def _validateModel(self):
if self.criterion.type=='ClassNLLCriterion':
last_layer = self.net[-1]
while isinstance(last_layer, Container):
last_layer = last_layer[-1]
if last_layer.type != 'SoftMax':
log_model.info('add SoftMax layer to last layer for '
'using ClassNLLCriterion')
self.net.add(SoftMax())
def forward(self,input):
if isinstance(input,np.ndarray):
x = Def_TensorTypes[len(input.shape)-1]
if not self._forward:
log_model.info('compile the network')
self._forward = function(inputs=[x],outputs=self.get_output(x),
allow_input_downcast=True)
return self._forward(input)
else:
return self._forward(input)
return self.get_output(input)