COMPMID-1944 Add support for "reflect" padding mode in NEPad

Change-Id: I56c42524497d37d44708648571fa211ac1afbd98
Signed-off-by: Usama Arif <usama.arif@arm.com>
Reviewed-on: https://review.mlplatform.org/c/885
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez <pablo.tello@arm.com>

1 files changed, 231 insertions, 14 deletions

diff --git a/src/runtime/NEON/functions/NEPadLayer.cpp b/src/runtime/NEON/functions/NEPadLayer.cpp
index f5c2718cec..62a7d4559b 100644
--- a/src/runtime/NEON/functions/NEPadLayer.cpp
+++ b/src/runtime/NEON/functions/NEPadLayer.cpp
@@ -25,7 +25,6 @@
 
 #include "arm_compute/runtime/NEON/NEScheduler.h"
 
-#include "arm_compute/core/ITensor.h"
 #include "arm_compute/core/Types.h"
 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
 
@@ -61,18 +60,29 @@ Coordinates get_subtensor_coords(const PaddingList &paddings)
 
     return coords;
 }
+
+uint32_t last_padding_dimension(const PaddingList &padding)
+{
+    int last_padding_dim = padding.size() - 1;
+    for(; last_padding_dim >= 0; --last_padding_dim)
+    {
+        if(padding[last_padding_dim].first > 0 || padding[last_padding_dim].second > 0)
+        {
+            break;
+        }
+    }
+    return static_cast<uint32_t>(last_padding_dim);
+}
 } // namespace
 
 NEPadLayer::NEPadLayer()
-    : _memset_kernel(), _copy_kernel(), _output_subtensor()
+    : _copy_kernel(), _mode(), _padding(), _memset_kernel(), _num_dimensions(0), _slice_functions(nullptr), _concat_functions(nullptr), _slice_results(nullptr), _concat_results(nullptr),
+      _output_subtensor()
 {
 }
 
-void NEPadLayer::configure(ITensor *input, ITensor *output, const PaddingList &padding, PixelValue constant_value)
+void NEPadLayer::configure_constant_mode(ITensor *input, ITensor *output, const PaddingList &padding, const PixelValue constant_value)
 {
-    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
-    ARM_COMPUTE_THROW_ON_ERROR(NEPadLayer::validate(input->info(), output->info(), padding, constant_value));
-
     // Auto-init
     auto_init_if_empty(*output->info(), get_expected_output_tensorinfo(*input->info(), padding));
 
@@ -86,23 +96,230 @@ void NEPadLayer::configure(ITensor *input, ITensor *output, const PaddingList &p
     _copy_kernel.configure(input, &_output_subtensor);
 }
 
-Status NEPadLayer::validate(const ITensorInfo *input, const ITensorInfo *output, const PaddingList &padding, PixelValue constant_value)
+void NEPadLayer::configure_reflect_symmetric_mode(ITensor *input, ITensor *output)
+{
+    // Reflecting can be performed by effectively unfolding the input as follows:
+    // For each dimension starting at DimX:
+    //      For before and after:
+    //          Use strided slice to extract and reverse the part of the
+    //          input / previously produced tensor required for the padding.
+    //      Concatenate the before and after padding with the input / previously
+    //      produced tensor along the current dimension.
+
+    // Two strided slice functions will be required for each dimension padded as well as a
+    // concatenate function and the tensors to hold the temporary results.
+    _slice_functions  = arm_compute::support::cpp14::make_unique<NEStridedSlice[]>(2 * _num_dimensions);
+    _slice_results    = arm_compute::support::cpp14::make_unique<Tensor[]>(2 * _num_dimensions);
+    _concat_functions = arm_compute::support::cpp14::make_unique<NEConcatenateLayer[]>(_num_dimensions);
+    _concat_results   = arm_compute::support::cpp14::make_unique<Tensor[]>(_num_dimensions - 1);
+    Coordinates starts_before, ends_before, starts_after, ends_after, strides;
+    ITensor    *prev = input;
+    for(uint32_t i = 0; i < _num_dimensions; ++i)
+    {
+        // Values in strides from the previous dimensions need to be set to 1 to avoid reversing again.
+        if(i > 0)
+        {
+            strides.set(i - 1, 1);
+        }
+
+        if(_padding[i].first > 0 || _padding[i].second > 0)
+        {
+            // Set the starts, ends, and strides values for the current dimension.
+            // Due to the bit masks passed to strided slice, the values below the current dimension in
+            // starts and ends will be ignored so do not need to be modified.
+            if(_mode == PaddingMode::REFLECT)
+            {
+                starts_before.set(i, _padding[i].first);
+                ends_before.set(i, 0);
+                starts_after.set(i, input->info()->dimension(i) - 2);
+                ends_after.set(i, input->info()->dimension(i) - _padding[i].second - 2);
+                strides.set(i, -1);
+            }
+            else
+            {
+                starts_before.set(i, _padding[i].first - 1);
+                ends_before.set(i, -1);
+                starts_after.set(i, input->info()->dimension(i) - 1);
+                ends_after.set(i, input->info()->dimension(i) - _padding[i].second - 1);
+                strides.set(i, -1);
+            }
+
+            // Strided slice wraps negative indexes around to the end of the range,
+            // instead this should indicate use of the full range and so the bit mask will be modified.
+            const int32_t begin_mask_before = starts_before[i] < 0 ? ~0 : ~(1u << i);
+            const int32_t end_mask_before   = ends_before[i] < 0 ? ~0 : ~(1u << i);
+            const int32_t begin_mask_after  = starts_after[i] < 0 ? ~0 : ~(1u << i);
+            const int32_t end_mask_after    = ends_after[i] < 0 ? ~0 : ~(1u << i);
+
+            // Reflect the input values for the padding before and after the input.
+            std::vector<ITensor *> concat_vector;
+            if(_padding[i].first > 0)
+            {
+                if(i < prev->info()->num_dimensions())
+                {
+                    _slice_functions[2 * i].configure(prev, &_slice_results[2 * i], starts_before, ends_before, strides, begin_mask_before, end_mask_before);
+                    concat_vector.push_back(&_slice_results[2 * i]);
+                }
+                else
+                {
+                    // Performing the slice is unnecessary if the result would simply be a copy of the tensor.
+                    concat_vector.push_back(prev);
+                }
+            }
+            concat_vector.push_back(prev);
+            if(_padding[i].second > 0)
+            {
+                if(i < prev->info()->num_dimensions())
+                {
+                    _slice_functions[2 * i + 1].configure(prev, &_slice_results[2 * i + 1], starts_after, ends_after, strides, begin_mask_after, end_mask_after);
+                    concat_vector.push_back(&_slice_results[2 * i + 1]);
+                }
+                else
+                {
+                    // Performing the slice is unnecessary if the result would simply be a copy of the tensor.
+                    concat_vector.push_back(prev);
+                }
+            }
+            // Concatenate the padding before and after with the input.
+            ITensor *out = (i == _num_dimensions - 1) ? output : &_concat_results[i];
+            _concat_functions[i].configure(concat_vector, out, get_index_data_layout_dimension(input->info()->data_layout(), i));
+            if(i != _num_dimensions - 1)
+            {
+                _concat_results[i].allocator()->allocate();
+            }
+            prev = out;
+        }
+        _slice_results[2 * i].allocator()->allocate();
+        _slice_results[2 * i + 1].allocator()->allocate();
+    }
+}
+
+void NEPadLayer::configure(ITensor *input, ITensor *output, const PaddingList &padding, const PixelValue constant_value, const PaddingMode mode)
+{
+    ARM_COMPUTE_ERROR_THROW_ON(validate(input->info(), output->info(), padding, constant_value, mode));
+
+    _padding = padding;
+    _mode    = mode;
+
+    const TensorShape padded_shape = misc::shape_calculator::compute_padded_shape(input->info()->tensor_shape(), _padding);
+
+    auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(padded_shape));
+
+    // Find the last dimension requiring padding so that it is known when to write to output and whether any padding is applied.
+    _num_dimensions = last_padding_dimension(padding) + 1;
+    if(_num_dimensions > 0)
+    {
+        switch(_mode)
+        {
+            case PaddingMode::CONSTANT:
+            {
+                configure_constant_mode(input, output, padding, constant_value);
+                break;
+            }
+            case PaddingMode::REFLECT:
+            case PaddingMode::SYMMETRIC:
+            {
+                configure_reflect_symmetric_mode(input, output);
+                break;
+            }
+            default:
+                ARM_COMPUTE_ERROR("Padding mode not supported.");
+        }
+    }
+    else
+    {
+        // Copy the input to the whole output if no padding is applied
+        _copy_kernel.configure(input, output);
+    }
+}
+
+Status NEPadLayer::validate(const ITensorInfo *input, const ITensorInfo *output, const PaddingList &padding, const PixelValue constant_value, const PaddingMode mode)
 {
     ARM_COMPUTE_UNUSED(constant_value);
-    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
 
-    auto output_clone = output->clone();
+    const TensorShape padded_shape = misc::shape_calculator::compute_padded_shape(input->tensor_shape(), padding);
 
-    SubTensorInfo output_subtensor_info(output_clone.get(), input->tensor_shape(), get_subtensor_coords(padding), true);
-    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*input, *output_clone, padding));
-    ARM_COMPUTE_RETURN_ON_ERROR(NECopyKernel::validate(input, &output_subtensor_info));
+    if(output->total_size() > 0)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), padded_shape);
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+    }
 
+    switch(mode)
+    {
+        case PaddingMode::CONSTANT:
+        {
+            auto          output_clone = output->clone();
+            SubTensorInfo output_subtensor_info(output_clone.get(), input->tensor_shape(), get_subtensor_coords(padding), true);
+            ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*input, *output_clone, padding));
+            ARM_COMPUTE_RETURN_ON_ERROR(NECopyKernel::validate(input, &output_subtensor_info));
+            break;
+        }
+        case PaddingMode::REFLECT:
+        case PaddingMode::SYMMETRIC:
+        {
+            for(uint32_t i = 0; i < padding.size(); ++i)
+            {
+                if(mode == PaddingMode::REFLECT)
+                {
+                    ARM_COMPUTE_RETURN_ERROR_ON(padding[i].first >= input->dimension(i));
+                    ARM_COMPUTE_RETURN_ERROR_ON(padding[i].second >= input->dimension(i));
+                }
+                else
+                {
+                    ARM_COMPUTE_RETURN_ERROR_ON(padding[i].first > input->dimension(i));
+                    ARM_COMPUTE_RETURN_ERROR_ON(padding[i].second > input->dimension(i));
+                }
+            }
+            break;
+        }
+        default:
+        {
+            ARM_COMPUTE_ERROR("Invalid mode");
+        }
+    }
     return Status{};
 }
 
 void NEPadLayer::run()
 {
-    NEScheduler::get().schedule(&_memset_kernel, Window::DimY);
-    NEScheduler::get().schedule(&_copy_kernel, Window::DimY);
+    if(_num_dimensions > 0)
+    {
+        switch(_mode)
+        {
+            case PaddingMode::CONSTANT:
+            {
+                NEScheduler::get().schedule(&_memset_kernel, Window::DimY);
+                NEScheduler::get().schedule(&_copy_kernel, Window::DimY);
+                break;
+            }
+            case PaddingMode::REFLECT:
+            case PaddingMode::SYMMETRIC:
+            {
+                for(uint32_t i = 0; i < _num_dimensions; ++i)
+                {
+                    if(_padding[i].first > 0 || _padding[i].second > 0)
+                    {
+                        if(_padding[i].first > 0 && _slice_results[2 * i].info()->total_size() > 0)
+                        {
+                            _slice_functions[2 * i].run();
+                        }
+                        if(_padding[i].second > 0 && _slice_results[2 * i + 1].info()->total_size() > 0)
+                        {
+                            _slice_functions[2 * i + 1].run();
+                        }
+                        _concat_functions[i].run();
+                    }
+                }
+                break;
+            }
+            default:
+                ARM_COMPUTE_ERROR("Padding mode not supported.");
+        }
+    }
+    else
+    {
+        NEScheduler::get().schedule(&_copy_kernel, Window::DimY);
+    }
 }
 } // namespace arm_compute