commit b91e34c9837756c9ee45917e13fb6a6cb901f795
author Michalis Spyrou <michalis.spyrou@arm.com> Wed Dec 20 15:50:55 2017 +0000
committer Anthony Barbier <anthony.barbier@arm.com> Fri Nov 02 16:42:33 2018 +0000
tree 6f5dd4c2ec527f2a188ac940a081206810ec4d44
parent aa1209a1bfc9fa24a24c1b47d309e27ba2cd90a7

COMPMID-746 Allow NEDirectConvolution to work without biases for QS.

Renamed BiasAccumulateKernel to OutputStage. If no bias is provided
when the input is quantized, the kernel simply downscales the input.
Throw error if no bias is provided and input is floating point.

Change-Id: I645a4ee9c6014b0547778fdd92c9ec72ef2f0aab
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/114158
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>

src/runtime/NEON/functions/NEDirectConvolutionLayer.cpp

diff --git a/src/runtime/NEON/functions/NEDirectConvolutionLayer.cpp b/src/runtime/NEON/functions/NEDirectConvolutionLayer.cpp
index ef5d987..c26c99a 100644
--- a/src/runtime/NEON/functions/NEDirectConvolutionLayer.cpp
+++ b/src/runtime/NEON/functions/NEDirectConvolutionLayer.cpp
@@ -34,7 +34,7 @@
 using namespace arm_compute;
 
 NEDirectConvolutionLayer::NEDirectConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager)
-    : _memory_group(std::move(memory_manager)), _accumulate_bias_kernel(), _conv_kernel(), _input_border_handler(), _accumulator(), _has_bias(false)
+    : _memory_group(std::move(memory_manager)), _output_stage_kernel(), _conv_kernel(), _input_border_handler(), _accumulator(), _has_bias(false), _is_fixed_point(false)
 {
 }
 
@@ -50,17 +50,16 @@
     _has_bias = (bias != nullptr);
 
     // Allocate the intermediate accumulator tensor in case of fixed point input
-    if(is_data_type_fixed_point(input->info()->data_type()))
+    _is_fixed_point = is_data_type_fixed_point(input->info()->data_type());
+    if(_is_fixed_point)
     {
         const DataType promoted_dt = (input->info()->data_type() == DataType::QS8) ? DataType::QS16 : DataType::QS32;
         _accumulator.allocator()->init(TensorInfo(output->info()->tensor_shape(), 1, promoted_dt, output->info()->fixed_point_position()));
         _memory_group.manage(&_accumulator);
         _conv_kernel.configure(input, weights, &_accumulator, conv_info);
-        // TODO (COMPMID-746): Fix accumulate biases to just down-cast when no bias is provided
-        if(_has_bias)
-        {
-            _accumulate_bias_kernel.configure(&_accumulator, bias, output);
-        }
+
+        // When no bias is provided, we need to downscale the accumulator tensor
+        _output_stage_kernel.configure(&_accumulator, bias, output);
         _accumulator.allocator()->allocate();
     }
     else
@@ -68,7 +67,7 @@
         _conv_kernel.configure(input, weights, output, conv_info);
         if(_has_bias)
         {
-            _accumulate_bias_kernel.configure(output, bias);
+            _output_stage_kernel.configure(output, bias);
         }
     }
 
@@ -91,20 +90,17 @@
     // Validate Convolution kernel
     ARM_COMPUTE_RETURN_ON_ERROR(NEDirectConvolutionLayerKernel::validate(input, weights, &accumulator, conv_info));
 
-    // Validate bias
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG((bias == nullptr) && is_data_type_fixed_point(data_type),
-                                    "Biases should be provided for fixed point inputs");
     if(bias != nullptr)
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(weights, bias);
         ARM_COMPUTE_RETURN_ERROR_ON_MSG(bias->dimension(0) != weights->dimension(3),
                                         "Biases size and number of input feature maps should match");
         ARM_COMPUTE_RETURN_ERROR_ON_MSG(bias->num_dimensions() > 1, "Biases should be one dimensional");
-
-        // Validate bias kernel
-        ARM_COMPUTE_RETURN_ON_ERROR(NEDirectConvolutionLayerBiasAccumulateKernel::validate(&accumulator, bias, output));
     }
 
+    // Validate bias kernel
+    ARM_COMPUTE_RETURN_ON_ERROR(NEDirectConvolutionLayerOutputStageKernel::validate(&accumulator, bias, output));
+
     return Status{};
 }
 
@@ -115,10 +111,9 @@
     _memory_group.acquire();
 
     NEScheduler::get().schedule(&_conv_kernel, Window::DimZ);
-    if(_has_bias)
+    if(_has_bias || _is_fixed_point)
     {
-        NEScheduler::get().schedule(&_accumulate_bias_kernel, Window::DimY);
+        NEScheduler::get().schedule(&_output_stage_kernel, Window::DimY);
     }
-
     _memory_group.release();
 }