(inputs, kernel, downsample=False)
return output
pair_base
pair_base
pair_base
def pair_base(inputs, kernel, downsample=False):
    """
        pair_base
    """
    filters = inputs.shape[1]
    if downsample:
        output = layers.conv(inputs, filters, (1, kernel), (1, 2))
        output = layers.conv(output, filters, (kernel, 1), (2, 1))
        output = layers.conv(output, filters * 2, (1, 1))
    else:
        output = layers.conv(inputs, filters, (1, kernel))
        output = layers.conv(output, filters, (kernel, 1))
    return output
def pair_base ( inputs , kernel , downsample = False ) : filters = inputs . shape [ 1 ] if downsample : output = layers . conv ( inputs , filters , ( 1 , kernel ) , ( 1 , 2 ) ) output = layers . conv ( output , filters , ( kernel , 1 ) , ( 2 , 1 ) ) output = layers . conv ( output , filters * 2 , ( 1 , 1 ) ) else : output = layers . conv ( inputs , filters , ( 1 , kernel ) ) output = layers . conv ( output , filters , ( kernel , 1 ) ) return output