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Tensorboard

Using Tensorboard with Tensorflow.rb is very easy. To make use of tensorboard. First, please make sure that you have installed tensorflow completely and tensorflow.rb is working on your system. I will walk you through a very simple example.
Consider the function

require 'tensorflow'
graph = Tensorflow::Graph.new
tensor_1 = Tensorflow::Tensor.new([[2, 23, 10, 6]])
tensor_2 = Tensorflow::Tensor.new([[22, 3, 7, 12]])
placeholder_1 = graph.placeholder('tensor1', tensor_1.type_num)
placeholder_2 = graph.placeholder('tensor2', tensor_2.type_num)
opspec = Tensorflow::OpSpec.new('Addition_of_tensors', 'Add', nil, [placeholder_1, placeholder_2])

op = graph.AddOperation(opspec)
session_op = Tensorflow::Session_options.new
session = Tensorflow::Session.new(graph, session_op)
hash = {}
hash[placeholder_1] = tensor_1
hash[placeholder_2] = tensor_2
out_tensor = session.run(hash, [op.output(0)], [])
puts out_tensor[0]
graph.write_file("addition.pb")

This example is very simple and easy to understand. A graph just adds takes two tensors and adds them. If you look at the last line that says graph.write_file("addition.pb")
Here I am saving the graph defination in protobuf format in the file addition.pb Now you can use the tensorboard.py file and convert the addition.pb to a format understandable by tensorboard. You can change directory and filename variable as per your convinience. After running the tensorboard.py file on your addition.py file a new directory will be made as specified in the directory variable and then you can run tensorboard by running the command tensorboard --logdir=directory. Example if you directory is /home/arafat/Desktop/test then the command must be run as tensorboard --logdir=/home/arafat/Desktop/test