Removing experimental from run_functions_eagerly. Also removed all references for the experimental one from documentation.

PiperOrigin-RevId: 309036487
Change-Id: I91ab0f8857387c337f329c13e78ffba312ae362c

tensorflow/python/autograph/g3doc/reference/debugging.md

@@ -62,7 +62,7 @@ Adding a call to `tf.config.experimental_execute_functions_eagerly` before
 executing the function will land the debugger in the original code instead:
 
 ```
-tf.config.experimental_run_functions_eagerly(True)
+tf.config.run_functions_eagerly(True)
 f(1)
 ```
 

tensorflow/python/eager/context.py

@@ -1793,7 +1793,7 @@ def executing_eagerly():
   cases.
 
   *  Executing inside `tf.function`, unless under `tf.init_scope` or
-     `tf.config.experimental_run_functions_eagerly(True)` is previously called.
+     `tf.config.run_functions_eagerly(True)` is previously called.
   *  Executing inside a transformation function for `tf.dataset`.
   *  `tf.compat.v1.disable_eager_execution()` is called.
 
@@ -1815,8 +1815,8 @@ def executing_eagerly():
 
   Inside `tf.function` after
 
-  `tf.config.experimental_run_functions_eagerly(True)` is called:
-  >>> tf.config.experimental_run_functions_eagerly(True)
+  `tf.config.run_functions_eagerly(True)` is called:
+  >>> tf.config.run_functions_eagerly(True)
   >>> @tf.function
   ... def fn():
   ...   with tf.init_scope():
@@ -1825,7 +1825,7 @@ def executing_eagerly():
   >>> fn()
   True
   True
-  >>> tf.config.experimental_run_functions_eagerly(False)
+  >>> tf.config.run_functions_eagerly(False)
 
   Inside a transformation function for `tf.dataset`:
 
@@ -1858,7 +1858,7 @@ def executing_eagerly_v1():
   this API might return `False` in the following use cases.
 
   *  Executing inside `tf.function`, unless under `tf.init_scope` or
-     `tf.config.experimental_run_functions_eagerly(True)` is previously called.
+     `tf.config.run_functions_eagerly(True)` is previously called.
   *  Executing inside a transformation function for `tf.dataset`.
   *  `tf.compat.v1.disable_eager_execution()` is called.
 
@@ -1881,9 +1881,9 @@ def executing_eagerly_v1():
   False
 
   Inside `tf.function`
-  after  `tf.config.experimental_run_functions_eagerly(True)` is called:
+  after  `tf.config.run_functions_eagerly(True)` is called:
 
-  >>> tf.config.experimental_run_functions_eagerly(True)
+  >>> tf.config.run_functions_eagerly(True)
   >>> @tf.function
   ... def fn():
   ...   with tf.init_scope():
@@ -1892,7 +1892,7 @@ def executing_eagerly_v1():
   >>> fn()
   True
   True
-  >>> tf.config.experimental_run_functions_eagerly(False)
+  >>> tf.config.run_functions_eagerly(False)
 
   Inside a transformation function for `tf.dataset`:
 

tensorflow/python/eager/def_function.py

@@ -41,6 +41,7 @@ from tensorflow.python.ops import resource_variable_ops
 from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.profiler import traceme
 from tensorflow.python.training.tracking import base as trackable
+from tensorflow.python.util import deprecation
 from tensorflow.python.util import nest
 from tensorflow.python.util import object_identity
 from tensorflow.python.util import tf_decorator
@@ -305,8 +306,11 @@ class UnliftedInitializerVariable(resource_variable_ops.UninitializedVariable):
 RUN_FUNCTIONS_EAGERLY = False
 
 
+@deprecation.deprecated(
+    None,
+    "Use tf.config.run_functions_eagerly instead of the experimental version.")
 @tf_export("config.experimental_run_functions_eagerly")
-def run_functions_eagerly(run_eagerly):
+def experimental_run_functions_eagerly(run_eagerly):
   """Enables / disables eager execution of `tf.function`s.
 
   Calling `tf.config.experimental_run_functions_eagerly(True)` will make all
@@ -345,6 +349,60 @@ def run_functions_eagerly(run_eagerly):
   Calling `tf.config.experimental_run_functions_eagerly(False)` will undo this
   behavior.
 
+  Note: This flag has no effect on functions passed into tf.data transformations
+  as arguments. tf.data functions are never executed eagerly and are always
+  executed as a compiled Tensorflow Graph.
+
+  Args:
+    run_eagerly: Boolean. Whether to run functions eagerly.
+  """
+  return run_functions_eagerly(run_eagerly)
+
+
+@tf_export("config.run_functions_eagerly")
+def run_functions_eagerly(run_eagerly):
+  """Enables / disables eager execution of `tf.function`s.
+
+  Calling `tf.config.run_functions_eagerly(True)` will make all
+  invocations of `tf.function` run eagerly instead of running as a traced graph
+  function.
+
+  This can be useful for debugging or profiling. For example, let's say you
+  implemented a simple iterative sqrt function, and you want to collect the
+  intermediate values and plot the convergence.  Appending the values to a list
+  in `@tf.function` normally wouldn't work since it will just record the Tensors
+  being traced, not the values.  Instead, you can do the following.
+
+  >>> ys = []
+  >>>
+  >>> @tf.function
+  ... def sqrt(x):
+  ...   y = x / 2
+  ...   d = y
+  ...   for _ in range(10):
+  ...     d /= 2
+  ...     if y * y < x:
+  ...       y += d
+  ...     else:
+  ...       y -= d
+  ...     ys.append(y.numpy())
+  ...   return y
+  >>>
+  >>> tf.config.run_functions_eagerly(True)
+  >>> sqrt(tf.constant(2.))
+  <tf.Tensor: shape=(), dtype=float32, numpy=1.4150391>
+  >>> ys
+  [1.5, 1.25, 1.375, 1.4375, 1.40625, 1.421875, 1.4140625, 1.4179688, 1.4160156,
+  1.4150391]
+  >>> tf.config.run_functions_eagerly(False)
+
+  Calling `tf.config.run_functions_eagerly(False)` will undo this
+  behavior.
+
+  Note: This flag has no effect on functions passed into tf.data transformations
+  as arguments. tf.data functions are never executed eagerly and are always
+  executed as a compiled Tensorflow Graph.
+
   Args:
     run_eagerly: Boolean. Whether to run functions eagerly.
   """
@@ -352,9 +410,18 @@ def run_functions_eagerly(run_eagerly):
   RUN_FUNCTIONS_EAGERLY = bool(run_eagerly)
 
 
+@deprecation.deprecated(
+    None,
+    "Use tf.config.functions_run_eagerly instead of the experimental version.")
 @tf_export("config.experimental_functions_run_eagerly")
-def functions_run_eagerly():
+def experimental_functions_run_eagerly():
   """Returns the value of the `experimental_run_functions_eagerly` setting."""
+  return functions_run_eagerly()
+
+
+@tf_export("config.functions_run_eagerly")
+def functions_run_eagerly():
+  """Returns the value of the `run_functions_eagerly` setting."""
   return RUN_FUNCTIONS_EAGERLY
 
 

tensorflow/python/keras/engine/training_v1.py

@@ -534,7 +534,7 @@ class Model(training_lib.Model):
                        'is enabled.')
     if not self.dynamic:
       if self._run_eagerly is None:
-        # Respect `tf.config.experimental_run_functions_eagerly` unless
+        # Respect `tf.config.run_functions_eagerly` unless
         # `run_eagerly` was explicitly passed to `compile`.
         return def_function.RUN_FUNCTIONS_EAGERLY
       else:

tensorflow/python/ops/parallel_for/control_flow_ops.py

@@ -195,7 +195,7 @@ def pfor(loop_fn, iters, fallback_to_while_loop=True, parallel_iterations=None):
     if functions_run_eagerly:
       logging.warning(
           "It looks like tf.function behavior was disabled, perhaps using "
-          "tf.config.experimental_run_functions_eagerly. Vectorization "
+          "tf.config.run_functions_eagerly. Vectorization "
           "primitives (e.g. tf.vectorized_map) require tf.function to work. "
           "These primitives will override the disable.")
       def_function.run_functions_eagerly(False)

tensorflow/tools/api/golden/v1/tensorflow.config.pbtxt

@@ -40,6 +40,10 @@ tf_module {
     name: "experimental_run_functions_eagerly"
     argspec: "args=[\'run_eagerly\'], varargs=None, keywords=None, defaults=None"
   }
+  member_method {
+    name: "functions_run_eagerly"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
   member_method {
     name: "get_logical_device_configuration"
     argspec: "args=[\'device\'], varargs=None, keywords=None, defaults=None"
@@ -60,6 +64,10 @@ tf_module {
     name: "list_physical_devices"
     argspec: "args=[\'device_type\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "run_functions_eagerly"
+    argspec: "args=[\'run_eagerly\'], varargs=None, keywords=None, defaults=None"
+  }
   member_method {
     name: "set_logical_device_configuration"
     argspec: "args=[\'device\', \'logical_devices\'], varargs=None, keywords=None, defaults=None"

tensorflow/tools/api/golden/v2/tensorflow.config.pbtxt

@@ -40,6 +40,10 @@ tf_module {
     name: "experimental_run_functions_eagerly"
     argspec: "args=[\'run_eagerly\'], varargs=None, keywords=None, defaults=None"
   }
+  member_method {
+    name: "functions_run_eagerly"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
   member_method {
     name: "get_logical_device_configuration"
     argspec: "args=[\'device\'], varargs=None, keywords=None, defaults=None"
@@ -60,6 +64,10 @@ tf_module {
     name: "list_physical_devices"
     argspec: "args=[\'device_type\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "run_functions_eagerly"
+    argspec: "args=[\'run_eagerly\'], varargs=None, keywords=None, defaults=None"
+  }
   member_method {
     name: "set_logical_device_configuration"
     argspec: "args=[\'device\', \'logical_devices\'], varargs=None, keywords=None, defaults=None"