Apply clang-format on repository
Code is formatted as per a revised clang format configuration
file(not part of this delivery). Version 14.0.6 is used.
Exclusion List:
- files with .cl extension
- files that are not strictly C/C++ (e.g. Android.bp, Sconscript ...)
And the following directories
- compute_kernel_writer/validation/
- tests/
- include/
- src/core/NEON/kernels/convolution/
- src/core/NEON/kernels/arm_gemm/
- src/core/NEON/kernels/arm_conv/
- data/
There will be a follow up for formatting of .cl files and the
files under tests/ and compute_kernel_writer/validation/.
Signed-off-by: Felix Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>
Change-Id: Ib7eb1fcf4e7537b9feaefcfc15098a804a3fde0a
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10391
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
diff --git a/src/cpu/kernels/meanstddevnorm/generic/neon/fp16.cpp b/src/cpu/kernels/meanstddevnorm/generic/neon/fp16.cpp
index 96e4030..6470f39 100644
--- a/src/cpu/kernels/meanstddevnorm/generic/neon/fp16.cpp
+++ b/src/cpu/kernels/meanstddevnorm/generic/neon/fp16.cpp
@@ -23,9 +23,9 @@
*/
#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS)
-#include "src/cpu/kernels/meanstddevnorm/generic/neon/impl.h"
#include "src/core/NEON/wrapper/wrapper.h"
#include "src/cpu/CpuTypes.h"
+#include "src/cpu/kernels/meanstddevnorm/generic/neon/impl.h"
namespace arm_compute
{
@@ -45,64 +45,66 @@
Iterator input_itr(input, win);
Iterator output_itr(output, win);
- execute_window_loop(win, [&](const Coordinates &)
- {
- int x = window_start_x;
- auto in_ptr = reinterpret_cast<const float16_t *>(input_itr.ptr());
- auto out_ptr = reinterpret_cast<float16_t *>(output_itr.ptr());
-
- float16x8_t sum_vec = vdupq_n_f16(static_cast<float16_t>(0.0f));
- float32x4_t sum_sq_vec = vdupq_n_f32(0.0f);
-
- for(; x <= (window_end_x - window_step_x); x += window_step_x)
+ execute_window_loop(
+ win,
+ [&](const Coordinates &)
{
- float16x8_t data = vld1q_f16(in_ptr + x);
- sum_vec = vaddq_f16(sum_vec, data);
- float32x4_t dl = vcvt_f32_f16(vget_low_f16(data));
- float32x4_t dh = vcvt_f32_f16(vget_high_f16(data));
- sum_sq_vec = vaddq_f32(sum_sq_vec, vmulq_f32(dl, dl));
- sum_sq_vec = vaddq_f32(sum_sq_vec, vmulq_f32(dh, dh));
- }
+ int x = window_start_x;
+ auto in_ptr = reinterpret_cast<const float16_t *>(input_itr.ptr());
+ auto out_ptr = reinterpret_cast<float16_t *>(output_itr.ptr());
- float16x4_t sum_carry_res = vpadd_f16(vget_high_f16(sum_vec), vget_low_f16(sum_vec));
- sum_carry_res = vpadd_f16(sum_carry_res, sum_carry_res);
- sum_carry_res = vpadd_f16(sum_carry_res, sum_carry_res);
+ float16x8_t sum_vec = vdupq_n_f16(static_cast<float16_t>(0.0f));
+ float32x4_t sum_sq_vec = vdupq_n_f32(0.0f);
- float32x4_t sum_sq_carry_res = vpaddq_f32(sum_sq_vec, sum_sq_vec);
- sum_sq_carry_res = vpaddq_f32(sum_sq_carry_res, sum_sq_carry_res);
+ for (; x <= (window_end_x - window_step_x); x += window_step_x)
+ {
+ float16x8_t data = vld1q_f16(in_ptr + x);
+ sum_vec = vaddq_f16(sum_vec, data);
+ float32x4_t dl = vcvt_f32_f16(vget_low_f16(data));
+ float32x4_t dh = vcvt_f32_f16(vget_high_f16(data));
+ sum_sq_vec = vaddq_f32(sum_sq_vec, vmulq_f32(dl, dl));
+ sum_sq_vec = vaddq_f32(sum_sq_vec, vmulq_f32(dh, dh));
+ }
- float16_t sum = vget_lane_f16(sum_carry_res, 0);
- float sum_sq = vgetq_lane_f32(sum_sq_carry_res, 0);
+ float16x4_t sum_carry_res = vpadd_f16(vget_high_f16(sum_vec), vget_low_f16(sum_vec));
+ sum_carry_res = vpadd_f16(sum_carry_res, sum_carry_res);
+ sum_carry_res = vpadd_f16(sum_carry_res, sum_carry_res);
- // Compute left-over elements
- for(; x < window_end_x; ++x)
- {
- float16_t data = *(in_ptr + x);
- sum += data;
- float fdata = static_cast<float>(data);
- sum_sq += fdata * fdata;
- }
+ float32x4_t sum_sq_carry_res = vpaddq_f32(sum_sq_vec, sum_sq_vec);
+ sum_sq_carry_res = vpaddq_f32(sum_sq_carry_res, sum_sq_carry_res);
- float16_t mean = sum / input->info()->dimension(0);
- float var = (sum_sq / input->info()->dimension(0)) - (mean * mean);
- float16_t stddev_inv = static_cast<float16_t>(1.f / sqrt(var + epsilon));
+ float16_t sum = vget_lane_f16(sum_carry_res, 0);
+ float sum_sq = vgetq_lane_f32(sum_sq_carry_res, 0);
- float16x8_t mean_vec = vdupq_n_f16(mean);
- float16x8_t stddev_inv_vec = vdupq_n_f16(stddev_inv);
+ // Compute left-over elements
+ for (; x < window_end_x; ++x)
+ {
+ float16_t data = *(in_ptr + x);
+ sum += data;
+ float fdata = static_cast<float>(data);
+ sum_sq += fdata * fdata;
+ }
- for(x = window_start_x; x <= (window_end_x - window_step_x); x += window_step_x)
- {
- float16x8_t data = vld1q_f16(in_ptr + x);
- float16x8_t res = vmulq_f16(vsubq_f16(data, mean_vec), stddev_inv_vec);
- // Store results
- vst1q_f16(out_ptr + x, res);
- }
- for(; x < window_end_x; ++x)
- {
- *(out_ptr + x) = (*(in_ptr + x) - mean) * stddev_inv;
- }
- },
- input_itr, output_itr);
+ float16_t mean = sum / input->info()->dimension(0);
+ float var = (sum_sq / input->info()->dimension(0)) - (mean * mean);
+ float16_t stddev_inv = static_cast<float16_t>(1.f / sqrt(var + epsilon));
+
+ float16x8_t mean_vec = vdupq_n_f16(mean);
+ float16x8_t stddev_inv_vec = vdupq_n_f16(stddev_inv);
+
+ for (x = window_start_x; x <= (window_end_x - window_step_x); x += window_step_x)
+ {
+ float16x8_t data = vld1q_f16(in_ptr + x);
+ float16x8_t res = vmulq_f16(vsubq_f16(data, mean_vec), stddev_inv_vec);
+ // Store results
+ vst1q_f16(out_ptr + x, res);
+ }
+ for (; x < window_end_x; ++x)
+ {
+ *(out_ptr + x) = (*(in_ptr + x) - mean) * stddev_inv;
+ }
+ },
+ input_itr, output_itr);
}
void neon_fp16_meanstddevnorm(ITensor *input, ITensor *output, float epsilon, const Window &window)