Activation Softmax Forward done
This commit is contained in:
@@ -130,6 +130,23 @@
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#define PANIC_OMP_PARALLEL_FOR_IF(condition) \
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_Pragma(PANIC_STRINGIFY(omp parallel for if(condition) num_threads(PANIC_OMP_NUM_THREADS)))
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// Expands to:
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// #pragma omp parallel for if(condition)
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// num_threads(PANIC_OMP_NUM_THREADS)
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// schedule(static)
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// reduction(operation:variable)
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//
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// Runs the loop in parallel only when condition is true.
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// Each thread receives a private copy of variable.
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// Afterward, OpenMP combines those copies using operation.
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// schedule(static) assigns fixed groups of iterations to each thread.
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#define PANIC_OMP_PARALLEL_FOR_REDUCTION_IF(condition, operation, variable) \
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_Pragma(PANIC_STRINGIFY(omp parallel for if(condition) \
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num_threads(PANIC_OMP_NUM_THREADS) \
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schedule(static) \
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reduction(operation:variable)))
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#else
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// Expands to:
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@@ -147,6 +164,21 @@
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#define PANIC_OMP_PARALLEL_FOR_IF(condition) \
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_Pragma(PANIC_STRINGIFY(omp parallel for if(condition)))
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// Expands to:
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// #pragma omp parallel for if(condition)
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// num_threads(PANIC_OMP_NUM_THREADS)
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// schedule(static)
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// reduction(operation:variable)
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//
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// Runs the loop in parallel only when condition is true.
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// Each thread receives a private copy of variable.
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// Afterward, OpenMP combines those copies using operation.
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// schedule(static) assigns fixed groups of iterations to each thread.
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#define PANIC_OMP_PARALLEL_FOR_REDUCTION_IF(condition, operation, variable) \
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_Pragma(PANIC_STRINGIFY(omp parallel for if(condition) \
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schedule(static) \
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reduction(operation:variable)))
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#endif
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#else
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@@ -0,0 +1,306 @@
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/**++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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*
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*
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* PANIC
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* Portable Algorithms and Numerics In C++
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*
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* Scientific computing from scratch, with feeling.
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*
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* Copyright (c) 2026 Michelle Bausager
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*
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* This file is part of PANIC.
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*
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||||
* PANIC is free software licensed under the GNU General Public License v3.0 or later.
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* You may redistribute and/or modify it under the terms of the GPL.
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||||
*
|
||||
* PANIC is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY;
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||||
* without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
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||||
* See the LICENSE file for the full license text.
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||||
*
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* SPDX-License-Identifier: GPL-3.0-or-later
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*
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*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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*
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* Project Name: PANIC
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* Module Name: math
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* File Name: div.hpp
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* Revision: 0.1.0
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* Date: 30-07-2026
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* Author: Michelle Bausager
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*
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* Description:
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* Functions to divide panic::tensor
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*
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*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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*
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* @file mul.hpp
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* @brief Public API for multiplying operations on PANIC vectors and matrices.
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*
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* This header contains the declarations that users of the math module should call.
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* The comments here describe how each function is used, what dimensions are required,
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* and what is returned on failure.
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*
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* Implementation details, OpenMP thresholds, and explicit template instantiations are
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* kept in mul.cpp.
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*
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*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*/
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#pragma once
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#include <tensor/vector.hpp> // for panic::vector
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#include <tensor/matrix.hpp> // for panic::matrix
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namespace panic{
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namespace math{
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/**
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* @brief Divides a scalar to every element of a vector.
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*
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* Computes:
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* @code
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* c[i] = a[i] / k
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* @endcode
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*
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* @tparam T Numeric element type.
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* @param a Input vector.
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* @param k Scalar value multiplied to each element of @p a.
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* @param c Output vector. Resized to match @p a.
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*
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* @return true if @p c was resized and filled successfully.
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* @return false if resizing @p c failed.
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*
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* @note This overload writes the result into an existing vector to avoid
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* unnecessary temporary allocations.
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*/
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template <typename T>
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bool div(const panic::tensor::vector<T>& a, const T k, panic::tensor::vector<T>& c);
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/**
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* @brief Returns a new vector containing a scalar divided to every element.
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*
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* Computes:
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* @code
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* result[i] = a[i] / k
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* @endcode
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*
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* @tparam T Numeric element type.
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* @param a Input vector.
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* @param k Scalar value miltiplied to each element of @p a.
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*
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* @return A new vector containing the result.
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* @return An empty vector if the operation fails.
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*
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* @note This overload is convenient, but may allocate a new vector.
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*/
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template <typename T>
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panic::tensor::vector<T> div(const panic::tensor::vector<T>& a, const T k);
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/**
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* @brief Divide a vector elementwise too a vector.
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*
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* Computes:
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* @code
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* c[i] = a[i] / b[i]
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* @endcode
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*
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* @tparam T Numeric element type.
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* @param a First vector.
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* @param b Second vector. Must have size of @p a
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* @param c Output vector. Resized to match @p a.
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*
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* @return true if @p c was resized and filled successfully.
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* @return false if vector sizes do not match or resizing @p c failed.
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*/
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template <typename T>
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bool div(const panic::tensor::vector<T>& a, const panic::tensor::vector<T>& b, panic::tensor::vector<T>& c);
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/**
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* @brief Returns a new vector containing a vector diveded elementwise.
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*
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* Computes:
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* @code
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* result[i] = a[i] / b[i]
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* @endcode
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*
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* @tparam T Numeric element type.
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* @param a First vector.
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* @param b Second vector. Must have size of @p a
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* @param k Scalar value multiplied to each element of @p a.
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*
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* @return A new vector containing the result.
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* @return An empty vector if the operation fails.
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*
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* @note This overload is convenient, but may allocate a new vector.
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*/
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template <typename T>
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panic::tensor::vector<T> div(const panic::tensor::vector<T>& a, const panic::tensor::vector<T>& b);
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/**
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* @brief Divides a scalar to every element of a matix.
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*
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* Computes:
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* @code
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* C(i,j) = A(i,j) / k
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* @endcode
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||||
*
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||||
* @tparam T Numeric element type.
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||||
* @param A Input matrix.
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||||
* @param k Scalar value multiplied to each element of @p A.
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* @param C Output Matrix. Resized to match @p A.
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*
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* @return true if @p C was resized and filled successfully.
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||||
* @return false if resizing @p C failed.
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||||
*
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||||
* @note This overload writes the result into an existing vector to avoid
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||||
* unnecessary temporary allocations.
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||||
*/
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template <typename T>
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bool div(const panic::tensor::matrix<T>& A, const T k, panic::tensor::matrix<T>& C);
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/**
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* @brief Returns a new matrix containing a scalar diveded to every element.
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*
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* Computes:
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* @code
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* result(i,j) = A(i,j) / k
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||||
* @endcode
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||||
*
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||||
* @tparam T Numeric element type.
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||||
* @param A Input matrix.
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||||
* @param k Scalar value multiplied to each element of @p A.
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||||
*
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||||
* @return A new matrix containing the result.
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||||
* @return An empty matrix if the operation fails.
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||||
*
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||||
* @note This overload is convenient, but may allocate a new vector.
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||||
*/
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template <typename T>
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panic::tensor::matrix<T> div(const panic::tensor::matrix<T>& A, const T k);
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/**
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* @brief Divides a matrix elementwise too a matrix.
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||||
*
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* Computes:
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* @code
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* C(i,j) = A(i,j) / B(i,j)
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||||
* @endcode
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||||
*
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||||
* @tparam T Numeric element type.
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||||
* @param A First matrix.
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||||
* @param B Second matrix. Must have size of @p A.
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||||
* @param C Output matrix. Resized to match @p A.
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||||
*
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||||
* @return true if @p C was resized and filled successfully.
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||||
* @return false if vector sizes do not match or resizing @p c failed.
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||||
*/
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||||
template <typename T>
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bool div(const panic::tensor::matrix<T>& A, const panic::tensor::matrix<T>& B, panic::tensor::matrix<T>& C);
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||||
/**
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||||
* @brief Returns a new matrix containing a matrix divided elementwise.
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||||
*
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||||
* Computes:
|
||||
* @code
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||||
* result(i,j) = A(i,j) / B(i,j)
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||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A Input matrix.
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||||
* @param B Second matrix. Must have size of @p A.
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||||
*
|
||||
* @return A new matrix containing the result.
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||||
* @return An empty matrix if the operation fails.
|
||||
*
|
||||
* @note This overload is convenient, but may allocate a new vector.
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||||
*/
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||||
template <typename T>
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||||
panic::tensor::matrix<T> div(const panic::tensor::matrix<T>& A, const panic::tensor::matrix<T>& B);
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||||
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||||
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||||
/**
|
||||
* @brief Divides a vector rowwise too a matrix.
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||||
*
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||||
* Computes:
|
||||
* @code
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||||
* C(i,j) = A(i,j) / b[j]
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||||
* @endcode
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||||
*
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||||
* @tparam T Numeric element type.
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||||
* @param A Matrix.
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||||
* @param b Vector. Must have size of @p A.cols().
|
||||
* @param C Output matrix. Resized to match @p A.
|
||||
*
|
||||
* @return true if @p C was resized and filled successfully.
|
||||
* @return false if vector sizes do not match or resizing @p c failed.
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||||
*/
|
||||
template <typename T>
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||||
bool div_rowwise(const panic::tensor::matrix<T>& A, const panic::tensor::vector<T>& b, panic::tensor::matrix<T>& C);
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||||
|
||||
/**
|
||||
* @brief Divides a vector rowwise too a matrix.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* result(i,j) = A(i,j) / b[j]
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A Matrix.
|
||||
* @param b Vector. Must have size of @p A.cols().
|
||||
*
|
||||
* @return A new matrix containing the result.
|
||||
* @return An empty matrix if the operation fails.
|
||||
*
|
||||
* @note This overload is convenient, but may allocate a new vector.
|
||||
*/
|
||||
template <typename T>
|
||||
panic::tensor::matrix<T> div_rowwise(const panic::tensor::matrix<T>& A, const panic::tensor::vector<T>& b);
|
||||
|
||||
/**
|
||||
* @brief Divides a vector colwise too a matrix.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* C(i,j) = A(i,j) / b[i]
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A Matrix.
|
||||
* @param b Vector. Must have size of @p A.rows().
|
||||
* @param C Output matrix. Resized to match @p A.
|
||||
*
|
||||
* @return true if @p C was resized and filled successfully.
|
||||
* @return false if vector sizes do not match or resizing @p c failed.
|
||||
*/
|
||||
template <typename T>
|
||||
bool div_colwise(const panic::tensor::matrix<T>& A, const panic::tensor::vector<T>& b, panic::tensor::matrix<T>& C);
|
||||
|
||||
/**
|
||||
* @brief Divides a vector colwise too a matrix.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* result(i,j) = A(i,j) / b[i]
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A Matrix.
|
||||
* @param b Vector. Must have size of @p A.rows().
|
||||
*
|
||||
* @return A new matrix containing the result.
|
||||
* @return An empty matrix if the operation fails.
|
||||
*
|
||||
* @note This overload is convenient, but may allocate a new vector.
|
||||
*/
|
||||
template <typename T>
|
||||
panic::tensor::matrix<T> div_colwise(const panic::tensor::matrix<T>& A, const panic::tensor::vector<T>& b);
|
||||
|
||||
|
||||
|
||||
|
||||
} // namespace math
|
||||
} // namespace panic
|
||||
@@ -0,0 +1,286 @@
|
||||
/**++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
|
||||
*
|
||||
*
|
||||
* PANIC
|
||||
* Portable Algorithms and Numerics In C++
|
||||
*
|
||||
* Scientific computing from scratch, with feeling.
|
||||
*
|
||||
* Copyright (c) 2026 Michelle Bausager
|
||||
*
|
||||
* This file is part of PANIC.
|
||||
*
|
||||
* PANIC is free software licensed under the GNU General Public License v3.0 or later.
|
||||
* You may redistribute and/or modify it under the terms of the GPL.
|
||||
*
|
||||
* PANIC is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY;
|
||||
* without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
|
||||
* See the LICENSE file for the full license text.
|
||||
*
|
||||
* SPDX-License-Identifier: GPL-3.0-or-later
|
||||
*
|
||||
*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
|
||||
*
|
||||
* Project Name: PANIC
|
||||
* Module Name: math
|
||||
* File Name: sub.hpp
|
||||
* Revision: 0.1.0
|
||||
* Date: 25-06-2026
|
||||
* Author: Michelle Bausager
|
||||
*
|
||||
* Description:
|
||||
* Functions to subtracts panic::tensor togther;
|
||||
*
|
||||
*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*/
|
||||
#pragma once
|
||||
|
||||
#include <tensor/vector.hpp> // for panic::vector
|
||||
#include <tensor/matrix.hpp> // for panic::matrix
|
||||
|
||||
namespace panic{
|
||||
namespace math{
|
||||
|
||||
|
||||
/**
|
||||
* @brief Subs a scalar to every element of a vector.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* c[i] = a[i] - k
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param a Input vector.
|
||||
* @param k Scalar value added to each element of @p a.
|
||||
* @param c Output vector. Resized to match @p a.
|
||||
*
|
||||
* @return true if @p c was resized and filled successfully.
|
||||
* @return false if resizing @p c failed.
|
||||
*
|
||||
* @note This overload writes the result into an existing vector to avoid
|
||||
* unnecessary temporary allocations.
|
||||
*/
|
||||
template <typename T>
|
||||
bool sub(const panic::tensor::vector<T>& a, const T k, panic::tensor::vector<T>& c);
|
||||
|
||||
/**
|
||||
* @brief Returns a new vector containing a scalar subtraced to every element.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* result[i] = a[i] - k
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param a Input vector.
|
||||
* @param k Scalar value subtracted to each element of @p a.
|
||||
*
|
||||
* @return A new vector containing the result.
|
||||
* @return An empty vector if the operation fails.
|
||||
*
|
||||
* @note This overload is convenient, but may allocate a new vector.
|
||||
*/
|
||||
template <typename T>
|
||||
panic::tensor::vector<T> sub(const panic::tensor::vector<T>& a, const T k);
|
||||
|
||||
/**
|
||||
* @brief subtracts a vector elementwise too a vector.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* c[i] = a[i] - b[i]
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param a First vector.
|
||||
* @param b Second vector. Must have size of @p a
|
||||
* @param c Output vector. Resized to match @p a.
|
||||
*
|
||||
* @return true if @p c was resized and filled successfully.
|
||||
* @return false if vector sizes do not match or resizing @p c failed.
|
||||
*/
|
||||
template <typename T>
|
||||
bool sub(const panic::tensor::vector<T>& a, const panic::tensor::vector<T>& b, panic::tensor::vector<T>& c);
|
||||
|
||||
/**
|
||||
* @brief Returns a new vector containing a vector subtracted elementwise.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* result[i] = a[i] - b[i]
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param a First vector.
|
||||
* @param b Second vector. Must have size of @p a
|
||||
* @param k Scalar value subtracted to each element of @p a.
|
||||
*
|
||||
* @return A new vector containing the result.
|
||||
* @return An empty vector if the operation fails.
|
||||
*
|
||||
* @note This overload is convenient, but may allocate a new vector.
|
||||
*/
|
||||
template <typename T>
|
||||
panic::tensor::vector<T> sub(const panic::tensor::vector<T>& a, const panic::tensor::vector<T>& b);
|
||||
|
||||
/**
|
||||
* @brief subtracts a scalar to every element of a matix.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* C(i,j) = A(i,j) - k
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A Input matrix.
|
||||
* @param k Scalar value added to each element of @p A.
|
||||
* @param C Output Matrix. Resized to match @p A.
|
||||
*
|
||||
* @return true if @p C was resized and filled successfully.
|
||||
* @return false if resizing @p C failed.
|
||||
*
|
||||
* @note This overload writes the result into an existing vector to avoid
|
||||
* unnecessary temporary allocations.
|
||||
*/
|
||||
template <typename T>
|
||||
bool sub(const panic::tensor::matrix<T>& A, const T k, panic::tensor::matrix<T>& C);
|
||||
|
||||
/**
|
||||
* @brief Returns a new matrix containing a scalar subtracted to every element.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* result(i,j) = A(i,j) - k
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A Input matrix.
|
||||
* @param k Scalar value subtracted to each element of @p A.
|
||||
*
|
||||
* @return A new matrix containing the result.
|
||||
* @return An empty matrix if the operation fails.
|
||||
*
|
||||
* @note This overload is convenient, but may allocate a new vector.
|
||||
*/
|
||||
template <typename T>
|
||||
panic::tensor::matrix<T> sub(const panic::tensor::matrix<T>& A, const T k);
|
||||
|
||||
/**
|
||||
* @brief subtracts a matrix elementwise too a matrix.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* C(i,j) = A(i,j) - B(i,j)
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A First matrix.
|
||||
* @param B Second matrix. Must have size of @p A.
|
||||
* @param C Output matrix. Resized to match @p A.
|
||||
*
|
||||
* @return true if @p C was resized and filled successfully.
|
||||
* @return false if vector sizes do not match or resizing @p c failed.
|
||||
*/
|
||||
template <typename T>
|
||||
bool sub(const panic::tensor::matrix<T>& A, const panic::tensor::matrix<T>& B, panic::tensor::matrix<T>& C);
|
||||
|
||||
/**
|
||||
* @brief Returns a new matrix containing a matrix subtracted elementwise.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* result(i,j) = A(i,j) - B(i,j)
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A Input matrix.
|
||||
* @param B Second matrix. Must have size of @p A.
|
||||
*
|
||||
* @return A new matrix containing the result.
|
||||
* @return An empty matrix if the operation fails.
|
||||
*
|
||||
* @note This overload is convenient, but may allocate a new vector.
|
||||
*/
|
||||
template <typename T>
|
||||
panic::tensor::matrix<T> sub(const panic::tensor::matrix<T>& A, const panic::tensor::matrix<T>& B);
|
||||
|
||||
/**
|
||||
* @brief subtracts a vector rowwise too a matrix.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* C(i,j) = A(i,j) - b[j]
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A Matrix.
|
||||
* @param b Vector. Must have size of @p A.cols().
|
||||
* @param C Output matrix. Resized to match @p A.
|
||||
*
|
||||
* @return true if @p C was resized and filled successfully.
|
||||
* @return false if vector sizes do not match or resizing @p c failed.
|
||||
*/
|
||||
template <typename T>
|
||||
bool sub_rowwise(const panic::tensor::matrix<T>& A, const panic::tensor::vector<T>& b, panic::tensor::matrix<T>& C);
|
||||
|
||||
/**
|
||||
* @brief subtracts a vector rowwise too a matrix.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* result(i,j) = A(i,j) - b[j]
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A Matrix.
|
||||
* @param b Vector. Must have size of @p A.cols().
|
||||
*
|
||||
* @return A new matrix containing the result.
|
||||
* @return An empty matrix if the operation fails.
|
||||
*
|
||||
* @note This overload is convenient, but may allocate a new vector.
|
||||
*/
|
||||
template <typename T>
|
||||
panic::tensor::matrix<T> sub_rowwise(const panic::tensor::matrix<T>& A, const panic::tensor::vector<T>& b);
|
||||
|
||||
/**
|
||||
* @brief subtracts a vector colwise too a matrix.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* C(i,j) = A(i,j) - b[i]
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A Matrix.
|
||||
* @param b Vector. Must have size of @p A.rows().
|
||||
* @param C Output matrix. Resized to match @p A.
|
||||
*
|
||||
* @return true if @p C was resized and filled successfully.
|
||||
* @return false if vector sizes do not match or resizing @p c failed.
|
||||
*/
|
||||
template <typename T>
|
||||
bool sub_colwise(const panic::tensor::matrix<T>& A, const panic::tensor::vector<T>& b, panic::tensor::matrix<T>& C);
|
||||
|
||||
/**
|
||||
* @brief subtracts a vector colwise too a matrix.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* result(i,j) = A(i,j) - b[i]
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A Matrix.
|
||||
* @param b Vector. Must have size of @p A.rows().
|
||||
*
|
||||
* @return A new matrix containing the result.
|
||||
* @return An empty matrix if the operation fails.
|
||||
*
|
||||
* @note This overload is convenient, but may allocate a new vector.
|
||||
*/
|
||||
template <typename T>
|
||||
panic::tensor::matrix<T> sub_colwise(const panic::tensor::matrix<T>& A, const panic::tensor::vector<T>& b);
|
||||
|
||||
} // namespace math
|
||||
} // namespace panic
|
||||
@@ -0,0 +1,158 @@
|
||||
/**++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
|
||||
*
|
||||
* PANIC
|
||||
* Portable Algorithms and Numerics In C++
|
||||
*
|
||||
* Scientific computing from scratch, with feeling.
|
||||
*
|
||||
* Copyright (c) 2026 Michelle Bausager
|
||||
*
|
||||
* This file is part of PANIC.
|
||||
*
|
||||
* PANIC is free software licensed under the GNU General Public License v3.0 or later.
|
||||
* You may redistribute and/or modify it under the terms of the GPL.
|
||||
*
|
||||
* PANIC is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY;
|
||||
* without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
|
||||
* See the LICENSE file for the full license text.
|
||||
*
|
||||
* SPDX-License-Identifier: GPL-3.0-or-later
|
||||
*
|
||||
*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
|
||||
*
|
||||
* Project Name: PANIC
|
||||
* Module Name: math
|
||||
* File Name: sum.hpp
|
||||
* Revision: 0.1.0
|
||||
* Date: 25-06-2026
|
||||
* Author: Michelle Bausager
|
||||
*
|
||||
* Description:
|
||||
* Functions to sum up arrays
|
||||
*
|
||||
*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*/
|
||||
#pragma once
|
||||
|
||||
#include <tensor/vector.hpp> // for panic::vector
|
||||
#include <tensor/matrix.hpp> // for panic::matrix
|
||||
|
||||
namespace panic{
|
||||
namespace math{
|
||||
|
||||
|
||||
|
||||
|
||||
/**
|
||||
* @brief Returns the sum value of a vector
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* result = sum(a)
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param a Input vector.
|
||||
*
|
||||
* @return A new vector containing the result.
|
||||
* @return An empty vector if the operation fails.
|
||||
*
|
||||
* @note This overload is convenient, but may allocate a new vector.
|
||||
*/
|
||||
template <typename T>
|
||||
T sum(const panic::tensor::vector<T>& a);
|
||||
|
||||
/**
|
||||
* @brief Returns the sum value of a matrix.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* result = sum(A)
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A Input matrix.
|
||||
*
|
||||
* @return A new matrix containing the result.
|
||||
* @return An empty matrix if the operation fails.
|
||||
*
|
||||
*/
|
||||
template <typename T>
|
||||
T sum(const panic::tensor::matrix<T>& A);
|
||||
|
||||
/**
|
||||
* @brief Find the sum values row-wise of a matrix.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* c(i) = sum(A(i,j))
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A Input matrix.
|
||||
* @param c Output vector. Resized to match @p A.cols().
|
||||
*
|
||||
* @return true if @p c was resized and filled successfully.
|
||||
* @return false if vector sizes do not match or resizing @p c failed.
|
||||
*/
|
||||
template <typename T>
|
||||
bool sum_rowwise(const panic::tensor::matrix<T>& A, panic::tensor::vector<T>& c);
|
||||
|
||||
/**
|
||||
* @brief Returns a new matrix containing the sum row-wise elementwise.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* result[i] = sum(A(i,j))
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A Input matrix.
|
||||
*
|
||||
* @return A new matrix containing the result.
|
||||
* @return An empty matrix if the operation fails.
|
||||
*
|
||||
* @note This overload is convenient, but may allocate a new vector.
|
||||
*/
|
||||
template <typename T>
|
||||
panic::tensor::vector<T> sum_rowwise(const panic::tensor::matrix<T>& A);
|
||||
|
||||
|
||||
/**
|
||||
* @brief Find the sumation values column-wise of a matrix.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* C(j) = sum(A(i,j))
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A Input matrix.
|
||||
* @param C Output matrix. Resized to match @p A.rows().
|
||||
*
|
||||
* @return true if @p c was resized and filled successfully.
|
||||
* @return false if vector sizes do not match or resizing @p c failed.
|
||||
*/
|
||||
template <typename T>
|
||||
bool sum_colwise(const panic::tensor::matrix<T>& A, panic::tensor::vector<T>& c);
|
||||
|
||||
/**
|
||||
* @brief Returns a new matrix containing the sumation column-wise elementwise.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* result[j] = sum(A(i,j))
|
||||
* @endcode
|
||||
*
|
||||
* @tparam T Numeric element type.
|
||||
* @param A Input matrix.
|
||||
*
|
||||
* @return A new matrix containing the result.
|
||||
* @return An empty matrix if the operation fails.
|
||||
*
|
||||
* @note This overload is convenient, but may allocate a new vector.
|
||||
*/
|
||||
template <typename T>
|
||||
panic::tensor::vector<T> sum_colwise(const panic::tensor::matrix<T>& A);
|
||||
|
||||
} // namespace math
|
||||
} // namespace panic
|
||||
+4
-4
@@ -22,7 +22,7 @@
|
||||
*
|
||||
* Project Name: PANIC
|
||||
* Module Name: neural_network
|
||||
* File Name: activation_ReLU.hpp
|
||||
* File Name: activation_relu.hpp
|
||||
* Revision: 0.1.0
|
||||
* Date: 29-08-2026
|
||||
* Author: Michelle Bausager
|
||||
@@ -56,19 +56,19 @@ namespace panic{
|
||||
*
|
||||
* The struct is used in PANIC nural_network library.
|
||||
*/
|
||||
struct activation_ReLU : public layer{
|
||||
struct activation_relu : public layer{
|
||||
|
||||
/**
|
||||
* @brief Empthy constructor
|
||||
*
|
||||
*/
|
||||
activation_ReLU();
|
||||
activation_relu();
|
||||
|
||||
/**
|
||||
* @brief Default de-constructor
|
||||
*
|
||||
*/
|
||||
~activation_ReLU() = default;
|
||||
~activation_relu() = default;
|
||||
|
||||
/**
|
||||
* @brief Forward function for layer
|
||||
@@ -0,0 +1,94 @@
|
||||
/**++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
|
||||
*
|
||||
* PANIC
|
||||
* Portable Algorithms and Numerics In C++
|
||||
*
|
||||
* Scientific computing from scratch, with feeling.
|
||||
*
|
||||
* Copyright (c) 2026 Michelle Bausager
|
||||
*
|
||||
* This file is part of PANIC.
|
||||
*
|
||||
* PANIC is free software licensed under the GNU General Public License v3.0 or later.
|
||||
* You may redistribute and/or modify it under the terms of the GPL.
|
||||
*
|
||||
* PANIC is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY;
|
||||
* without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
|
||||
* See the LICENSE file for the full license text.
|
||||
*
|
||||
* SPDX-License-Identifier: GPL-3.0-or-later
|
||||
*
|
||||
*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
|
||||
*
|
||||
* Project Name: PANIC
|
||||
* Module Name: neural_network
|
||||
* File Name: activation_softmax.hpp
|
||||
* Revision: 0.1.0
|
||||
* Date: 29-08-2026
|
||||
* Author: Michelle Bausager
|
||||
*
|
||||
* Description:
|
||||
* Defines the activation layer for Softmax
|
||||
*
|
||||
*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*/
|
||||
#pragma once
|
||||
|
||||
//---------------------------------------------------------------------------------------------------------------------------
|
||||
// INCLUDE DESCRIPTION
|
||||
//---------------------------------------------------------------------------------------------------------------------------
|
||||
#include <config/types.hpp> // panic::uint_t, panic::int_t, and panic::real_t
|
||||
#include <neural_network/layer/layer.hpp> // for base layer struct
|
||||
|
||||
#include <tensor/matrix.hpp>
|
||||
|
||||
|
||||
namespace panic{
|
||||
namespace neural_network{
|
||||
|
||||
/**
|
||||
* @brief struct for softmax activation layer used in neural networks
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* panic::neural_network::activation_softmax myactivation();
|
||||
* myactivation.forward(inputMatrix);
|
||||
* @endcode
|
||||
*
|
||||
* The struct is used in PANIC nural_network library.
|
||||
*/
|
||||
struct activation_softmax : public layer{
|
||||
|
||||
/**
|
||||
* @brief Empthy constructor
|
||||
*
|
||||
*/
|
||||
activation_softmax();
|
||||
|
||||
/**
|
||||
* @brief Default de-constructor
|
||||
*
|
||||
*/
|
||||
~activation_softmax() = default;
|
||||
|
||||
/**
|
||||
* @brief Forward function for layer
|
||||
*
|
||||
* @param inputs Data input for forward pass.
|
||||
*
|
||||
* @Note Calculates -> outputs = inputs * weights + biases
|
||||
*/
|
||||
bool forward(const panic::tensor::real_matrix& inputs);
|
||||
|
||||
/**
|
||||
* @brief Backward function for layer
|
||||
*
|
||||
* @param inputs Data input for bacward pass.
|
||||
*
|
||||
* @Note Calculates derivative of forward function.
|
||||
*/
|
||||
bool backward(const panic::tensor::real_matrix& dinpus);
|
||||
};
|
||||
|
||||
} // namespace tensor
|
||||
} // namespace panic
|
||||
|
||||
@@ -143,7 +143,7 @@ struct model{
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* model.add_activation_ReLU(3,4);
|
||||
* model.add_activation_relu(3,4);
|
||||
* @endcode
|
||||
*
|
||||
*
|
||||
@@ -151,7 +151,23 @@ struct model{
|
||||
*
|
||||
* @note This function is convenient, but it allocates a new layer.
|
||||
*/
|
||||
bool add_activation_ReLU();
|
||||
bool add_activation_relu();
|
||||
|
||||
/**
|
||||
* @brief Adds a activation Softmax layer to the model.
|
||||
*
|
||||
* Computes:
|
||||
* @code
|
||||
* model.add_activation_softmax(3,4);
|
||||
* @endcode
|
||||
*
|
||||
*
|
||||
* @return true if layer is added
|
||||
*
|
||||
* @note This function is convenient, but it allocates a new layer.
|
||||
*/
|
||||
bool add_activation_softmax();
|
||||
|
||||
|
||||
/**
|
||||
* @brief Loops over all layers forward function
|
||||
|
||||
Reference in New Issue
Block a user