"""Vanilla Neural Network for simple tests.
Authors
* Elena Rastorgueva 2020
"""
import paddle
from paddlespeech.s2t.models.wav2vec2.modules import containers
from paddlespeech.s2t.models.wav2vec2.modules import linear


class VanillaNN(containers.Sequential):
    """A simple vanilla Deep Neural Network.
    Arguments
    ---------
    activation : paddle 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 = paddle.rand([10, 120, 60])
    >>> model = VanillaNN(input_shape=inputs.shape)
    >>> outputs = model(inputs)
    >>> outputs.shape
    paddle.shape([10, 120, 512])
    """

    def __init__(
        self,
        input_shape,
        activation=paddle.nn.LeakyReLU,
        dnn_blocks=2,
        dnn_neurons=512,
    ):
        super().__init__(input_shape=input_shape)

        for block_index in range(dnn_blocks):
            self.append(
                linear.Linear,
                n_neurons=dnn_neurons,
                bias=True,
                layer_name="linear",
            )
            self.append(activation(), layer_name="act")