(bottom, pool=P.Pooling.AVE)
return pool, conv_1x1, conv_1x1_bn, conv_1x1_scale, conv_1x1_relu, conv_1x1_2, conv_1x1_2_bn, conv_1x1_2_scale, \
           conv_1x1_2_relu, conv_1x3_reduce, conv_1x3_reduce_bn, conv_1x3_reduce_scale, conv_1x3_reduce_relu, conv_1x3, \
           conv_1x3_bn, conv_1x3_scale, conv_1x3_relu, conv_3x1, conv_3x1_bn, conv_3x1_scale, conv_3x1_relu, \
           conv_3x3_reduce, conv_3x3_reduce_bn, conv_3x3_reduce_scale, conv_3x3_reduce_relu, conv_3x3, conv_3x3_bn, \
           conv_3x3_scale, conv_3x3_relu, conv_1x3_2, conv_1x3_2_bn, conv_1x3_2_scale, conv_1x3_2_relu, conv_3x1_2, \
           conv_3x1_2_bn, conv_3x1_2_scale, conv_3x1_2_relu, concat
input:1280or2048x8x8
    output:2048x8x8
    :param pool: pool_type
    :param bottom: bottom layer
    :return: layers
input:1280or2048x8x8
    output:2048x8x8
    :param pool: pool_type
    :param bottom: bottom layer
    :return: layers
input : 1280or2048x8x8 output : 2048x8x8 : param pool : pool_type : param bottom : bottom layer : return : layers
def inception_v3_c(bottom, pool=P.Pooling.AVE):
    """
    input:1280or2048x8x8
    output:2048x8x8
    :param pool: pool_type
    :param bottom: bottom layer
    :return: layers
    """
    pool = L.Pooling(bottom, kernel_size=3, stride=1, pad=1, pool=pool)  # 1280or2048x8x8
    conv_1x1, conv_1x1_bn, conv_1x1_scale, conv_1x1_relu = \
        factorization_conv_bn_scale_relu(pool, num_output=192, kernel_size=1)  # 192x8x8

    conv_1x1_2, conv_1x1_2_bn, conv_1x1_2_scale, conv_1x1_2_relu = \
        factorization_conv_bn_scale_relu(bottom, num_output=320, kernel_size=1)  # 320x8x8

    conv_1x3_reduce, conv_1x3_reduce_bn, conv_1x3_reduce_scale, conv_1x3_reduce_relu = \
        factorization_conv_bn_scale_relu(bottom, num_output=384, kernel_size=1)  # 384x8x8
    conv_1x3, conv_1x3_bn, conv_1x3_scale, conv_1x3_relu = \
        factorization_conv_mxn(conv_1x3_reduce, num_output=384, kernel_h=1, kernel_w=3, pad_h=0, pad_w=1)  # 384x8x8
    conv_3x1, conv_3x1_bn, conv_3x1_scale, conv_3x1_relu = \
        factorization_conv_mxn(conv_1x3_reduce, num_output=384, kernel_h=3, kernel_w=1, pad_h=1, pad_w=0)  # 384x8x8

    conv_3x3_reduce, conv_3x3_reduce_bn, conv_3x3_reduce_scale, conv_3x3_reduce_relu = \
        factorization_conv_bn_scale_relu(bottom, num_output=448, kernel_size=1)  # 448x8x8
    conv_3x3, conv_3x3_bn, conv_3x3_scale, conv_3x3_relu = \
        factorization_conv_bn_scale_relu(conv_3x3_reduce, num_output=384, kernel_size=3, pad=1)  # 384x8x8
    conv_1x3_2, conv_1x3_2_bn, conv_1x3_2_scale, conv_1x3_2_relu = \
        factorization_conv_mxn(conv_3x3, num_output=384, kernel_h=1, kernel_w=3, pad_h=0, pad_w=1)  # 384x8x8
    conv_3x1_2, conv_3x1_2_bn, conv_3x1_2_scale, conv_3x1_2_relu = \
        factorization_conv_mxn(conv_3x3, num_output=384, kernel_h=3, kernel_w=1, pad_h=1, pad_w=0)  # 384x8x8

    concat = L.Concat(conv_1x1_2, conv_1x3, conv_3x1, conv_1x3_2, conv_3x1_2, conv_1x1)  # 2048(192+320+384+384+384+384)x8x8

    return pool, conv_1x1, conv_1x1_bn, conv_1x1_scale, conv_1x1_relu, conv_1x1_2, conv_1x1_2_bn, conv_1x1_2_scale, \
           conv_1x1_2_relu, conv_1x3_reduce, conv_1x3_reduce_bn, conv_1x3_reduce_scale, conv_1x3_reduce_relu, conv_1x3, \
           conv_1x3_bn, conv_1x3_scale, conv_1x3_relu, conv_3x1, conv_3x1_bn, conv_3x1_scale, conv_3x1_relu, \
           conv_3x3_reduce, conv_3x3_reduce_bn, conv_3x3_reduce_scale, conv_3x3_reduce_relu, conv_3x3, conv_3x3_bn, \
           conv_3x3_scale, conv_3x3_relu, conv_1x3_2, conv_1x3_2_bn, conv_1x3_2_scale, conv_1x3_2_relu, conv_3x1_2, \
           conv_3x1_2_bn, conv_3x1_2_scale, conv_3x1_2_relu, concat
def inception_v3_c ( bottom , pool = P . Pooling . AVE ) : pool = L . Pooling ( bottom , kernel_size = 3 , stride = 1 , pad = 1 , pool = pool ) # 1280or2048x8x8 conv_1x1 , conv_1x1_bn , conv_1x1_scale , conv_1x1_relu = factorization_conv_bn_scale_relu ( pool , num_output = 192 , kernel_size = 1 ) # 192x8x8 conv_1x1_2 , conv_1x1_2_bn , conv_1x1_2_scale , conv_1x1_2_relu = factorization_conv_bn_scale_relu ( bottom , num_output = 320 , kernel_size = 1 ) # 320x8x8 conv_1x3_reduce , conv_1x3_reduce_bn , conv_1x3_reduce_scale , conv_1x3_reduce_relu = factorization_conv_bn_scale_relu ( bottom , num_output = 384 , kernel_size = 1 ) # 384x8x8 conv_1x3 , conv_1x3_bn , conv_1x3_scale , conv_1x3_relu = factorization_conv_mxn ( conv_1x3_reduce , num_output = 384 , kernel_h = 1 , kernel_w = 3 , pad_h = 0 , pad_w = 1 ) # 384x8x8 conv_3x1 , conv_3x1_bn , conv_3x1_scale , conv_3x1_relu = factorization_conv_mxn ( conv_1x3_reduce , num_output = 384 , kernel_h = 3 , kernel_w = 1 , pad_h = 1 , pad_w = 0 ) # 384x8x8 conv_3x3_reduce , conv_3x3_reduce_bn , conv_3x3_reduce_scale , conv_3x3_reduce_relu = factorization_conv_bn_scale_relu ( bottom , num_output = 448 , kernel_size = 1 ) # 448x8x8 conv_3x3 , conv_3x3_bn , conv_3x3_scale , conv_3x3_relu = factorization_conv_bn_scale_relu ( conv_3x3_reduce , num_output = 384 , kernel_size = 3 , pad = 1 ) # 384x8x8 conv_1x3_2 , conv_1x3_2_bn , conv_1x3_2_scale , conv_1x3_2_relu = factorization_conv_mxn ( conv_3x3 , num_output = 384 , kernel_h = 1 , kernel_w = 3 , pad_h = 0 , pad_w = 1 ) # 384x8x8 conv_3x1_2 , conv_3x1_2_bn , conv_3x1_2_scale , conv_3x1_2_relu = factorization_conv_mxn ( conv_3x3 , num_output = 384 , kernel_h = 3 , kernel_w = 1 , pad_h = 1 , pad_w = 0 ) # 384x8x8 concat = L . Concat ( conv_1x1_2 , conv_1x3 , conv_3x1 , conv_1x3_2 , conv_3x1_2 , conv_1x1 ) # 2048(192+320+384+384+384+384)x8x8 return pool , conv_1x1 , conv_1x1_bn , conv_1x1_scale , conv_1x1_relu , conv_1x1_2 , conv_1x1_2_bn , conv_1x1_2_scale , conv_1x1_2_relu , conv_1x3_reduce , conv_1x3_reduce_bn , conv_1x3_reduce_scale , conv_1x3_reduce_relu , conv_1x3 , conv_1x3_bn , conv_1x3_scale , conv_1x3_relu , conv_3x1 , conv_3x1_bn , conv_3x1_scale , conv_3x1_relu , conv_3x3_reduce , conv_3x3_reduce_bn , conv_3x3_reduce_scale , conv_3x3_reduce_relu , conv_3x3 , conv_3x3_bn , conv_3x3_scale , conv_3x3_relu , conv_1x3_2 , conv_1x3_2_bn , conv_1x3_2_scale , conv_1x3_2_relu , conv_3x1_2 , conv_3x1_2_bn , conv_3x1_2_scale , conv_3x1_2_relu , concat