Remove legacy block evaluation support

1 files changed, 0 insertions, 108 deletions

diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorReverse.h b/unsupported/Eigen/CXX11/src/Tensor/TensorReverse.h
index ae3ab5f81..1db5d2e5e 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorReverse.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorReverse.h
@@ -115,7 +115,6 @@ struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device
   enum {
     IsAligned         = false,
     PacketAccess      = TensorEvaluator<ArgType, Device>::PacketAccess,
-    BlockAccess       = true,
     BlockAccessV2     = NumDims > 0,
     PreferBlockAccess = true,
     Layout            = TensorEvaluator<ArgType, Device>::Layout,
@@ -248,112 +247,6 @@ struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device
         internal::kSkewedInnerDims, block_total_size_max));
   }
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void block(
-      OutputTensorBlock* output_block) const {
-    if (NumDims <= 0) return;
-
-    // TODO(ezhulenev): If underlying tensor expression supports and prefers
-    // block evaluation we must use it. Currently we use coeff and packet
-    // access into the underlying tensor expression.
-    // static const bool useBlockAccessForArgType =
-    //     TensorEvaluator<ArgType, Device>::BlockAccess &&
-    //     TensorEvaluator<ArgType, Device>::PreferBlockAccess;
-
-    static const bool isColMajor =
-        static_cast<int>(Layout) == static_cast<int>(ColMajor);
-
-    static const Index inner_dim_idx = isColMajor ? 0 : NumDims - 1;
-    const bool inner_dim_reversed = m_reverse[inner_dim_idx];
-
-    CoeffReturnType* data = output_block->data();
-    Index block_offset = 0;
-
-    Index input_offset = reverseIndex(output_block->first_coeff_index());
-
-    // Initialize output block iterator state. Dimension in this array are
-    // always in inner_most -> outer_most order (col major layout).
-    array<BlockIteratorState, NumDims> it;
-    for (Index i = 0; i < NumDims; ++i) {
-      const Index dim = isColMajor ? i : NumDims - 1 - i;
-      it[i].size = output_block->block_sizes()[dim];
-      it[i].count = 0;
-      it[i].reverse = m_reverse[dim];
-
-      it[i].block_stride = output_block->block_strides()[dim];
-      it[i].block_span = it[i].block_stride * (it[i].size - 1);
-
-      it[i].input_stride = m_strides[dim];
-      it[i].input_span = it[i].input_stride * (it[i].size - 1);
-
-      if (it[i].reverse) {
-        it[i].input_stride = -1 * it[i].input_stride;
-        it[i].input_span = -1 * it[i].input_span;
-      }
-    }
-
-    // If multiple inner dimensions have the same reverse flag, check if we can
-    // merge them into a single virtual inner dimension.
-    int effective_inner_dim = 0;
-    for (int i = 1; i < NumDims; ++i) {
-      if (it[i].reverse != it[effective_inner_dim].reverse) break;
-      if (it[i].block_stride != it[effective_inner_dim].size) break;
-      if (it[i].block_stride != numext::abs(it[i].input_stride)) break;
-
-      it[i].size = it[effective_inner_dim].size * it[i].size;
-
-      it[i].block_stride = 1;
-      it[i].input_stride = (inner_dim_reversed ? -1 : 1);
-
-      it[i].block_span = it[i].block_stride * (it[i].size - 1);
-      it[i].input_span = it[i].input_stride * (it[i].size - 1);
-
-      effective_inner_dim = i;
-    }
-
-    eigen_assert(it[effective_inner_dim].block_stride == 1);
-    eigen_assert(it[effective_inner_dim].input_stride ==
-                 (inner_dim_reversed ? -1 : 1));
-
-    const Index inner_dim_size = it[effective_inner_dim].size;
-
-    while (it[NumDims - 1].count < it[NumDims - 1].size) {
-      // Copy inner-most dimension data from reversed location in input.
-      Index dst = block_offset;
-      Index src = input_offset;
-
-      // NOTE(ezhulenev): Adding vectorized path with internal::preverse showed
-      // worse results in benchmarks than a simple coefficient loop.
-      if (inner_dim_reversed) {
-        for (Index i = 0; i < inner_dim_size; ++i) {
-          data[dst] = m_impl.coeff(src);
-          ++dst;
-          --src;
-        }
-      } else {
-        for (Index i = 0; i < inner_dim_size; ++i) {
-          data[dst] = m_impl.coeff(src);
-          ++dst;
-          ++src;
-        }
-      }
-
-      // For the 1d tensor we need to generate only one inner-most dimension.
-      if ((NumDims - effective_inner_dim) == 1) break;
-
-      // Update offset.
-      for (Index i = effective_inner_dim + 1; i < NumDims; ++i) {
-        if (++it[i].count < it[i].size) {
-          block_offset += it[i].block_stride;
-          input_offset += it[i].input_stride;
-          break;
-        }
-        if (i != NumDims - 1) it[i].count = 0;
-        block_offset -= it[i].block_span;
-        input_offset -= it[i].input_span;
-      }
-    }
-  }
-
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorBlockV2
   blockV2(TensorBlockDesc& desc, TensorBlockScratch& scratch,
           bool /*root_of_expr_ast*/ = false) const {
@@ -535,7 +428,6 @@ struct TensorEvaluator<TensorReverseOp<ReverseDimensions, ArgType>, Device>
   enum {
     IsAligned = false,
     PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
-    BlockAccess = false,
     BlockAccessV2 = false,
     PreferBlockAccess = false,
     Layout = TensorEvaluator<ArgType, Device>::Layout,