diff --git a/tensorflow/core/kernels/cuda_sparse.cc b/tensorflow/core/kernels/cuda_sparse.cc
index 7485bef45a2..9d4ddc13d0d 100644
--- a/tensorflow/core/kernels/cuda_sparse.cc
+++ b/tensorflow/core/kernels/cuda_sparse.cc
@@ -200,66 +200,6 @@ Status GpuSparse::Initialize() {
// Check the actual declarations in the cusparse.h header file.
//=============================================================================
-template <typename Scalar, typename SparseFn>
-static inline Status GtsvImpl(SparseFn op, cusparseHandle_t cusparse_handle,
- int m, int n, const Scalar* dl, const Scalar* d,
- const Scalar* du, Scalar* B, int ldb) {
- TF_RETURN_IF_GPUSPARSE_ERROR(op(cusparse_handle, m, n, AsCudaComplex(dl),
- AsCudaComplex(d), AsCudaComplex(du),
- AsCudaComplex(B), ldb));
- return Status::OK();
-}
-
-#define GTSV_INSTANCE(Scalar, sparse_prefix) \
- template <> \
- Status GpuSparse::Gtsv<Scalar>(int m, int n, const Scalar* dl, \
- const Scalar* d, const Scalar* du, Scalar* B, \
- int ldb) const { \
- DCHECK(initialized_); \
- return GtsvImpl(SPARSE_FN(gtsv, sparse_prefix), *gpusparse_handle_, m, n, \
- dl, d, du, B, ldb); \
- }
-
-TF_CALL_LAPACK_TYPES(GTSV_INSTANCE);
-
-#define GTSV_NO_PIVOT_INSTANCE(Scalar, sparse_prefix) \
- template <> \
- Status GpuSparse::GtsvNoPivot<Scalar>(int m, int n, const Scalar* dl, \
- const Scalar* d, const Scalar* du, \
- Scalar* B, int ldb) const { \
- DCHECK(initialized_); \
- return GtsvImpl(SPARSE_FN(gtsv_nopivot, sparse_prefix), \
- *gpusparse_handle_, m, n, dl, d, du, B, ldb); \
- }
-
-TF_CALL_LAPACK_TYPES(GTSV_NO_PIVOT_INSTANCE);
-
-template <typename Scalar, typename SparseFn>
-static inline Status GtsvStridedBatchImpl(SparseFn op,
- cusparseHandle_t cusparse_handle,
- int m, const Scalar* dl,
- const Scalar* d, const Scalar* du,
- Scalar* x, int batchCount,
- int batchStride) {
- TF_RETURN_IF_GPUSPARSE_ERROR(op(cusparse_handle, m, AsCudaComplex(dl),
- AsCudaComplex(d), AsCudaComplex(du),
- AsCudaComplex(x), batchCount, batchStride));
- return Status::OK();
-}
-
-#define GTSV_STRIDED_BATCH_INSTANCE(Scalar, sparse_prefix) \
- template <> \
- Status GpuSparse::GtsvStridedBatch<Scalar>( \
- int m, const Scalar* dl, const Scalar* d, const Scalar* du, Scalar* x, \
- int batchCount, int batchStride) const { \
- DCHECK(initialized_); \
- return GtsvStridedBatchImpl(SPARSE_FN(gtsvStridedBatch, sparse_prefix), \
- *gpusparse_handle_, m, dl, d, du, x, \
- batchCount, batchStride); \
- }
-
-TF_CALL_LAPACK_TYPES(GTSV_STRIDED_BATCH_INSTANCE);
-
template <typename Scalar, typename SparseFn>
static inline Status Gtsv2Impl(SparseFn op, cusparseHandle_t cusparse_handle,
int m, int n, const Scalar* dl, const Scalar* d,
diff --git a/tensorflow/core/kernels/cuda_sparse.h b/tensorflow/core/kernels/cuda_sparse.h
index f96a9b2187c..5dd62037ff0 100644
--- a/tensorflow/core/kernels/cuda_sparse.h
+++ b/tensorflow/core/kernels/cuda_sparse.h
@@ -190,37 +190,6 @@ class GpuSparse {
// Wrappers for cuSparse start here.
//
- // Solves tridiagonal system of equations.
- // Note: Cuda Toolkit 9.0+ has better-performing gtsv2 routine. gtsv will be
- // removed in Cuda Toolkit 11.0.
- // See: https://docs.nvidia.com/cuda/cusparse/index.html#cusparse-lt-t-gt-gtsv
- // Returns Status::OK() if the kernel was launched successfully.
- template <typename Scalar>
- Status Gtsv(int m, int n, const Scalar *dl, const Scalar *d, const Scalar *du,
- Scalar *B, int ldb) const;
-
- // Solves tridiagonal system of equations without pivoting.
- // Note: Cuda Toolkit 9.0+ has better-performing gtsv2_nopivot routine.
- // gtsv_nopivot will be removed in Cuda Toolkit 11.0.
- // See:
- // https://docs.nvidia.com/cuda/cusparse/index.html#cusparse-lt-t-gt-gtsv_nopivot
- // Returns Status::OK() if the kernel was launched successfully.
- template <typename Scalar>
- Status GtsvNoPivot(int m, int n, const Scalar *dl, const Scalar *d,
- const Scalar *du, Scalar *B, int ldb) const;
-
- // Solves a batch of tridiagonal systems of equations. Doesn't support
- // multiple right-hand sides per each system. Doesn't do pivoting.
- // Note: Cuda Toolkit 9.0+ has better-performing gtsv2StridedBatch routine.
- // gtsvStridedBatch will be removed in Cuda Toolkit 11.0.
- // See:
- // https://docs.nvidia.com/cuda/cusparse/index.html#cusparse-lt-t-gt-gtsvstridedbatch
- // Returns Status::OK() if the kernel was launched successfully.
- template <typename Scalar>
- Status GtsvStridedBatch(int m, const Scalar *dl, const Scalar *d,
- const Scalar *du, Scalar *x, int batchCount,
- int batchStride) const;
-
// Solves tridiagonal system of equations.
// See: https://docs.nvidia.com/cuda/cusparse/index.html#gtsv2
template <typename Scalar>
diff --git a/tensorflow/core/kernels/tridiagonal_solve_op_gpu.cu.cc b/tensorflow/core/kernels/tridiagonal_solve_op_gpu.cu.cc
index 3825e29189a..089fa8c040f 100644
--- a/tensorflow/core/kernels/tridiagonal_solve_op_gpu.cu.cc
+++ b/tensorflow/core/kernels/tridiagonal_solve_op_gpu.cu.cc
@@ -200,13 +200,6 @@ class TridiagonalSolveOpGpuLinalg : public LinearAlgebraOp<Scalar> {
const Scalar* superdiag, const Scalar* diag,
const Scalar* subdiag, Scalar* rhs, const int num_eqs,
const int num_rhs) const {
-#if CUDA_VERSION < 9000
- auto function =
- pivoting_ ? &GpuSparse::Gtsv<Scalar> : &GpuSparse::GtsvNoPivot<Scalar>;
- OP_REQUIRES_OK(
- context, (cusparse_solver.get()->*function)(
- num_eqs, num_rhs, subdiag, diag, superdiag, rhs, num_eqs));
-#else
auto buffer_function = pivoting_
? &GpuSparse::Gtsv2BufferSizeExt<Scalar>
: &GpuSparse::Gtsv2NoPivotBufferSizeExt<Scalar>;
@@ -225,7 +218,6 @@ class TridiagonalSolveOpGpuLinalg : public LinearAlgebraOp<Scalar> {
OP_REQUIRES_OK(context, (cusparse_solver.get()->*solver_function)(
num_eqs, num_rhs, subdiag, diag, superdiag, rhs,
num_eqs, buffer));
-#endif // CUDA_VERSION < 9000
}
void SolveForSizeOneOrTwo(OpKernelContext* context, const Scalar* diagonals,
@@ -318,11 +310,7 @@ class TridiagonalSolveOpGpu : public OpKernel {
std::unique_ptr<GpuSparse> cusparse_solver(new GpuSparse(context));
OP_REQUIRES_OK(context, cusparse_solver->Initialize());
-#if CUDA_VERSION < 9000
- OP_REQUIRES_OK(context, cusparse_solver->GtsvStridedBatch(
- matrix_size, subdiag, diag, superdiag, x,
- batch_size, matrix_size));
-#else
+
size_t buffer_size;
OP_REQUIRES_OK(context, cusparse_solver->Gtsv2StridedBatchBufferSizeExt(
matrix_size, subdiag, diag, superdiag, x,
@@ -335,7 +323,6 @@ class TridiagonalSolveOpGpu : public OpKernel {
OP_REQUIRES_OK(context, cusparse_solver->Gtsv2StridedBatch(
matrix_size, subdiag, diag, superdiag, x,
batch_size, matrix_size, buffer));
-#endif // CUDA_VERSION < 9000
}
void TransposeLhsForGtsvBatched(OpKernelContext* context, const Tensor& lhs,