def decoder(layer_number=1,
hidden_number=500,
output_number=100,
Dropout_rate=0.2,
cell='gru'):
cell_type = cell
Muilti_cell = RNN.SequentialRNNCell()
for i in range(layer_number):
if cell_type == 'gru' or cell_type == 'GRU':
Muilti_cell.add(
RNN.GRUCell(num_hidden=hidden_number,
num_output=output_number,
prefix="gru_decoder_{}".format(i)))
print("stack {}-'{}'- decoder cell".format(i, cell_type))
elif cell_type == 'lstm' or cell_type == 'LSTM':
Muilti_cell.add(
RNN.LSTMCell(num_hidden=hidden_number,
num_output=output_number,
prefix="lstm_decoder_{}".format(i)))
print("stack {}-'{}'- decoder cell".format(i, cell_type))
else:
Muilti_cell.add(
RNN.RNNCell(num_hidden=hidden_number,
num_output=output_number,
prefix="rnn_decoder_{}".format(i)))
print("stack {}-'{}'- decoder cell".format(i, cell_type))
if Dropout_rate > 0 and (layer_number - 1) > i:
Muilti_cell.add(
RNN.DropoutCell(Dropout_rate,
prefix="dropout_decoder_{}".format(i)))
print("stack {}-'{}'- decoder dropout cell".format(i, cell_type))
return Muilti_cell
def decoder(layer_number=1 , hidden_number=500 , output_number = 100 , Dropout_rate=0.2 , Zoneout_rate=0.0 , Residual=True , cell='gru'):
print("<<<decoder structure>>>")
cell_type = cell
Muilti_cell = RNN.SequentialRNNCell()
for i in range(layer_number):
if cell_type == 'gru' or cell_type == 'GRU' or cell_type == 'Gru' :
if Residual == True and Zoneout_rate > 0:
print("residualcell applied_{}".format(i))
Residual_cell=RNN.ResidualCell(RNN.GRUCell(num_hidden=hidden_number, num_output= output_number ,prefix="gru_decoder_{}".format(i)))
print("zoneoutcell applied-{}".format(i))
Zoneout_cell=RNN.ZoneoutCell(Residual_cell,zoneout_outputs=Zoneout_rate , zoneout_states=Zoneout_rate)
Muilti_cell.add(Zoneout_cell)
elif Residual == True and Zoneout_rate == 0:
print("residualcell applied_{}".format(i))
Residual_cell=RNN.ResidualCell(RNN.GRUCell(num_hidden=hidden_number, num_output= output_number ,prefix="gru_decoder_{}".format(i)))
Muilti_cell.add(Residual_cell)
elif Residual == False and Zoneout_rate > 0:
print("zoneoutcell applied-{}".format(i))
Zoneout_cell=RNN.ZoneoutCell(RNN.GRUCell(num_hidden=hidden_number, num_output= output_number ,prefix="gru_decoder_{}".format(i)),zoneout_outputs=Zoneout_rate , zoneout_states=Zoneout_rate)
Muilti_cell.add(Zoneout_cell)
else:
Muilti_cell.add(RNN.GRUCell(num_hidden=hidden_number, num_output= output_number ,prefix="gru_decoder_{}".format(i)))
print("stack {}-'{}'- decoder cell".format(i,cell_type))
elif cell_type == 'lstm' or cell_type == 'LSTM' or cell_type == 'Lstm':
if Residual == True and Zoneout_rate > 0:
print("residualcell applied_{}".format(i))
Residual_cell=RNN.ResidualCell(RNN.LSTMCell(num_hidden=hidden_number, num_output=output_number, prefix="lstm_decoder_{}".format(i)))
print("zoneoutcell applied-{}".format(i))
Zoneout_cell=RNN.ZoneoutCell(Residual_cell,zoneout_outputs=Zoneout_rate , zoneout_states=Zoneout_rate)
Muilti_cell.add(Zoneout_cell)
elif Residual == True and Zoneout_rate == 0:
print("residualcell applied_{}".format(i))
Residual_cell=RNN.ResidualCell(RNN.LSTMCell(num_hidden=hidden_number, num_output=output_number, prefix="lstm_decoder_{}".format(i)))
Muilti_cell.add(Residual_cell)
elif Residual == False and Zoneout_rate > 0:
print("zoneoutcell applied-{}".format(i))
Zoneout_cell=RNN.ZoneoutCell(RNN.LSTMCell(num_hidden=hidden_number, num_output=output_number, prefix="lstm_decoder_{}".format(i)),zoneout_outputs=Zoneout_rate , zoneout_states=Zoneout_rate)
Muilti_cell.add(Zoneout_cell)
else:
Muilti_cell.add(RNN.LSTMCell(num_hidden=hidden_number, num_output=output_number, prefix="lstm_decoder_{}".format(i)))
print("stack {}-'{}'- decoder cell".format(i,cell_type))
else:
if Residual == True and Zoneout_rate > 0:
print("residualcell applied_{}".format(i))
Residual_cell=RNN.ResidualCell(RNN.RNNCell(num_hidden=hidden_number, num_output=output_number, activation='relu' , prefix="rnn_decoder_{}".format(i)))
print("zoneoutcell applied-{}".format(i))
Zoneout_cell=RNN.ZoneoutCell(Residual_cell,zoneout_outputs=Zoneout_rate , zoneout_states=Zoneout_rate)
Muilti_cell.add(Zoneout_cell)
elif Residual == True and Zoneout_rate == 0:
print("residualcell applied_{}".format(i))
Residual_cell=RNN.ResidualCell(RNN.RNNCell(num_hidden=hidden_number, num_output=output_number, activation='relu', prefix="rnn_decoder_{}".format(i)))
Muilti_cell.add(Residual_cell)
elif Residual == False and Zoneout_rate > 0:
print("zoneoutcell applied-{}".format(i))
Zoneout_cell=RNN.ZoneoutCell(RNN.RNNCell(num_hidden=hidden_number, num_output=output_number, activation='relu' , prefix="rnn_decoder_{}".format(i)),zoneout_outputs=Zoneout_rate , zoneout_states=Zoneout_rate)
Muilti_cell.add(Zoneout_cell)
else:
Muilti_cell.add(RNN.RNNCell(num_hidden=hidden_number , num_output=output_number , activation='relu' , prefix="rnn_decoder_{}".format(i)))
print("stack {}-'{}'- decoder cell".format(i,cell_type))
if Dropout_rate > 0 and (layer_number-1) > i:
Muilti_cell.add(RNN.DropoutCell(Dropout_rate, prefix="dropout_decoder_{}".format(i)))
print("stack {}-'{}'- decoder dropout cell".format(i,cell_type))
print("\n")
return Muilti_cell