ubuntu16.04에 TensorFlow 설치 및 많은 경고

ubuntu16.04에 TensorFlow 설치 및 많은 경고

환경 : 우분투 16.04/ 텐서플로우 1.14.0/ 파이썬3.5.3

이 명령을 사용하여 TensorFlow를 설치했습니다.

sudo pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.1-cp27-none-linux_x86_64.whl

이것이 그 결과입니다.

DEPRECATION: Python 2.7 will reach the end of its life on January 1st, 2020. Please upgrade your Python as Python 2.7 won't be maintained after that date. A future version of pip will drop support for Python 2.7. More details about Python 2 support in pip, can be found at https://pip.pypa.io/en/latest/development/release-process/#python-2-support
WARNING: The directory '/home/hanbit-o/.cache/pip/http' or its parent directory is not owned by the current user and the cache has been disabled. Please check the permissions and owner of that directory. If executing pip with sudo, you may want sudo's -H flag.
WARNING: The directory '/home/hanbit-o/.cache/pip' or its parent directory is not owned by the current user and caching wheels has been disabled. check the permissions and owner of that directory. If executing pip with sudo, you may want sudo's -H flag.
Collecting tensorflow==0.7.1 from https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.1-cp27-none-linux_x86_64.whl
  Downloading https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.1-cp27-none-linux_x86_64.whl (13.8MB)
Requirement already satisfied, skipping upgrade: wheel in /usr/local/lib/python2.7/dist-packages (from tensorflow==0.7.1) (0.33.4)
Requirement already satisfied, skipping upgrade: protobuf==3.0.0b2 in /usr/local/lib/python2.7/dist-packages (from tensorflow==0.7.1) (3.0.0b2)
Requirement already satisfied, skipping upgrade: six>=1.10.0 in /usr/lib/python2.7/dist-packages (from tensorflow==0.7.1) (1.10.0)
Requirement already satisfied, skipping upgrade: numpy>=1.8.2 in /home/hanbit-o/.local/lib/python2.7/site-packages (from tensorflow==0.7.1) (1.16.4)
Requirement already satisfied, skipping upgrade: setuptools in /usr/lib/python2.7/dist-packages (from protobuf==3.0.0b2->tensorflow==0.7.1) (20.7.0)
Installing collected packages: tensorflow
  Found existing installation: tensorflow 0.7.1
    Uninstalling tensorflow-0.7.1:
      Successfully uninstalled tensorflow-0.7.1
Successfully installed tensorflow-0.7.1

이때 python2에 대한 경고가 있습니다.

사실 python2에 TensorFlow를 설치했기 때문에 python3에서도 TensorFlow를 사용하고 싶은 생각이 듭니다. 프롬프트에 많은 의견이 있습니다.

Python 3.5.3 (default, Aug 28 2019, 20:35:32) 
[GCC 5.4.0 20160609] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow
/home/hanbit-o/.local/lib/python3.5/site-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint8 = np.dtype([("qint8", np.int8, 1)])
/home/hanbit-o/.local/lib/python3.5/site-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_quint8 = np.dtype([("quint8", np.uint8, 1)])
/home/hanbit-o/.local/lib/python3.5/site-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint16 = np.dtype([("qint16", np.int16, 1)])
/home/hanbit-o/.local/lib/python3.5/site-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_quint16 = np.dtype([("quint16", np.uint16, 1)])
/home/hanbit-o/.local/lib/python3.5/site-packages/tensorflow/python/framework/dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint32 = np.dtype([("qint32", np.int32, 1)])
/home/hanbit-o/.local/lib/python3.5/site-packages/tensorflow/python/framework/dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  np_resource = np.dtype([("resource", np.ubyte, 1)])
/home/hanbit-o/.local/lib/python3.5/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint8 = np.dtype([("qint8", np.int8, 1)])
/home/hanbit-o/.local/lib/python3.5/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_quint8 = np.dtype([("quint8", np.uint8, 1)])
/home/hanbit-o/.local/lib/python3.5/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint16 = np.dtype([("qint16", np.int16, 1)])
/home/hanbit-o/.local/lib/python3.5/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_quint16 = np.dtype([("quint16", np.uint16, 1)])
/home/hanbit-o/.local/lib/python3.5/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint32 = np.dtype([("qint32", np.int32, 1)])
/home/hanbit-o/.local/lib/python3.5/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  np_resource = np.dtype([("resource", np.ubyte, 1)])
>>> 

그리고 나는 그것을 무시하려고 노력했습니다.

>>> hello = tf.constant('Hello, TensorFlow!')
>>> sess = tf.Session()
2019-10-09 21:40:31.902027: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-10-09 21:40:31.926393: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3398000000 Hz
2019-10-09 21:40:31.929440: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x42f31d0 executing computations on platform Host. Devices:
2019-10-09 21:40:31.929480: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): <undefined>, <undefined>
>>> sess.run(hello)
]b'Hello, TensorFlow!'
>>> a = tf.constant(10)
>>> b = tf.constant(32)
>>> sess.run(a+b)
2019-10-09 21:41:28.143676: W tensorflow/compiler/jit/mark_for_compilation_pass.cc:1412] (One-time warning): Not using XLA:CPU for cluster because envvar TF_XLA_FLAGS=--tf_xla_cpu_global_jit was not set.  If you want XLA:CPU, either set that envvar, or use experimental_jit_scope to enable XLA:CPU.  To confirm that XLA is active, pass --vmodule=xla_compilation_cache=1 (as a proper command-line flag, not via TF_XLA_FLAGS) or set the envvar XLA_FLAGS=--xla_hlo_profile.
42

작동(?)인데 왜 경고가 많이 나오나요?

답변1

먼저 Python 3에서 텐서플로우를 사용하려면 pip3. 설치 하지 않은 경우 pip3다음을 사용하여 설치할 수 있습니다. sudo apt install python3-pip
그러면 다음 명령을 실행하여 텐서플로우를 간단히 설치할 수 있으며 pip3 install tensorflow, sudo를 사용할 필요가 없습니다.

둘째, numpy 버전으로 인해 경고가 표시됩니다. 아마도 설치한 tensorflow 버전에서 지원하지 않는 numpy 버전(1.17 또는 1.15)이 있을 수 있습니다.
따라서 이러한 경고를 해결하려면 다음을 수행할 수 있습니다.

  • 최신 버전의 numpy에서 잘 작동하는 tensorflow 2.0을 설치하십시오. 명령은pip3 install --upgrade tensoflow

또는

  • numpy를 1.13.3<=numpy<=1.14.5로 다운그레이드하고 tensorflow의 현재 버전을 유지하세요. 캠맨드는pip3 install nupmpy==1.14

참고:표시된 경고는 설치가 실패했음을 의미하지 않습니다. Tensorflow는 잘 작동합니다. 간단히 무시하면 모든 것이 잘 작동할 것입니다.

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