COMPMID-3585: Android R while_fib_n_5_quant8 failure on CpuAcc
Assembly kernels do not support quantized GEMM when the multiplier is
greater than 1 (which leads to negative result shift used for
requantization).
Change-Id: I7a766cd0d13f549d217613ca67bc952923f309de
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3538
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp b/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp
index 31d5359..dada6d1 100644
--- a/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp
+++ b/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp
@@ -117,8 +117,18 @@
{
if(is_data_type_quantized_asymmetric(a_to_use->info()->data_type()) && info.gemmlowp_output_stage().type == GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT)
{
- _asm_glue.configure(a_to_use, b, c, output, gemm_info);
- _fused_assembly_path = _asm_glue.is_configured();
+ // Result shifts < 0 are not supported by asm kernels
+ const std::vector<int32_t> &shifts = info.gemmlowp_output_stage().gemmlowp_shifts;
+ const bool is_asm_supported = info.gemmlowp_output_stage().gemmlowp_shift >= 0
+ && std::all_of(shifts.cbegin(), shifts.cend(), [](int32_t val)
+ {
+ return val >= 0;
+ });
+ if(is_asm_supported)
+ {
+ _asm_glue.configure(a_to_use, b, c, output, gemm_info);
+ _fused_assembly_path = _asm_glue.is_configured();
+ }
}
else
{
@@ -327,22 +337,20 @@
// Check if we need to run the optimized assembly kernel
bool run_optimised = false;
bool run_optimised_requantized = false;
- if(a_to_use->data_type() == DataType::QASYMM8 && info.gemmlowp_output_stage().type == GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT)
+ if(is_data_type_quantized_asymmetric(a_to_use->data_type()) && info.gemmlowp_output_stage().type == GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT)
{
- run_optimised = bool(NEGEMMAssemblyDispatch::validate(a_to_use, b, c, output, gemm_info));
- run_optimised_requantized = run_optimised;
-
- const UniformQuantizationInfo a_qinfo = a_to_use->quantization_info().uniform();
- const QuantizationInfo b_qinfo = b->quantization_info();
- const UniformQuantizationInfo output_qinfo = output->quantization_info().uniform();
- for(auto const s : b_qinfo.scale())
+ // Result shifts < 0 are not supported by asm kernels
+ const std::vector<int32_t> &shifts = info.gemmlowp_output_stage().gemmlowp_shifts;
+ const bool is_asm_supported = info.gemmlowp_output_stage().gemmlowp_shift >= 0
+ && std::all_of(shifts.cbegin(), shifts.cend(), [](int32_t val)
{
- const float fmultipler = a_qinfo.scale * s / output_qinfo.scale;
- if(fmultipler > 1.f)
- {
- run_optimised_requantized = false;
- break;
- }
+ return val >= 0;
+ });
+
+ if(is_asm_supported)
+ {
+ run_optimised = bool(NEGEMMAssemblyDispatch::validate(a_to_use, b, c, output, gemm_info));
+ run_optimised_requantized = run_optimised;
}
}
else
@@ -429,6 +437,9 @@
{
if(!run_optimised)
{
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.reinterpret_input_as_3d(), "NEGEMMLowpMatrixMultiplyKernel cannot reinterpret the input tensor as 3D");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.depth_output_gemm3d() != 0, "NEGEMMLowpMatrixMultiplyKernel cannot reinterpret the output tensor as 3D");
+
ARM_COMPUTE_RETURN_ON_ERROR(NEGEMMLowpMatrixMultiplyKernel::validate(matrix_a_info, matrix_b_info, &mm_result_s32_info));
}
@@ -445,6 +456,9 @@
{
if(!run_optimised)
{
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.reinterpret_input_as_3d(), "NEGEMMLowpMatrixMultiplyKernel cannot reinterpret the input tensor as 3D");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.depth_output_gemm3d() != 0, "NEGEMMLowpMatrixMultiplyKernel cannot reinterpret the output tensor as 3D");
+
ARM_COMPUTE_RETURN_ON_ERROR(NEGEMMLowpMatrixMultiplyKernel::validate(matrix_a_info, matrix_b_info, output));
}
// Validate offset contribution kernel