Add complex tensors support to matrix_determinant.

PiperOrigin-RevId: 161132422

tensorflow/contrib/linalg/python/ops/linear_operator_test_util.py

@@ -169,10 +169,6 @@ class LinearOperatorDerivedClassTest(test.TestCase):
     for use_placeholder in False, True:
       for shape in self._shapes_to_test:
         for dtype in self._dtypes_to_test:
-          if dtype.is_complex:
-            self.skipTest(
-                "tf.matrix_determinant does not work with complex, so this "
-                "test is being skipped.")
           with self.test_session(graph=ops.Graph()) as sess:
             sess.graph.seed = random_seed.DEFAULT_GRAPH_SEED
             operator, mat, feed_dict = self._operator_and_mat_and_feed_dict(
@@ -190,10 +186,6 @@ class LinearOperatorDerivedClassTest(test.TestCase):
     for use_placeholder in False, True:
       for shape in self._shapes_to_test:
         for dtype in self._dtypes_to_test:
-          if dtype.is_complex:
-            self.skipTest(
-                "tf.matrix_determinant does not work with complex, so this "
-                "test is being skipped.")
           with self.test_session(graph=ops.Graph()) as sess:
             sess.graph.seed = random_seed.DEFAULT_GRAPH_SEED
             operator, mat, feed_dict = self._operator_and_mat_and_feed_dict(

tensorflow/core/kernels/determinant_op.cc

@@ -18,6 +18,7 @@ limitations under the License.
 
 #include "third_party/eigen3/Eigen/LU"
 #include "tensorflow/core/framework/kernel_def_builder.h"
+#include "tensorflow/core/framework/numeric_types.h"
 #include "tensorflow/core/framework/op_kernel.h"
 #include "tensorflow/core/framework/tensor_shape.h"
 #include "tensorflow/core/kernels/linalg_ops_common.h"
@@ -62,7 +63,14 @@ class DeterminantOp : public LinearAlgebraOp<Scalar> {
 
 REGISTER_LINALG_OP("MatrixDeterminant", (DeterminantOp<float>), float);
 REGISTER_LINALG_OP("MatrixDeterminant", (DeterminantOp<double>), double);
+REGISTER_LINALG_OP("MatrixDeterminant", (DeterminantOp<complex64>), complex64);
+REGISTER_LINALG_OP("MatrixDeterminant", (DeterminantOp<complex128>),
+                   complex128);
 REGISTER_LINALG_OP("BatchMatrixDeterminant", (DeterminantOp<float>), float);
 REGISTER_LINALG_OP("BatchMatrixDeterminant", (DeterminantOp<double>), double);
+REGISTER_LINALG_OP("BatchMatrixDeterminant", (DeterminantOp<complex64>),
+                   complex64);
+REGISTER_LINALG_OP("BatchMatrixDeterminant", (DeterminantOp<complex128>),
+                   complex128);
 
 }  // namespace tensorflow

tensorflow/core/ops/linalg_ops.cc

@@ -189,7 +189,7 @@ Status SvdShapeFn(InferenceContext* c) {
 REGISTER_OP("MatrixDeterminant")
     .Input("input: T")
     .Output("output: T")
-    .Attr("T: {float, double}")
+    .Attr("T: {float, double, complex64, complex128}")
     .SetShapeFn([](InferenceContext* c) {
       ShapeHandle input;
       TF_RETURN_IF_ERROR(c->WithRankAtLeast(c->input(0), 2, &input));
@@ -560,7 +560,7 @@ REGISTER_OP("BatchSelfAdjointEig")
 REGISTER_OP("BatchMatrixDeterminant")
     .Input("input: T")
     .Output("output: T")
-    .Attr("T: {float, double}")
+    .Attr("T: {float, double, complex64, complex128}")
     .Deprecated(13, "Use MatrixDeterminant instead.");
 
 REGISTER_OP("BatchMatrixInverse")

tensorflow/python/kernel_tests/determinant_op_test.py

@@ -66,6 +66,41 @@ class DeterminantOpTest(test.TestCase):
     # A multidimensional batch of 2x2 matrices
     self._compareDeterminant(np.random.rand(3, 4, 5, 2, 2).astype(np.float64))
 
+  def testBasicComplex64(self):
+    # 2x2 matrices
+    self._compareDeterminant(
+        np.array([[2., 3.], [3., 4.]]).astype(np.complex64))
+    self._compareDeterminant(
+        np.array([[0., 0.], [0., 0.]]).astype(np.complex64))
+    self._compareDeterminant(
+        np.array([[1. + 1.j, 1. - 1.j], [-1. + 1.j, -1. - 1.j]]).astype(
+            np.complex64))
+    # 5x5 matrices (Eigen forces LU decomposition)
+    self._compareDeterminant(
+        np.array([[2., 3., 4., 5., 6.], [3., 4., 9., 2., 0.], [
+            2., 5., 8., 3., 8.
+        ], [1., 6., 7., 4., 7.], [2., 3., 4., 5., 6.]]).astype(np.complex64))
+    # A multidimensional batch of 2x2 matrices
+    self._compareDeterminant(np.random.rand(3, 4, 5, 2, 2).astype(np.complex64))
+
+  def testBasicComplex128(self):
+    # 2x2 matrices
+    self._compareDeterminant(
+        np.array([[2., 3.], [3., 4.]]).astype(np.complex128))
+    self._compareDeterminant(
+        np.array([[0., 0.], [0., 0.]]).astype(np.complex128))
+    self._compareDeterminant(
+        np.array([[1. + 1.j, 1. - 1.j], [-1. + 1.j, -1. - 1.j]]).astype(
+            np.complex128))
+    # 5x5 matrices (Eigen forces LU decomposition)
+    self._compareDeterminant(
+        np.array([[2., 3., 4., 5., 6.], [3., 4., 9., 2., 0.], [
+            2., 5., 8., 3., 8.
+        ], [1., 6., 7., 4., 7.], [2., 3., 4., 5., 6.]]).astype(np.complex128))
+    # A multidimensional batch of 2x2 matrices
+    self._compareDeterminant(
+        np.random.rand(3, 4, 5, 2, 2).astype(np.complex128))
+
   def testOverflow(self):
     max_double = np.finfo("d").max
     huge_matrix = np.array([[max_double, 0.0], [0.0, max_double]])