Tanh Activation

tanh_actv_type

tanh_actv_type(
  scale=1.0,
  attributes=...
)

The hyperbolic tangent (tanh) activation function squashes values to a range between -1 and 1.

\[f(x) = s \tanh(x) = s \frac{e^x - e^{-x}}{e^x + e^{-x}}\]

where \(s\) is a scaling factor (default 1.0). This activation is zero-centered, which can make optimisation easier compared to sigmoid. It’s commonly used in recurrent neural networks.

Arguments

• scale (real): Scaling factor for the output. Default: 1.0.

• attributes (array): Optional ONNX attributes.

Shape:

• Input: Any shape.

• Output: Same shape as input, with values in range (-1, 1).