.. _l-onnx-doc-IsNaN: ===== IsNaN ===== .. contents:: :local: .. _l-onnx-op-isnan-13: IsNaN - 13 ========== **Version** * **name**: `IsNaN (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 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. **Examples** **default** :: node = onnx.helper.make_node( "IsNaN", inputs=["x"], outputs=["y"], ) x = np.array([3.0, np.nan, 4.0, np.nan], dtype=np.float32) y = np.isnan(x) expect(node, inputs=[x], outputs=[y], name="test_isnan") **Differences** .. raw:: html
00Returns which elements of the input are NaN.Returns which elements of the input are NaN.
11
22**Inputs****Inputs**
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44* **X** (heterogeneous) - **T1**:* **X** (heterogeneous) - **T1**:
55 input input
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77**Outputs****Outputs**
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99* **Y** (heterogeneous) - **T2**:* **Y** (heterogeneous) - **T2**:
1010 output output
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1212**Type Constraints****Type Constraints**
1313
1414* **T1** in (* **T1** in (
15 tensor(bfloat16),
1516 tensor(double), tensor(double),
1617 tensor(float), tensor(float),
1718 tensor(float16) tensor(float16)
1819 ): ):
1920 Constrain input types to float tensors. Constrain input types to float tensors.
2021* **T2** in (* **T2** in (
2122 tensor(bool) tensor(bool)
2223 ): ):
2324 Constrain output types to boolean tensors. Constrain output types to boolean tensors.
.. _l-onnx-op-isnan-9: IsNaN - 9 ========= **Version** * **name**: `IsNaN (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 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.