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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 Add(Base):
@staticmethod
def export() -> None:
node = onnx.helper.make_node(
"Add",
inputs=["x", "y"],
outputs=["sum"],
)
x = np.random.randn(3, 4, 5).astype(np.float32)
y = np.random.randn(3, 4, 5).astype(np.float32)
expect(node, inputs=[x, y], outputs=[x + y], name="test_add")
@staticmethod
def export_add_uint8() -> None:
node = onnx.helper.make_node(
"Add",
inputs=["x", "y"],
outputs=["sum"],
)
x = np.random.randint(24, size=(3, 4, 5), dtype=np.uint8)
y = np.random.randint(24, size=(3, 4, 5), dtype=np.uint8)
expect(node, inputs=[x, y], outputs=[x + y], name="test_add_uint8")
@staticmethod
def export_add_broadcast() -> None:
node = onnx.helper.make_node(
"Add",
inputs=["x", "y"],
outputs=["sum"],
)
x = np.random.randn(3, 4, 5).astype(np.float32)
y = np.random.randn(5).astype(np.float32)
expect(node, inputs=[x, y], outputs=[x + y], name="test_add_bcast")
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