[Documentation]: Fix #19657

PiperOrigin-RevId: 200213440

1 files changed, 14 insertions, 0 deletions

diff --git a/tensorflow/python/data/ops/dataset_ops.py b/tensorflow/python/data/ops/dataset_ops.py
index 597f92048e..7c1e9dd754 100644
--- a/tensorflow/python/data/ops/dataset_ops.py
+++ b/tensorflow/python/data/ops/dataset_ops.py
@@ -223,6 +223,13 @@ class Dataset(object):
   def from_tensors(tensors):
     """Creates a `Dataset` with a single element, comprising the given tensors.
 
+    Note that if `tensors` contains a NumPy array, and eager execution is not
+    enabled, the values will be embedded in the graph as one or more
+    @{tf.constant} operations. For large datasets (> 1 GB), this can waste
+    memory and run into byte limits of graph serialization.  If tensors contains
+    one or more large NumPy arrays, consider the alternative described in
+    @{$programmers_guide/datasets#consuming_numpy_arrays$this guide}.
+
     Args:
       tensors: A nested structure of tensors.
 
@@ -235,6 +242,13 @@ class Dataset(object):
   def from_tensor_slices(tensors):
     """Creates a `Dataset` whose elements are slices of the given tensors.
 
+    Note that if `tensors` contains a NumPy array, and eager execution is not
+    enabled, the values will be embedded in the graph as one or more
+    @{tf.constant} operations. For large datasets (> 1 GB), this can waste
+    memory and run into byte limits of graph serialization.  If tensors contains
+    one or more large NumPy arrays, consider the alternative described in
+    @{$programmers_guide/datasets#consuming_numpy_arrays$this guide}.
+
     Args:
       tensors: A nested structure of tensors, each having the same size in the
         0th dimension.