How to write graph to tensorboard using tensorflow 2.0?

Question

Am doing this

    # eager on
    tf.summary.trace_on(graph=True, profiler=True)
    tf.summary.trace_export('stuff', step=1, profiler_outdir='output')
    # ... call train operation
    tf.summary.trace_off()

Profile section shows up in tensorboard but no graph yet.

Answer 1

Please find the github gist here where I have created a graph using Tf2.0 and visualized it in tensorboard. Also for more information, please go through the following link.

Code for the same is mentioned below:

!pip install tensorflow==2.0.0-beta1

import tensorflow as tf
# The function to be traced.
@tf.function
def my_func(x, y):
  # A simple hand-rolled layer.
  return tf.nn.relu(tf.matmul(x, y))

# Set up logging.
logdir = './logs/func'
writer = tf.summary.create_file_writer(logdir)

# Sample data for your function.
x = tf.random.uniform((3, 3))
y = tf.random.uniform((3, 3))

# Bracket the function call with
# tf.summary.trace_on() and tf.summary.trace_export().
tf.summary.trace_on(graph=True, profiler=True)
# Call only one tf.function when tracing.
z = my_func(x, y)
with writer.as_default():
  tf.summary.trace_export(
      name="my_func_trace",
      step=0,
      profiler_outdir=logdir)

%load_ext tensorboard
%tensorboard --logdir ./logs/func

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