"""Vanilla Neural Network for simple tests.
Authors
* Elena Rastorgueva 2020
"""
import torch
import speechbrain as sb
[docs]class VanillaNN(sb.nnet.containers.Sequential):
"""A simple vanilla Deep Neural Network.
Arguments
---------
activation : torch class
A class used for constructing the activation layers.
dnn_blocks : int
The number of linear neural blocks to include.
dnn_neurons : int
The number of neurons in the linear layers.
Example
-------
>>> inputs = torch.rand([10, 120, 60])
>>> model = VanillaNN(input_shape=inputs.shape)
>>> outputs = model(inputs)
>>> outputs.shape
torch.Size([10, 120, 512])
"""
def __init__(
self,
input_shape,
activation=torch.nn.LeakyReLU,
dnn_blocks=2,
dnn_neurons=512,
):
super().__init__(input_shape=input_shape)
for block_index in range(dnn_blocks):
self.append(
sb.nnet.linear.Linear,
n_neurons=dnn_neurons,
bias=True,
layer_name="linear",
)
self.append(activation(), layer_name="act")