Fix documentation markdown

PiperOrigin-RevId: 203019816

1 files changed, 3 insertions, 3 deletions

diff --git a/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py b/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py
index 14e025973e..49cd318b89 100644
--- a/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py
+++ b/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py
@@ -216,8 +216,8 @@ class _SIGNAL(object):
 class TPUEstimatorSpec(model_fn_lib._TPUEstimatorSpec):  # pylint: disable=protected-access
   """Ops and objects returned from a `model_fn` and passed to `TPUEstimator`.
 
-  See `EstimatorSpec` for `mode`, 'predictions, 'loss', 'train_op', and
-  'export_outputs`.
+  See `EstimatorSpec` for `mode`, `predictions`, `loss`, `train_op`, and
+  `export_outputs`.
 
   For evaluation, `eval_metrics `is a tuple of `metric_fn` and `tensors`, where
   `metric_fn` runs on CPU to generate metrics and `tensors` represents the
@@ -231,7 +231,7 @@ class TPUEstimatorSpec(model_fn_lib._TPUEstimatorSpec):  # pylint: disable=prote
   size is the first dimension. Once all tensors are available at CPU host from
   all shards, they are concatenated (on CPU) and passed as positional arguments
   to the `metric_fn` if `tensors` is list or keyword arguments if `tensors` is
-  dict. `metric_fn` takes the `tensors` and returns a dict from metric string
+  a dict. `metric_fn` takes the `tensors` and returns a dict from metric string
   name to the result of calling a metric function, namely a `(metric_tensor,
   update_op)` tuple. See `TPUEstimator` for MNIST example how to specify the
   `eval_metrics`.