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-rw-r--r--tensorflow/python/ops/distributions/transformed_distribution.py4
1 files changed, 2 insertions, 2 deletions
diff --git a/tensorflow/python/ops/distributions/transformed_distribution.py b/tensorflow/python/ops/distributions/transformed_distribution.py
index 09b26a9fb7..1be3819569 100644
--- a/tensorflow/python/ops/distributions/transformed_distribution.py
+++ b/tensorflow/python/ops/distributions/transformed_distribution.py
@@ -339,7 +339,7 @@ class TransformedDistribution(distribution_lib.Distribution):
self.distribution.event_shape_tensor()))
def _event_shape(self):
- # If there's a chance that the event_shape has been overriden, we return
+ # If there's a chance that the event_shape has been overridden, we return
# what we statically know about the `event_shape_override`. This works
# because: `_is_maybe_event_override` means `static_override` is `None` or a
# non-empty list, i.e., we don't statically know the `event_shape` or we do.
@@ -360,7 +360,7 @@ class TransformedDistribution(distribution_lib.Distribution):
self.distribution.batch_shape_tensor())
def _batch_shape(self):
- # If there's a chance that the batch_shape has been overriden, we return
+ # If there's a chance that the batch_shape has been overridden, we return
# what we statically know about the `batch_shape_override`. This works
# because: `_is_maybe_batch_override` means `static_override` is `None` or a
# non-empty list, i.e., we don't statically know the `batch_shape` or we do.