diff options
Diffstat (limited to 'tensorflow/contrib/learn/python/learn/experiment.py')
| -rw-r--r-- | tensorflow/contrib/learn/python/learn/experiment.py | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/tensorflow/contrib/learn/python/learn/experiment.py b/tensorflow/contrib/learn/python/learn/experiment.py index 491c4343bd..cd47b82d82 100644 --- a/tensorflow/contrib/learn/python/learn/experiment.py +++ b/tensorflow/contrib/learn/python/learn/experiment.py @@ -455,7 +455,7 @@ class Experiment(object): def train_and_evaluate(self): """Interleaves training and evaluation. - The frequency of evaluation is controlled by the contructor arg + The frequency of evaluation is controlled by the constructor arg `min_eval_frequency`. When this parameter is 0, evaluation happens only after training has completed. Note that evaluation cannot happen more frequently than checkpoints are taken. If no new snapshots are @@ -515,9 +515,9 @@ class Experiment(object): This differs from `train_and_evaluate` as follows: 1. The procedure will have train and evaluation in turns. The model - will be trained for a number of steps (usuallly smaller than `train_steps` + will be trained for a number of steps (usually smaller than `train_steps` if provided) and then be evaluated. `train_and_evaluate` will train the - model for `train_steps` (no small training iteraions). + model for `train_steps` (no small training iterations). 2. Due to the different approach this schedule takes, it leads to two differences in resource control. First, the resources (e.g., memory) used |