Remove deprecated run_as argument for convert.

PiperOrigin-RevId: 260190100

tensorflow/python/autograph/__init__.py

@@ -40,7 +40,6 @@ from tensorflow.python.autograph.impl.api import AutoGraphError
 from tensorflow.python.autograph.impl.api import convert
 from tensorflow.python.autograph.impl.api import converted_call
 from tensorflow.python.autograph.impl.api import do_not_convert
-from tensorflow.python.autograph.impl.api import RunMode
 from tensorflow.python.autograph.impl.api import StackTraceMapper
 from tensorflow.python.autograph.impl.api import to_code
 from tensorflow.python.autograph.impl.api import to_graph
@@ -56,7 +55,6 @@ _allowed_symbols = [
     'AutoGraphError',
     'ConversionOptions',
     'Feature',
-    'RunMode',
     'StackTraceMapper',
     'convert',
     'converted_call',

tensorflow/python/autograph/docs/pyfunc_dtypes.md

@@ -1,33 +0,0 @@
-# Specifying return data type for `py_func` calls
-
-The `py_func` op requires specifying a
-[data type](https://www.tensorflow.org/guide/tensors#data_types).
-
-When wrapping a function with `py_func`, for instance using
-`@autograph.do_not_convert(run_as=autograph.RunMode.PY_FUNC)`, you have two
-options to specify the returned data type:
-
- * explicitly, with a specified `tf.DType` value
- * by matching the data type of an input argument, which is then assumed to be
-     a `Tensor`
-
-Examples:
-
-Specify an explicit data type:
-
-```
-  def foo(a):
-    return a + 1
-
-  autograph.util.wrap_py_func(f, return_dtypes=[tf.float32])
-```
-
-Match the data type of the first argument:
-
-```
-  def foo(a):
-    return a + 1
-
-  autograph.util.wrap_py_func(
-      f, return_dtypes=[autograph.utils.py_func.MatchDType(0)])
-```

tensorflow/python/autograph/impl/api.py

@@ -28,7 +28,6 @@ import re
 import sys
 import textwrap
 import traceback
-from enum import Enum
 
 # pylint:disable=g-bad-import-order
 import six
@@ -42,7 +41,6 @@ from tensorflow.python.autograph.pyct import errors
 from tensorflow.python.autograph.pyct import inspect_utils
 from tensorflow.python.autograph.pyct import origin_info
 from tensorflow.python.autograph.utils import ag_logging as logging
-from tensorflow.python.autograph.utils import py_func
 from tensorflow.python.framework import errors_impl
 from tensorflow.python.util import tf_decorator
 from tensorflow.python.util import tf_inspect
@@ -238,20 +236,6 @@ def convert(recursive=False, optional_features=None, force_conversion=True):
   return decorator
 
 
-class RunMode(Enum):
-  """Specifies the way a converted function or method should be executed in TF.
-
-  Attributes:
-   * GRAPH: Call this function directly, as-is. This is suitable for functions
-     that were already designed for TF graphs and contain ops.
-   * PY_FUNC: Wrap this function into a py_func op. This is suitable for code
-     that will only run correctly in Python, for example code that renders to
-     the display, reads keyboard input, etc.
-  """
-  GRAPH = 1
-  PY_FUNC = 2
-
-
 def call_with_unspecified_conversion_status(func):
   """Decorator that resets the conversion context to the unspecified status."""
   def wrapper(*args, **kwargs):
@@ -272,18 +256,11 @@ def do_not_convert_internal(f):
 
 
 @tf_export('autograph.experimental.do_not_convert')
-def do_not_convert(func=None, run_as=RunMode.GRAPH, return_dtypes=None):
+def do_not_convert(func=None):
   """Decorator that suppresses the conversion of a function.
 
-  See also: docs/pyfunc_dtypes.md
-
   Args:
     func: function to decorate.
-    run_as: RunMode, specifies how to use the function in TensorFlow.
-    return_dtypes: Optional[Iterable[ Union[tf.DType,
-      utils.py_func.MatchDType]]], the return data types of the converted
-      function, if run_as is RunMode.PY_FUNC. Ignored otherwise. May be set to
-      None if the function has no return values.
 
   Returns:
     If `func` is not None, returns a `Callable` which is equivalent to
@@ -293,29 +270,12 @@ def do_not_convert(func=None, run_as=RunMode.GRAPH, return_dtypes=None):
     above case.
   """
   if func is None:
-    return functools.partial(
-        do_not_convert,
-        run_as=run_as,
-        return_dtypes=return_dtypes)
+    return do_not_convert
 
-  def graph_wrapper(*args, **kwargs):
+  def wrapper(*args, **kwargs):
     with ag_ctx.ControlStatusCtx(status=ag_ctx.Status.DISABLED):
       return func(*args, **kwargs)
 
-  def py_func_wrapper(*args, **kwargs):
-    if kwargs:
-      raise NotImplementedError('RunMode.PY_FUNC does not yet support kwargs')
-    # TODO(mdan): Add support for kwargs.
-    return py_func.wrap_py_func(
-        func, return_dtypes, args, kwargs, use_dummy_return=not return_dtypes)
-
-  if run_as == RunMode.GRAPH:
-    wrapper = graph_wrapper
-  elif run_as == RunMode.PY_FUNC:
-    wrapper = py_func_wrapper
-  else:
-    raise ValueError('unknown value for run_as: %s' % run_as)
-
   if inspect.isfunction(func) or inspect.ismethod(func):
     wrapper = functools.update_wrapper(wrapper, func)
 

tensorflow/python/autograph/impl/api_test.py

@@ -35,7 +35,6 @@ from tensorflow.python.autograph.core import converter
 from tensorflow.python.autograph.impl import api
 from tensorflow.python.autograph.pyct import inspect_utils
 from tensorflow.python.autograph.pyct import parser
-from tensorflow.python.autograph.utils import py_func
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.eager import def_function
 from tensorflow.python.eager import function
@@ -108,11 +107,11 @@ class ApiTest(test.TestCase):
       self.assertListEqual([0, 1], self.evaluate(x).tolist())
 
   @test_util.run_deprecated_v1
-  def test_convert_then_do_not_convert_graph(self):
+  def test_convert_then_do_not_convert(self):
 
     class TestClass(object):
 
-      @api.do_not_convert(run_as=api.RunMode.GRAPH)
+      @api.do_not_convert
       def called_member(self, a):
         return tf.negative(a)
 
@@ -128,32 +127,6 @@ class ApiTest(test.TestCase):
         constant_op.constant(-2))
     self.assertAllEqual((0, 1), self.evaluate(x))
 
-  @test_util.run_deprecated_v1
-  def test_convert_then_do_not_convert_py_func(self):
-
-    class TestClass(object):
-
-      @api.do_not_convert(
-          run_as=api.RunMode.PY_FUNC, return_dtypes=py_func.MatchDType(1))
-      def called_member(self, a):
-        return np.negative(a)
-
-      @api.convert(recursive=True)
-      def test_method(self, x, s, a):
-        while tf.reduce_sum(x) > s:
-          y = self.called_member(a)
-          # set_shape works around while_loop's limitations.
-          # TODO(mdan): Allow specifying shapes (or ShapeLike) instead.
-          y.set_shape(a.shape)
-          x //= y
-        return x
-
-    tc = TestClass()
-    x = tc.test_method(
-        constant_op.constant((2, 4)), constant_op.constant(1),
-        constant_op.constant(-2))
-    self.assertAllEqual((0, 1), self.evaluate(x))
-
   @test_util.run_deprecated_v1
   def test_decorator_calls_decorated(self):
 

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

@@ -6,7 +6,7 @@ tf_module {
   }
   member_method {
     name: "do_not_convert"
-    argspec: "args=[\'func\', \'run_as\', \'return_dtypes\'], varargs=None, keywords=None, defaults=[\'None\', \'RunMode.GRAPH\', \'None\'], "
+    argspec: "args=[\'func\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
   member_method {
     name: "set_loop_options"

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

@@ -6,7 +6,7 @@ tf_module {
   }
   member_method {
     name: "do_not_convert"
-    argspec: "args=[\'func\', \'run_as\', \'return_dtypes\'], varargs=None, keywords=None, defaults=[\'None\', \'RunMode.GRAPH\', \'None\'], "
+    argspec: "args=[\'func\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
   member_method {
     name: "set_loop_options"