shamoya

---
# ubuntu-personal-devel-ramp-up.yml
# Author: shamoya
#
# My way to ramp-up and eth2 validator on a fresh install of ubuntu 20.04
# Only prerequisites are: ansible (2.9) and python3-apt.
# It uses ansible to do all the magic on the localhost only (can be expended to remote easily though).
# I prefered simple all-in-one ansible playbook so I can manage it with gist.
# command to run: ansible-playbook -K ubuntu-personal-devel-ramp-up.yml
#

shamoya

"""Benchmark tensorflow distributed by assigning a tensor between two workers.

Usage:
  Start worker 1:
  python rdma_bench.py --workers="hostname1:port,hostname2:port" --protocol=grpc+verbs --task 0

  Start worker 2:
  python rdma_bench.py --workers="hostname1:port,hostname2:port" --protocol=grpc+verbs --task 1

  Run the tests:

shamoya

"""Benchmark tensorflow distributed by adding vector of ones on worker2
to variable on worker1 as fast as possible.

On 2014 macbook, TensorFlow 0.10 this shows

Local rate:       2175.28 MB per second
Distributed rate: 107.13 MB per second

"""

shamoya

import tensorflow as tf
from tensorflow.python.framework import ops
import numpy as np

# Define custom py_func which takes also a grad op as argument:
def py_func(func, inp, Tout, stateful=True, name=None, grad=None):
    
    # Need to generate a unique name to avoid duplicates:
    rnd_name = 'PyFuncGrad' + str(np.random.randint(0, 1E+8))