LinearOperator name change: LinearOperatorMatrix --> LinearOperatorFullMatrix

Change: 148895969

9 files changed, 61 insertions, 60 deletions

diff --git a/tensorflow/contrib/linalg/BUILD b/tensorflow/contrib/linalg/BUILD
index b6d4625e6b..9b196e2cf5 100644
--- a/tensorflow/contrib/linalg/BUILD
+++ b/tensorflow/contrib/linalg/BUILD
@@ -100,9 +100,9 @@ cuda_py_tests(
 )
 
 cuda_py_tests(
-    name = "linear_operator_matrix_test",
+    name = "linear_operator_full_matrix_test",
     size = "medium",
-    srcs = ["python/kernel_tests/linear_operator_matrix_test.py"],
+    srcs = ["python/kernel_tests/linear_operator_full_matrix_test.py"],
     additional_deps = [
         ":linalg_py",
         "//tensorflow/python:array_ops",
diff --git a/tensorflow/contrib/linalg/__init__.py b/tensorflow/contrib/linalg/__init__.py
index 8398956ee3..44421a6b7d 100644
--- a/tensorflow/contrib/linalg/__init__.py
+++ b/tensorflow/contrib/linalg/__init__.py
@@ -20,7 +20,7 @@ See the @{$python/contrib.linalg} guide.
 @@LinearOperatorDiag
 @@LinearOperatorIdentity
 @@LinearOperatorScaledIdentity
-@@LinearOperatorMatrix
+@@LinearOperatorFullMatrix
 @@LinearOperatorTriL
 @@LinearOperatorUDVHUpdate
 @@LinearOperatorComposition
@@ -37,8 +37,8 @@ from tensorflow.contrib.linalg.python.ops.linear_operator import *
 from tensorflow.contrib.linalg.python.ops.linear_operator_addition import *
 from tensorflow.contrib.linalg.python.ops.linear_operator_composition import *
 from tensorflow.contrib.linalg.python.ops.linear_operator_diag import *
+from tensorflow.contrib.linalg.python.ops.linear_operator_full_matrix import *
 from tensorflow.contrib.linalg.python.ops.linear_operator_identity import *
-from tensorflow.contrib.linalg.python.ops.linear_operator_matrix import *
 from tensorflow.contrib.linalg.python.ops.linear_operator_tril import *
 from tensorflow.contrib.linalg.python.ops.linear_operator_udvh_update import *
 
diff --git a/tensorflow/contrib/linalg/python/kernel_tests/linear_operator_addition_test.py b/tensorflow/contrib/linalg/python/kernel_tests/linear_operator_addition_test.py
index 5bb1c61e14..4746484755 100644
--- a/tensorflow/contrib/linalg/python/kernel_tests/linear_operator_addition_test.py
+++ b/tensorflow/contrib/linalg/python/kernel_tests/linear_operator_addition_test.py
@@ -137,7 +137,8 @@ class LinearOperatorAdditionCorrectnessTest(test.TestCase):
       self.assertEqual(None, op.is_non_singular)
 
   def test_matrix_diag_tril_diag_uses_custom_name(self):
-    op0 = linalg.LinearOperatorMatrix([[-1., -1.], [-1., -1.]], name="matrix")
+    op0 = linalg.LinearOperatorFullMatrix(
+        [[-1., -1.], [-1., -1.]], name="matrix")
     op1 = linalg.LinearOperatorDiag([1., 1.], name="diag_a")
     op2 = linalg.LinearOperatorTriL([[2., 0.], [1.5, 2.]], name="tril")
     op3 = linalg.LinearOperatorDiag([3., 3.], name="diag_b")
@@ -145,24 +146,24 @@ class LinearOperatorAdditionCorrectnessTest(test.TestCase):
       op_sum = add_operators([op0, op1, op2, op3], operator_name="my_operator")
       self.assertEqual(1, len(op_sum))
       op = op_sum[0]
-      self.assertTrue(isinstance(op, linalg_lib.LinearOperatorMatrix))
+      self.assertTrue(isinstance(op, linalg_lib.LinearOperatorFullMatrix))
       self.assertAllClose([[5., -1.], [0.5, 5.]], op.to_dense().eval())
       self.assertEqual("my_operator", op.name)
 
   def test_incompatible_domain_dimensions_raises(self):
-    op1 = linalg.LinearOperatorMatrix(rng.rand(2, 3))
+    op1 = linalg.LinearOperatorFullMatrix(rng.rand(2, 3))
     op2 = linalg.LinearOperatorDiag(rng.rand(2, 4))
     with self.assertRaisesRegexp(ValueError, "must.*same domain dimension"):
       add_operators([op1, op2])
 
   def test_incompatible_range_dimensions_raises(self):
-    op1 = linalg.LinearOperatorMatrix(rng.rand(2, 3))
+    op1 = linalg.LinearOperatorFullMatrix(rng.rand(2, 3))
     op2 = linalg.LinearOperatorDiag(rng.rand(3, 3))
     with self.assertRaisesRegexp(ValueError, "must.*same range dimension"):
       add_operators([op1, op2])
 
   def test_non_broadcastable_batch_shape_raises(self):
-    op1 = linalg.LinearOperatorMatrix(rng.rand(2, 3, 3))
+    op1 = linalg.LinearOperatorFullMatrix(rng.rand(2, 3, 3))
     op2 = linalg.LinearOperatorDiag(rng.rand(4, 3, 3))
     with self.assertRaisesRegexp(ValueError, "Incompatible shapes"):
       add_operators([op1, op2])
@@ -397,7 +398,7 @@ class AddAndReturnMatrixTest(test.TestCase):
 
     self.assertTrue(self._adder.can_add(diag1, diag2))
     operator = self._adder.add(diag1, diag2, "my_operator", hints)
-    self.assertTrue(isinstance(operator, linalg.LinearOperatorMatrix))
+    self.assertTrue(isinstance(operator, linalg.LinearOperatorFullMatrix))
 
     with self.test_session():
       self.assertAllClose([[0., 0.], [0., 5.]], operator.to_dense().eval())
diff --git a/tensorflow/contrib/linalg/python/kernel_tests/linear_operator_composition_test.py b/tensorflow/contrib/linalg/python/kernel_tests/linear_operator_composition_test.py
index 6309d36258..998073e28b 100644
--- a/tensorflow/contrib/linalg/python/kernel_tests/linear_operator_composition_test.py
+++ b/tensorflow/contrib/linalg/python/kernel_tests/linear_operator_composition_test.py
@@ -65,11 +65,11 @@ class SquareLinearOperatorCompositionTest(
       # feed_dict.
       matrices = sess.run(matrices)
       operator = linalg.LinearOperatorComposition(
-          [linalg.LinearOperatorMatrix(m_ph) for m_ph in matrices_ph])
+          [linalg.LinearOperatorFullMatrix(m_ph) for m_ph in matrices_ph])
       feed_dict = {m_ph: m for (m_ph, m) in zip(matrices_ph, matrices)}
     else:
       operator = linalg.LinearOperatorComposition(
-          [linalg.LinearOperatorMatrix(m) for m in matrices])
+          [linalg.LinearOperatorFullMatrix(m) for m in matrices])
       feed_dict = None
 
     # Convert back to Tensor.  Needed if use_placeholder, since then we have
@@ -86,7 +86,7 @@ class SquareLinearOperatorCompositionTest(
     # The matrix values do not effect auto-setting of the flags.
     matrix = [[1., 0.], [1., 1.]]
     operator = linalg.LinearOperatorComposition(
-        [linalg.LinearOperatorMatrix(matrix)],
+        [linalg.LinearOperatorFullMatrix(matrix)],
         is_positive_definite=True,
         is_non_singular=True,
         is_self_adjoint=False)
@@ -98,8 +98,8 @@ class SquareLinearOperatorCompositionTest(
     # Matrix with two positive eigenvalues, 11 and 8.
     # The matrix values do not effect auto-setting of the flags.
     matrix = [[11., 0.], [1., 8.]]
-    operator_1 = linalg.LinearOperatorMatrix(matrix, is_non_singular=True)
-    operator_2 = linalg.LinearOperatorMatrix(matrix, is_non_singular=True)
+    operator_1 = linalg.LinearOperatorFullMatrix(matrix, is_non_singular=True)
+    operator_2 = linalg.LinearOperatorFullMatrix(matrix, is_non_singular=True)
 
     operator = linalg.LinearOperatorComposition(
         [operator_1, operator_2],
@@ -114,8 +114,8 @@ class SquareLinearOperatorCompositionTest(
 
   def test_name(self):
     matrix = [[11., 0.], [1., 8.]]
-    operator_1 = linalg.LinearOperatorMatrix(matrix, name="left")
-    operator_2 = linalg.LinearOperatorMatrix(matrix, name="right")
+    operator_1 = linalg.LinearOperatorFullMatrix(matrix, name="left")
+    operator_2 = linalg.LinearOperatorFullMatrix(matrix, name="right")
 
     operator = linalg.LinearOperatorComposition([operator_1, operator_2])
 
@@ -123,8 +123,8 @@ class SquareLinearOperatorCompositionTest(
 
   def test_different_dtypes_raises(self):
     operators = [
-        linalg.LinearOperatorMatrix(rng.rand(2, 3, 3)),
-        linalg.LinearOperatorMatrix(rng.rand(2, 3, 3).astype(np.float32))
+        linalg.LinearOperatorFullMatrix(rng.rand(2, 3, 3)),
+        linalg.LinearOperatorFullMatrix(rng.rand(2, 3, 3).astype(np.float32))
     ]
     with self.assertRaisesRegexp(TypeError, "same dtype"):
       linalg.LinearOperatorComposition(operators)
@@ -176,11 +176,11 @@ class NonSquareLinearOperatorCompositionTest(
       # feed_dict.
       matrices = sess.run(matrices)
       operator = linalg.LinearOperatorComposition(
-          [linalg.LinearOperatorMatrix(m_ph) for m_ph in matrices_ph])
+          [linalg.LinearOperatorFullMatrix(m_ph) for m_ph in matrices_ph])
       feed_dict = {m_ph: m for (m_ph, m) in zip(matrices_ph, matrices)}
     else:
       operator = linalg.LinearOperatorComposition(
-          [linalg.LinearOperatorMatrix(m) for m in matrices])
+          [linalg.LinearOperatorFullMatrix(m) for m in matrices])
       feed_dict = None
 
     # Convert back to Tensor.  Needed if use_placeholder, since then we have
@@ -194,16 +194,16 @@ class NonSquareLinearOperatorCompositionTest(
 
   def test_static_shapes(self):
     operators = [
-        linalg.LinearOperatorMatrix(rng.rand(2, 3, 4)),
-        linalg.LinearOperatorMatrix(rng.rand(2, 4, 5))
+        linalg.LinearOperatorFullMatrix(rng.rand(2, 3, 4)),
+        linalg.LinearOperatorFullMatrix(rng.rand(2, 4, 5))
     ]
     operator = linalg.LinearOperatorComposition(operators)
     self.assertAllEqual((2, 3, 5), operator.shape)
 
   def test_shape_tensors_when_statically_available(self):
     operators = [
-        linalg.LinearOperatorMatrix(rng.rand(2, 3, 4)),
-        linalg.LinearOperatorMatrix(rng.rand(2, 4, 5))
+        linalg.LinearOperatorFullMatrix(rng.rand(2, 3, 4)),
+        linalg.LinearOperatorFullMatrix(rng.rand(2, 4, 5))
     ]
     operator = linalg.LinearOperatorComposition(operators)
     with self.test_session():
@@ -217,8 +217,8 @@ class NonSquareLinearOperatorCompositionTest(
     feed_dict = {mat_ph_1: mat_1, mat_ph_2: mat_2}
 
     operators = [
-        linalg.LinearOperatorMatrix(mat_ph_1),
-        linalg.LinearOperatorMatrix(mat_ph_2)
+        linalg.LinearOperatorFullMatrix(mat_ph_1),
+        linalg.LinearOperatorFullMatrix(mat_ph_2)
     ]
     operator = linalg.LinearOperatorComposition(operators)
     with self.test_session():
diff --git a/tensorflow/contrib/linalg/python/kernel_tests/linear_operator_matrix_test.py b/tensorflow/contrib/linalg/python/kernel_tests/linear_operator_full_matrix_test.py
index dcb2661197..93cbb48e1b 100644
--- a/tensorflow/contrib/linalg/python/kernel_tests/linear_operator_matrix_test.py
+++ b/tensorflow/contrib/linalg/python/kernel_tests/linear_operator_full_matrix_test.py
@@ -29,7 +29,7 @@ linalg = linalg_lib
 random_seed.set_random_seed(23)
 
 
-class SquareLinearOperatorMatrixTest(
+class SquareLinearOperatorFullMatrixTest(
     linear_operator_test_util.SquareLinearOperatorDerivedClassTest):
   """Most tests done in the base class LinearOperatorDerivedClassTest."""
 
@@ -45,10 +45,10 @@ class SquareLinearOperatorMatrixTest(
       # values are random and we want the same value used for both mat and
       # feed_dict.
       matrix = matrix.eval()
-      operator = linalg.LinearOperatorMatrix(matrix)
+      operator = linalg.LinearOperatorFullMatrix(matrix)
       feed_dict = {matrix_ph: matrix}
     else:
-      operator = linalg.LinearOperatorMatrix(matrix)
+      operator = linalg.LinearOperatorFullMatrix(matrix)
       feed_dict = None
 
     # Convert back to Tensor.  Needed if use_placeholder, since then we have
@@ -60,7 +60,7 @@ class SquareLinearOperatorMatrixTest(
   def test_is_x_flags(self):
     # Matrix with two positive eigenvalues.
     matrix = [[1., 0.], [1., 11.]]
-    operator = linalg.LinearOperatorMatrix(
+    operator = linalg.LinearOperatorFullMatrix(
         matrix,
         is_positive_definite=True,
         is_non_singular=True,
@@ -70,7 +70,7 @@ class SquareLinearOperatorMatrixTest(
     self.assertFalse(operator.is_self_adjoint)
 
 
-class SquareLinearOperatorMatrixSymmetricPositiveDefiniteTest(
+class SquareLinearOperatorFullMatrixSymmetricPositiveDefiniteTest(
     linear_operator_test_util.SquareLinearOperatorDerivedClassTest):
   """Most tests done in the base class LinearOperatorDerivedClassTest.
 
@@ -104,11 +104,11 @@ class SquareLinearOperatorMatrixSymmetricPositiveDefiniteTest(
       # values are random and we want the same value used for both mat and
       # feed_dict.
       matrix = matrix.eval()
-      operator = linalg.LinearOperatorMatrix(
+      operator = linalg.LinearOperatorFullMatrix(
           matrix, is_self_adjoint=True, is_positive_definite=True)
       feed_dict = {matrix_ph: matrix}
     else:
-      operator = linalg.LinearOperatorMatrix(
+      operator = linalg.LinearOperatorFullMatrix(
           matrix, is_self_adjoint=True, is_positive_definite=True)
       feed_dict = None
 
@@ -121,7 +121,7 @@ class SquareLinearOperatorMatrixSymmetricPositiveDefiniteTest(
   def test_is_x_flags(self):
     # Matrix with two positive eigenvalues.
     matrix = [[1., 0.], [0., 7.]]
-    operator = linalg.LinearOperatorMatrix(
+    operator = linalg.LinearOperatorFullMatrix(
         matrix, is_positive_definite=True, is_self_adjoint=True)
 
     self.assertTrue(operator.is_positive_definite)
@@ -132,7 +132,7 @@ class SquareLinearOperatorMatrixSymmetricPositiveDefiniteTest(
     self.assertTrue(operator._is_spd)
 
 
-class NonSquareLinearOperatorMatrixTest(
+class NonSquareLinearOperatorFullMatrixTest(
     linear_operator_test_util.NonSquareLinearOperatorDerivedClassTest):
   """Most tests done in the base class LinearOperatorDerivedClassTest."""
 
@@ -144,10 +144,10 @@ class NonSquareLinearOperatorMatrixTest(
       # values are random and we want the same value used for both mat and
       # feed_dict.
       matrix = matrix.eval()
-      operator = linalg.LinearOperatorMatrix(matrix)
+      operator = linalg.LinearOperatorFullMatrix(matrix)
       feed_dict = {matrix_ph: matrix}
     else:
-      operator = linalg.LinearOperatorMatrix(matrix)
+      operator = linalg.LinearOperatorFullMatrix(matrix)
       feed_dict = None
 
     # Convert back to Tensor.  Needed if use_placeholder, since then we have
@@ -159,7 +159,7 @@ class NonSquareLinearOperatorMatrixTest(
   def test_is_x_flags(self):
     # Matrix with two positive eigenvalues.
     matrix = [[3., 0.], [1., 1.]]
-    operator = linalg.LinearOperatorMatrix(
+    operator = linalg.LinearOperatorFullMatrix(
         matrix,
         is_positive_definite=True,
         is_non_singular=True,
@@ -170,7 +170,7 @@ class NonSquareLinearOperatorMatrixTest(
 
   def test_matrix_must_have_at_least_two_dims_or_raises(self):
     with self.assertRaisesRegexp(ValueError, "at least 2 dimensions"):
-      linalg.LinearOperatorMatrix([1.])
+      linalg.LinearOperatorFullMatrix([1.])
 
 
 if __name__ == "__main__":
diff --git a/tensorflow/contrib/linalg/python/ops/linear_operator_addition.py b/tensorflow/contrib/linalg/python/ops/linear_operator_addition.py
index 69e7f2bbd9..7617e1b591 100644
--- a/tensorflow/contrib/linalg/python/ops/linear_operator_addition.py
+++ b/tensorflow/contrib/linalg/python/ops/linear_operator_addition.py
@@ -24,8 +24,8 @@ import six
 
 from tensorflow.contrib.linalg.python.ops import linear_operator
 from tensorflow.contrib.linalg.python.ops import linear_operator_diag
+from tensorflow.contrib.linalg.python.ops import linear_operator_full_matrix
 from tensorflow.contrib.linalg.python.ops import linear_operator_identity
-from tensorflow.contrib.linalg.python.ops import linear_operator_matrix
 from tensorflow.contrib.linalg.python.ops import linear_operator_tril
 from tensorflow.python.framework import ops
 from tensorflow.python.ops import array_ops
@@ -356,7 +356,7 @@ class _AddAndReturnTriL(_Adder):
 
 
 class _AddAndReturnMatrix(_Adder):
-  """"Handles additions resulting in a `LinearOperatorMatrix`."""
+  """"Handles additions resulting in a `LinearOperatorFullMatrix`."""
 
   def can_add(self, op1, op2):  # pylint: disable=unused-argument
     return isinstance(op1, linear_operator.LinearOperator) and isinstance(
@@ -367,7 +367,7 @@ class _AddAndReturnMatrix(_Adder):
       op_add_to_tensor, op_other = op1, op2
     else:
       op_add_to_tensor, op_other = op2, op1
-    return linear_operator_matrix.LinearOperatorMatrix(
+    return linear_operator_full_matrix.LinearOperatorFullMatrix(
         matrix=op_add_to_tensor.add_to_tensor(op_other.to_dense()),
         is_non_singular=hints.is_non_singular,
         is_self_adjoint=hints.is_self_adjoint,
@@ -399,7 +399,7 @@ def _type(operator):
     return _DIAG
   if isinstance(operator, linear_operator_tril.LinearOperatorTriL):
     return _TRIL
-  if isinstance(operator, linear_operator_matrix.LinearOperatorMatrix):
+  if isinstance(operator, linear_operator_full_matrix.LinearOperatorFullMatrix):
     return _MATRIX
   if isinstance(operator, linear_operator_identity.LinearOperatorIdentity):
     return _IDENTITY
diff --git a/tensorflow/contrib/linalg/python/ops/linear_operator_composition.py b/tensorflow/contrib/linalg/python/ops/linear_operator_composition.py
index 781282eb35..11ce5e0e64 100644
--- a/tensorflow/contrib/linalg/python/ops/linear_operator_composition.py
+++ b/tensorflow/contrib/linalg/python/ops/linear_operator_composition.py
@@ -52,8 +52,8 @@ class LinearOperatorComposition(linear_operator.LinearOperator):
 
   ```python
   # Create a 2 x 2 linear operator composed of two 2 x 2 operators.
-  operator_1 = LinearOperatorMatrix([[1., 2.], [3., 4.]])
-  operator_2 = LinearOperatorMatrix([[1., 0.], [0., 1.]])
+  operator_1 = LinearOperatorFullMatrix([[1., 2.], [3., 4.]])
+  operator_2 = LinearOperatorFullMatrix([[1., 0.], [0., 1.]])
   operator = LinearOperatorComposition([operator_1, operator_2])
 
   operator.to_dense()
@@ -72,11 +72,11 @@ class LinearOperatorComposition(linear_operator.LinearOperator):
 
   # Create a [2, 3] batch of 4 x 5 linear operators.
   matrix_45 = tf.random_normal(shape=[2, 3, 4, 5])
-  operator_45 = LinearOperatorMatrix(matrix)
+  operator_45 = LinearOperatorFullMatrix(matrix)
 
   # Create a [2, 3] batch of 5 x 6 linear operators.
   matrix_56 = tf.random_normal(shape=[2, 3, 5, 6])
-  operator_56 = LinearOperatorMatrix(matrix_56)
+  operator_56 = LinearOperatorFullMatrix(matrix_56)
 
   # Compose to create a [2, 3] batch of 4 x 6 operators.
   opeartor_46 = LinearOperatorComposition([operator_45, operator_56])
diff --git a/tensorflow/contrib/linalg/python/ops/linear_operator_matrix.py b/tensorflow/contrib/linalg/python/ops/linear_operator_full_matrix.py
index 2bd99845d8..f8d0202baf 100644
--- a/tensorflow/contrib/linalg/python/ops/linear_operator_matrix.py
+++ b/tensorflow/contrib/linalg/python/ops/linear_operator_full_matrix.py
@@ -25,10 +25,10 @@ from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import linalg_ops
 from tensorflow.python.ops import math_ops
 
-__all__ = ["LinearOperatorMatrix"]
+__all__ = ["LinearOperatorFullMatrix"]
 
 
-class LinearOperatorMatrix(linear_operator.LinearOperator):
+class LinearOperatorFullMatrix(linear_operator.LinearOperator):
   """`LinearOperator` that wraps a [batch] matrix.
 
   This operator wraps a [batch] matrix `A` (which is a `Tensor`) with shape
@@ -39,7 +39,7 @@ class LinearOperatorMatrix(linear_operator.LinearOperator):
   ```python
   # Create a 2 x 2 linear operator.
   matrix = [[1., 2.], [3., 4.]]
-  operator = LinearOperatorMatrix(matrix)
+  operator = LinearOperatorFullMatrix(matrix)
 
   operator.to_dense()
   ==> [[1., 2.]
@@ -57,7 +57,7 @@ class LinearOperatorMatrix(linear_operator.LinearOperator):
 
   # Create a [2, 3] batch of 4 x 4 linear operators.
   matrix = tf.random_normal(shape=[2, 3, 4, 4])
-  operator = LinearOperatorMatrix(matrix)
+  operator = LinearOperatorFullMatrix(matrix)
   ```
 
   #### Shape compatibility
@@ -72,14 +72,14 @@ class LinearOperatorMatrix(linear_operator.LinearOperator):
 
   #### Performance
 
-  `LinearOperatorMatrix` has exactly the same performance as would be achieved
-  by using standard `TensorFlow` matrix ops.  Intelligent choices are made
-  based on the following initialization hints.
+  `LinearOperatorFullMatrix` has exactly the same performance as would be
+  achieved by using standard `TensorFlow` matrix ops.  Intelligent choices are
+  made based on the following initialization hints.
 
   * If `dtype` is real, and `is_self_adjoint` and `is_positive_definite`, a
     Cholesky factorization is used for the determinant and solve.
 
-  In all cases, suppose `operator` is a `LinearOperatorMatrix` of shape
+  In all cases, suppose `operator` is a `LinearOperatorFullMatrix` of shape
   `[M, N]`, and `x.shape = [N, R]`.  Then
 
   * `operator.apply(x)` is `O(M * N * R)`.
@@ -108,8 +108,8 @@ class LinearOperatorMatrix(linear_operator.LinearOperator):
                is_non_singular=None,
                is_self_adjoint=None,
                is_positive_definite=None,
-               name="LinearOperatorMatrix"):
-    """Initialize a `LinearOperatorMatrix`.
+               name="LinearOperatorFullMatrix"):
+    """Initialize a `LinearOperatorFullMatrix`.
 
     Args:
       matrix:  Shape `[B1,...,Bb, M, N]` with `b >= 0`, `M, N >= 0`.
@@ -139,7 +139,7 @@ class LinearOperatorMatrix(linear_operator.LinearOperator):
       if self._is_spd:
         self._chol = linalg_ops.cholesky(self._matrix)
 
-      super(LinearOperatorMatrix, self).__init__(
+      super(LinearOperatorFullMatrix, self).__init__(
           dtype=self._matrix.dtype,
           graph_parents=[self._matrix],
           is_non_singular=is_non_singular,
diff --git a/tensorflow/contrib/linalg/python/ops/linear_operator_test_util.py b/tensorflow/contrib/linalg/python/ops/linear_operator_test_util.py
index 8fed8f7c46..0b7fc3da39 100644
--- a/tensorflow/contrib/linalg/python/ops/linear_operator_test_util.py
+++ b/tensorflow/contrib/linalg/python/ops/linear_operator_test_util.py
@@ -336,7 +336,7 @@ class NonSquareLinearOperatorDerivedClassTest(LinearOperatorDerivedClassTest):
 
   Square shapes are never tested by this class, so if you want to test your
   operator with a square shape, create two test classes, the other subclassing
-  SquareLinearOperatorMatrixTest.
+  SquareLinearOperatorFullMatrixTest.
 
   Sub-classes must still define all abstractmethods from
   LinearOperatorDerivedClassTest that are not defined here.