def build_model(config):
"""Builds the cnn."""
params = config.model_arch
get_model = getattr(models, 'get_model_'+str(params['architecture']))
model = get_model(params)
#model = model_kenun.build_convnet_model(params)
# Learning setup
t_params = config.training_params
sgd = SGD(lr=t_params["learning_rate"], decay=t_params["decay"],
momentum=t_params["momentum"], nesterov=t_params["nesterov"])
adam = Adam(lr=0.001, beta_1=0.9, beta_2=0.999, epsilon=1e-08)
optimizer = eval(t_params['optimizer'])
metrics = ['mean_squared_error']
if config.model_arch["final_activation"] == 'softmax':
metrics.append('categorical_accuracy')
if t_params['loss_func'] == 'cosine':
loss_func = eval(t_params['loss_func'])
else:
loss_func = t_params['loss_func']
model.compile(loss=loss_func, optimizer=optimizer,metrics=metrics)
return model
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