TensorFlow: Upstream changes to git

Changes:
- Updates to docs
- Several changes for Python 3 compatibility
- Added license headers

Base CL: 108710566

1 files changed, 23 insertions, 10 deletions

diff --git a/tensorflow/python/kernel_tests/sparse_matmul_op_test.py b/tensorflow/python/kernel_tests/sparse_matmul_op_test.py
index 3e5e059327..8f0c60c455 100644
--- a/tensorflow/python/kernel_tests/sparse_matmul_op_test.py
+++ b/tensorflow/python/kernel_tests/sparse_matmul_op_test.py
@@ -46,11 +46,11 @@ class SparseMatMulTest(tf.test.TestCase):
     np_ans = x_mat * y_mat
     with self.test_session(use_gpu=False):
       tf_ans = tf.matmul(x, y,
-                                transpose_a=tr_a, transpose_b=tr_b,
-                                a_is_sparse=sp_a,
-                                b_is_sparse=sp_b)
+                         transpose_a=tr_a, transpose_b=tr_b,
+                         a_is_sparse=sp_a,
+                         b_is_sparse=sp_b)
       out = tf_ans.eval()
-    self.assertAllClose(np_ans, out)
+    self.assertAllClose(np_ans, out, rtol=1e-4, atol=1e-4)
     self.assertShapeEqual(np_ans, tf_ans)
 
   def testFloatBasic(self):
@@ -58,7 +58,20 @@ class SparseMatMulTest(tf.test.TestCase):
     y = np.arange(-1., 1.).reshape([1, 2]).astype(np.float32)
     self._testCpuMatmul(x, y)
 
-  # Tests testing random sized matrices.
+  # Tests setting one dimension to be a high value.
+  def testFloatLarge(self):
+    r1 = np.random.randint(6000, 20000)
+    r2 = np.random.randint(1, 10)
+    r3 = np.random.randint(1, 10)
+    for m, k, n in [(r1, r2, r3),
+                    (r2, r1, r3),
+                    (r2, r3, r1)]:
+      x = RandMatrix(m, k, False)
+      y = RandMatrix(k, n, False)
+      self._testCpuMatmul(x, y)
+      self._testCpuMatmul(x, y, sp_a=False, sp_b=True)
+
+  # Tests random sized matrices.
   def testFloatRandom(self):
     for _ in range(10):
       for tr_a in [True, False]:
@@ -78,11 +91,11 @@ class MatMulGradientTest(tf.test.TestCase):
       a = tf.constant(RandMatrix(3, 2, tr_a), dtype=tf.float32)
       b = tf.constant(RandMatrix(2, 4, tr_b), dtype=tf.float32)
       m = tf.matmul(a, b,
-                           name=name,
-                           transpose_a=tr_a,
-                           transpose_b=tr_b,
-                           a_is_sparse=sp_a,
-                           b_is_sparse=sp_b)
+                    name=name,
+                    transpose_a=tr_a,
+                    transpose_b=tr_b,
+                    a_is_sparse=sp_a,
+                    b_is_sparse=sp_b)
       err = (gc.ComputeGradientError(a, [2, 3] if tr_a else [3, 2], m, [3, 4]) +
              gc.ComputeGradientError(b, [4, 2] if tr_b else [2, 4], m, [3, 4]))
     print("sparse_matmul gradient err = ", err)