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…base class - Change Step() to virtual with default implementation - Add pure virtual ComputeLR() for subclasses to implement. - Adapt test helpers (IdentityScheduler, LinearDecayScheduler) to implement ComputeLR() instead of Step(). - All existing tests pass without behavioral changes. BREAKING CHANGE: Subclasses must implement ComputeLR() instead of Step().
…t and update all tests to use Create<T>() factory method.
…entialLR - enhance LRScheduler with chained and closed form learning rate methods - adapt methods(Step, InitialStep, GetClosedFormLR, GetChainedFormLR) to match PyTorch‘s design - add tests for consistency - refactor LinearLR: add end_factor, and rename this class - add SequentialLR InitialStep and UndoChildInitialSteps BREAKING CHANGE: Subclasses must implement GetClosedFormLR instead of ComputeLR(). Should use LinearLR instead of LinearwarmupLR.
- Add LRSchedulerConfig struct with parameters for all basic schedulers(constant, linear, step) - Add CreateLRScheduler() factory function - Support automatic warmup wrapping via SequentialLR when warmup_steps > 0 - Adapt test files
…tial, Chained, and Lambda)
…ommon total_iters
- Add gflags: --lr_scheduler, --warmup_steps, --step_size, --gamma, --start_factor, --end_factor, --lr_total_iters, --total_steps - Replace nullptr scheduler with factory-created scheduler - Move scheduler.Step() after optimizer.Step() in both DP and PP paths - Replace hardcoded FLAGS_learning_rate in log with scheduler->GetLR()
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