in models/vertex_unet.py [0:0]
def forward(self, geom: th.Tensor, expression_encoding: th.Tensor):
"""
:param geom: B x T x n_vertices x 3 Tensor containing template face meshes
:param expression_encoding: B x T x heads x classes Tensor containing one hot expression encodings
:return: geom: B x T x n_vertices x 3 Tensor containing predicted face meshes
"""
x = (geom - self.mean) / self.stddev
x = x.view(x.shape[0], x.shape[1], self.n_vertices*3)
geom_encoding, skips = self._encode(x)
x = self._fuse(geom_encoding, expression_encoding)
x = self._decode(x, skips)
x = x.view(x.shape[0], x.shape[1], self.n_vertices, 3)
geom = x * self.stddev + self.mean
return {"geom": geom}