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Functions1,082 in github.com/cxcscmu/AutoGEO

↓ 1 callersFunctionmain
()
LLaMA-Factory/scripts/api_example/test_image.py:24
↓ 1 callersFunctionmain
()
LLaMA-Factory/tests/check_license.py:22
↓ 1 callersFunctionmean_dict_list
Calculate mean values for each key across a list of dictionaries. Args: dict_list: List of dictionaries with numeric values
autogeo/evaluation/aggregate_results.py:5
↓ 1 callersFunctionmerge_dataset
r"""Merge multiple datasets to a unified dataset.
LLaMA-Factory/src/llamafactory/data/data_utils.py:51
↓ 1 callersFunctionmerge_single_chunk
(chunk_index: int, chunk_rules: List[str])
autogeo/rules/merger.py:200
↓ 1 callersFunctionmini_rewrite_documents
Rewrite documents using AutoGEO Mini (local model). Args: model_path: Path to the model checkpoint data_dir: Directory contai
autogeo/rewriters/mini.py:407
↓ 1 callersMethodmonitor
r"""Monitorgit the training progress and logs.
LLaMA-Factory/src/llamafactory/webui/runner.py:404
↓ 1 callersMethododds_ratio_loss
r"""Compute ORPO's odds ratio (OR) loss for batched log probabilities of the policy model.
LLaMA-Factory/src/llamafactory/train/dpo/trainer.py:136
↓ 1 callersMethodon_log
(self, args: "TrainingArguments", state: "TrainerState", control: "TrainerControl", **kwargs)
LLaMA-Factory/src/llamafactory/train/callbacks.py:271
↓ 1 callersMethodon_save
(self, args: "TrainingArguments", state: "TrainerState", control: "TrainerControl", **kwargs)
LLaMA-Factory/src/llamafactory/train/callbacks.py:120
↓ 1 callersMethodon_step_end
(self, args: "TrainingArguments", state: "TrainerState", control: "TrainerControl", **kwargs)
LLaMA-Factory/src/llamafactory/train/callbacks.py:255
↓ 1 callersMethodon_train_begin
(self, args: "TrainingArguments", state: "TrainerState", control: "TrainerControl", **kwargs)
LLaMA-Factory/src/llamafactory/train/callbacks.py:238
↓ 1 callersMethodon_train_end
(self, args: "TrainingArguments", state: "TrainerState", control: "TrainerControl", **kwargs)
LLaMA-Factory/src/llamafactory/train/callbacks.py:245
↓ 1 callersFunctionparse_args
Parse command-line arguments for the e2b_router script. Arguments: --host (str): The hostname or IP address to bind the server to. D
open-r1/scripts/e2b_router.py:139
↓ 1 callersFunctionparse_args
Parse command-line arguments for the morph_router script. Arguments: --host (str): The hostname or IP address to bind the server to.
open-r1/scripts/morph_router.py:143
↓ 1 callersFunctionpatch_code
(text, lang)
open-r1/src/open_r1/utils/competitive_programming/code_patcher.py:89
↓ 1 callersFunctionpatch_config
( config: "PretrainedConfig", tokenizer: "PreTrainedTokenizer", model_args: "ModelArguments",
LLaMA-Factory/src/llamafactory/model/patcher.py:92
↓ 1 callersFunctionpatch_model
( model: "PreTrainedModel", tokenizer: "PreTrainedTokenizer", model_args: "ModelArguments", is
LLaMA-Factory/src/llamafactory/model/patcher.py:154
↓ 1 callersFunctionpatch_processor
( processor: "ProcessorMixin", tokenizer: "PreTrainedTokenizer", model_args: "ModelArguments", )
LLaMA-Factory/src/llamafactory/model/patcher.py:74
↓ 1 callersFunctionpatch_target_modules
r"""Freeze vision tower for VLM LoRA tuning.
LLaMA-Factory/src/llamafactory/model/model_utils/visual.py:182
↓ 1 callersFunctionpatch_tokenizer
(tokenizer: "PreTrainedTokenizer", model_args: "ModelArguments")
LLaMA-Factory/src/llamafactory/model/patcher.py:50
↓ 1 callersFunctionpatch_valuehead_model
(model: "AutoModelForCausalLMWithValueHead")
LLaMA-Factory/src/llamafactory/model/patcher.py:194
↓ 1 callersMethodppo_train
r"""Implement training loop for the PPO stage, like _inner_training_loop() in Huggingface's Trainer.
LLaMA-Factory/src/llamafactory/train/ppo/trainer.py:187
↓ 1 callersFunctionprepare_model_for_training
r"""Prepare the model before training. Include: (1) cast the layernorm in fp32 (2) make output embedding layer require grads (3) add
LLaMA-Factory/src/llamafactory/model/model_utils/checkpointing.py:141
↓ 1 callersFunctionprepare_valuehead_model
(model: "PreTrainedModel")
LLaMA-Factory/src/llamafactory/model/model_utils/valuehead.py:61
↓ 1 callersFunctionprint_attn_implementation
(config: "PretrainedConfig")
LLaMA-Factory/src/llamafactory/model/model_utils/attention.py:77
↓ 1 callersMethodprint_data_example
r"""Print a data example to stdout.
LLaMA-Factory/src/llamafactory/data/processor/processor_utils.py:43
↓ 1 callersFunctionprocess_example
(example, session, args, output_file, pbar)
open-r1/scripts/generate_reasoning.py:45
↓ 1 callersFunctionpush_to_hub_revision
Pushes the model to branch on a Hub repo.
open-r1/src/open_r1/utils/hub.py:39
↓ 1 callersFunctionread_cloud_json
r"""Read a JSON/JSONL file from cloud storage (S3 or GCS). Args: cloud_path: str Cloud path in the format: - 's3:
LLaMA-Factory/src/llamafactory/data/data_utils.py:170
↓ 1 callersFunctionreasoning_steps_reward
r"""Reward function that checks for clear step-by-step reasoning. Regex pattern: Step \d+: - matches "Step 1:", "Step 2:", etc. ^\
open-r1/src/open_r1/rewards.py:486
↓ 1 callersFunctionregister_autoclass
(config: "PretrainedConfig", model: "PreTrainedModel", tokenizer: "PreTrainedTokenizer")
LLaMA-Factory/src/llamafactory/model/model_utils/misc.py:80
↓ 1 callersFunctionrepeat_each_element_k_times
(list_to_repeat: list, k: int)
open-r1/scripts/pass_rate_filtering/compute_pass_rate.py:137
↓ 1 callersFunctionresize_embedding_layer
r"""Resize token embeddings.
LLaMA-Factory/src/llamafactory/model/model_utils/embedding.py:40
↓ 1 callersFunctionrestore_layernorm
r"""Restore the layernorm parameters in the model. The model is already unwrapped (and gathered).
LLaMA-Factory/src/llamafactory/train/ppo/ppo_utils.py:76
↓ 1 callersFunctionrewrite_document
Rewrite a document using AutoGEO rules. Args: document: Original document text to rewrite dataset: Name of the dataset (Resea
autogeo/rewriters/core.py:276
↓ 1 callersFunctionrule_candidate_data
Construct rule candidate data from evaluation results. Args: num_examples: Number of examples to process data_dir: Directory
autogeo/loader/rule_candidate_data.py:6
↓ 1 callersFunctionrun_dpo
( model_args: "ModelArguments", data_args: "DataArguments", training_args: "Seq2SeqTrainingArgumen
LLaMA-Factory/src/llamafactory/train/dpo/workflow.py:36
↓ 1 callersFunctionrun_kto
( model_args: "ModelArguments", data_args: "DataArguments", training_args: "Seq2SeqTrainingArgumen
LLaMA-Factory/src/llamafactory/train/kto/workflow.py:35
↓ 1 callersFunctionrun_lighteval_job
( benchmark: str, training_args: Union["SFTConfig", "GRPOConfig"], model_args: "ModelConfig", )
open-r1/src/open_r1/utils/evaluation.py:69
↓ 1 callersFunctionrun_ppo
( model_args: "ModelArguments", data_args: "DataArguments", training_args: "Seq2SeqTrainingArgumen
LLaMA-Factory/src/llamafactory/train/ppo/workflow.py:34
↓ 1 callersFunctionrun_pt
( model_args: "ModelArguments", data_args: "DataArguments", training_args: "Seq2SeqTrainingArgumen
LLaMA-Factory/src/llamafactory/train/pt/workflow.py:36
↓ 1 callersFunctionrun_rm
( model_args: "ModelArguments", data_args: "DataArguments", training_args: "Seq2SeqTrainingArgumen
LLaMA-Factory/src/llamafactory/train/rm/workflow.py:35
↓ 1 callersFunctionrun_script
(script: str, language: str)
open-r1/scripts/e2b_router.py:110
↓ 1 callersFunctionrun_script
(script: str, language: str)
open-r1/scripts/morph_router.py:96
↓ 1 callersFunctionrun_sft
( model_args: "ModelArguments", data_args: "DataArguments", training_args: "Seq2SeqTrainingArgumen
LLaMA-Factory/src/llamafactory/train/sft/workflow.py:40
↓ 1 callersFunctionrun_submission
Executes a submission against a test case using the Piston execution environment. Args: client: PistonClient instance for executing
open-r1/src/open_r1/utils/competitive_programming/ioi_scoring.py:267
↓ 1 callersMethodsave_checkpoint
Save checkpoint for resuming. Args: checkpoint_data: Data to save checkpoint_name: Name of the checkpoint
autogeo/utils/logger.py:139
↓ 1 callersFunctionsave_cmd
r"""Save CLI commands to launch training.
LLaMA-Factory/src/llamafactory/webui/common.py:197
↓ 1 callersFunctionsave_config
(input_dir: str, output_dir: str)
LLaMA-Factory/scripts/convert_ckpt/llamafy_baichuan2.py:76
↓ 1 callersFunctionsave_config
(input_dir: str, output_dir: str, torch_dtype: str)
LLaMA-Factory/scripts/convert_ckpt/llamafy_qwen.py:113
↓ 1 callersMethodsave_predictions
r"""Save model predictions to `output_dir`. A custom behavior that not contained in Seq2SeqTrainer.
LLaMA-Factory/src/llamafactory/train/rm/trainer.py:112
↓ 1 callersMethodsave_predictions
r"""Save model predictions to `output_dir`. A custom behavior that not contained in Seq2SeqTrainer.
LLaMA-Factory/src/llamafactory/train/sft/trainer.py:132
↓ 1 callersFunctionsave_result
Save individual result and update main file.
autogeo/extract_rules.py:333
↓ 1 callersFunctionsave_weight
(input_dir: str, output_dir: str, shard_size: str, save_safetensors: bool)
LLaMA-Factory/scripts/convert_ckpt/llamafy_baichuan2.py:31
↓ 1 callersFunctionsave_weight
(input_dir: str, output_dir: str, shard_size: str, save_safetensors: bool)
LLaMA-Factory/scripts/convert_ckpt/llamafy_qwen.py:39
↓ 1 callersMethodscore
(cls, value: str)
autogeo/evaluation/metrics/geu_score.py:166
↓ 1 callersFunctionscore_single_test_case
( client: PistonClient, problem_data: dict, test_input: str, test_output: str, submission:
open-r1/src/open_r1/utils/competitive_programming/cf_scoring.py:12
↓ 1 callersFunctionscore_single_test_case
Scores a single test case by running the submission against the provided input and output. Args: client: PistonClient instance for e
open-r1/src/open_r1/utils/competitive_programming/ioi_scoring.py:138
↓ 1 callersFunctionsearch_for_fit
r"""Find the index of largest number that fits into the knapsack with the given capacity.
LLaMA-Factory/src/llamafactory/data/processor/processor_utils.py:48
↓ 1 callersMethodsimpo_loss
r"""Compute SimPO loss for batched log probabilities of the policy model.
LLaMA-Factory/src/llamafactory/train/dpo/trainer.py:146
↓ 1 callersFunctionskip_check_imports
r"""Avoid flash attention import error in custom model files.
LLaMA-Factory/src/llamafactory/extras/misc.py:238
↓ 1 callersFunctionsplit_dataset
r"""Split the dataset and returns a dataset dict containing train set and validation set. Support both map dataset and iterable dataset.
LLaMA-Factory/src/llamafactory/data/data_utils.py:79
↓ 1 callersFunctionsupport_rate
(m)
autogeo/loader/cold_start_data.py:56
↓ 1 callersFunctionsweeper
()
LLaMA-Factory/src/llamafactory/api/app.py:54
↓ 1 callersFunctiontest_chat
r"""Test the SGLang engine's basic chat functionality.
LLaMA-Factory/tests/e2e/test_sglang.py:43
↓ 1 callersFunctiontest_multimodal_collator
()
LLaMA-Factory/tests/data/test_collator.py:74
↓ 1 callersFunctiontest_stream_chat
r"""Test the SGLang engine's streaming chat functionality.
LLaMA-Factory/tests/e2e/test_sglang.py:52
↓ 1 callersMethodtool_extractor
r"""Extract all the function calls from the assistant message. It should be an inverse function of `function_formatter`.
LLaMA-Factory/src/llamafactory/data/tool_utils.py:79
↓ 1 callersMethodtool_formatter
r"""Generate the system message describing all the available tools.
LLaMA-Factory/src/llamafactory/data/tool_utils.py:67
↓ 1 callersFunctiontry_download_model_from_other_hub
(model_args: "ModelArguments")
LLaMA-Factory/src/llamafactory/extras/misc.py:257
↓ 1 callersFunctionupdate_attr
(obj: Any, name: str, value: Any)
LLaMA-Factory/src/llamafactory/webui/chatter.py:73
↓ 1 callersFunctionzipngram
(text: str, ngram_size: int)
open-r1/src/open_r1/rewards.py:671
Method__call__
(self, features: list[dict[str, Any]])
LLaMA-Factory/src/llamafactory/data/collator.py:108
Method__call__
(self, features: list[dict[str, Any]])
LLaMA-Factory/src/llamafactory/data/collator.py:242
Method__call__
r"""Pad batched data to the longest sequence in the batch. We generate 2 * n examples where the first n examples represent chosen examples an
LLaMA-Factory/src/llamafactory/data/collator.py:258
Method__call__
r"""Convert a single example in the dataset to the standard format.
LLaMA-Factory/src/llamafactory/data/converter.py:79
Method__call__
(self, example: dict[str, Any])
LLaMA-Factory/src/llamafactory/data/converter.py:86
Method__call__
(self, example: dict[str, Any])
LLaMA-Factory/src/llamafactory/data/converter.py:136
Method__call__
(self, eval_preds: "EvalPrediction", compute_result: bool = True)
LLaMA-Factory/src/llamafactory/train/rm/metric.py:42
Method__call__
(self, eval_preds: "EvalPrediction", compute_result: bool = True)
LLaMA-Factory/src/llamafactory/train/sft/metric.py:76
Method__call__
(self, eval_preds: "EvalPrediction", compute_result: bool = True)
LLaMA-Factory/src/llamafactory/train/sft/metric.py:107
Method__call__
r"""Pad batched data to the longest sequence in the batch.
LLaMA-Factory/scripts/stat_utils/cal_ppl.py:37
Method__call__
(self, features: list[dict[str, Any]])
LLaMA-Factory/tests/train/test_sft_trainer.py:52
Method__del__
r"""Ensure server is cleaned up when object is deleted.
LLaMA-Factory/src/llamafactory/chat/sglang_engine.py:283
Function__init__
(self, data, **kwargs)
LLaMA-Factory/src/llamafactory/data/loader.py:206
Method__init__
Initialize logger. Args: log_dir: Directory to save log files task_name: Name of the task (used in log filena
autogeo/utils/logger.py:14
Method__init__
(self, *args, **kwargs)
open-r1/src/grpo.py:50
Method__init__
Initializes the RoutedSandbox with the specified router URL. Args: router_url (str): The URL of the E2B Router.
open-r1/src/open_r1/utils/routed_sandbox.py:32
Method__init__
Initialize the routed MorphCloud sandbox client. Args: router_url: The URL of the MorphCloud router, including host and
open-r1/src/open_r1/utils/routed_morph.py:35
Method__init__
Initialize the E2B provider. Args: num_parallel: Number of parallel sandboxes to use e2b_router_url: URL for the E2B
open-r1/src/open_r1/utils/code_providers.py:66
Method__init__
Initialize the Morph provider. Args: num_parallel: Number of parallel executions to use morph_router_url: URL for the
open-r1/src/open_r1/utils/code_providers.py:172
Method__init__
(self, **kwargs)
open-r1/src/open_r1/utils/callbacks.py:38
Method__init__
(self, model_config)
open-r1/src/open_r1/utils/callbacks.py:44
Method__init__
Initialize the MorphCloud execution client. Args: api_key: Optional API key for MorphCloud. If not provided, will use MO
open-r1/src/open_r1/utils/competitive_programming/morph_client.py:31
Method__init__
( self, base_endpoint: str | list[str] = "http://ip-10-53-80-65:3223/api/v2", session=
open-r1/src/open_r1/utils/competitive_programming/piston_client.py:59
Method__init__
(self, vision_hidden_size: int, text_hidden_size: int, projector_hidden_act: str)
LLaMA-Factory/src/llamafactory/model/model_utils/visual.py:119
Method__init__
( self, model_args: "ModelArguments", data_args: "DataArguments", finetuning_a
LLaMA-Factory/src/llamafactory/chat/vllm_engine.py:46
Method__init__
r"""Initialize an inference engine.
LLaMA-Factory/src/llamafactory/chat/base_engine.py:53
Method__init__
( self, model_args: "ModelArguments", data_args: "DataArguments", finetuning_a
LLaMA-Factory/src/llamafactory/chat/sglang_engine.py:58
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