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* sampling: enhance penalty handling in common_sampler_init - Set default value for penalty_last_n based on model context if not specified. - Ensure penalty_last_n and n_prev are non-negative. - Update llama_sampler_penalties structure to inherit from llama_sampler_backend and add backend input handling for penalties. - Implement backend initialization and application logic for penalties, including frequency and presence adjustments. * tests: add backend penalties sampling tests and utility functions - Introduced `accept_prompt` and `unique_prompt_tokens` functions to handle prompt acceptance and token uniqueness. - Implemented `compare_penalties_logits` to compare logits from backend and CPU samplers with penalties. - Added `test_backend_penalties_sampling` to validate backend penalties with various configurations. - Enhanced the test suite for better coverage of penalty handling in sampling. * sampling: add support for top-k penalties in backend sampling * sampling: add fix to ensure stable numerical results. Preserve masked logits as -Inf and no longer generate NaN. * sampling: enhance penalty comparison tests with masking penalties logic * add comments on padding * sampling: add comments on modifications * add the unit test to cover masked-out token as -INF * validate repeat penalty to ensure it is finite and greater than 0; add tests for invalid values * refactor: test functions to share logic and be less verbose * add test to cover case where previously penalized token is not part of candidates * remove comments * remove redundant penalty_last_n initialization and validation in common_sampler_init * add support for penalties in sampler chain with configurable positions * add validation for penalty parameters and enhance tests for non-finite values * add context parameter to common_sampler_init and set default for penalty_last_n * add llama_n_ctx parameter to common_sampler_init for improved sampler initialization * replace penalty_last_n x n_candidates comparison matrix with a vocabulary-sized count tensor * add tests for backend penalties sampling without filler entries , token_count.size() == n_active == n_max == 64 * add test for backend penalties sampling after top-p with large history window * remove as unused * add is_disabled method, tensor logits reshape, add rest review suggestions * clarify comment