NonZero¶
NonZero - 13¶
Version¶
name: NonZero (GitHub)
domain:
main
since_version:
13
function:
False
support_level:
SupportType.COMMON
shape inference:
True
This version of the operator has been available since version 13.
Summary¶
Returns the indices of the elements that are non-zero (in row-major order - by dimension). NonZero behaves similar to numpy.nonzero: https://docs.scipy.org/doc/numpy/reference/generated/numpy.nonzero.html, but for scalar input, NonZero produces output shape (0, N) instead of (1, N), which is different from Numpy’s behavior.
Inputs¶
X (heterogeneous) - T:
input
Outputs¶
Y (heterogeneous) - tensor(int64):
output
Type Constraints¶
T in (
tensor(bfloat16)
,tensor(bool)
,tensor(complex128)
,tensor(complex64)
,tensor(double)
,tensor(float)
,tensor(float16)
,tensor(int16)
,tensor(int32)
,tensor(int64)
,tensor(int8)
,tensor(string)
,tensor(uint16)
,tensor(uint32)
,tensor(uint64)
,tensor(uint8)
):Constrain to all tensor types.
NonZero - 9¶
Version¶
name: NonZero (GitHub)
domain:
main
since_version:
9
function:
False
support_level:
SupportType.COMMON
shape inference:
True
This version of the operator has been available since version 9.
Summary¶
Returns the indices of the elements that are non-zero (in row-major order - by dimension). NonZero behaves similar to numpy.nonzero: https://docs.scipy.org/doc/numpy/reference/generated/numpy.nonzero.html, but for scalar input, NonZero produces output shape (0, N) instead of (1, N), which is different from Numpy’s behavior.
Inputs¶
X (heterogeneous) - T:
input
Outputs¶
Y (heterogeneous) - tensor(int64):
output
Type Constraints¶
T in (
tensor(bool)
,tensor(complex128)
,tensor(complex64)
,tensor(double)
,tensor(float)
,tensor(float16)
,tensor(int16)
,tensor(int32)
,tensor(int64)
,tensor(int8)
,tensor(string)
,tensor(uint16)
,tensor(uint32)
,tensor(uint64)
,tensor(uint8)
):Constrain to all tensor types.