Remove unused _SlimRNNCell.

This cell type has been private for a while, and neither used by internal code, nor exposed as a public API.

PiperOrigin-RevId: 203853628

2 files changed, 0 insertions, 47 deletions

diff --git a/tensorflow/contrib/rnn/BUILD b/tensorflow/contrib/rnn/BUILD
index 4eb5c920b3..2a84629080 100644
--- a/tensorflow/contrib/rnn/BUILD
+++ b/tensorflow/contrib/rnn/BUILD
@@ -118,7 +118,6 @@ cuda_py_tests(
         "//tensorflow/python:framework_for_generated_wrappers",
         "//tensorflow/python:init_ops",
         "//tensorflow/python:math_ops",
-        "//tensorflow/python:random_ops",
         "//tensorflow/python:rnn",
         "//tensorflow/python:rnn_cell",
         "//tensorflow/python:variable_scope",
diff --git a/tensorflow/contrib/rnn/python/kernel_tests/core_rnn_cell_test.py b/tensorflow/contrib/rnn/python/kernel_tests/core_rnn_cell_test.py
index 86f1e27abd..578aa752a3 100644
--- a/tensorflow/contrib/rnn/python/kernel_tests/core_rnn_cell_test.py
+++ b/tensorflow/contrib/rnn/python/kernel_tests/core_rnn_cell_test.py
@@ -18,7 +18,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import functools
 import os
 
 import numpy as np
@@ -35,7 +34,6 @@ from tensorflow.python.framework import test_util
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import init_ops
 from tensorflow.python.ops import math_ops
-from tensorflow.python.ops import random_ops
 from tensorflow.python.ops import rnn
 from tensorflow.python.ops import rnn_cell_impl
 from tensorflow.python.ops import variable_scope
@@ -935,50 +933,6 @@ class DropoutWrapperTest(test.TestCase):
     self.assertAllClose(res0[1].h, res1[1].h)
 
 
-class SlimRNNCellTest(test.TestCase):
-
-  def testBasicRNNCell(self):
-    with self.test_session() as sess:
-      with variable_scope.variable_scope(
-          "root", initializer=init_ops.constant_initializer(0.5)):
-        x = array_ops.zeros([1, 2])
-        m = array_ops.zeros([1, 2])
-        my_cell = functools.partial(basic_rnn_cell, num_units=2)
-        # pylint: disable=protected-access
-        g, _ = rnn_cell_impl._SlimRNNCell(my_cell)(x, m)
-        # pylint: enable=protected-access
-        sess.run([variables_lib.global_variables_initializer()])
-        res = sess.run([g], {
-            x.name: np.array([[1., 1.]]),
-            m.name: np.array([[0.1, 0.1]])
-        })
-        self.assertEqual(res[0].shape, (1, 2))
-
-  def testBasicRNNCellMatch(self):
-    batch_size = 32
-    input_size = 100
-    num_units = 10
-    with self.test_session() as sess:
-      with variable_scope.variable_scope(
-          "root", initializer=init_ops.constant_initializer(0.5)):
-        inputs = random_ops.random_uniform((batch_size, input_size))
-        _, initial_state = basic_rnn_cell(inputs, None, num_units)
-        rnn_cell = rnn_cell_impl.BasicRNNCell(num_units)
-        outputs, state = rnn_cell(inputs, initial_state)
-        variable_scope.get_variable_scope().reuse_variables()
-        my_cell = functools.partial(basic_rnn_cell, num_units=num_units)
-        # pylint: disable=protected-access
-        slim_cell = rnn_cell_impl._SlimRNNCell(my_cell)
-        # pylint: enable=protected-access
-        slim_outputs, slim_state = slim_cell(inputs, initial_state)
-        self.assertEqual(slim_outputs.get_shape(), outputs.get_shape())
-        self.assertEqual(slim_state.get_shape(), state.get_shape())
-        sess.run([variables_lib.global_variables_initializer()])
-        res = sess.run([slim_outputs, slim_state, outputs, state])
-        self.assertAllClose(res[0], res[2])
-        self.assertAllClose(res[1], res[3])
-
-
 def basic_rnn_cell(inputs, state, num_units, scope=None):
   if state is None:
     if inputs is not None: