Update project name

include/aidge/learningRate/LRScheduler.hpp

-/********************************************************************************
- * Copyright (c) 2023 CEA-List
- *
- * This program and the accompanying materials are made available under the
- * terms of the Eclipse Public License 2.0 which is available at
- * http://www.eclipse.org/legal/epl-2.0.
- *
- * SPDX-License-Identifier: EPL-2.0
- *
- ********************************************************************************/
-
-#ifndef AIDGE_CORE_OPTIMIZER_LRSCHEDULER_H_
-#define AIDGE_CORE_OPTIMIZER_LRSCHEDULER_H_
-
-#include <cstddef>     // std::size_t
-#include <functional>  // std::function
-#include <vector>
-
-namespace Aidge {
-
-/**
- * @class LRScheduler
- * @brief Manage the learning rate evolution.
- *
- */
-class LRScheduler {
-private:
-    /// @brief Current step
-    std::size_t mStep = 0;
-    /// @brief Pointer to LR update function. Takes a single float value as parameter.
-    std::function<float(float, const std::size_t)> mStepFunc;
-
-    /// @brief Current learning Rate
-    float mLR;
-    /// @brief Initial learning Rate passed in the constructor
-    float mInitialLR;
-
-    /// @brief Step LRScheduler switches from warmup to LR (>= 1)
-    std::size_t mSwitchStep;
-    /// @brief Initial Warm Up passed in the constructor
-    float mInitialWarmUp;
-
-public:
-    LRScheduler() = delete;
-
-    /**
-     * @brief Construct a new LRScheduler object. Default is ConstantLR.
-     *
-     * @param initialLR Initial learning rate.
-     * Will default to 0 if a negative value is passed.
-     * @param stepFunc Recursive update function for learning rate value.
-     * Default is the Constant function.
-     * @param nb_warmup_steps Number of warm-up steps before starting to use
-     * ``stepFunc`` for learning rate update. If specified, learning rate will
-     * linearly increase from 0 to ``initialLR``.
-     * Default is 0.
-     */
-    LRScheduler(const float initialLR,
-                std::function<float(float, const std::size_t)> stepFunc = [](float val, const std::size_t /*step*/) { return val; },
-                const std::size_t nb_warmup_steps = 0)
-        : mStepFunc(stepFunc),
-          mLR((initialLR > 0.0f) ? initialLR : 0.0f),
-          mInitialLR(mLR),
-          mSwitchStep(nb_warmup_steps + 1),
-          mInitialWarmUp(mLR / static_cast<float>(nb_warmup_steps + 1))
-    {
-        // ctor
-    }
-
-    // Copy constructor
-    LRScheduler(const LRScheduler& other)
-        : mStep(other.mStep),
-          mStepFunc(other.mStepFunc),
-          mLR(other.mLR),
-          mInitialLR(other.mInitialLR),
-          mSwitchStep(other.mSwitchStep),
-          mInitialWarmUp(other.mInitialWarmUp)
-    {
-        // Copy constructor implementation
-    }
-
-    LRScheduler& operator=(const LRScheduler&) = default;
-    // LRScheduler(LRScheduler&&)      = default;
-
-public:
-    // Getters & setters
-    constexpr inline float learningRate() const noexcept { return mLR; }
-
-    constexpr void setNbWarmupSteps(const std::size_t nb_warmup_steps) noexcept {
-        mSwitchStep = nb_warmup_steps + 1;
-        mInitialWarmUp = mLR / static_cast<float>(nb_warmup_steps + 1);
-    }
-
-    /**
-     * @brief Update the learning rate to the next value.
-     * @note If the current step is lower than the switch step, the learning rate follows
-     * a linear function from 0 to the initial learning rate
-     * @note Else, the learning rate is updated using the provided function.
-     */
-    constexpr void update() {
-        mLR = (mStep++ < mSwitchStep) ?
-                static_cast<float>(mStep) *  mInitialWarmUp :
-                mStepFunc(mLR, mStep);
-    };
-
-    std::vector<float> lr_profiling(const std::size_t nbStep) const;
-
-    constexpr void reset() noexcept {
-        mStep = 0;
-        mLR = mInitialLR;
-    }
-};
-
-} // namespace Aidge
-
-#endif /* AIDGE_CORE_OPTIMIZER_LRSCHEDULER_H_ */

include/aidge/learningRate/LRSchedulerList.hpp

-/********************************************************************************
- * Copyright (c) 2023 CEA-List
- *
- * This program and the accompanying materials are made available under the
- * terms of the Eclipse Public License 2.0 which is available at
- * http://www.eclipse.org/legal/epl-2.0.
- *
- * SPDX-License-Identifier: EPL-2.0
- *
- ********************************************************************************/
-
-#ifndef AIDGE_CORE_OPTIMIZER_LRSCHEDULERSLIST_H_
-#define AIDGE_CORE_OPTIMIZER_LRSCHEDULERSLIST_H_
-
-#include "aidge/optimizer/LR/LRScheduler.hpp"
-
-#include <cstddef>  // std::size_t
-
-namespace Aidge {
-
-LRScheduler ConstantLR(const float initialLR) {
-    return LRScheduler(initialLR);
-}
-
-
-LRScheduler StepLR(const float initialLR, const std::size_t stepSize, float gamma = 0.1f) {
-    return LRScheduler(initialLR,
-                    [stepSize, gamma](float val, const std::size_t step) {
-                        return (step % stepSize == 0) ? val*gamma : val;
-                    });
-}
-} // namespace Aidge
-
-#endif /* AIDGE_CORE_OPTIMIZER_LRSCHEDULERSLIST_H_ */
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project_name.txt

-aidge_learning
+aidge_learning
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