(l-onnx-doc-IsNaN)=

# IsNaN


(l-onnx-op-isnan-20)=

## IsNaN - 20

### Version

- **name**: [IsNaN (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators.md#IsNaN)
- **domain**: `main`
- **since_version**: `20`
- **function**: `False`
- **support_level**: `SupportType.COMMON`
- **shape inference**: `True`

This version of the operator has been available
**since version 20**.

### Summary

Returns which elements of the input are NaN.

### Inputs

- **X** (heterogeneous) - **T1**:

  input

### Outputs

- **Y** (heterogeneous) - **T2**:

  output

### Type Constraints

* **T1** in ( `tensor(bfloat16)`, `tensor(double)`, `tensor(float)`, `tensor(float16)`, `tensor(float8e4m3fn)`, `tensor(float8e4m3fnuz)`, `tensor(float8e5m2)`, `tensor(float8e5m2fnuz)` ):

  Constrain input types to float tensors.
* **T2** in ( `tensor(bool)` ):

  Constrain output types to boolean tensors.

### Examples

#### default

```python
import numpy as np
import onnx

node = onnx.helper.make_node(
    "IsNaN",
    inputs=["x"],
    outputs=["y"],
)

x = np.array([-1.2, np.nan, np.inf, 2.8, -np.inf, np.inf], dtype=np.float32)
y = np.isnan(x)
expect(node, inputs=[x], outputs=[y], name="test_isnan")
```

#### _float16

```python
import numpy as np
import onnx

node = onnx.helper.make_node(
    "IsNaN",
    inputs=["x"],
    outputs=["y"],
)

x = np.array([-1.2, np.nan, np.inf, 2.8, -np.inf, np.inf], dtype=np.float16)
y = np.isnan(x)
expect(node, inputs=[x], outputs=[y], name="test_isnan_float16")
```

```{toctree}
text_diff_IsNaN_13_20
```

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

## IsNaN - 13

### Version

- **name**: [IsNaN (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators.md#IsNaN)
- **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 which elements of the input are NaN.

### Inputs

- **X** (heterogeneous) - **T1**:

  input

### Outputs

- **Y** (heterogeneous) - **T2**:

  output

### Type Constraints

* **T1** in ( `tensor(bfloat16)`, `tensor(double)`, `tensor(float)`, `tensor(float16)` ):

  Constrain input types to float tensors.
* **T2** in ( `tensor(bool)` ):

  Constrain output types to boolean tensors.

```{toctree}
text_diff_IsNaN_9_20
text_diff_IsNaN_9_13
```

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

## IsNaN - 9

### Version

- **name**: [IsNaN (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators.md#IsNaN)
- **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 which elements of the input are NaN.

### Inputs

- **X** (heterogeneous) - **T1**:

  input

### Outputs

- **Y** (heterogeneous) - **T2**:

  output

### Type Constraints

* **T1** in ( `tensor(double)`, `tensor(float)`, `tensor(float16)` ):

  Constrain input types to float tensors.
* **T2** in ( `tensor(bool)` ):

  Constrain output types to boolean tensors.