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.

Examples

default

import numpy as np
import onnx

node = onnx.helper.make_node(
    "NonZero",
    inputs=["condition"],
    outputs=["result"],
)

condition = np.array([[1, 0], [1, 1]], dtype=bool)
result = np.array(
    np.nonzero(condition), dtype=np.int64
)  # expected output [[0, 1, 1], [0, 0, 1]]
expect(node, inputs=[condition], outputs=[result], name="test_nonzero_example")

NonZero - 9 vs 13

NonZero - 9 #