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diff --git a/tensorflow/core/ops/linalg_ops.cc b/tensorflow/core/ops/linalg_ops.cc
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+++ b/tensorflow/core/ops/linalg_ops.cc
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+#include "tensorflow/core/framework/op.h"
+
+namespace tensorflow {
+
+REGISTER_OP("MatrixDeterminant")
+    .Input("input: T")
+    .Output("output: T")
+    .Attr("T: {float, double}")
+    .Doc(R"doc(
+Calculates the determinant of a square matrix.
+
+input: A tensor of shape `[M, M]`.
+output: A scalar, equal to the determinant of the input.
+T: The type of values in the input and output.
+)doc");
+
+REGISTER_OP("BatchMatrixDeterminant")
+    .Input("input: T")
+    .Output("output: T")
+    .Attr("T: {float, double}")
+    .Doc(R"doc(
+Calculates the determinants for a batch of square matrices.
+
+The input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions
+form square matrices. The output is a 1-D tensor containing the determinants
+for all input submatrices `[..., :, :]`.
+
+input: Shape is `[..., M, M]`.
+output: Shape is `[...]`.
+T: The type of values in the input and output.
+)doc");
+
+REGISTER_OP("MatrixInverse")
+    .Input("input: T")
+    .Output("output: T")
+    .Attr("T: {float, double}")
+    .Doc(R"doc(
+Calculates the inverse of a square invertible matrix. Checks for invertibility.
+
+input: Shape is `[M, M]`.
+output: Shape is `[M, M]` containing the matrix inverse of the input.
+T: The type of values in the input and output.
+)doc");
+
+REGISTER_OP("BatchMatrixInverse")
+    .Input("input: T")
+    .Output("output: T")
+    .Attr("T: {float, double}")
+    .Doc(R"doc(
+Calculates the inverse of square invertible matrices. Checks for invertibility.
+
+The input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions
+form square matrices. The output is a tensor of the same shape as the input
+containing the inverse for all input submatrices `[..., :, :]`.
+
+input: Shape is `[..., M, M]`.
+output: Shape is `[..., M, M]`.
+T: The type of values in the input and output.
+)doc");
+
+REGISTER_OP("Cholesky")
+    .Input("input: T")
+    .Output("output: T")
+    .Attr("T: {double, float}")
+    .Doc(R"doc(
+Calculates the Cholesky decomposition of a square matrix.
+
+The input has to be symmetric and positive definite. Only the lower-triangular
+part of the input will be used for this operation. The upper-triangular part
+will not be read.
+
+The result is the lower-triangular matrix of the Cholesky decomposition of the
+input.
+
+input: Shape is `[M, M]`.
+output: Shape is `[M, M]`.
+T: The type of values in the input and output.
+)doc");
+
+REGISTER_OP("BatchCholesky")
+    .Input("input: T")
+    .Output("output: T")
+    .Attr("T: {double, float}")
+    .Doc(R"doc(
+Calculates the Cholesky decomposition of a batch of square matrices.
+
+The input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions
+form square matrices, with the same constraints as the single matrix Cholesky
+decomposition above. The output is a tensor of the same shape as the input
+containing the Cholesky decompositions for all input submatrices `[..., :, :]`.
+
+input: Shape is `[..., M, M]`.
+output: Shape is `[..., M, M]`.
+T: The type of values in the input and output.
+)doc");
+
+}  // namespace tensorflow