From 4b869532f8b2aa7f02aa55c4f4813e994ea2df68 Mon Sep 17 00:00:00 2001 From: Luca Foschiani Date: Thu, 13 Feb 2020 15:07:36 +0000 Subject: COMPMID-2966 Add support for QASYMM8_SIGNED in NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel Signed-off-by: Luca Foschiani Change-Id: Ia8692f8fda16fa3b73f343e4b5b1b55e14403225 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2750 Reviewed-by: Michele Di Giorgio Tested-by: Arm Jenkins Comments-Addressed: Arm Jenkins --- tests/validation/fixtures/GEMMLowpFixture.h | 114 +++++++++++++++++++++++++++- 1 file changed, 112 insertions(+), 2 deletions(-) (limited to 'tests/validation/fixtures/GEMMLowpFixture.h') diff --git a/tests/validation/fixtures/GEMMLowpFixture.h b/tests/validation/fixtures/GEMMLowpFixture.h index be9ce96dcb..e3dc7381fc 100644 --- a/tests/validation/fixtures/GEMMLowpFixture.h +++ b/tests/validation/fixtures/GEMMLowpFixture.h @@ -301,8 +301,16 @@ protected: TensorType c = create_tensor(shape, DataType::QASYMM8, 1); // Create and configure function - FunctionType output_stage; - output_stage.configure(&a, add_bias ? &b : nullptr, &c, result_offset, result_mult_int, result_shift, min, max); + FunctionType output_stage; + GEMMLowpOutputStageInfo output_stage_info = GEMMLowpOutputStageInfo(); + output_stage_info.type = GEMMLowpOutputStageType::QUANTIZE_DOWN; + output_stage_info.gemmlowp_offset = result_offset; + output_stage_info.gemmlowp_multiplier = result_mult_int; + output_stage_info.gemmlowp_shift = result_shift; + output_stage_info.gemmlowp_min_bound = min; + output_stage_info.gemmlowp_max_bound = max; + output_stage_info.output_data_type = DataType::QASYMM8; + output_stage.configure(&a, add_bias ? &b : nullptr, &c, output_stage_info); ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(c.info()->is_resizable(), framework::LogLevel::ERRORS); @@ -366,6 +374,108 @@ protected: SimpleTensor _reference{}; }; +template +class GEMMLowpQuantizeDownInt32ToInt8ScaleValidationFixture : public framework::Fixture +{ +public: + template + void setup(TensorShape shape, int32_t result_offset, int32_t result_mult_int, int32_t result_shift, int32_t min, int32_t max, bool add_bias) + { + _target = compute_target(shape, result_offset, result_mult_int, result_shift, min, max, add_bias); + _reference = compute_reference(shape, result_offset, result_mult_int, result_shift, min, max, add_bias); + } + +protected: + template + void fill(U &&tensor, int i) + { + std::uniform_int_distribution<> distribution(-6000, 6000); + library->fill(tensor, distribution, i); + } + + TensorType compute_target(const TensorShape &shape, int32_t result_offset, int32_t result_mult_int, int32_t result_shift, int32_t min, int32_t max, bool add_bias) + { + TensorShape shape_bias(shape[0]); + + // Create tensors + TensorType a = create_tensor(shape, DataType::S32, 1); + TensorType b = create_tensor(shape_bias, DataType::S32, 1); + TensorType c = create_tensor(shape, DataType::QASYMM8_SIGNED, 1); + + // Create and configure function + FunctionType output_stage; + GEMMLowpOutputStageInfo output_stage_info = GEMMLowpOutputStageInfo(); + output_stage_info.type = GEMMLowpOutputStageType::QUANTIZE_DOWN; + output_stage_info.gemmlowp_offset = result_offset; + output_stage_info.gemmlowp_multiplier = result_mult_int; + output_stage_info.gemmlowp_shift = result_shift; + output_stage_info.gemmlowp_min_bound = min; + output_stage_info.gemmlowp_max_bound = max; + output_stage_info.output_data_type = DataType::QASYMM8_SIGNED; + output_stage.configure(&a, add_bias ? &b : nullptr, &c, output_stage_info); + + ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(c.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Allocate tensors + a.allocator()->allocate(); + c.allocator()->allocate(); + + ARM_COMPUTE_EXPECT(!a.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!c.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Fill tensor + fill(AccessorType(a), 0); + + if(add_bias) + { + ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Allocate bias tensor + b.allocator()->allocate(); + + ARM_COMPUTE_EXPECT(!b.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Fill tensor + fill(AccessorType(b), 1); + } + + // Compute GEMM function + output_stage.run(); + return c; + } + + SimpleTensor compute_reference(const TensorShape &shape, int32_t result_offset, int32_t result_mult_int, int32_t result_shift, int32_t min, int32_t max, bool add_bias) + { + // Create reference + TensorShape shape_bias(shape[0]); + + SimpleTensor a{ shape, DataType::S32, 1 }; + SimpleTensor b{ shape_bias, DataType::S32, 1 }; + + // Fill reference + fill(a, 0); + + const std::vector result_mult_int_vec = { result_mult_int }; + const std::vector result_shift_vec = { result_shift }; + + if(add_bias) + { + // Fill bias + fill(b, 1); + + return reference::gemmlowp_quantize_down_scale(a, b, result_offset, result_mult_int_vec, result_shift_vec, min, max); + } + else + { + return reference::gemmlowp_quantize_down_scale(a, result_offset, result_mult_int_vec, result_shift_vec, min, max); + } + } + + TensorType _target{}; + SimpleTensor _reference{}; +}; + template class GEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointValidationFixture : public framework::Fixture { -- cgit v1.2.1