Logging config for colab (#2611)
* only configure logging on cli to play nicely with colab * allow reloading the config on the fly from a dict * make sure to use dict for yaml * reuse existing function for load * make cli args optional * mps fix and respect max_steps
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@@ -5,6 +5,7 @@ import logging
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import os
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import tempfile
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from pathlib import Path
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from tempfile import NamedTemporaryFile
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from typing import Union
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from urllib.parse import urlparse
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@@ -158,7 +159,9 @@ def plugin_set_cfg(cfg: DictDefault):
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plugin_manager.cfg = cfg
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def load_cfg(config: Union[str, Path] = Path("examples/"), **kwargs) -> DictDefault:
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def load_cfg(
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config: str | Path | DictDefault = Path("examples/"), **kwargs
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) -> DictDefault:
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"""
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Loads the `axolotl` configuration stored at `config`, validates it, and performs
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various setup.
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@@ -170,13 +173,24 @@ def load_cfg(config: Union[str, Path] = Path("examples/"), **kwargs) -> DictDefa
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Returns:
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`DictDefault` mapping configuration keys to values.
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"""
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config = check_remote_config(config)
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if Path(config).is_dir():
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config = choose_config(Path(config))
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if isinstance(config, (str, Path)):
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config = check_remote_config(config)
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if Path(config).is_dir():
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config = choose_config(Path(config))
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# Load the config from the yaml file
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with open(config, encoding="utf-8") as file:
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cfg: DictDefault = DictDefault(yaml.safe_load(file))
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# Load the config from the yaml file
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with open(config, encoding="utf-8") as file:
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cfg: DictDefault = DictDefault(yaml.safe_load(file))
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cfg.axolotl_config_path = config
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else:
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cfg = config
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with NamedTemporaryFile(
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mode="w", delete=False, suffix=".yml", prefix="axolotl_config_"
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) as temp_file:
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temp_file.write(yaml.dump(config.to_dict()))
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temp_file.close()
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cfg.axolotl_config_path = temp_file.name
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# If there are any options passed in the cli, if it is something that seems valid
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# from the yaml, then overwrite the value
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@@ -190,8 +204,6 @@ def load_cfg(config: Union[str, Path] = Path("examples/"), **kwargs) -> DictDefa
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else:
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cfg[k] = kwargs[k]
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cfg.axolotl_config_path = config
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try:
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device_props = torch.cuda.get_device_properties("cuda")
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gpu_version = "sm_" + str(device_props.major) + str(device_props.minor)
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