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diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorContractionMkldnn.h b/unsupported/Eigen/CXX11/src/Tensor/TensorContractionMkldnn.h
deleted file mode 100644
index a97f043c1..000000000
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorContractionMkldnn.h
+++ /dev/null
@@ -1,116 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2018 Eugene Zhulenev <ezhulenev@google.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-#ifndef EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_MKLDNN_H
-#define EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_MKLDNN_H
-
-#if defined(EIGEN_USE_MKLDNN)
-// Support for MklDnn sgemm kernel in Tensor contractions:
-//
-// 1. Prepare packed Lhs/Rhs blocks from tensor expressions using
-//    DataMapper (see TensorContractionInputMapper).
-// 2. Invoke gemm kernel with packed blocks (replacement for default
-// gebp_kernel).
-
-namespace Eigen {
-namespace internal {
-
-template <typename Scalar, typename StorageIndex, typename DataMapper,
-          int StorageOrder>
-struct mkldnn_gemm_pack;
-
-// mkl_gemm_pack for ColMajor storage order.
-template <typename Scalar, typename StorageIndex, typename DataMapper>
-struct mkldnn_gemm_pack<Scalar, StorageIndex, DataMapper,
-                        /*StorageOrder*/ ColMajor> {
-  typedef typename internal::packet_traits<Scalar>::type Packet;
-  typedef typename DataMapper::LinearMapper LinearMapper;
-
-  enum { PacketSize = internal::packet_traits<Scalar>::size };
-
-  EIGEN_DONT_INLINE
-  void operator()(Scalar *block, const DataMapper &data_mapper,
-                  StorageIndex rows, StorageIndex cols) {
-    const StorageIndex unrolled_rows =
-        (rows / (4 * PacketSize)) * (4 * PacketSize);
-    const StorageIndex vectorized_rows = (rows / PacketSize) * PacketSize;
-
-    for (StorageIndex col = 0; col < cols; ++col) {
-      LinearMapper lm = data_mapper.getLinearMapper(0, col);
-
-      // Give compiler a strong possibility to unroll the loop.
-      for (StorageIndex i = 0; i < unrolled_rows; i += 4 * PacketSize) {
-        for (StorageIndex j = 0; j < 4; ++j) {
-          const Packet p = lm.template loadPacket<Packet>(i + j * PacketSize);
-          internal::pstoreu(block + j * PacketSize, p);
-        }
-        block += 4 * PacketSize;
-      }
-
-      // Process remaining rows with packets.
-      for (StorageIndex i = unrolled_rows; i < vectorized_rows;
-           i += PacketSize) {
-        const Packet p = lm.template loadPacket<Packet>(i);
-        internal::pstoreu(block, p);
-        block += PacketSize;
-      }
-
-      // Finalize with coefficients.
-      for (StorageIndex i = vectorized_rows; i < rows; ++i) {
-        *block = lm(i);
-        ++block;
-      }
-    }
-  }
-};
-
-template <typename Scalar, typename StorageIndex, typename OutputMapper,
-          bool ConjugateLhs = false, bool ConjugateRhs = false>
-struct mkldnn_gemm_kernel;
-
-// mkldnn_gemm_kernel for floats defined as a thin layer on top of mkldnn_sgemm.
-template <typename StorageIndex, typename OutputMapper, bool ConjugateLhs,
-          bool ConjugateRhs>
-struct mkldnn_gemm_kernel</*Scalar*/ float, StorageIndex, OutputMapper,
-                          ConjugateLhs, ConjugateRhs> {
-  EIGEN_DONT_INLINE
-  void operator()(const OutputMapper &output, const float *blockA,
-                  const float *blockB, const StorageIndex rows,
-                  const StorageIndex depth, const StorageIndex cols,
-                  float alpha) {
-    static const int max_index = (std::numeric_limits<int>::max)();
-
-    eigen_assert(max_index > rows);
-    eigen_assert(max_index > cols);
-    eigen_assert(max_index > depth);
-    eigen_assert(max_index > output.stride());
-
-    const int m = static_cast<int>(rows);
-    const int n = static_cast<int>(cols);
-    const int k = static_cast<int>(depth);
-
-    const char transposeA = ConjugateLhs ? 'Y' : 'N';
-    const char transposeB = ConjugateRhs ? 'Y' : 'N';
-
-    const int ldA = ConjugateLhs ? k : m;
-    const int ldB = ConjugateRhs ? n : k;
-    const int ldC = static_cast<int>(output.stride());
-
-    const float beta = 1.0;
-
-    mkldnn_status_t st = mkldnn_sgemm(&transposeA, &transposeB, &m, &n, &k,
-                                      &alpha, blockA, &ldA, blockB, &ldB, &beta,
-                                      const_cast<float*>(output.data()), &ldC);
-    eigen_assert(st == 0);
-  }
-};
-
-}  // namespace internal
-}  // namespace Eigen
-#endif  // EIGEN_USE_MKLDNN
-#endif  // EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_MKLDNN_H