资源简介
使用tflearn高层封装，用alexnet对鲜花数据集进行训练
代码片段和文件信息
from __future__ import division print_function absolute_import
import tflearn
from tflearn.layers.core import input_data dropout fully_connected
from tflearn.layers.conv import conv_2d max_pool_2d
from tflearn.layers.normalization import local_response_normalization
from tflearn.layers.estimator import regression
import tflearn.datasets.oxflower17 as oxflower17
X Y = oxflower17.load_data（one_hot=True resize_pics=（227 227）） ##此句调用了tflearn文件夹下dataset中oxflower17.py函数，
##此函数主要作用是下载Oxfords数据
# Building ‘AlexNet‘
network = input_data（shape=[None 227 227 3]）
network = conv_2d（network 96 11 strides=4 activation=‘relu‘）
network = max_pool_2d（network 3 strides=2）
network = local_response_normalization（network）
network = conv_2d（network 256 5 activation=‘rel
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