Tanh

class deeptrack.elementwise.Tanh(feature: Feature | None = None, **kwargs: Any)

Bases: ElementwiseFeature

Apply the hyperbolic tangent function elementwise.

This feature applies xp.tanh to each element in a NumPy array or a PyTorch tensor. It supports both direct input and pipeline composition.

Parameters

feature: Feature | None, optional

The input feature to which the hyperbolic tangent function will be applied. If None, the function is applied directly to the input array or tensor.

Examples

>>> import deeptrack as dt
>>> from deeptrack.elementwise import Tanh

Use with NumPy directly:

>>> import numpy as np
>>>
>>> result = Tanh()(np.array([-1.0, 0.0, 1.0]))
>>> result
array([-0.76159416,  0.        ,  0.76159416])

Use with PyTorch directly:

>>> import torch
>>>
>>> result = Tanh()(torch.tensor([-1.0, 0.0, 1.0]))
>>> result
tensor([-0.7616,  0.0000,  0.7616])

Use in a pipeline with a NumPy value:

>>> value = dt.Value(value=np.array([-1.0, 0.0, 1.0]))
>>> pipeline = value >> Tanh()
>>> result = pipeline()
>>> result
array([-0.76159416,  0.        ,  0.76159416])

Use in a pipeline with a PyTorch value:

>>> value = dt.Value(value=torch.tensor([-1.0, 0.0, 1.0]))
>>> pipeline = value >> Tanh()
>>> result = pipeline()
>>> result
tensor([-0.7616,  0.0000,  0.7616])

These are equivalent to:

>>> pipeline = Tanh(value)