5d182a1056
* Add runpod sls handler * remove LICENSE and fix README * chore: lint * use axolotl cloud image as base and various fixes * fix: trim allowed cuda versions * restore dockerfile * chore: update title * use axolotl cloud image --------- Co-authored-by: Wing Lian <wing@axolotl.ai> Co-authored-by: NanoCode012 <nano@axolotl.ai>
90 lines
2.7 KiB
Python
90 lines
2.7 KiB
Python
"""
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Runpod launcher utils
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"""
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import os
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import yaml
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def get_output_dir(run_id):
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path = f"fine-tuning/{run_id}"
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return path
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def make_valid_config(input_args):
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"""
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Creates and saves updated config file, returns the path to the new config
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:param input_args: dict of input args
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:return: str, path to the updated config file
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"""
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# Load default config
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with open("config/config.yaml", "r", encoding="utf-8") as fin:
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all_args = yaml.safe_load(fin)
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if not input_args:
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print("No args provided, using defaults")
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else:
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all_args.update(input_args)
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# Create updated config path
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updated_config_path = "config/updated_config.yaml"
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# Save updated config to new file
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with open(updated_config_path, "w", encoding="utf-8") as f:
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yaml.dump(all_args, f)
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return updated_config_path
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def set_config_env_vars(args: dict):
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"""
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Convert API arguments into environment variables.
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Handles nested dictionaries, lists, and special values.
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Args:
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args (dict): The arguments dictionary from the API request
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"""
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def process_value(value):
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"""Convert Python values to string format for environment variables"""
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if value is None:
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return ""
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if isinstance(value, bool):
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return str(value).lower()
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if isinstance(value, (list, dict)):
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return str(value)
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return str(value)
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def set_env_vars(data, prefix=""):
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"""Recursively set environment variables from nested dictionary"""
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for key, value in data.items():
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env_key = prefix + key.upper()
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# Handle special cases
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if isinstance(value, dict):
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# For nested dictionaries (like special_tokens)
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set_env_vars(value, f"{env_key}_")
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elif isinstance(value, list):
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# Handle list of dictionaries (like datasets)
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if value and isinstance(value[0], dict):
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for i, item in enumerate(value):
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set_env_vars(item, f"{env_key}_{i}_")
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else:
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# For simple lists (like lora_target_modules)
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os.environ[env_key] = process_value(value)
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else:
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# Handle all other cases
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os.environ[env_key] = process_value(value)
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# Clear any existing related environment variables
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# This prevents old values from persisting
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for key in list(os.environ.keys()):
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if key.startswith(
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("BASE_MODEL", "MODEL_TYPE", "TOKENIZER_TYPE", "DATASET", "LORA_", "WANDB_")
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):
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del os.environ[key]
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# Set new environment variables
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set_env_vars(args)
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