From 3cd148f98338f8c03ce2757c528423338990a90d Mon Sep 17 00:00:00 2001
From: Eugene Zhulenev <ezhulenev@google.com>
Date: Tue, 9 Jul 2019 12:10:26 -0700
Subject: Fix expression evaluation heuristic for TensorSliceOp

---
 .../Eigen/CXX11/src/Tensor/TensorMorphing.h        | 22 ++++++++++++----------
 1 file changed, 12 insertions(+), 10 deletions(-)

(limited to 'unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h')

diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h b/unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h
index 8f6e987b3..9ab1415ac 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h
@@ -479,9 +479,12 @@ class TensorSlicingOp : public TensorBase<TensorSlicingOp<StartIndices, Sizes, X
 
 // Fixme: figure out the exact threshold
 namespace {
-template <typename Index, typename Device> struct MemcpyTriggerForSlicing {
+template <typename Index, typename Device, bool BlockAccess> struct MemcpyTriggerForSlicing {
   EIGEN_DEVICE_FUNC MemcpyTriggerForSlicing(const Device& device) : threshold_(2 * device.numThreads()) { }
-  EIGEN_DEVICE_FUNC bool operator ()(Index val) const { return val > threshold_; }
+  EIGEN_DEVICE_FUNC bool operator ()(Index total, Index contiguous) const {
+    const bool prefer_block_evaluation = BlockAccess && total > 32*1024;
+    return !prefer_block_evaluation && contiguous > threshold_;
+  }
 
  private:
   Index threshold_;
@@ -490,18 +493,18 @@ template <typename Index, typename Device> struct MemcpyTriggerForSlicing {
 // It is very expensive to start the memcpy kernel on GPU: we therefore only
 // use it for large copies.
 #ifdef EIGEN_USE_GPU
-template <typename Index> struct MemcpyTriggerForSlicing<Index, GpuDevice>  {
+template <typename Index, bool BlockAccess> struct MemcpyTriggerForSlicing<Index, GpuDevice, BlockAccess>  {
   EIGEN_DEVICE_FUNC MemcpyTriggerForSlicing(const GpuDevice&) { }
-  EIGEN_DEVICE_FUNC bool operator ()(Index val) const { return val > 4*1024*1024; }
+  EIGEN_DEVICE_FUNC bool operator ()(Index total, Index contiguous) const { return contiguous > 4*1024*1024; }
 };
 #endif
 
 // It is very expensive to start the memcpy kernel on GPU: we therefore only
 // use it for large copies.
 #ifdef EIGEN_USE_SYCL
-template <typename Index> struct MemcpyTriggerForSlicing<Index, Eigen::SyclDevice>  {
+template <typename Index, bool BlockAccess> struct MemcpyTriggerForSlicing<Index, Eigen::SyclDevice, BlockAccess>  {
   EIGEN_DEVICE_FUNC MemcpyTriggerForSlicing(const SyclDevice&) { }
-  EIGEN_DEVICE_FUNC bool operator ()(Index val) const { return val > 4*1024*1024; }
+  EIGEN_DEVICE_FUNC bool operator ()(Index total, Index contiguous) const { return contiguous > 4*1024*1024; }
 };
 #endif
 
@@ -592,8 +595,7 @@ struct TensorEvaluator<const TensorSlicingOp<StartIndices, Sizes, ArgType>, Devi
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(EvaluatorPointerType data) {
     m_impl.evalSubExprsIfNeeded(NULL);
     if (!NumTraits<typename internal::remove_const<Scalar>::type>::RequireInitialization
-        && data && m_impl.data()
-        && !BlockAccess) {
+        && data && m_impl.data()) {
       Index contiguous_values = 1;
       if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
         for (int i = 0; i < NumDims; ++i) {
@@ -611,8 +613,8 @@ struct TensorEvaluator<const TensorSlicingOp<StartIndices, Sizes, ArgType>, Devi
         }
       }
       // Use memcpy if it's going to be faster than using the regular evaluation.
-      const MemcpyTriggerForSlicing<Index, Device> trigger(m_device);
-      if (trigger(contiguous_values)) {
+      const MemcpyTriggerForSlicing<Index, Device, BlockAccess> trigger(m_device);
+      if (trigger(internal::array_prod(dimensions()), contiguous_values)) {
         EvaluatorPointerType src = (EvaluatorPointerType)m_impl.data();
         for (Index i = 0; i < internal::array_prod(dimensions()); i += contiguous_values) {
           Index offset = srcCoeff(i);
-- 
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