tensorflow minist数据集分类笔记

最新推荐文章于 2025-05-28 22:19:51 发布

ArtistA

最新推荐文章于 2025-05-28 22:19:51 发布

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分类专栏：机器学习文章标签： tensorflow

本文链接：https://blog.youkuaiyun.com/ArtistA/article/details/69852830

这篇博客深入探讨了TensorFlow中CNN网络在MNIST数据集上的实现，包括数据读取、会话配置、操作命名、张量类型比较以及防止过拟合的dropout策略。同时，解释了权重生成、偏置计算以及交叉熵误差和优化方法。

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本文作为笔者对于tensorflow源码学习的一个笔记，将详细阐述minist教程中cnn网络的实现及其代码细节：

# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the 'License');
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an 'AS IS' BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""A simple MNIST classifier which displays summaries in TensorBoard.
 This is an unimpressive MNIST model, but it is a good example of using
tf.name_scope to make a graph legible in the TensorBoard graph explorer, and of
naming summary tags so that they are grouped meaningfully in TensorBoard.
It demonstrates the functionality of every TensorBoard dashboard.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data

头文件声明，其中input_data为tutorial中自己撰写的用于读取minist数据集的模块

flags = tf.app.flags
FLAGS = flags.FLAGS
flags.DEFINE_boolean('fake_data', False, 'If true, uses fake data '
                     'for unit testing.')
flags.DEFINE_integer('max_steps', 1000, 'Number of steps to run trainer.')
flags.DEFINE_float('learning_rate', 0.001, 'Initial learning rate.')
flags.DEFINE_float('dropout', 0.9, 'Keep probability for training dropout.')
flags.DEFINE_string('data_dir', '/tmp/data', 'Directory for storing data')
flags.DEFINE_string('summaries_dir', '/tmp/mnist_lo