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[tune] fix small docs typo (#13355)

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Signed-off-by: Richard Liaw <rliaw@berkeley.edu>
This commit is contained in:
Richard Liaw
2021-01-16 00:49:17 -08:00
committed by GitHub
parent 1d3941e41a
commit 86387504ee
1 changed files with 18 additions and 18 deletions
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doc/source/tune/user-guide.rst
+18 -18
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@@ -222,29 +222,29 @@ To use Tune's checkpointing features, you must expose a ``checkpoint_dir`` argum
.. code-block:: python
import os
import time
from ray import tune
import os
import time
from ray import tune
def train_func(config, checkpoint_dir=None):
start = 0
if checkpoint_dir:
with open(os.path.join(checkpoint_dir, "checkpoint")) as f:
state = json.loads(f.read())
start = state["step"] + 1
def train_func(config, checkpoint_dir=None):
start = 0
if checkpoint_dir:
with open(os.path.join(checkpoint_dir, "checkpoint")) as f:
state = json.loads(f.read())
start = state["step"] + 1
for step in range(start, 100):
time.sleep(1)
for step in range(start, 100):
time.sleep(1)
# Obtain a checkpoint directory
with tune.checkpoint_dir(step=step) as checkpoint_dir:
path = os.path.join(checkpoint_dir, "checkpoint")
with open(path, "w") as f:
f.write(json.dumps({"step": start}))
# Obtain a checkpoint directory
with tune.checkpoint_dir(step=step) as checkpoint_dir:
path = os.path.join(checkpoint_dir, "checkpoint")
with open(path, "w") as f:
f.write(json.dumps({"step": step}))
tune.report(hello="world", ray="tune")
tune.report(hello="world", ray="tune")
tune.run(train_func)
tune.run(train_func)
In this example, checkpoints will be saved by training iteration to ``local_dir/exp_name/trial_name/checkpoint_<step>``.