eager: Rename in_eager_mode to executing_eagerly and get rid of in_graph_mode.

This is in preparation to introduce one public, stable symbol: tf.executing_eagerly()
(i.e., part of moving APIs related to eager execution from "contrib" to a namespace
where we provide API stability guarantees)

PiperOrigin-RevId: 188212646

9 files changed, 55 insertions, 54 deletions

diff --git a/tensorflow/python/framework/constant_op.py b/tensorflow/python/framework/constant_op.py
index d3d8c9c154..782b505d6c 100644
--- a/tensorflow/python/framework/constant_op.py
+++ b/tensorflow/python/framework/constant_op.py
@@ -181,7 +181,7 @@ def constant(value, dtype=None, shape=None, name="Const", verify_shape=False):
     TypeError: if shape is incorrectly specified or unsupported.
   """
   ctx = context.context()
-  if not ctx.in_graph_mode():
+  if ctx.executing_eagerly():
     t = convert_to_eager_tensor(value, ctx, dtype)
     if shape is None:
       return t
diff --git a/tensorflow/python/framework/function.py b/tensorflow/python/framework/function.py
index caa604999c..14d72d8a3d 100644
--- a/tensorflow/python/framework/function.py
+++ b/tensorflow/python/framework/function.py
@@ -489,10 +489,10 @@ class _DefinedFunction(object):
 
     # Adds this function into 'g'.
     # pylint: disable=protected-access
-    if context.in_graph_mode():
-      g._add_function(self)
-    else:
+    if context.executing_eagerly():
       context.context().add_function_def(self.definition)
+    else:
+      g._add_function(self)
     # pylint: enable=protected-access
 
     # Ensures related sub-routines are defined in 'g', too.
diff --git a/tensorflow/python/framework/meta_graph.py b/tensorflow/python/framework/meta_graph.py
index 4c1bd736d7..4bb9941bb7 100644
--- a/tensorflow/python/framework/meta_graph.py
+++ b/tensorflow/python/framework/meta_graph.py
@@ -695,7 +695,7 @@ def import_scoped_meta_graph(meta_graph_or_file,
   Raises:
     ValueError: If the graph_def contains unbound inputs.
   """
-  if context.in_eager_mode():
+  if context.executing_eagerly():
     raise ValueError("Exporting/importing meta graphs is not supported when "
                      "eager execution is enabled.")
   if isinstance(meta_graph_or_file, meta_graph_pb2.MetaGraphDef):
@@ -856,7 +856,7 @@ def export_scoped_meta_graph(filename=None,
   Raises:
     ValueError: When the `GraphDef` is larger than 2GB.
   """
-  if context.in_eager_mode():
+  if context.executing_eagerly():
     raise ValueError("Exporting/importing meta graphs is not supported when "
                      "Eager Execution is enabled.")
   graph = graph or ops.get_default_graph()
diff --git a/tensorflow/python/framework/ops.py b/tensorflow/python/framework/ops.py
index 2a8319a19f..8ff247fdb1 100644
--- a/tensorflow/python/framework/ops.py
+++ b/tensorflow/python/framework/ops.py
@@ -395,10 +395,10 @@ class Tensor(_TensorLike):
         "Tensor._shape cannot be assigned, use Tensor.set_shape instead.")
 
   def __iter__(self):
-    if context.in_graph_mode():
+    if not context.executing_eagerly():
       raise TypeError(
-          "`Tensor` objects are not iterable when eager execution is not "
-          "enabled. To iterate over this tensor use `tf.map_fn`.")
+          "Tensor objects are not iterable when eager execution is not "
+          "enabled. To iterate over this tensor use tf.map_fn.")
     shape = self._shape_tuple()
     if shape is None:
       raise TypeError("Cannot iterate over a tensor with unknown shape.")
@@ -772,7 +772,7 @@ class _EagerTensorBase(Tensor):
       six.raise_from(core._status_to_exception(e.code, e.message), None)
 
     # Record the copy on tape and define backprop copy as well.
-    if not context.in_graph_mode():
+    if context.executing_eagerly():
       self_device = self.device
       def grad_fun(dresult):
         return [dresult._copy(device_name=self_device)]
@@ -993,7 +993,7 @@ def internal_convert_to_tensor(value,
 
   """
   if ctx is None: ctx = context.context()
-  if ctx.in_eager_mode():
+  if ctx.executing_eagerly():
     # Fast path for EagerTensors that don't need any conversion.
     if isinstance(value, EagerTensor):
       # Note that we don't check that value's dtype matches the dtype
@@ -4797,15 +4797,15 @@ def device(device_name_or_function):
   Raises:
     RuntimeError: If eager execution is enabled and a function is passed in.
   """
-  if context.in_graph_mode():
-    return get_default_graph().device(device_name_or_function)
-  else:
+  if context.executing_eagerly():
     # TODO(agarwal): support device functions in EAGER mode.
     if callable(device_name_or_function):
       raise RuntimeError(
           "tf.device does not support functions when eager execution "
           "is enabled.")
     return context.device(device_name_or_function)
+  else:
+    return get_default_graph().device(device_name_or_function)
 
 
 @tf_export("container")
@@ -4824,7 +4824,12 @@ def container(container_name):
 
 @tf_export("colocate_with")
 def colocate_with(op, ignore_existing=False):
-  if context.in_graph_mode():
+  if context.executing_eagerly():
+    if op is not None:
+      return device(op.device)
+    else:
+      return _NullContextmanager()
+  else:
     default_graph = get_default_graph()
     if isinstance(op, EagerTensor):
       if default_graph.building_function:
@@ -4833,11 +4838,6 @@ def colocate_with(op, ignore_existing=False):
         raise ValueError("Encountered an Eager-defined Tensor during graph "
                          "construction, but a function was not being built.")
     return default_graph.colocate_with(op, ignore_existing)
-  else:
-    if op is not None:
-      return device(op.device)
-    else:
-      return _NullContextmanager()
 
 
 @tf_export("control_dependencies")
@@ -4857,10 +4857,10 @@ def control_dependencies(control_inputs):
    A context manager that specifies control dependencies for all
    operations constructed within the context.
   """
-  if context.in_graph_mode():
-    return get_default_graph().control_dependencies(control_inputs)
-  else:
+  if context.executing_eagerly():
     return _NullContextmanager()
+  else:
+    return get_default_graph().control_dependencies(control_inputs)
 
 
 class _DefaultStack(threading.local):
@@ -5123,7 +5123,7 @@ def init_scope():
   """
   # pylint: enable=g-doc-return-or-yield,line-too-long
 
-  if context.in_eager_mode():
+  if context.executing_eagerly():
     # Fastpath.
     with tape.stop_recording():
       yield
@@ -5705,7 +5705,7 @@ class name_scope(object):  # pylint: disable=invalid-name
     self._default_name = default_name
     self._values = values
     self._ctx = context.context()
-    self._in_eager_mode = self._ctx.in_eager_mode()
+    self._in_eager_mode = self._ctx.executing_eagerly()
 
   def __enter__(self):
     """Start the scope block.
@@ -5884,7 +5884,7 @@ def get_from_proto_function(collection_name):
 
 
 def _assert_collection_is_ok(collection_name):
-  if context.in_eager_mode():
+  if context.executing_eagerly():
     if collection_name in GraphKeys._VARIABLE_COLLECTIONS:  # pylint: disable=protected-access
       raise ValueError("When Eager Execution is enabled, variable "
                        "collections are not supported.")
diff --git a/tensorflow/python/framework/ops_test.py b/tensorflow/python/framework/ops_test.py
index 55576f0e88..c294f830bc 100644
--- a/tensorflow/python/framework/ops_test.py
+++ b/tensorflow/python/framework/ops_test.py
@@ -1763,7 +1763,13 @@ class ControlDependenciesTest(test_util.TensorFlowTestCase):
       return constant_op.constant(2.0)
     future.calls = 0
 
-    if context.in_graph_mode():
+    if context.executing_eagerly():
+      a = constant_op.constant(1.0)
+      b = future()
+      with ops.control_dependencies([a, b]):
+        c = constant_op.constant(3.0)
+      self.assertEqual(future.calls, 1)
+    else:
       g = ops.Graph()
       with g.as_default():
         a = constant_op.constant(1.0)
@@ -1772,12 +1778,6 @@ class ControlDependenciesTest(test_util.TensorFlowTestCase):
           c = constant_op.constant(3.0)
       self.assertEqual(c.op.control_inputs, [a.op, b.op])
       self.assertEqual(future.calls, 1)
-    else:
-      a = constant_op.constant(1.0)
-      b = future()
-      with ops.control_dependencies([a, b]):
-        c = constant_op.constant(3.0)
-      self.assertEqual(future.calls, 1)
 
   def testBasicWithConversion(self):
     g = ops.Graph()
@@ -2150,11 +2150,11 @@ class InitScopeTest(test_util.TensorFlowTestCase):
           with ops.init_scope():
             # Because g is building a function, init_scope should
             # escape out to the eager context.
-            self.assertTrue(context.in_eager_mode())
+            self.assertTrue(context.executing_eagerly())
           # g should be reinstated as the default graph, and the
           # graph context should be re-entered.
           self.assertIs(g, ops.get_default_graph())
-          self.assertTrue(context.in_graph_mode())
+          self.assertFalse(context.executing_eagerly())
 
   def testStaysInEagerWhenOnlyEagerContextActive(self):
     with context.eager_mode():
@@ -2277,12 +2277,13 @@ class InitScopeTest(test_util.TensorFlowTestCase):
     with context.eager_mode():
       def foo():
         with ops.name_scope("inner"), ops.init_scope():
-          if context.in_graph_mode():
-            self.assertEqual(ops.get_name_scope(), "inner")
-          else:
+          if context.executing_eagerly():
             # A trailing slash is always appended when eager execution is
             # enabled.
             self.assertEqual(context.context().scope_name, "inner/")
+          else:
+            self.assertEqual(ops.get_name_scope(), "inner")
+
       foo()
       self.assertEqual(ops.get_name_scope(), "")
       foo_compiled = eager_function.defun(foo)
diff --git a/tensorflow/python/framework/random_seed.py b/tensorflow/python/framework/random_seed.py
index 1e74a790a3..b724432e00 100644
--- a/tensorflow/python/framework/random_seed.py
+++ b/tensorflow/python/framework/random_seed.py
@@ -52,20 +52,20 @@ def get_seed(op_seed):
     A tuple of two integers that should be used for the local seed of this
     operation.
   """
-  is_graph_mode = context.in_graph_mode()
+  eager = context.executing_eagerly()
 
-  if is_graph_mode:
-    global_seed = ops.get_default_graph().seed
-  else:
+  if eager:
     global_seed = context.global_seed()
+  else:
+    global_seed = ops.get_default_graph().seed
 
   if global_seed is not None:
     if op_seed is None:
       # pylint: disable=protected-access
-      if is_graph_mode:
-        op_seed = ops.get_default_graph()._last_id
-      else:
+      if eager:
         op_seed = context.internal_operation_seed()
+      else:
+        op_seed = ops.get_default_graph()._last_id
 
     seeds = _truncate_seed(global_seed), _truncate_seed(op_seed)
   else:
@@ -176,7 +176,7 @@ def set_random_seed(seed):
   Args:
     seed: integer.
   """
-  if context.in_graph_mode():
-    ops.get_default_graph().seed = seed
-  else:
+  if context.executing_eagerly():
     context.set_global_seed(seed)
+  else:
+    ops.get_default_graph().seed = seed
diff --git a/tensorflow/python/framework/random_seed_test.py b/tensorflow/python/framework/random_seed_test.py
index b4c98ab8b2..1944922686 100644
--- a/tensorflow/python/framework/random_seed_test.py
+++ b/tensorflow/python/framework/random_seed_test.py
@@ -40,13 +40,13 @@ class RandomSeedTest(test.TestCase):
         ((2**31 - 1, 0), (0, 2**31 - 1)),  # Don't wrap to (0, 0) either
         ((0, 2**31 - 1), (0, 2**31 - 1)),  # Wrapping for the other argument
     ]
-    if context.in_graph_mode():
-      # 0 will be the default_graph._lastid.
-      test_cases.append(((1, None), (1, 0)))
-    else:
+    if context.executing_eagerly():
       # operation seed is random number generated based on global seed.
       # it's not tested due to possibility of platform or version difference.
       pass
+    else:
+      # 0 will be the default_graph._lastid.
+      test_cases.append(((1, None), (1, 0)))
     for tc in test_cases:
       tinput, toutput = tc[0], tc[1]
       random_seed.set_random_seed(tinput[0])
diff --git a/tensorflow/python/framework/tensor_util.py b/tensorflow/python/framework/tensor_util.py
index 135562e831..984bcecdfe 100644
--- a/tensorflow/python/framework/tensor_util.py
+++ b/tensorflow/python/framework/tensor_util.py
@@ -828,7 +828,7 @@ def constant_value_as_shape(tensor):  # pylint: disable=invalid-name
   Returns:
     A `TensorShape` based on the constant value of the given `tensor`.
   """
-  if context.in_eager_mode():
+  if context.executing_eagerly():
     return tensor_shape.as_shape(
         [dim if dim != -1 else None for dim in tensor.numpy()])
 
diff --git a/tensorflow/python/framework/test_util.py b/tensorflow/python/framework/test_util.py
index 1c8398e686..9fc1154201 100644
--- a/tensorflow/python/framework/test_util.py
+++ b/tensorflow/python/framework/test_util.py
@@ -816,7 +816,7 @@ class TensorFlowTestCase(googletest.TestCase):
     Returns:
       tensors numpy values.
     """
-    if context.in_eager_mode():
+    if context.executing_eagerly():
       return self._eval_helper(tensors)
     else:
       sess = ops.get_default_session()