COMPMID-2980 (Nightly) armv7a build failures

Change-Id: I8c2a20fc345694d1ad6e0fe63e4f22fb73e6c1df
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2463
Tested-by: Arm Jenkins <bsgcomp@arm.com>

5 files changed, 28 insertions, 26 deletions

diff --git a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp
index 5e47dd56ae..ca4fe732a7 100644
--- a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp
+++ b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp
@@ -202,9 +202,9 @@ void NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayerOptimizedInternal::
         const UniformQuantizationInfo wq_info = weights->info()->quantization_info().uniform();
         const UniformQuantizationInfo oq_info = (output->info()->total_size() == 0) ? iq_info : output->info()->quantization_info().uniform();
 
-        float multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale;
-        int   output_multiplier;
-        int   output_shift;
+        float   multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale;
+        int32_t output_multiplier;
+        int32_t output_shift;
         quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift);
         _output_stage_kernel.configure(&_accumulator, biases, _is_nchw ? output : &_permuted_output, output_multiplier, output_shift, oq_info.offset);
         _accumulator.allocator()->allocate();
diff --git a/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp b/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
index ee622f4699..b3b90f8599 100644
--- a/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
+++ b/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
@@ -255,9 +255,9 @@ void NEFullyConnectedLayer::configure(const ITensor *input, const ITensor *weigh
         const UniformQuantizationInfo wq_info = weights->info()->quantization_info().uniform();
         const UniformQuantizationInfo oq_info = output->info()->quantization_info().uniform();
 
-        float multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale;
-        int   output_multiplier;
-        int   output_shift;
+        float   multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale;
+        int32_t output_multiplier;
+        int32_t output_shift;
         quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift);
         _gemmlowp_output_stage.configure(&_gemmlowp_output, biases, output, output_multiplier, output_shift, oq_info.offset);
         _gemmlowp_output.allocator()->allocate();
diff --git a/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp b/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp
index bb9620b293..0507c6b2bd 100644
--- a/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp
+++ b/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp
@@ -33,7 +33,8 @@
 #include <set>
 #include <tuple>
 
-using namespace arm_compute;
+namespace arm_compute
+{
 using namespace arm_compute::misc::shape_calculator;
 
 NEConvolutionLayerReshapeWeights::NEConvolutionLayerReshapeWeights()
@@ -131,11 +132,11 @@ void NEGEMMConvolutionLayer::configure_mm(const ITensor *input, const ITensor *w
         }
 
         // Merge activation with output stage
-        PixelValue type_min = 0;
-        PixelValue type_max = 0;
+        PixelValue type_min{};
+        PixelValue type_max{};
         std::tie(type_min, type_max) = get_min_max(data_type);
-        int min_activation = type_min.get<int>();
-        int max_activation = type_max.get<int>();
+        int32_t min_activation = type_min.get<int32_t>();
+        int32_t max_activation = type_max.get<int32_t>();
 
         if(supported_acts.count(act_info.activation()) != 0)
         {
@@ -190,11 +191,11 @@ Status NEGEMMConvolutionLayer::validate_mm(const ITensorInfo *input, const ITens
         const UniformQuantizationInfo uoqinfo = oqinfo.uniform();
 
         // Merge activation with output stage
-        PixelValue type_min = 0;
-        PixelValue type_max = 0;
+        PixelValue type_min{};
+        PixelValue type_max{};
         std::tie(type_min, type_max) = get_min_max(data_type);
-        int min_activation = type_min.get<int>();
-        int max_activation = type_max.get<int>();
+        int32_t min_activation = type_min.get<int32_t>();
+        int32_t max_activation = type_max.get<int32_t>();
 
         const std::set<ActivationLayerInfo::ActivationFunction> supported_acts = { ActivationLayerInfo::ActivationFunction::RELU,
                                                                                    ActivationLayerInfo::ActivationFunction::BOUNDED_RELU,
@@ -595,3 +596,4 @@ void NEGEMMConvolutionLayer::prepare()
         _is_prepared = true;
     }
 }
+} // namespace arm_compute
diff --git a/src/runtime/NEON/functions/NELSTMLayerQuantized.cpp b/src/runtime/NEON/functions/NELSTMLayerQuantized.cpp
index cfd996b538..cdfc035400 100644
--- a/src/runtime/NEON/functions/NELSTMLayerQuantized.cpp
+++ b/src/runtime/NEON/functions/NELSTMLayerQuantized.cpp
@@ -136,8 +136,8 @@ void NELSTMLayerQuantized::configure(const ITensor *input,
     _output_lowp.allocator()->init(TensorInfo(_output_highp.info()->tensor_shape(), 1, DataType::QSYMM16, qsymm_3));
 
     const float multiplier        = 4096.f * qasymm.uniform().scale * qweights.uniform().scale;
-    int         output_multiplier = 0;
-    int         output_shift      = 0;
+    int32_t     output_multiplier = 0;
+    int32_t     output_shift      = 0;
     quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift);
 
     _memory_group.manage(&_output_lowp);
@@ -342,8 +342,8 @@ Status NELSTMLayerQuantized::validate(const ITensorInfo *input,
     const TensorInfo output_lowp(output_highp.tensor_shape(), 1, DataType::QSYMM16, qsymm_3);
 
     const float multiplier        = 4096.f * qasymm.uniform().scale * qweights.uniform().scale;
-    int         output_multiplier = 0;
-    int         output_shift      = 0;
+    int32_t     output_multiplier = 0;
+    int32_t     output_shift      = 0;
     ARM_COMPUTE_RETURN_ON_ERROR(quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift));
 
     // _output_stage
diff --git a/src/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.cpp b/src/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.cpp
index c564e22d46..3235eee19a 100644
--- a/src/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.cpp
+++ b/src/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.cpp
@@ -263,8 +263,8 @@ std::unique_ptr<depthwise::IDepthwiseConvolution> create_convolver(const ITensor
 
         // Calculate rescale parameters
         const float fmultipler  = iqinfo.scale * wqinfo.scale / oqinfo.scale;
-        int         qmultiplier = 0;
-        int         qshift      = 0;
+        int32_t     qmultiplier = 0;
+        int32_t     qshift      = 0;
         quantization::calculate_quantized_multiplier_less_than_one(fmultipler, &qmultiplier, &qshift);
         qasymm8::QAsymm8RescaleParams rescale_params(qshift, qmultiplier, fmultipler);
 
@@ -285,15 +285,15 @@ std::unique_ptr<depthwise::IDepthwiseConvolution> create_convolver(const ITensor
         const qasymm8::QAsymm8Params         oqinfo{ static_cast<uint8_t>(output_qinfo.offset), output_qinfo.scale };
 
         // Calculate rescale parameters
-        std::vector<float> fmultipliers;
-        std::vector<int>   qmultipliers;
-        std::vector<int>   qshifts;
+        std::vector<float>   fmultipliers;
+        std::vector<int32_t> qmultipliers;
+        std::vector<int32_t> qshifts;
 
         for(auto const s : wqinfo.scales)
         {
             const float fmultipler  = iqinfo.scale * s / oqinfo.scale;
-            int         qmultiplier = 0;
-            int         qshift      = 0;
+            int32_t     qmultiplier = 0;
+            int32_t     qshift      = 0;
             quantization::calculate_quantized_multiplier_less_than_one(fmultipler, &qmultiplier, &qshift);
             fmultipliers.push_back(fmultipler);
             qmultipliers.push_back(qmultiplier);