COMPMID-3375: Port NEActivationLayer functions/kernels to run on

different tensors.

Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: I98782bb73e9dc0899ffb1796aca6f99714adea94
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3343
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

10 files changed, 154 insertions, 92 deletions

diff --git a/src/core/NEON/kernels/NEActivationLayerKernel.cpp b/src/core/NEON/kernels/NEActivationLayerKernel.cpp
index ffbfd710f9..2c00a76305 100644
--- a/src/core/NEON/kernels/NEActivationLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEActivationLayerKernel.cpp
@@ -95,7 +95,7 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c
     return Status{};
 }
 
-std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
+std::pair<Status, Window> validate_and_configure_window(const ITensorInfo *input, ITensorInfo *output)
 {
     // Configure kernel window
     Window win = calculate_max_window(*input, Steps());
@@ -116,23 +116,15 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen
 } // namespace
 
 NEActivationLayerKernel::NEActivationLayerKernel()
-    : _input(nullptr), _output(nullptr), _func(nullptr), _act_info()
+    : _func(nullptr), _act_info()
 {
 }
 
-void NEActivationLayerKernel::configure(ITensor *input, ITensor *output, ActivationLayerInfo activation_info)
+void NEActivationLayerKernel::configure(const ITensorInfo *input, ITensorInfo *output, ActivationLayerInfo activation_info)
 {
-    ARM_COMPUTE_ERROR_ON_NULLPTR(input);
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
-    _input    = input;
     _act_info = activation_info;
-    _output   = input;
-
-    // Out-of-place calculation
-    if(output != nullptr)
-    {
-        _output = output;
-    }
 
     // Disabled activation, thus no operation needed
     if(!activation_info.enabled())
@@ -140,7 +132,7 @@ void NEActivationLayerKernel::configure(ITensor *input, ITensor *output, Activat
         _func = nullptr;
     }
 
-    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (output != nullptr) ? output->info() : nullptr, activation_info));
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input, output, activation_info));
 
     // Activation functions : FP32
     static std::map<ActivationFunction, ActivationFunctionExecutorPtr> act_map_f32 =
@@ -218,7 +210,7 @@ void NEActivationLayerKernel::configure(ITensor *input, ITensor *output, Activat
 
     };
 
-    switch(input->info()->data_type())
+    switch(input->data_type())
     {
         case DataType::QASYMM8_SIGNED:
             _func = act_map_qasymm8_signed[activation_info.activation()];
@@ -242,14 +234,14 @@ void NEActivationLayerKernel::configure(ITensor *input, ITensor *output, Activat
     }
 
     // Configure kernel window
-    auto win_config = validate_and_configure_window(input->info(), (output != nullptr) ? output->info() : nullptr);
+    auto win_config = validate_and_configure_window(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
     ICPPKernel::configure(win_config.second);
 }
 
 template <ActivationLayerInfo::ActivationFunction F, typename T>
 typename std::enable_if<arm_compute::utils::traits::is_floating_point<T>::value, void>::type
-NEActivationLayerKernel::activation(const Window &window)
+NEActivationLayerKernel::activation(const ITensor *src, ITensor *dst, const Window &window)
 {
     /** NEON vector tag type. */
     using ExactTagType = typename wrapper::traits::neon_bitvector_tag_t<T, wrapper::traits::BitWidth::W128>;
@@ -262,16 +254,16 @@ NEActivationLayerKernel::activation(const Window &window)
     Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
     win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
 
-    Iterator input(_input, win_collapsed);
-    Iterator output(_output, win_collapsed);
+    Iterator input(src, win_collapsed);
+    Iterator output(dst, win_collapsed);
 
     // A small delta added to the input to prevent NAN values caused by zeros in inputs to SQRT
 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-    const auto delta = wrapper::vdup_n(static_cast<T>(1e-7), ExactTagType{});
+    const auto delta = wrapper::vdup_n(static_cast<T>(1e-7), ExactTagType {});
 #else  /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
-    const auto delta = wrapper::vdup_n(static_cast<T>(1e-24), ExactTagType{});
+    const auto delta = wrapper::vdup_n(static_cast<T>(1e-24), ExactTagType {});
 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
-    const auto const_1     = wrapper::vdup_n(static_cast<T>(1.f), ExactTagType{});
+    const auto const_1     = wrapper::vdup_n(static_cast<T>(1.f), ExactTagType {});
     const auto const_0     = wrapper::vdup_n(static_cast<T>(0.f), ExactTagType{});
     const auto const_6     = wrapper::vdup_n(static_cast<T>(6.f), ExactTagType{});
     const auto const_3     = wrapper::vdup_n(static_cast<T>(3.f), ExactTagType{});
@@ -402,7 +394,7 @@ NEActivationLayerKernel::activation(const Window &window)
 }
 
 template <ActivationLayerInfo::ActivationFunction F, typename T>
-typename std::enable_if<std::is_same<T, qasymm8_t>::value, void>::type NEActivationLayerKernel::activation(const Window &window)
+typename std::enable_if<std::is_same<T, qasymm8_t>::value, void>::type NEActivationLayerKernel::activation(const ITensor *src, ITensor *dst, const Window &window)
 {
     const int                window_step_x  = 16 / sizeof(T);
     const auto               window_start_x = static_cast<int>(window.x().start());
@@ -412,11 +404,11 @@ typename std::enable_if<std::is_same<T, qasymm8_t>::value, void>::type NEActivat
     Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
     win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
 
-    Iterator input(_input, win_collapsed);
-    Iterator output(_output, win_collapsed);
+    Iterator input(src, win_collapsed);
+    Iterator output(dst, win_collapsed);
 
-    const UniformQuantizationInfo qi_in           = _input->info()->quantization_info().uniform();
-    const UniformQuantizationInfo qi_out          = _output->info()->quantization_info().uniform();
+    const UniformQuantizationInfo qi_in           = src->info()->quantization_info().uniform();
+    const UniformQuantizationInfo qi_out          = dst->info()->quantization_info().uniform();
     const qasymm8x16_t            va              = vdupq_n_u8(quantize_qasymm8(_act_info.a(), qi_in));
     const qasymm8x16_t            vb              = vdupq_n_u8(quantize_qasymm8(_act_info.b(), qi_in));
     const qasymm8_t               a               = quantize_qasymm8(_act_info.a(), qi_in);
@@ -579,7 +571,7 @@ typename std::enable_if<std::is_same<T, qasymm8_t>::value, void>::type NEActivat
 }
 
 template <ActivationLayerInfo::ActivationFunction F, typename T>
-typename std::enable_if<std::is_same<T, qasymm8_signed_t>::value, void>::type NEActivationLayerKernel::activation(const Window &window)
+typename std::enable_if<std::is_same<T, qasymm8_signed_t>::value, void>::type NEActivationLayerKernel::activation(const ITensor *src, ITensor *dst, const Window &window)
 {
     const int                window_step_x  = 16 / sizeof(T);
     const auto               window_start_x = static_cast<int>(window.x().start());
@@ -589,11 +581,11 @@ typename std::enable_if<std::is_same<T, qasymm8_signed_t>::value, void>::type NE
     Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
     win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
 
-    Iterator input(_input, win_collapsed);
-    Iterator output(_output, win_collapsed);
+    Iterator input(src, win_collapsed);
+    Iterator output(dst, win_collapsed);
 
-    const UniformQuantizationInfo qi_in           = _input->info()->quantization_info().uniform();
-    const UniformQuantizationInfo qi_out          = _output->info()->quantization_info().uniform();
+    const UniformQuantizationInfo qi_in           = src->info()->quantization_info().uniform();
+    const UniformQuantizationInfo qi_out          = dst->info()->quantization_info().uniform();
     const qasymm8x16_signed_t     va              = vdupq_n_s8(quantize_qasymm8_signed(_act_info.a(), qi_in));
     const qasymm8x16_signed_t     vb              = vdupq_n_s8(quantize_qasymm8_signed(_act_info.b(), qi_in));
     const qasymm8_signed_t        a               = quantize_qasymm8_signed(_act_info.a(), qi_in);
@@ -756,7 +748,7 @@ typename std::enable_if<std::is_same<T, qasymm8_signed_t>::value, void>::type NE
 }
 
 template <ActivationLayerInfo::ActivationFunction F, typename T>
-typename std::enable_if<std::is_same<T, qsymm16_t>::value, void>::type NEActivationLayerKernel::activation(const Window &window)
+typename std::enable_if<std::is_same<T, qsymm16_t>::value, void>::type NEActivationLayerKernel::activation(const ITensor *src, ITensor *dst, const Window &window)
 {
     const int                window_step_x  = 16 / sizeof(T);
     const auto               window_start_x = static_cast<int>(window.x().start());
@@ -766,11 +758,11 @@ typename std::enable_if<std::is_same<T, qsymm16_t>::value, void>::type NEActivat
     Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
     win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
 
-    Iterator input(_input, win_collapsed);
-    Iterator output(_output, win_collapsed);
+    Iterator input(src, win_collapsed);
+    Iterator output(dst, win_collapsed);
 
-    const UniformQuantizationInfo qi_in    = _input->info()->quantization_info().uniform();
-    const UniformQuantizationInfo qi_out   = _output->info()->quantization_info().uniform();
+    const UniformQuantizationInfo qi_in    = src->info()->quantization_info().uniform();
+    const UniformQuantizationInfo qi_out   = dst->info()->quantization_info().uniform();
     const auto                    vconst_1 = vdupq_n_f32(1.f);
     const float32x4_t             va_f32   = vdupq_n_f32(_act_info.a());
     const float32x4_t             vb_f32   = vdupq_n_f32(_act_info.b());
@@ -863,7 +855,9 @@ Status NEActivationLayerKernel::validate(const ITensorInfo *input, const ITensor
     return Status{};
 }
 
-void NEActivationLayerKernel::run(const Window &window, const ThreadInfo &info)
+void NEActivationLayerKernel::run_op(const std::vector<InputTensor> &inputs,
+                                     const std::vector<OutputTensor> &outputs,
+                                     const Window &window, const ThreadInfo &info)
 {
     // Early exit on disabled activation
     if(!_act_info.enabled())
@@ -876,5 +870,7 @@ void NEActivationLayerKernel::run(const Window &window, const ThreadInfo &info)
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
     ARM_COMPUTE_ERROR_ON(_func == nullptr);
 
-    (this->*_func)(window);
+    ARM_COMPUTE_ERROR_ON(inputs.empty() || outputs.empty());
+
+    (this->*_func)(inputs[0].tensor, outputs[0].tensor, window);
 }
diff --git a/src/core/NEON/kernels/NEReshapeLayerKernel.cpp b/src/core/NEON/kernels/NEReshapeLayerKernel.cpp
index 600f8f9bf1..c141eecf75 100644
--- a/src/core/NEON/kernels/NEReshapeLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEReshapeLayerKernel.cpp
@@ -86,29 +86,32 @@ void NEReshapeLayerKernel::configure(const ITensorInfo *input, ITensorInfo *outp
     INEKernel::configure(win);
 }
 
-void NEReshapeLayerKernel::run_op(const std::vector<InputOperatorTensors *> &inputs, std::vector<OutputOperatorTensors *> &outputs, const Window &window, const ThreadInfo &info)
+void NEReshapeLayerKernel::run_op(const std::vector<InputTensor> &inputs, const std::vector<OutputTensor> &outputs, const Window &window, const ThreadInfo &info)
 {
     ARM_COMPUTE_UNUSED(info);
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
 
-    switch(inputs[0]->second->info()->data_type())
+    const auto src = inputs[0].tensor;
+    auto       dst = outputs[0].tensor;
+
+    switch(src->info()->data_type())
     {
         case DataType::U8:
         case DataType::S8:
         case DataType::QASYMM8:
         case DataType::QASYMM8_SIGNED:
-            reshape_tensor<uint8_t>(window, inputs[0]->second, outputs[0]->second);
+            reshape_tensor<uint8_t>(window, src, dst);
             break;
         case DataType::U16:
         case DataType::S16:
         case DataType::F16:
-            reshape_tensor<uint16_t>(window, inputs[0]->second, outputs[0]->second);
+            reshape_tensor<uint16_t>(window, src, dst);
             break;
         case DataType::U32:
         case DataType::S32:
         case DataType::F32:
-            reshape_tensor<uint32_t>(window, inputs[0]->second, outputs[0]->second);
+            reshape_tensor<uint32_t>(window, src, dst);
             break;
         default:
             ARM_COMPUTE_ERROR("Unsupported data type!");
diff --git a/src/runtime/CPP/CPPScheduler.cpp b/src/runtime/CPP/CPPScheduler.cpp
index db551590ea..41e1a2d647 100644
--- a/src/runtime/CPP/CPPScheduler.cpp
+++ b/src/runtime/CPP/CPPScheduler.cpp
@@ -363,7 +363,7 @@ void CPPScheduler::run_workloads(std::vector<IScheduler::Workload> &workloads)
 }
 #endif /* DOXYGEN_SKIP_THIS */
 
-void CPPScheduler::schedule_common(ICPPKernel *kernel, const Hints &hints, std::vector<InputOperatorTensors *> &inputs, std::vector<OutputOperatorTensors *> &outputs)
+void CPPScheduler::schedule_common(ICPPKernel *kernel, const Hints &hints, const std::vector<InputTensor> &inputs, const std::vector<OutputTensor> &outputs)
 {
     ARM_COMPUTE_ERROR_ON_MSG(!kernel, "The child class didn't set the kernel");
 
@@ -473,15 +473,15 @@ void CPPScheduler::schedule_common(ICPPKernel *kernel, const Hints &hints, std::
     }
 }
 
-void CPPScheduler::schedule_op(ICPPKernel *kernel, const Hints &hints, std::vector<InputOperatorTensors *> &inputs, std::vector<OutputOperatorTensors *> &outputs)
+void CPPScheduler::schedule_op(ICPPKernel *kernel, const Hints &hints, const std::vector<InputTensor> &inputs, const std::vector<OutputTensor> &outputs)
 {
     schedule_common(kernel, hints, inputs, outputs);
 }
 
 void CPPScheduler::schedule(ICPPKernel *kernel, const Hints &hints)
 {
-    std::vector<InputOperatorTensors *>  inputs;
-    std::vector<OutputOperatorTensors *> outputs;
+    const std::vector<InputTensor> inputs;
+    std::vector<OutputTensor>      outputs;
     schedule_common(kernel, hints, inputs, outputs);
 }
 } // namespace arm_compute
diff --git a/src/runtime/CPP/SingleThreadScheduler.cpp b/src/runtime/CPP/SingleThreadScheduler.cpp
index 777f84bec8..8257628090 100644
--- a/src/runtime/CPP/SingleThreadScheduler.cpp
+++ b/src/runtime/CPP/SingleThreadScheduler.cpp
@@ -49,7 +49,7 @@ void SingleThreadScheduler::schedule(ICPPKernel *kernel, const Hints &hints)
     kernel->run(kernel->window(), info);
 }
 
-void SingleThreadScheduler::schedule_op(ICPPKernel *kernel, const Hints &hints, std::vector<InputOperatorTensors *> &inputs, std::vector<OutputOperatorTensors *> &outputs)
+void SingleThreadScheduler::schedule_op(ICPPKernel *kernel, const Hints &hints, const std::vector<InputTensor> &inputs, const std::vector<OutputTensor> &outputs)
 {
     ARM_COMPUTE_UNUSED(hints);
     ThreadInfo info;
diff --git a/src/runtime/NEON/INEOperator.cpp b/src/runtime/NEON/INEOperator.cpp
index c24d5c47f1..78790856ee 100644
--- a/src/runtime/NEON/INEOperator.cpp
+++ b/src/runtime/NEON/INEOperator.cpp
@@ -33,7 +33,7 @@ INEOperator::INEOperator(IRuntimeContext *ctx)
 {
 }
 
-void INEOperator::run(std::vector<InputOperatorTensors *> &inputs, std::vector<OutputOperatorTensors *> &outputs, std::vector<OperatorTensors *> &workspace)
+void INEOperator::run(std::vector<InputTensor> inputs, std::vector<OutputTensor> outputs, std::vector<OperatorTensor> workspace)
 {
     ARM_COMPUTE_UNUSED(workspace);
 
@@ -45,7 +45,7 @@ void INEOperator::run(std::vector<InputOperatorTensors *> &inputs, std::vector<O
     NEScheduler::get().schedule_op(_kernel.get(), Window::DimY, inputs, outputs);
 }
 
-void INEOperator::prepare(std::vector<OperatorTensors *> constants)
+void INEOperator::prepare(std::vector<OperatorTensor> constants)
 {
     ARM_COMPUTE_UNUSED(constants);
 }
diff --git a/src/runtime/NEON/functions/NEActivationLayer.cpp b/src/runtime/NEON/functions/NEActivationLayer.cpp
index e4d1125c79..889ff6b1f4 100644
--- a/src/runtime/NEON/functions/NEActivationLayer.cpp
+++ b/src/runtime/NEON/functions/NEActivationLayer.cpp
@@ -23,25 +23,76 @@
  */
 #include "arm_compute/runtime/NEON/functions/NEActivationLayer.h"
 
+#include "arm_compute/core/Error.h"
 #include "arm_compute/core/NEON/kernels/NEActivationLayerKernel.h"
+#include "arm_compute/core/experimental/Types.h"
 #include "arm_compute/runtime/IRuntimeContext.h"
+#include "arm_compute/runtime/Tensor.h"
 #include "support/MemorySupport.h"
 
 namespace arm_compute
 {
-NEActivationLayer::NEActivationLayer(IRuntimeContext *ctx) // NOLINT
-    : INESimpleFunctionNoBorder(ctx)
+namespace experimental
 {
-}
-void NEActivationLayer::configure(ITensor *input, ITensor *output, ActivationLayerInfo activation_info)
+void NEActivationLayer::configure(const ITensorInfo *input, ITensorInfo *output, const ActivationLayerInfo &activation_info)
 {
     auto k = arm_compute::support::cpp14::make_unique<NEActivationLayerKernel>();
     k->configure(input, output, activation_info);
     _kernel = std::move(k);
 }
 
+Status NEActivationLayer::validate(const ITensorInfo *input, const ITensorInfo *output, const ActivationLayerInfo &activation_info)
+{
+    return NEActivationLayerKernel::validate(input, output, activation_info);
+}
+
+MemoryRequirements NEActivationLayer::workspace() const
+{
+    return MemoryRequirements{};
+}
+} // namespace experimental
+
+struct NEActivationLayer::Impl
+{
+    const ITensor                                   *src{ nullptr };
+    ITensor                                         *dst{ nullptr };
+    IRuntimeContext                                 *ctx{ nullptr };
+    std::unique_ptr<experimental::NEActivationLayer> op{ nullptr };
+};
+
+NEActivationLayer::NEActivationLayer(IRuntimeContext *ctx)
+    : _impl(support::cpp14::make_unique<Impl>())
+{
+    _impl->ctx = ctx;
+}
+
+NEActivationLayer::NEActivationLayer(NEActivationLayer &&) = default;
+
+NEActivationLayer &NEActivationLayer::operator=(NEActivationLayer &&) = default;
+
+NEActivationLayer::~NEActivationLayer() = default;
+
+void NEActivationLayer::configure(ITensor *input, ITensor *output, ActivationLayerInfo activation_info)
+{
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input);
+
+    _impl->src = input;
+    _impl->dst = output == nullptr ? input : output;
+
+    _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEActivationLayer>();
+    _impl->op->configure(_impl->src->info(), _impl->dst->info(), activation_info);
+}
+
 Status NEActivationLayer::validate(const ITensorInfo *input, const ITensorInfo *output, const ActivationLayerInfo &act_info)
 {
-    return NEActivationLayerKernel::validate(input, output, act_info);
+    return experimental::NEActivationLayer::validate(input, output, act_info);
+}
+
+void NEActivationLayer::run()
+{
+    const InputTensor src{ TensorType::ACL_SRC, _impl->src };
+    OutputTensor      dst{ TensorType::ACL_DST, _impl->dst };
+
+    _impl->op->run({ src }, { dst }, {});
 }
 } // namespace arm_compute
diff --git a/src/runtime/NEON/functions/NELSTMLayer.cpp b/src/runtime/NEON/functions/NELSTMLayer.cpp
index f9d445fe71..0a111363e3 100644
--- a/src/runtime/NEON/functions/NELSTMLayer.cpp
+++ b/src/runtime/NEON/functions/NELSTMLayer.cpp
@@ -474,7 +474,7 @@ Status NELSTMLayer::validate(const ITensorInfo *input,
                                                                               RoundingPolicy::TO_ZERO));
         ARM_COMPUTE_RETURN_ON_ERROR(NEArithmeticAddition::validate(&forget_gate, forget_gate_bias, &forget_gate, ConvertPolicy::SATURATE));
     }
-    ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayerKernel::validate(&forget_gate, &forget_gate, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC)));
+    ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayer::validate(&forget_gate, &forget_gate, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC)));
 
     // Validate input gate
     if(!lstm_params.has_cifg_opt())
@@ -508,7 +508,7 @@ Status NELSTMLayer::validate(const ITensorInfo *input,
             ARM_COMPUTE_RETURN_ON_ERROR(NEPixelWiseMultiplicationKernel::validate(&input_gate, lstm_params.input_layer_norm_weights(), &input_gate, 1, ConvertPolicy::SATURATE, RoundingPolicy::TO_ZERO));
             ARM_COMPUTE_RETURN_ON_ERROR(NEArithmeticAddition::validate(&input_gate, lstm_params.input_gate_bias(), &input_gate, ConvertPolicy::SATURATE));
         }
-        ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayerKernel::validate(&input_gate, nullptr, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC)));
+        ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayer::validate(&input_gate, nullptr, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC)));
     }
     else
     {
@@ -526,14 +526,14 @@ Status NELSTMLayer::validate(const ITensorInfo *input,
                                                                               RoundingPolicy::TO_ZERO));
         ARM_COMPUTE_RETURN_ON_ERROR(NEArithmeticAddition::validate(&cell_state_tmp, cell_bias, &cell_state_tmp, ConvertPolicy::SATURATE));
     }
-    ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayerKernel::validate(&cell_state_tmp, nullptr, activation_info));
+    ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayer::validate(&cell_state_tmp, nullptr, activation_info));
     ARM_COMPUTE_RETURN_ON_ERROR(NEPixelWiseMultiplicationKernel::validate(&cell_state_tmp, &input_gate, &cell_state_tmp, 1, ConvertPolicy::SATURATE, RoundingPolicy::TO_ZERO));
     ARM_COMPUTE_RETURN_ON_ERROR(NEPixelWiseMultiplicationKernel::validate(&cell_state_tmp, &forget_gate, &cell_state_tmp, 1, ConvertPolicy::SATURATE, RoundingPolicy::TO_ZERO));
     ARM_COMPUTE_RETURN_ON_ERROR(NEArithmeticAddition::validate(&cell_state_tmp, &cell_state_tmp, &cell_state_tmp, ConvertPolicy::SATURATE));
     if(cell_threshold != 0.f)
     {
-        ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayerKernel::validate(&cell_state_tmp, nullptr, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, -cell_threshold,
-                                                                                                                    cell_threshold)));
+        ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayer::validate(&cell_state_tmp, nullptr, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, -cell_threshold,
+                                                                                                              cell_threshold)));
     }
 
     // Validate output gate tmp
@@ -559,18 +559,18 @@ Status NELSTMLayer::validate(const ITensorInfo *input,
                                                                               RoundingPolicy::TO_ZERO));
         ARM_COMPUTE_RETURN_ON_ERROR(NEArithmeticAddition::validate(&output_gate_tmp, output_gate_bias, &output_gate_tmp, ConvertPolicy::SATURATE));
     }
-    ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayerKernel::validate(&output_gate_tmp, nullptr, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC)));
+    ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayer::validate(&output_gate_tmp, nullptr, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC)));
 
     // Validate output state
-    ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayerKernel::validate(&cell_state_tmp, &cell_state_tmp, activation_info));
+    ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayer::validate(&cell_state_tmp, &cell_state_tmp, activation_info));
     ARM_COMPUTE_RETURN_ON_ERROR(NEPixelWiseMultiplicationKernel::validate(&cell_state_tmp, &output_gate_tmp, &output_gate_tmp, 1, ConvertPolicy::SATURATE, RoundingPolicy::TO_ZERO));
     if(lstm_params.has_projection())
     {
         ARM_COMPUTE_RETURN_ON_ERROR(NEFullyConnectedLayer::validate(&output_gate_tmp, lstm_params.projection_weights(), lstm_params.projection_bias(), output_state_out));
         if(projection_threshold != 0.f)
         {
-            ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayerKernel::validate(output_state_out, output_state_out,
-                                                                          ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, -projection_threshold, projection_threshold)));
+            ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayer::validate(output_state_out, output_state_out,
+                                                                    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, -projection_threshold, projection_threshold)));
         }
     }
 
@@ -612,7 +612,7 @@ void NELSTMLayer::run()
         NEScheduler::get().schedule(&_pixelwise_mul_forget_gate_coeff, Window::DimY);
         NEScheduler::get().schedule(&_accum_forget_gate_bias, Window::DimY);
     }
-    NEScheduler::get().schedule(&_activation_forget_gate, Window::DimY);
+    _activation_forget_gate.run();
 
     if(_run_cifg_opt)
     {
@@ -642,7 +642,7 @@ void NELSTMLayer::run()
             NEScheduler::get().schedule(&_pixelwise_mul_input_gate_coeff, Window::DimY);
             NEScheduler::get().schedule(&_accum_input_gate_bias, Window::DimY);
         }
-        NEScheduler::get().schedule(&_activation_input_gate, Window::DimY);
+        _activation_input_gate.run();
     }
 
     _fully_connected_cell_state.run();
@@ -655,14 +655,14 @@ void NELSTMLayer::run()
         NEScheduler::get().schedule(&_pixelwise_mul_cell_gate_coeff, Window::DimY);
         NEScheduler::get().schedule(&_accum_cell_gate_bias, Window::DimY);
     }
-    NEScheduler::get().schedule(&_activation_cell_state, Window::DimY);
+    _activation_cell_state.run();
     NEScheduler::get().schedule(&_pixelwise_mul_cell_state1, Window::DimY);
     NEScheduler::get().schedule(&_pixelwise_mul_cell_state2, Window::DimY);
     NEScheduler::get().schedule(&_accum_cell_state2, Window::DimY);
 
     if(_perform_cell_clipping)
     {
-        NEScheduler::get().schedule(&_cell_clip, Window::DimY);
+        _cell_clip.run();
     }
 
     _fully_connected_output.run();
@@ -677,9 +677,9 @@ void NELSTMLayer::run()
         NEScheduler::get().schedule(&_pixelwise_mul_output_gate_coeff, Window::DimY);
         NEScheduler::get().schedule(&_accum_output_gate_bias, Window::DimY);
     }
-    NEScheduler::get().schedule(&_activation_output, Window::DimY);
+    _activation_output.run();
 
-    NEScheduler::get().schedule(&_activation_output_state, Window::DimY);
+    _activation_output_state.run();
     NEScheduler::get().schedule(&_pixelwise_mul_output_state2, Window::DimY);
 
     if(_has_projection_weights)
@@ -687,7 +687,7 @@ void NELSTMLayer::run()
         _fully_connected_output_state.run();
         if(_perform_projection_clipping)
         {
-            NEScheduler::get().schedule(&_projection_clip, Window::DimY);
+            _projection_clip.run();
         }
     }
 
diff --git a/src/runtime/NEON/functions/NERNNLayer.cpp b/src/runtime/NEON/functions/NERNNLayer.cpp
index 154b060c3d..4a15777be9 100644
--- a/src/runtime/NEON/functions/NERNNLayer.cpp
+++ b/src/runtime/NEON/functions/NERNNLayer.cpp
@@ -34,8 +34,8 @@
 namespace arm_compute
 {
 NERNNLayer::NERNNLayer(std::shared_ptr<IMemoryManager> memory_manager)
-    : _memory_group(std::move(memory_manager)), _gemm_state_f(), _add_kernel(), _activation_kernel(), _fully_connected(memory_manager), _copy_kernel(), _fully_connected_out(), _gemm_output(),
-      _add_output(), _is_prepared(false)
+    : _memory_group(std::move(memory_manager)), _gemm_state_f(), _add_kernel(), _activation(), _fully_connected(memory_manager), _copy_kernel(), _fully_connected_out(), _gemm_output(), _add_output(),
+      _is_prepared(false)
 {
 }
 
@@ -60,7 +60,7 @@ Status NERNNLayer::validate(const ITensorInfo *input, const ITensorInfo *weights
 
     ARM_COMPUTE_RETURN_ON_ERROR(NEFullyConnectedLayer::validate(input, weights, bias, &shape_info));
     ARM_COMPUTE_RETURN_ON_ERROR(NEArithmeticAdditionKernel::validate(&shape_info, &shape_info, &shape_info, ConvertPolicy::SATURATE));
-    ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayerKernel::validate(&shape_info, &shape_info, info));
+    ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayer::validate(&shape_info, &shape_info, info));
 
     return Status{};
 }
@@ -95,7 +95,7 @@ void NERNNLayer::configure(const ITensor *input, const ITensor *weights, const I
     _fully_connected_out.allocator()->allocate();
     _gemm_output.allocator()->allocate();
 
-    _activation_kernel.configure(&_add_output, hidden_state, info);
+    _activation.configure(&_add_output, hidden_state, info);
     _add_output.allocator()->allocate();
 
     _copy_kernel.configure(hidden_state, output);
@@ -112,7 +112,7 @@ void NERNNLayer::run()
     _gemm_state_f.run();
 
     NEScheduler::get().schedule(&_add_kernel, Window::DimY);
-    NEScheduler::get().schedule(&_activation_kernel, Window::DimY);
+    _activation.run();
 
     // copy hidden out to output
     NEScheduler::get().schedule(&_copy_kernel, Window::DimY);
diff --git a/src/runtime/NEON/functions/NEReshapeLayer.cpp b/src/runtime/NEON/functions/NEReshapeLayer.cpp
index 680abef026..daf358e7db 100644
--- a/src/runtime/NEON/functions/NEReshapeLayer.cpp
+++ b/src/runtime/NEON/functions/NEReshapeLayer.cpp
@@ -44,7 +44,7 @@ void NEReshapeLayer::configure(const ITensorInfo *input, ITensorInfo *output)
 
 Status NEReshapeLayer::validate(const ITensorInfo *input, const ITensorInfo *output)
 {
-    return arm_compute::NEReshapeLayer::validate(input, output);
+    return arm_compute::NEReshapeLayerKernel::validate(input, output);
 }
 
 MemoryRequirements NEReshapeLayer::workspace() const
@@ -53,32 +53,44 @@ MemoryRequirements NEReshapeLayer::workspace() const
 }
 } // namespace experimental
 
-void NEReshapeLayer::configure(const ITensor *input, ITensor *output)
+struct NEReshapeLayer::Impl
 {
-    _input  = input;
-    _output = output;
+    const ITensor                                *src{ nullptr };
+    ITensor                                      *dst{ nullptr };
+    std::unique_ptr<experimental::NEReshapeLayer> op{ nullptr };
+};
 
-    auto k = arm_compute::support::cpp14::make_unique<NEReshapeLayerKernel>();
-    k->configure(input->info(), output->info());
-    _kernel = std::move(k);
+NEReshapeLayer::NEReshapeLayer()
+    : _impl(support::cpp14::make_unique<Impl>())
+{
+}
+
+NEReshapeLayer::NEReshapeLayer(NEReshapeLayer &&) = default;
+
+NEReshapeLayer &NEReshapeLayer::operator=(NEReshapeLayer &&) = default;
+
+NEReshapeLayer::~NEReshapeLayer() = default;
+
+void NEReshapeLayer::configure(const ITensor *input, ITensor *output)
+{
+    _impl->src = input;
+    _impl->dst = output;
+    _impl->op  = arm_compute::support::cpp14::make_unique<experimental::NEReshapeLayer>();
+    _impl->op->configure(input->info(), output->info());
 }
 
 Status NEReshapeLayer::validate(const ITensorInfo *input, const ITensorInfo *output)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
-    ARM_COMPUTE_RETURN_ON_ERROR(NEReshapeLayerKernel::validate(input, output));
+    ARM_COMPUTE_RETURN_ON_ERROR(experimental::NEReshapeLayer::validate(input, output));
 
     return Status{};
 }
 
 void NEReshapeLayer::run()
 {
-    InputOperatorTensors  src_0 = std::make_pair(TensorType::ACL_SRC, _input);
-    OutputOperatorTensors dst_0 = std::make_pair(TensorType::ACL_DST, _output);
-
-    std::vector<InputOperatorTensors *>  inputs  = { &src_0 };
-    std::vector<OutputOperatorTensors *> outputs = { &dst_0 };
-
-    NEScheduler::get().schedule_op(_kernel.get(), Window::DimY, inputs, outputs);
+    const InputTensor src{ TensorType::ACL_SRC, _impl->src };
+    OutputTensor      dst{ TensorType::ACL_DST, _impl->dst };
+    _impl->op->run({ src }, { dst }, {});
 }
 } // namespace arm_compute
diff --git a/src/runtime/OMP/OMPScheduler.cpp b/src/runtime/OMP/OMPScheduler.cpp
index a1851f03c3..6d6b285019 100644
--- a/src/runtime/OMP/OMPScheduler.cpp
+++ b/src/runtime/OMP/OMPScheduler.cpp
@@ -83,7 +83,7 @@ void OMPScheduler::schedule(ICPPKernel *kernel, const Hints &hints)
     }
 }
 
-void OMPScheduler::schedule_op(ICPPKernel *kernel, const Hints &hints, std::vector<InputOperatorTensors *> &inputs, std::vector<OutputOperatorTensors *> &outputs)
+void OMPScheduler::schedule_op(ICPPKernel *kernel, const Hints &hints, const std::vector<InputTensor> &inputs, const std::vector<OutputTensor> &outputs)
 {
     ARM_COMPUTE_ERROR_ON_MSG(!kernel, "The child class didn't set the kernel");
     ARM_COMPUTE_ERROR_ON_MSG(hints.strategy() == StrategyHint::DYNAMIC,