COMPMID-2769: Add support for QASYMM8_SIGNED in NEFullyConnectedLayer

Change-Id: I4c35c522375ae5a5de78716e079ebb9ffad15956
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2581
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

2 files changed, 108 insertions, 6 deletions

diff --git a/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp b/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
index 4c264e4832..92ccd5d1cc 100644
--- a/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
+++ b/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
@@ -141,9 +141,8 @@ void NEFullyConnectedLayer::configure_fc_fc(const ITensor *input, const ITensor
 void NEFullyConnectedLayer::configure(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output,
                                       FullyConnectedLayerInfo fc_info)
 {
-    ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
-
     // Perform validate step
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
     ARM_COMPUTE_ERROR_THROW_ON(NEFullyConnectedLayer::validate(input->info(),
                                                                weights->info(),
                                                                biases != nullptr ? biases->info() : nullptr,
@@ -260,7 +259,13 @@ void NEFullyConnectedLayer::configure(const ITensor *input, const ITensor *weigh
         int32_t output_multiplier;
         int32_t output_shift;
         quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift);
-        _gemmlowp_output_stage.configure(&_gemmlowp_output, biases, output, output_multiplier, output_shift, oq_info.offset);
+
+        GEMMLowpOutputStageInfo gemmlowp_output_stage_info;
+        gemmlowp_output_stage_info.gemmlowp_multiplier = output_multiplier;
+        gemmlowp_output_stage_info.gemmlowp_shift      = output_shift;
+        gemmlowp_output_stage_info.gemmlowp_offset     = oq_info.offset;
+        gemmlowp_output_stage_info.type                = GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT;
+        _gemmlowp_output_stage.configure(&_gemmlowp_output, biases, output, gemmlowp_output_stage_info);
         _gemmlowp_output.allocator()->allocate();
     }
 
@@ -272,7 +277,7 @@ Status NEFullyConnectedLayer::validate(const ITensorInfo *input, const ITensorIn
 {
     ARM_COMPUTE_UNUSED(fc_info.retain_internal_weights);
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output);
-    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights, output);
     ARM_COMPUTE_RETURN_ERROR_ON(weights->num_dimensions() > 2);
 
@@ -361,7 +366,13 @@ Status NEFullyConnectedLayer::validate(const ITensorInfo *input, const ITensorIn
         int32_t output_multiplier;
         int32_t output_shift;
         ARM_COMPUTE_RETURN_ON_ERROR(quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift));
-        ARM_COMPUTE_RETURN_ON_ERROR(NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::validate(&gemmlowp_output, biases, output));
+
+        GEMMLowpOutputStageInfo gemmlowp_output_stage_info;
+        gemmlowp_output_stage_info.gemmlowp_multiplier = output_multiplier;
+        gemmlowp_output_stage_info.gemmlowp_shift      = output_shift;
+        gemmlowp_output_stage_info.gemmlowp_offset     = oq_info.offset;
+        gemmlowp_output_stage_info.type                = GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT;
+        ARM_COMPUTE_RETURN_ON_ERROR(NEGEMMLowpOutputStage::validate(&gemmlowp_output, biases, output, gemmlowp_output_stage_info));
     }
 
     return Status{};
diff --git a/src/runtime/NEON/functions/NEGEMMLowpOutputStage.cpp b/src/runtime/NEON/functions/NEGEMMLowpOutputStage.cpp
index 3ef9351b78..465dddaac2 100644
--- a/src/runtime/NEON/functions/NEGEMMLowpOutputStage.cpp
+++ b/src/runtime/NEON/functions/NEGEMMLowpOutputStage.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -28,6 +28,7 @@
 #include "arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h"
 #include "arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.h"
 #include "arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h"
+#include "arm_compute/core/Validate.h"
 #include "support/ToolchainSupport.h"
 
 namespace arm_compute
@@ -81,4 +82,94 @@ Status NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint::validate(const ITens
 {
     return NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::validate(input, bias, output, min, max);
 }
+
+void NEGEMMLowpOutputStage::configure(const ITensor *input, const ITensor *bias, ITensor *output, const GEMMLowpOutputStageInfo &info)
+{
+    // Perform validate step
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+    ARM_COMPUTE_ERROR_THROW_ON(NEGEMMLowpOutputStage::validate(input->info(), bias != nullptr ? bias->info() : nullptr, output->info(), info));
+
+    if(info.type == GEMMLowpOutputStageType::QUANTIZE_DOWN)
+    {
+        switch(output->info()->data_type())
+        {
+            case DataType::QASYMM8:
+            {
+                auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel>();
+                k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_offset, info.gemmlowp_min_bound, info.gemmlowp_max_bound);
+                _kernel = std::move(k);
+                break;
+            }
+            default:
+                ARM_COMPUTE_ERROR("Unsupported output data type.");
+        }
+    }
+    else if(info.type == GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT)
+    {
+        switch(output->info()->data_type())
+        {
+            case DataType::QASYMM8:
+            {
+                auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel>();
+                k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_offset, info.gemmlowp_min_bound, info.gemmlowp_max_bound);
+                _kernel = std::move(k);
+                break;
+            }
+            case DataType::QASYMM8_SIGNED:
+            {
+                auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel>();
+                k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_offset, info.gemmlowp_min_bound, info.gemmlowp_max_bound);
+                _kernel = std::move(k);
+                break;
+            }
+            case DataType::QSYMM16:
+            {
+                auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel>();
+                k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_min_bound, info.gemmlowp_max_bound);
+                _kernel = std::move(k);
+                break;
+            }
+            default:
+                ARM_COMPUTE_ERROR("Unsupported output data type.");
+        }
+    }
+    else
+    {
+        ARM_COMPUTE_ERROR("Unsupported output stage quantization type.");
+    }
+}
+
+Status NEGEMMLowpOutputStage::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo &info)
+{
+    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::UNKNOWN, "NEGEMMLowpQuantizeDownScaleByFixedPoint cannot be used with UNKNOWN output data type.");
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM16);
+
+    ARM_COMPUTE_RETURN_ERROR_ON((info.type != GEMMLowpOutputStageType::QUANTIZE_DOWN) && (info.type != GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT));
+
+    if(info.type == GEMMLowpOutputStageType::QUANTIZE_DOWN)
+    {
+        switch(output->data_type())
+        {
+            case DataType::QASYMM8:
+                return NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound);
+            default:
+                return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported output data type.");
+        }
+    }
+    else
+    {
+        switch(output->data_type())
+        {
+            case DataType::QASYMM8:
+                return NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound);
+            case DataType::QASYMM8_SIGNED:
+                return NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound);
+            case DataType::QSYMM16:
+                return NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound);
+            default:
+                return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported output data type.");
+        }
+    }
+}
 } // namespace arm_compute