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| 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 /tests/validation/reference/ActivationLayer.h | |
| 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 'tests/validation/reference/ActivationLayer.h')
| -rw-r--r-- | tests/validation/reference/ActivationLayer.h | 5 |
1 files changed, 4 insertions, 1 deletions
diff --git a/tests/validation/reference/ActivationLayer.h b/tests/validation/reference/ActivationLayer.h index 8aad1af63e..97733238ef 100644 --- a/tests/validation/reference/ActivationLayer.h +++ b/tests/validation/reference/ActivationLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2020 Arm Limited. + * Copyright (c) 2017-2020, 2022 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -84,6 +84,9 @@ inline T activate_float(T x, T a, T b, ActivationLayerInfo::ActivationFunction a case ActivationLayerInfo::ActivationFunction::HARD_SWISH: ret = x * ((std::min(std::max(static_cast<T>(x + 3), static_cast<T>(0.0f)), static_cast<T>(6.0f))) * 0.166666667f); break; + case ActivationLayerInfo::ActivationFunction::GELU: + ret = x * 0.5f * (1 + erf(x / std::sqrt(2.0f))); + break; default: ARM_COMPUTE_ERROR("Unsupported activation function"); break; |