1 files changed, 82 insertions, 0 deletions
diff --git a/tensorflow/python/kernel_tests/sparse_matmul_op_test.py b/tensorflow/python/kernel_tests/sparse_matmul_op_test.py
new file mode 100644
index 0000000000..d87d15cae9
--- /dev/null
+++ b/tensorflow/python/kernel_tests/sparse_matmul_op_test.py
@@ -0,0 +1,82 @@
+"""Tests for tensorflow.ops.tf.matmul."""
+
+import tensorflow.python.platform
+
+import numpy as np
+import tensorflow as tf
+
+from tensorflow.python.kernel_tests import gradient_checker as gc
+
+
+def RandMatrix(rows, cols, tr):
+  if tr:
+    rows, cols = cols, rows
+  return (np.clip(np.random.uniform(low=-100.0, high=100.0, size=rows * cols),
+                  0, 100) / 100).reshape([rows, cols]).astype(np.float32)
+
+
+class SparseMatMulTest(tf.test.TestCase):
+
+  def _testCpuMatmul(self, x, y, tr_a=False, tr_b=False,
+                     sp_a=True, sp_b=False):
+    x_mat = np.matrix(x)
+    if tr_a:
+      x_mat = np.transpose(x_mat)
+    y_mat = np.matrix(y)
+    if tr_b:
+      y_mat = np.transpose(y_mat)
+    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)
+      out = tf_ans.eval()
+    self.assertAllClose(np_ans, out)
+    self.assertShapeEqual(np_ans, tf_ans)
+
+  def testFloatBasic(self):
+    x = np.arange(0., 4.).reshape([4, 1]).astype(np.float32)
+    y = np.arange(-1., 1.).reshape([1, 2]).astype(np.float32)
+    self._testCpuMatmul(x, y)
+
+  # Tests testing random sized matrices.
+  def testFloatRandom(self):
+    for _ in range(10):
+      for tr_a in [True, False]:
+        for tr_b in [True, False]:
+          for sp_a in [True, False]:
+            for sp_b in [True, False]:
+              n, k, m = np.random.randint(1, 100, size=3)
+              x = RandMatrix(n, k, tr_a)
+              y = RandMatrix(k, m, tr_b)
+              self._testCpuMatmul(x, y, tr_a, tr_b, sp_a, sp_b)
+
+
+class MatMulGradientTest(tf.test.TestCase):
+
+  def _testGradients(self, tr_a, tr_b, sp_a, sp_b, name):
+    with self.test_session():
+      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)
+      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
+    self.assertLess(err, 1e-3)
+
+  def testGradientInput(self):
+    for tr_a in [True, False]:
+      for tr_b in [True, False]:
+        for sp_a in [True, False]:
+          for sp_b in [True, False]:
+            name = "sparse_matmul_%s_%s_%s_%s" % (tr_a, tr_b, sp_a, sp_b)
+            self._testGradients(tr_a, tr_b, sp_a, sp_b, name)
+
+if __name__ == "__main__":
+  tf.test.main()