mirror of
https://github.com/vale981/ray
synced 2025-03-09 12:56:46 -04:00
e311013afd
* moveit * moveit * docstrings to ref * Update tune-usage.rst Co-authored-by: Sven Mika <sven@anyscale.io>
92 lines
3.8 KiB
ReStructuredText
92 lines
3.8 KiB
ReStructuredText
Console Output (Reporters)
|
|
==========================
|
|
|
|
By default, Tune reports experiment progress periodically to the command-line as follows.
|
|
|
|
.. code-block:: bash
|
|
|
|
== Status ==
|
|
Memory usage on this node: 11.4/16.0 GiB
|
|
Using FIFO scheduling algorithm.
|
|
Resources requested: 4/12 CPUs, 0/0 GPUs, 0.0/3.17 GiB heap, 0.0/1.07 GiB objects
|
|
Result logdir: /Users/foo/ray_results/myexp
|
|
Number of trials: 4 (4 RUNNING)
|
|
+----------------------+----------+---------------------+-----------+--------+--------+--------+--------+------------------+-------+
|
|
| Trial name | status | loc | param1 | param2 | param3 | acc | loss | total time (s) | iter |
|
|
|----------------------+----------+---------------------+-----------+--------+--------+--------+--------+------------------+-------|
|
|
| MyTrainable_a826033a | RUNNING | 10.234.98.164:31115 | 0.303706 | 0.0761 | 0.4328 | 0.1289 | 1.8572 | 7.54952 | 15 |
|
|
| MyTrainable_a8263fc6 | RUNNING | 10.234.98.164:31117 | 0.929276 | 0.158 | 0.3417 | 0.4865 | 1.6307 | 7.0501 | 14 |
|
|
| MyTrainable_a8267914 | RUNNING | 10.234.98.164:31111 | 0.068426 | 0.0319 | 0.1147 | 0.9585 | 1.9603 | 7.0477 | 14 |
|
|
| MyTrainable_a826b7bc | RUNNING | 10.234.98.164:31112 | 0.729127 | 0.0748 | 0.1784 | 0.1797 | 1.7161 | 7.05715 | 14 |
|
|
+----------------------+----------+---------------------+-----------+--------+--------+--------+--------+------------------+-------+
|
|
|
|
Note that columns will be hidden if they are completely empty. The output can be configured in various ways by instantiating a ``CLIReporter`` instance (or ``JupyterNotebookReporter`` if you're using jupyter notebook). Here's an example:
|
|
|
|
.. code-block:: python
|
|
|
|
from ray.tune import CLIReporter
|
|
|
|
# Limit the number of rows.
|
|
reporter = CLIReporter(max_progress_rows=10)
|
|
# Add a custom metric column, in addition to the default metrics.
|
|
# Note that this must be a metric that is returned in your training results.
|
|
reporter.add_metric_column("custom_metric")
|
|
tune.run(my_trainable, progress_reporter=reporter)
|
|
|
|
Extending ``CLIReporter`` lets you control reporting frequency. For example:
|
|
|
|
.. code-block:: python
|
|
|
|
class ExperimentTerminationReporter(CLIReporter):
|
|
def should_report(self, trials, done=False):
|
|
"""Reports only on experiment termination."""
|
|
return done
|
|
|
|
tune.run(my_trainable, progress_reporter=ExperimentTerminationReporter())
|
|
|
|
class TrialTerminationReporter(CLIReporter):
|
|
def __init__(self):
|
|
self.num_terminated = 0
|
|
|
|
def should_report(self, trials, done=False):
|
|
"""Reports only on trial termination events."""
|
|
old_num_terminated = self.num_terminated
|
|
self.num_terminated = len([t for t in trials if t.status == Trial.TERMINATED])
|
|
return self.num_terminated > old_num_terminated
|
|
|
|
tune.run(my_trainable, progress_reporter=TrialTerminationReporter())
|
|
|
|
The default reporting style can also be overriden more broadly by extending the ``ProgressReporter`` interface directly. Note that you can print to any output stream, file etc.
|
|
|
|
.. code-block:: python
|
|
|
|
from ray.tune import ProgressReporter
|
|
|
|
class CustomReporter(ProgressReporter):
|
|
|
|
def should_report(self, trials, done=False):
|
|
return True
|
|
|
|
def report(self, trials, *sys_info):
|
|
print(*sys_info)
|
|
print("\n".join([str(trial) for trial in trials]))
|
|
|
|
tune.run(my_trainable, progress_reporter=CustomReporter())
|
|
|
|
ProgressReporter
|
|
----------------
|
|
|
|
.. autoclass:: ray.tune.ProgressReporter
|
|
:members:
|
|
|
|
CLIReporter
|
|
-----------
|
|
|
|
.. autoclass:: ray.tune.CLIReporter
|
|
|
|
JupyterNotebookReporter
|
|
-----------------------
|
|
|
|
.. autoclass:: ray.tune.JupyterNotebookReporter
|
|
|
|
|