python/methylnet/models.py
def forward(self, x):
		"""Return reconstructed output, mean and variance of embeddings.
		"""
		mean, logvar = self.encode(x)
		z = self.sample_z(mean, logvar)
		out = self.decode(z)
		return out, mean, logvar
Return reconstructed output, mean and variance of embeddings.
		
Return reconstructed output, mean and variance of embeddings.
Return reconstructed output mean and variance of embeddings .
def forward(self, x):
		mean, logvar = self.encode(x)
		z = self.sample_z(mean, logvar)
		out = self.decode(z)
		return out, mean, logvar
def forward ( self , x ) : mean , logvar = self . encode ( x ) z = self . sample_z ( mean , logvar ) out = self . decode ( z ) return out , mean , logvar
Return reconstructed output, mean and variance of embeddings.
Return reconstructed output mean and variance of embeddings .
"""Return reconstructed output, mean and variance of embeddings.
		"""
self
x