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Diffstat (limited to 'tests/validation/Reference.cpp')
| -rw-r--r-- | tests/validation/Reference.cpp | 596 |
1 files changed, 596 insertions, 0 deletions
diff --git a/tests/validation/Reference.cpp b/tests/validation/Reference.cpp new file mode 100644 index 0000000000..263c57b16b --- /dev/null +++ b/tests/validation/Reference.cpp @@ -0,0 +1,596 @@ +/* + * Copyright (c) 2017 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 "Reference.h" + +#include "Globals.h" +#include "Helpers.h" +#include "ReferenceCPP.h" +#include "TensorLibrary.h" +#include "validation/Helpers.h" + +#include <random> + +using namespace arm_compute::test; + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +RawTensor Reference::compute_reference_integral_image(const TensorShape &shape) +{ + // Create reference + RawTensor ref_src = library->get(shape, DataType::U8); + RawTensor ref_dst = library->get(shape, DataType::U32); + + // Fill reference + library->fill_tensor_uniform(ref_src, 0); + + // Compute reference + ReferenceCPP::integral_image(ref_src, ref_dst); + + return ref_dst; +} +RawTensor Reference::compute_reference_absolute_difference(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out) +{ + // Create reference + RawTensor ref_src1 = library->get(shape, dt_in0); + RawTensor ref_src2 = library->get(shape, dt_in1); + RawTensor ref_dst = library->get(shape, dt_out); + + // Fill reference + library->fill_tensor_uniform(ref_src1, 0); + library->fill_tensor_uniform(ref_src2, 1); + + // Compute reference + ReferenceCPP::absolute_difference(ref_src1, ref_src2, ref_dst); + + return ref_dst; +} + +RawTensor Reference::compute_reference_accumulate(const TensorShape &shape) +{ + // Create reference + RawTensor ref_src = library->get(shape, DataType::U8); + RawTensor ref_dst = library->get(shape, DataType::S16); + + // Fill reference + library->fill_tensor_uniform(ref_src, 0); + library->fill_tensor_uniform(ref_dst, 1); + + // Compute reference + ReferenceCPP::accumulate(ref_src, ref_dst); + + return ref_dst; +} + +RawTensor Reference::compute_reference_accumulate_squared(const TensorShape &shape, uint32_t shift) +{ + // Create reference + RawTensor ref_src = library->get(shape, DataType::U8); + RawTensor ref_dst = library->get(shape, DataType::S16); + + // Fill reference + // ref_dst tensor filled with non-negative values + library->fill_tensor_uniform(ref_src, 0); + library->fill_tensor_uniform(ref_dst, 1, static_cast<int16_t>(0), std::numeric_limits<int16_t>::max()); + + // Compute reference + ReferenceCPP::accumulate_squared(ref_src, ref_dst, shift); + + return ref_dst; +} + +RawTensor Reference::compute_reference_accumulate_weighted(const TensorShape &shape, float alpha) +{ + // Create reference + RawTensor ref_src = library->get(shape, DataType::U8); + RawTensor ref_dst = library->get(shape, DataType::U8); + + // Fill reference + library->fill_tensor_uniform(ref_src, 0); + library->fill_tensor_uniform(ref_dst, 1); + + // Compute reference + ReferenceCPP::accumulate_weighted(ref_src, ref_dst, alpha); + + return ref_dst; +} + +RawTensor Reference::compute_reference_arithmetic_addition(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, ConvertPolicy convert_policy) +{ + // Create reference + RawTensor ref_src1 = library->get(shape, dt_in0); + RawTensor ref_src2 = library->get(shape, dt_in1); + RawTensor ref_dst = library->get(shape, dt_out); + + // Fill reference + library->fill_tensor_uniform(ref_src1, 0); + library->fill_tensor_uniform(ref_src2, 1); + + // Compute reference + ReferenceCPP::arithmetic_addition(ref_src1, ref_src2, ref_dst, convert_policy); + + return ref_dst; +} + +RawTensor Reference::compute_reference_arithmetic_subtraction(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, ConvertPolicy convert_policy) +{ + // Create reference + RawTensor ref_src1 = library->get(shape, dt_in0); + RawTensor ref_src2 = library->get(shape, dt_in1); + RawTensor ref_dst = library->get(shape, dt_out); + + // Fill reference + library->fill_tensor_uniform(ref_src1, 0); + library->fill_tensor_uniform(ref_src2, 1); + + // Compute reference + ReferenceCPP::arithmetic_subtraction(ref_src1, ref_src2, ref_dst, convert_policy); + + return ref_dst; +} + +RawTensor Reference::compute_reference_bitwise_and(const TensorShape &shape) +{ + // Create reference + RawTensor ref_src1 = library->get(shape, DataType::U8); + RawTensor ref_src2 = library->get(shape, DataType::U8); + RawTensor ref_dst = library->get(shape, DataType::U8); + + // Fill reference + library->fill_tensor_uniform(ref_src1, 0); + library->fill_tensor_uniform(ref_src2, 1); + + // Compute reference + ReferenceCPP::bitwise_and(ref_src1, ref_src2, ref_dst); + + return ref_dst; +} + +RawTensor Reference::compute_reference_bitwise_or(const TensorShape &shape) +{ + // Create reference + RawTensor ref_src1 = library->get(shape, DataType::U8); + RawTensor ref_src2 = library->get(shape, DataType::U8); + RawTensor ref_dst = library->get(shape, DataType::U8); + + // Fill reference + library->fill_tensor_uniform(ref_src1, 0); + library->fill_tensor_uniform(ref_src2, 1); + + // Compute reference + ReferenceCPP::bitwise_or(ref_src1, ref_src2, ref_dst); + + return ref_dst; +} + +RawTensor Reference::compute_reference_bitwise_xor(const TensorShape &shape) +{ + // Create reference + RawTensor ref_src1 = library->get(shape, DataType::U8); + RawTensor ref_src2 = library->get(shape, DataType::U8); + RawTensor ref_dst = library->get(shape, DataType::U8); + + // Fill reference + library->fill_tensor_uniform(ref_src1, 0); + library->fill_tensor_uniform(ref_src2, 1); + + // Compute reference + ReferenceCPP::bitwise_xor(ref_src1, ref_src2, ref_dst); + + return ref_dst; +} + +RawTensor Reference::compute_reference_bitwise_not(const TensorShape &shape) +{ + // Create reference + RawTensor ref_src = library->get(shape, DataType::U8); + RawTensor ref_dst = library->get(shape, DataType::U8); + + // Fill reference + library->fill_tensor_uniform(ref_src, 0); + + // Compute reference + ReferenceCPP::bitwise_not(ref_src, ref_dst); + + return ref_dst; +} + +RawTensor Reference::compute_reference_box3x3(const TensorShape &shape) +{ + // Create reference + RawTensor ref_src = library->get(shape, DataType::U8); + RawTensor ref_dst = library->get(shape, DataType::U8); + + // Fill reference + library->fill_tensor_uniform(ref_src, 0); + + // Compute reference + ReferenceCPP::box3x3(ref_src, ref_dst); + + return ref_dst; +} + +RawTensor Reference::compute_reference_depth_convert(const TensorShape &shape, DataType dt_in, DataType dt_out, ConvertPolicy policy, uint32_t shift, uint32_t fixed_point_position) +{ + RawTensor ref_src = library->get(shape, dt_in, 1, fixed_point_position); + RawTensor ref_dst = library->get(shape, dt_out, 1, fixed_point_position); + + // Fill reference + library->fill_tensor_uniform(ref_src, 0); + + // Compute reference + ReferenceCPP::depth_convert(ref_src, ref_dst, policy, shift); + + return ref_dst; +} + +RawTensor Reference::compute_reference_gemm(const TensorShape &src_shape1, const TensorShape &src_shape2, const TensorShape &src_shape3, + const TensorShape &dst_shape, float alpha, float beta, DataType dt, int fixed_point_position) +{ + RawTensor src1 = library->get(src_shape1, dt, 1, fixed_point_position); + RawTensor src2 = library->get(src_shape2, dt, 1, fixed_point_position); + RawTensor src3 = library->get(src_shape3, dt, 1, fixed_point_position); + RawTensor dst = library->get(dst_shape, dt, 1, fixed_point_position); + + // Fill reference + if(dt == DataType::F32) + { + std::uniform_real_distribution<> distribution(-1.0f, 1.0f); + library->fill(src1, distribution, 0); + library->fill(src2, distribution, 1); + library->fill(src3, distribution, 2); + } + else + { + library->fill_tensor_uniform(src1, 0); + library->fill_tensor_uniform(src2, 1); + library->fill_tensor_uniform(src3, 2); + } + + // Compute reference + ReferenceCPP::gemm(src1, src2, src3, dst, alpha, beta); + + return dst; +} + +RawTensor Reference::compute_reference_pixel_wise_multiplication(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, float scale, ConvertPolicy convert_policy, + RoundingPolicy rounding_policy) +{ + // Create reference + RawTensor ref_src1 = library->get(shape, dt_in0); + RawTensor ref_src2 = library->get(shape, dt_in1); + RawTensor ref_dst = library->get(shape, dt_out); + + // Fill reference + library->fill_tensor_uniform(ref_src1, 0); + library->fill_tensor_uniform(ref_src2, 1); + + // Compute reference + ReferenceCPP::pixel_wise_multiplication(ref_src1, ref_src2, ref_dst, scale, convert_policy, rounding_policy); + + return ref_dst; +} + +RawTensor Reference::compute_reference_fixed_point_pixel_wise_multiplication(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, float scale, int fixed_point_position, + ConvertPolicy convert_policy, RoundingPolicy rounding_policy) +{ + // Create reference + RawTensor ref_src1 = library->get(shape, dt_in0, 1, fixed_point_position); + RawTensor ref_src2 = library->get(shape, dt_in1, 1, fixed_point_position); + RawTensor ref_dst = library->get(shape, dt_out, 1, fixed_point_position); + + // Fill reference + library->fill_tensor_uniform(ref_src1, 0); + library->fill_tensor_uniform(ref_src2, 1); + + // Compute reference + ReferenceCPP::fixed_point_pixel_wise_multiplication(ref_src1, ref_src2, ref_dst, scale, convert_policy, rounding_policy); + + return ref_dst; +} + +RawTensor Reference::compute_reference_threshold(const TensorShape &shape, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper) +{ + // Create reference + RawTensor ref_src1 = library->get(shape, DataType::U8); + RawTensor ref_dst = library->get(shape, DataType::U8); + + // Fill reference + library->fill_tensor_uniform(ref_src1, 0); + + // Compute reference + ReferenceCPP::threshold(ref_src1, ref_dst, threshold, false_value, true_value, type, upper); + + return ref_dst; +} + +RawTensor Reference::compute_reference_activation_layer(const TensorShape &shape, DataType dt, ActivationLayerInfo act_info, int fixed_point_position) +{ + // Create reference + RawTensor ref_src = library->get(shape, dt, 1, fixed_point_position); + RawTensor ref_dst = library->get(shape, dt, 1, fixed_point_position); + + // Fill reference + if(dt == DataType::F32) + { + float min_bound = 0; + float max_bound = 0; + std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<float>(act_info.activation()); + std::uniform_real_distribution<> distribution(min_bound, max_bound); + library->fill(ref_src, distribution, 0); + } + else + { + int min_bound = 0; + int max_bound = 0; + std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<int8_t>(act_info.activation(), fixed_point_position); + std::uniform_int_distribution<> distribution(min_bound, max_bound); + library->fill(ref_src, distribution, 0); + } + + // Compute reference + ReferenceCPP::activation_layer(ref_src, ref_dst, act_info); + + return ref_dst; +} + +RawTensor Reference::compute_reference_batch_normalization_layer(const TensorShape &shape0, const TensorShape &shape1, DataType dt, float epsilon, int fixed_point_position) +{ + // Create reference + RawTensor ref_src = library->get(shape0, dt, 1, fixed_point_position); + RawTensor ref_dst = library->get(shape0, dt, 1, fixed_point_position); + RawTensor ref_mean = library->get(shape1, dt, 1, fixed_point_position); + RawTensor ref_var = library->get(shape1, dt, 1, fixed_point_position); + RawTensor ref_beta = library->get(shape1, dt, 1, fixed_point_position); + RawTensor ref_gamma = library->get(shape1, dt, 1, fixed_point_position); + + // Fill tensors with values from -1 to 1. + if(dt == DataType::F32) + { + float min_bound = 0.f; + float max_bound = 0.f; + std::tie(min_bound, max_bound) = get_batchnormalization_layer_test_bounds<float>(); + std::uniform_real_distribution<> distribution(min_bound, max_bound); + std::uniform_real_distribution<> distribution_var(0, max_bound); + library->fill(ref_src, distribution, 0); + library->fill(ref_mean, distribution, 1); + library->fill(ref_var, distribution_var, 0); + library->fill(ref_beta, distribution, 3); + library->fill(ref_gamma, distribution, 4); + } + else + { + int min_bound = 0; + int max_bound = 0; + std::tie(min_bound, max_bound) = get_batchnormalization_layer_test_bounds<int8_t>(fixed_point_position); + std::uniform_int_distribution<> distribution(min_bound, max_bound); + std::uniform_int_distribution<> distribution_var(0, max_bound); + library->fill(ref_src, distribution, 0); + library->fill(ref_mean, distribution, 1); + library->fill(ref_var, distribution_var, 0); + library->fill(ref_beta, distribution, 3); + library->fill(ref_gamma, distribution, 4); + } + + // Compute reference + ReferenceCPP::batch_normalization_layer(ref_src, ref_dst, ref_mean, ref_var, ref_beta, ref_gamma, epsilon, fixed_point_position); + + return ref_dst; +} + +RawTensor Reference::compute_reference_convolution_layer(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, DataType dt, + const PadStrideInfo &conv_info, int fixed_point_position) +{ + // Create reference + RawTensor ref_src = library->get(input_shape, dt, 1, fixed_point_position); + RawTensor ref_weights = library->get(weights_shape, dt, 1, fixed_point_position); + RawTensor ref_bias = library->get(bias_shape, dt, 1, fixed_point_position); + RawTensor ref_dst = library->get(output_shape, dt, 1, fixed_point_position); + + // Fill reference + if(dt == DataType::F32) + { + std::uniform_real_distribution<> distribution(-1.0f, 1.0f); + library->fill(ref_src, distribution, 0); + library->fill(ref_weights, distribution, 1); + library->fill(ref_bias, distribution, 2); + } + else + { + library->fill_tensor_uniform(ref_src, 0); + library->fill_tensor_uniform(ref_weights, 1); + library->fill_tensor_uniform(ref_bias, 2); + } + + // Compute reference + ReferenceCPP::convolution_layer(ref_src, ref_weights, ref_bias, ref_dst, conv_info); + + return ref_dst; +} + +RawTensor Reference::compute_reference_fully_connected_layer(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, + DataType dt, bool transpose_weights, int fixed_point_position) +{ + // Create reference + RawTensor ref_src = library->get(input_shape, dt, 1, fixed_point_position); + RawTensor ref_bias = library->get(bias_shape, dt, 1, fixed_point_position); + RawTensor ref_dst = library->get(output_shape, dt, 1, fixed_point_position); + + // Swap the first and second dimension of weights' shape if transpose_weights is true + TensorShape ws = weights_shape; + if(transpose_weights) + { + const size_t dimx = ws.x(); + ws.set(0, ws.y()); + ws.set(1, dimx); + } + + RawTensor ref_weights = library->get(ws, dt, 1, fixed_point_position); + + // Fill reference + if(dt == DataType::F32) + { + std::uniform_real_distribution<> distribution(-1.0f, 1.0f); + library->fill(ref_src, distribution, 0); + library->fill(ref_weights, distribution, 1); + library->fill(ref_bias, distribution, 2); + } + else + { + library->fill_tensor_uniform(ref_src, 0); + library->fill_tensor_uniform(ref_weights, 1); + library->fill_tensor_uniform(ref_bias, 2); + } + + // Compute reference + ReferenceCPP::fully_connected_layer(ref_src, ref_weights, ref_bias, ref_dst); + + return ref_dst; +} + +RawTensor Reference::compute_reference_normalization_layer(const TensorShape &shape, DataType dt, NormalizationLayerInfo norm_info, int fixed_point_position) +{ + // Create reference + RawTensor ref_src = library->get(shape, dt, 1, fixed_point_position); + RawTensor ref_dst = library->get(shape, dt, 1, fixed_point_position); + + // Fill reference + if(dt == DataType::QS8) + { + const int8_t one_fixed_point = 1 << fixed_point_position; + const int8_t minus_one_fixed_point = -one_fixed_point; + library->fill_tensor_uniform(ref_src, 0, minus_one_fixed_point, one_fixed_point); + } + else + { + library->fill_tensor_uniform(ref_src, 0); + } + + // Compute reference + ReferenceCPP::normalization_layer(ref_src, ref_dst, norm_info); + + return ref_dst; +} + +RawTensor Reference::compute_reference_pooling_layer(const TensorShape &shape_in, const TensorShape &shape_out, DataType dt, PoolingLayerInfo pool_info, int fixed_point_position) +{ + // Create reference + RawTensor ref_src = library->get(shape_in, dt, 1, fixed_point_position); + RawTensor ref_dst = library->get(shape_out, dt, 1, fixed_point_position); + + // Fill reference + int min = 0; + int max = 0; + switch(dt) + { + case DataType::F32: + min = -1; + max = 1; + break; + case DataType::QS8: + min = -(1 << fixed_point_position); + max = (1 << fixed_point_position); + break; + default: + ARM_COMPUTE_ERROR("DataType not supported."); + } + std::uniform_real_distribution<> distribution(min, max); + library->fill(ref_src, distribution, 0.0); + + // Compute reference + ReferenceCPP::pooling_layer(ref_src, ref_dst, pool_info, fixed_point_position); + + return ref_dst; +} + +RawTensor Reference::compute_reference_softmax_layer(const TensorShape &shape, DataType dt, int fixed_point_position) +{ + // Create reference + RawTensor ref_src = library->get(shape, dt, 1, fixed_point_position); + RawTensor ref_dst = library->get(shape, dt, 1, fixed_point_position); + + // Fill reference + if(arm_compute::is_data_type_float(dt)) + { + std::uniform_real_distribution<> distribution(-10, 10); + library->fill(ref_src, distribution, 0); + } + else + { + int one_fixed = 1 << fixed_point_position; + std::uniform_int_distribution<> distribution(-one_fixed, one_fixed); + library->fill(ref_src, distribution, 0); + } + + // Compute reference + ReferenceCPP::softmax_layer(ref_src, ref_dst); + + return ref_dst; +} + +RawTensor Reference::compute_reference_fixed_point_operation(const TensorShape &shape, DataType dt_in, DataType dt_out, FixedPointOp op, int fixed_point_position) +{ + // Create reference + RawTensor ref_src = library->get(shape, dt_in, 1, fixed_point_position); + RawTensor ref_dst = library->get(shape, dt_out, 1, fixed_point_position); + + // Fill reference + int min = 0; + int max = 0; + switch(op) + { + case(FixedPointOp::INV_SQRT): + min = 32; + max = 127; + break; + case(FixedPointOp::LOG): + min = (1 << (fixed_point_position - 1)); + max = 63; + break; + case(FixedPointOp::EXP): + min = 1; + max = (1 << (fixed_point_position - 1)); + break; + case(FixedPointOp::RECIPROCAL): + min = 15; + max = 100; + break; + default: + ARM_COMPUTE_ERROR("Fixed point operation not supported"); + } + std::uniform_int_distribution<> distribution(min, max); + library->fill(ref_src, distribution, 0); + + // Compute reference + ReferenceCPP::fixed_point_operation(ref_src, ref_dst, op); + + return ref_dst; +} + +} // namespace validation +} // namespace test +} // namespace arm_compute |