def input_types(self):
return {
"input":
NeuralType(('B', 'T', 'D'), EncodedRepresentation()),
"seq_lens":
NeuralType(('B'), LengthsType()),
"conditioning":
NeuralType(('B', 'T', 'D'), EncodedRepresentation(),
optional=True),
}
def input_types(self):
return {
"input":
NeuralType(('B', 'T'), TokenIndex()),
"conditioning":
NeuralType(('B', 'T', 'D'), EncodedRepresentation(),
optional=True),
}
def output_types(self):
return {
"out": NeuralType(('B', 'T', 'D'), EncodedRepresentation()),
"log_dur_preds": NeuralType(('B', 'T'), TokenDurationType()),
"pitch_preds": NeuralType(('B', 'T'), RegressionValuesType()),
"energy_preds": NeuralType(('B', 'T'), RegressionValuesType()),
"spec_len": NeuralType(('B'), LengthsType()),
}
def input_types(self):
return {
"x":
NeuralType(('B', 'T', 'D'), EncodedRepresentation()),
"x_len":
NeuralType(('B'), LengthsType()),
"dur_target":
NeuralType(('B', 'T'), TokenDurationType(), optional=True),
"pitch_target":
NeuralType(('B', 'T'), RegressionValuesType(), optional=True),
"energy_target":
NeuralType(('B', 'T'), RegressionValuesType(), optional=True),
"spec_len":
NeuralType(('B'), LengthsType(), optional=True),
}
def output_types(self):
return {
"out": NeuralType(('B', 'T'), EncodedRepresentation()),
}
def input_types(self):
return {
"enc": NeuralType(('B', 'T', 'D'), EncodedRepresentation()),
"enc_mask": NeuralType(('B', 'T', 1), TokenDurationType()),
}
def input_types(self):
return {
"decoder_input": NeuralType(('B', 'T', 'D'),
EncodedRepresentation()),
"lengths": NeuralType(('B'), LengthsType()),
}
