Question

我已经尝试安装Tensorflow几周了，我在简单安装时遇到了很多错误，所以我认为最好从源代码安装Tensorflow。我完全遵循Tensorflow网站上的说明，而我的./configure大部分都是默认的，所以我可以在修改之前看看它是否有效：

./configure Please specify the location of python. [Default is /usr/bin/python]: /Library/Frameworks/Python.framework/Versions/3.6/bin/python3 Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native]: Do you wish to build TensorFlow with Google Cloud Platform support? [y/N] n No Google Cloud Platform support will be enabled for TensorFlow Do you wish to build TensorFlow with Hadoop File System support? [y/N] n No Hadoop File System support will be enabled for TensorFlow Do you wish to build TensorFlow with the XLA just-in-time compiler (experimental)? [y/N] No XLA support will be enabled for TensorFlow Found possible Python library paths: /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages Please input the desired Python library path to use. Default is [/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages] /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages Do you wish to build TensorFlow with OpenCL support? [y/N] n No OpenCL support will be enabled for TensorFlow Do you wish to build TensorFlow with CUDA support? [y/N] n No CUDA support will be enabled for TensorFlow INFO: Starting clean (this may take a while). Consider using --async if the clean takes more than several minutes. Configuration finished

（这不是我第一次编辑配置）

在此之后，我直接从Tensorflow.org网站上执行以下bazel构建命令，从源代码安装：

bazel build --config=opt //tensorflow/tools/pip_package:build_pip_package

（将来，我将添加一些额外的标志来解释我已经收到关于SSE，AVX等的CPU指令错误的事实。）

当我执行那个bazel命令时，我会得到一个非常长的等待时间和一堆堆错误：

r08ErCk:tensorflow kendrick$ bazel build --config=opt //tensorflow/tools/pip_package:build_pip_package WARNING: /Users/kendrick/tensorflow/tensorflow/contrib/learn/BUILD:15:1: in py_library rule //tensorflow/contrib/learn:learn: target '//tensorflow/contrib/learn:learn' depends on deprecated target '//tensorflow/contrib/session_bundle:exporter': Use SavedModel Builder instead. WARNING: /Users/kendrick/tensorflow/tensorflow/contrib/learn/BUILD:15:1: in py_library rule //tensorflow/contrib/learn:learn: target '//tensorflow/contrib/learn:learn' depends on deprecated target '//tensorflow/contrib/session_bundle:gc': Use SavedModel instead. INFO: Found 1 target... INFO: From Compiling external/protobuf/src/google/protobuf/compiler/js/embed.cc [for host]: external/protobuf/src/google/protobuf/compiler/js/embed.cc:37:12: warning: unused variable 'output_file' [-Wunused-const-variable] const char output_file[] = "well_known_types_embed.cc"; ^ 1 warning generated. INFO: From Compiling external/protobuf/python/google/protobuf/pyext/message_factory.cc: external/protobuf/python/google/protobuf/pyext/message_factory.cc:78:28: warning: ISO C++11 does not allow conversion from string literal to 'char *' [-Wwritable-strings] static char* kwlist[] = {"pool", 0}; ^ external/protobuf/python/google/protobuf/pyext/message_factory.cc:222:6: warning: ISO C++11 does not allow conversion from string literal to 'char *' [-Wwritable-strings] {"pool", (getter)GetPool, NULL, "DescriptorPool"}, ^ external/protobuf/python/google/protobuf/pyext/message_factory.cc:222:37: warning: ISO C++11 does not allow conversion from string literal to 'char *' [-Wwritable-strings] {"pool", (getter)GetPool, NULL, "DescriptorPool"}, ^ 3 warnings generated.

这只是所有错误的一小部分，看起来类似于堆积的错误。即使在所有错误消息之后，命令也永远不会返回，我只是在空行上获得闪烁的光标。

有人可以向我提供一些关于我应该进入终端的确切说明以避免这些错误吗？我已经持续数周的堆栈建议，但仍然会出错。

MAC OS Sierra（MacBook Air）

我应该怎么进入终端？（具体地）

到目前为止，我所做的一切几乎都与Tensorflow.org网站上的说明完全相同。

Answer 1

我第一次使用http://queirozf.com/entries/installing-cuda-tk-and-tensorflow-on-a-clean-ubuntu-16-04-install安装，这不仅是一个非常简单的过程，而且使用tf非常简单..只需source <name_of_virtual_environment>/bin/activate然后通过它运行python / python3。登记/> 请记住，链接中的演练是针对gpu tensorflow的，但是使用cpu tensorflow下载为mac，而使用此虚拟环境进程应该可以正常工作。

Answer 2

由于你没有GPU，有SSE和AVX，并且在mac sierra上 - 谷歌上的说明不适用于1.3。我很困惑为什么他们没有提供一个确切的脚本来做到这一点。无论如何，这是您的问题的答案http://www.josephmiguel.com/building-tensorflow-1-3-from-source-on-mac-osx-sierra-macbook-pro-i7-with-sse-and-avx/

/*
do each of these steps independently
will take around 1hr to complete all the steps regardless of machine type

*/


one time install

install anaconda3 pkg # manually download this and install the package
conda update conda
conda create -n dl python=3.6 anaconda
source activate dl

cd /
brew install bazel
pip install six numpy wheel
pip install –upgrade https://storage.googleapis.com/tensorflow/mac/cpu/protobuf-3.1.0-cp35-none-macosx_10_11_x86_64.whl

sudo -i
cd /
rm -rf tensorflow # if rerunning the script
cd /
git clone https://github.com/tensorflow/tensorflow


Step 1

cd /tensorflow
git checkout r1.3 -f
cd /
chmod -R 777 tensorflow
cd /tensorflow
./configure # accept all default settings


Step 2

// https://stackoverflow.com/questions/41293077/how-to-compile-tensorflow-with-sse4-2-and-avx-instructions
bazel build –config=opt –copt=-mavx –copt=-mavx2 –copt=-mfma //tensorflow/tools/pip_package:build_pip_package


Step 3

bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
pip install /tmp/tensorflow_pkg/tensorflow-1.0.1-cp36-cp36m-macosx_10_7_x86_64.whl


Step 4

cd ~
ipython


Step 5

import tensorflow as tf
hello = tf.constant(‘Hello, TensorFlow!’)
sess = tf.Session()
print(sess.run(hello))


Step 6

pip uninstall /tmp/tensorflow_pkg/tensorflow-1.0.1-cp36-cp36m-macosx_10_7_x86_64.whl

在编译Tensorflow时如何执行Bazel Build Command？

2 个答案: