Doc/fix activation functions for NBEATS and NHITS (#2759)

* doc add missing activation function

* doc shorten activation function text (now similar to nbeats, nhits)

* fix typo

* lint

---------

Co-authored-by: Dennis Bader <[email protected]>

Author: turbotimon

darts/models/forecasting/nbeats.py

@@ -609,7 +609,8 @@ def __init__(
             prediction time).
         activation
             The activation function of encoder/decoder intermediate layer (default='ReLU').
-            Supported activations: ['ReLU','RReLU', 'PReLU', 'Softplus', 'Tanh', 'SELU', 'LeakyReLU',  'Sigmoid']
+            Supported activations: ['ReLU', 'RReLU', 'PReLU', 'ELU', 'Softplus', 'Tanh', 'SELU', 'LeakyReLU', 'Sigmoid',
+            'GELU']
         **kwargs
             Optional arguments to initialize the pytorch_lightning.Module, pytorch_lightning.Trainer, and
             Darts' :class:`TorchForecastingModel`.

darts/models/forecasting/nhits.py

@@ -543,7 +543,8 @@ def __init__(
             prediction time).
         activation
             The activation function of encoder/decoder intermediate layer (default='ReLU').
-            Supported activations: ['ReLU','RReLU', 'PReLU', 'Softplus', 'Tanh', 'SELU', 'LeakyReLU',  'Sigmoid']
+            Supported activations: ['ReLU', 'RReLU', 'PReLU', 'ELU', 'Softplus', 'Tanh', 'SELU', 'LeakyReLU', 'Sigmoid',
+            'GELU']
         MaxPool1d
             Use MaxPool1d pooling. False uses AvgPool1d
         **kwargs

darts/models/forecasting/tsmixer_model.py

@@ -581,8 +581,9 @@ def __init__(
         num_blocks
             The number of mixer blocks in the model. The number includes the first block and all subsequent blocks.
         activation
-            The name of the activation function to use in the mixer layers. Default: `"ReLU"`. Must be one of
-            `"ReLU", "RReLU", "PReLU", "ELU", "Softplus", "Tanh", "SELU", "LeakyReLU", "Sigmoid", "GELU"`.
+            The activation function to use in the mixer layers (default='ReLU').
+            Supported activations: ['ReLU', 'RReLU', 'PReLU', 'ELU', 'Softplus', 'Tanh', 'SELU', 'LeakyReLU', 'Sigmoid',
+            'GELU']
         dropout
             Fraction of neurons affected by dropout. This is compatible with Monte Carlo dropout at inference time
             for model uncertainty estimation (enabled with ``mc_dropout=True`` at prediction time).