From e7715df2de24c699956104b28c665d1aeaa7b97b Mon Sep 17 00:00:00 2001 From: Yi Situ Date: Tue, 27 Oct 2020 21:01:07 -0700 Subject: [PATCH] Fixed the markdown formatting of client.monitor and client.trace API documentation. PiperOrigin-RevId: 339387773 Change-Id: Ib63d60169bccf85082b2f71a87a4d8d68636a9fe --- tensorflow/python/profiler/profiler_client.py | 88 +++++++++++-------- 1 file changed, 53 insertions(+), 35 deletions(-) diff --git a/tensorflow/python/profiler/profiler_client.py b/tensorflow/python/profiler/profiler_client.py index d383d8b7b86..d4aaa8ca5ce 100644 --- a/tensorflow/python/profiler/profiler_client.py +++ b/tensorflow/python/profiler/profiler_client.py @@ -65,46 +65,61 @@ def trace(service_addr, UnavailableError: If no trace event was collected. Example usage (CPU/GPU): - # Start a profiler server before your model runs. + ```python - tf.profiler.experimental.server.start(6009) - # (Model code goes here). - # Send gRPC request to the profiler server to collect a trace of your model. - ```python - tf.profiler.experimental.client.trace('grpc://localhost:6009', - '/nfs/tb_log', 2000) + # Start a profiler server before your model runs. + tf.profiler.experimental.server.start(6009) + # (Model code goes here). + # Send gRPC request to the profiler server to collect a trace of your model. + tf.profiler.experimental.client.trace('grpc://localhost:6009', + '/nfs/tb_log', 2000) + ``` Example usage (Multiple GPUs): - # E.g. your worker IP addresses are 10.0.0.2, 10.0.0.3, 10.0.0.4, and you - # would like to schedule start of profiling 1 second from now, for a duration - # of 2 seconds. - options['delay_ms'] = 1000 - tf.profiler.experimental.client.trace( - 'grpc://10.0.0.2:8466,grpc://10.0.0.3:8466,grpc://10.0.0.4:8466', - 'gs://your_tb_dir', - 2000, - options=options) + + ```python + # E.g. your worker IP addresses are 10.0.0.2, 10.0.0.3, 10.0.0.4, and you + # would like to schedule start of profiling 1 second from now, for a + # duration of 2 seconds. + options['delay_ms'] = 1000 + tf.profiler.experimental.client.trace( + 'grpc://10.0.0.2:8466,grpc://10.0.0.3:8466,grpc://10.0.0.4:8466', + 'gs://your_tb_dir', + 2000, + options=options) + ``` Example usage (TPU): - # Send gRPC request to a TPU worker to collect a trace of your model. A - # profiler service has been started in the TPU worker at port 8466. + ```python - # E.g. your TPU IP address is 10.0.0.2 and you want to profile for 2 seconds. - tf.profiler.experimental.client.trace('grpc://10.0.0.2:8466', - 'gs://your_tb_dir', 2000) + # Send gRPC request to a TPU worker to collect a trace of your model. A + # profiler service has been started in the TPU worker at port 8466. + # E.g. your TPU IP address is 10.0.0.2 and you want to profile for 2 seconds + # . + tf.profiler.experimental.client.trace('grpc://10.0.0.2:8466', + 'gs://your_tb_dir', 2000) + ``` Example usage (Multiple TPUs): - # Send gRPC request to a TPU pod to collect a trace of your model on multiple - # TPUs. A profiler service has been started in all the TPU workers at the - # port 8466. + ```python - # E.g. your TPU IP addresses are 10.0.0.2, 10.0.0.3, 10.0.0.4, and you want to - # profile for 2 seconds. - tf.profiler.experimental.client.trace('grpc://10.0.0.2:8466', - 'gs://your_tb_dir', - 2000, '10.0.0.2,10.0.0.3,10.0.0.4') + # Send gRPC request to a TPU pod to collect a trace of your model on + # multipleTPUs. A profiler service has been started in all the TPU workers + # at theport 8466. + # E.g. your TPU IP addresses are 10.0.0.2, 10.0.0.3, 10.0.0.4, and you want + # to profile for 2 seconds. + tf.profiler.experimental.client.trace('grpc://10.0.0.2:8466', + 'gs://your_tb_dir', + 2000, '10.0.0.2,10.0.0.3,10.0.0.4') + ``` + Launch TensorBoard and point it to the same logdir you provided to this API. - $ tensorboard --logdir=/tmp/tb_log (or gs://your_tb_dir in the above examples) + + ```shell + # logdir can be gs://your_tb_dir as in the above examples. + $ tensorboard --logdir=/tmp/tb_log + ``` + Open your browser and go to localhost:6006/#profile to view profiling results. """ @@ -136,12 +151,15 @@ def monitor(service_addr, duration_ms, level=1): A string of monitoring output. Example usage: - # Continuously send gRPC requests to the Cloud TPU to monitor the model - # execution. - ```python - for query in range(0, 100): - print(tf.profiler.experimental.client.monitor('grpc://10.0.0.2:8466', 1000)) + ```python + # Continuously send gRPC requests to the Cloud TPU to monitor the model + # execution. + + for query in range(0, 100): + print( + tf.profiler.experimental.client.monitor('grpc://10.0.0.2:8466', 1000)) + ``` """ return _pywrap_profiler.monitor(