def block_reduction_b(input):
if K.image_dim_ordering() == "th":
channel_axis = 1
else:
channel_axis = -1
branch_0 = conv2d_bn(input, 192, 1, 1)
branch_0 = conv2d_bn(branch_0, 192, 3, 3, subsample=(2, 2), border_mode='valid')
branch_1 = conv2d_bn(input, 256, 1, 1)
branch_1 = conv2d_bn(branch_1, 256, 1, 7)
branch_1 = conv2d_bn(branch_1, 320, 7, 1)
branch_1 = conv2d_bn(branch_1, 320, 3, 3, subsample=(2,2), border_mode='valid')
branch_2 = MaxPooling2D((3, 3), strides=(2, 2), border_mode='valid')(input)
x = merge([branch_0, branch_1, branch_2], mode='concat', concat_axis=channel_axis)
return x
评论列表
文章目录