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

37 lines
1.1 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.model import expect
class SingleRelu(Base):
@staticmethod
def export() -> None:
node = onnx.helper.make_node("Relu", ["x"], ["y"], name="test")
graph = onnx.helper.make_graph(
nodes=[node],
name="SingleRelu",
inputs=[
onnx.helper.make_tensor_value_info("x", onnx.TensorProto.FLOAT, [1, 2])
],
outputs=[
onnx.helper.make_tensor_value_info("y", onnx.TensorProto.FLOAT, [1, 2])
],
)
model = onnx.helper.make_model_gen_version(
graph,
producer_name="backend-test",
opset_imports=[onnx.helper.make_opsetid("", 9)],
)
x = np.random.randn(1, 2).astype(np.float32)
y = np.maximum(x, 0)
expect(model, inputs=[x], outputs=[y], name="test_single_relu_model")