SYMBOL INDEX (178 symbols across 17 files)

FILE: mlx_lm_lora/synthetic_prompts.py
  function parse_args (line 38) | def parse_args():
  function load_documents (line 125) | def load_documents(docs_dir: str) -> List[Dict[str, str]]:
  function create_generation_prompt (line 169) | def create_generation_prompt(
  function clean_latex_for_json (line 210) | def clean_latex_for_json(text: str) -> str:
  function generate_dataset (line 223) | def generate_dataset(args):
  function main (line 434) | def main():

FILE: mlx_lm_lora/train.py
  function load_reward_functions_from_file (line 139) | def load_reward_functions_from_file(file_path):
  function calculate_iters (line 156) | def calculate_iters(train_set, batch_size, epochs) -> int:
  function load_reference_model (line 166) | def load_reference_model(args):
  function load_judge_model (line 177) | def load_judge_model(args, reference_model=None):
  function build_parser (line 194) | def build_parser():
  function train_model (line 504) | def train_model(
  function evaluate_model (line 772) | def evaluate_model(
  function build_lora_config (line 1046) | def build_lora_config(args):
  function run (line 1060) | def run(args, training_callback: TrainingCallback = None):
  function main (line 1168) | def main(args=None):

FILE: mlx_lm_lora/train_judge.py
  function load_reward_functions_from_file (line 82) | def load_reward_functions_from_file(file_path):
  function calculate_iters (line 100) | def calculate_iters(train_set, batch_size, epochs) -> int:
  function build_parser (line 110) | def build_parser():
  function train_model (line 257) | def train_model(
  function evaluate_model (line 345) | def evaluate_model(args, model: nn.Module, tokenizer, test_set):
  function run (line 359) | def run(args, training_callback: TrainingCallback = None):
  function main (line 430) | def main(args=None):

FILE: mlx_lm_lora/trainer/cpo_trainer.py
  function get_token_scores (line 19) | def get_token_scores(model, x, mask, cache=None):
  function compute_score (line 25) | def compute_score(scores, mask, loss_type):
  function cpo_loss (line 30) | def cpo_loss(
  function iterate_cpo_batches (line 80) | def iterate_cpo_batches(dataset, batch_size, max_seq_length, train=False):
  function evaluate_cpo (line 139) | def evaluate_cpo(
  function train_cpo (line 210) | def train_cpo(

FILE: mlx_lm_lora/trainer/datasets.py
  class GRPODataset (line 10) | class GRPODataset:
    method __init__ (line 11) | def __init__(
    method __getitem__ (line 44) | def __getitem__(self, idx: int) -> Tuple[List[int], List[int], str, str]:
    method __len__ (line 47) | def __len__(self) -> int:
    method process (line 50) | def process(self, d):
  class PreferenceDataset (line 54) | class PreferenceDataset:
    method __init__ (line 55) | def __init__(
    method __getitem__ (line 69) | def __getitem__(self, idx: int):
    method __len__ (line 72) | def __len__(self):
    method process (line 75) | def process(self, d):
  class JudgeDataset (line 79) | class JudgeDataset:
    method __init__ (line 80) | def __init__(
    method process (line 100) | def process(self, d):
    method __getitem__ (line 132) | def __getitem__(self, idx: int):
    method __len__ (line 135) | def __len__(self):
  class PromptDataset (line 139) | class PromptDataset:
    method __init__ (line 140) | def __init__(
    method process (line 150) | def process(self, d):
    method __getitem__ (line 170) | def __getitem__(self, idx: int):
    method __len__ (line 173) | def __len__(self):
  class DPODataset (line 177) | class DPODataset:
    method __init__ (line 178) | def __init__(
    method __getitem__ (line 217) | def __getitem__(self, idx: int):
    method __len__ (line 220) | def __len__(self):
    method process (line 223) | def process(self, d):
  class ORPODataset (line 227) | class ORPODataset:
    method __init__ (line 228) | def __init__(
    method _extract_content (line 320) | def _extract_content(self, data):
    method __len__ (line 339) | def __len__(self):
    method process (line 342) | def process(self, d):
    method __getitem__ (line 345) | def __getitem__(self, idx: int):
  class TextDataset (line 353) | class TextDataset:
    method __init__ (line 358) | def __init__(
    method process (line 368) | def process(self, d):
    method __getitem__ (line 374) | def __getitem__(self, idx: int):
    method __len__ (line 377) | def __len__(self):
  class ChatDataset (line 381) | class ChatDataset:
    method __init__ (line 387) | def __init__(
    method process (line 399) | def process(self, d):
    method __getitem__ (line 418) | def __getitem__(self, idx: int):
    method __len__ (line 421) | def __len__(self):
  class CompletionsDataset (line 425) | class CompletionsDataset:
    method __init__ (line 432) | def __init__(
    method process (line 446) | def process(self, d):
    method __getitem__ (line 469) | def __getitem__(self, idx: int):
    method __len__ (line 472) | def __len__(self):
  class ConcatenatedDataset (line 476) | class ConcatenatedDataset:
    method __init__ (line 477) | def __init__(self, data: List[Any]):
    method __getitem__ (line 481) | def __getitem__(self, idx: int):
    method process (line 491) | def process(self, d):
    method __len__ (line 494) | def __len__(self):
  class CacheDataset (line 498) | class CacheDataset:
    method __init__ (line 499) | def __init__(self, data: Any):
    method itemlen (line 503) | def itemlen(self, idx: int):
    method __getitem__ (line 506) | def __getitem__(self, idx: int):
    method __len__ (line 511) | def __len__(self):
  function create_dataset (line 515) | def create_dataset(
  function load_local_dataset (line 612) | def load_local_dataset(
  function load_hf_dataset (line 629) | def load_hf_dataset(
  function load_custom_hf_dataset (line 656) | def load_custom_hf_dataset(args, tokenizer: PreTrainedTokenizer):
  function load_dataset (line 715) | def load_dataset(args, tokenizer: PreTrainedTokenizer):

FILE: mlx_lm_lora/trainer/dpo_trainer.py
  class DPOTrainingArgs (line 25) | class DPOTrainingArgs(SFTTrainingArgs):
  function get_token_scores (line 44) | def get_token_scores(model, x, mask, cache=None):
  function compute_score (line 50) | def compute_score(scores, mask, loss_type):
  function dpo_loss (line 55) | def dpo_loss(
  function iterate_dpo_batches (line 110) | def iterate_dpo_batches(dataset, batch_size, max_seq_length, train=False):
  function evaluate_dpo (line 169) | def evaluate_dpo(
  function train_dpo (line 261) | def train_dpo(

FILE: mlx_lm_lora/trainer/grpo_reward_functions.py
  function register_reward_function (line 12) | def register_reward_function(name: str = None):
  function get_reward_function (line 38) | def get_reward_function(name: str) -> RewardFunctions:
  function get_default_reward_functions (line 58) | def get_default_reward_functions() -> List[RewardFunctions]:
  function list_available_reward_functions (line 71) | def list_available_reward_functions() -> List[str]:
  function r1_extract_xml_answer (line 78) | def r1_extract_xml_answer(text: str) -> str:
  function r1_int_reward_func (line 89) | def r1_int_reward_func(
  function r1_accuracy_reward_func (line 99) | def r1_accuracy_reward_func(
  function r1_soft_format_reward_func (line 111) | def r1_soft_format_reward_func(
  function r1_strict_format_reward_func (line 145) | def r1_strict_format_reward_func(
  function r1_count_xml (line 156) | def r1_count_xml(

FILE: mlx_lm_lora/trainer/grpo_trainer.py
  class GRPOTrainingArgs (line 28) | class GRPOTrainingArgs(SFTTrainingArgs):
  function get_per_token_logps (line 91) | def get_per_token_logps(model: nn.Module, inputs, lengths):
  function generate_grpo (line 112) | def generate_grpo(
  function calculate_rewards_and_advantages (line 205) | def calculate_rewards_and_advantages(
  function grpo_loss (line 351) | def grpo_loss(
  function iterate_grpo_batches (line 540) | def iterate_grpo_batches(dataset, batch_size, max_seq_length, train=False):
  function evaluate_grpo (line 593) | def evaluate_grpo(
  function train_grpo (line 737) | def train_grpo(

FILE: mlx_lm_lora/trainer/judge.py
  class LLMPairwiseJudge (line 175) | class LLMPairwiseJudge:
    method __init__ (line 176) | def __init__(
    method judge (line 188) | def judge(
  class LLMPPOJudge (line 233) | class LLMPPOJudge:
    method __init__ (line 234) | def __init__(
    method judge (line 246) | def judge(
  class HumanPairwiseJudge (line 315) | class HumanPairwiseJudge:
    method __init__ (line 316) | def __init__(
    method judge (line 322) | def judge(

FILE: mlx_lm_lora/trainer/online_dpo_trainer.py
  class OnlineDPOTrainingArgs (line 24) | class OnlineDPOTrainingArgs(SFTTrainingArgs):
  function generate_for_online_dpo (line 61) | def generate_for_online_dpo(
  function compute_score (line 99) | def compute_score(scores, mask, loss_type):
  function online_dpo_loss (line 106) | def online_dpo_loss(
  function iterate_online_dpo_batches (line 162) | def iterate_online_dpo_batches(dataset, batch_size, max_seq_length, trai...
  function evaluate_online_dpo (line 190) | def evaluate_online_dpo(
  function train_online_dpo (line 367) | def train_online_dpo(

FILE: mlx_lm_lora/trainer/orpo_trainer.py
  class ORPOTrainingArgs (line 25) | class ORPOTrainingArgs(SFTTrainingArgs):
  function get_logps (line 35) | def get_logps(model, tokens, mask, cache=None):
  function orpo_loss (line 54) | def orpo_loss(
  function iterate_orpo_batches (line 95) | def iterate_orpo_batches(dataset, batch_size, max_seq_length, train=False):
  function evaluate_orpo (line 170) | def evaluate_orpo(
  function train_orpo (line 228) | def train_orpo(

FILE: mlx_lm_lora/trainer/ppo_trainer.py
  class PPOTrainingArgs (line 25) | class PPOTrainingArgs(OnlineDPOTrainingArgs):
  function ppo_loss (line 31) | def ppo_loss(
  function evaluate_ppo (line 113) | def evaluate_ppo(
  function train_ppo (line 289) | def train_ppo(

FILE: mlx_lm_lora/trainer/rlhf_reinforce_trainer.py
  class RLHFReinforceTrainingArgs (line 22) | class RLHFReinforceTrainingArgs(SFTTrainingArgs):
  function compute_kl_penalty (line 35) | def compute_kl_penalty(logits_policy, logits_ref, masks):
  function rlhf_reinforce_loss (line 44) | def rlhf_reinforce_loss(
  function get_model_logits (line 90) | def get_model_logits(model, tokens, masks):
  function evaluate_rlhf_reinforce (line 97) | def evaluate_rlhf_reinforce(
  function train_rlhf_reinforce (line 220) | def train_rlhf_reinforce(

FILE: mlx_lm_lora/trainer/sft_trainer.py
  function reset_prompt_cache (line 25) | def reset_prompt_cache(cache):
  function _find_cache_offset (line 59) | def _find_cache_offset(cache):
  function grad_checkpoint (line 76) | def grad_checkpoint(layer):
  class SFTTrainingArgs (line 93) | class SFTTrainingArgs:
  function _symmetric_fake_quantize_tensor (line 162) | def _symmetric_fake_quantize_tensor(x, bits: int, group_size: int):
  function _install_qat_hooks (line 202) | def _install_qat_hooks(model, args: SFTTrainingArgs):
  function default_loss (line 243) | def default_loss(model, batch, lengths, cache=None):
  function iterate_batches (line 260) | def iterate_batches(
  function evaluate_sft (line 313) | def evaluate_sft(
  function train_sft (line 368) | def train_sft(

FILE: mlx_lm_lora/trainer/xpo_trainer.py
  class XPOTrainingArgs (line 25) | class XPOTrainingArgs(OnlineDPOTrainingArgs):
  function get_current_alpha (line 34) | def get_current_alpha(
  function xpo_loss (line 45) | def xpo_loss(
  function iterate_online_dpo_batches (line 129) | def iterate_online_dpo_batches(dataset, batch_size, max_seq_length, trai...
  function evaluate_xpo (line 157) | def evaluate_xpo(
  function train_xpo (line 335) | def train_xpo(

FILE: mlx_lm_lora/utils.py
  function calculate_iters (line 20) | def calculate_iters(train_set, batch_size, epochs) -> int:
  function find_lmstudio_models_path (line 30) | def find_lmstudio_models_path() -> Path:
  function save_pretrained (line 45) | def save_pretrained(
  function save_pretrained_merged (line 113) | def save_pretrained_merged(
  function from_pretrained (line 169) | def from_pretrained(
  function push_to_hub (line 245) | def push_to_hub(
  function save_to_lmstudio_merged (line 301) | def save_to_lmstudio_merged(
  function save_pretrained_merged_vision (line 336) | def save_pretrained_merged_vision(

FILE: mlx_lm_lora/visuals.py
  class Colors (line 1) | class Colors:
  function print_banner (line 26) | def print_banner():
  function print_info (line 46) | def print_info(message):
  function print_success (line 51) | def print_success(message):
  function print_warning (line 56) | def print_warning(message):
  function print_error (line 61) | def print_error(message):
  function print_section (line 66) | def print_section(title):