mirror of https://github.com/hpcaitech/ColossalAI
113 lines
3.8 KiB
Python
113 lines
3.8 KiB
Python
# This code has been adapted from the DeepSpeed library.
|
|
# Copyright (c) Microsoft Corporation.
|
|
# Licensed under the MIT License.
|
|
|
|
import functools
|
|
from typing import Optional
|
|
|
|
import torch
|
|
|
|
|
|
def substitute_init_recursively(cls, func, visited: set):
|
|
for subcls in cls.__subclasses__():
|
|
substitute_init_recursively(subcls, func, visited)
|
|
if subcls not in visited:
|
|
func(subcls)
|
|
visited.add(subcls)
|
|
|
|
|
|
def call_to_str(base, *args, **kwargs):
|
|
"""Construct a string representation of a call.
|
|
|
|
Args:
|
|
base (str): name of the call
|
|
args (tuple, optional): args to ``base``
|
|
kwargs (dict, optional): kwargs supplied to ``base``
|
|
|
|
Returns:
|
|
str: A string representation of base(*args, **kwargs)
|
|
"""
|
|
name = f"{base}("
|
|
if args:
|
|
name += ", ".join(repr(arg) for arg in args)
|
|
if kwargs:
|
|
name += ", "
|
|
if kwargs:
|
|
name += ", ".join(f"{key}={repr(arg)}" for key, arg in kwargs.items())
|
|
name += ")"
|
|
return name
|
|
|
|
|
|
class InsertPostInitMethodToModuleSubClasses(object):
|
|
def __init__(self, default_dtype: Optional[torch.dtype] = None):
|
|
self._old_default_dtype = None
|
|
self._default_dtype = default_dtype
|
|
|
|
def __enter__(self):
|
|
r"""
|
|
Enter the context scope.
|
|
"""
|
|
if self._default_dtype is not None:
|
|
self._old_default_dtype = torch.get_default_dtype()
|
|
torch.set_default_dtype(self._default_dtype)
|
|
|
|
def preprocess_after(f):
|
|
@functools.wraps(f)
|
|
def wrapper(module: torch.nn.Module, *args, **kwargs):
|
|
f(module, *args, **kwargs)
|
|
self._post_init_method(module, *args, **kwargs)
|
|
|
|
return wrapper
|
|
|
|
def _enable_class(cls):
|
|
cls._old_init = cls.__init__
|
|
cls.__init__ = preprocess_after(cls.__init__)
|
|
|
|
# The function is called during init subclass.
|
|
def _init_subclass(cls, **kwargs):
|
|
cls.__init__ = preprocess_after(cls.__init__)
|
|
|
|
# Replace .__init__() for all existing subclasses of torch.nn.Module
|
|
# Execution self._post_init_method after the default init function.
|
|
substitute_init_recursively(torch.nn.modules.module.Module, _enable_class, set())
|
|
|
|
# holding on to the current __init__subclass__ for exit
|
|
torch.nn.modules.module.Module._old_init_subclass = torch.nn.modules.module.Module.__init_subclass__
|
|
# Replace .__init__() for future subclasses of torch.nn.Module
|
|
torch.nn.modules.module.Module.__init_subclass__ = classmethod(_init_subclass)
|
|
|
|
self._pre_context_exec()
|
|
return self
|
|
|
|
def __exit__(self, exc_type, exc_value, traceback):
|
|
if self._default_dtype is not None:
|
|
torch.set_default_dtype(self._old_default_dtype)
|
|
|
|
def _disable_class(cls):
|
|
if not hasattr(cls, "_old_init"):
|
|
raise AttributeError(
|
|
f"_old_init is not found in the {cls.__name__}, please make sure that you have imported {cls.__name__} before entering the context."
|
|
)
|
|
cls.__init__ = cls._old_init
|
|
|
|
# Replace .__init__() for all existing subclasses of torch.nn.Module
|
|
substitute_init_recursively(torch.nn.modules.module.Module, _disable_class, set())
|
|
|
|
# Replace .__init__() for future subclasses of torch.nn.Module
|
|
torch.nn.modules.module.Module.__init_subclass__ = torch.nn.modules.module.Module._old_init_subclass
|
|
|
|
self._post_context_exec()
|
|
# Now that we cleaned up the metaclass injection, raise the exception.
|
|
if exc_type is not None:
|
|
return False
|
|
|
|
# To be implemented by inheriting classes
|
|
def _post_init_method(self, module, *args, **kwargs):
|
|
pass
|
|
|
|
def _pre_context_exec(self):
|
|
pass
|
|
|
|
def _post_context_exec(self):
|
|
pass
|