Tensorflow : Python 3.5에서 MNIST 데이터 읽기

Question

그냥 ML 및 Tensorflow를 시작합니다. 이후 (내 생각) 성공적으로 내 우분투 시스템에 tensorflow를 설치하는 데. 필자의 didgelt에 대해 tensorflow가있는 CNN을 구현하려고했습니다. stackoverflow에서 몇 가지 질문을 통해 읽고 솔루션 없이는 약 2 일간 속일 경우. 4 개 GZ 파일이 잘못된 위치에 있는지

--------------------------------------------------------------------------- 
NotFoundError        Traceback (most recent call last) 
<ipython-input-3-17f8ae55d032> in <module>() 
     7 
     8 # Import MNIST data 
----> 9 from tensorflow.examples.tutorials.mnist import input_data 
    10 data = input_data.read_data_sets("./MNIST/", one_hot=True) 
    11 

/home/vanmunky/anaconda/envs/tensorflow/lib/python3.5/site-packages/tensorflow/examples/tutorials/mnist/__init__.py in <module>() 
    19 from __future__ import print_function 
    20 
---> 21 from tensorflow.examples.tutorials.mnist import input_data 
    22 from tensorflow.examples.tutorials.mnist import mnist 

/home/vanmunky/anaconda/envs/tensorflow/lib/python3.5/site-packages/tensorflow/examples/tutorials/mnist/input_data.py in <module>() 
    27 from six.moves import xrange # pylint: disable=redefined-builtin 
    28 import tensorflow as tf 
---> 29 from tensorflow.contrib.learn.python.learn.datasets.mnist import read_data_sets 

/home/vanmunky/anaconda/envs/tensorflow/lib/python3.5/site-packages/tensorflow/contrib/__init__.py in <module>() 
    23 from tensorflow.contrib import copy_graph 
    24 from tensorflow.contrib import crf 
---> 25 from tensorflow.contrib import cudnn_rnn 
    26 from tensorflow.contrib import distributions 
    27 from tensorflow.contrib import factorization 

/home/vanmunky/anaconda/envs/tensorflow/lib/python3.5/site-packages/tensorflow/contrib/cudnn_rnn/__init__.py in <module>() 
    19 from __future__ import print_function 
    20 
---> 21 from tensorflow.contrib.cudnn_rnn.python.ops.cudnn_rnn_ops import CudnnGRU 
    22 from tensorflow.contrib.cudnn_rnn.python.ops.cudnn_rnn_ops import CudnnLSTM 
    23 from tensorflow.contrib.cudnn_rnn.python.ops.cudnn_rnn_ops import CudnnRNNRelu 

/home/vanmunky/anaconda/envs/tensorflow/lib/python3.5/site-packages/tensorflow/contrib/cudnn_rnn/python/ops/cudnn_rnn_ops.py in <module>() 
    26 
    27 _cudnn_rnn_ops_so = loader.load_op_library(
---> 28  resource_loader.get_path_to_datafile("_cudnn_rnn_ops.so")) 
    29 
    30 _cudnn_rnn_common_doc_string = """ 

/home/vanmunky/anaconda/envs/tensorflow/lib/python3.5/site-packages/tensorflow/contrib/util/loader.py in load_op_library(path) 
    40 if os.name != 'nt': 
    41  path = resource_loader.get_path_to_datafile(path) 
---> 42  ret = load_library.load_op_library(path) 
    43  assert ret, 'Could not load %s' % path 
    44  return ret 

/home/vanmunky/anaconda/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/framework/load_library.py in load_op_library(library_filename) 
    62  # pylint: disable=protected-access 
    63  raise errors_impl._make_specific_exception(
---> 64   None, None, error_msg, error_code) 
    65  # pylint: enable=protected-access 
    66 finally: 

NotFoundError: /home/vanmunky/anaconda/envs/tensorflow/lib/python3.5/site-packages/tensorflow/contrib/cudnn_rnn/python/ops/_cudnn_rnn_ops.so: cannot open shared object file: No such file or directory 

임 거의 확실하지만, 나는 거의 모든 곳에서 넣어 :

import tensorflow as tf 
    import matplotlib.pyplot as plt 
    import struct 
    import numpy as np 
    from mpl_toolkits.mplot3d import Axes3D 

    from tensorflow.examples.tutorials.mnist import input_data 
    data = input_data.read_data_sets("./MNIST/", one_hot=True) 

    mnist = MNIST("./data/") 

    # for now i just wanna print something that tells me i successfully 
    # read the data 
    print("Size of:") 
    print("- Training-set:\t\t{}".format(len(data.train.labels))) 
    print("- Test-set:\t\t{}".format(len(data.test.labels))) 
    print("- Validation-set:\t{}".format(len(data.validation.labels))) 

내가 뭘 나가 같습니다. 그래서이 코드에 따라 데이터를 정확히 어디에 두어야합니까? 또는 코드가 잘못 되었습니까? 나는 무엇을 놓치나요?

감사

Answer 1

스택 트레이스 내에서 문제는 데이터 집합을 mnist하는 경로에 있지 않습니다. tensorflow with GPU 지원을 설치했지만 필수 cudnn 라이브러리에 연결할 수 없습니다. gpu로 tensorflow를 실제로 사용하려면 모두 GPU requirements인지 확인하십시오. 그렇지 않으면 tensorflow with CPU (anaconda를 사용한다고 가정)을 다시 설치하기 만하면됩니다.