/******************************************************** * ██████╗ ██████╗████████╗██╗ * ██╔════╝ ██╔════╝╚══██╔══╝██║ * ██║ ███╗██║ ██║ ██║ * ██║ ██║██║ ██║ ██║ * ╚██████╔╝╚██████╗ ██║ ███████╗ * ╚═════╝ ╚═════╝ ╚═╝ ╚══════╝ * Geophysical Computational Tools & Library (GCTL) * * Copyright (c) 2022 Yi Zhang (yizhang-geo@zju.edu.cn) * * GCTL is distributed under a dual licensing scheme. You can redistribute * it and/or modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation, either version 2 * of the License, or (at your option) any later version. You should have * received a copy of the GNU Lesser General Public License along with this * program. If not, see . * * If the terms and conditions of the LGPL v.2. would prevent you from using * the GCTL, please consider the option to obtain a commercial license for a * fee. These licenses are offered by the GCTL's original author. As a rule, * licenses are provided "as-is", unlimited in time for a one time fee. Please * send corresponding requests to: yizhang-geo@zju.edu.cn. Please do not forget * to include some description of your company and the realm of its activities. * Also add information on how to contact you by electronic and paper mail. ******************************************************/ #include "olayer_binaryentropy.h" gctl::binary_entropy::binary_entropy() {} gctl::binary_entropy::~binary_entropy() {} void gctl::binary_entropy::check_target_data(const matrix &target) { int nobs = target.col_size(); int ncls = target.row_size(); // Each element should be either 0 or 1 for (size_t i = 0; i < nobs; i++) { for (size_t j = 0; j < ncls; j++) { if (fabs(target[j][i] - 1.0) > 1e-6 && fabs(target[j][i]) > 1e-6) { throw std::invalid_argument("[gctl::binary_entropy] Target data should only contain zero or one."); } } } return; } void gctl::binary_entropy::check_target_data(const array &target) { int nobs = target.size(); for (size_t i = 0; i < nobs; i++) { if (target[i] != 0 && target[i] != 1) { throw std::invalid_argument("[gctl::binary_entropy] Target data should only contain zero or one."); } } return; } void gctl::binary_entropy::evaluation(const matrix &prev_layer_data, const matrix &target) { int nobs = prev_layer_data.col_size(); int ncls = prev_layer_data.row_size(); if (target.col_size() != nobs || target.row_size() != ncls) { throw std::invalid_argument("[gctl::binary_entropy] Target data have incorrect dimension."); } // Compute the derivative of the input of this layer // L = -y * log(phat) - (1 - y) * log(1 - phat) // in = phat // d(L) / d(in) = -y / phat + (1 - y) / (1 - phat), y is either 0 or 1 der_in_.resize(ncls, nobs); int i, j; #pragma omp parallel for private (i, j) schedule(guided) for (i = 0; i < ncls; i++) { for (j = 0; j < nobs; j++) { der_in_[i][j] = -1.0*target[i][j]/prev_layer_data[i][j] + (1.0 - target[i][j])/(1.0 - prev_layer_data[i][j]); } } return; } void gctl::binary_entropy::evaluation(const matrix &prev_layer_data, const array &target) { // target is a vector of class labels that take values from [0, 1, ..., nclass - 1] // The i-th element of target is the class label for observation i int nobs = prev_layer_data.col_size(); int ncls = prev_layer_data.row_size(); if (ncls != 1) { throw std::invalid_argument("[gctl::binary_entropy] Only one response variable is allowed when class labels are used as target data."); } if (target.size() != nobs) { throw std::invalid_argument("[gctl::binary_entropy] Target data have incorrect dimension."); } // Compute the derivative of the input of this layer // L = -log(phat[y]) // in = phat // d(L) / d(in) = [0, 0, ..., -1/phat[y], 0, ..., 0] der_in_.resize(ncls, nobs); der_in_.assign_all(0.0); int j; #pragma omp parallel for private (j) schedule(guided) for (j = 0; j < nobs; j++) { der_in_[0][j] = -1.0*target[j]/prev_layer_data[0][j] + (1.0 - target[j])/(1.0 - prev_layer_data[0][j]); } return; } double gctl::binary_entropy::loss_value() const { // L = -y * log(phat) - (1 - y) * log(1 - phat) // y = 0 => L = -log(1 - phat) // y = 1 => L = -log(phat) // m_din contains 1/(1 - phat) if y = 0, and -1/phat if y = 1, so // L = log(abs(m_din)).sum() double res = 0.0; int nobs = der_in_.col_size(); int ncls = der_in_.row_size(); int i, j; //#pragma omp parallel for private (i, j) schedule(guided) for (i = 0; i < ncls; i++) { for (j = 0; j < nobs; j++) { res += std::log(fabs(der_in_[i][j])); } } return res/der_in_.col_size(); } std::string gctl::binary_entropy::get_output_name() const { return "BinaryClassEntropy"; } gctl::olayer_type_e gctl::binary_entropy::get_output_type() const { return BinaryClassEntropy; }