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authorPablo Marquez Tello <pablo.tello@arm.com>2023-09-04 14:18:37 +0100
committerPablo Marquez Tello <pablo.tello@arm.com>2023-09-08 12:32:25 +0000
commit3912f47b5849c2c7c4e68ff922869decf22fe303 (patch)
tree9292bf64b62a556661f2d0b6855365e3e3c295ea
parent45e5b5a4c6aa0e8dadf3c1d08031807eb0a1523b (diff)
downloadComputeLibrary-3912f47b5849c2c7c4e68ff922869decf22fe303.tar.gz
Meanstddevnorm changes 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: I7e6d998e427982d4a037dbce6d17ca378665e07f Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10241 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>
-rw-r--r--src/cpu/kernels/meanstddevnorm/generic/neon/fp16.cpp78
-rw-r--r--src/cpu/kernels/meanstddevnorm/generic/neon/impl.cpp79
2 files changed, 78 insertions, 79 deletions
diff --git a/src/cpu/kernels/meanstddevnorm/generic/neon/fp16.cpp b/src/cpu/kernels/meanstddevnorm/generic/neon/fp16.cpp
index 47bf64ae57..96e4030268 100644
--- a/src/cpu/kernels/meanstddevnorm/generic/neon/fp16.cpp
+++ b/src/cpu/kernels/meanstddevnorm/generic/neon/fp16.cpp
@@ -22,13 +22,89 @@
* SOFTWARE.
*/
#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS)
-#include "src/cpu/CpuTypes.h"
+
#include "src/cpu/kernels/meanstddevnorm/generic/neon/impl.h"
+#include "src/core/NEON/wrapper/wrapper.h"
+#include "src/cpu/CpuTypes.h"
namespace arm_compute
{
namespace cpu
{
+template <>
+void mean_stddev_normalization<float16_t, 8>(ITensor *input, ITensor *output, float epsilon, const Window &window)
+{
+ // Set build options
+ Window win = window;
+ win.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+ const int window_step_x = 8;
+ const auto window_start_x = static_cast<int>(window.x().start());
+ const auto window_end_x = static_cast<int>(window.x().end());
+
+ 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)
+ {
+ 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));
+ }
+
+ 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);
+
+ 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 sum = vget_lane_f16(sum_carry_res, 0);
+ float sum_sq = vgetq_lane_f32(sum_sq_carry_res, 0);
+
+ // 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;
+ }
+
+ 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)
{
return mean_stddev_normalization<float16_t, 8>(input, output, epsilon, window);
diff --git a/src/cpu/kernels/meanstddevnorm/generic/neon/impl.cpp b/src/cpu/kernels/meanstddevnorm/generic/neon/impl.cpp
index 0d00acdd0c..0522d6e277 100644
--- a/src/cpu/kernels/meanstddevnorm/generic/neon/impl.cpp
+++ b/src/cpu/kernels/meanstddevnorm/generic/neon/impl.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2019-2022 Arm Limited.
+ * Copyright (c) 2019-2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -101,82 +101,5 @@ void mean_stddev_normalization(ITensor *input, ITensor *output, float epsilon, c
input_itr, output_itr);
}
template void mean_stddev_normalization<float, 4>(ITensor *input, ITensor *output, float epsilon, const Window &window);
-
-#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS)
-template <>
-void mean_stddev_normalization<float16_t, 8>(ITensor *input, ITensor *output, float epsilon, const Window &window)
-{
- // Set build options
- Window win = window;
- win.set(Window::DimX, Window::Dimension(0, 1, 1));
-
- const int window_step_x = 8;
- const auto window_start_x = static_cast<int>(window.x().start());
- const auto window_end_x = static_cast<int>(window.x().end());
-
- 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)
- {
- 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));
- }
-
- 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);
-
- 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 sum = vget_lane_f16(sum_carry_res, 0);
- float sum_sq = vgetq_lane_f32(sum_sq_carry_res, 0);
-
- // 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;
- }
-
- 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);
-}
-#endif //defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS)
-
} // namespace cpu
} // namespace arm_compute