def conv1d_block(filters, upsample=True, activation=tf.nn.relu, index=0):
    if upsample:
        model.add(layers.UpSampling1D(name=('UpSampling' + str(index)), size=2))
    model.add(layers.Conv1D(filters=filters, kernel_size=5, padding='same', name=('Conv1D' + str(index)), activation=activation))
    model.add(layers.BatchNormalization())
def conv1d_block(filters, upsample=True, activation=tf.nn.relu, index=0):
    if upsample:
        model.add(layers.UpSampling1D(name=('UpSampling' + str(index)), size=2))
    model.add(layers.Conv1D(filters=filters, kernel_size=5, padding='same', name=('Conv1D' + str(index)), activation=activation))
    model.add(layers.BatchNormalization())