if layer.type == "block":
// TODO support block
DLPyError("Block is not supported in network")
if layer.type == "transconvo":
layer.calculate_output_padding()
del layer.config["output_size"]
option = layer.to_model_params()
rt = self._retrieve_("deeplearn.addlayer", model = self.model_name, **option)
if rt.severity > 1:
raise DLPyError("there seems to be an error while adding the " + layer.name + ".")
After Change
rt = self._retrieve_("deeplearn.addlayer", model = self.model_name, **option)
if rt.severity > 1:
raise DLPyError("there seems to be an error while adding the " + layer.name + ".")
self.num_params = self.count_params()
print("NOTE: Model compiled successfully.")
def _retrieve_(self, _name_, message_level="error", **kwargs):
""" Call a CAS action """
