Adding Sycl backend for TensorImagePatchOP.h; adding Sycl backend for TensorInflation.h.

unsupported/Eigen/CXX11/src/Tensor/TensorImagePatch.h

@@ -70,12 +70,8 @@ class TensorImagePatchOp : public TensorBase<TensorImagePatchOp<Rows, Cols, XprT
                                                            DenseIndex in_row_strides, DenseIndex in_col_strides,
                                                            DenseIndex row_inflate_strides, DenseIndex col_inflate_strides,
                                                            PaddingType padding_type, Scalar padding_value)
-      : m_xpr(expr), m_patch_rows(patch_rows), m_patch_cols(patch_cols),
+      : TensorImagePatchOp(expr, patch_rows, patch_cols, row_strides,col_strides, in_row_strides, in_col_strides, row_inflate_strides,
-        m_row_strides(row_strides), m_col_strides(col_strides),
+         col_inflate_strides, 0,0,0,0,padding_value, padding_type, false ){}
-        m_in_row_strides(in_row_strides), m_in_col_strides(in_col_strides),
-        m_row_inflate_strides(row_inflate_strides), m_col_inflate_strides(col_inflate_strides),
-        m_padding_explicit(false), m_padding_top(0), m_padding_bottom(0), m_padding_left(0), m_padding_right(0),
-        m_padding_type(padding_type), m_padding_value(padding_value) {}
 
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorImagePatchOp(const XprType& expr, DenseIndex patch_rows, DenseIndex patch_cols,
                                                            DenseIndex row_strides, DenseIndex col_strides,
@@ -83,14 +79,15 @@ class TensorImagePatchOp : public TensorBase<TensorImagePatchOp<Rows, Cols, XprT
                                                            DenseIndex row_inflate_strides, DenseIndex col_inflate_strides,
                                                            DenseIndex padding_top, DenseIndex padding_bottom,
                                                            DenseIndex padding_left, DenseIndex padding_right,
-                                                           Scalar padding_value)
+                                                           Scalar padding_value, PaddingType padding_type=PADDING_VALID,
+                                                           bool padding_explicit=true)
       : m_xpr(expr), m_patch_rows(patch_rows), m_patch_cols(patch_cols),
         m_row_strides(row_strides), m_col_strides(col_strides),
         m_in_row_strides(in_row_strides), m_in_col_strides(in_col_strides),
         m_row_inflate_strides(row_inflate_strides), m_col_inflate_strides(col_inflate_strides),
-        m_padding_explicit(true), m_padding_top(padding_top), m_padding_bottom(padding_bottom),
+        m_padding_explicit(padding_explicit), m_padding_top(padding_top), m_padding_bottom(padding_bottom),
         m_padding_left(padding_left), m_padding_right(padding_right),
-        m_padding_type(PADDING_VALID), m_padding_value(padding_value) {}
+        m_padding_type(padding_type), m_padding_value(padding_value) {}
 
     EIGEN_DEVICE_FUNC
     DenseIndex patch_rows() const { return m_patch_rows; }
@@ -172,7 +169,7 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
   };
 
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
-      : m_impl(op.expression(), device)
+      : m_impl(op.expression(), device), m_op(op)
   {
     EIGEN_STATIC_ASSERT((NumDims >= 4), YOU_MADE_A_PROGRAMMING_MISTAKE);
 
@@ -241,6 +238,8 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
           break;
         default:
           eigen_assert(false && "unexpected padding");
+          m_outputCols=0; // silence the uninitialised warnig;
+          m_outputRows=0; //// silence the uninitialised warnig;
       }
     }
     eigen_assert(m_outputRows > 0);
@@ -420,7 +419,10 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
 
   EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
 
-  const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; }
+  // required by sycl
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const XprType& xpr() const { return m_op; }
+
 
   Index rowPaddingTop() const { return m_rowPaddingTop; }
   Index colPaddingLeft() const { return m_colPaddingLeft; }
@@ -501,6 +503,8 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
   Scalar m_paddingValue;
 
   TensorEvaluator<ArgType, Device> m_impl;
+  // required for sycl
+  const XprType& m_op;
 };
 
 

unsupported/Eigen/CXX11/src/Tensor/TensorInflation.h

@@ -215,6 +215,12 @@ struct TensorEvaluator<const TensorInflationOp<Strides, ArgType>, Device>
 
   EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
 
+  /// required by sycl in order to extract the accessor
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE  const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; }
+  /// required by sycl in order to extract the accessor
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE  const Strides& functor() const { return m_strides; }
+
+
  protected:
   Dimensions m_dimensions;
   array<Index, NumDims> m_outputStrides;

unsupported/Eigen/CXX11/src/Tensor/TensorSyclConvertToDeviceExpression.h

@@ -165,6 +165,20 @@ KERNELBROKERCONVERTCHIPPINGOP()
 
 
 
+
+/// specialisation of the \ref ConvertToDeviceExpression struct when the node type is TensorImagePatchOp
+#define KERNELBROKERCONVERTIMAGEPATCHOP(CVQual)\
+template<DenseIndex Rows, DenseIndex Cols, typename XprType>\
+struct ConvertToDeviceExpression<CVQual TensorImagePatchOp<Rows, Cols, XprType> >{\
+  typedef CVQual TensorImagePatchOp<Rows, Cols, typename ConvertToDeviceExpression<XprType>::Type> Type;\
+};
+KERNELBROKERCONVERTIMAGEPATCHOP(const)
+KERNELBROKERCONVERTIMAGEPATCHOP()
+#undef KERNELBROKERCONVERTIMAGEPATCHOP
+
+
+
+
 }  // namespace internal
 }  // namespace TensorSycl
 }  // namespace Eigen

unsupported/Eigen/CXX11/src/Tensor/TensorSyclExprConstructor.h

@@ -385,6 +385,24 @@ SYCLTENSORCHIPPINGOPEXPR(const)
 SYCLTENSORCHIPPINGOPEXPR()
 #undef SYCLTENSORCHIPPINGOPEXPR
 
+// TensorImagePatchOp
+#define SYCLTENSORIMAGEPATCHOPEXPR(CVQual)\
+template<DenseIndex Rows, DenseIndex Cols, typename OrigXprType, typename XprType, typename... Params>\
+struct  ExprConstructor<CVQual TensorImagePatchOp<Rows, Cols, OrigXprType>, CVQual TensorImagePatchOp<Rows, Cols, XprType>, Params... > {\
+  typedef ExprConstructor<OrigXprType, XprType, Params...> my_xpr_type;\
+  typedef CVQual TensorImagePatchOp<Rows, Cols, typename my_xpr_type::Type> Type;\
+  my_xpr_type xprExpr;\
+  Type expr;\
+  template <typename FuncDetector>\
+  ExprConstructor(FuncDetector &funcD, const utility::tuple::Tuple<Params...> &t)\
+  : xprExpr(funcD.xprExpr, t), expr(xprExpr.expr, funcD.m_patch_rows, funcD.m_patch_cols, funcD.m_row_strides, funcD.m_col_strides,\
+    funcD.m_in_row_strides, funcD.m_in_col_strides, funcD.m_row_inflate_strides, funcD.m_col_inflate_strides, \
+    funcD.m_padding_top, funcD.m_padding_bottom, funcD.m_padding_left, funcD.m_padding_right, funcD.m_padding_value, funcD.m_padding_type, funcD.m_padding_explicit){}\
+};
+
+SYCLTENSORIMAGEPATCHOPEXPR(const)
+SYCLTENSORIMAGEPATCHOPEXPR()
+#undef SYCLTENSORIMAGEPATCHOPEXPR
 
 
 // TensorLayoutSwapOp

unsupported/Eigen/CXX11/src/Tensor/TensorSyclExtractAccessor.h

@@ -226,6 +226,20 @@ SYCLTENSORCHIPPINGOPEXTACC()
 #undef SYCLTENSORCHIPPINGOPEXTACC
 
 
+// specialisation of the \ref ExtractAccessor struct when the node type is
+/// TensorImagePatchOp.
+#define SYCLTENSORIMAGEPATCHOPEXTACC(CVQual)\
+template<DenseIndex Rows, DenseIndex Cols, typename XprType, typename Dev>\
+struct ExtractAccessor<TensorEvaluator<CVQual TensorImagePatchOp<Rows, Cols, XprType>, Dev> >{\
+  static inline auto getTuple(cl::sycl::handler& cgh, const TensorEvaluator<CVQual TensorImagePatchOp<Rows, Cols, XprType>, Dev>& eval)\
+  RETURN_CPP11(AccessorConstructor::getTuple(cgh, eval.impl()))\
+};
+
+SYCLTENSORIMAGEPATCHOPEXTACC(const)
+SYCLTENSORIMAGEPATCHOPEXTACC()
+#undef SYCLTENSORIMAGEPATCHOPEXTACC
+
+
 // specialisation of the \ref ExtractAccessor struct when the node type is
 /// TensorLayoutSwapOp.
 #define SYCLTENSORLAYOUTSWAPOPEXTACC(CVQual)\

unsupported/Eigen/CXX11/src/Tensor/TensorSyclExtractFunctors.h

@@ -296,7 +296,7 @@ SYCLEXTRFUNCCONTRACTCONCAT(TensorConcatenationOp, axis(),)
 //TensorChippingOp
 #define SYCLEXTRFUNCCHIPPINGOP(CVQual)\
 template<DenseIndex DimId, typename XprType, typename Device>\
-struct FunctorExtractor<TensorEvaluator<CVQual TensorChippingOp<DimId, XprType>, Device>>{\
+struct FunctorExtractor<TensorEvaluator<CVQual TensorChippingOp<DimId, XprType>, Device> >{\
   FunctorExtractor<Eigen::TensorEvaluator<XprType, Device> > xprExpr;\
   const DenseIndex m_dim;\
   const DenseIndex m_offset;\
@@ -310,6 +310,40 @@ SYCLEXTRFUNCCHIPPINGOP(const)
 SYCLEXTRFUNCCHIPPINGOP()
 #undef SYCLEXTRFUNCCHIPPINGOP
 
+#define SYCLEXTRFUNCIMAGEPATCHOP(CVQual)\
+template<DenseIndex Rows, DenseIndex Cols, typename XprType, typename Device>\
+struct FunctorExtractor<TensorEvaluator<CVQual TensorImagePatchOp<Rows, Cols, XprType>, Device> >{\
+typedef CVQual TensorImagePatchOp<Rows, Cols, XprType> Self;\
+FunctorExtractor<Eigen::TensorEvaluator<XprType, Device> > xprExpr;\
+const DenseIndex m_patch_rows;\
+const DenseIndex m_patch_cols;\
+const DenseIndex m_row_strides;\
+const DenseIndex m_col_strides;\
+const DenseIndex m_in_row_strides;\
+const DenseIndex m_in_col_strides;\
+const DenseIndex m_row_inflate_strides;\
+const DenseIndex m_col_inflate_strides;\
+const bool m_padding_explicit;\
+const DenseIndex m_padding_top;\
+const DenseIndex m_padding_bottom;\
+const DenseIndex m_padding_left;\
+const DenseIndex m_padding_right;\
+const PaddingType m_padding_type;\
+const typename Self::Scalar m_padding_value;\
+FunctorExtractor(const TensorEvaluator<Self, Device>& expr)\
+: xprExpr(expr.impl()), m_patch_rows(expr.xpr().patch_rows()), m_patch_cols(expr.xpr().patch_cols()),\
+  m_row_strides(expr.xpr().row_strides()), m_col_strides(expr.xpr().col_strides()),\
+  m_in_row_strides(expr.xpr().in_row_strides()), m_in_col_strides(expr.xpr().in_col_strides()),\
+  m_row_inflate_strides(expr.xpr().row_inflate_strides()), m_col_inflate_strides(expr.xpr().col_inflate_strides()),\
+  m_padding_explicit(expr.xpr().padding_explicit()),m_padding_top(expr.xpr().padding_top()),\
+  m_padding_bottom(expr.xpr().padding_bottom()), m_padding_left(expr.xpr().padding_left()),\
+  m_padding_right(expr.xpr().padding_right()), m_padding_type(expr.xpr().padding_type()),\
+  m_padding_value(expr.xpr().padding_value()){}\
+};
+
+SYCLEXTRFUNCIMAGEPATCHOP(const)
+SYCLEXTRFUNCIMAGEPATCHOP()
+#undef SYCLEXTRFUNCIMAGEPATCHOP
 /// template deduction function for FunctorExtractor
 template <typename Evaluator>
 auto inline extractFunctors(const Evaluator& evaluator)-> FunctorExtractor<Evaluator> {

unsupported/Eigen/CXX11/src/Tensor/TensorSyclLeafCount.h

@@ -161,6 +161,16 @@ SLICESTRIDEOPLEAFCOUNT()
 #undef SLICESTRIDEOPLEAFCOUNT
 
 
+#define TENSORIMAGEPATCHOPLEAFCOUNT(CVQual)\
+template<DenseIndex Rows, DenseIndex Cols, typename XprType>\
+struct LeafCount<CVQual TensorImagePatchOp<Rows, Cols, XprType> >:CategoryCount<XprType>{};
+
+
+TENSORIMAGEPATCHOPLEAFCOUNT(const)
+TENSORIMAGEPATCHOPLEAFCOUNT()
+#undef TENSORIMAGEPATCHOPLEAFCOUNT
+
+
 } /// namespace TensorSycl
 } /// namespace internal
 } /// namespace Eigen

unsupported/Eigen/CXX11/src/Tensor/TensorSyclPlaceHolderExpr.h

@@ -221,6 +221,20 @@ SYCLSLICESTRIDEOPPLH()
 #undef SYCLSLICESTRIDEOPPLH
 
 
+
+/// specialisation of the \ref PlaceHolderExpression when the node is
+/// TensorImagePatchOp
+#define SYCLTENSORIMAGEPATCHOP(CVQual)\
+template<DenseIndex Rows, DenseIndex Cols, typename XprType, size_t N>\
+struct PlaceHolderExpression<CVQual TensorImagePatchOp<Rows, Cols, XprType>, N> {\
+  typedef CVQual TensorImagePatchOp<Rows, Cols, typename CalculateIndex <N, XprType>::ArgType> Type;\
+};
+
+SYCLTENSORIMAGEPATCHOP(const)
+SYCLTENSORIMAGEPATCHOP()
+#undef SYCLTENSORIMAGEPATCHOP
+
+
 /// template deduction for \ref PlaceHolderExpression struct
 template <typename Expr>
 struct createPlaceHolderExpression {

unsupported/test/CMakeLists.txt

@@ -169,6 +169,8 @@ if(EIGEN_TEST_CXX11)
     ei_add_test_sycl(cxx11_tensor_chipping_sycl "-std=c++11")
     ei_add_test_sycl(cxx11_tensor_patch_sycl "-std=c++11")
     ei_add_test_sycl(cxx11_tensor_layout_swap_sycl "-std=c++11")
+    ei_add_test_sycl(cxx11_tensor_image_patchOP_sycl "-std=c++11")
+    ei_add_test_sycl(cxx11_tensor_inflation_sycl "-std=c++11")
   endif(EIGEN_TEST_SYCL)
   # It should be safe to always run these tests as there is some fallback code for
   # older compiler that don't support cxx11.

unsupported/test/cxx11_tensor_inflation_sycl.cpp

@@ -0,0 +1,136 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Contact: <eigen@codeplay.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/.
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_NO_COMPLEX
+#define EIGEN_TEST_FUNC cxx11_tensor_inflation_sycl
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int64_t
+#define EIGEN_USE_SYCL
+
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+// Inflation Defenition for each dimention the inflated val would be
+//((dim-1)*strid[dim] +1)
+
+// for 1 dimnention vector of size 3 with value (4,4,4) with the inflated stride value of 3 would be changed to
+// tensor of size (2*3) +1 = 7 with the value of
+// (4, 0, 0, 4, 0, 0, 4).
+
+template <typename DataType, int DataLayout, typename IndexType>
+void test_simple_inflation_sycl(const Eigen::SyclDevice &sycl_device) {
+
+
+  IndexType sizeDim1 = 2;
+  IndexType sizeDim2 = 3;
+  IndexType sizeDim3 = 5;
+  IndexType sizeDim4 = 7;
+  array<IndexType, 4> tensorRange = {{sizeDim1, sizeDim2, sizeDim3, sizeDim4}};
+  Tensor<DataType, 4, DataLayout,IndexType> tensor(tensorRange);
+  Tensor<DataType, 4, DataLayout,IndexType> no_stride(tensorRange);
+  tensor.setRandom();
+
+  array<IndexType, 4> strides;
+  strides[0] = 1;
+  strides[1] = 1;
+  strides[2] = 1;
+  strides[3] = 1;
+
+
+  const size_t tensorBuffSize =tensor.size()*sizeof(DataType);
+  DataType* gpu_data_tensor  = static_cast<DataType*>(sycl_device.allocate(tensorBuffSize));
+  DataType* gpu_data_no_stride  = static_cast<DataType*>(sycl_device.allocate(tensorBuffSize));
+
+  TensorMap<Tensor<DataType, 4, DataLayout,IndexType>> gpu_tensor(gpu_data_tensor, tensorRange);
+  TensorMap<Tensor<DataType, 4, DataLayout,IndexType>> gpu_no_stride(gpu_data_no_stride, tensorRange);
+
+  sycl_device.memcpyHostToDevice(gpu_data_tensor, tensor.data(), tensorBuffSize);
+  gpu_no_stride.device(sycl_device)=gpu_tensor.inflate(strides);
+  sycl_device.memcpyDeviceToHost(no_stride.data(), gpu_data_no_stride, tensorBuffSize);
+
+  VERIFY_IS_EQUAL(no_stride.dimension(0), sizeDim1);
+  VERIFY_IS_EQUAL(no_stride.dimension(1), sizeDim2);
+  VERIFY_IS_EQUAL(no_stride.dimension(2), sizeDim3);
+  VERIFY_IS_EQUAL(no_stride.dimension(3), sizeDim4);
+
+  for (IndexType i = 0; i < 2; ++i) {
+    for (IndexType j = 0; j < 3; ++j) {
+      for (IndexType k = 0; k < 5; ++k) {
+        for (IndexType l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(tensor(i,j,k,l), no_stride(i,j,k,l));
+        }
+      }
+    }
+  }
+
+
+  strides[0] = 2;
+  strides[1] = 4;
+  strides[2] = 2;
+  strides[3] = 3;
+
+  IndexType inflatedSizeDim1 = 3;
+  IndexType inflatedSizeDim2 = 9;
+  IndexType inflatedSizeDim3 = 9;
+  IndexType inflatedSizeDim4 = 19;
+  array<IndexType, 4> inflatedTensorRange = {{inflatedSizeDim1, inflatedSizeDim2, inflatedSizeDim3, inflatedSizeDim4}};
+
+  Tensor<DataType, 4, DataLayout, IndexType> inflated(inflatedTensorRange);
+
+  const size_t inflatedTensorBuffSize =inflated.size()*sizeof(DataType);
+  DataType* gpu_data_inflated  = static_cast<DataType*>(sycl_device.allocate(inflatedTensorBuffSize));
+  TensorMap<Tensor<DataType, 4, DataLayout, IndexType>> gpu_inflated(gpu_data_inflated, inflatedTensorRange);
+  gpu_inflated.device(sycl_device)=gpu_tensor.inflate(strides);
+  sycl_device.memcpyDeviceToHost(inflated.data(), gpu_data_inflated, inflatedTensorBuffSize);
+
+  VERIFY_IS_EQUAL(inflated.dimension(0), inflatedSizeDim1);
+  VERIFY_IS_EQUAL(inflated.dimension(1), inflatedSizeDim2);
+  VERIFY_IS_EQUAL(inflated.dimension(2), inflatedSizeDim3);
+  VERIFY_IS_EQUAL(inflated.dimension(3), inflatedSizeDim4);
+
+  for (IndexType i = 0; i < inflatedSizeDim1; ++i) {
+    for (IndexType j = 0; j < inflatedSizeDim2; ++j) {
+      for (IndexType k = 0; k < inflatedSizeDim3; ++k) {
+        for (IndexType l = 0; l < inflatedSizeDim4; ++l) {
+          if (i % strides[0] == 0 &&
+              j % strides[1] == 0 &&
+              k % strides[2] == 0 &&
+              l % strides[3] == 0) {
+            VERIFY_IS_EQUAL(inflated(i,j,k,l),
+                            tensor(i/strides[0], j/strides[1], k/strides[2], l/strides[3]));
+          } else {
+            VERIFY_IS_EQUAL(0, inflated(i,j,k,l));
+          }
+        }
+      }
+    }
+  }
+  sycl_device.deallocate(gpu_data_tensor);
+  sycl_device.deallocate(gpu_data_no_stride);
+  sycl_device.deallocate(gpu_data_inflated);
+}
+
+template<typename DataType, typename dev_Selector> void sycl_inflation_test_per_device(dev_Selector s){
+  QueueInterface queueInterface(s);
+  auto sycl_device = Eigen::SyclDevice(&queueInterface);
+  test_simple_inflation_sycl<DataType, RowMajor, int64_t>(sycl_device);
+  test_simple_inflation_sycl<DataType, ColMajor, int64_t>(sycl_device);
+}
+void test_cxx11_tensor_inflation_sycl()
+{
+  for (const auto& device :Eigen::get_sycl_supported_devices()) {
+    CALL_SUBTEST(sycl_inflation_test_per_device<float>(device));
+  }
+}