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chore: import upstream snapshot with attribution
2026-07-13 12:41:19 +08:00

81 行
2.1 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.node import expect
class SplitToSequence(Base):
@staticmethod
def export_with_split_1() -> None:
data = np.arange(18).reshape((3, 6)).astype(np.float32)
split = np.array(2, dtype=np.int64)
node = onnx.helper.make_node(
"SplitToSequence", ["data", "split"], ["seq"], axis=1
)
expected_outputs = [
[
np.array([[0.0, 1.0], [6.0, 7.0], [12.0, 13.0]], dtype=np.float32),
np.array([[2.0, 3.0], [8.0, 9.0], [14.0, 15.0]], dtype=np.float32),
np.array([[4.0, 5.0], [10.0, 11.0], [16.0, 17.0]], dtype=np.float32),
]
]
expect(
node,
inputs=[data, split],
outputs=expected_outputs,
name="test_split_to_sequence_1",
)
@staticmethod
def export_with_split_2() -> None:
data = np.arange(18).reshape((3, 6)).astype(np.float32)
split = np.array([1, 2], dtype=np.int64)
node = onnx.helper.make_node(
"SplitToSequence", ["data", "split"], ["seq"], axis=0
)
expected_outputs = [
[
data[:1],
data[1:],
]
]
expect(
node,
inputs=[data, split],
outputs=expected_outputs,
name="test_split_to_sequence_2",
)
@staticmethod
def export_nokeepdims() -> None:
data = np.arange(18).reshape((3, 6)).astype(np.float32)
node = onnx.helper.make_node(
"SplitToSequence",
["data"],
["seq"],
axis=1,
keepdims=0,
)
expected_outputs = [[data[:, i] for i in range(data.shape[1])]]
expect(
node,
inputs=[data],
outputs=expected_outputs,
name="test_split_to_sequence_nokeepdims",
)