Tensorflow学习笔记（第二天）-TensorFlow运作方式入门

    这部分教程直接给出了源码，以为会很快的跑起来，没想到遇到了许多问题。

第一个错误：

    直接运行给出的实例代码 fully_connected_feed.py

NotFoundError: Failed to create a directory: /tmp\tensorflow; No such file or directory

解决方法：这个是找不到文件，无法创建字典。修改代码中的地址：将下面的红色部分的地址前面加/，或者改为你自己代码位置的地址

 parser.add_argument(
      '--input_data_dir',
      type=str,
      default=os.path.join(os.getenv('TEST_TMPDIR', '/tmp'),
                           ' tensorflow/mnist/input_data'),
      help='Directory to put the input data.'
  )
  parser.add_argument(
      '--log_dir',
      type=str,
      default=os.path.join(os.getenv('TEST_TMPDIR', '/tmp'),
                           ' tensorflow/mnist/logs/fully_connected_feed'),
      help='Directory to put the log data.'
  )

第二个错误：

URLError: <urlopen error [WinError 10060] 由于连接方在一段时间后没有正确答复或连接的主机没有反应，连接尝试失败。>

这个问题是无法访问网址，从而无法获取MINST的数据集

解决办法：下载下MINST数据集，复制到上面的input_data文件夹中

MINST数据集：http://yann.lecun.com/exdb/mnist/

三、代码 full_connected_feed.py

# 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.

# ==============================================================================

"""Trains and Evaluates the MNIST network using a feed dictionary."""

from __future__ import absolute_import

from __future__ import division

from __future__ import print_function

# pylint: disable=missing-docstring

import argparse

import os

import sys

import time

from six.moves import xrange  # pylint: disable=redefined-builtin

import tensorflow as tf

from tensorflow.examples.tutorials.mnist import input_data

from tensorflow.examples.tutorials.mnist import mnist

# Basic model parameters as external flags.

FLAGS = None

def placeholder_inputs(batch_size):

  """Generate placeholder variables