COMPMID-1648: CLNormalizationLayer IN_MAP_2D support for NHWC for FP32/FP16

Change-Id: I49f1d865f5e7562f1d80db849353a89ef77e6a9e

1 files changed, 85 insertions, 3 deletions

diff --git a/src/core/CL/cl_kernels/normalization_layer.cl b/src/core/CL/cl_kernels/normalization_layer.cl
index 0b6df39c9a..390f8fcbeb 100644
--- a/src/core/CL/cl_kernels/normalization_layer.cl
+++ b/src/core/CL/cl_kernels/normalization_layer.cl
@@ -32,6 +32,7 @@
 #define LOAD_OP(offset, ptr) vload4(offset, ptr)
 #define STORE_OP(data, offset, ptr) vstore4(data, offset, ptr)
 
+#if defined(NUM_SLICES)
 /** Apply cross-map normalization.
  *
  * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
@@ -91,9 +92,10 @@ __kernel void normalization_layer_cross_map(TENSOR3D_DECLARATION(input),
 
     STORE_OP(normalized_pixel, 0, (__global DATA_TYPE *)out.ptr);
 }
+#endif /* defined(NUM_SLICES) */
 
 #if defined(WIDTH_SIZE)
-/** Apply in-map normalization.
+/** Apply in-map normalization when tensors are in the NCHW data layout format.
  *
  * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
  * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size, e.g. -DVEC_SIZE=16
@@ -117,8 +119,8 @@ __kernel void normalization_layer_cross_map(TENSOR3D_DECLARATION(input),
  * @param[in]  output_step_z                        output_stride_z * number of elements along Z processed per workitem(in bytes)
  * @param[in]  output_offset_first_element_in_bytes The offset of the first element in the destination tensor
  */
-__kernel void normalization_layer_in_map(TENSOR3D_DECLARATION(input),
-                                         TENSOR3D_DECLARATION(output))
+__kernel void normalization_layer_in_map_nchw(TENSOR3D_DECLARATION(input),
+                                              TENSOR3D_DECLARATION(output))
 {
     Tensor3D in  = CONVERT_TO_TENSOR3D_STRUCT(input);
     Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output);
@@ -170,3 +172,83 @@ __kernel void normalization_layer_in_map(TENSOR3D_DECLARATION(input),
     STORE_OP(normalized_pixel, 0, (__global DATA_TYPE *)out.ptr);
 }
 #endif // defined(WIDTH_SIZE)
+
+#if defined(NUM_SLICES)
+/** Apply in-map normalization when tensors are in the NHWC data layout format.
+ *
+ * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
+ * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size, e.g. -DVEC_SIZE=16
+ * @note The radius should be given as a preprocessor argument using -DRADIUS=size. e.g. -DRADIUS=5
+ * @note The number of slices should be given as a preprocessor argument using -DNUM_SLICES=size. e.g. -DNUM_SLICES=192
+ * @note Scaling coefficient (= alpha/norm_size), beta and kappa need to be passed at compile time using -DCOEFF, -DALPHA and -DKAPPA
+ *
+ * @param[in]  input_ptr                            Pointer to the first source tensor. Supported data types: F16/F32
+ * @param[in]  input_stride_x                       Stride of the first source tensor in X dimension (in bytes)
+ * @param[in]  input_step_x                         input_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  input_stride_y                       Stride of the first source tensor in Y dimension (in bytes)
+ * @param[in]  input_step_y                         input_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  input_stride_z                       Stride of the first source tensor in Z dimension (in bytes)
+ * @param[in]  input_step_z                         input_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in]  input_offset_first_element_in_bytes  The offset of the first element in the first source tensor
+ * @param[out] output_ptr                           Pointer to the destination tensor. Supported data types: same as @p input_ptr
+ * @param[in]  output_stride_x                      Stride of the destination tensor in X dimension (in bytes)
+ * @param[in]  output_step_x                        output_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  output_stride_y                      Stride of the first destination tensor in Y dimension (in bytes)
+ * @param[in]  output_step_y                        output_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  output_stride_z                      Stride of the first source tensor in Z dimension (in bytes)
+ * @param[in]  output_step_z                        output_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in]  output_offset_first_element_in_bytes The offset of the first element in the destination tensor
+ */
+__kernel void normalization_layer_in_map_nhwc(TENSOR3D_DECLARATION(input),
+                                              TENSOR3D_DECLARATION(output))
+{
+    Tensor3D in  = CONVERT_TO_TENSOR3D_STRUCT(input);
+    Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output);
+
+    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+    acc = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))0;
+    const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+    coeff_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(COEFF);
+    const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+    beta_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(BETA);
+    const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+    kappa_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(KAPPA);
+
+    const int current_cols = get_global_id(1);
+    const int first_col    = max(-(int)RADIUS, -current_cols);
+    const int last_col     = min((int)RADIUS, (int)get_global_size(1) - 1 - current_cols);
+
+#if defined(IN_MAP_2D)
+    const int current_rows = get_global_id(2);
+    const int first_row    = max(-(int)RADIUS, -current_rows);
+    const int last_row     = min((int)RADIUS, (int)NUM_SLICES - 1 - current_rows);
+#endif /* defined(IN_MAP_2D) */
+
+#if defined(IN_MAP_2D)
+    for(int j = first_row; j <= last_row; ++j)
+    {
+#endif /* defined(IN_MAP_2D) */
+        for(int i = first_col; i <= last_col; ++i)
+        {
+#if defined(IN_MAP_2D)
+            VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+            values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, 0, i, j));
+#else  /* defined(IN_MAP_2D) */
+            VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+            values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, 0, i, 0));
+#endif /* defined(IN_MAP_2D) */
+            acc = ADD_OP(acc, MUL_OP(values, values));
+        }
+#if defined(IN_MAP_2D)
+    }
+#endif /* defined(IN_MAP_2D) */
+
+    acc = ADD_OP(MUL_OP(acc, coeff_v), kappa_v);
+    const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+    normalized = POW_OP(acc, beta_v);
+    const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+    normalized_pixel = DIV_OP(LOAD_OP(0, (__global DATA_TYPE *)in.ptr), normalized);
+
+    STORE_OP(normalized_pixel, 0, (__global DATA_TYPE *)out.ptr);
+}
+#endif /* defined(NUM_SLICES) */