Tensorflow profiling in TF2.0

Question

I am trying to visualize the performance of tf.data.Datasets using TF2.0 (Beta). I found examples on how to use profiler in older versions of tensorflow. How is profiling done in TF2.0? I could use tf.compat.v1, but the procedure does not seem to be straight forward.

I want to measure memory consumption (device placement wise) and timeline.

Below examples explain profiling with TF1.x Can I measure the execution time of individual operations with TensorFlow?

Understanding tensorflow profiling results

Answer 1

Meanwhile, I found solution to my question: Using the trace_on and trace_export around my training step to get the profiler output, as described here