def forward(self, input):
    '\n        input: [B, N, latent_size + point_dim]\n        :param latent_codes: [B, N, LATENT_CODE_DIM]\n        :param points: [B, N, 3]\n        :return: sdf_pred: [B, N]\n        '
    x = self.layers1(input)
    x = torch.cat((x, input), dim=(- 1))
    x = self.layers2(x)
    return x
input: [B, N, latent_size + point_dim]
:param latent_codes: [B, N, LATENT_CODE_DIM]
:param points: [B, N, 3]
:return: sdf_pred: [B, N]
def forward(self, input):
    '\n        input: [B, N, latent_size + point_dim]\n        :param latent_codes: [B, N, LATENT_CODE_DIM]\n        :param points: [B, N, 3]\n        :return: sdf_pred: [B, N]\n        '
    x = self.layers1(input)
    x = torch.cat((x, input), dim=(- 1))
    x = self.layers2(x)
    return x