mirror of
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440 lines
16 KiB
C++
440 lines
16 KiB
C++
#ifndef MLPP_ACTIVATION_H
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#define MLPP_ACTIVATION_H
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/*************************************************************************/
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/* activation.h */
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/*************************************************************************/
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/* This file is part of: */
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/* PMLPP Machine Learning Library */
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/* https://github.com/Relintai/pmlpp */
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/*************************************************************************/
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/* Copyright (c) 2023-present Péter Magyar. */
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/* Copyright (c) 2022-2023 Marc Melikyan */
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/* */
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/* Permission is hereby granted, free of charge, to any person obtaining */
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/* a copy of this software and associated documentation files (the */
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/* "Software"), to deal in the Software without restriction, including */
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/* without limitation the rights to use, copy, modify, merge, publish, */
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/* distribute, sublicense, and/or sell copies of the Software, and to */
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/* permit persons to whom the Software is furnished to do so, subject to */
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/* the following conditions: */
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/* */
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/* The above copyright notice and this permission notice shall be */
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/* included in all copies or substantial portions of the Software. */
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/* */
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/* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, */
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/* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF */
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/* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.*/
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/* IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY */
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/* CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, */
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/* TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE */
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/* SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */
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/*************************************************************************/
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#include "core/math/math_defs.h"
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#include "core/object/func_ref.h"
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#include "core/object/reference.h"
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#include "../lin_alg/mlpp_matrix.h"
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#include "../lin_alg/mlpp_vector.h"
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#include <vector>
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//TODO Activation functions should either have a variant which does not allocate, or they should just be reworked altogether
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//TODO Methods here should probably use error macros, in a way where they get disabled in non-tools(?) (maybe release?) builds
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class MLPPActivation : public Reference {
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GDCLASS(MLPPActivation, Reference);
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public:
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enum ActivationFunction {
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ACTIVATION_FUNCTION_LINEAR = 0,
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ACTIVATION_FUNCTION_SIGMOID,
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ACTIVATION_FUNCTION_SWISH,
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ACTIVATION_FUNCTION_MISH,
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ACTIVATION_FUNCTION_SIN_C,
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ACTIVATION_FUNCTION_SOFTMAX,
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ACTIVATION_FUNCTION_SOFTPLUS,
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ACTIVATION_FUNCTION_SOFTSIGN,
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ACTIVATION_FUNCTION_ADJ_SOFTMAX,
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ACTIVATION_FUNCTION_C_LOG_LOG,
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ACTIVATION_FUNCTION_LOGIT,
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ACTIVATION_FUNCTION_GAUSSIAN_CDF,
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ACTIVATION_FUNCTION_RELU,
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ACTIVATION_FUNCTION_GELU,
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ACTIVATION_FUNCTION_SIGN,
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ACTIVATION_FUNCTION_UNIT_STEP,
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ACTIVATION_FUNCTION_SINH,
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ACTIVATION_FUNCTION_COSH,
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ACTIVATION_FUNCTION_TANH,
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ACTIVATION_FUNCTION_CSCH,
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ACTIVATION_FUNCTION_SECH,
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ACTIVATION_FUNCTION_COTH,
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ACTIVATION_FUNCTION_ARSINH,
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ACTIVATION_FUNCTION_ARCOSH,
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ACTIVATION_FUNCTION_ARTANH,
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ACTIVATION_FUNCTION_ARCSCH,
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ACTIVATION_FUNCTION_ARSECH,
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ACTIVATION_FUNCTION_ARCOTH,
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};
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public:
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typedef real_t (MLPPActivation::*RealActivationFunctionPointer)(real_t);
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typedef Ref<MLPPVector> (MLPPActivation::*VectorActivationFunctionPointer)(const Ref<MLPPVector> &);
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typedef Ref<MLPPMatrix> (MLPPActivation::*MatrixActivationFunctionPointer)(const Ref<MLPPMatrix> &);
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RealActivationFunctionPointer get_activation_function_ptr_real(const ActivationFunction func, const bool deriv = false);
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VectorActivationFunctionPointer get_activation_function_ptr_vector(const ActivationFunction func, const bool deriv = false);
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MatrixActivationFunctionPointer get_activation_function_ptr_matrix(const ActivationFunction func, const bool deriv = false);
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RealActivationFunctionPointer get_activation_function_ptr_normal_real(const ActivationFunction func);
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VectorActivationFunctionPointer get_activation_function_ptr_normal_vector(const ActivationFunction func);
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MatrixActivationFunctionPointer get_activation_function_ptr_normal_matrix(const ActivationFunction func);
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RealActivationFunctionPointer get_activation_function_ptr_deriv_real(const ActivationFunction func);
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VectorActivationFunctionPointer get_activation_function_ptr_deriv_vector(const ActivationFunction func);
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MatrixActivationFunctionPointer get_activation_function_ptr_deriv_matrix(const ActivationFunction func);
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real_t run_activation_real(const ActivationFunction func, const real_t z, const bool deriv = false);
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Ref<MLPPVector> run_activation_vector(const ActivationFunction func, const Ref<MLPPVector> &z, const bool deriv = false);
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Ref<MLPPMatrix> run_activation_matrix(const ActivationFunction func, const Ref<MLPPMatrix> &z, const bool deriv = false);
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real_t run_activation_norm_real(const ActivationFunction func, const real_t z);
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Ref<MLPPVector> run_activation_norm_vector(const ActivationFunction func, const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> run_activation_norm_matrix(const ActivationFunction func, const Ref<MLPPMatrix> &z);
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real_t run_activation_deriv_real(const ActivationFunction func, const real_t z);
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Ref<MLPPVector> run_activation_deriv_vector(const ActivationFunction func, const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> run_activation_deriv_matrix(const ActivationFunction func, const Ref<MLPPMatrix> &z);
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Ref<MLPPVector> activationr(const Ref<MLPPVector> &z, real_t (*function)(real_t));
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//ACTIVATION FUNCTIONS
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//LINEAR
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real_t linear_normr(real_t z);
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Ref<MLPPVector> linear_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> linear_normm(const Ref<MLPPMatrix> &z);
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real_t linear_derivr(real_t z);
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Ref<MLPPVector> linear_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> linear_derivm(const Ref<MLPPMatrix> &z);
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//SIGMOID
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real_t sigmoid_normr(real_t z);
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Ref<MLPPVector> sigmoid_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> sigmoid_normm(const Ref<MLPPMatrix> &z);
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real_t sigmoid_derivr(real_t z);
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Ref<MLPPVector> sigmoid_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> sigmoid_derivm(const Ref<MLPPMatrix> &z);
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//SOFTMAX
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real_t softmax_normr(real_t z);
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Ref<MLPPVector> softmax_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> softmax_normm(const Ref<MLPPMatrix> &z);
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real_t softmax_derivr(real_t z);
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Ref<MLPPVector> softmax_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> softmax_derivm(const Ref<MLPPMatrix> &z);
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//ADJ_SOFTMAX
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real_t adj_softmax_normr(real_t z);
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Ref<MLPPVector> adj_softmax_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> adj_softmax_normm(const Ref<MLPPMatrix> &z);
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real_t adj_softmax_derivr(real_t z);
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Ref<MLPPVector> adj_softmax_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> adj_softmax_derivm(const Ref<MLPPMatrix> &z);
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//SOFTMAX DERIV
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Ref<MLPPMatrix> softmax_deriv_normv(const Ref<MLPPVector> &z);
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Vector<Ref<MLPPMatrix>> softmax_deriv_normm(const Ref<MLPPMatrix> &z);
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Ref<MLPPMatrix> softmax_deriv_derivv(const Ref<MLPPVector> &z);
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Vector<Ref<MLPPMatrix>> softmax_deriv_derivm(const Ref<MLPPMatrix> &z);
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//SOFTPLUS
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real_t softplus_normr(real_t z);
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Ref<MLPPVector> softplus_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> softplus_normm(const Ref<MLPPMatrix> &z);
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real_t softplus_derivr(real_t z);
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Ref<MLPPVector> softplus_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> softplus_derivm(const Ref<MLPPMatrix> &z);
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//SOFTSIGN
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real_t softsign_normr(real_t z);
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Ref<MLPPVector> softsign_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> softsign_normm(const Ref<MLPPMatrix> &z);
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real_t softsign_derivr(real_t z);
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Ref<MLPPVector> softsign_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> softsign_derivm(const Ref<MLPPMatrix> &z);
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//GAUSSIANCDF
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real_t gaussian_cdf_normr(real_t z);
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Ref<MLPPVector> gaussian_cdf_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> gaussian_cdf_normm(const Ref<MLPPMatrix> &z);
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real_t gaussian_cdf_derivr(real_t z);
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Ref<MLPPVector> gaussian_cdf_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> gaussian_cdf_derivm(const Ref<MLPPMatrix> &z);
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//CLOGLOG
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real_t cloglog_normr(real_t z);
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Ref<MLPPVector> cloglog_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> cloglog_normm(const Ref<MLPPMatrix> &z);
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real_t cloglog_derivr(real_t z);
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Ref<MLPPVector> cloglog_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> cloglog_derivm(const Ref<MLPPMatrix> &z);
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//LOGIT
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real_t logit_normr(real_t z);
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Ref<MLPPVector> logit_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> logit_normm(const Ref<MLPPMatrix> &z);
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real_t logit_derivr(real_t z);
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Ref<MLPPVector> logit_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> logit_derivm(const Ref<MLPPMatrix> &z);
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//UNITSTEP
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real_t unit_step_normr(real_t z);
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Ref<MLPPVector> unit_step_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> unit_step_normm(const Ref<MLPPMatrix> &z);
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real_t unit_step_derivr(real_t z);
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Ref<MLPPVector> unit_step_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> unit_step_derivm(const Ref<MLPPMatrix> &z);
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//SWISH
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real_t swish_normr(real_t z);
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Ref<MLPPVector> swish_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> swish_normm(const Ref<MLPPMatrix> &z);
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real_t swish_derivr(real_t z);
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Ref<MLPPVector> swish_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> swish_derivm(const Ref<MLPPMatrix> &z);
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//MISH
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real_t mish_normr(real_t z);
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Ref<MLPPVector> mish_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> mish_normm(const Ref<MLPPMatrix> &z);
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real_t mish_derivr(real_t z);
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Ref<MLPPVector> mish_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> mish_derivm(const Ref<MLPPMatrix> &z);
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//SINC
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real_t sinc_normr(real_t z);
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Ref<MLPPVector> sinc_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> sinc_normm(const Ref<MLPPMatrix> &z);
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real_t sinc_derivr(real_t z);
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Ref<MLPPVector> sinc_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> sinc_derivm(const Ref<MLPPMatrix> &z);
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//RELU
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real_t relu_normr(real_t z);
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Ref<MLPPVector> relu_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> relu_normm(const Ref<MLPPMatrix> &z);
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real_t relu_derivr(real_t z);
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Ref<MLPPVector> relu_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> relu_derivm(const Ref<MLPPMatrix> &z);
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//LEAKYRELU
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real_t leaky_relu_normr(real_t z, real_t c);
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Ref<MLPPVector> leaky_relu_normv(const Ref<MLPPVector> &z, real_t c);
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Ref<MLPPMatrix> leaky_relu_normm(const Ref<MLPPMatrix> &z, real_t c);
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real_t leaky_relu_derivr(real_t z, real_t c);
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Ref<MLPPVector> leaky_relu_derivv(const Ref<MLPPVector> &z, real_t c);
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Ref<MLPPMatrix> leaky_relu_derivm(const Ref<MLPPMatrix> &z, real_t c);
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//ELU
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real_t elu_normr(real_t z, real_t c);
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Ref<MLPPVector> elu_normv(const Ref<MLPPVector> &z, real_t c);
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Ref<MLPPMatrix> elu_normm(const Ref<MLPPMatrix> &z, real_t c);
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real_t elu_derivr(real_t z, real_t c);
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Ref<MLPPVector> elu_derivv(const Ref<MLPPVector> &z, real_t c);
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Ref<MLPPMatrix> elu_derivm(const Ref<MLPPMatrix> &z, real_t c);
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//SELU
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real_t selu_normr(real_t z, real_t lambda, real_t c);
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Ref<MLPPVector> selu_normv(const Ref<MLPPVector> &z, real_t lambda, real_t c);
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Ref<MLPPMatrix> selu_normm(const Ref<MLPPMatrix> &z, real_t lambda, real_t c);
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real_t selu_derivr(real_t z, real_t lambda, real_t c);
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Ref<MLPPVector> selu_derivv(const Ref<MLPPVector> &z, real_t lambda, real_t c);
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Ref<MLPPMatrix> selu_derivm(const Ref<MLPPMatrix> &z, real_t lambda, real_t c);
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//GELU
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real_t gelu_normr(real_t z);
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Ref<MLPPVector> gelu_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> gelu_normm(const Ref<MLPPMatrix> &z);
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real_t gelu_derivr(real_t z);
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Ref<MLPPVector> gelu_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> gelu_derivm(const Ref<MLPPMatrix> &z);
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//SIGN
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real_t sign_normr(real_t z);
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Ref<MLPPVector> sign_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> sign_normm(const Ref<MLPPMatrix> &z);
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real_t sign_derivr(real_t z);
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Ref<MLPPVector> sign_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> sign_derivm(const Ref<MLPPMatrix> &z);
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//SINH
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real_t sinh_normr(real_t z);
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Ref<MLPPVector> sinh_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> sinh_normm(const Ref<MLPPMatrix> &z);
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real_t sinh_derivr(real_t z);
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Ref<MLPPVector> sinh_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> sinh_derivm(const Ref<MLPPMatrix> &z);
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//COSH
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real_t cosh_normr(real_t z);
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Ref<MLPPVector> cosh_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> cosh_normm(const Ref<MLPPMatrix> &z);
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real_t cosh_derivr(real_t z);
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Ref<MLPPVector> cosh_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> cosh_derivm(const Ref<MLPPMatrix> &z);
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//TANH
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real_t tanh_normr(real_t z);
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Ref<MLPPVector> tanh_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> tanh_normm(const Ref<MLPPMatrix> &z);
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real_t tanh_derivr(real_t z);
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Ref<MLPPVector> tanh_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> tanh_derivm(const Ref<MLPPMatrix> &z);
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//CSCH
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real_t csch_normr(real_t z);
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Ref<MLPPVector> csch_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> csch_normm(const Ref<MLPPMatrix> &z);
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real_t csch_derivr(real_t z);
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Ref<MLPPVector> csch_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> csch_derivm(const Ref<MLPPMatrix> &z);
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//SECH
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real_t sech_normr(real_t z);
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Ref<MLPPVector> sech_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> sech_normm(const Ref<MLPPMatrix> &z);
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real_t sech_derivr(real_t z);
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Ref<MLPPVector> sech_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> sech_derivm(const Ref<MLPPMatrix> &z);
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//COTH
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real_t coth_normr(real_t z);
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Ref<MLPPVector> coth_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> coth_normm(const Ref<MLPPMatrix> &z);
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real_t coth_derivr(real_t z);
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Ref<MLPPVector> coth_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> coth_derivm(const Ref<MLPPMatrix> &z);
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//ARSINH
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real_t arsinh_normr(real_t z);
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Ref<MLPPVector> arsinh_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> arsinh_normm(const Ref<MLPPMatrix> &z);
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real_t arsinh_derivr(real_t z);
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Ref<MLPPVector> arsinh_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> arsinh_derivm(const Ref<MLPPMatrix> &z);
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//ARCOSH
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real_t arcosh_normr(real_t z);
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Ref<MLPPVector> arcosh_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> arcosh_normm(const Ref<MLPPMatrix> &z);
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real_t arcosh_derivr(real_t z);
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Ref<MLPPVector> arcosh_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> arcosh_derivm(const Ref<MLPPMatrix> &z);
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//ARTANH
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real_t artanh_normr(real_t z);
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Ref<MLPPVector> artanh_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> artanh_normm(const Ref<MLPPMatrix> &z);
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real_t artanh_derivr(real_t z);
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Ref<MLPPVector> artanh_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> artanh_derivm(const Ref<MLPPMatrix> &z);
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//ARCSCH
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real_t arcsch_normr(real_t z);
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Ref<MLPPVector> arcsch_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> arcsch_normm(const Ref<MLPPMatrix> &z);
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real_t arcsch_derivr(real_t z);
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Ref<MLPPVector> arcsch_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> arcsch_derivm(const Ref<MLPPMatrix> &z);
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//ARSECH
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real_t arsech_normr(real_t z);
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Ref<MLPPVector> arsech_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> arsech_normm(const Ref<MLPPMatrix> &z);
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real_t arsech_derivr(real_t z);
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Ref<MLPPVector> arsech_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> arsech_derivm(const Ref<MLPPMatrix> &z);
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//ARCOTH
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real_t arcoth_normr(real_t z);
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Ref<MLPPVector> arcoth_normv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> arcoth_normm(const Ref<MLPPMatrix> &z);
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real_t arcoth_derivr(real_t z);
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Ref<MLPPVector> arcoth_derivv(const Ref<MLPPVector> &z);
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Ref<MLPPMatrix> arcoth_derivm(const Ref<MLPPMatrix> &z);
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protected:
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static void _bind_methods();
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};
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VARIANT_ENUM_CAST(MLPPActivation::ActivationFunction);
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#endif /* Activation_hpp */
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