Add#
Domain:
ai.onnxSince version: 14
Performs element-wise binary addition (with Numpy-style broadcasting support).
This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check the broadcasting behavior in ONNX.
Inputs
A (T): First operand.
B (T): Second operand.
Outputs
C (T): Result, has same element type as two inputs
Type Constraints
T: Constrain input and output types to all numeric tensors. Allowed types: tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8).
Examples#
test_add
Node:
Add(x, y) -> (sum)
Inputs:
x: shape=(3, 4, 5), dtype=float32
[[[-0.846573 , 1.2833743 , 0.7443729 , -0.53892165, -0.18734488],
[ 0.12178429, -2.0982637 , 1.5225194 , 0.8434675 , 0.33549327],
[ 0.09154005, 0.84206796, -1.6517702 , -0.6042637 , 1.0845611 ],
[ 1.5201056 , 0.99814653, -0.17626205, 1.6406455 , 0.7513234 ]],
[[ 1.7203773 , -1.0786597 , 0.17007604, 0.51496613, 0.2197246 ],
[-1.1963571 , 0.40040365, -1.2112149 , -0.33787218, -1.3460412 ],
[ 0.7294753 , 0.6825587 , -1.2590255 , -2.3378267 , -0.7833349 ],
[ 1.8637013 , -0.9699887 , -1.1392695 , -0.08200161, -1.0864431 ]],
[[-2.0017872 , -1.6769867 , 0.01457232, 0.58369064, 1.4740808 ],
[ 0.33742025, 1.0194283 , -0.9550304 , 1.0498446 , -0.16838181],
[ 0.04257414, 1.3051497 , -1.2076538 , -0.4271947 , -1.4134941 ],
[ 0.7686854 , 1.2206558 , -1.1196595 , -1.1292622 , -0.41522065]]]
y: shape=(3, 4, 5), dtype=float32
[[[-1.233148 , 0.13186626, 0.7939877 , 0.4511548 , 0.17302549],
[-1.5203902 , 0.49947104, -0.45518056, -0.561509 , -0.2619732 ],
[ 0.7643679 , -0.5008771 , -1.6715151 , -1.0876864 , 0.5858355 ],
[ 0.23310411, 0.8712918 , 0.08240927, -0.22854084, 0.3831807 ]],
[[ 2.166861 , 0.8242299 , 0.07636173, 0.1569699 , -0.9098289 ],
[-1.2892655 , 1.7136036 , 0.452536 , -0.3871883 , 0.8681424 ],
[ 0.64394414, -0.11681466, -0.55781925, 1.5857856 , 0.96086985],
[ 0.36460796, -1.7471066 , -0.6675202 , -0.9307984 , -0.81704015]],
[[ 0.04730104, -0.42357075, 0.6734053 , 0.58307636, 1.2070061 ],
[-0.21970329, 0.09768768, -0.29589003, -0.2054249 , 0.8043798 ],
[ 0.6403441 , 0.47908017, -2.3431432 , -0.43361774, -1.4350805 ],
[ 2.3141932 , -0.77084607, 0.03072728, -0.6819856 , 0.3865685 ]]]
Outputs:
sum: shape=(3, 4, 5), dtype=float32
[[[-2.079721 , 1.4152405 , 1.5383606 , -0.08776686, -0.01431939],
[-1.3986058 , -1.5987927 , 1.0673388 , 0.28195846, 0.07352006],
[ 0.8559079 , 0.34119087, -3.3232853 , -1.6919501 , 1.6703966 ],
[ 1.7532097 , 1.8694384 , -0.09385278, 1.4121046 , 1.1345041 ]],
[[ 3.8872385 , -0.25442976, 0.24643777, 0.67193604, -0.6901043 ],
[-2.4856226 , 2.1140072 , -0.7586789 , -0.72506046, -0.47789878],
[ 1.3734195 , 0.56574404, -1.8168447 , -0.7520411 , 0.17753494],
[ 2.2283094 , -2.7170954 , -1.8067896 , -1.0128 , -1.9034832 ]],
[[-1.9544861 , -2.1005573 , 0.6879776 , 1.166767 , 2.681087 ],
[ 0.11771697, 1.117116 , -1.2509204 , 0.8444197 , 0.635998 ],
[ 0.68291825, 1.7842299 , -3.550797 , -0.8608124 , -2.8485746 ],
[ 3.0828786 , 0.44980973, -1.0889323 , -1.8112478 , -0.02865216]]]
test_add_bcast
Node:
Add(x, y) -> (sum)
Inputs:
x: shape=(3, 4, 5), dtype=float32
[[[-1.0009542 , 1.3335403 , 0.51886207, -0.87937015, -0.34444883],
[ 0.7261377 , 0.44689482, -0.11980146, 1.3952885 , 1.7246119 ],
[ 1.1329428 , -0.75994855, 1.0185796 , -1.1640126 , -1.4462589 ],
[ 1.9671117 , -0.78563446, -0.6370028 , -0.6990264 , -0.05147265]],
[[-0.93405545, -1.5452816 , -0.27895346, -0.28968734, 1.3620633 ],
[ 0.25097892, 0.15541512, -0.5576033 , 0.56766975, 0.5894251 ],
[-2.0840185 , -2.129933 , -0.3347914 , 2.2643888 , -0.5795392 ],
[ 1.4404445 , -1.6125345 , -0.38877857, 0.26226655, -0.65531564]],
[[ 0.41839996, -0.17184599, -1.1314857 , -0.20180649, 1.4405026 ],
[-0.71997935, -0.674459 , -0.47517473, -0.01454322, 0.70281273],
[ 0.09478609, -0.51084805, -0.6076167 , 0.76374954, 1.212502 ],
[-0.83932626, 0.27163088, -0.34415314, -0.098693 , -0.49040416]]]
y: shape=(5,), dtype=float32
[ 0.08745956, -1.0263144 , -0.35410684, -0.36685738, -2.0796497 ]
Outputs:
sum: shape=(3, 4, 5), dtype=float32
[[[-0.9134946 , 0.30722594, 0.16475523, -1.2462275 , -2.4240985 ],
[ 0.81359726, -0.57941955, -0.4739083 , 1.028431 , -0.3550378 ],
[ 1.2204024 , -1.786263 , 0.66447276, -1.53087 , -3.5259085 ],
[ 2.0545712 , -1.8119488 , -0.99110967, -1.0658838 , -2.1311224 ]],
[[-0.8465959 , -2.5715961 , -0.63306034, -0.6565447 , -0.7175864 ],
[ 0.33843848, -0.87089926, -0.91171014, 0.20081237, -1.4902246 ],
[-1.9965589 , -3.1562476 , -0.6888982 , 1.8975314 , -2.6591887 ],
[ 1.527904 , -2.6388488 , -0.7428854 , -0.10459083, -2.7349653 ]],
[[ 0.5058595 , -1.1981604 , -1.4855926 , -0.56866384, -0.63914704],
[-0.6325198 , -1.7007734 , -0.82928157, -0.38140061, -1.376837 ],
[ 0.18224566, -1.5371624 , -0.96172357, 0.39689216, -0.8671477 ],
[-0.7518667 , -0.7546835 , -0.69825995, -0.46555036, -2.5700538 ]]]
test_add_int16
Node:
Add(x, y) -> (sum)
Inputs:
x: shape=(3, 4, 5), dtype=int16
[[[ 0, 0, 0, 0, -1],
[ 0, 0, 0, -1, 0],
[ 2, 0, 0, 1, 1],
[ 0, -1, 0, 0, 0]],
[[ 0, 0, 0, 1, 0],
[ 0, -1, 0, -1, 1],
[ 0, -1, 0, 0, -1],
[ 0, 1, -1, -1, 0]],
[[ 0, 1, 1, 0, 0],
[-2, 0, 0, 0, 0],
[ 0, 0, 0, 0, -1],
[-1, 0, 0, 0, 0]]]
y: shape=(3, 4, 5), dtype=int16
[[[ 1, 0, -2, 0, 0],
[ 1, 1, 1, 0, 0],
[ 0, -1, 0, 0, -1],
[-1, 0, 0, 0, 0]],
[[ 0, 0, 0, 1, 1],
[ 0, 0, -2, 0, 0],
[-1, 0, 0, 0, 0],
[ 0, -1, 0, 0, 1]],
[[ 0, 0, 1, 0, 0],
[ 0, -1, 0, 0, 1],
[ 1, 0, -1, 0, 0],
[ 0, -1, 0, 0, 0]]]
Outputs:
sum: shape=(3, 4, 5), dtype=int16
[[[ 1, 0, -2, 0, -1],
[ 1, 1, 1, -1, 0],
[ 2, -1, 0, 1, 0],
[-1, -1, 0, 0, 0]],
[[ 0, 0, 0, 2, 1],
[ 0, -1, -2, -1, 1],
[-1, -1, 0, 0, -1],
[ 0, 0, -1, -1, 1]],
[[ 0, 1, 2, 0, 0],
[-2, -1, 0, 0, 1],
[ 1, 0, -1, 0, -1],
[-1, -1, 0, 0, 0]]]
test_add_int32
Node:
Add(x, y) -> (sum)
Inputs:
x: shape=(3, 4, 5), dtype=int32
[[[ 0, -1, 1, 2, -1],
[ 0, 0, 0, 0, 0],
[ 0, 0, 2, 1, 0],
[-1, 1, -1, 0, 1]],
[[ 1, -1, -2, 1, 1],
[-1, 0, 0, -1, 0],
[ 0, 2, 0, 0, -1],
[ 0, 0, 0, 0, 0]],
[[ 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0],
[ 0, 0, 0, -1, 0],
[ 1, 1, 0, 0, 0]]]
y: shape=(3, 4, 5), dtype=int32
[[[ 0, 0, -1, 1, 0],
[ 1, -1, 2, 0, -1],
[ 1, 0, -2, 0, 0],
[ 0, 1, 0, 0, 0]],
[[ 0, -1, 0, 0, -1],
[ 0, 1, 0, 0, 1],
[ 1, 0, 0, 0, 0],
[-1, 1, 1, 1, 1]],
[[ 1, 0, 0, 1, 0],
[ 2, 0, 1, 0, 0],
[ 0, 0, 1, 0, 1],
[-1, 0, 0, 0, -1]]]
Outputs:
sum: shape=(3, 4, 5), dtype=int32
[[[ 0, -1, 0, 3, -1],
[ 1, -1, 2, 0, -1],
[ 1, 0, 0, 1, 0],
[-1, 2, -1, 0, 1]],
[[ 1, -2, -2, 1, 0],
[-1, 1, 0, -1, 1],
[ 1, 2, 0, 0, -1],
[-1, 1, 1, 1, 1]],
[[ 1, 0, 0, 1, 0],
[ 2, 0, 1, 0, 0],
[ 0, 0, 1, -1, 1],
[ 0, 1, 0, 0, -1]]]
test_add_int64
Node:
Add(x, y) -> (sum)
Inputs:
x: shape=(3, 4, 5), dtype=int64
[[[-1, 0, 0, 0, 0],
[-1, -1, 2, 1, 0],
[ 0, 0, 0, 1, -1],
[ 0, 0, 0, -1, -1]],
[[ 0, 1, 0, 0, 2],
[ 0, -1, 0, -1, 1],
[-2, 1, 0, 1, 0],
[ 1, 0, 2, -1, 0]],
[[-1, -1, 0, 1, 0],
[ 0, 0, -1, -1, 1],
[ 0, 1, 0, -1, 0],
[ 0, 0, 0, 0, -1]]]
y: shape=(3, 4, 5), dtype=int64
[[[ 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0],
[ 0, 1, -1, 0, 1],
[ 1, 1, 0, 0, 0]],
[[ 1, -2, 2, 0, -1],
[ 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0]],
[[ 0, 0, 0, 0, 0],
[-1, 0, 0, 0, 0],
[ 1, 0, 0, 0, 1],
[ 1, 0, 0, 0, 0]]]
Outputs:
sum: shape=(3, 4, 5), dtype=int64
[[[-1, 0, 0, 0, 0],
[-1, -1, 2, 1, 0],
[ 0, 1, -1, 1, 0],
[ 1, 1, 0, -1, -1]],
[[ 1, -1, 2, 0, 1],
[ 0, -1, 0, -1, 1],
[-2, 1, 0, 1, 0],
[ 1, 0, 2, -1, 0]],
[[-1, -1, 0, 1, 0],
[-1, 0, -1, -1, 1],
[ 1, 1, 0, -1, 1],
[ 1, 0, 0, 0, -1]]]
test_add_int8
Node:
Add(x, y) -> (sum)
Inputs:
x: shape=(3, 4, 5), dtype=int8
[[[ 0, -1, 0, 0, 0],
[ 0, 0, 0, 0, 0],
[-2, 1, 1, -1, 0],
[ 1, 0, -2, 0, -1]],
[[ 0, 0, 1, 0, 0],
[ 0, 1, 0, 1, 0],
[ 0, -1, 0, 0, 0],
[ 0, 0, 0, -2, 0]],
[[ 0, 0, 0, 0, -1],
[-1, 0, 0, 0, 1],
[ 0, 0, 0, 0, 2],
[ 0, 1, -1, 0, 0]]]
y: shape=(3, 4, 5), dtype=int8
[[[ 0, 0, 1, -1, 0],
[ 1, 0, 0, 0, 0],
[-1, 2, 1, 0, -1],
[ 0, 0, 0, 0, 0]],
[[ 1, 0, 1, 2, 0],
[ 0, -1, 0, 0, 0],
[ 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0]],
[[ 0, 0, 0, 0, 0],
[ 0, -1, 0, 0, -2],
[ 0, 0, 0, 0, 0],
[ 0, -1, 0, 0, 0]]]
Outputs:
sum: shape=(3, 4, 5), dtype=int8
[[[ 0, -1, 1, -1, 0],
[ 1, 0, 0, 0, 0],
[-3, 3, 2, -1, -1],
[ 1, 0, -2, 0, -1]],
[[ 1, 0, 2, 2, 0],
[ 0, 0, 0, 1, 0],
[ 0, -1, 0, 0, 0],
[ 0, 0, 0, -2, 0]],
[[ 0, 0, 0, 0, -1],
[-1, -1, 0, 0, -1],
[ 0, 0, 0, 0, 2],
[ 0, 0, -1, 0, 0]]]
test_add_uint16
Node:
Add(x, y) -> (sum)
Inputs:
x: shape=(3, 4, 5), dtype=uint16
[[[21, 11, 16, 14, 6],
[21, 15, 5, 19, 8],
[21, 6, 3, 8, 20],
[22, 9, 1, 4, 2]],
[[11, 0, 22, 22, 3],
[ 1, 13, 16, 7, 16],
[ 9, 21, 13, 3, 2],
[23, 0, 6, 11, 18]],
[[19, 11, 9, 1, 17],
[22, 16, 4, 10, 3],
[ 5, 15, 23, 22, 10],
[22, 1, 21, 11, 7]]]
y: shape=(3, 4, 5), dtype=uint16
[[[11, 17, 4, 7, 7],
[20, 20, 19, 18, 8],
[13, 1, 12, 16, 2],
[17, 22, 7, 0, 18]],
[[16, 20, 7, 4, 21],
[16, 17, 15, 7, 4],
[ 1, 21, 14, 18, 13],
[13, 7, 16, 1, 8]],
[[13, 11, 5, 11, 6],
[14, 15, 15, 19, 2],
[ 4, 18, 12, 5, 14],
[ 4, 2, 4, 18, 19]]]
Outputs:
sum: shape=(3, 4, 5), dtype=uint16
[[[32, 28, 20, 21, 13],
[41, 35, 24, 37, 16],
[34, 7, 15, 24, 22],
[39, 31, 8, 4, 20]],
[[27, 20, 29, 26, 24],
[17, 30, 31, 14, 20],
[10, 42, 27, 21, 15],
[36, 7, 22, 12, 26]],
[[32, 22, 14, 12, 23],
[36, 31, 19, 29, 5],
[ 9, 33, 35, 27, 24],
[26, 3, 25, 29, 26]]]
test_add_uint32
Node:
Add(x, y) -> (sum)
Inputs:
x: shape=(3, 4, 5), dtype=uint32
[[[ 0, 19, 9, 6, 12],
[ 7, 1, 23, 17, 17],
[20, 14, 10, 9, 14],
[ 3, 14, 12, 19, 0]],
[[14, 10, 7, 21, 4],
[ 0, 6, 6, 5, 12],
[ 3, 8, 16, 0, 0],
[ 6, 3, 13, 4, 18]],
[[ 5, 19, 7, 20, 15],
[19, 21, 12, 17, 1],
[ 5, 22, 16, 8, 14],
[ 5, 14, 15, 5, 1]]]
y: shape=(3, 4, 5), dtype=uint32
[[[ 3, 23, 15, 4, 16],
[21, 4, 7, 8, 14],
[19, 14, 6, 7, 19],
[18, 19, 0, 10, 12]],
[[20, 5, 8, 17, 10],
[ 7, 15, 2, 2, 14],
[16, 23, 3, 21, 1],
[10, 4, 8, 12, 16]],
[[ 3, 20, 21, 21, 4],
[20, 5, 12, 23, 21],
[11, 3, 22, 5, 17],
[ 8, 8, 22, 6, 8]]]
Outputs:
sum: shape=(3, 4, 5), dtype=uint32
[[[ 3, 42, 24, 10, 28],
[28, 5, 30, 25, 31],
[39, 28, 16, 16, 33],
[21, 33, 12, 29, 12]],
[[34, 15, 15, 38, 14],
[ 7, 21, 8, 7, 26],
[19, 31, 19, 21, 1],
[16, 7, 21, 16, 34]],
[[ 8, 39, 28, 41, 19],
[39, 26, 24, 40, 22],
[16, 25, 38, 13, 31],
[13, 22, 37, 11, 9]]]
test_add_uint64
Node:
Add(x, y) -> (sum)
Inputs:
x: shape=(3, 4, 5), dtype=uint64
[[[16, 1, 1, 16, 17],
[15, 6, 2, 16, 2],
[ 5, 23, 18, 23, 22],
[23, 19, 1, 12, 18]],
[[ 1, 21, 21, 13, 8],
[ 5, 7, 2, 5, 16],
[ 2, 11, 1, 22, 3],
[17, 4, 12, 19, 10]],
[[ 9, 21, 1, 11, 19],
[ 2, 16, 10, 15, 5],
[ 3, 9, 21, 12, 3],
[17, 23, 5, 0, 19]]]
y: shape=(3, 4, 5), dtype=uint64
[[[ 2, 12, 18, 11, 20],
[18, 23, 7, 5, 1],
[ 8, 0, 13, 11, 11],
[13, 6, 8, 0, 3]],
[[ 7, 20, 16, 21, 4],
[ 3, 2, 9, 3, 5],
[ 0, 15, 17, 4, 7],
[14, 18, 2, 14, 16]],
[[11, 14, 10, 4, 8],
[ 5, 5, 22, 3, 17],
[ 4, 9, 14, 23, 14],
[ 9, 23, 11, 11, 14]]]
Outputs:
sum: shape=(3, 4, 5), dtype=uint64
[[[18, 13, 19, 27, 37],
[33, 29, 9, 21, 3],
[13, 23, 31, 34, 33],
[36, 25, 9, 12, 21]],
[[ 8, 41, 37, 34, 12],
[ 8, 9, 11, 8, 21],
[ 2, 26, 18, 26, 10],
[31, 22, 14, 33, 26]],
[[20, 35, 11, 15, 27],
[ 7, 21, 32, 18, 22],
[ 7, 18, 35, 35, 17],
[26, 46, 16, 11, 33]]]
test_add_uint8
Node:
Add(x, y) -> (sum)
Inputs:
x: shape=(3, 4, 5), dtype=uint8
[[[22, 20, 5, 8, 7],
[21, 14, 4, 22, 17],
[ 7, 19, 0, 4, 23],
[15, 17, 14, 1, 0]],
[[ 7, 2, 19, 19, 10],
[ 7, 2, 2, 11, 7],
[22, 1, 6, 11, 18],
[ 6, 7, 16, 1, 17]],
[[14, 2, 19, 18, 17],
[16, 14, 21, 23, 0],
[11, 18, 15, 13, 20],
[11, 3, 0, 17, 11]]]
y: shape=(3, 4, 5), dtype=uint8
[[[15, 13, 23, 13, 16],
[14, 23, 4, 1, 8],
[ 0, 3, 8, 19, 14],
[22, 9, 21, 20, 13]],
[[ 4, 13, 23, 3, 18],
[ 7, 0, 11, 14, 8],
[ 9, 1, 12, 6, 22],
[16, 7, 10, 11, 10]],
[[ 9, 14, 12, 1, 17],
[ 9, 21, 21, 1, 14],
[23, 16, 5, 14, 14],
[ 3, 6, 14, 12, 14]]]
Outputs:
sum: shape=(3, 4, 5), dtype=uint8
[[[37, 33, 28, 21, 23],
[35, 37, 8, 23, 25],
[ 7, 22, 8, 23, 37],
[37, 26, 35, 21, 13]],
[[11, 15, 42, 22, 28],
[14, 2, 13, 25, 15],
[31, 2, 18, 17, 40],
[22, 14, 26, 12, 27]],
[[23, 16, 31, 19, 34],
[25, 35, 42, 24, 14],
[34, 34, 20, 27, 34],
[14, 9, 14, 29, 25]]]
test_cc_add
Node:
Add(x, y) -> (z)
Inputs:
x: shape=(2, 3), dtype=float32
[[1., 2., 3.],
[4., 5., 6.]]
y: shape=(2, 3), dtype=float32
[[10., 20., 30.],
[40., 50., 60.]]
Outputs:
z: shape=(2, 3), dtype=float32
[[11., 22., 33.],
[44., 55., 66.]]
test_cc_add_bcast
Node:
Add(x, y) -> (z)
Inputs:
x: shape=(2, 2), dtype=float32
[[1., 2.],
[3., 4.]]
y: shape=(), dtype=float32
0.5
Outputs:
z: shape=(2, 2), dtype=float32
[[1.5, 2.5],
[3.5, 4.5]]
test_cc_add_bfloat16
Node:
Add(x, y) -> (z)
Inputs:
x: shape=(4,), dtype=bfloat16
[1, 2, 3, 4]
y: shape=(4,), dtype=bfloat16
[0.5, 1.5, 2.5, 3.5]
Outputs:
z: shape=(4,), dtype=bfloat16
[1.5, 3.5, 5.5, 7.5]
test_cc_add_double
Node:
Add(x, y) -> (z)
Inputs:
x: shape=(2, 3), dtype=float64
[[1., 2., 3.],
[4., 5., 6.]]
y: shape=(2, 3), dtype=float64
[[10., 20., 30.],
[40., 50., 60.]]
Outputs:
z: shape=(2, 3), dtype=float64
[[11., 22., 33.],
[44., 55., 66.]]
test_cc_add_empty_shape_scalars
Node:
Add(x, y) -> (z)
Inputs:
x: shape=(), dtype=float32
2.5
y: shape=(), dtype=float32
3.5
Outputs:
z: shape=(), dtype=float32
6.
test_cc_add_empty_shape_zero_dim
Node:
Add(x, y) -> (z)
Inputs:
x: shape=(0,), dtype=float32
[]
y: shape=(0,), dtype=float32
[]
Outputs:
z: shape=(0,), dtype=float32
[]
test_cc_add_empty_shape_zero_dim_2d
Node:
Add(x, y) -> (z)
Inputs:
x: shape=(0, 3), dtype=float32
[]
y: shape=(0, 3), dtype=float32
[]
Outputs:
z: shape=(0, 3), dtype=float32
[]
test_cc_add_float16
Node:
Add(x, y) -> (z)
Inputs:
x: shape=(2, 3), dtype=float16
[[1., 2., 3.],
[4., 5., 6.]]
y: shape=(2, 3), dtype=float16
[[10., 20., 30.],
[40., 50., 60.]]
Outputs:
z: shape=(2, 3), dtype=float16
[[11., 22., 33.],
[44., 55., 66.]]
test_cc_add_nan_inf
Node:
Add(x, y) -> (z)
Inputs:
x: shape=(6,), dtype=float32
[ nan, inf, -inf, inf, 1., 0.]
y: shape=(6,), dtype=float32
[ 1., 2., -2., -inf, nan, inf]
Outputs:
z: shape=(6,), dtype=float32
[ nan, inf, -inf, nan, nan, inf]
test_cc_add_nan_inf_bcast_inf_scalar
Node:
Add(x, y) -> (z)
Inputs:
x: shape=(4,), dtype=float32
[ 1., -1., 2., -2.]
y: shape=(), dtype=float32
inf
Outputs:
z: shape=(4,), dtype=float32
[inf, inf, inf, inf]
test_cc_add_nan_inf_bcast_nan_scalar
Node:
Add(x, y) -> (z)
Inputs:
x: shape=(4,), dtype=float32
[ 1., -1., 2., -2.]
y: shape=(), dtype=float32
nan
Outputs:
z: shape=(4,), dtype=float32
[nan, nan, nan, nan]
Differences with previous version (13)#
SchemaDiff: Add (domain 'ai.onnx')
old version: 13
new version: 14
breaking: no
Type constraints:
changed ‘T’: added types: [‘tensor(int16)’, ‘tensor(int8)’, ‘tensor(uint16)’, ‘tensor(uint8)’]