def __init__()

in models/encoders.py [0:0]

• 13 lines of code
• 3 McCabe index (conditional complexity)

    def __init__(self, latent_dim: int = 128, n_vertices: int = 6172, mean: th.Tensor = None, stddev: th.Tensor = None,
                 model_name: str = 'expression_encoder'):
        """
        :param latent_dim: size of the latent expression embedding before quantization through Gumbel softmax
        :param n_vertices: number of face mesh vertices
        :param mean: mean position of each vertex
        :param stddev: standard deviation of each vertex position
        :param model_name: name of the model, used to load and save the model
        """
        super().__init__(model_name)

        self.n_vertices = n_vertices

        shape = (1, 1, n_vertices, 3)
        self.register_buffer("mean", th.zeros(shape) if mean is None else mean.view(shape))
        self.register_buffer("stddev", th.ones(shape) if stddev is None else stddev.view(shape))

        self.layers = th.nn.ModuleList([
            th.nn.Linear(self.n_vertices * 3, 256),
            th.nn.Linear(256, 128),
        ])
        self.lstm = th.nn.LSTM(input_size=128, hidden_size=128, num_layers=1, batch_first=True)
        self.code = th.nn.Linear(128, latent_dim)