(l-onnx-doc-NonZero)=

# NonZero


(l-onnx-op-nonzero-13)=

## NonZero - 13

### Version

- **name**: [NonZero (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators.md#NonZero)
- **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.

```{toctree}
text_diff_NonZero_9_13
```

(l-onnx-op-nonzero-9)=

## NonZero - 9

### Version

- **name**: [NonZero (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators.md#NonZero)
- **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.