Remove contrib.specs AutoFunction

This does clever things with the TensorFlow namespaces which we can't
maintain.
Change: 142050311

4 files changed, 0 insertions, 91 deletions

diff --git a/tensorflow/contrib/specs/README.md b/tensorflow/contrib/specs/README.md
index e2c6c5c8bc..7ed6569ed8 100644
--- a/tensorflow/contrib/specs/README.md
+++ b/tensorflow/contrib/specs/README.md
@@ -207,25 +207,6 @@ actually just values placed in the namespace somehow. The `Import`
 function takes an arbitrary Python statement that eventually needs to
 assign a value to the variable `f` that is then wrapped up as a function.
 
-# AutoFunction
-
-Not all functions available in TensorFlow have corresponding short names
-in specs; in order to access other functions conveniently, you can refer
-to any function in a number of existing modules using the full function
-name in that module.  Module shortcuts are defined for:
-
- - `TF` = `tf`
- - `NN` = `tf.nn`
- - `SL` = `slim`
-
-You can, of course, introduce more abbreviations in your own code.
-
-These are defined as:
-
-    TF = specs_lib.AutoFunction(tf)
-
-Using these definitions, `SL.conv2d(64, 5)` is equivalent to `Cr(64, 5)`.
-
 # Summaries
 
 There are a number of functions that give you information about the structure
diff --git a/tensorflow/contrib/specs/python/specs_lib.py b/tensorflow/contrib/specs/python/specs_lib.py
index e2ddd7567e..12663c2788 100644
--- a/tensorflow/contrib/specs/python/specs_lib.py
+++ b/tensorflow/contrib/specs/python/specs_lib.py
@@ -169,57 +169,6 @@ class Function(Composable):
     return self.f(x, *args, **kw)
 
 
-class AutoFunction(object):
-  """Automatically curry functions when accessed as attributes.
-
-  This class wraps a dictionary mapping keys to values. When an attribute
-  is accessed, the class looks up the attribute in the dictionary and
-  wraps it (curries it) using Function(...). When wrapped around
-  existing modules implementing TensorFlow functions or layers, this
-  turns those functions or layers automatically into specs-compatible
-  layers.
-
-  For example, `net` and `net2` are equivalent:
-      TF = AutoFunction(tf)
-      with specs.ops:
-        net = TF.conv2d(64, 5) ** 3 | Flat
-        net2 = Cr(64, 5) ** 3 | Flat
-
-  Attributes:
-      source: A dictionary holding the underlying key-value mappings.
-  """
-
-  def __init__(self, source):
-    """Creates an AutoFunction wrapper for a module.
-
-    Args:
-        source: A dictionary or a module.
-    """
-    if not isinstance(source, dict):
-      source = vars(source)
-    self.source = source
-
-  def __getattr__(self, key):
-    """Looks up the key in the source dictionary and curries the result.
-
-    Args:
-        key: The symbol name to look up.
-
-    Returns:
-        The curried argument.
-
-    Raises:
-        ValueError: The key does not exist, or it doesn't refer to a callable.
-    """
-    result = self.source.get(key, None)
-    if result is None:
-      raise ValueError("%s: no such symbol")
-    if not callable(result):
-      raise ValueError("value of %s is not callable (type is %s)" %
-                       (key, type(result)))
-    return Function(result)
-
-
 class Composition(Composable):
   """A function composition.
 
diff --git a/tensorflow/contrib/specs/python/specs_ops.py b/tensorflow/contrib/specs/python/specs_ops.py
index 5658fc3e98..241de5458b 100644
--- a/tensorflow/contrib/specs/python/specs_ops.py
+++ b/tensorflow/contrib/specs/python/specs_ops.py
@@ -235,11 +235,3 @@ class Shared(specs_lib.Composable):
     else:
       with tf.variable_scope(self.scope, values=[x], reuse=True):
         return self.subnet.funcall(x)
-
-# AutoFunction bindings of some existing modules
-
-TF = specs_lib.AutoFunction(tf)
-NN = specs_lib.AutoFunction(tf.nn)
-SL = specs_lib.AutoFunction(slim)
-
-# pylint: enable=invalid-name
diff --git a/tensorflow/contrib/specs/python/specs_test.py b/tensorflow/contrib/specs/python/specs_test.py
index 67e4a559a9..b9ddfc4658 100644
--- a/tensorflow/contrib/specs/python/specs_test.py
+++ b/tensorflow/contrib/specs/python/specs_test.py
@@ -213,19 +213,6 @@ class SpecsTest(tf.test.TestCase):
       _ = g.funcall(inputs)
       self.assertEqual(len(tf.global_variables()), 2)
 
-  def testAutoFunction(self):
-    with self.test_session():
-      inputs = tf.constant(_rand(1, 18, 19, 5))
-      with specs.ops:
-        # pylint: disable=undefined-variable
-        net = SL.conv2d(64, 5)
-      outputs = net.funcall(inputs)
-      self.assertEqual(outputs.get_shape().as_list(), [1, 18, 19, 64])
-      tf.global_variables_initializer().run()
-      result = outputs.eval()
-      self.assertEqual(tuple(result.shape), (1, 18, 19, 64))
-      self.assertEqual(summaries.tf_spec_structure("net = Cr(64, 5)", inputs),
-                       "_ var conv var biasadd relu")
 
 if __name__ == "__main__":
   tf.test.main()