def gen_model(input_dim=10, output_dim=8, batch_size=100):
model_LSTM = Sequential()
model_LSTM.name = "LSTM"
model_LSTM.batch_size = batch_size
model_LSTM.input_dim = input_dim
model_LSTM.output_dim = output_dim
model_LSTM.add(LSTM(input_shape=(None, input_dim), units=units, return_sequences=True))
model_LSTM.add(LSTM(units=units, return_sequences=True))
model_LSTM.add(LSTM(units=output_dim, return_sequences=True))
model_LSTM.add(Activation('sigmoid'))
sgd = Adam(lr=lr, clipnorm=clipnorm)
model_LSTM.compile(loss='binary_crossentropy', optimizer=sgd, metrics=[
'binary_accuracy'], sample_weight_mode="temporal")
return model_LSTM
def gen_model(input_dim=10, output_dim=8, batch_size=100):
model_dense = Sequential()
model_dense.name = "FFW"
model_dense.batch_size = batch_size
model_dense.input_dim = input_dim
model_dense.output_dim = output_dim
model_dense.add(Dense(input_shape=(None, input_dim), units=output_dim))
model_dense.add(Activation('sigmoid'))
sgd = Adam(lr=lr, clipnorm=clipnorm)
model_dense.compile(loss='binary_crossentropy',
optimizer=sgd,
metrics=['binary_accuracy'],
sample_weight_mode="temporal")
return model_dense
def gen_model(input_dim,
batch_size,
output_dim,
n_slots=n_slots,
m_depth=m_depth,
controller_model=None,
activation="sigmoid",
read_heads=1,
write_heads=1):
model = Sequential()
model.name = "NTM_-_" + controller_model.name
model.batch_size = batch_size
model.input_dim = input_dim
model.output_dim = output_dim
ntm = NTM(output_dim,
n_slots=n_slots,
m_depth=m_depth,
shift_range=3,
controller_model=controller_model,
activation=activation,
read_heads=read_heads,
write_heads=write_heads,
return_sequences=True,
input_shape=(None, input_dim),
batch_size=batch_size)
model.add(ntm)
sgd = Adam(lr=learning_rate, clipnorm=clipnorm)
model.compile(loss='binary_crossentropy',
optimizer=sgd,
metrics=['binary_accuracy'],
sample_weight_mode="temporal")
return model
n_slots = 128
m_depth = 20
learning_rate = 5e-4
clipnorm = 10
def gen_model(input_dim.batch_size,output_dim,
n_slots = n_slots,
m_depth = m_depth,
controller_model = None,
activation = "sigmoid",
read_head = 1,
write_head = 1):
model = Sequential()
model.name = "NTM_-_"+ controller_model.name
model.batch_size = batch_size
model.input_dim = input_dim
model.ouput_dim =output_dim
ntm = NTM(output_dim, n_slots = n_slots, m_depth = m_depth,
shift_range = 3,
controller_model = controller_model,
activation = activation,
read_heads = read_heads,
write_heads = write_heads,
# return_sequences = True,
input_shape = (None,input_dim),
batch_size = batch_size)
model.add(NTM)
