wehub-resource-sync
5cbd3f29e3
Fuzz / Run fuzz harnesses (${{ github.event_name == 'schedule' && 'nightly' || 'smoke' }}) (push) Has been cancelled
Create Releases / call-mac (push) Has been cancelled
Create Releases / call-linux (push) Has been cancelled
Create Releases / call-sdist (push) Has been cancelled
Create Releases / call-win (push) Has been cancelled
Create Releases / call-pyodide (push) Has been cancelled
Windows_No_Exception_CI / build (x64, 3.10) (push) Has been cancelled
Check URLs / build (push) Has been cancelled
Create Releases / Attest CI build artifacts (push) Has been cancelled
Create Releases / Check for Publish release build to pypi (push) Has been cancelled
Create Releases / Check for Publish preview build to test.pypi-weekly (push) Has been cancelled
Create Releases / Publish preview build to test.pypi-weekly (push) Has been cancelled
Create Releases / Check for Publish release build to test.pypi (rc-candidates) (push) Has been cancelled
Create Releases / Publish release build to test.pypi (push) Has been cancelled
Create Releases / Check for Publish preview build to pypi-weekly (push) Has been cancelled
Create Releases / Publish preview build to pypi-weekly (push) Has been cancelled
Create Releases / Publish release build to pypi (push) Has been cancelled
Create Releases / test source distribution (push) Has been cancelled
clang-tidy / clang-tidy (push) Has been cancelled
Lint / Validate SBOM (push) Has been cancelled
Lint / Enforce style (push) Has been cancelled
CI / Test windows-2022, 3.14, External, debug=0, unity_build=0, onnx_ml=1, autogen=0 (push) Has been cancelled
CI / Test windows-latest, 3.10, Internal, debug=0, unity_build=0, onnx_ml=1, autogen=0 (push) Has been cancelled
CI / Test windows-latest, 3.14, Internal, debug=0, unity_build=0, onnx_ml=1, autogen=0 (push) Has been cancelled
CI / Test windows-latest, 3.14t, Internal, debug=0, unity_build=0, onnx_ml=1, autogen=0 (push) Has been cancelled
CI / Test ubuntu-24.04, 3.14, Internal, debug=1, unity_build=0, onnx_ml=1, autogen=0 (push) Has been cancelled
CI / Test ubuntu-24.04, 3.14, External, debug=0, unity_build=1, onnx_ml=1, autogen=1 (push) Has been cancelled
CI / Test ubuntu-24.04, 3.14, External, debug=0, unity_build=0, onnx_ml=0, autogen=0 (push) Has been cancelled
CI / Test macos-latest, 3.10, Internal, debug=0, unity_build=0, onnx_ml=1, autogen=0 (push) Has been cancelled
CI / Test macos-latest, 3.14, Internal, debug=0, unity_build=0, onnx_ml=1, autogen=0 (push) Has been cancelled
CI / Test macos-latest, 3.14t, Internal, debug=0, unity_build=0, onnx_ml=1, autogen=0 (push) Has been cancelled
CI / Test ubuntu-24.04, 3.14, External, debug=0, unity_build=0, onnx_ml=1, autogen=0 (push) Has been cancelled
CI / Test ubuntu-24.04, 3.10, Internal, debug=0, unity_build=0, onnx_ml=1, autogen=0 (push) Has been cancelled
CI / Test ubuntu-24.04, 3.14, Internal, debug=0, unity_build=0, onnx_ml=1, autogen=0 (push) Has been cancelled
CI / Test ubuntu-24.04, 3.14t, Internal, debug=0, unity_build=0, onnx_ml=1, autogen=0 (push) Has been cancelled
Pixi CI / Install and lint (ubuntu-24.04-arm) (push) Has been cancelled
Pixi CI / Install and lint (windows-2022) (push) Has been cancelled
Pixi CI / Xcode generator build (push) Has been cancelled
Pixi CI / Install and test (macos-latest, default) (push) Has been cancelled
Pixi CI / Install and test (ubuntu-24.04-arm, default) (push) Has been cancelled
Pixi CI / Install and test (ubuntu-latest, default) (push) Has been cancelled
Pixi CI / Install and test (windows-2022, default) (push) Has been cancelled
Pixi CI / Install and test (macos-latest, oldies) (push) Has been cancelled
Pixi CI / Install and test (ubuntu-24.04-arm, oldies) (push) Has been cancelled
Pixi CI / Install and test (ubuntu-latest, oldies) (push) Has been cancelled
Pixi CI / Install and test (windows-2022, oldies) (push) Has been cancelled
CodeQL / Analyze (actions) (push) Has been cancelled
CodeQL / Analyze (cpp) (push) Has been cancelled
CodeQL / Analyze (python) (push) Has been cancelled
Copilot Setup Steps / copilot-setup-steps (push) Has been cancelled
Generate and publish ONNX docs / build (push) Has been cancelled
Generate and publish ONNX docs / deploy (push) Has been cancelled
Scorecard supply-chain security / Scorecard analysis (push) Has been cancelled
350 lines
11 KiB
Python
350 lines
11 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 Col2Im(Base):
|
|
"""Col2Im operator with N-dimension support
|
|
|
|
The tests below can be reproduced in Python using https://github.com/f-dangel/unfoldNd/
|
|
"""
|
|
|
|
@staticmethod
|
|
def export() -> None:
|
|
input = np.array(
|
|
[
|
|
[
|
|
[1.0, 6.0, 11.0, 16.0, 21.0], # (1, 5, 5)
|
|
[2.0, 7.0, 12.0, 17.0, 22.0],
|
|
[3.0, 8.0, 13.0, 18.0, 23.0],
|
|
[4.0, 9.0, 14.0, 19.0, 24.0],
|
|
[5.0, 0.0, 15.0, 20.0, 25.0],
|
|
]
|
|
]
|
|
).astype(np.float32)
|
|
|
|
image_shape = np.array([5, 5]).astype(np.int64)
|
|
block_shape = np.array([1, 5]).astype(np.int64)
|
|
node = onnx.helper.make_node(
|
|
"Col2Im", ["input", "image_shape", "block_shape"], ["output"]
|
|
)
|
|
|
|
output = np.array(
|
|
[
|
|
[
|
|
[
|
|
[1.0, 2.0, 3.0, 4.0, 5.0], # (1, 1, 5, 5)
|
|
[6.0, 7.0, 8.0, 9.0, 0.0],
|
|
[11.0, 12.0, 13.0, 14.0, 15.0],
|
|
[16.0, 17.0, 18.0, 19.0, 20.0],
|
|
[21.0, 22.0, 23.0, 24.0, 25.0],
|
|
]
|
|
]
|
|
]
|
|
).astype(np.float32)
|
|
|
|
expect(
|
|
node,
|
|
inputs=[input, image_shape, block_shape],
|
|
outputs=[output],
|
|
name="test_col2im",
|
|
)
|
|
|
|
@staticmethod
|
|
def export_col2im_strides() -> None:
|
|
input = np.array(
|
|
[
|
|
[
|
|
[0.0, 0.0, 0.0, 0.0], # (1, 9, 4)
|
|
[1.0, 1.0, 1.0, 1.0],
|
|
[1.0, 1.0, 1.0, 1.0],
|
|
[1.0, 1.0, 1.0, 1.0],
|
|
[0.0, 0.0, 0.0, 0.0],
|
|
[0.0, 0.0, 0.0, 0.0],
|
|
[0.0, 0.0, 0.0, 0.0],
|
|
[1.0, 1.0, 1.0, 1.0],
|
|
[0.0, 0.0, 0.0, 0.0],
|
|
]
|
|
]
|
|
).astype(np.float32)
|
|
image_shape = np.array([5, 5]).astype(np.int64)
|
|
block_shape = np.array([3, 3]).astype(np.int64)
|
|
|
|
output = np.array(
|
|
[
|
|
[
|
|
[
|
|
[0.0, 1.0, 1.0, 1.0, 1.0], # (1, 1, 5, 5)
|
|
[1.0, 0.0, 1.0, 0.0, 0.0],
|
|
[0.0, 2.0, 1.0, 2.0, 1.0],
|
|
[1.0, 0.0, 1.0, 0.0, 0.0],
|
|
[0.0, 1.0, 0.0, 1.0, 0.0],
|
|
]
|
|
]
|
|
]
|
|
).astype(np.float32)
|
|
|
|
node = onnx.helper.make_node(
|
|
"Col2Im",
|
|
["input", "image_shape", "block_shape"],
|
|
["output"],
|
|
strides=[2, 2],
|
|
)
|
|
expect(
|
|
node,
|
|
inputs=[input, image_shape, block_shape],
|
|
outputs=[output],
|
|
name="test_col2im_strides",
|
|
)
|
|
|
|
@staticmethod
|
|
def export_col2im_pads() -> None:
|
|
input = np.array(
|
|
[
|
|
[
|
|
[
|
|
1.0,
|
|
6.0,
|
|
11.0,
|
|
16.0,
|
|
21.0,
|
|
26,
|
|
31,
|
|
36,
|
|
41,
|
|
46,
|
|
51,
|
|
56,
|
|
61,
|
|
66,
|
|
71,
|
|
], # (1, 5, 15)
|
|
[
|
|
2.0,
|
|
7.0,
|
|
12.0,
|
|
17.0,
|
|
22.0,
|
|
27,
|
|
32,
|
|
37,
|
|
42,
|
|
47,
|
|
52,
|
|
57,
|
|
62,
|
|
67,
|
|
72,
|
|
],
|
|
[
|
|
3.0,
|
|
8.0,
|
|
13.0,
|
|
18.0,
|
|
23.0,
|
|
28,
|
|
33,
|
|
38,
|
|
43,
|
|
48,
|
|
53,
|
|
58,
|
|
63,
|
|
68,
|
|
73,
|
|
],
|
|
[
|
|
4.0,
|
|
9.0,
|
|
14.0,
|
|
19.0,
|
|
24.0,
|
|
29,
|
|
34,
|
|
39,
|
|
44,
|
|
49,
|
|
54,
|
|
59,
|
|
64,
|
|
69,
|
|
74,
|
|
],
|
|
[
|
|
5.0,
|
|
10.0,
|
|
15.0,
|
|
20.0,
|
|
25.0,
|
|
30,
|
|
35,
|
|
40,
|
|
45,
|
|
50,
|
|
55,
|
|
60,
|
|
65,
|
|
70,
|
|
75,
|
|
],
|
|
]
|
|
]
|
|
).astype(np.float32)
|
|
image_shape = np.array([5, 5]).astype(np.int64)
|
|
block_shape = np.array([1, 5]).astype(np.int64)
|
|
|
|
output = np.array(
|
|
[
|
|
[
|
|
[
|
|
[8.0, 21.0, 24.0, 27.0, 24.0], # (1, 1, 5, 5)
|
|
[38.0, 66.0, 69.0, 72.0, 54.0],
|
|
[68.0, 111.0, 114.0, 117.0, 84.0],
|
|
[98.0, 156.0, 159.0, 162.0, 114.0],
|
|
[128.0, 201.0, 204.0, 207.0, 144.0],
|
|
]
|
|
]
|
|
]
|
|
).astype(np.float32)
|
|
|
|
node = onnx.helper.make_node(
|
|
"Col2Im",
|
|
["input", "image_shape", "block_shape"],
|
|
["output"],
|
|
pads=[0, 1, 0, 1],
|
|
)
|
|
expect(
|
|
node,
|
|
inputs=[input, image_shape, block_shape],
|
|
outputs=[output],
|
|
name="test_col2im_pads",
|
|
)
|
|
|
|
@staticmethod
|
|
def export_col2im_dilations() -> None:
|
|
input = np.array(
|
|
[
|
|
[
|
|
[1.0, 5.0, 9.0, 13.0, 17], # (1, 4, 5)
|
|
[2.0, 6.0, 10.0, 14.0, 18],
|
|
[3.0, 7.0, 11.0, 15.0, 19],
|
|
[4.0, 8.0, 12.0, 16.0, 20],
|
|
]
|
|
]
|
|
).astype(np.float32)
|
|
image_shape = np.array([6, 6]).astype(np.int64)
|
|
block_shape = np.array([2, 2]).astype(np.int64)
|
|
|
|
output = np.array(
|
|
[
|
|
[
|
|
[
|
|
[1.0, 0.0, 0.0, 0.0, 0.0, 2.0], # (1, 1, 6, 6)
|
|
[8.0, 0.0, 0.0, 0.0, 0.0, 10.0],
|
|
[16.0, 0.0, 0.0, 0.0, 0.0, 18.0],
|
|
[24.0, 0.0, 0.0, 0.0, 0.0, 26.0],
|
|
[32.0, 0.0, 0.0, 0.0, 0.0, 34.0],
|
|
[19.0, 0.0, 0.0, 0.0, 0.0, 20.0],
|
|
]
|
|
]
|
|
]
|
|
).astype(np.float32)
|
|
|
|
node = onnx.helper.make_node(
|
|
"Col2Im",
|
|
["input", "image_shape", "block_shape"],
|
|
["output"],
|
|
dilations=[1, 5],
|
|
)
|
|
expect(
|
|
node,
|
|
inputs=[input, image_shape, block_shape],
|
|
outputs=[output],
|
|
name="test_col2im_dilations",
|
|
)
|
|
|
|
@staticmethod
|
|
def export_col2im_5d() -> None:
|
|
input = np.array(
|
|
[
|
|
[
|
|
[1, 6, 11, 16, 21, 26, 31, 36, 41, 46, 51, 56], # (1, 10, 12)
|
|
[2, 7, 12, 17, 22, 27, 32, 37, 42, 47, 52, 57],
|
|
[3, 8, 13, 18, 23, 28, 33, 38, 43, 48, 53, 58],
|
|
[4, 9, 14, 19, 24, 29, 34, 39, 44, 49, 54, 59],
|
|
[5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60],
|
|
[61, 66, 71, 76, 81, 86, 91, 96, 101, 106, 111, 116],
|
|
[62, 67, 72, 77, 82, 87, 92, 97, 102, 107, 112, 117],
|
|
[63, 68, 73, 78, 83, 88, 93, 98, 103, 108, 113, 118],
|
|
[64, 69, 74, 79, 84, 89, 94, 99, 104, 109, 114, 119],
|
|
[65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120],
|
|
]
|
|
]
|
|
).astype(np.float32)
|
|
image_shape = np.array([3, 4, 5]).astype(np.int64)
|
|
block_shape = np.array([1, 1, 5]).astype(np.int64)
|
|
|
|
output = np.array(
|
|
[
|
|
[
|
|
[
|
|
[
|
|
[1, 2, 3, 4, 5], # (1, 2, 3, 4, 5)
|
|
[6, 7, 8, 9, 10],
|
|
[11, 12, 13, 14, 15],
|
|
[16, 17, 18, 19, 20],
|
|
],
|
|
[
|
|
[21, 22, 23, 24, 25],
|
|
[26, 27, 28, 29, 30],
|
|
[31, 32, 33, 34, 35],
|
|
[36, 37, 38, 39, 40],
|
|
],
|
|
[
|
|
[41, 42, 43, 44, 45],
|
|
[46, 47, 48, 49, 50],
|
|
[51, 52, 53, 54, 55],
|
|
[56, 57, 58, 59, 60],
|
|
],
|
|
],
|
|
[
|
|
[
|
|
[61, 62, 63, 64, 65],
|
|
[66, 67, 68, 69, 70],
|
|
[71, 72, 73, 74, 75],
|
|
[76, 77, 78, 79, 80],
|
|
],
|
|
[
|
|
[81, 82, 83, 84, 85],
|
|
[86, 87, 88, 89, 90],
|
|
[91, 92, 93, 94, 95],
|
|
[96, 97, 98, 99, 100],
|
|
],
|
|
[
|
|
[101, 102, 103, 104, 105],
|
|
[106, 107, 108, 109, 110],
|
|
[111, 112, 113, 114, 115],
|
|
[116, 117, 118, 119, 120],
|
|
],
|
|
],
|
|
]
|
|
]
|
|
).astype(np.float32)
|
|
|
|
node = onnx.helper.make_node(
|
|
"Col2Im", ["input", "image_shape", "block_shape"], ["output"]
|
|
)
|
|
expect(
|
|
node,
|
|
inputs=[input, image_shape, block_shape],
|
|
outputs=[output],
|
|
name="test_col2im_5d",
|
|
)
|