Fix matrix_inverse_tril_test handling the inverse of 0

The inverse of 0 is undefined, so when computing the inverse of a lower
triangular numpy array, we need to ensure the zeros in the upper
parts of the triangle remain as zero. After doing the inverse
of an array, iterator over the array and set the values above the
main diagonal to zero.
See: https://github.com/numpy/numpy/issues/11445
Fixes: #20013

1 files changed, 12 insertions, 1 deletions

diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/matrix_inverse_tril_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/matrix_inverse_tril_test.py
index 85d604e34a..49a9afe3f6 100644
--- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/matrix_inverse_tril_test.py
+++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/matrix_inverse_tril_test.py
@@ -29,6 +29,17 @@ from tensorflow.python.platform import test
 class MatrixInverseTriLBijectorTest(test.TestCase):
   """Tests the correctness of the Y = inv(tril) transformation."""
 
+  #The inverse of 0 is undefined, as the numbers above the main
+  #diagonal must be zero, we zero out these numbers after running inverse.
+  #See: https://github.com/numpy/numpy/issues/11445
+  def _inv(self, x):
+    y = np.linalg.inv(x)
+    #triu_indices only works on 2d arrays
+    #need to iterate over all the 2d arrays in a x-dimensional array.
+    for idx in np.ndindex(y.shape[0:-2]):
+      y[idx][np.triu_indices(y[idx].shape[-1], 1)] = 0
+    return y
+
   @test_util.run_in_graph_and_eager_modes
   def testComputesCorrectValues(self):
     inv = bijectors.MatrixInverseTriL(validate_args=True)
@@ -98,7 +109,7 @@ class MatrixInverseTriLBijectorTest(test.TestCase):
                      [2., 3.]]],
                    [[[4., 0.],
                      [5., -6.]]]], dtype=np.float32)
-    x_inv_ = np.linalg.inv(x_)
+    x_inv_ = self._inv(x_)
     expected_fldj_ = -4. * np.sum(
         np.log(np.abs(np.diagonal(x_, axis1=-2, axis2=-1))), axis=-1)