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I've spent to much time trying to install Tensorflow with the packages I want in a conda env. For some reason, conda-forge has tensorflow-hub, but doesn't have tensorflow-text. I need both to run a model.

What's the most user-friendly way to get tensorflow up and running?

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so i gave up on conda and install what i need with pip...

The conda environment.yml that I used to build the environment is here gist.github.com/dimazest/40571

LD_LIBRARRY_PATH might be needed to be redefined, I used this command to fire up a notebook

LD_LIBRARY_PATH="$CONDA_PREFIX/lib":$LD_LIBRARY_PATH jupyter-notebook

A training step takes 38 ms on an Nvidia K40 which I got for $100.

On Google's Colab, a training step takes 21ms. (I don't remember what GPU I've used).

Colab is not expensive, but it is annoying to do long training runs as a connection is likely to drop.

I'm willing to compromise speed in favor of ease of development and early testing on a local machine.

If needed, the final model can always be trained in the cloud on a beefy GPU.

A training step on a CPU in a intel/intel-optimized-tensorflow-avx512 container takes 138 ms.

It is slower than my old GPU, but it might be fast enough to get the first version of a model.

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