Add util which creates Python callable with tf.Variables explicitly as

arguments.

PiperOrigin-RevId: 187561302

5 files changed, 0 insertions, 340 deletions

diff --git a/tensorflow/contrib/bayesflow/BUILD b/tensorflow/contrib/bayesflow/BUILD
index 270c309ec3..3592cff90b 100644
--- a/tensorflow/contrib/bayesflow/BUILD
+++ b/tensorflow/contrib/bayesflow/BUILD
@@ -252,23 +252,6 @@ cuda_py_test(
 )
 
 cuda_py_test(
-    name = "variable_utils_test",
-    size = "small",
-    srcs = ["python/kernel_tests/variable_utils_test.py"],
-    additional_deps = [
-        ":bayesflow_py",
-        "//third_party/py/numpy",
-        "//tensorflow/python:client_testlib",
-        "//tensorflow/python:framework",
-        "//tensorflow/python:framework_for_generated_wrappers",
-        "//tensorflow/python:framework_test_lib",
-        "//tensorflow/python:gradients",
-        "//tensorflow/python:math_ops",
-        "//tensorflow/python:platform_test",
-    ],
-)
-
-cuda_py_test(
     name = "variational_sgd_optimizer_test",
     size = "small",
     srcs = ["python/kernel_tests/variational_sgd_optimizer_test.py"],
diff --git a/tensorflow/contrib/bayesflow/__init__.py b/tensorflow/contrib/bayesflow/__init__.py
index 528c4fbacd..c411026346 100644
--- a/tensorflow/contrib/bayesflow/__init__.py
+++ b/tensorflow/contrib/bayesflow/__init__.py
@@ -30,7 +30,6 @@ from tensorflow.contrib.bayesflow.python.ops import mcmc_diagnostics
 from tensorflow.contrib.bayesflow.python.ops import metropolis_hastings
 from tensorflow.contrib.bayesflow.python.ops import monte_carlo
 from tensorflow.contrib.bayesflow.python.ops import optimizers
-from tensorflow.contrib.bayesflow.python.ops import variable_utils
 # pylint: enable=unused-import,line-too-long
 
 from tensorflow.python.util.all_util import remove_undocumented
@@ -49,7 +48,6 @@ _allowed_symbols = [
     'optimizers',
     'special_math',
     'stochastic_variables',
-    'variable_utils',
     'variational_inference',
 ]
 
diff --git a/tensorflow/contrib/bayesflow/python/kernel_tests/variable_utils_test.py b/tensorflow/contrib/bayesflow/python/kernel_tests/variable_utils_test.py
deleted file mode 100644
index f978cf8641..0000000000
--- a/tensorflow/contrib/bayesflow/python/kernel_tests/variable_utils_test.py
+++ /dev/null
@@ -1,135 +0,0 @@
-# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ==============================================================================
-"""Tests for utility functions related to managing `tf.Variable`s."""
-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import warnings
-
-import numpy as np
-
-from tensorflow.contrib.bayesflow.python.ops import variable_utils
-
-from tensorflow.python.framework import constant_op
-from tensorflow.python.framework import ops
-from tensorflow.python.ops import variable_scope as varscope_ops
-from tensorflow.python.ops import variables as variables_ops
-from tensorflow.python.platform import test
-
-
-def test_fn(x):
-  x = ops.convert_to_tensor(x, name="x")
-  dtype = x.dtype.as_numpy_dtype
-  s = x.shape.as_list()
-  z = varscope_ops.get_variable(
-      name="z",
-      dtype=dtype,
-      initializer=np.arange(np.prod(s)).reshape(s).astype(dtype))
-  y = varscope_ops.get_variable(
-      name="y",
-      dtype=dtype,
-      initializer=np.arange(np.prod(s)).reshape(s).astype(dtype)**2)
-  return x + y + z
-
-
-class _WrapCallableTest(object):
-
-  def testDefaultArgsWorkCorrectly(self):
-    with self.test_session():
-      x = constant_op.constant(self.dtype([0.1, 0.2]))
-      wrapped_fn, vars_args = variable_utils.externalize_variables_as_args(
-          test_fn, [x])
-
-      varscope_ops.get_variable_scope().reuse_variables()
-
-      result = wrapped_fn(self.dtype(2), [3, 4, 5], 0.5)
-
-      y_actual = varscope_ops.get_variable("y", dtype=self.dtype)
-      z_actual = varscope_ops.get_variable("z", dtype=self.dtype)
-
-      variables_ops.global_variables_initializer().run()
-      result_ = result.eval()
-
-      self.assertEqual(self.dtype, result_.dtype)
-      self.assertAllEqual([5.5, 6.5, 7.5], result_)
-      self.assertAllEqual([y_actual, z_actual], vars_args)
-
-  def testNonDefaultArgsWorkCorrectly(self):
-    with self.test_session():
-      x = constant_op.constant(self.dtype([0.1, 0.2]))
-
-      _ = test_fn(self.dtype([0., 0.]))   # Needed to create vars.
-      varscope_ops.get_variable_scope().reuse_variables()
-
-      y_actual = varscope_ops.get_variable("y", dtype=self.dtype)
-
-      wrapped_fn, vars_args = variable_utils.externalize_variables_as_args(
-          test_fn, [x], possible_ancestor_vars=[y_actual])
-
-      result = wrapped_fn(self.dtype([2, 3]), 0.5)  # x, y
-
-      variables_ops.global_variables_initializer().run()
-      result_ = result.eval()
-
-      self.assertEqual(self.dtype, result_.dtype)
-      self.assertAllEqual([2.5, 4.5], result_)
-      self.assertAllEqual([y_actual], vars_args)
-
-  def testWarnings(self):
-    with self.test_session():
-      x = constant_op.constant(self.dtype([0.1, 0.2]))
-      wrapped_fn, _ = variable_utils.externalize_variables_as_args(
-          test_fn, [x], possible_ancestor_vars=[])
-      varscope_ops.get_variable_scope().reuse_variables()
-      with warnings.catch_warnings(record=True) as w:
-        wrapped_fn(self.dtype(2))
-      w = sorted(w, key=lambda w: str(w.message))
-      self.assertEqual(2, len(w))
-      self.assertRegexpMatches(
-          str(w[0].message),
-          r"Variable .* 'y:0' .* not found in bypass dict.")
-      self.assertRegexpMatches(
-          str(w[1].message),
-          r"Variable .* 'z:0' .* not found in bypass dict.")
-
-  def testExceptions(self):
-    with self.test_session():
-      x = constant_op.constant(self.dtype([0.1, 0.2]))
-      wrapped_fn, _ = variable_utils.externalize_variables_as_args(
-          test_fn,
-          [x],
-          possible_ancestor_vars=[],
-          assert_variable_override=True)
-      varscope_ops.get_variable_scope().reuse_variables()
-      with self.assertRaisesRegexp(ValueError, r"not found"):
-        wrapped_fn(self.dtype(2))
-
-
-class WrapCallableTest16(test.TestCase, _WrapCallableTest):
-  dtype = np.float16
-
-
-class WrapCallableTest32(test.TestCase, _WrapCallableTest):
-  dtype = np.float32
-
-
-class WrapCallableTest64(test.TestCase, _WrapCallableTest):
-  dtype = np.float64
-
-
-if __name__ == "__main__":
-  test.main()
diff --git a/tensorflow/contrib/bayesflow/python/ops/variable_utils.py b/tensorflow/contrib/bayesflow/python/ops/variable_utils.py
deleted file mode 100644
index eadf6f4d5f..0000000000
--- a/tensorflow/contrib/bayesflow/python/ops/variable_utils.py
+++ /dev/null
@@ -1,29 +0,0 @@
-# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ==============================================================================
-"""Utility functions related to managing `tf.Variable`s."""
-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-# go/tf-wildcard-import
-from tensorflow.contrib.bayesflow.python.ops.variable_utils_impl import *  # pylint: disable=wildcard-import,unused-wildcard-import,g-importing-member
-from tensorflow.python.util import all_util
-
-_allowed_symbols = [
-    "externalize_variables_as_args",
-]
-
-all_util.remove_undocumented(__name__, _allowed_symbols)
diff --git a/tensorflow/contrib/bayesflow/python/ops/variable_utils_impl.py b/tensorflow/contrib/bayesflow/python/ops/variable_utils_impl.py
deleted file mode 100644
index ca3d75b5bf..0000000000
--- a/tensorflow/contrib/bayesflow/python/ops/variable_utils_impl.py
+++ /dev/null
@@ -1,157 +0,0 @@
-# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ==============================================================================
-"""Utility functions related to managing `tf.Variable`s.
-
-@@externalize_variables_as_args
-"""
-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import warnings
-
-from tensorflow.python.framework import ops
-from tensorflow.python.ops import gradients_impl as gradients_ops
-from tensorflow.python.ops import variable_scope as varscope_ops
-from tensorflow.python.ops import variables as variables_ops
-
-__all__ = [
-    "externalize_variables_as_args",
-]
-
-
-# Cause all warnings to always be triggered.
-# Not having this means subsequent calls wont trigger the warning.
-warnings.simplefilter("always")
-
-
-def externalize_variables_as_args(fn,
-                                  fn_args=(),
-                                  ancestor_variables=None,
-                                  possible_ancestor_vars=None,
-                                  assert_variable_override=False,
-                                  name=None):
-  """"Converts variables within a callable into explicit args.
-
-  Makes a new callable from `fn` which has arguments `list(fn_args) +
-  list(ancestor_variables)`. If `ancestor_variables` is not specified, it is
-  inferred by checking which of `possible_ancestor_vars` actually influences the
-  return value of `fn` (concretely, gradient of `fn(*fn_args)` is not `None`).
-  By default `possible_ancestor_vars` is `tf.trainable_variables() +
-  tf.get_collection(tf.GraphKeys.TRAINABLE_RESOURCE_VARIABLES)`.
-
-  #### Examples:
-
-  ```python
-  num_samples = 2
-  num_dims = 1
-  dtype = np.float32
-
-  def foo(x):
-    x = tf.convert_to_tensor(x, dtype=dtype, name="x")
-    s = x.shape.as_list()
-    y = tf.get_variable(
-        name="y",
-        dtype=dtype,
-        initializer=np.arange(np.prod(s)).reshape(s).astype(dtype))
-    return x + y
-
-  x = tf.constant(dtype([0.1, 0.2]))
-
-  wrapped_foo, discovered_ancestor_variables = (
-      externalize_variables_as_args(foo, [x]))
-
-  new_x = dtype([[1.], [2.]])
-  new_y = dtype([[3.], [4.]])
-  new_result = wrapped_foo(new_x, new_y)
-  # ==> [[4.], [6.]]
-
-  discovered_ancestor_variables == [tf.get_variable("y", dtype)]
-  # ==> [True]
-  ```
-
-  Args:
-    fn: Python callable which returns a `Tensor` and accepts `*fn_args`.
-    fn_args: Python list of args to `fn`. Represents dummy arguments passed to
-      `fn` to trace its execution; actual values are unimportant. These args are
-      only used to construct the output of `fn` and to resolve the ancestor
-      `tf.Variable`s.
-      Default value: `()` (i.e., `fn` takes no args).
-    ancestor_variables: Python list of `tf.Variable`s. When `None` the list is
-      expanded to non-`None` gradients of `fn(*fn_args)`. By directly providing
-      the `ancestor_variables` the internal call to `fn` is avoided.
-      Default value: `None` (i.e., `tf.Variable` dependencies are discovered).
-    possible_ancestor_vars: Python list of possible `tf.Variable`s which might
-      be a dependency of computing `fn(*fn_args)`.
-      Default value: `None` (i.e., expanded as described above).
-    assert_variable_override: Python `bool` indicating that not finding a
-      `tf.Variable` in the override list is an exception.
-      Default value: `False` (i.e., missing a `Variable` triggers a `warning`).
-    name: Python `str` name prefixed to Ops created by this function.
-      Default value: `None` (i.e., "externalize_variables_as_args").
-
-  Returns:
-    wrapped_fn: Python callable taking arguments like
-      `*(list(fn_args) + discovered_ancestor_variables)`.
-    discovered_ancestor_variables: Python list of `tf.Variable`s known to be a
-      dependency of `fn(*fn_args)`.
-
-  Raises:
-    ValueError: if `assert_variable_override` is `True` and `Variable` is
-      requested but not overridden.
-  """
-  def _make_bypassing_custom_getter_fn(new_var_dict):
-    """Return dict value rather than what would otherwise be dict key."""
-    def _custom_getter(getter, *args, **kwargs):
-      v = getter(*args, **kwargs)
-      new_v = new_var_dict.get(v, None)
-      if new_v is None:
-        msg = "Variable \"{}\" not found in bypass dict.".format(v)
-        if assert_variable_override:
-          raise ValueError(msg)
-        warnings.warn(msg)
-        return v
-      return new_v
-    return _custom_getter
-
-  with ops.name_scope(name, "externalize_variables_as_args"):
-    if ancestor_variables is not None and not ancestor_variables:
-      return fn, ()
-    if ancestor_variables is None:
-      y = fn(*fn_args)  # Side-effect: adds trainable vars.
-      if possible_ancestor_vars is None:
-        possible_ancestor_vars = (
-            variables_ops.trainable_variables() +
-            ops.get_collection(ops.GraphKeys.TRAINABLE_RESOURCE_VARIABLES))
-      # TODO(b/72873296): Add a dedicated op for identifying ancestors.
-      ancestors = [v for g, v
-                   in zip(gradients_ops.gradients(y, possible_ancestor_vars),
-                          possible_ancestor_vars)
-                   if g is not None]
-      ancestor_variables = sorted(ancestors, key=lambda v: v.name)
-  n = len(fn_args)
-  def _fn(*args):
-    with ops.name_scope("wrapped_fn"):
-      vars_dict = dict(
-          (k, ops.convert_to_tensor(
-              v, dtype=k.dtype.base_dtype, name=k.op.name))
-          for k, v in zip(ancestor_variables, args[n:]))
-      with varscope_ops.variable_scope(
-          varscope_ops.get_variable_scope(),
-          reuse=True,
-          custom_getter=_make_bypassing_custom_getter_fn(vars_dict)):
-        return fn(*args[:n])
-  return _fn, ancestor_variables