diff --git a/tensorflow/c/eager/c_api_experimental_test.cc b/tensorflow/c/eager/c_api_experimental_test.cc
index 53984c0e6c0..f15bdef789a 100644
--- a/tensorflow/c/eager/c_api_experimental_test.cc
+++ b/tensorflow/c/eager/c_api_experimental_test.cc
@@ -267,10 +267,10 @@ TEST(CAPI, MonitoringMultipleSampler) {
   TFE_MonitoringSamplerCellAdd(cell1, 2.0);
   TF_Buffer* result1 = TF_NewBuffer();
   TFE_MonitoringSamplerCellValue(cell1, result1);
-  tensorflow::HistogramProto hitogram1;
-  EXPECT_TRUE(hitogram1.ParseFromString(
+  tensorflow::HistogramProto histogram1;
+  EXPECT_TRUE(histogram1.ParseFromString(
       {reinterpret_cast<const char*>(result1->data), result1->length}));
-  EXPECT_EQ(hitogram1.sum(), 3.0);
+  EXPECT_EQ(histogram1.sum(), 3.0);
   delete result1;
 
   auto* sampler2 = TFE_MonitoringNewSampler2("test/sampler2", buckets, status,
@@ -281,10 +281,10 @@ TEST(CAPI, MonitoringMultipleSampler) {
   TFE_MonitoringSamplerCellAdd(cell2, 3.0);
   TF_Buffer* result2 = TF_NewBuffer();
   TFE_MonitoringSamplerCellValue(cell2, result2);
-  tensorflow::HistogramProto hitogram2;
-  EXPECT_TRUE(hitogram2.ParseFromString(
+  tensorflow::HistogramProto histogram2;
+  EXPECT_TRUE(histogram2.ParseFromString(
       {reinterpret_cast<const char*>(result2->data), result2->length}));
-  EXPECT_EQ(hitogram2.sum(), 5.0);
+  EXPECT_EQ(histogram2.sum(), 5.0);
   delete result2;
 
   TFE_MonitoringDeleteBuckets(buckets);
diff --git a/tensorflow/compiler/xla/client/client.h b/tensorflow/compiler/xla/client/client.h
index eff8713ac34..5e26f64002b 100644
--- a/tensorflow/compiler/xla/client/client.h
+++ b/tensorflow/compiler/xla/client/client.h
@@ -42,7 +42,7 @@ class Client {
 
   // Compile the computation with the given argument shapes and returns the
   // handle to the compiled executable. The compiled executable is cached on the
-  // service, and the returned handle can be used for exection without
+  // service, and the returned handle can be used for execution without
   // re-compile.
   // * The shape and layout of the arguments being executed with will affect how
   //   the computation is compiled. If argument_shapes is empty, the parameters'
diff --git a/tensorflow/compiler/xla/service/cpu/runtime_matmul_mkl.cc b/tensorflow/compiler/xla/service/cpu/runtime_matmul_mkl.cc
index 8dc5f3c93b6..ac1e64f8adf 100644
--- a/tensorflow/compiler/xla/service/cpu/runtime_matmul_mkl.cc
+++ b/tensorflow/compiler/xla/service/cpu/runtime_matmul_mkl.cc
@@ -110,7 +110,7 @@ __xla_cpu_runtime_MKLSingleThreadedMatMulF32(const void* run_options_ptr,
                                              int64 m, int64 n, int64 k,
                                              int32 transpose_lhs,
                                              int32 transpose_rhs) {
-  // Set the thread number to 1 for single threaded excution.
+  // Set the thread number to 1 for single threaded execution.
   int prev_num_threads = mkl_set_num_threads_local(1);
   MatMulF32(nullptr, out, lhs, rhs, m, n, k, transpose_lhs, transpose_rhs);
   // Set thread number back to the previous number.
@@ -123,7 +123,7 @@ __xla_cpu_runtime_MKLSingleThreadedMatMulF64(const void* run_options_ptr,
                                              double* rhs, int64 m, int64 n,
                                              int64 k, int32 transpose_lhs,
                                              int32 transpose_rhs) {
-  // Set the thread number to 1 for single threaded excution.
+  // Set the thread number to 1 for single threaded execution.
   int prev_num_threads = mkl_set_num_threads_local(1);
   MatMulF64(nullptr, out, lhs, rhs, m, n, k, transpose_lhs, transpose_rhs);
   // Set thread number back to the previous number.
diff --git a/tensorflow/contrib/eager/python/examples/workshop/1_basic.ipynb b/tensorflow/contrib/eager/python/examples/workshop/1_basic.ipynb
index 75cb3f8227f..17121cc21f8 100644
--- a/tensorflow/contrib/eager/python/examples/workshop/1_basic.ipynb
+++ b/tensorflow/contrib/eager/python/examples/workshop/1_basic.ipynb
@@ -189,7 +189,7 @@
         "\n",
         "Implement a python function `bisecting_line_search(f, a, b, epsilon)` which returns a value such that `tf.abs(f(value)) < epsilon`.\n",
         "\n",
-        "One thing to keep in mind: python's `==` opertor is not overloaded on Tensors, so you need to use `tf.equal` to compare for equality."
+        "One thing to keep in mind: python's `==` operator is not overloaded on Tensors, so you need to use `tf.equal` to compare for equality."
       ]
     },
     {
diff --git a/tensorflow/python/keras/distribute/distributed_training_utils.py b/tensorflow/python/keras/distribute/distributed_training_utils.py
index 98cb6c8857e..8361409a58e 100644
--- a/tensorflow/python/keras/distribute/distributed_training_utils.py
+++ b/tensorflow/python/keras/distribute/distributed_training_utils.py
@@ -893,7 +893,7 @@ def _make_execution_function_with_cloning(model, mode):
     distributed_function = _make_graph_execution_function(model, mode)
 
   # We cache the distributed execution function on the model since creating
-  # distributed models and exection functions are expensive.
+  # distributed models and execution functions are expensive.
   distributed_model._distributed_function = distributed_function
   distributed_model._recompile_exec_function = False
   return distributed_function