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authorPablo Marquez Tello <pablo.tello@arm.com>2023-09-08 14:56:01 +0100
committerPablo Marquez Tello <pablo.tello@arm.com>2023-09-13 09:02:51 +0000
commitcf219a4be6e9e9637193b5c9aa4f1eedd0a23900 (patch)
treed0f82767492d8f24bdf6a2641576210e48a37cd7 /src/cpu/kernels/crop/generic/neon/impl.h
parent3912f47b5849c2c7c4e68ff922869decf22fe303 (diff)
downloadComputeLibrary-cf219a4be6e9e9637193b5c9aa4f1eedd0a23900.tar.gz
Changes in NECropResize 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 * fp16.cpp needs to use the template in_bounds_crop_window so it had to be moved from impl.cpp to impl.h * Removed the file src/cpu/kernels/crop/generic/neon/impl.cpp * Partially resolves MLCE-1102 Change-Id: I1953849153e672ff7938f54c877c7498117dcca4 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10282 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>
Diffstat (limited to 'src/cpu/kernels/crop/generic/neon/impl.h')
-rw-r--r--src/cpu/kernels/crop/generic/neon/impl.h74
1 files changed, 72 insertions, 2 deletions
diff --git a/src/cpu/kernels/crop/generic/neon/impl.h b/src/cpu/kernels/crop/generic/neon/impl.h
index 50f889705a..a59588be45 100644
--- a/src/cpu/kernels/crop/generic/neon/impl.h
+++ b/src/cpu/kernels/crop/generic/neon/impl.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2021 Arm Limited.
+ * Copyright (c) 2018-2021, 2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -28,6 +28,7 @@
#include "arm_compute/core/TensorInfo.h"
#include "src/core/NEON/wrapper/wrapper.h"
#include "src/core/common/Registrars.h"
+#include "src/cpu/kernels/crop/generic/neon/crop_helper.h"
namespace arm_compute
{
@@ -35,7 +36,76 @@ namespace cpu
{
template <typename T>
void in_bounds_crop_window(const ITensor *input, const ITensor *output, float *output_ptr, Coordinates input_offset,
- int32_t window_step_x, int32_t output_width_start, int32_t output_width_limit, bool input_has_single_channel, bool is_width_flipped);
+ int32_t window_step_x, int32_t output_width_start, int32_t output_width_limit, bool input_has_single_channel, bool is_width_flipped)
+{
+ // Reverse elements if width flipped.
+ if(is_width_flipped)
+ {
+ // Collapse first dimension if possible.
+ if(input_has_single_channel)
+ {
+ int32_t x = output_width_start;
+ Coordinates negative_offset(input_offset);
+ negative_offset.set(1, negative_offset[1] - window_step_x + 1);
+ for(; x <= output_width_limit - window_step_x; x += window_step_x, negative_offset[1] -= window_step_x)
+ {
+ auto in = load_as_f32(reinterpret_cast<T *>(input->ptr_to_element(negative_offset)));
+
+ in = wrapper::vrev64(in);
+ in = wrapper::vcombine(wrapper::vgethigh(in), wrapper::vgetlow(in));
+
+ wrapper::vstore(output_ptr + x, in);
+ }
+ input_offset[1] = negative_offset[1] + window_step_x - 1;
+ for(; x < output_width_limit; ++x, --input_offset[1])
+ {
+ *(output_ptr + x) = static_cast<float>(*reinterpret_cast<T *>(input->ptr_to_element(input_offset)));
+ }
+ }
+ else
+ {
+ for(int32_t x = output_width_start; x < output_width_limit; ++x, --input_offset[1])
+ {
+ input_offset.set(0, 0);
+ int32_t c = 0;
+ for(; c <= static_cast<int32_t>(input->info()->dimension(0)) - window_step_x; c += window_step_x, input_offset[0] += window_step_x)
+ {
+ auto in = load_as_f32(reinterpret_cast<T *>(input->ptr_to_element(input_offset)));
+ wrapper::vstore(output_ptr + x * output->info()->dimension(0) + c, in);
+ }
+ for(; c < static_cast<int32_t>(input->info()->dimension(0)); ++c, ++input_offset[0])
+ {
+ *(output_ptr + x * output->info()->dimension(0) + c) = static_cast<float>(*reinterpret_cast<T *>(input->ptr_to_element(input_offset)));
+ }
+ }
+ }
+ }
+ else
+ {
+ // Use memcpy if the elements don't need converting to float.
+ if(std::is_same<T, float>::value)
+ {
+ memcpy(static_cast<void *>(output_ptr + output_width_start * output->info()->dimension(0)),
+ reinterpret_cast<const void *>(input->ptr_to_element(input_offset)),
+ (output_width_limit - output_width_start) * output->info()->dimension(0) * output->info()->element_size());
+ }
+ else
+ {
+ int32_t x = 0;
+ int32_t limit = (output_width_limit - output_width_start) * static_cast<int32_t>(output->info()->dimension(0));
+ float *output_start_ptr = output_ptr + output_width_start * output->info()->dimension(0);
+ for(; x <= limit - window_step_x; x += window_step_x, input_offset[0] += window_step_x)
+ {
+ auto in = load_as_f32(reinterpret_cast<T *>(input->ptr_to_element(input_offset)));
+ wrapper::vstore(output_start_ptr + x, in);
+ }
+ for(; x < limit; ++x, ++input_offset[0])
+ {
+ *(output_start_ptr + x) = static_cast<float>(*reinterpret_cast<T *>(input->ptr_to_element(input_offset)));
+ }
+ }
+ }
+}
} // namespace cpu
} // namespace arm_compute
#endif //SRC_CORE_NEON_KERNELS_CROP_IMPL_H