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diff --git a/tensorflow/python/kernel_tests/matrix_inverse_op_test.py b/tensorflow/python/kernel_tests/matrix_inverse_op_test.py
new file mode 100644
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+++ b/tensorflow/python/kernel_tests/matrix_inverse_op_test.py
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+"""Tests for tensorflow.ops.math_ops.matrix_inverse."""
+import tensorflow.python.platform
+
+import numpy as np
+import tensorflow as tf
+
+
+class InverseOpTest(tf.test.TestCase):
+
+  def _verifyInverse(self, x):
+    for np_type in [np.float32, np.float64]:
+      y = x.astype(np_type)
+      with self.test_session():
+        # Verify that x^{-1} * x == Identity matrix.
+        if x.ndim == 2:
+          inv = tf.matrix_inverse(y)
+          tf_ans = tf.matmul(inv, y)
+          np_ans = np.identity(y.shape[-1])
+        else:
+          inv = tf.batch_matrix_inverse(y)
+          tf_ans = tf.batch_matmul(inv, y)
+          tiling = list(y.shape)
+          tiling[-2:] = [1, 1]
+          np_ans = np.tile(np.identity(y.shape[-1]), tiling)
+        out = tf_ans.eval()
+      self.assertAllClose(np_ans, out)
+      self.assertShapeEqual(y, tf_ans)
+
+  def testBasic(self):
+    # 2x2 matrices
+    matrix1 = np.array([[1., 2.], [3., 4.]])
+    matrix2 = np.array([[1., 3.], [3., 5.]])
+    self._verifyInverse(matrix1)
+    self._verifyInverse(matrix2)
+    # A multidimensional batch of 2x2 matrices
+    matrix_batch = np.concatenate([np.expand_dims(matrix1, 0),
+                                   np.expand_dims(matrix2, 0)])
+    matrix_batch = np.tile(matrix_batch, [2, 3, 1, 1])
+    self._verifyInverse(matrix_batch)
+
+  def testNonSquareMatrix(self):
+    # When the inverse of a non-square matrix is attempted we should return
+    # an error
+    with self.assertRaises(ValueError):
+      tf.matrix_inverse(np.array([[1., 2., 3.], [3., 4., 5.]]))
+
+  def testWrongDimensions(self):
+    # The input to the inverse should be at least a 2-dimensional tensor.
+    tensor3 = tf.constant([1., 2.])
+    with self.assertRaises(ValueError):
+      tf.matrix_inverse(tensor3)
+
+  def testNotInvertible(self):
+    # The input should be invertible.
+    with self.test_session():
+      with self.assertRaisesOpError("Input is not invertible."):
+        # All rows of the matrix below add to zero
+        tensor3 = tf.constant([[1., 0., -1.], [-1., 1., 0.], [0., -1., 1.]])
+        tf.matrix_inverse(tensor3).eval()
+
+    with self.test_session():
+      with self.assertRaisesOpError("Input is not invertible."):
+        # Determinant of the matrix below is zero
+        tensor3 = tf.constant([[1., 1.], [1., 1.]])
+        tf.matrix_inverse(tensor3).eval()
+
+    with self.test_session():
+      with self.assertRaisesOpError("Input is not invertible."):
+        # Determinant of the matrix below is zero
+        tensor3 = tf.constant([[np.inf, 1.], [1., 1.]])
+        tf.matrix_inverse(tensor3).eval()
+
+  def testEmpty(self):
+    self._verifyInverse(np.empty([0, 2, 2]))
+    self._verifyInverse(np.empty([2, 0, 0]))
+
+
+if __name__ == "__main__":
+  tf.test.main()