Add disable_mixed_precision_graph_rewrite function for unit testing

PiperOrigin-RevId: 248036105

tensorflow/python/training/experimental/mixed_precision.py

@@ -169,3 +169,54 @@ def _enable_mixed_precision_graph_rewrite_base(opt, loss_scale,
   config.set_optimizer_experimental_options({'auto_mixed_precision': True})
   mixed_precision_global_state.mixed_precision_is_enabled = True
   return opt
+
+
+@tf_export('train.experimental.disable_mixed_precision_graph_rewrite', v1=[])
+def disable_mixed_precision_graph_rewrite():
+  """Disables the mixed precision graph rewrite.
+
+  After this is called, the mixed precision graph rewrite will no longer run for
+  tf.functions, and so float32 operations will no longer be converted to
+  float16.
+
+  This does not undo the effects of loss scaling. Any optimizers wrapped with a
+  LossScaleOptimizer will continue to do loss scaling, although this loss
+  scaling will no longer be useful, as the graph rewrite no longer converts
+  tf.functions to use float16.
+
+  This function is useful for unit testing. A unit test can test using the mixed
+  precision graph rewrite, then disable it so future unit tests continue using
+  float32.
+  """
+  if not mixed_precision_global_state.mixed_precision_is_enabled:
+    tf_logging.warn('disable_mixed_precision_graph_rewrite() called when mixed '
+                    'precision is already disabled.')
+  config.set_optimizer_experimental_options({'auto_mixed_precision': False})
+  mixed_precision_global_state.mixed_precision_is_enabled = False
+
+
+@tf_export(v1=['train.experimental.disable_mixed_precision_graph_rewrite'])
+def disable_mixed_precision_graph_rewrite_v1():
+  """Disables the mixed precision graph rewrite.
+
+  After this is called, the mixed precision graph rewrite will no longer run for
+  new Sessions, and so float32 operations will no longer be converted to float16
+  in such Sessions. However, any existing Sessions will continue to have the
+  graph rewrite enabled if they were created after
+  `enable_mixed_precision_graph_rewrite` was called but before
+  `disable_mixed_precision_graph_rewrite` was called.
+
+  This does not undo the effects of loss scaling. Any optimizers wrapped with a
+  LossScaleOptimizer will continue to do loss scaling, although this loss
+  scaling will no longer be useful if the optimizer is used in new Sessions, as
+  the graph rewrite no longer converts the graph to use float16.
+
+  This function is useful for unit testing. A unit tests can test using the
+  mixed precision graph rewrite, then disable it so future unit tests continue
+  using float32. If this is done, unit tests should not share a single session,
+  as `enable_mixed_precision_graph_rewrite` and
+  `disable_mixed_precision_graph_rewrite` have no effect on existing sessions.
+  """
+  # We only have a separate V1 version of this function, because the V1
+  # docstring mentions sessions.
+  disable_mixed_precision_graph_rewrite()

tensorflow/python/training/experimental/mixed_precision_test.py

@@ -58,22 +58,15 @@ class MixedPrecisionTest(test.TestCase, parameterized.TestCase):
     # to ignore performance and always transform the graph.
     self._original_ignore_perf_value = os.getenv(self.IGNORE_PERF_VAR)
     os.environ[self.IGNORE_PERF_VAR] = '1'
-    # Set global variables to their original state, in case other tests modified
-    # them
-    mixed_precision_global_state.mixed_precision_is_enabled = False
-    mixed_precision_global_state.non_mixed_precision_session_created = False
 
   def tearDown(self):
-    # Set auto_mixed_precision back to it's default value.
-    config.set_optimizer_experimental_options({'auto_mixed_precision': False})
     # Set the IGNORE_PERF_VAR variable back to it's original value.
     if self._original_ignore_perf_value is not None:
       os.environ[self.IGNORE_PERF_VAR] = self._original_ignore_perf_value
     else:
       del os.environ[self.IGNORE_PERF_VAR]
-    # Revert global variables
+
-    mixed_precision_global_state.mixed_precision_is_enabled = False
+    mixed_precision.disable_mixed_precision_graph_rewrite()
-    mixed_precision_global_state.non_mixed_precision_session_created = False
     super(MixedPrecisionTest, self).tearDown()
 
   @test_util.run_in_graph_and_eager_modes
@@ -141,6 +134,10 @@ class MixedPrecisionTest(test.TestCase, parameterized.TestCase):
       self.assertEqual(f().numpy(), float('Inf'))
       # Outside a def_function.function, the grappler pass will not be applied.
       self.assertAlmostEqual(overflow_in_float16().numpy(), 2 ** 20)
+
+      # Test disabling mixed precision.
+      mixed_precision.disable_mixed_precision_graph_rewrite()
+      self.assertEqual(f().numpy(), 2 ** 20)
     else:
       with session.Session() as sess:
         out = overflow_in_float16()
@@ -154,8 +151,19 @@ class MixedPrecisionTest(test.TestCase, parameterized.TestCase):
         sess.run(var.initializer)
         self.assertEqual(sess.run(out), float('Inf'))
 
+      # Test disabling mixed precision.
+      mixed_precision.disable_mixed_precision_graph_rewrite()
+      with session.Session() as sess:
+        out = overflow_in_float16()
+        sess.run(var.initializer)
+        self.assertAlmostEqual(sess.run(out), 2 ** 20)
+
   @test.mock.patch.object(tf_logging, 'warn')
   def test_warn_if_session_already_exists(self, mock_warn):
+    # Set this to False, so Sessions created in previous tests do not trigger
+    # the warning.
+    mixed_precision_global_state.non_mixed_precision_session_created = False
+
     with session.Session():
       enable_mixed_precision_graph_rewrite(gradient_descent_v2.SGD(1.0))
       mock_warn.assert_any_call(
@@ -165,6 +173,10 @@ class MixedPrecisionTest(test.TestCase, parameterized.TestCase):
 
   @test.mock.patch.object(tf_logging, 'warn')
   def test_do_not_warn_if_session_does_not_already_exist(self, mock_warn):
+    # Set this to False, so Sessions created in previous tests do not trigger
+    # the warning.
+    mixed_precision_global_state.non_mixed_precision_session_created = False
+
     enable_mixed_precision_graph_rewrite(gradient_descent_v2.SGD(1.0))
     with session.Session():
       # Make sure the "You already have existing Sessions" warning was not

tensorflow/tools/api/golden/v1/tensorflow.train.experimental.pbtxt

@@ -8,6 +8,10 @@ tf_module {
     name: "PythonState"
     mtype: "<type \'type\'>"
   }
+  member_method {
+    name: "disable_mixed_precision_graph_rewrite"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
   member_method {
     name: "enable_mixed_precision_graph_rewrite"
     argspec: "args=[\'opt\', \'loss_scale\'], varargs=None, keywords=None, defaults=[\'dynamic\'], "

tensorflow/tools/api/golden/v2/tensorflow.train.experimental.pbtxt

@@ -4,6 +4,10 @@ tf_module {
     name: "PythonState"
     mtype: "<type \'type\'>"
   }
+  member_method {
+    name: "disable_mixed_precision_graph_rewrite"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
   member_method {
     name: "enable_mixed_precision_graph_rewrite"
     argspec: "args=[\'opt\', \'loss_scale\'], varargs=None, keywords=None, defaults=[\'dynamic\'], "