tensorflow笔记1——自动下载和安装 MNIST 到 TensorFlow 的 python 源码

最新推荐文章于 2024-04-19 08:05:00 发布

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最新推荐文章于 2024-04-19 08:05:00 发布

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分类专栏： tensorflow

本文链接：https://blog.youkuaiyun.com/feiye1023/article/details/55004103

这篇博客介绍了如何使用TensorFlow进行MNIST数据集的自动下载和安装，通过Python源码input_data.py实现。文中以RNN（循环神经网络）为处理方式，详细阐述了下载和安装过程。

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在学习tensorflow时，mnist数据集就相当于是程序界的helloworld，所以先跑一下mnist数据集，我采用rnn（循环神经网络）的方式处理。第一步就是要进行自动下载和安装 MNIST 到 TensorFlow 的 python 源码input_data。

inptu_data.py如下：

#!/usr/bin/Python
# -*- coding: utf-8 -*-
# Copyright 2015 Google Inc. 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.
# ==============================================================================
"""Functions for downloading and reading MNIST data."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import gzip
import os
import tensorflow.python.platform
import numpy
from six.moves import urllib
from six.moves import xrange  # pylint: disable=redefined-builtin
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import mnist

SOURCE_URL = 'http://yann.lecun.com/exdb/mnist/'
def maybe_download(filename, work_directory):
  """Download the data from Yann's website, unless it's already here."""
  if not os.path.exists(work_directory):
    os.mkdir(work_directory)
  filepath = os.path.join(work_directory, filename)
  if not os.path.exists(filepath):
    filepath, _ = urllib.request.urlretrieve(SOURCE_URL + filename, filepath)
    statinfo = os.stat(filepath)
    print('Successfully downloaded', filename, statinfo.st_size, 'bytes.')
  return