[Tensorflow] MNIST Data 다운로드 오류 발생시(Proxy Server 설정)

[업데이트 2018.03.18 14:11]

Tensorflow 예제 중에 MNIST data에 대해 classification하는 예제가 있습니다. 해당 예제의 경우 MNIST data를 다운로드를 하는데, 만약 다음과 같은 오류가 발생할 경우 proxy server 설정이 되어 있지 않은 경우입니다.  

C:\Python36\python.exe C:/dev/ai/NeuralNetwork03.py

Traceback (most recent call last):
  File "C:\Python36\lib\urllib\request.py", line 1318, in do_open
    encode_chunked=req.has_header('Transfer-encoding'))
  File "C:\Python36\lib\http\client.py", line 1239, in request
    self._send_request(method, url, body, headers, encode_chunked)
  File "C:\Python36\lib\http\client.py", line 1285, in _send_request
    self.endheaders(body, encode_chunked=encode_chunked)
  File "C:\Python36\lib\http\client.py", line 1234, in endheaders
    self._send_output(message_body, encode_chunked=encode_chunked)
  File "C:\Python36\lib\http\client.py", line 1026, in _send_output
    self.send(msg)
  File "C:\Python36\lib\http\client.py", line 964, in send
    self.connect()
  File "C:\Python36\lib\http\client.py", line 1400, in connect
    server_hostname=server_hostname)
  File "C:\Python36\lib\ssl.py", line 407, in wrap_socket
    _context=self, _session=session)
  File "C:\Python36\lib\ssl.py", line 814, in __init__
    self.do_handshake()
  File "C:\Python36\lib\ssl.py", line 1068, in do_handshake
    self._sslobj.do_handshake()
  File "C:\Python36\lib\ssl.py", line 689, in do_handshake
    self._sslobj.do_handshake()
ssl.SSLError: [SSL: TLSV1_ALERT_ACCESS_DENIED] tlsv1 alert access denied (_ssl.c:777)

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:/dev/ai/NeuralNetwork03.py", line 10, in 
    mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)
  File "C:\Python36\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\mnist.py", line 235, in read_data_sets
    SOURCE_URL + TRAIN_IMAGES)
  File "C:\Python36\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\base.py", line 208, in maybe_download
    temp_file_name, _ = urlretrieve_with_retry(source_url)
  File "C:\Python36\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\base.py", line 165, in wrapped_fn
    return fn(*args, **kwargs)
  File "C:\Python36\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\base.py", line 190, in urlretrieve_with_retry
    return urllib.request.urlretrieve(url, filename)
  File "C:\Python36\lib\urllib\request.py", line 248, in urlretrieve
    with contextlib.closing(urlopen(url, data)) as fp:
  File "C:\Python36\lib\urllib\request.py", line 223, in urlopen
    return opener.open(url, data, timeout)
  File "C:\Python36\lib\urllib\request.py", line 526, in open
    response = self._open(req, data)
  File "C:\Python36\lib\urllib\request.py", line 544, in _open
    '_open', req)
  File "C:\Python36\lib\urllib\request.py", line 504, in _call_chain
    result = func(*args)
  File "C:\Python36\lib\urllib\request.py", line 1361, in https_open
    context=self._context, check_hostname=self._check_hostname)
  File "C:\Python36\lib\urllib\request.py", line 1320, in do_open
    raise URLError(err)
urllib.error.URLError: 

Process finished with exit code 1

Windows 기준으로 환경변수로 아래와 같이 추가하게 되면 해결 할 수 있습니다.

HTTP_PROXY=http://proxy_server_hostname:proxy_server_port
HTTPS_PROXY=https://proxy_server_hostname:proxy_server_port

수정 후 정상적으로 실행된 결과입니다.

Microsoft Windows [Version 10.0.10586]
(c) 2015 Microsoft Corporation. All rights reserved.

C:\>C:\Python36\python.exe C:/dev/ai/NeuralNetwork03.py
Successfully downloaded train-images-idx3-ubyte.gz 9912422 bytes.
Extracting MNIST_data/train-images-idx3-ubyte.gz
Successfully downloaded train-labels-idx1-ubyte.gz 28881 bytes.
Extracting MNIST_data/train-labels-idx1-ubyte.gz
Successfully downloaded t10k-images-idx3-ubyte.gz 1648877 bytes.
Extracting MNIST_data/t10k-images-idx3-ubyte.gz
Successfully downloaded t10k-labels-idx1-ubyte.gz 4542 bytes.
Extracting MNIST_data/t10k-labels-idx1-ubyte.gz
WARNING:tensorflow:From C:/dev/ai/NeuralNetwork03.py:29: arg_max (from tensorflow.python.ops.gen_math_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use `argmax` instead
WARNING:tensorflow:From C:/dev/ai/NeuralNetwork03.py:29: arg_max (from tensorflow.python.ops.gen_math_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use `argmax` instead
2017-11-16 15:09:22.738972: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-11-16 15:09:22.741257: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-11-16 15:09:24.761612: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\common_runtime\gpu\gpu_device.cc:955] Found device 0 with properties:
name: Quadro M1000M
major: 5 minor: 0 memoryClockRate (GHz) 1.0715
pciBusID 0000:01:00.0
Total memory: 2.00GiB
Free memory: 1.65GiB
2017-11-16 15:09:24.764200: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\common_runtime\gpu\gpu_device.cc:976] DMA: 0
2017-11-16 15:09:24.765900: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\common_runtime\gpu\gpu_device.cc:986] 0:   Y
2017-11-16 15:09:24.767794: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\common_runtime\gpu\gpu_device.cc:1045] Creating TensorFlow device (/gpu:0) -> (device: 0, name: Quadro M1000M, pci bus id: 0000:01:00.0)
Epoch: 0001 cost = 2.826302619
Epoch: 0002 cost = 1.061668924
Epoch: 0003 cost = 0.838061295
Epoch: 0004 cost = 0.733232720
Epoch: 0005 cost = 0.669279865
Epoch: 0006 cost = 0.624611813
Epoch: 0007 cost = 0.591160332
Epoch: 0008 cost = 0.563868975
Epoch: 0009 cost = 0.541745164
Epoch: 0010 cost = 0.522673562
Epoch: 0011 cost = 0.506782307
Epoch: 0012 cost = 0.492447628
Epoch: 0013 cost = 0.479955819
Epoch: 0014 cost = 0.468893656
Epoch: 0015 cost = 0.458703467
Learning finished
Accuracy:  0.8951
Label:  [8]
Prediction:  [8]

C:\>

** MAC의 경우 터미널에서 아래와 같이 실행

/Applications/Python\ 3.6/Install\ Certificates.command

* 참고 : https://stackoverflow.com/questions/17247981/how-to-tell-python-to-automatically-use-the-proxy-setting-in-windows-xp-like-rs

* 참고 : https://www.tensorflow.org/get_started/mnist/beginners

* 참고 : https://hunkim.github.io/ml/

* 참고 : https://github.com/tensorflow/tensorflow/issues/10779