Changes to BoundingBoxTransform to enable fp16 in armv8a multi_isa builds

* Code guarded with __ARM_FEATURE_FP16_VECTOR_ARITHMETIC needs
  to be moved to an fp16.cpp file to allow compilation with
  -march=armv8.2-a+fp16

* Partially resolves MLCE-1102

Change-Id: I04822b043d9f87bc666750a8d95a8be8a6cc194d
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10239
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

2 files changed, 53 insertions, 62 deletions

diff --git a/src/cpu/kernels/boundingboxtransform/generic/neon/impl.cpp b/src/cpu/kernels/boundingboxtransform/generic/neon/impl.cpp
index d74a8a712d..b3ffd0a676 100644
--- a/src/cpu/kernels/boundingboxtransform/generic/neon/impl.cpp
+++ b/src/cpu/kernels/boundingboxtransform/generic/neon/impl.cpp
@@ -85,65 +85,5 @@ void bounding_box_transform_qsymm16(const ITensor *boxes, ITensor *pred_boxes, c
     },
     box_it);
 }
-
-template <typename T>
-void bounding_box_transform(const ITensor *boxes, ITensor *pred_boxes, const ITensor *deltas, BoundingBoxTransformInfo bbinfo, const Window &window)
-{
-    const size_t num_classes  = deltas->info()->tensor_shape()[0] >> 2;
-    const size_t deltas_width = deltas->info()->tensor_shape()[0];
-    const int    img_h        = std::floor(bbinfo.img_height() / bbinfo.scale() + 0.5f);
-    const int    img_w        = std::floor(bbinfo.img_width() / bbinfo.scale() + 0.5f);
-
-    const auto scale_after  = (bbinfo.apply_scale() ? T(bbinfo.scale()) : T(1));
-    const auto scale_before = T(bbinfo.scale());
-    ARM_COMPUTE_ERROR_ON(scale_before <= 0);
-    const auto offset = (bbinfo.correct_transform_coords() ? T(1.f) : T(0.f));
-
-    auto pred_ptr  = reinterpret_cast<T *>(pred_boxes->buffer() + pred_boxes->info()->offset_first_element_in_bytes());
-    auto delta_ptr = reinterpret_cast<T *>(deltas->buffer() + deltas->info()->offset_first_element_in_bytes());
-
-    Iterator box_it(boxes, window);
-    execute_window_loop(window, [&](const Coordinates & id)
-    {
-        const auto ptr    = reinterpret_cast<T *>(box_it.ptr());
-        const auto b0     = *ptr;
-        const auto b1     = *(ptr + 1);
-        const auto b2     = *(ptr + 2);
-        const auto b3     = *(ptr + 3);
-        const T    width  = (b2 / scale_before) - (b0 / scale_before) + T(1.f);
-        const T    height = (b3 / scale_before) - (b1 / scale_before) + T(1.f);
-        const T    ctr_x  = (b0 / scale_before) + T(0.5f) * width;
-        const T    ctr_y  = (b1 / scale_before) + T(0.5f) * height;
-        for(size_t j = 0; j < num_classes; ++j)
-        {
-            // Extract deltas
-            const size_t delta_id = id.y() * deltas_width + 4u * j;
-            const T      dx       = delta_ptr[delta_id] / T(bbinfo.weights()[0]);
-            const T      dy       = delta_ptr[delta_id + 1] / T(bbinfo.weights()[1]);
-            T            dw       = delta_ptr[delta_id + 2] / T(bbinfo.weights()[2]);
-            T            dh       = delta_ptr[delta_id + 3] / T(bbinfo.weights()[3]);
-            // Clip dw and dh
-            dw = std::min(dw, T(bbinfo.bbox_xform_clip()));
-            dh = std::min(dh, T(bbinfo.bbox_xform_clip()));
-            // Determine the predictions
-            const T pred_ctr_x = dx * width + ctr_x;
-            const T pred_ctr_y = dy * height + ctr_y;
-            const T pred_w     = std::exp(dw) * width;
-            const T pred_h     = std::exp(dh) * height;
-            // Store the prediction into the output tensor
-            pred_ptr[delta_id]     = scale_after * utility::clamp<T>(pred_ctr_x - T(0.5f) * pred_w, T(0), T(img_w - 1));
-            pred_ptr[delta_id + 1] = scale_after * utility::clamp<T>(pred_ctr_y - T(0.5f) * pred_h, T(0), T(img_h - 1));
-            pred_ptr[delta_id + 2] = scale_after * utility::clamp<T>(pred_ctr_x + T(0.5f) * pred_w - offset, T(0), T(img_w - 1));
-            pred_ptr[delta_id + 3] = scale_after * utility::clamp<T>(pred_ctr_y + T(0.5f) * pred_h - offset, T(0), T(img_h - 1));
-        }
-    },
-    box_it);
-}
-
-template void bounding_box_transform<float>(const ITensor *boxes, ITensor *pred_boxes, const ITensor *deltas, BoundingBoxTransformInfo bbinfo, const Window &window);
-
-#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS)
-template void bounding_box_transform<float16_t>(const ITensor *boxes, ITensor *pred_boxes, const ITensor *deltas, BoundingBoxTransformInfo bbinfo, const Window &window);
-#endif //defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS)
 } // namespace cpu
 } // namespace arm_compute
diff --git a/src/cpu/kernels/boundingboxtransform/generic/neon/impl.h b/src/cpu/kernels/boundingboxtransform/generic/neon/impl.h
index d9ff694ae5..7f990396df 100644
--- a/src/cpu/kernels/boundingboxtransform/generic/neon/impl.h
+++ b/src/cpu/kernels/boundingboxtransform/generic/neon/impl.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2022 Arm Limited.
+ * Copyright (c) 2022-2023 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -30,7 +30,58 @@ namespace arm_compute
 namespace cpu
 {
 template <typename T>
-void bounding_box_transform(const ITensor *boxes, ITensor *pred_boxes, const ITensor *deltas, BoundingBoxTransformInfo bbinfo, const Window &window);
+void bounding_box_transform(const ITensor *boxes, ITensor *pred_boxes, const ITensor *deltas, BoundingBoxTransformInfo bbinfo, const Window &window)
+{
+    const size_t num_classes  = deltas->info()->tensor_shape()[0] >> 2;
+    const size_t deltas_width = deltas->info()->tensor_shape()[0];
+    const int    img_h        = std::floor(bbinfo.img_height() / bbinfo.scale() + 0.5f);
+    const int    img_w        = std::floor(bbinfo.img_width() / bbinfo.scale() + 0.5f);
+
+    const auto scale_after  = (bbinfo.apply_scale() ? T(bbinfo.scale()) : T(1));
+    const auto scale_before = T(bbinfo.scale());
+    ARM_COMPUTE_ERROR_ON(scale_before <= 0);
+    const auto offset = (bbinfo.correct_transform_coords() ? T(1.f) : T(0.f));
+
+    auto pred_ptr  = reinterpret_cast<T *>(pred_boxes->buffer() + pred_boxes->info()->offset_first_element_in_bytes());
+    auto delta_ptr = reinterpret_cast<T *>(deltas->buffer() + deltas->info()->offset_first_element_in_bytes());
+
+    Iterator box_it(boxes, window);
+    execute_window_loop(window, [&](const Coordinates & id)
+    {
+        const auto ptr    = reinterpret_cast<T *>(box_it.ptr());
+        const auto b0     = *ptr;
+        const auto b1     = *(ptr + 1);
+        const auto b2     = *(ptr + 2);
+        const auto b3     = *(ptr + 3);
+        const T    width  = (b2 / scale_before) - (b0 / scale_before) + T(1.f);
+        const T    height = (b3 / scale_before) - (b1 / scale_before) + T(1.f);
+        const T    ctr_x  = (b0 / scale_before) + T(0.5f) * width;
+        const T    ctr_y  = (b1 / scale_before) + T(0.5f) * height;
+        for(size_t j = 0; j < num_classes; ++j)
+        {
+            // Extract deltas
+            const size_t delta_id = id.y() * deltas_width + 4u * j;
+            const T      dx       = delta_ptr[delta_id] / T(bbinfo.weights()[0]);
+            const T      dy       = delta_ptr[delta_id + 1] / T(bbinfo.weights()[1]);
+            T            dw       = delta_ptr[delta_id + 2] / T(bbinfo.weights()[2]);
+            T            dh       = delta_ptr[delta_id + 3] / T(bbinfo.weights()[3]);
+            // Clip dw and dh
+            dw = std::min(dw, T(bbinfo.bbox_xform_clip()));
+            dh = std::min(dh, T(bbinfo.bbox_xform_clip()));
+            // Determine the predictions
+            const T pred_ctr_x = dx * width + ctr_x;
+            const T pred_ctr_y = dy * height + ctr_y;
+            const T pred_w     = std::exp(dw) * width;
+            const T pred_h     = std::exp(dh) * height;
+            // Store the prediction into the output tensor
+            pred_ptr[delta_id]     = scale_after * utility::clamp<T>(pred_ctr_x - T(0.5f) * pred_w, T(0), T(img_w - 1));
+            pred_ptr[delta_id + 1] = scale_after * utility::clamp<T>(pred_ctr_y - T(0.5f) * pred_h, T(0), T(img_h - 1));
+            pred_ptr[delta_id + 2] = scale_after * utility::clamp<T>(pred_ctr_x + T(0.5f) * pred_w - offset, T(0), T(img_w - 1));
+            pred_ptr[delta_id + 3] = scale_after * utility::clamp<T>(pred_ctr_y + T(0.5f) * pred_h - offset, T(0), T(img_h - 1));
+        }
+    },
+    box_it);
+}
 
 void bounding_box_transform_qsymm16(const ITensor *boxes, ITensor *pred_boxes, const ITensor *deltas, BoundingBoxTransformInfo bbinfo, const Window &window);
 } // namespace cpu