diff options
| -rw-r--r-- | arm_compute/core/CL/kernels/CLROIAlignLayerKernel.h | 16 | ||||
| -rw-r--r-- | arm_compute/runtime/CL/functions/CLROIAlignLayer.h | 16 | ||||
| -rw-r--r-- | src/core/CL/CLKernelLibrary.cpp | 7 | ||||
| -rw-r--r-- | src/core/CL/cl_kernels/roi_align_layer_quantized.cl | 225 | ||||
| -rw-r--r-- | src/core/CL/kernels/CLROIAlignLayerKernel.cpp | 39 | ||||
| -rw-r--r-- | tests/validation/CL/ROIAlignLayer.cpp | 70 | ||||
| -rw-r--r-- | tests/validation/Helpers.cpp | 12 | ||||
| -rw-r--r-- | tests/validation/Helpers.h | 10 | ||||
| -rw-r--r-- | tests/validation/fixtures/ROIAlignLayerFixture.h | 93 | ||||
| -rw-r--r-- | tests/validation/reference/ROIAlignLayer.cpp | 39 | ||||
| -rw-r--r-- | tests/validation/reference/ROIAlignLayer.h | 6 |
11 files changed, 460 insertions, 73 deletions
diff --git a/arm_compute/core/CL/kernels/CLROIAlignLayerKernel.h b/arm_compute/core/CL/kernels/CLROIAlignLayerKernel.h index b5e02324bc..e8dd0c50c8 100644 --- a/arm_compute/core/CL/kernels/CLROIAlignLayerKernel.h +++ b/arm_compute/core/CL/kernels/CLROIAlignLayerKernel.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -51,9 +51,10 @@ public: /** Set the input and output tensors. * - * @param[in] input Source tensor. Data types supported: F16/F32. + * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32. * @param[in] rois ROIs tensor, it is a 2D tensor of size [5, N] (where N is the number of ROIs) containing top left and bottom right corner - * as coordinate of an image and batch_id of ROI [ batch_id, x1, y1, x2, y2 ]. Data types supported: same as @p input + * as coordinate of an image and batch_id of ROI [ batch_id, x1, y1, x2, y2 ]. + * Data types supported: QASYMM16 with scale of 0.125 and 0 offset if @p input is QASYMM8, otherwise same as @p input * @param[out] output Destination tensor. Data types supported: Same as @p input. * @param[in] pool_info Contains pooling operation information described in @ref ROIPoolingLayerInfo. * @@ -65,10 +66,11 @@ public: void configure(const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info); /** Static function to check if given info will lead to a valid configuration of @ref CLROIAlignLayerKernel * - * @param[in] input Source tensor info. Data types supported: F16/F32. - * @param[in] rois ROIs tensor info. Data types supported: same as @p input - * @param[out] output Destination tensor info. Data types supported: Same as @p input. - * @param[in] pool_info Contains pooling operation information described in @ref ROIPoolingLayerInfo. + * @param[in] input Source tensor info. Data types supported: QASYMM8/F16/F32. + * @param[in] rois ROIs tensor info. Data types supported: QASYMM16 with scale of 0.125 and 0 offset if @p input is QASYMM8, + * otherwise same as @p input + * @param[in] output Destination tensor info. Data types supported: Same as @p input. + * @param[in] pool_info Contains pooling operation information described in @ref ROIPoolingLayerInfo. * * @note The x and y dimensions of @p output tensor must be the same as @p pool_info 's pooled * width and pooled height. diff --git a/arm_compute/runtime/CL/functions/CLROIAlignLayer.h b/arm_compute/runtime/CL/functions/CLROIAlignLayer.h index fec0dac51a..e12978ac2b 100644 --- a/arm_compute/runtime/CL/functions/CLROIAlignLayer.h +++ b/arm_compute/runtime/CL/functions/CLROIAlignLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -43,9 +43,10 @@ class CLROIAlignLayer : public ICLSimpleFunction public: /** Set the input and output tensors. * - * @param[in] input Source tensor. Data types supported: F16/F32. + * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32. * @param[in] rois ROIs tensor, it is a 2D tensor of size [5, N] (where N is the number of ROIs) containing top left and bottom right corner - * as coordinate of an image and batch_id of ROI [ batch_id, x1, y1, x2, y2 ]. Data types supported: same as @p input + * as coordinate of an image and batch_id of ROI [ batch_id, x1, y1, x2, y2 ]. + * Data types supported: QASYMM16 with scale of 0.125 and 0 offset if @p input is QASYMM8, otherwise same as @p input * @param[out] output Destination tensor. Data types supported: Same as @p input. * @param[in] pool_info Contains pooling operation information described in @ref ROIPoolingLayerInfo. * @@ -57,10 +58,11 @@ public: void configure(const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info); /** Static function to check if given info will lead to a valid configuration of @ref CLROIAlignLayer * - * @param[in] input Source tensor info. Data types supported: F16/F32. - * @param[in] rois ROIs tensor info. Data types supported: same as @p input - * @param[out] output Destination tensor info. Data types supported: Same as @p input. - * @param[in] pool_info Contains pooling operation information described in @ref ROIPoolingLayerInfo. + * @param[in] input Source tensor info. Data types supported: QASYMM8/F16/F32. + * @param[in] rois ROIs tensor info. Data types supported: QASYMM16 with scale of 0.125 and 0 offset if @p input is QASYMM8, + * otherwise same as @p input + * @param[in] output Destination tensor info. Data types supported: Same as @p input. + * @param[in] pool_info Contains pooling operation information described in @ref ROIPoolingLayerInfo. * * @note The x and y dimensions of @p output tensor must be the same as @p pool_info 's pooled * width and pooled height. diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp index b938a1813a..4b3b37c3da 100644 --- a/src/core/CL/CLKernelLibrary.cpp +++ b/src/core/CL/CLKernelLibrary.cpp @@ -447,6 +447,7 @@ const std::map<std::string, std::string> CLKernelLibrary::_kernel_program_map = { "RGBA8888_to_RGB888_bt709", "color_convert.cl" }, { "RGBA8888_to_YUV444_bt709", "color_convert.cl" }, { "roi_align_layer", "roi_align_layer.cl" }, + { "roi_align_layer_quantized", "roi_align_layer_quantized.cl" }, { "roi_pooling_layer", "roi_pooling_layer.cl" }, { "scale_nearest_neighbour_nchw", "scale.cl" }, { "scale_nearest_neighbour_nhwc", "scale.cl" }, @@ -935,6 +936,10 @@ const std::map<std::string, std::string> CLKernelLibrary::_program_source_map = #include "./cl_kernels/roi_align_layer.clembed" }, { + "roi_align_layer_quantized.cl", +#include "./cl_kernels/roi_align_layer_quantized.clembed" + }, + { "roi_pooling_layer.cl", #include "./cl_kernels/roi_pooling_layer.clembed" }, @@ -1251,4 +1256,4 @@ std::string CLKernelLibrary::get_device_version() cl_uint CLKernelLibrary::get_num_compute_units() { return _device.getInfo<CL_DEVICE_MAX_COMPUTE_UNITS>(); -}
\ No newline at end of file +} diff --git a/src/core/CL/cl_kernels/roi_align_layer_quantized.cl b/src/core/CL/cl_kernels/roi_align_layer_quantized.cl new file mode 100644 index 0000000000..f9360e98f1 --- /dev/null +++ b/src/core/CL/cl_kernels/roi_align_layer_quantized.cl @@ -0,0 +1,225 @@ +/* + * Copyright (c) 2019 ARM Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "helpers.h" + +// This specifies the value to shift the result of roi_dims / pooled_dims before ceiling. +// It is close to the epsilon machine (for a floating point system, x and x+EPS are the same number). +#define EPS_GRID 0.00001f + +#if defined(DATA_TYPE) && defined(POOLED_DIM_X) && defined(POOLED_DIM_Y) && defined(MAX_DIM_X) && defined(MAX_DIM_Y) && defined(MAX_DIM_Z) && defined(SPATIAL_SCALE) && defined(OFFSET_IN) && defined(OFFSET_OUT) && defined(SCALE_IN) && defined(SCALE_OUT) && defined(OFFSET_ROIS) && defined(SCALE_ROIS) // Check for compile time constants + +#define CONVERT_RTE(x, type) (convert_##type##_rte((x))) +#define CONVERT_DOWN(x, type) CONVERT_RTE(x, type) +inline float dequantize_qasymm8(uchar input, float offset, float scale) +{ + return ((float)input - offset) * scale; +} + +inline uchar quantize_qasymm8(float input, float offset, float scale) +{ + float out_f32 = input / scale + offset; + uchar res_u8 = CONVERT_SAT(CONVERT_DOWN(out_f32, int), uchar); + return res_u8; +} + +inline float4 dequantize_qasymm16(ushort4 input, float offset, float scale) +{ + float4 in_f32 = (CONVERT(input, float4) - (float4)(offset)) * (float4)(scale); + return in_f32; +} + +/** Performs a roi align on a single output pixel. + * + * @param[in] input Pointer to input Tensor3D struct. + * @param[in] region_start_x Start x index projected onto the input tensor. + * @param[in] region_end_x End x index projected onto the input tensor. + * @param[in] region_start_y Start y index projected onto the input tensor. + * @param[in] region_end_y End y index projected onto the input tensor. + * @param[in] pz z index of the input tensor. + * + * @return An average pooled value from the region specified in the input tensor. + */ +inline DATA_TYPE roi_align_1x1(const Tensor3D *input, float region_start_x, + float bin_size_x, + float grid_size_x, + float region_end_x, + float region_start_y, + float bin_size_y, + float grid_size_y, + float region_end_y, + int pz) +{ + // Iterate through the pooling region + float sum = 0; + for(int iy = 0; iy < grid_size_y; ++iy) + { + for(int ix = 0; ix < grid_size_x; ++ix) + { + // Align the window in the middle of every bin + const float y = region_start_y + (iy + 0.5f) * bin_size_y / (float)grid_size_y; + const float x = region_start_x + (ix + 0.5f) * bin_size_x / (float)grid_size_x; + + // Interpolation in the unit square + const int y_low = (int)y; + const int x_low = (int)x; + const int y_high = y_low + 1; + const int x_high = x_low + 1; + + const float ly = y - y_low; + const float lx = x - x_low; + const float hy = 1.f - ly; + const float hx = 1.f - lx; + + const float w1 = hy * hx; + const float w2 = hy * lx; + const float w3 = ly * hx; + const float w4 = ly * lx; +#if defined(NHWC) + const DATA_TYPE data1 = *(__global DATA_TYPE *)tensor3D_offset(input, pz, x_low, y_low); + const DATA_TYPE data2 = *(__global DATA_TYPE *)tensor3D_offset(input, pz, x_high, y_low); + const DATA_TYPE data3 = *(__global DATA_TYPE *)tensor3D_offset(input, pz, x_low, y_high); + const DATA_TYPE data4 = *(__global DATA_TYPE *)tensor3D_offset(input, pz, x_high, y_high); +#else // !defined(NHWC) + const DATA_TYPE data1 = *(__global DATA_TYPE *)tensor3D_offset(input, x_low, y_low, pz); + const DATA_TYPE data2 = *(__global DATA_TYPE *)tensor3D_offset(input, x_high, y_low, pz); + const DATA_TYPE data3 = *(__global DATA_TYPE *)tensor3D_offset(input, x_low, y_high, pz); + const DATA_TYPE data4 = *(__global DATA_TYPE *)tensor3D_offset(input, x_high, y_high, pz); +#endif // defined(NHWC) + const float data1_f32 = dequantize_qasymm8(data1, OFFSET_IN, SCALE_IN); + const float data2_f32 = dequantize_qasymm8(data2, OFFSET_IN, SCALE_IN); + const float data3_f32 = dequantize_qasymm8(data3, OFFSET_IN, SCALE_IN); + const float data4_f32 = dequantize_qasymm8(data4, OFFSET_IN, SCALE_IN); + sum += w1 * data1_f32 + w2 * data2_f32 + w3 * data3_f32 + w4 * data4_f32; + } + } + + const float res_f32 = sum / (grid_size_x * grid_size_y); + return quantize_qasymm8(res_f32, OFFSET_OUT, SCALE_OUT); +} + +/** Performs a roi align function. + * + * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=uchar + * @note Datasize must be passed using -DDATA_SIZE e.g. -DDATA_SIZE=32; + * @note Input dimensions must be passed using -DMAX_DIM_X, -DMAX_DIM_Y and -DMAX_DIM_Z; + * @note Pooled region dimensions must be passed using -DPOOLED_DIM_X and -DPOOLED_DIM_Y; + * @note Spatial scale must be passed using -DSPATIAL_SCALE; + * @note Sampling ratio (i.e., the number of samples in each bin) may be passed using -DSAMPLING_RATIO. If not defined each roi + * will have a default sampling ratio of roi_dims/pooling_dims + * + * @param[in] input_ptr Pointer to the source tensor. Supported data types: QASYMM8 + * @param[in] input_stride_x Stride of the 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 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 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 pooled region of the source tensor as specifed by ROI + * @param[in] rois_ptr Pointer to the ROIs tensor. Layout: { batch_index, x1, y1, x2, y2 }. + * Supported data types: QASYMM16 with 0.125f scale and 0 offset + * @param[in] rois_stride_x Stride of the ROIs tensor in X dimension (in bytes) + * @param[in] rois_step_x Step of the ROIs tensor in X dimension (in bytes) + * @param[in] rois_stride_y Stride of the ROIs tensor in Y dimension (in bytes) + * @param[in] rois_step_y Step of the ROIs tensor in Y dimension (in bytes) + * @param[in] rois_offset_first_element_in_bytes The offset of the first element in the ROIs tensor + * @param[out] output_ptr Pointer to the destination tensor. Supported data types: 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 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 destination 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 + * @param[in] input_stride_w Stride of the source tensor in W dimension (in bytes) + * @param[in] output_stride_w Stride of the destination tensor in W dimension (in bytes) + */ +__kernel void roi_align_layer_quantized( + TENSOR3D_DECLARATION(input), + IMAGE_DECLARATION(rois), + TENSOR3D_DECLARATION(output), + unsigned int input_stride_w, unsigned int output_stride_w) +{ + // Get pixels pointer + Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(input); + Image rois = CONVERT_TO_IMAGE_STRUCT_NO_STEP(rois); + Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(output); + +#if defined(NHWC) + const int px = get_global_id(1); + const int py = get_global_id(2); + const int pw = get_global_id(0); +#else // !defined(NHWC) + const int px = get_global_id(0); + const int py = get_global_id(1); + const int pw = get_global_id(2); +#endif // defined(NHWC) + + // Load roi parameters + // roi is laid out as follows { batch_index, x1, y1, x2, y2 } + const ushort roi_batch = *((__global ushort *)offset(&rois, 0, pw)); + float4 roi = dequantize_qasymm16(vload4(0, (__global ushort *)offset(&rois, 1, pw)), OFFSET_ROIS, SCALE_ROIS); + float2 roi_anchor = roi.s01 * convert_float(SPATIAL_SCALE); + float2 roi_dims = fmax((roi.s23 - roi.s01) * convert_float(SPATIAL_SCALE), 1.f); + + // Calculate pooled region start and end + float2 spatial_indx = (float2)(px, py); + float2 pooled_dims = (float2)(POOLED_DIM_X, POOLED_DIM_Y); + float2 max_spatial_dims = (float2)(MAX_DIM_X, MAX_DIM_Y); + + float2 bin_size = (float2)((roi_dims.s0 / (float)POOLED_DIM_X), (roi_dims.s1 / (float)POOLED_DIM_Y)); + float2 region_start = spatial_indx * bin_size + roi_anchor; + float2 region_end = (spatial_indx + 1) * bin_size + roi_anchor; + + region_start = clamp(region_start, 0, max_spatial_dims); + region_end = clamp(region_end, 0, max_spatial_dims); + +#if defined(SAMPLING_RATIO) + float2 roi_bin_grid = SAMPLING_RATIO; +#else // !defined(SAMPLING_RATIO) + // Note that we subtract EPS_GRID before ceiling. This is to avoid situations where 1.000001 gets ceiled to 2. + float2 roi_bin_grid = ceil(bin_size - EPS_GRID); +#endif // defined(SAMPLING_RATIO) + + // Move input and output pointer across the fourth dimension + input.ptr += roi_batch * input_stride_w; + output.ptr += pw * output_stride_w; + for(int pz = 0; pz < MAX_DIM_Z; ++pz) + { +#if defined(NHWC) + __global DATA_TYPE *_output_ptr = (__global DATA_TYPE *)tensor3D_offset(&output, pz, px, py); +#else // !defined(NHWC) + __global DATA_TYPE *_output_ptr = (__global DATA_TYPE *)tensor3D_offset(&output, px, py, pz); +#endif // defined(NHWC) + *_output_ptr = (__global DATA_TYPE)roi_align_1x1(&input, + region_start.x, + bin_size.x, + roi_bin_grid.x, + region_end.x, + region_start.y, + bin_size.y, + roi_bin_grid.y, + region_end.y, pz); + } +} +#endif // Check for compile time constants diff --git a/src/core/CL/kernels/CLROIAlignLayerKernel.cpp b/src/core/CL/kernels/CLROIAlignLayerKernel.cpp index 50729f2421..134286bae1 100644 --- a/src/core/CL/kernels/CLROIAlignLayerKernel.cpp +++ b/src/core/CL/kernels/CLROIAlignLayerKernel.cpp @@ -45,11 +45,10 @@ namespace Status validate_arguments(const ITensorInfo *input, const ITensorInfo *rois, ITensorInfo *output, const ROIPoolingLayerInfo &pool_info) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, rois, output); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, rois); ARM_COMPUTE_RETURN_ERROR_ON(rois->dimension(0) != 5); ARM_COMPUTE_RETURN_ERROR_ON(rois->num_dimensions() > 2); ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F32, DataType::F16); ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(input, DataLayout::NHWC, DataLayout::NCHW); ARM_COMPUTE_RETURN_ERROR_ON((pool_info.pooled_width() == 0) || (pool_info.pooled_height() == 0)); @@ -59,6 +58,19 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *rois, ITe ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(compute_roi_align_shape(*input, *rois, pool_info), output->tensor_shape()); } + + if(input->data_type() == DataType::QASYMM8) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(rois, 1, DataType::QASYMM16); + + const UniformQuantizationInfo rois_qinfo = rois->quantization_info().uniform(); + ARM_COMPUTE_RETURN_ERROR_ON(rois_qinfo.scale != 0.125f); + ARM_COMPUTE_RETURN_ERROR_ON(rois_qinfo.offset != 0); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, rois); + } return Status{}; } @@ -104,9 +116,12 @@ void CLROIAlignLayerKernel::configure(const ICLTensor *input, const ICLTensor *r _rois = rois; _pool_info = pool_info; + const DataType data_type = input->info()->data_type(); + const bool is_qasymm = is_data_type_quantized_asymmetric(data_type); + // Set build options CLBuildOptions build_opts; - build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); + build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type)); build_opts.add_option("-DDATA_SIZE=" + get_data_size_from_data_type(input->info()->data_type())); build_opts.add_option("-DMAX_DIM_X=" + support::cpp11::to_string(_input->info()->dimension(get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::WIDTH)))); build_opts.add_option("-DMAX_DIM_Y=" + support::cpp11::to_string(_input->info()->dimension(get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT)))); @@ -117,9 +132,23 @@ void CLROIAlignLayerKernel::configure(const ICLTensor *input, const ICLTensor *r build_opts.add_option_if(input->info()->data_layout() == DataLayout::NHWC, "-DNHWC"); build_opts.add_option_if(pool_info.sampling_ratio() > 0, "-DSAMPLING_RATIO=" + support::cpp11::to_string(pool_info.sampling_ratio())); + if(is_qasymm) + { + const UniformQuantizationInfo iq_info = input->info()->quantization_info().uniform(); + const UniformQuantizationInfo roisq_info = rois->info()->quantization_info().uniform(); + const UniformQuantizationInfo oq_info = output->info()->quantization_info().uniform(); + + build_opts.add_option("-DOFFSET_IN=" + float_to_string_with_full_precision(iq_info.offset)); + build_opts.add_option("-DSCALE_IN=" + float_to_string_with_full_precision(iq_info.scale)); + build_opts.add_option("-DOFFSET_ROIS=" + float_to_string_with_full_precision(roisq_info.offset)); + build_opts.add_option("-DSCALE_ROIS=" + float_to_string_with_full_precision(roisq_info.scale)); + build_opts.add_option("-DOFFSET_OUT=" + float_to_string_with_full_precision(oq_info.offset)); + build_opts.add_option("-DSCALE_OUT=" + float_to_string_with_full_precision(oq_info.scale)); + } + // Create kernel - std::string kernel_name = "roi_align_layer"; - _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options())); + const std::string kernel_name = (is_qasymm) ? "roi_align_layer_quantized" : "roi_align_layer"; + _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options())); ICLKernel::configure_internal(win_config.second); } diff --git a/tests/validation/CL/ROIAlignLayer.cpp b/tests/validation/CL/ROIAlignLayer.cpp index 566e1985b3..b213c6815f 100644 --- a/tests/validation/CL/ROIAlignLayer.cpp +++ b/tests/validation/CL/ROIAlignLayer.cpp @@ -41,11 +41,13 @@ namespace validation { namespace { -RelativeTolerance<float> relative_tolerance_f32(0.01f); -AbsoluteTolerance<float> absolute_tolerance_f32(0.001f); +constexpr RelativeTolerance<float> relative_tolerance_f32(0.01f); +constexpr AbsoluteTolerance<float> absolute_tolerance_f32(0.001f); -RelativeTolerance<float> relative_tolerance_f16(0.01f); -AbsoluteTolerance<float> absolute_tolerance_f16(0.001f); +constexpr RelativeTolerance<float> relative_tolerance_f16(0.01f); +constexpr AbsoluteTolerance<float> absolute_tolerance_f16(0.001f); + +constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); } // namespace TEST_SUITE(CL) @@ -55,13 +57,14 @@ TEST_SUITE(RoiAlign) // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( framework::dataset::make("InputInfo", { TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), - TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Mismatching data type input/rois - TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Mismatching data type input/output - TensorInfo(TensorShape(250U, 128U, 2U), 1, DataType::F32), // Mismatching depth size input/output - TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Mismatching number of rois and output batch size - TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Invalid number of values per ROIS - TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Mismatching height and width input/output - + TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Mismatching data type input/rois + TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Mismatching data type input/output + TensorInfo(TensorShape(250U, 128U, 2U), 1, DataType::F32), // Mismatching depth size input/output + TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Mismatching number of rois and output batch size + TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Invalid number of values per ROIS + TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Mismatching height and width input/output + TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::QASYMM8, QuantizationInfo(1.f / 255.f, 127)), // Invalid ROIS data type + TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::QASYMM8, QuantizationInfo(1.f / 255.f, 127)), // Invalid ROIS Quantization Info }), framework::dataset::make("RoisInfo", { TensorInfo(TensorShape(5, 4U), 1, DataType::F32), TensorInfo(TensorShape(5, 4U), 1, DataType::F16), @@ -70,6 +73,8 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( TensorInfo(TensorShape(5, 10U), 1, DataType::F32), TensorInfo(TensorShape(4, 4U), 1, DataType::F32), TensorInfo(TensorShape(5, 4U), 1, DataType::F32), + TensorInfo(TensorShape(5, 4U), 1, DataType::F32), + TensorInfo(TensorShape(5, 4U), 1, DataType::QASYMM16, QuantizationInfo(0.2f, 0)), })), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::F32), TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::F32), @@ -78,6 +83,8 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::F32), TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::F32), TensorInfo(TensorShape(5U, 5U, 3U, 4U), 1, DataType::F32), + TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::QASYMM8, QuantizationInfo(1.f / 255.f, 120)), + TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::QASYMM8, QuantizationInfo(1.f / 255.f, 120)), })), framework::dataset::make("PoolInfo", { ROIPoolingLayerInfo(7U, 7U, 1./8), ROIPoolingLayerInfo(7U, 7U, 1./8), @@ -86,8 +93,9 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( ROIPoolingLayerInfo(7U, 7U, 1./8), ROIPoolingLayerInfo(7U, 7U, 1./8), ROIPoolingLayerInfo(7U, 7U, 1./8), + ROIPoolingLayerInfo(7U, 7U, 1./8), })), - framework::dataset::make("Expected", { true, false, false, false, false, false, false })), + framework::dataset::make("Expected", { true, false, false, false, false, false, false, false, false })), input_info, rois_info, output_info, pool_info, expected) { ARM_COMPUTE_EXPECT(bool(CLROIAlignLayer::validate(&input_info.clone()->set_is_resizable(true), &rois_info.clone()->set_is_resizable(true), &output_info.clone()->set_is_resizable(true), pool_info)) == expected, framework::LogLevel::ERRORS); @@ -99,24 +107,46 @@ template <typename T> using CLROIAlignLayerFixture = ROIAlignLayerFixture<CLTensor, CLAccessor, CLROIAlignLayer, T>; TEST_SUITE(Float) -FIXTURE_DATA_TEST_CASE(SmallROIAlignLayerFloat, CLROIAlignLayerFixture<float>, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::SmallROIDataset(), - framework::dataset::make("DataType", { DataType::F32 })), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) +TEST_SUITE(FP32) +FIXTURE_DATA_TEST_CASE(Small, CLROIAlignLayerFixture<float>, framework::DatasetMode::ALL, + combine(combine(datasets::SmallROIDataset(), + framework::dataset::make("DataType", { DataType::F32 })), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) { // Validate output validate(CLAccessor(_target), _reference, relative_tolerance_f32, .02f, absolute_tolerance_f32); } -FIXTURE_DATA_TEST_CASE(SmallROIAlignLayerHalf, CLROIAlignLayerFixture<half>, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::SmallROIDataset(), - framework::dataset::make("DataType", { DataType::F16 })), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) +TEST_SUITE_END() // FP32 +TEST_SUITE(FP16) +FIXTURE_DATA_TEST_CASE(Small, CLROIAlignLayerFixture<half>, framework::DatasetMode::ALL, + combine(combine(datasets::SmallROIDataset(), + framework::dataset::make("DataType", { DataType::F16 })), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) { // Validate output validate(CLAccessor(_target), _reference, relative_tolerance_f16, .02f, absolute_tolerance_f16); } +TEST_SUITE_END() // FP16 TEST_SUITE_END() // Float +template <typename T> +using CLROIAlignLayerQuantizedFixture = ROIAlignLayerQuantizedFixture<CLTensor, CLAccessor, CLROIAlignLayer, T>; + +TEST_SUITE(Quantized) +TEST_SUITE(QASYMM8) +FIXTURE_DATA_TEST_CASE(Small, CLROIAlignLayerQuantizedFixture<uint8_t>, framework::DatasetMode::ALL, + combine(combine(combine(combine(datasets::SmallROIDataset(), + framework::dataset::make("DataType", { DataType::QASYMM8 })), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), + framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, 127) })), + framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(2.f / 255.f, 120) }))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_qasymm8); +} +TEST_SUITE_END() // QASYMM8 +TEST_SUITE_END() // Quantized + TEST_SUITE_END() // RoiAlign TEST_SUITE_END() // CL } // namespace validation diff --git a/tests/validation/Helpers.cpp b/tests/validation/Helpers.cpp index 360859e487..a811cabf56 100644 --- a/tests/validation/Helpers.cpp +++ b/tests/validation/Helpers.cpp @@ -120,6 +120,18 @@ SimpleTensor<float> convert_from_asymmetric(const SimpleTensor<uint8_t> &src) return dst; } +SimpleTensor<float> convert_from_asymmetric(const SimpleTensor<uint16_t> &src) +{ + const UniformQuantizationInfo &quantization_info = src.quantization_info().uniform(); + SimpleTensor<float> dst{ src.shape(), DataType::F32, 1, QuantizationInfo(), src.data_layout() }; + + for(int i = 0; i < src.num_elements(); ++i) + { + dst[i] = dequantize_qasymm16(src[i], quantization_info); + } + return dst; +} + SimpleTensor<uint8_t> convert_to_asymmetric(const SimpleTensor<float> &src, const QuantizationInfo &quantization_info) { SimpleTensor<uint8_t> dst{ src.shape(), DataType::QASYMM8, 1, quantization_info }; diff --git a/tests/validation/Helpers.h b/tests/validation/Helpers.h index 44dd7a9b81..0d6515b5c5 100644 --- a/tests/validation/Helpers.h +++ b/tests/validation/Helpers.h @@ -177,7 +177,7 @@ void fill_lookuptable(T &&table) } } -/** Convert quantized simple tensor into float using tensor quantization information. +/** Convert 8-bit asymmetric quantized simple tensor into float using tensor quantization information. * * @param[in] src Quantized tensor. * @@ -185,6 +185,14 @@ void fill_lookuptable(T &&table) */ SimpleTensor<float> convert_from_asymmetric(const SimpleTensor<uint8_t> &src); +/** Convert 16-bit asymmetric quantized simple tensor into float using tensor quantization information. + * + * @param[in] src Quantized tensor. + * + * @return Float tensor. + */ +SimpleTensor<float> convert_from_asymmetric(const SimpleTensor<uint16_t> &src); + /** Convert float simple tensor into quantized using specified quantization information. * * @param[in] src Float tensor. diff --git a/tests/validation/fixtures/ROIAlignLayerFixture.h b/tests/validation/fixtures/ROIAlignLayerFixture.h index dfbb478a41..b9b85d3073 100644 --- a/tests/validation/fixtures/ROIAlignLayerFixture.h +++ b/tests/validation/fixtures/ROIAlignLayerFixture.h @@ -26,7 +26,7 @@ #include "arm_compute/core/TensorShape.h" #include "arm_compute/core/Types.h" -#include "arm_compute/runtime/CL/functions/CLROIAlignLayer.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "tests/AssetsLibrary.h" #include "tests/Globals.h" #include "tests/IAccessor.h" @@ -42,14 +42,17 @@ namespace test namespace validation { template <typename TensorType, typename AccessorType, typename FunctionType, typename T> -class ROIAlignLayerFixture : public framework::Fixture +class ROIAlignLayerGenericFixture : public framework::Fixture { public: + using TRois = typename std::conditional<std::is_same<typename std::decay<T>::type, uint8_t>::value, uint16_t, T>::type; + template <typename...> - void setup(TensorShape input_shape, const ROIPoolingLayerInfo pool_info, TensorShape rois_shape, DataType data_type, DataLayout data_layout) + void setup(TensorShape input_shape, const ROIPoolingLayerInfo pool_info, TensorShape rois_shape, DataType data_type, DataLayout data_layout, QuantizationInfo qinfo, QuantizationInfo output_qinfo) { - _target = compute_target(input_shape, data_type, data_layout, pool_info, rois_shape); - _reference = compute_reference(input_shape, data_type, pool_info, rois_shape); + _rois_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::QASYMM16 : data_type; + _target = compute_target(input_shape, data_type, data_layout, pool_info, rois_shape, qinfo, output_qinfo); + _reference = compute_reference(input_shape, data_type, pool_info, rois_shape, qinfo, output_qinfo); } protected: @@ -66,17 +69,17 @@ protected: const size_t num_rois = rois_shape.y(); std::mt19937 gen(library->seed()); - T *rois_ptr = static_cast<T *>(rois.data()); + TRois *rois_ptr = static_cast<TRois *>(rois.data()); const float pool_width = pool_info.pooled_width(); const float pool_height = pool_info.pooled_height(); const float roi_scale = pool_info.spatial_scale(); // Calculate distribution bounds - const auto scaled_width = static_cast<T>((shape[get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH)] / roi_scale) / pool_width); - const auto scaled_height = static_cast<T>((shape[get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT)] / roi_scale) / pool_height); - const auto min_width = static_cast<T>(pool_width / roi_scale); - const auto min_height = static_cast<T>(pool_height / roi_scale); + const auto scaled_width = static_cast<float>((shape[get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH)] / roi_scale) / pool_width); + const auto scaled_height = static_cast<float>((shape[get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT)] / roi_scale) / pool_height); + const auto min_width = static_cast<float>(pool_width / roi_scale); + const auto min_height = static_cast<float>(pool_height / roi_scale); // Create distributions std::uniform_int_distribution<int> dist_batch(0, shape[3] - 1); @@ -93,11 +96,21 @@ protected: const auto x2 = x1 + dist_w(gen); const auto y2 = y1 + dist_h(gen); - rois_ptr[values_per_roi * pw] = batch_idx; - rois_ptr[values_per_roi * pw + 1] = x1; - rois_ptr[values_per_roi * pw + 2] = y1; - rois_ptr[values_per_roi * pw + 3] = x2; - rois_ptr[values_per_roi * pw + 4] = y2; + rois_ptr[values_per_roi * pw] = batch_idx; + if(rois.data_type() == DataType::QASYMM16) + { + rois_ptr[values_per_roi * pw + 1] = quantize_qasymm16(static_cast<float>(x1), rois.quantization_info()); + rois_ptr[values_per_roi * pw + 2] = quantize_qasymm16(static_cast<float>(y1), rois.quantization_info()); + rois_ptr[values_per_roi * pw + 3] = quantize_qasymm16(static_cast<float>(x2), rois.quantization_info()); + rois_ptr[values_per_roi * pw + 4] = quantize_qasymm16(static_cast<float>(y2), rois.quantization_info()); + } + else + { + rois_ptr[values_per_roi * pw + 1] = static_cast<TRois>(x1); + rois_ptr[values_per_roi * pw + 2] = static_cast<TRois>(y1); + rois_ptr[values_per_roi * pw + 3] = static_cast<TRois>(x2); + rois_ptr[values_per_roi * pw + 4] = static_cast<TRois>(y2); + } } } @@ -105,17 +118,23 @@ protected: DataType data_type, DataLayout data_layout, const ROIPoolingLayerInfo &pool_info, - const TensorShape rois_shape) + const TensorShape rois_shape, + const QuantizationInfo &qinfo, + const QuantizationInfo &output_qinfo) { if(data_layout == DataLayout::NHWC) { permute(input_shape, PermutationVector(2U, 0U, 1U)); } + const QuantizationInfo rois_qinfo = is_data_type_quantized(data_type) ? QuantizationInfo(0.125f, 0) : QuantizationInfo(); + // Create tensors - TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, QuantizationInfo(), data_layout); - TensorType rois_tensor = create_tensor<TensorType>(rois_shape, data_type); - TensorType dst; + TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, qinfo, data_layout); + TensorType rois_tensor = create_tensor<TensorType>(rois_shape, _rois_data_type, 1, rois_qinfo); + + const TensorShape dst_shape = misc::shape_calculator::compute_roi_align_shape(*(src.info()), *(rois_tensor.info()), pool_info); + TensorType dst = create_tensor<TensorType>(dst_shape, data_type, 1, output_qinfo, data_layout); // Create and configure function FunctionType roi_align_layer; @@ -147,23 +166,51 @@ protected: SimpleTensor<T> compute_reference(const TensorShape &input_shape, DataType data_type, const ROIPoolingLayerInfo &pool_info, - const TensorShape rois_shape) + const TensorShape rois_shape, + const QuantizationInfo &qinfo, + const QuantizationInfo &output_qinfo) { // Create reference tensor - SimpleTensor<T> src{ input_shape, data_type }; - SimpleTensor<T> rois_tensor{ rois_shape, data_type }; + SimpleTensor<T> src{ input_shape, data_type, 1, qinfo }; + const QuantizationInfo rois_qinfo = is_data_type_quantized(data_type) ? QuantizationInfo(0.125f, 0) : QuantizationInfo(); + SimpleTensor<TRois> rois_tensor{ rois_shape, _rois_data_type, 1, rois_qinfo }; // Fill reference tensor fill(src); generate_rois(rois_tensor, input_shape, pool_info, rois_shape); - return reference::roi_align_layer(src, rois_tensor, pool_info); + return reference::roi_align_layer(src, rois_tensor, pool_info, output_qinfo); } TensorType _target{}; SimpleTensor<T> _reference{}; + DataType _rois_data_type{}; +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ROIAlignLayerFixture : public ROIAlignLayerGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(TensorShape input_shape, const ROIPoolingLayerInfo pool_info, TensorShape rois_shape, DataType data_type, DataLayout data_layout) + { + ROIAlignLayerGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, pool_info, rois_shape, data_type, data_layout, + QuantizationInfo(), QuantizationInfo()); + } }; +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ROIAlignLayerQuantizedFixture : public ROIAlignLayerGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(TensorShape input_shape, const ROIPoolingLayerInfo pool_info, TensorShape rois_shape, DataType data_type, + DataLayout data_layout, QuantizationInfo qinfo, QuantizationInfo output_qinfo) + { + ROIAlignLayerGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, pool_info, rois_shape, + data_type, data_layout, qinfo, output_qinfo); + } +}; } // namespace validation } // namespace test } // namespace arm_compute diff --git a/tests/validation/reference/ROIAlignLayer.cpp b/tests/validation/reference/ROIAlignLayer.cpp index 8a76983d44..8ad78ff915 100644 --- a/tests/validation/reference/ROIAlignLayer.cpp +++ b/tests/validation/reference/ROIAlignLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -112,15 +112,31 @@ T clamp(T value, T lower, T upper) { return std::max(lower, std::min(value, upper)); } + +SimpleTensor<float> convert_rois_from_asymmetric(SimpleTensor<uint16_t> rois) +{ + const UniformQuantizationInfo &quantization_info = rois.quantization_info().uniform(); + SimpleTensor<float> dst{ rois.shape(), DataType::F32, 1, QuantizationInfo(), rois.data_layout() }; + + for(int i = 0; i < rois.num_elements(); i += 5) + { + dst[i] = static_cast<float>(rois[i]); // batch idx + dst[i + 1] = dequantize_qasymm16(rois[i + 1], quantization_info); + dst[i + 2] = dequantize_qasymm16(rois[i + 2], quantization_info); + dst[i + 3] = dequantize_qasymm16(rois[i + 3], quantization_info); + dst[i + 4] = dequantize_qasymm16(rois[i + 4], quantization_info); + } + return dst; +} } // namespace -template <typename T> -SimpleTensor<T> roi_align_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &rois, const ROIPoolingLayerInfo &pool_info) +template <typename T, typename TRois> +SimpleTensor<T> roi_align_layer(const SimpleTensor<T> &src, const SimpleTensor<TRois> &rois, const ROIPoolingLayerInfo &pool_info, const QuantizationInfo &output_qinfo) { const size_t values_per_roi = rois.shape()[0]; const size_t num_rois = rois.shape()[1]; DataType dst_data_type = src.data_type(); - const auto *rois_ptr = static_cast<const T *>(rois.data()); + const auto *rois_ptr = static_cast<const TRois *>(rois.data()); TensorShape input_shape = src.shape(); TensorShape output_shape(pool_info.pooled_width(), pool_info.pooled_height(), src.shape()[2], num_rois); @@ -183,8 +199,19 @@ SimpleTensor<T> roi_align_layer(const SimpleTensor<T> &src, const SimpleTensor<T } return dst; } -template SimpleTensor<float> roi_align_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &rois, const ROIPoolingLayerInfo &pool_info); -template SimpleTensor<half> roi_align_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &rois, const ROIPoolingLayerInfo &pool_info); + +template SimpleTensor<float> roi_align_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &rois, const ROIPoolingLayerInfo &pool_info, const QuantizationInfo &output_qinfo); +template SimpleTensor<half> roi_align_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &rois, const ROIPoolingLayerInfo &pool_info, const QuantizationInfo &output_qinfo); + +template <> +SimpleTensor<uint8_t> roi_align_layer(const SimpleTensor<uint8_t> &src, const SimpleTensor<uint16_t> &rois, const ROIPoolingLayerInfo &pool_info, const QuantizationInfo &output_qinfo) +{ + SimpleTensor<float> src_tmp = convert_from_asymmetric(src); + SimpleTensor<float> rois_tmp = convert_rois_from_asymmetric(rois); + SimpleTensor<float> dst_tmp = roi_align_layer<float, float>(src_tmp, rois_tmp, pool_info, output_qinfo); + SimpleTensor<uint8_t> dst = convert_to_asymmetric(dst_tmp, output_qinfo); + return dst; +} } // namespace reference } // namespace validation } // namespace test diff --git a/tests/validation/reference/ROIAlignLayer.h b/tests/validation/reference/ROIAlignLayer.h index b67ff42166..e1568133e7 100644 --- a/tests/validation/reference/ROIAlignLayer.h +++ b/tests/validation/reference/ROIAlignLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -36,8 +36,8 @@ namespace validation { namespace reference { -template <typename T> -SimpleTensor<T> roi_align_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &rois, const ROIPoolingLayerInfo &pool_info); +template <typename T, typename TRois> +SimpleTensor<T> roi_align_layer(const SimpleTensor<T> &src, const SimpleTensor<TRois> &rois, const ROIPoolingLayerInfo &pool_info, const QuantizationInfo &output_qinfo); } // namespace reference } // namespace validation } // namespace test |