From f47bfb97fa8bc928a7860b84b7b227f716f65e58 Mon Sep 17 00:00:00 2001 From: Sanghoon Lee Date: Tue, 23 Jan 2018 15:16:47 +0000 Subject: COMPMID-594: Implement reference and CL/NEON validation for LocallyConnected Change-Id: I01e7abcf3f1b19458128e277044af850ad9fa224 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/118610 Reviewed-by: Anthony Barbier Tested-by: Jenkins --- tests/validation/reference/Convolution3d.h | 223 +++++++++++++++++++++++++++++ 1 file changed, 223 insertions(+) create mode 100644 tests/validation/reference/Convolution3d.h (limited to 'tests/validation/reference/Convolution3d.h') diff --git a/tests/validation/reference/Convolution3d.h b/tests/validation/reference/Convolution3d.h new file mode 100644 index 0000000000..b99d534635 --- /dev/null +++ b/tests/validation/reference/Convolution3d.h @@ -0,0 +1,223 @@ +/* + * Copyright (c) 2017-2018 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: + *asymm_int_mult + * 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, asymm_int_multDAMAGES 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. + */ +#ifndef __ARM_COMPUTE_TEST_VALIDATION_CONVOLUTION_H__ +#define __ARM_COMPUTE_TEST_VALIDATION_CONVOLUTION_H__ + +#include "arm_compute/core/utils/quantization/AsymmHelpers.h" +#include "tests/validation/FixedPoint.h" +#include "tests/validation/Helpers.h" +#include "tests/validation/reference/UtilsQuantizedAsymm.h" + +namespace arm_compute +{ +namespace test +{ +namespace convolution_3d +{ +namespace detail +{ +inline bool is_valid_pixel(int i, int min, int max) +{ + return (i >= min && i < max); +} + +// 3D convolution for floating point type +template < typename T, typename TB, typename std::enable_if < validation::is_floating_point::value &&validation::is_floating_point::value, int >::type = 0 > +inline void convolution3d(const SimpleTensor &in, const SimpleTensor &weights, const SimpleTensor &bias, SimpleTensor &out, + int i_offset, int w_offset, int b_offset, int o_offset, + int xi, int yi, int width_in, int height_in, int depth_in, int width_weights, int height_weights) +{ + const T *in_ptr = in.data() + i_offset; + const T *w_ptr = weights.data() + w_offset; + const TB *b_ptr = bias.data() + b_offset; + T *out_ptr = out.data() + o_offset; + + const int half_width_weights_start = width_weights / 2; + const int half_width_weights_end = ((width_weights % 2) == 0) ? (half_width_weights_start - 1) : half_width_weights_start; + const int half_height_weights_start = height_weights / 2; + const int half_height_weights_end = ((height_weights % 2) == 0) ? (half_height_weights_start - 1) : half_height_weights_start; + + // Reset accumulator + T acc(0); + + // Compute a 2D convolution for each IFM and accumulate the result + for(int ifm = 0; ifm < depth_in; ++ifm) + { + // Compute the offset for the input slice + const int offset_slice_in = xi + yi * width_in + ifm * width_in * height_in; + + // Compute 2D convolution + for(int yk = -half_height_weights_start; yk <= half_height_weights_end; ++yk) + { + for(int xk = -half_width_weights_start; xk <= half_width_weights_end; ++xk) + { + // Check if the pixel is out-of-bound + if(is_valid_pixel(xi + xk, 0, width_in) && is_valid_pixel(yi + yk, 0, height_in)) + { + const int idx = xk + half_width_weights_start; + const int idy = yk + half_height_weights_start; + + const T i_value = in_ptr[offset_slice_in + xk + yk * width_in]; + const T w_value = w_ptr[idx + idy * width_weights + ifm * width_weights * height_weights]; + + acc += i_value * w_value; + } + } + } + } + + // Accumulate the bias and store the result + *out_ptr = acc + (*b_ptr); +} + +// 3D convolution for fixed point type +template < typename T, typename TB, typename std::enable_if < std::is_integral::value &&std::is_integral::value, int >::type = 0 > +inline void convolution3d(const SimpleTensor &in, const SimpleTensor &weights, const SimpleTensor &bias, SimpleTensor &out, + int i_offset, int w_offset, int b_offset, int o_offset, + int xi, int yi, int width_in, int height_in, int depth_in, int width_weights, int height_weights) +{ + const T *in_ptr = in.data() + i_offset; + const T *w_ptr = weights.data() + w_offset; + const T *b_ptr = bias.data() + b_offset; + T *out_ptr = out.data() + o_offset; + int fixed_point_position = in.fixed_point_position(); + + const int half_width_weights_start = width_weights / 2; + const int half_width_weights_end = ((width_weights % 2) == 0) ? (half_width_weights_start - 1) : half_width_weights_start; + const int half_height_weights_start = height_weights / 2; + const int half_height_weights_end = ((height_weights % 2) == 0) ? (half_height_weights_start - 1) : half_height_weights_start; + + using namespace fixed_point_arithmetic; + using promoted_type = fixed_point_arithmetic::traits::promote_t; + + // Reset accumulator + fixed_point acc(0, fixed_point_position); + + // Compute a 2D convolution for each IFM and accumulate the result + for(int ifm = 0; ifm < depth_in; ++ifm) + { + // Compute the offset for the input slice + const int offset_slice_in = xi + yi * width_in + ifm * width_in * height_in; + + // Compute 2D convolution + for(int yk = -half_height_weights_start; yk <= half_height_weights_end; ++yk) + { + for(int xk = -half_width_weights_start; xk <= half_width_weights_end; ++xk) + { + // Check if the pixel is out-of-bound + if(is_valid_pixel(xi + xk, 0, width_in) && is_valid_pixel(yi + yk, 0, height_in)) + { + const int idx = xk + half_width_weights_start; + const int idy = yk + half_height_weights_start; + + const fixed_point i_value(in_ptr[offset_slice_in + xk + yk * width_in], fixed_point_position, true); + const fixed_point w_value(w_ptr[idx + idy * width_weights + ifm * width_weights * height_weights], fixed_point_position, true); + const fixed_point iw = i_value * w_value; + acc = iw + acc; + } + } + } + } + + // Get the bias + const fixed_point b(*b_ptr, fixed_point_position, true); + + // Accumulate the bias and covert back + acc = acc + b; + fixed_point res(acc); + *out_ptr = res.raw(); +} + +// 3D convolution for QASYMM8 type +template <> +inline void convolution3d(const SimpleTensor &in, const SimpleTensor &weights, const SimpleTensor &bias, SimpleTensor &out, + int i_offset, int w_offset, int b_offset, int o_offset, + int xi, int yi, int width_in, int height_in, int depth_in, int width_weights, int height_weights) +{ + const uint8_t *in_ptr = in.data() + i_offset; + const uint8_t *w_ptr = weights.data() + w_offset; + const int32_t *b_ptr = bias.data() + b_offset; + uint8_t *out_ptr = out.data() + o_offset; + + const int input_offset = -in.quantization_info().offset; + const float input_scale = in.quantization_info().scale; + const int weights_offset = -weights.quantization_info().offset; + const float weights_scale = weights.quantization_info().scale; + const int output_offset = out.quantization_info().offset; + const float output_scale = out.quantization_info().scale; + + int output_multiplier = 0; + int output_shift = 0; + const float multiplier = input_scale * weights_scale / output_scale; + arm_compute::quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); + + const int half_width_weights_start = width_weights / 2; + const int half_width_weights_end = ((width_weights % 2) == 0) ? (half_width_weights_start - 1) : half_width_weights_start; + const int half_height_weights_start = height_weights / 2; + const int half_height_weights_end = ((height_weights % 2) == 0) ? (half_height_weights_start - 1) : half_height_weights_start; + + // Reset accumulator + int32_t acc(0); + + // Compute a 2D convolution for each IFM and accumulate the result + for(int ifm = 0; ifm < depth_in; ++ifm) + { + // Compute the offset for the input slice + const int offset_slice_in = xi + yi * width_in + ifm * width_in * height_in; + + // Compute 2D convolution + for(int yk = -half_height_weights_start; yk <= half_height_weights_end; ++yk) + { + for(int xk = -half_width_weights_start; xk <= half_width_weights_end; ++xk) + { + // Check if the pixel is out-of-bound + if(is_valid_pixel(xi + xk, 0, width_in) && is_valid_pixel(yi + yk, 0, height_in)) + { + const int idx = xk + half_width_weights_start; + const int idy = yk + half_height_weights_start; + + const uint8_t i_value = in_ptr[offset_slice_in + xk + yk * width_in]; + const uint8_t w_value = w_ptr[idx + idy * width_weights + ifm * width_weights * height_weights]; + + acc += (i_value + input_offset) * (w_value + weights_offset); + } + } + } + } + + // Accumulate the bias + acc += (*b_ptr); + + acc = validation::asymm_rounding_divide_by_pow2(validation::asymm_int_mult(acc, output_multiplier), output_shift); + acc += output_offset; + acc = utility::clamp(acc, 0, 255); + + // Store the result + *out_ptr = acc; +} +} // namespace detail +} // namespace convolution_3d +} // namespace test +} // namespace arm_compute +#endif /*__ARM_COMPUTE_TEST_VALIDATION_CONVOLUTION_H__ */ -- cgit v1.2.1