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authorGeorgios Pinitas <georgios.pinitas@arm.com>2017-06-19 16:11:53 +0100
committerAnthony Barbier <anthony.barbier@arm.com>2018-09-17 14:14:20 +0100
commitce093143ec7b554edefc533c90e45c80946cde51 (patch)
tree1e4aa13ba3fe10c93ca42e2f5477bd2c4888324e /src/core/CL/cl_kernels/pooling_layer.cl
parent4c2938ed50a78753bfbdbb2f3cbf43f5fed779f9 (diff)
downloadComputeLibrary-ce093143ec7b554edefc533c90e45c80946cde51.tar.gz
COMPMID-403:Add support for 7x7 pooling on CL.
Change-Id: I3c2c8d7e8e61d7737170cb1568900ce4ac337068 Reviewed-on: http://mpd-gerrit.cambridge.arm.com/78181 Reviewed-by: Michele DiGiorgio <michele.digiorgio@arm.com> Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com> Reviewed-by: Moritz Pflanzer <moritz.pflanzer@arm.com>
Diffstat (limited to 'src/core/CL/cl_kernels/pooling_layer.cl')
-rw-r--r--src/core/CL/cl_kernels/pooling_layer.cl91
1 files changed, 87 insertions, 4 deletions
diff --git a/src/core/CL/cl_kernels/pooling_layer.cl b/src/core/CL/cl_kernels/pooling_layer.cl
index 1902df9b7d..6bdb174235 100644
--- a/src/core/CL/cl_kernels/pooling_layer.cl
+++ b/src/core/CL/cl_kernels/pooling_layer.cl
@@ -41,7 +41,6 @@ float calculate_avg_scale(const int pool_size, const int upper_bound_w, const in
/** Performs a pooling function of pool size equal to 2.
*
- * @note Pooling stride must be passed using -DPOOL_STRIDE e.g -DPOOL_STRIDE=2. Supported strides are 1,2,3
* @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are F16, F32;
* @note In case of average pooling -DPOOL_AVG must be provided otherwise max pooling will be performed.
*
@@ -88,7 +87,7 @@ __kernel void pooling_layer_2(
data0 = POOL_OP(data0, data1);
DATA_TYPE res = POOL_OP(data0.s0, data0.s1);
- // Divide by 4 in case of average pooling
+ // Divide by pool region in case of average pooling
#ifdef POOL_AVG
res *= calculate_avg_scale(2, max_dims.x, max_dims.y, paddings.x, paddings.y, strides.x, strides.y);
#endif
@@ -99,7 +98,6 @@ __kernel void pooling_layer_2(
/** Performs a pooling function of pool size equal to 3.
*
- * @note Pooling stride must be passed using -DPOOL_STRIDE e.g -DPOOL_STRIDE=2. Supported strides are 1,2,3
* @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are F16, F32;
* @note In case of average pooling -DPOOL_AVG must be provided otherwise max pooling will be performed.
*
@@ -149,7 +147,7 @@ __kernel void pooling_layer_3(
data0 = POOL_OP(data0, data2);
DATA_TYPE res = POOL_OP(POOL_OP(data0.s0, data0.s1), data0.s2);
- // Divide by 4 in case of average pooling
+ // Divide by pool region in case of average pooling
#ifdef POOL_AVG
res *= calculate_avg_scale(3, max_dims.x, max_dims.y, paddings.x, paddings.y, strides.x, strides.y);
#endif
@@ -157,3 +155,88 @@ __kernel void pooling_layer_3(
// Store result
*(__global DATA_TYPE *)output.ptr = res;
}
+
+/** Performs a pooling function of pool size equal to 7.
+ *
+ * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are F16, F32;
+ * @note In case of average pooling -DPOOL_AVG must be provided otherwise max pooling will be performed.
+ *
+ * @param[in] input_ptr Pointer to the source image. Supported data types: F16, F32
+ * @param[in] input_stride_x Stride of the source image 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 source image 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 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 source image
+ * @param[out] output_ptr Pointer to the destination image. Supported data types: F16, F32
+ * @param[in] output_stride_x Stride of the destination image 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 destination image 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 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 image
+ * @param[in] max_dims The maximum index that can be accessed in x and y dimension (width + pad)
+ * @param[in] strides The pooling operation strides in each dimension
+ * @param[in] paddings The pooling operation paddings in each dimension
+ */
+__kernel void pooling_layer_7(
+ TENSOR3D_DECLARATION(input),
+ TENSOR3D_DECLARATION(output)
+#ifdef POOL_AVG
+ ,
+ int2 max_dims, int2 strides, int2 paddings
+#endif
+)
+{
+ // Get pixels pointer
+ Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input);
+ Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output);
+
+ // Load data
+ VEC_DATA_TYPE(DATA_TYPE, 8)
+ data0 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0));
+ VEC_DATA_TYPE(DATA_TYPE, 8)
+ data1 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0));
+ VEC_DATA_TYPE(DATA_TYPE, 8)
+ data2 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 2, 0));
+ VEC_DATA_TYPE(DATA_TYPE, 8)
+ data3 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 3, 0));
+ VEC_DATA_TYPE(DATA_TYPE, 8)
+ data4 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 4, 0));
+ VEC_DATA_TYPE(DATA_TYPE, 8)
+ data5 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 5, 0));
+ VEC_DATA_TYPE(DATA_TYPE, 8)
+ data6 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 6, 0));
+
+ // Pool operation of all rows
+ data0 = POOL_OP(data0, data1);
+ data2 = POOL_OP(data2, data3);
+ data4 = POOL_OP(data4, data5);
+ data0 = POOL_OP(data0, data2);
+ data4 = POOL_OP(data4, data6);
+ data0 = POOL_OP(data0, data4);
+
+ // Set last element
+#ifdef POOL_AVG
+ data0.s7 = 0;
+#else
+ data0.s7 = data0.s6;
+#endif
+
+ // Reduce result
+ VEC_DATA_TYPE(DATA_TYPE, 4)
+ reduce4 = POOL_OP(data0.s0123, data0.s4567);
+ VEC_DATA_TYPE(DATA_TYPE, 2)
+ reduce2 = POOL_OP(reduce4.s01, reduce4.s23);
+ DATA_TYPE res = POOL_OP(reduce2.s0, reduce2.s1);
+
+ // Divide by pool region in case of average pooling
+#ifdef POOL_AVG
+ res *= calculate_avg_scale(7, max_dims.x, max_dims.y, paddings.x, paddings.y, strides.x, strides.y);
+#endif
+
+ // Store result
+ *(__global DATA_TYPE *)output.ptr = res;
+}