diff --git a/tensorflow/python/eager/def_function_xla_jit_test.py b/tensorflow/python/eager/def_function_xla_jit_test.py
index b63a3b434d4..78d44a81b0b 100644
--- a/tensorflow/python/eager/def_function_xla_jit_test.py
+++ b/tensorflow/python/eager/def_function_xla_jit_test.py
@@ -29,6 +29,7 @@ from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import control_flow_ops
 from tensorflow.python.ops import control_flow_util
 from tensorflow.python.ops import math_ops
+from tensorflow.python.ops import random_ops
 from tensorflow.python.ops import resource_variable_ops
 from tensorflow.python.ops import tensor_array_ops
 from tensorflow.python.platform import test
@@ -385,6 +386,24 @@ class DefFunctionTest(test.TestCase):
     f64_input = constant_op.constant([1.1, 2.2, 3.3], dtype=dtypes.float64)
     self.assertAllClose([1.1, 3.3, 6.6], f(f64_input))
 
+  def testNoExcessiveRetracing(self):
+    inner_retracings = 0
+
+    @def_function.function(experimental_compile=True)
+    def inner(a, b):
+      nonlocal inner_retracings
+      inner_retracings += 1
+      return a * b + a
+
+    def outer(a, b):
+      return inner(a, b)
+
+    func_input = random_ops.random_normal([10, 10])
+    for _ in range(2):
+      def_function.function(outer)(func_input, func_input)
+
+    self.assertEqual(inner_retracings, 1)
+
 
 if __name__ == '__main__':
   ops.enable_eager_execution()
diff --git a/tensorflow/python/eager/function.py b/tensorflow/python/eager/function.py
index a40eaf886b3..c02318cb814 100644
--- a/tensorflow/python/eager/function.py
+++ b/tensorflow/python/eager/function.py
@@ -2981,9 +2981,10 @@ class Function(object):
     if not executing_eagerly:
       # We want to force function retracing for each different
       # XLAControlFlowContext, so add `xla_context_id` to the cache key.
-      tpu_context = _enclosing_xla_context()
-      if tpu_context is not None:
-        xla_context_id = id(tpu_context)
+      xla_context = _enclosing_xla_context()
+      if xla_context is not None and \
+            xla_context.RequiresUniqueFunctionRetracing():
+        xla_context_id = id(xla_context)
 
       with ops.init_scope():
         # The graph, or whether we're executing eagerly, should be a part of the
diff --git a/tensorflow/python/ops/control_flow_ops.py b/tensorflow/python/ops/control_flow_ops.py
index 3398308d42e..748f842a9e0 100644
--- a/tensorflow/python/ops/control_flow_ops.py
+++ b/tensorflow/python/ops/control_flow_ops.py
@@ -3682,6 +3682,11 @@ class XLAControlFlowContext(ControlFlowContext):
   def AddValue(self, x):
     return x
 
+  def RequiresUniqueFunctionRetracing(self):
+    """Returns whether the tf.function should be retraced if the context changes.
+    """
+    return False
+
 
 def from_control_flow_context_def(context_def, import_scope=None):
   """Deserializes `context_def` into the appropriate ControlFlowContext.
diff --git a/tensorflow/python/tpu/tpu.py b/tensorflow/python/tpu/tpu.py
index 28eba69b7da..ce3aaa8a058 100644
--- a/tensorflow/python/tpu/tpu.py
+++ b/tensorflow/python/tpu/tpu.py
@@ -639,6 +639,12 @@ class TPUReplicateContext(control_flow_ops.XLAControlFlowContext):
   def GetControlPivot(self):
     return self._pivot
 
+  def RequiresUniqueFunctionRetracing(self):
+    # More context: b/158152827. TPU stack uses the TPUReplicateContext to
+    # create replicated variable handles and cluster TPU computations, thus we
+    # always retrace a tf.function when the wrapped TPUReplicateContext changes.
+    return True
+
 
 class OutsideCompilationV2Context(control_flow_ops.ControlFlowContext):
   """The context for outside compilation in Tensorflow 2.0.