slice layer ocl support

Signed-off-by: NLi Peng <peng.li@intel.com>

modules/dnn/src/layers/slice_layer.cpp

@@ -43,6 +43,7 @@
 #include "../precomp.hpp"
 #include "layers_common.hpp"
 #include <opencv2/dnn/shape_utils.hpp>
+#include "opencl_kernels_dnn.hpp"
 
 namespace cv
 {
@@ -171,11 +172,59 @@ public:
         }
     }
 
+#ifdef HAVE_OPENCL
+    bool forward_ocl(InputArrayOfArrays inputs_, OutputArrayOfArrays outputs_, OutputArrayOfArrays internals_)
+    {
+        std::vector<UMat> inputs;
+        std::vector<UMat> outputs;
+
+        inputs_.getUMatVector(inputs);
+        outputs_.getUMatVector(outputs);
+
+        if (inputs[0].dims < 4)
+            return false;
+
+        const UMat& inpMat = inputs[0];
+        for (size_t i = 0; i < outputs.size(); i++)
+        {
+            int groups = outputs[i].size[0];
+            int channels = outputs[i].size[1];
+            int rows = outputs[i].size[2];
+            int cols = outputs[i].size[3];
+
+            int number = (cols % 8 == 0) ? 8 : ((cols % 4 == 0) ? 4 : 1);
+            String buildopt = format("-DNUM=%d ", number);
+            String kname = format("slice%d", number);
+            ocl::Kernel kernel(kname.c_str(), ocl::dnn::slice_oclsrc, buildopt);
+            size_t global[] = { (size_t)groups * channels, (size_t)rows * cols / number };
+            int idx = 0;
+            kernel.set(idx++, ocl::KernelArg::PtrReadOnly(inpMat));
+            kernel.set(idx++, (int)(inpMat.size[2] * inpMat.size[3]));
+            kernel.set(idx++, (int)inpMat.size[3]);
+            kernel.set(idx++, (int)global[0]);
+            kernel.set(idx++, (int)(rows * cols));
+            kernel.set(idx++, (int)cols);
+            kernel.set(idx++, (int)sliceRanges[i][2].start);
+            kernel.set(idx++, (int)sliceRanges[i][3].start);
+            kernel.set(idx++, ocl::KernelArg::PtrWriteOnly(outputs[i]));
+            bool ret = kernel.run(2, global, NULL, false);
+            if (!ret)
+                return false;
+        }
+
+        return true;
+    }
+#endif
+
     void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
 
+        CV_OCL_RUN((preferableTarget == DNN_TARGET_OPENCL) &&
+                   OCL_PERFORMANCE_CHECK(ocl::Device::getDefault().isIntel()),
+                   forward_ocl(inputs_arr, outputs_arr, internals_arr))
+
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 

modules/dnn/src/opencl/slice.cl

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2017, Intel Corporation, all rights reserved.
+// Copyright (c) 2016-2017 Fabian David Tschopp, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#define Dtype float
+#define Dtype4 float4
+#define Dtype8 float8
+
+#if NUM == 8
+    #define load(src, index) vload8(0, src + index)
+    #define store(vec, dst, index) vstore8(vec, 0, dst + index)
+    #define vec_type Dtype8
+    #define SLICE slice8
+#elif NUM == 4
+    #define load(src, index) vload4(0, src + index)
+    #define store(vec, dst, index) vstore4(vec, 0, dst + index)
+    #define vec_type Dtype4
+    #define SLICE slice4
+#elif NUM == 1
+    #define load(src, index) src[index]
+    #define store(vec, dst, index) dst[index] = vec
+    #define vec_type Dtype
+    #define SLICE slice1
+#endif
+
+__kernel void SLICE(__global const Dtype* src,
+                    const int src_plane_size,
+                    const int src_cols,
+                    const int channels,
+                    const int dst_plane_size,
+                    const int dst_cols,
+                    const int row_offset,
+                    const int col_offset,
+                    __global Dtype* dst)
+{
+    int x = get_global_id(0);
+    int y = get_global_id(1) * NUM;
+
+    if ((x >= channels) || (y >= dst_plane_size))
+        return;
+
+    int row = y / dst_cols + row_offset;
+    int col = y % dst_cols + col_offset;
+
+    int src_index = x * src_plane_size + row * src_cols + col;
+    int dst_index = x * dst_plane_size + y;
+    vec_type val = load(src, src_index);
+    store(val, dst, dst_index);
+}

modules/dnn/test/test_layers.cpp

@@ -367,11 +367,14 @@ OCL_TEST(Layer_Test_PReLU, Accuracy)
 //    );
 //}
 
-static void test_Reshape_Split_Slice_layers()
+static void test_Reshape_Split_Slice_layers(int targetId)
 {
     Net net = readNetFromCaffe(_tf("reshape_and_slice_routines.prototxt"));
     ASSERT_FALSE(net.empty());
 
+    net.setPreferableBackend(DNN_BACKEND_DEFAULT);
+    net.setPreferableTarget(targetId);
+
     Mat input(6, 12, CV_32F);
     RNG rng(0);
     rng.fill(input, RNG::UNIFORM, -1, 1);
@@ -384,7 +387,12 @@ static void test_Reshape_Split_Slice_layers()
 
 TEST(Layer_Test_Reshape_Split_Slice, Accuracy)
 {
-    test_Reshape_Split_Slice_layers();
+    test_Reshape_Split_Slice_layers(DNN_TARGET_CPU);
+}
+
+OCL_TEST(Layer_Test_Reshape_Split_Slice, Accuracy)
+{
+    test_Reshape_Split_Slice_layers(DNN_TARGET_OPENCL);
 }
 
 TEST(Layer_Conv_Elu, Accuracy)