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)
diff --git a/src/cpu/kernels/meanstddevnorm/generic/neon/impl.cpp b/src/cpu/kernels/meanstddevnorm/generic/neon/impl.cpp
index 0522d6e..11f6294 100644
--- a/src/cpu/kernels/meanstddevnorm/generic/neon/impl.cpp
+++ b/src/cpu/kernels/meanstddevnorm/generic/neon/impl.cpp
@@ -23,6 +23,7 @@
*/
#include "src/cpu/kernels/meanstddevnorm/generic/neon/impl.h"
+
#include "src/core/NEON/wrapper/wrapper.h"
namespace arm_compute
@@ -45,60 +46,62 @@
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 ScalarType *>(input_itr.ptr());
- auto out_ptr = reinterpret_cast<ScalarType *>(output_itr.ptr());
-
- auto sum_vec = wrapper::vdup_n(static_cast<ScalarType>(0.f), ExactTagType{});
- auto sum_sq_vec = wrapper::vdup_n(static_cast<ScalarType>(0.f), ExactTagType{});
-
- for(; x <= (window_end_x - window_step_x); x += window_step_x)
+ execute_window_loop(
+ win,
+ [&](const Coordinates &)
{
- auto data = wrapper::vloadq(in_ptr + x);
- sum_vec = wrapper::vadd(sum_vec, data);
- sum_sq_vec = wrapper::vadd(sum_sq_vec, wrapper::vmul(data, data));
- }
+ int x = window_start_x;
+ auto in_ptr = reinterpret_cast<const ScalarType *>(input_itr.ptr());
+ auto out_ptr = reinterpret_cast<ScalarType *>(output_itr.ptr());
- auto sum_carry_res = wrapper::vpadd(wrapper::vgethigh(sum_vec), wrapper::vgetlow(sum_vec));
- auto sum_sq_carry_res = wrapper::vpadd(wrapper::vgethigh(sum_sq_vec), wrapper::vgetlow(sum_sq_vec));
- for(int i = 0; i < size / 4; ++i)
- {
- sum_carry_res = wrapper::vpadd(sum_carry_res, sum_carry_res);
- sum_sq_carry_res = wrapper::vpadd(sum_sq_carry_res, sum_sq_carry_res);
- }
+ auto sum_vec = wrapper::vdup_n(static_cast<ScalarType>(0.f), ExactTagType{});
+ auto sum_sq_vec = wrapper::vdup_n(static_cast<ScalarType>(0.f), ExactTagType{});
- auto sum = wrapper::vgetlane(sum_carry_res, 0);
- auto sum_sq = wrapper::vgetlane(sum_sq_carry_res, 0);
+ for (; x <= (window_end_x - window_step_x); x += window_step_x)
+ {
+ auto data = wrapper::vloadq(in_ptr + x);
+ sum_vec = wrapper::vadd(sum_vec, data);
+ sum_sq_vec = wrapper::vadd(sum_sq_vec, wrapper::vmul(data, data));
+ }
- // Compute left-over elements
- for(; x < window_end_x; ++x)
- {
- ScalarType data = *(in_ptr + x);
- sum += data;
- sum_sq += data * data;
- }
+ auto sum_carry_res = wrapper::vpadd(wrapper::vgethigh(sum_vec), wrapper::vgetlow(sum_vec));
+ auto sum_sq_carry_res = wrapper::vpadd(wrapper::vgethigh(sum_sq_vec), wrapper::vgetlow(sum_sq_vec));
+ for (int i = 0; i < size / 4; ++i)
+ {
+ sum_carry_res = wrapper::vpadd(sum_carry_res, sum_carry_res);
+ sum_sq_carry_res = wrapper::vpadd(sum_sq_carry_res, sum_sq_carry_res);
+ }
- ScalarType mean = sum / input->info()->dimension(0);
- ScalarType var = (sum_sq / input->info()->dimension(0)) - (mean * mean);
- ScalarType stddev_inv = 1.f / sqrt(var + epsilon);
+ auto sum = wrapper::vgetlane(sum_carry_res, 0);
+ auto sum_sq = wrapper::vgetlane(sum_sq_carry_res, 0);
- auto mean_vec = wrapper::vdup_n(mean, ExactTagType{});
- auto stddev_inv_vec = wrapper::vdup_n(stddev_inv, ExactTagType{});
- for(x = window_start_x; x <= (window_end_x - window_step_x); x += window_step_x)
- {
- auto data = wrapper::vloadq(in_ptr + x);
- auto res = wrapper::vmul(wrapper::vsub(data, mean_vec), stddev_inv_vec);
- // Store results
- wrapper::vstore(out_ptr + x, res);
- }
- for(; x < window_end_x; ++x)
- {
- *(out_ptr + x) = (*(in_ptr + x) - mean) * stddev_inv;
- }
- },
- input_itr, output_itr);
+ // Compute left-over elements
+ for (; x < window_end_x; ++x)
+ {
+ ScalarType data = *(in_ptr + x);
+ sum += data;
+ sum_sq += data * data;
+ }
+
+ ScalarType mean = sum / input->info()->dimension(0);
+ ScalarType var = (sum_sq / input->info()->dimension(0)) - (mean * mean);
+ ScalarType stddev_inv = 1.f / sqrt(var + epsilon);
+
+ auto mean_vec = wrapper::vdup_n(mean, ExactTagType{});
+ auto stddev_inv_vec = wrapper::vdup_n(stddev_inv, ExactTagType{});
+ for (x = window_start_x; x <= (window_end_x - window_step_x); x += window_step_x)
+ {
+ auto data = wrapper::vloadq(in_ptr + x);
+ auto res = wrapper::vmul(wrapper::vsub(data, mean_vec), stddev_inv_vec);
+ // Store results
+ wrapper::vstore(out_ptr + x, res);
+ }
+ for (; x < window_end_x; ++x)
+ {
+ *(out_ptr + x) = (*(in_ptr + x) - mean) * stddev_inv;
+ }
+ },
+ input_itr, output_itr);
}
template void mean_stddev_normalization<float, 4>(ITensor *input, ITensor *output, float epsilon, const Window &window);
} // namespace cpu
diff --git a/src/cpu/kernels/meanstddevnorm/generic/neon/qasymm8.cpp b/src/cpu/kernels/meanstddevnorm/generic/neon/qasymm8.cpp
index 53af1e4..32654df 100644
--- a/src/cpu/kernels/meanstddevnorm/generic/neon/qasymm8.cpp
+++ b/src/cpu/kernels/meanstddevnorm/generic/neon/qasymm8.cpp
@@ -23,6 +23,7 @@
*/
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Window.h"
+
#include "src/core/NEON/NEAsymm.h"
#include "src/core/NEON/NEMath.h"
#include "src/core/NEON/wrapper/wrapper.h"
@@ -69,77 +70,76 @@
const float32x4_t quant_min_vec = vdupq_n_f32(0.0f);
execute_window_loop(
- win, [&](const Coordinates &)
- {
- int x = window_start_x;
- auto in_ptr = reinterpret_cast<const uint8_t *>(input_itr.ptr());
- auto out_ptr = reinterpret_cast<uint8_t *>(output_itr.ptr());
-
- uint32x4_t sum_vec = vdupq_n_u32(0);
- uint32x4_t sum_sq_vec = vdupq_n_u32(0);
-
- for(; x <= (window_end_x - window_step_x); x += window_step_x)
+ win,
+ [&](const Coordinates &)
{
- const uint8x16_t data = vld1q_u8(in_ptr + x);
- sum_vec = vaddq_u32(sum_vec, vpaddlq_u16(vpaddlq_u8(data)));
- const uint16x8_t squares_low = vmull_u8(vget_low_u8(data), vget_low_u8(data));
- const uint16x8_t squares_high = vmull_u8(vget_high_u8(data), vget_high_u8(data));
- sum_sq_vec = vaddq_u32(sum_sq_vec, vaddq_u32(vpaddlq_u16(squares_low), vpaddlq_u16(squares_high)));
- }
+ int x = window_start_x;
+ auto in_ptr = reinterpret_cast<const uint8_t *>(input_itr.ptr());
+ auto out_ptr = reinterpret_cast<uint8_t *>(output_itr.ptr());
+
+ uint32x4_t sum_vec = vdupq_n_u32(0);
+ uint32x4_t sum_sq_vec = vdupq_n_u32(0);
+
+ for (; x <= (window_end_x - window_step_x); x += window_step_x)
+ {
+ const uint8x16_t data = vld1q_u8(in_ptr + x);
+ sum_vec = vaddq_u32(sum_vec, vpaddlq_u16(vpaddlq_u8(data)));
+ const uint16x8_t squares_low = vmull_u8(vget_low_u8(data), vget_low_u8(data));
+ const uint16x8_t squares_high = vmull_u8(vget_high_u8(data), vget_high_u8(data));
+ sum_sq_vec = vaddq_u32(sum_sq_vec, vaddq_u32(vpaddlq_u16(squares_low), vpaddlq_u16(squares_high)));
+ }
#ifdef __aarch64__
- sum_vec = vpaddq_u32(sum_vec, sum_vec);
- sum_vec = vpaddq_u32(sum_vec, sum_vec);
- uint32_t sum = vgetq_lane_u32(sum_vec, 0);
- sum_sq_vec = vpaddq_u32(sum_sq_vec, sum_sq_vec);
- sum_sq_vec = vpaddq_u32(sum_sq_vec, sum_sq_vec);
- uint32_t sum_sq = vgetq_lane_u32(sum_sq_vec, 0);
+ sum_vec = vpaddq_u32(sum_vec, sum_vec);
+ sum_vec = vpaddq_u32(sum_vec, sum_vec);
+ uint32_t sum = vgetq_lane_u32(sum_vec, 0);
+ sum_sq_vec = vpaddq_u32(sum_sq_vec, sum_sq_vec);
+ sum_sq_vec = vpaddq_u32(sum_sq_vec, sum_sq_vec);
+ uint32_t sum_sq = vgetq_lane_u32(sum_sq_vec, 0);
#elif __arm__ // #ifdef __aarch64__
- uint32_t sum = vgetq_lane_u32(sum_vec, 0) +
- vgetq_lane_u32(sum_vec, 1) +
- vgetq_lane_u32(sum_vec, 2) +
- vgetq_lane_u32(sum_vec, 3);
+ uint32_t sum = vgetq_lane_u32(sum_vec, 0) + vgetq_lane_u32(sum_vec, 1) + vgetq_lane_u32(sum_vec, 2) +
+ vgetq_lane_u32(sum_vec, 3);
- uint32_t sum_sq = vgetq_lane_u32(sum_sq_vec, 0) +
- vgetq_lane_u32(sum_sq_vec, 1) +
- vgetq_lane_u32(sum_sq_vec, 2) +
- vgetq_lane_u32(sum_sq_vec, 3);
+ uint32_t sum_sq = vgetq_lane_u32(sum_sq_vec, 0) + vgetq_lane_u32(sum_sq_vec, 1) +
+ vgetq_lane_u32(sum_sq_vec, 2) + vgetq_lane_u32(sum_sq_vec, 3);
#endif // #ifdef __aarch64__
- for(; x < window_end_x; ++x)
- {
- auto data = static_cast<uint32_t>(*(in_ptr + x));
- sum += data;
- sum_sq += (data * data);
- }
+ for (; x < window_end_x; ++x)
+ {
+ auto data = static_cast<uint32_t>(*(in_ptr + x));
+ sum += data;
+ sum_sq += (data * data);
+ }
- const float mean = (static_cast<float>(sum) / static_cast<float>(input->info()->dimension(0)));
- const float var = (static_cast<float>(sum_sq) / static_cast<float>(input->info()->dimension(0))) - (mean * mean);
- const float stdev_inv = 1.0f / sqrtf(var + epsilon);
- const float32x4_t v_scale = vdupq_n_f32(stdev_inv * output_inv_scale);
- const float32x4_t v_offset = vdupq_n_f32(-mean * stdev_inv * output_inv_scale + output_offset);
- for(x = window_start_x; x <= (window_end_x - window_step_x); x += window_step_x)
- {
- const uint8x16_t data = vld1q_u8(in_ptr + x);
- float32x4_t db1 = vcvtq_f32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_low_u8(data)))));
- float32x4_t db2 = vcvtq_f32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_low_u8(data)))));
- float32x4_t db3 = vcvtq_f32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_high_u8(data)))));
- float32x4_t db4 = vcvtq_f32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_high_u8(data)))));
- db1 = clamp_v4f32(vaddq_f32(vmulq_f32(db1, v_scale), v_offset), quant_min_vec, quant_max_vec);
- db2 = clamp_v4f32(vaddq_f32(vmulq_f32(db2, v_scale), v_offset), quant_min_vec, quant_max_vec);
- db3 = clamp_v4f32(vaddq_f32(vmulq_f32(db3, v_scale), v_offset), quant_min_vec, quant_max_vec);
- db4 = clamp_v4f32(vaddq_f32(vmulq_f32(db4, v_scale), v_offset), quant_min_vec, quant_max_vec);
- const uint8x16_t out = fuse_shorts_u16(fuse_words_f32(db1, db2), fuse_words_f32(db3, db4));
- vst1q_u8(out_ptr + x, out);
- }
+ const float mean = (static_cast<float>(sum) / static_cast<float>(input->info()->dimension(0)));
+ const float var =
+ (static_cast<float>(sum_sq) / static_cast<float>(input->info()->dimension(0))) - (mean * mean);
+ const float stdev_inv = 1.0f / sqrtf(var + epsilon);
+ const float32x4_t v_scale = vdupq_n_f32(stdev_inv * output_inv_scale);
+ const float32x4_t v_offset = vdupq_n_f32(-mean * stdev_inv * output_inv_scale + output_offset);
+ for (x = window_start_x; x <= (window_end_x - window_step_x); x += window_step_x)
+ {
+ const uint8x16_t data = vld1q_u8(in_ptr + x);
+ float32x4_t db1 = vcvtq_f32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_low_u8(data)))));
+ float32x4_t db2 = vcvtq_f32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_low_u8(data)))));
+ float32x4_t db3 = vcvtq_f32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_high_u8(data)))));
+ float32x4_t db4 = vcvtq_f32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_high_u8(data)))));
+ db1 = clamp_v4f32(vaddq_f32(vmulq_f32(db1, v_scale), v_offset), quant_min_vec, quant_max_vec);
+ db2 = clamp_v4f32(vaddq_f32(vmulq_f32(db2, v_scale), v_offset), quant_min_vec, quant_max_vec);
+ db3 = clamp_v4f32(vaddq_f32(vmulq_f32(db3, v_scale), v_offset), quant_min_vec, quant_max_vec);
+ db4 = clamp_v4f32(vaddq_f32(vmulq_f32(db4, v_scale), v_offset), quant_min_vec, quant_max_vec);
+ const uint8x16_t out = fuse_shorts_u16(fuse_words_f32(db1, db2), fuse_words_f32(db3, db4));
+ vst1q_u8(out_ptr + x, out);
+ }
- for(; x < window_end_x; ++x)
- {
- auto data = static_cast<float32_t>(*(in_ptr + x));
- const uint8_t res = data * (stdev_inv * output_inv_scale) + (-mean * stdev_inv * output_inv_scale + output_offset);
- *(out_ptr + x) = res;
- }
- },
- input_itr, output_itr);
+ for (; x < window_end_x; ++x)
+ {
+ auto data = static_cast<float32_t>(*(in_ptr + x));
+ const uint8_t res =
+ data * (stdev_inv * output_inv_scale) + (-mean * stdev_inv * output_inv_scale + output_offset);
+ *(out_ptr + x) = res;
+ }
+ },
+ input_itr, output_itr);
}
} // namespace cpu
} // namespace arm_compute