254 lines
7.0 KiB
C++
254 lines
7.0 KiB
C++
/***************************************************************************************************
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* Copyright (c) 2017-2021, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without modification, are permitted
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* provided that the following conditions are met:
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* * Redistributions of source code must retain the above copyright notice, this list of
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* conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright notice, this list of
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* conditions and the following disclaimer in the documentation and/or other materials
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* provided with the distribution.
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* * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used
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* to endorse or promote products derived from this software without specific prior written
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* permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
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* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
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* FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
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* OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
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* STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*
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**************************************************************************************************/
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/*! \file
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\brief This extends the contents of cutlass/functional.h with frequently used activation functions.
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*/
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#pragma once
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#include "cutlass/cutlass.h"
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#include "cutlass/numeric_types.h"
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#include "cutlass/constants.h"
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#include "cutlass/complex.h"
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#include "cutlass/array.h"
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#include "cutlass/half.h"
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#include "cutlass/functional.h"
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/////////////////////////////////////////////////////////////////////////////////////////////////
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namespace cutlass {
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namespace epilogue {
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namespace thread {
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/////////////////////////////////////////////////////////////////////////////////////////////////
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template <typename T>
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struct Identity {
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CUTLASS_HOST_DEVICE
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T operator()(T value) const {
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return value;
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}
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};
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/////////////////////////////////////////////////////////////////////////////////////////////////
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/// ReLu operator - propagates NaNs
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template <typename T>
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struct ReLu {
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CUTLASS_HOST_DEVICE
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T operator()(T const & threshold, T value) const {
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if (value < threshold) {
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value = threshold;
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}
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return value;
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}
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CUTLASS_HOST_DEVICE
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T operator()(T value) const {
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if (value < T()) {
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value = T();
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}
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return value;
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}
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};
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template <typename T, int N>
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struct ReLu<Array<T, N>> {
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CUTLASS_HOST_DEVICE
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Array<T, N> operator()(T const & threshold, Array<T, N> const &frag) const {
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Array<T, N> result;
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CUTLASS_PRAGMA_UNROLL
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for (int i = 0; i < N; ++i) {
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T value = frag[i];
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if (value < threshold) {
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value = threshold;
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}
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result[i] = value;
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}
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return result;
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}
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};
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// Sigmoid operator
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template <typename T>
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struct Sigmoid {
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CUTLASS_HOST_DEVICE
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T operator()(T const &scalar) const {
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return T(1) / (T(1) + exp(-scalar));
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}
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};
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template <>
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struct Sigmoid<float> {
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CUTLASS_HOST_DEVICE
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float operator()(float const &scalar) const {
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return 1.0f / (1.0f + expf(-scalar));
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}
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};
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template <typename T, int N>
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struct Sigmoid<Array<T, N> > {
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CUTLASS_HOST_DEVICE
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Array<T, N> operator()(Array<T, N> const &rhs) const {
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Array<T, N> y;
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Sigmoid<T> sigmoid_op;
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CUTLASS_PRAGMA_UNROLL
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for (int i = 0; i < int(rhs.size()); ++i) {
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y[i] = sigmoid_op(rhs[i]);
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}
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return y;
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}
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};
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//
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// GELU function definitions implemented as described by
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// Hendrycks, D., and Gimpel, K. in
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// "Gaussian Error Linear Units (GELUs)." (2020)
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// https://arxiv.org/pdf/1606.08415.pdf
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//
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// Floating-point constants are Taylor coefficients described in the paper.
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//
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// GELU operator
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template <typename T>
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struct GELU {
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CUTLASS_HOST_DEVICE
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T operator()(T const &scalar) const {
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return T(cutlass::constants::half<T>() * scalar *
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(cutlass::constants::one<T>() + (T)erff((float)(scalar / cutlass::constants::root_two<T>()))));
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}
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};
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template <>
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struct GELU<float> {
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CUTLASS_HOST_DEVICE
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float operator()(float const &scalar) const {
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return cutlass::constants::half<float>() * scalar *
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(cutlass::constants::one<float>() + erff( scalar / cutlass::constants::root_two<float>() ));
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}
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};
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template <>
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struct GELU<double> {
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CUTLASS_HOST_DEVICE
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double operator()(double const &scalar) const {
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return cutlass::constants::half<double>() * scalar *
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(cutlass::constants::one<double>() + erf( scalar / cutlass::constants::root_two<double>() ));
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}
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};
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template <typename T, int N>
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struct GELU<Array<T, N> > {
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CUTLASS_HOST_DEVICE
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Array<T, N> operator()(Array<T, N> const &rhs) const {
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Array<T, N> y;
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GELU<T> gelu_op;
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CUTLASS_PRAGMA_UNROLL
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for (int i = 0; i < N; ++i) {
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y[i] = gelu_op(rhs[i]);
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}
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return y;
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}
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};
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// GELU operator implemented using the Taylor series approximation
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template <typename T>
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struct GELU_taylor {
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CUTLASS_HOST_DEVICE
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T operator()(T const &z) const {
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T k0 = T(0.7978845608028654);
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T k1 = T(0.044715);
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return T(cutlass::constants::half<T>() * z *
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(cutlass::constants::one<T>() + fast_tanh(k0 * z * (cutlass::constants::one<T>() + k1 * z * z))));
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}
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};
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template <typename T, int N>
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struct GELU_taylor<Array<T, N> > {
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CUTLASS_HOST_DEVICE
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Array<T, N> operator()(Array<T, N> const &rhs) const {
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Array<T, N> y;
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GELU_taylor<T> gelu_op;
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CUTLASS_PRAGMA_UNROLL
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for (int i = 0; i < N; ++i) {
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y[i] = gelu_op(rhs[i]);
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}
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return y;
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}
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};
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/// Computes backwards pass for GELU operator assuming d_t is the layer gradient and
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/// z is computed from the forward pass.
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template <typename T>
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struct dGELU {
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CUTLASS_HOST_DEVICE
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T operator()(T const &d_t, T const &z) const {
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T k0 = T(0.7978845608028654);
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T k1 = T(0.044715);
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T k2 = T(0.1070322243);
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T tanh_out = fast_tanh(k0 * z * (1 + k1 * z * z));
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T ff = constants::half<T>() * z * ((1 - tanh_out * tanh_out) * (k0 + k2 * z * z)) +
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constants::half<T>() * (1 + tanh_out);
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return ff * d_t;
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}
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};
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template <typename T, int N>
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struct dGELU<Array<T, N> > {
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CUTLASS_HOST_DEVICE
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Array<T, N> operator()(Array<T, N> const &d_t, Array<T, N> const &z) const {
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Array<T, N> y;
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dGELU<T> gelu_op;
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CUTLASS_PRAGMA_UNROLL
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for (int i = 0; i < N; ++i) {
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y[i] = gelu_op(d_t[i], z[i]);
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}
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return y;
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}
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};
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/////////////////////////////////////////////////////////////////////////////////////////////////
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} // namespace thread
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} // namespace epilogue
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} // namespace cutlass
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/////////////////////////////////////////////////////////////////////////////////////////////////
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