Merge pull request #23998 from ManHyuk:fix_typo

PiperOrigin-RevId: 223878153

tensorflow/compiler/xla/service/algebraic_simplifier_test.cc

@@ -1672,7 +1672,7 @@ TEST_F(AlgebraicSimplifierTest, ReshapeOfTransposeOfRngToRng) {
       (AlgebraicSimplifierOptions(bitcasting_callback())));
   EXPECT_TRUE(simplifier.Run(m.get()).ValueOrDie());
 
-  // Verify that that reshape(transpose(rng)) is replace by a single rng of the
+  // Verify that reshape(transpose(rng)) is replace by a single rng of the
   // same shape as the reshape.
   EXPECT_THAT(computation->root_instruction(), GmockMatch(m::Rng()));
   EXPECT_TRUE(ShapeUtil::Equal(computation->root_instruction()->shape(),

tensorflow/compiler/xla/shape_util.cc

@@ -1168,7 +1168,7 @@ Status ForEachMutableSubshapeHelper(
   // Let the argument `permutation` be P.  This is a permutation over `shape`'s
   // dimensions, so our return value will be a shape with dims P.I = P.  Our
   // goal is to construct a layout permutation L* that we can apply to P such
-  // that that the physical dimension ordering of the returned shape is the same
+  // that the physical dimension ordering of the returned shape is the same
   // as that of the original shape, namely L'.
   //
   // Our returned shape has dims P and layout L*, so its in-memory layout is

tensorflow/python/ops/ragged/ragged_tensor.py

@@ -64,7 +64,7 @@ class RaggedTensor(object):
   a 3-D `RaggedTensor` that stores the fixed-size word embedding for each
   word in a sentence, for each sentence in a batch, could be written as
   `[num_sentences, (num_words), embedding_size]`.  The parentheses around
-  `(num_words)` indicate that that dimension is ragged, and that the length
+  `(num_words)` indicate that dimension is ragged, and that the length
   of each element list in that dimension may vary for each item.
 
   ### Component Tensors