def __init__()

in ar-cnn/model.py [0:0]

• 26 lines of code
• 7 McCabe index (conditional complexity)

    def __init__(self,
                 input_dim,
                 num_filters,
                 growth_factor,
                 num_layers,
                 dropout_rate_encoder,
                 dropout_rate_decoder,
                 batch_norm_encoder,
                 batch_norm_decoder,
                 learning_rate,
                 optimizer_enum,
                 pre_trained=None):

        # PianoRoll Input Dimensions
        self.input_dim = input_dim
        # Number of filters in the convolution
        self.num_filters = num_filters
        # Growth rate of number of filters at each convolution
        self.growth_factor = growth_factor
        # Number of Encoder and Decoder layers
        self.num_layers = num_layers
        # A list of dropout values at each encoder layer
        self.dropout_rate_encoder = dropout_rate_encoder
        # A list of dropout values at each decoder layer
        self.dropout_rate_decoder = dropout_rate_decoder
        # A list of flags to ensure if batch_nromalization at each encoder
        self.batch_norm_encoder = batch_norm_encoder
        # A list of flags to ensure if batch_nromalization at each decoder
        self.batch_norm_decoder = batch_norm_decoder
        # Path to pretrained Model
        self.pre_trained = pre_trained
        # Learning rate for the model
        self.learning_rate = learning_rate
        # Optimizer to use while training the model
        self.optimizer_enum = optimizer_enum
        if self.num_layers < 1:
            raise ValueError(
                "Number of layers should be greater than or equal to 1")