# This configuration file allows to define the layers that constitute each
#of the neural network models used by our MLP, RNN and LSTM models.
# The first layer is the input layer, meaning that to it we add the input shape expected.
#Note that we can still add the number of neurons on the first layer.
# The last layer is the output layer, meaning that from it we have our prediction share price days
#therefore, we don't define units for this layer as this is defined from the terminal directly.
# There are several types of parameters available to configure your Neural Network model, and more on
#these can be found in https://www.tensorflow.org/api_docs/python/tf/keras/layers
# So far the following type of layers are allowed: Dense, SimpleRNN, LSTM, and Dropout

# This is an on-going work, hence, feel free to request support for more types of layers

# From the terminal, we are able to define:
#   - The number of inputs used by the module
#   - The number of training epochs
#   - The frequency of data training (i.e. do we use all data, or every other day - may speed up training)
#   - The preprocessing type: normalization, standardization, or none
#   - The optimizer
#   - The loss function

MultiLayer_Perceptron \
    = [ {'Dense':
                {'units':50, 'activation':'relu'} },
        {'Dense':
                {'units':100, 'activation':'relu'} },
        {'Dense':
                {'units':80, 'activation':'relu'} },
        {'Dense':
                {'units':30, 'activation':'relu'} },
        {'Dense':
                {'activation':'linear'} }]

Recurrent_Neural_Network \
    = [ {'SimpleRNN':
                {'units':100, 'activation':'linear', 'return_sequences':True} },
        {'SimpleRNN':
                {'units':50, 'activation':'linear', 'return_sequences':True} },
        {'Dropout':
                {'rate':0.2} },
        {'SimpleRNN':
                {'units':21, 'activation':'linear', 'return_sequences':False} },
        {'Dense':
                {'activation':'linear'} }]

Long_Short_Term_Memory \
    = [ {'LSTM':
                {'units':25, 'activation':'tanh', 'return_sequences':True} },
        {'LSTM':
                {'units':15, 'activation':'tanh', 'return_sequences':False} },
        {'Dense':
                {'activation':'linear'} }]