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Commit cf9d4735 authored by A. Unique TensorFlower's avatar A. Unique TensorFlower
Browse files

Update the default arguments for orbit.Controller train_and_evaluate() and...

Update the default arguments for orbit.Controller train_and_evaluate() and evaluate_continuously() to match the default for evaluate().

PiperOrigin-RevId: 335659533
parent 662a40be
...@@ -273,7 +273,7 @@ class Controller: ...@@ -273,7 +273,7 @@ class Controller:
def train_and_evaluate(self, def train_and_evaluate(self,
train_steps: int = None, train_steps: int = None,
eval_steps: int = None, eval_steps: int = -1,
eval_interval: int = None): eval_interval: int = None):
"""Runs interleaved training and evaluation. """Runs interleaved training and evaluation.
...@@ -285,7 +285,7 @@ class Controller: ...@@ -285,7 +285,7 @@ class Controller:
Args: Args:
train_steps: The global step count to train up to. train_steps: The global step count to train up to.
eval_steps: The number of steps to run during an evaluation. If None, this eval_steps: The number of steps to run during an evaluation. If -1, this
method will evaluate over the entire evaluation dataset. method will evaluate over the entire evaluation dataset.
eval_interval: The number of training steps to run between evaluations. If eval_interval: The number of training steps to run between evaluations. If
set, training will always stop every `eval_interval` steps, even if this set, training will always stop every `eval_interval` steps, even if this
...@@ -310,7 +310,7 @@ class Controller: ...@@ -310,7 +310,7 @@ class Controller:
self._maybe_save_checkpoint(check_interval=False) self._maybe_save_checkpoint(check_interval=False)
def evaluate_continuously(self, def evaluate_continuously(self,
steps: int = None, steps: int = -1,
timeout: Optional[Union[int, float]] = None, timeout: Optional[Union[int, float]] = None,
timeout_fn: Optional[Callable[[], bool]] = None): timeout_fn: Optional[Callable[[], bool]] = None):
"""Continuously monitors a directory and evaluates new checkpoints in it. """Continuously monitors a directory and evaluates new checkpoints in it.
...@@ -320,7 +320,8 @@ class Controller: ...@@ -320,7 +320,8 @@ class Controller:
checkpoints found there. checkpoints found there.
Args: Args:
steps: The number of steps to run when evaluating. steps: The number of steps to run when evaluating. If -1, this method will
evaluate over the entire evaluation dataset.
timeout: The maximum number of seconds to wait between checkpoints. See timeout: The maximum number of seconds to wait between checkpoints. See
tf.train.checkpoints_iterator documentation. tf.train.checkpoints_iterator documentation.
timeout_fn: Optional callable to call after a timeout. If the function timeout_fn: Optional callable to call after a timeout. If the function
......
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