diff options
| author | Murray Kornelsen <murray.kornelsen@mail.mcgill.ca> | 2022-07-13 21:22:39 -0400 |
|---|---|---|
| committer | Pablo Marquez Tello <pablo.tello@arm.com> | 2022-09-14 09:15:03 +0000 |
| commit | 926f502ca731fa49bcdf949408ce25728616e5f2 (patch) | |
| tree | 7e221103a9c0c5c0e4c054abc07cbdf11c7c7b4e /src/cpu/kernels/activation/generic/neon/qasymm8.cpp | |
| parent | 6e09e1404c635d948cf20eb6b4b5747dfb6656f2 (diff) | |
| download | ComputeLibrary-926f502ca731fa49bcdf949408ce25728616e5f2.tar.gz | |
Adding GELU activation
OpenCL implementation uses built in erf.
NEON implementation requires new vectorized erf.
Uses the following approximation:
erf(x) = 1 - 1 / (1 + a1x + a2x^2 + a3x^3 + a4x^4)^4
a1 = 0.278393, a2 = 0.230389, a3 = 0.000972, a4 = 0.078108
From https://en.wikipedia.org/wiki/Error_function#Numerical_approximations
Signed-off-by: Murray Kornelsen <murray.kornelsen@mail.mcgill.ca>
Change-Id: I2d3964b2c26a4334166b17135f9104bc6324fad2
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7921
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Pablo Marquez Tello <pablo.tello@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/cpu/kernels/activation/generic/neon/qasymm8.cpp')
| -rw-r--r-- | src/cpu/kernels/activation/generic/neon/qasymm8.cpp | 29 |
1 files changed, 28 insertions, 1 deletions
diff --git a/src/cpu/kernels/activation/generic/neon/qasymm8.cpp b/src/cpu/kernels/activation/generic/neon/qasymm8.cpp index 67d9e0a8ca..05a0b505ca 100644 --- a/src/cpu/kernels/activation/generic/neon/qasymm8.cpp +++ b/src/cpu/kernels/activation/generic/neon/qasymm8.cpp @@ -58,9 +58,13 @@ void neon_qasymm8_activation(const ITensor *src, ITensor *dst, const ActivationL const qasymm8_t b = quantize_qasymm8(act_info.b(), qi_in); const qasymm8_t const_0 = quantize_qasymm8(0.f, qi_in); const qasymm8x16_t vconst_0 = vdupq_n_u8(const_0); + const auto vconst_1 = vdupq_n_f32(1.f); + #ifndef __aarch64__ - const auto vconst_1 = vdupq_n_f32(1.f); const auto vconst_0_f32 = vdupq_n_f32(0); +#else // #ifndef __aarch64__ + const auto const_inv_2 = vdupq_n_f32(0.5f); + const auto const_inv_sqrt_2 = vdupq_n_f32(0.70710678118f); #endif // __aarch64__ const float32x4_t va_f32 = vdupq_n_f32(act_info.a()); const float32x4_t vb_f32 = vdupq_n_f32(act_info.b()); @@ -193,6 +197,23 @@ void neon_qasymm8_activation(const ITensor *src, ITensor *dst, const ActivationL tmp = vquantize(tmp_dep, qi_out); } +#else // #ifndef __aarch64__ + else if (act == ActivationLayerInfo::ActivationFunction::GELU) + { + const auto vin_deq = vdequantize(vin, qi_in); + // Perform activation + const float32x4x4_t tmp_dep = + { + { + wrapper::vmul(vin_deq.val[0], wrapper::vmul(const_inv_2, wrapper::vadd(vconst_1, wrapper::verf(wrapper::vmul(vin_deq.val[0], const_inv_sqrt_2))))), + wrapper::vmul(vin_deq.val[1], wrapper::vmul(const_inv_2, wrapper::vadd(vconst_1, wrapper::verf(wrapper::vmul(vin_deq.val[1], const_inv_sqrt_2))))), + wrapper::vmul(vin_deq.val[2], wrapper::vmul(const_inv_2, wrapper::vadd(vconst_1, wrapper::verf(wrapper::vmul(vin_deq.val[2], const_inv_sqrt_2))))), + wrapper::vmul(vin_deq.val[3], wrapper::vmul(const_inv_2, wrapper::vadd(vconst_1, wrapper::verf(wrapper::vmul(vin_deq.val[3], const_inv_sqrt_2))))), + } + }; + // Re-quantize to new output space + tmp = vquantize(tmp_dep, qi_out); + } #endif // __aarch64__ else { @@ -248,6 +269,12 @@ void neon_qasymm8_activation(const ITensor *src, ITensor *dst, const ActivationL tmp_f = tmp_f > 0 ? tmp_f : tmp_f * a_f32; tmp = quantize_qasymm8(tmp_f, qi_out); } + else if(act == ActivationLayerInfo::ActivationFunction::GELU) + { + float tmp_f = dequantize_qasymm8(in, qi_in); + tmp = tmp_f * 0.5f * (1.0f + std::erff(in / 1.41421356237f)); + tmp = quantize_qasymm8(tmp_f, qi_out); + } #endif // __aarch64__ else { |