Update docstrings of checkpoint_path arguments
@@ -172,7 +172,7 @@ class Runner(object):
Args:
num_devices: Number of devices to use for training.
with_eval: Enable evaluation during training.
- checkpoint_path: The checkpoint path to load the model weights from it.
+ checkpoint_path: The checkpoint path to load the model weights from.
hvd: Optional Horovod module.
return_summary: Return a summary of the training from this function.
fallback_to_cpu: If no GPU is detected, allow the training to run on CPU.
@@ -306,7 +306,7 @@ class Runner(object):
``eval_features_file`` from the data configuration.
labels_file: The output labels file to evaluate. If not set, will load
``eval_labels_file`` from the data configuration.
- checkpoint_path: The checkpoint path to load the model weights from it.
+ checkpoint_path: The checkpoint path to load the model weights from.
Returns:
A dict of evaluation metrics.
@@ -407,7 +407,7 @@ class Runner(object):
features_file: The file(s) to infer from.
predictions_file: If set, predictions are saved in this file, otherwise
they are printed on the standard output.
- checkpoint_path: Path of a specific checkpoint to predict. If ``None``,
+ checkpoint_path: Path to a specific checkpoint to load. If ``None``,
the latest is used.
log_time: If ``True``, several time metrics will be printed in the logs at
the end of the inference loop.
@@ -455,7 +455,7 @@ class Runner(object):
Args:
features_file: The input file.
predictions_file: The predictions file to score.
- checkpoint_path: Path of a specific checkpoint to use. If ``None``,
+ checkpoint_path: Path to specific checkpoint to load. If ``None``,
the latest is used.
output_file: The file where the scores are saved. Otherwise, they will be
printed on the standard output.
