.. _op_ai_onnx_Sigmoid: Sigmoid ======= - **Domain**: ``ai.onnx`` - **Since version**: 13 Sigmoid takes one input data (Tensor ) and produces one output data (Tensor ) where the sigmoid function, y = 1 / (1 + exp(-x)), is applied to the tensor element-wise. **Inputs** - **X** (*T*): Input tensor **Outputs** - **Y** (*T*): Output tensor **Type Constraints** - **T**: Constrain input and output types to float tensors. Allowed types: tensor(bfloat16), tensor(double), tensor(float), tensor(float16). Examples -------- **test_cc_sigmoid** .. code-block:: text Node: Sigmoid(X) -> (Y) .. code-block:: text Inputs: X: shape=(2, 3), dtype=float32 [[-4., -1., 0.], [ 1., 2., 4.]] Outputs: Y: shape=(2, 3), dtype=float32 [[0.01798621, 0.26894143, 0.5 ], [0.7310586 , 0.880797 , 0.98201376]] **test_cc_sigmoid_bfloat16** .. code-block:: text Node: Sigmoid(x) -> (y) .. code-block:: text Inputs: x: shape=(2, 3), dtype=bfloat16 [[-2, -1, 0], [0.5, 1, 2]] Outputs: y: shape=(2, 3), dtype=bfloat16 [[0.119141, 0.269531, 0.5], [0.621094, 0.730469, 0.878906]] **test_cc_sigmoid_double** .. code-block:: text Node: Sigmoid(x) -> (y) .. code-block:: text Inputs: x: shape=(2, 3), dtype=float64 [[-2. , -1. , 0. ], [ 0.5, 1. , 2. ]] Outputs: y: shape=(2, 3), dtype=float64 [[0.11920292, 0.26894142, 0.5 ], [0.62245933, 0.73105858, 0.88079708]] **test_cc_sigmoid_float16** .. code-block:: text Node: Sigmoid(x) -> (y) .. code-block:: text Inputs: x: shape=(2, 3), dtype=float16 [[-2. , -1. , 0. ], [ 0.5, 1. , 2. ]] Outputs: y: shape=(2, 3), dtype=float16 [[0.1192, 0.269 , 0.5 ], [0.6226, 0.731 , 0.881 ]] Differences with previous version (6) ------------------------------------- **SchemaDiff**: ``Sigmoid`` (domain ``'ai.onnx'``) * old version: 6 * new version: 13 * breaking: no **Type constraints:** * changed 'T': added types: ['tensor(bfloat16)'] Version History --------------- - :doc:`Version 6 ` - :doc:`Version 1 `