utils/interpolation_base.py [284:306]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        return vertices_new

    def insert_additional_vertices(self, vertices):
        num_t = self.param.num_timesteps
        num_vert = vertices.shape[1]
        self.param.num_timesteps = num_t * 2 - 1

        vertices = vertices.unsqueeze(1)

        vertices = vertices * torch.as_tensor(
            [1, 0], device=device, dtype=torch.float32
        ).unsqueeze(0).unsqueeze(2).unsqueeze(3)
        vertices = vertices.reshape([num_t * 2, num_vert, 3])
        vertices = vertices[0 : num_t * 2 - 1, ...]

        for i in range(num_t - 1):
            vertices[i * 2 + 1, ...] = (
                0.5 * (vertices[i * 2, ...] + vertices[i * 2 + 2, ...]).clone()
            )

        self.vert_sequence.data = vertices

        return vertices
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



utils/interpolation_base.py [412:434]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        return vertices_new

    def insert_additional_vertices(self, vertices):
        num_t = self.param.num_timesteps
        num_vert = vertices.shape[1]
        self.param.num_timesteps = num_t * 2 - 1

        vertices = vertices.unsqueeze(1)

        vertices = vertices * torch.as_tensor(
            [1, 0], device=device, dtype=torch.float32
        ).unsqueeze(0).unsqueeze(2).unsqueeze(3)
        vertices = vertices.reshape([num_t * 2, num_vert, 3])
        vertices = vertices[0 : num_t * 2 - 1, ...]

        for i in range(num_t - 1):
            vertices[i * 2 + 1, ...] = (
                0.5 * (vertices[i * 2, ...] + vertices[i * 2 + 2, ...]).clone()
            )

        self.vert_sequence.data = vertices

        return vertices
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -