None:
for op_dtype in all_numeric_dtypes:
data_0 = np.array([3, 2, 1]).astype(op_dtype)
data_1 = np.array([1, 4, 4]).astype(op_dtype)
result = np.array([3, 4, 4]).astype(op_dtype)
node = onnx.helper.make_node(
"Max",
inputs=["data_0", "data_1"],
outputs=["result"],
)
expect(
node,
inputs=[data_0, data_1],
outputs=[result],
name=f"test_max_{np.dtype(op_dtype).name}",
)