Skip to content

Runner

danling.runner.Runner

Bases: BaseRunner

Dynamic runner class that selects the appropriate platform based on configuration.

This runner dynamically modifies the __class__ attribute to adapt to the platform.

It’s safe (and recommended) to inherit from this class to extend the Runner.

Valid platform options are:

  • “auto” (default)
  • “torch”
  • “accelerate”
  • “deepspeed”

Examples:

Python Console Session
1
2
>>> config = Config({"platform": "accelerate"})
>>> runner = Runner(config)
See Also
Source code in danling/runner/runner.py
Python
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
class Runner(BaseRunner):
    r"""
    Dynamic runner class that selects the appropriate platform based on configuration.

    This runner dynamically modifies the `__class__` attribute to adapt to the platform.

    It's safe (and recommended) to inherit from this class to extend the Runner.

    Valid platform options are:

    - "auto" (default)
    - "torch"
    - "accelerate"
    - "deepspeed"

    Examples:
        >>> config = Config({"platform": "accelerate"})
        >>> runner = Runner(config)

    See Also:
        - [`BaseRunner`][danling.runner.BaseRunner]: Base class for all runners.
        - [`TorchRunner`][danling.runner.TorchRunner]: PyTorch runner.
        - [`AccelerateRunner`][danling.runner.AccelerateRunner]: PyTorch runner with Accelerate.
        - [`DeepSpeedRunner`][danling.runner.DeepSpeedRunner]: PyTorch runner with DeepSpeed.
    """

    def __init__(self, config: Config) -> None:
        platform = config.get("platform", "auto").lower()

        if platform == "auto":
            platform = "deepspeed" if ds.is_successful() else "torch"

        if platform == "accelerate":
            ac.check()
            self.__class__ = type("AccelerateRunner", (self.__class__, AccelerateRunner), {})
        elif platform == "deepspeed":
            ds.check()
            self.__class__ = type("DeepSpeedRunner", (self.__class__, DeepSpeedRunner), {})
        elif platform == "torch":
            self.__class__ = type("TorchRunner", (self.__class__, TorchRunner), {})
        else:
            raise ValueError(f"Unknown platform: {platform}. Valid options are: torch, accelerate, deepspeed")

        super().__init__(config)