环境：Ubuntu
16.04/ tensorflow1.14.0/ python3.5.3
我使用此命令安装了 TensorFlow。
sudo pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.1-cp27-none-linux_x86_64.whl
这就是它的结果。
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
这时会出现 python2 的警告
实际上，我想在 python3 上使用 TensorFlow，因为我在 python2 上安装了 TensorFlow。提示上有很多注释。
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)])
>>>
我试图忽略它。
>>> 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
它是有效的（？），但为什么会出现这么多警告？
答案1
首先，要将 tensorflow 与 python 3 一起使用，您必须使用 安装它pip3。如果尚未pip3安装，可以使用 安装它sudo apt install python3-pip
然后，您可以通过运行以下命令简单地安装 tensorflow pip3 install tensorflow，而无需使用 sudo。
其次，由于 numpy 版本的原因，您收到警告，可能是您安装的 tensorflow 版本不支持 numpy 版本（1.17 或 1.15）。
因此，要解决这些警告，您可以：
- 安装 tensorflow 2.0，它可以与最新版本的 numpy 配合使用。命令是
pip3 install --upgrade tensoflow
或者
- 将 numpy 降级到 1.13.3<=numpy<=1.14.5 并保留当前版本的 tensorflow。命令如下
pip3 install nupmpy==1.14
注意：您收到的警告并不意味着安装失败。Tensorflow 运行良好，您可以忽略它们，一切都会正常运行。