adityaiitb

Frozen graph is deprecated in TF2. Using Saved model is the new approach. Instead of creating a configuration file and using bazel in steps 1 and 2 described here, simply use the saved_model_cli. The final compilation step of creating a binary can be performed using a makefile instead of bazel.

1. Create a TF saved_model using tf.saved_model.save.
2. Use the saved_model_cli to perform XLA AOT compilation.

saved_model_cli aot_compile_cpu \
    --dir resnet/1 \
    --tag_set serve \
 --signature_def_key serving_default \

carlthome

kmhofmann

Building TensorFlow from source (TF 2.3.0, Ubuntu 20.04)

Why build from source?

The official instructions on installing TensorFlow are here: https://www.tensorflow.org/install. If you want to install TensorFlow just using pip, you are running a supported Ubuntu LTS distribution, and you're happy to install the respective tested CUDA versions (which often are outdated), by all means go ahead. A good alternative may be to run a Docker image.

I am usually unhappy with installing what in effect are pre-built binaries. These binaries are often not compatible with the Ubuntu version I am running, the CUDA version that I have installed, and so on. Furthermore, they may be slower than binaries optimized for the target architecture, since certain instructions are not being used (e.g. AVX2, FMA).

So installing TensorFlow from source becomes a necessity. The official instructions on building TensorFlow from source are here: ht

iambibhas

Here is a list of scopes to use in Sublime Text 2 snippets - 

ActionScript: source.actionscript.2
AppleScript: source.applescript
ASP: source.asp
Batch FIle: source.dosbatch
C#: source.cs
C++: source.c++
Clojure: source.clojure
CoffeeScript: source.coffee