Pip: need to change package name tensorflow-gpu to tensorflow

I am trying to install gpu enabled tensorflow in a conda environment

I am using the command:

pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.1.0-cp35-cp35m-linux_x86_64.whl

      

When I look at the packages installed with the conda list, I end up with a package named tensorflow-gpu.

You can't even import this package because it has a '-' in it.

How do I change the name to "tensorflow"?

Edit: I now think there must be something else in this. Why this serious package in the deep learning community has this obvious problem. Hopefully a tensorflow expert can answer. I am following instructions for Ubuntu and Anaconda here: https://www.tensorflow.org/install/install_linux

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When you install tensorflow gpu version, Anaconda will show that you have installed tensorflow-gpu. -gpu just indicates that this is the gpu version and is not part of the name. You can still just import tensorflow and the gpu version will be found.



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I had a similar problem that was pretty frustrating. I started with a newly created .whl file and tried to install.

pip install /home/ubuntu/xfer/tensorflow_gpu-1.2.1-cp27-none-linux_x86_64.whl

      

Command line check:

pip show tensorflow

      

no package called tensorflow

pip show tensorflow-gpu

      

but there is tensorflow-gpu package in version 1.2.1

However, single line execution in python failed despite assurances that conda would replace:



import tensorflow as tf

      

Then I repeated the pip installation in the .whl file with the --upgrade option:

pip install --upgrade /home/ubuntu/xfer/tensorflow_gpu-1.2.1-cp27-none-linux_x86_64.whl

      

And then one line of python succeeded:

import tensorflow as tf

      

And in fact, based on https://www.tensorflow.org/install/install_linux#run_a_short_tensorflow_program , then a slightly longer program will run, which will also be successful:

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

      

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