diff options
Diffstat (limited to 'src/core/CL/cl_kernels/pooling_layer_quantized.cl')
-rw-r--r-- | src/core/CL/cl_kernels/pooling_layer_quantized.cl | 134 |
1 files changed, 69 insertions, 65 deletions
diff --git a/src/core/CL/cl_kernels/pooling_layer_quantized.cl b/src/core/CL/cl_kernels/pooling_layer_quantized.cl index fe13464b1e..04fef98cd0 100644 --- a/src/core/CL/cl_kernels/pooling_layer_quantized.cl +++ b/src/core/CL/cl_kernels/pooling_layer_quantized.cl @@ -47,8 +47,6 @@ #define DIV_OP(x, y) (x * (1.f / y)) -#define DIV_OP_NHWC(x, y) (convert_float8(x) * (float8)(1.f / y)) - #if defined(POOL_L2) #error "L2 pooling is not supported" #endif /* defined(POOL_L2) */ @@ -155,34 +153,22 @@ __kernel void pooling_layer_MxN_quantized_nchw( *(__global DATA_TYPE *)output.ptr = result_q8; } -int calculate_avg_scale_nhwc(const int pool_size_x, const int pool_size_y, int upper_bound_w, int upper_bound_h, - const int pad_x, const int pad_y, const int stride_x, const int stride_y) -{ - int start_x = get_global_id(1) * stride_x - pad_x; -#if defined(DST_DEPTH) - int start_y = (get_global_id(2) % DST_DEPTH) * stride_y - pad_y; -#else /* defined(DST_DEPTH) */ - int start_y = get_global_id(2) * stride_y - pad_y; -#endif /* defined(DST_DEPTH) */ - - const int end_x = min(start_x + pool_size_x, upper_bound_w); - const int end_y = min(start_y + pool_size_y, upper_bound_h); - - start_x = max(0, start_x); - start_y = max(0, start_y); - - return ((end_y - start_y) * (end_x - start_x)); -} - -/** Performs a pooling function of pool size equal to N (NHWC) +#if defined(VEC_SIZE) && defined(VEC_SIZE_LEFTOVER) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(DST_CHANNELS) && defined(DST_HEIGHT) && defined(DST_BATCH_SIZE) && defined(ACC_DATA_TYPE) +/** Performs pooling layer of size equal to MxN. This OpenCL kernel can perform the following pooling types: + * -# max, -DPOOL_MAX must be passed at compile time + * -# average, -DPOOL_AVG must be passed at compile time. If padding has to be expluded, -DEXCLUDE_PADDING should be passed at compile time * - * @note Pool sizes must be passed using -DPOOL_SIZE_X and -DPOOL_SIZE_Y e.g. -DPOOL_SIZE_X=13; - * @note Tensors width and height must be passed at compile time using -DMAX_WIDTH and -DMAX_HEIGHT - * @note Strides must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y which are the steps of the window along the x and y directions - * @note Pad values must be passed at compile time using -DPAD_X and -DPAD_Y which are the pooling paddings in x and y dimension - * @note In case of average pooling the following information must be passed at compile time: - * -DPOOL_AVG must be provided otherwise max pooling will be performed. + * @note Datatype must be passed at compile type using -DDATA_TYPE e.g. -DDATA_TYPE=uchar. Supported data types are QASYMM8/QASYMM8_SIGNED + * @note Accumulation data type must be passed at compile time using -DACC_DATA_TYPE e.g. -DACC_DATA_TYPE=int + * @note Pool size must be passed at compile time using -DPOOL_SIZE_X and -DPOOL_SIZE_Y. e.g. -DPOOL_SIZE_X=4, -DPOOL_SIZE_Y=4 + * @note Input tensor width and height must be passed at compile time using -DSRC_WIDTH and -DSRC_HEIGHT + * @note Output tensor height, channels and batch size must be passed at compile time using -DDST_HEIGHT, -DDST_CHANNELS and -DDST_BATCH_SIZE + * @note Pool strides must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y which are the steps of the window along the x and y directions + * @note Pool pads must be passed at compile time using -DPAD_X and -DPAD_Y + * @note Vector size must be passed at compile time using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 + * @note Leftover vector size must be passed at compile time using -DVEC_SIZE_LEFTOVER. e.g. -DVEC_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VEC_SIZE * @note The initial value for the pooling operation must be passed at compile time using -DINITIAL_VALUE e.g. -DINITIAL_VALUE=0 + * @note If the output has be requantized, -DOFFSET_IN1, -DOFFSET_OUT, -DSCALE_IN1 and -DSCALE_OUT muste be passed at compile time * * @param[in] input_ptr Pointer to the source image. Supported data types: QASYMM8/QASYMM8_SIGNED * @param[in] input_stride_x Stride of the source image in X dimension (in bytes) @@ -209,57 +195,75 @@ __kernel void pooling_layer_MxN_quantized_nhwc( TENSOR4D_DECLARATION(input), TENSOR4D_DECLARATION(output)) { - // Get pixels pointer -#if defined(DST_DEPTH) - Tensor4D input = CONVERT_TO_TENSOR4D_STRUCT(input, DST_DEPTH); - Tensor4D output = CONVERT_TO_TENSOR4D_STRUCT(output, DST_DEPTH); -#else /* defined(DST_DEPTH) */ - Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); - Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); -#endif /* defined(DST_DEPTH) */ + // Note: If C is not multiple of VEC_SIZE, we shift back of VEC_SIZE_LEFTOVER elements to compute the leftover elements for get_global_id(0) == 0 + // Note: If C is less than VEC_SIZE, VEC_SIZE should be SHRINKED to the closest smaller VEC_SIZE. This operation is performed on the host side + int offset_c = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0) * sizeof(DATA_TYPE); + int idx_out_w = get_global_id(1); +#if DST_BATCH_SIZE != 1 + // If batch size != 1, the batch size dimension is collapsed over the height dimension + int idx_out_h = get_global_id(2) % DST_HEIGHT; + int idx_out_n = get_global_id(2) / DST_HEIGHT; +#else //DST_BATCH_SIZE != 1 + int idx_out_h = get_global_id(2); + int idx_out_n = 0; +#endif // DST_BATCH_SIZE != 1 - int8 vdata = INITIAL_VALUE; + int idx_in_w = idx_out_w * STRIDE_X - PAD_X; + int idx_in_h = idx_out_h * STRIDE_Y - PAD_Y; + + __global unsigned char *in_base_ptr = input_ptr + input_offset_first_element_in_bytes + + offset_c + + idx_out_n * input_stride_w; + + __global unsigned char *out_base_ptr = output_ptr + output_offset_first_element_in_bytes + + offset_c + + idx_out_w * output_stride_y + + idx_out_h * output_stride_z + + idx_out_n * output_stride_w; + + int pool_x_s = max((int)0, -idx_in_w); + int pool_x_e = min((int)POOL_SIZE_X, (int)SRC_WIDTH - idx_in_w); + int pool_y_s = max((int)0, -idx_in_h); + int pool_y_e = min((int)POOL_SIZE_Y, (int)SRC_HEIGHT - idx_in_h); + +#if defined(POOL_AVG) && defined(EXCLUDE_PADDING) + int filter_size = 0; +#elif defined(POOL_AVG) && !defined(EXCLUDE_PADDING) // defined(POOL_AVG) && defined(EXCLUDE_PADDING) + int filter_size = POOL_SIZE_X * POOL_SIZE_Y; +#endif // defined(POOL_AVG) && !defined(EXCLUDE_PADDING) - const int idx_width = get_global_id(1) * STRIDE_X; -#if defined(DST_DEPTH) - const int idx_height = (get_global_id(2) % DST_DEPTH) * STRIDE_Y; -#else /* defined(DST_DEPTH) */ - const int idx_height = get_global_id(2) * STRIDE_Y; -#endif /* defined(DST_DEPTH) */ + VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE) + res0 = INITIAL_VALUE; - for(int y = 0; y < POOL_SIZE_Y; ++y) + for(int y = pool_y_s; y < pool_y_e; ++y) { - int y1 = select(y, PAD_Y - idx_height, y + idx_height - PAD_Y < 0 || y + idx_height - PAD_Y >= MAX_HEIGHT); - for(int x = 0; x < POOL_SIZE_X; ++x) + for(int x = pool_x_s; x < pool_x_e; ++x) { - int x1 = select(x, PAD_X - idx_width - 1, x + idx_width - PAD_X < 0 || x + idx_width - PAD_X >= MAX_WIDTH); - x1 = select(x1, PAD_X - idx_width - 1, y != y1); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) data; + VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE) data0; -#if defined(DST_DEPTH) - VEC_TYPE(8) - data = vload8(0, (__global DATA_TYPE *)tensor4D_offset(&input, 0, x1 - PAD_X, y1 - PAD_Y, 0)); -#else /* defined(DST_DEPTH) */ - VEC_TYPE(8) - data = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, x1 - PAD_X, y1 - PAD_Y)); -#endif /* defined(DST_DEPTH) */ + data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(in_base_ptr + (x + idx_in_w) * input_stride_y + (y + idx_in_h) * input_stride_z)); + data0 = CONVERT(data, VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE)); - int8 data0 = convert_int8(data); - vdata = POOL_OP(vdata, data0); + res0 = POOL_OP(res0, data0); + +#if defined(POOL_AVG) && defined(EXCLUDE_PADDING) + filter_size++; +#endif // defined(POOL_AVG) && defined(EXCLUDE_PADDING) } } #if defined(POOL_AVG) - // Divide by pool region in case of average pooling - vdata = convert_int8(round(DIV_OP_NHWC(vdata, calculate_avg_scale_nhwc(POOL_SIZE_X, POOL_SIZE_Y, MAX_WIDTH, MAX_HEIGHT, PAD_X, PAD_Y, STRIDE_X, STRIDE_Y)))); -#endif /* defined(POOL_AVG) */ + res0 = (res0 + (VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE))(filter_size >> 1)) / filter_size; +#endif // defined(POOL_AVG) - VEC_TYPE(8) - out_q8 = CONVERT(vdata, VEC_TYPE(8)); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) out_q0 = CONVERT(res0, VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)); #if defined(OFFSET_IN1) && defined(OFFSET_OUT) && defined(SCALE_IN1) && defined(SCALE_OUT) - REQUANTIZE(8, out_q8, OFFSET_IN1, OFFSET_OUT, SCALE_IN1, SCALE_OUT, out_q8); + REQUANTIZE(VEC_SIZE, out_q0, OFFSET_IN1, OFFSET_OUT, SCALE_IN1, SCALE_OUT, out_q0); #endif /* defined(OFFSET_IN1) && defined(OFFSET_OUT) && defined(SCALE_IN1) && defined(SCALE_OUT) */ // Store result - vstore8(out_q8, 0, (__global DATA_TYPE *)output.ptr); + STORE_VECTOR_SELECT(out_q, DATA_TYPE, out_base_ptr, VEC_SIZE, VEC_SIZE_LEFTOVER, ((VEC_SIZE_LEFTOVER != 0) && get_global_id(0) == 0)); } -#endif /* defined(DATA_TYPE) && defined(INITIAL_VALUE) */ +#endif // defined(VEC_SIZE) && defined(VEC_SIZE_LEFTOVER) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(DST_CHANNELS) && defined(DST_HEIGHT) && defined(DST_BATCH_SIZE) && defined(SELECT_DATA_TYPE) && defined(ACC_DATA_TYPE) +#endif // defined(DATA_TYPE) && defined(INITIAL_VALUE)
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