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Fixed the markdown formatting of client.monitor and client.trace API documentation.

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PiperOrigin-RevId: 339387773
Change-Id: Ib63d60169bccf85082b2f71a87a4d8d68636a9fe
This commit is contained in:
Yi Situ 2020-10-27 21:01:07 -07:00 committed by TensorFlower Gardener
parent b368310cbf
commit e7715df2de
1 changed files with 53 additions and 35 deletions
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88
tensorflow/python/profiler/profiler_client.py
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@ -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(