fcn_audio

fcn_audio.py

# FCN Model
def create_model(num_classes=10, input_shape=None, dropout_ratio=None):
    model = Sequential()
    if input_shape is None:
        model.add(Input(shape=(None, None, 1)))
    else:
        model.add(Input(shape=input_shape))
    model.add(Conv2D(filters=16, kernel_size=(2, 4), activation='relu'))
    model.add(MaxPooling2D(pool_size=(2, 3)))
    model.add(Conv2D(filters=32, kernel_size=(2, 4), activation='relu'))
    model.add(MaxPooling2D(pool_size=2))
    model.add(Conv2D(filters=64, kernel_size=(2, 4), activation='relu'))
    model.add(MaxPooling2D(pool_size=2))
    model.add(Conv2D(filters=128, kernel_size=(2, 4), activation='relu'))
    model.add(GlobalAveragePooling2D())
    if dropout_ratio is not None:
        model.add(Dropout(dropout_ratio))
    # Add dense linear layer
    model.add(Dense(num_classes, activation='softmax'))
    return model