COMPMID-617 Add validation methods to Kernels

- NEActivationLayer
- NESoftmax
- NEDirectConvolutionLayer
- NENormalizationLayer
- NEPoolingLayer

Change-Id: Ib279f1c1b7f9247679b0d6593aed7393da8fe87b
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/111335
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

5 files changed, 64 insertions, 2 deletions

diff --git a/src/runtime/NEON/functions/NEActivationLayer.cpp b/src/runtime/NEON/functions/NEActivationLayer.cpp
index 57a1738f85..cdf1b54659 100644
--- a/src/runtime/NEON/functions/NEActivationLayer.cpp
+++ b/src/runtime/NEON/functions/NEActivationLayer.cpp
@@ -34,3 +34,8 @@ void NEActivationLayer::configure(ITensor *input, ITensor *output, ActivationLay
     k->configure(input, output, activation_info);
     _kernel = std::move(k);
 }
+
+Status NEActivationLayer::validate(const ITensorInfo *input, const ITensorInfo *output, const ActivationLayerInfo &act_info)
+{
+    return NEActivationLayerKernel::validate(input, output, act_info);
+}
diff --git a/src/runtime/NEON/functions/NEDirectConvolutionLayer.cpp b/src/runtime/NEON/functions/NEDirectConvolutionLayer.cpp
index 52a4cc158f..2eabe459a5 100644
--- a/src/runtime/NEON/functions/NEDirectConvolutionLayer.cpp
+++ b/src/runtime/NEON/functions/NEDirectConvolutionLayer.cpp
@@ -85,6 +85,30 @@ void NEDirectConvolutionLayer::configure(ITensor *input, const ITensor *weights,
     _input_border_handler.configure(input, _conv_kernel.border_size(), BorderMode::CONSTANT, PixelValue(static_cast<float>(0.f)));
 }
 
+Status NEDirectConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, const ITensorInfo *output, const PadStrideInfo &conv_info)
+{
+    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, bias, output);
+
+    DataType data_type = output->data_type();
+    if(is_data_type_fixed_point(data_type))
+    {
+        // Promote data type in case of fixed point
+        data_type = ((data_type == DataType::QS8) ? DataType::QS16 : DataType::QS32);
+    }
+    TensorInfo accumulator(output->clone()->set_is_resizable(true).reset_padding().set_data_type(data_type));
+
+    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");
+
+    ARM_COMPUTE_RETURN_ON_ERROR(NEDirectConvolutionLayerKernel::validate(input, weights, &accumulator, conv_info));
+    ARM_COMPUTE_RETURN_ON_ERROR(NEDirectConvolutionLayerBiasAccumulateKernel::validate(&accumulator, bias, output));
+
+    return Status{};
+}
+
 void NEDirectConvolutionLayer::run()
 {
     NEScheduler::get().schedule(&_input_border_handler, Window::DimZ);
diff --git a/src/runtime/NEON/functions/NENormalizationLayer.cpp b/src/runtime/NEON/functions/NENormalizationLayer.cpp
index da4314b5ed..af98ac1f17 100644
--- a/src/runtime/NEON/functions/NENormalizationLayer.cpp
+++ b/src/runtime/NEON/functions/NENormalizationLayer.cpp
@@ -39,7 +39,7 @@ NENormalizationLayer::NENormalizationLayer(std::shared_ptr<IMemoryManager> memor
 
 void NENormalizationLayer::configure(const ITensor *input, ITensor *output, const NormalizationLayerInfo &norm_info)
 {
-    ARM_COMPUTE_ERROR_ON(input == nullptr);
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     TensorInfo tensor_info(input->info()->tensor_shape(), 1, input->info()->data_type(), input->info()->fixed_point_position());
     _input_squared.allocator()->init(tensor_info);
@@ -56,6 +56,17 @@ void NENormalizationLayer::configure(const ITensor *input, ITensor *output, cons
     _input_squared.allocator()->allocate();
 }
 
+Status NENormalizationLayer::validate(const ITensorInfo *input, const ITensorInfo *output, const NormalizationLayerInfo &norm_info)
+{
+    // Perform validation step
+    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
+
+    ARM_COMPUTE_RETURN_ON_ERROR(NENormalizationLayerKernel::validate(input, input, output, norm_info));
+    ARM_COMPUTE_RETURN_ON_ERROR(NEPixelWiseMultiplicationKernel::validate(input, input, output, 1.0f, ConvertPolicy::SATURATE, RoundingPolicy::TO_ZERO));
+
+    return Status{};
+}
+
 void NENormalizationLayer::run()
 {
     _memory_group.acquire();
diff --git a/src/runtime/NEON/functions/NEPoolingLayer.cpp b/src/runtime/NEON/functions/NEPoolingLayer.cpp
index f8a85b9897..530c7fca4a 100644
--- a/src/runtime/NEON/functions/NEPoolingLayer.cpp
+++ b/src/runtime/NEON/functions/NEPoolingLayer.cpp
@@ -48,6 +48,11 @@ void NEPoolingLayer::configure(ITensor *input, ITensor *output, const PoolingLay
     _border_handler.configure(input, _pooling_layer_kernel.border_size(), border_mode, PixelValue(static_cast<float>(0.f)));
 }
 
+Status NEPoolingLayer::validate(const ITensorInfo *input, const ITensorInfo *output, const PoolingLayerInfo &pool_info)
+{
+    return NEPoolingLayerKernel::validate(input, output, pool_info);
+}
+
 void NEPoolingLayer::run()
 {
     // Fill border
diff --git a/src/runtime/NEON/functions/NESoftmaxLayer.cpp b/src/runtime/NEON/functions/NESoftmaxLayer.cpp
index 84ecfdaf33..8e6773c5b1 100644
--- a/src/runtime/NEON/functions/NESoftmaxLayer.cpp
+++ b/src/runtime/NEON/functions/NESoftmaxLayer.cpp
@@ -38,7 +38,7 @@ NESoftmaxLayer::NESoftmaxLayer(std::shared_ptr<IMemoryManager> memory_manager)
 
 void NESoftmaxLayer::configure(ITensor *input, ITensor *output, float beta)
 {
-    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     // Create intermediate tensors shapes
     TensorInfo tensor_info_tmp(input->info()->tensor_shape(), input->info()->num_channels(), input->info()->data_type(), input->info()->fixed_point_position());
@@ -67,6 +67,23 @@ void NESoftmaxLayer::configure(ITensor *input, ITensor *output, float beta)
     _sum.allocator()->allocate();
 }
 
+Status NESoftmaxLayer::validate(const ITensorInfo *input, const ITensorInfo *output, float beta)
+{
+    // Perform validation step
+    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
+
+    TensorShape max_sum_shape = input->tensor_shape();
+    max_sum_shape.set(0, 1);
+
+    TensorInfo tensor_info_max_sum(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(max_sum_shape));
+
+    ARM_COMPUTE_RETURN_ON_ERROR(NELogits1DMaxKernel::validate(input, &tensor_info_max_sum));
+    ARM_COMPUTE_RETURN_ON_ERROR(NELogits1DShiftExpSumKernel::validate(input, &tensor_info_max_sum, input, &tensor_info_max_sum, beta));
+    ARM_COMPUTE_RETURN_ON_ERROR(NELogits1DNormKernel::validate(input, &tensor_info_max_sum, output));
+
+    return Status{};
+}
+
 void NESoftmaxLayer::run()
 {
     _memory_group.acquire();