mirror of https://github.com/hpcaitech/ColossalAI
80 lines
3.0 KiB
Python
80 lines
3.0 KiB
Python
#!/usr/bin/env python
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# -*- encoding: utf-8 -*-
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import inspect
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from colossalai.legacy.registry import *
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def build_from_config(module, config: dict):
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"""Returns an object of :class:`module` constructed from `config`.
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Args:
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module: A python or user-defined class
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config: A python dict containing information used in the construction of the return object
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Returns: An ``object`` of interest
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Raises:
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AssertionError: Raises an AssertionError if `module` is not a class
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"""
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assert inspect.isclass(module), 'module must be a class'
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return module(**config)
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def build_from_registry(config, registry: Registry):
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r"""Returns an object constructed from `config`, the type of the object
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is specified by `registry`.
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Note:
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the `config` is used to construct the return object such as `LAYERS`, `OPTIMIZERS`
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and other support types in `registry`. The `config` should contain
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all required parameters of corresponding object. The details of support
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types in `registry` and the `mod_type` in `config` could be found in
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`registry <https://github.com/hpcaitech/ColossalAI/blob/main/colossalai/registry/__init__.py>`_.
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Args:
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config (dict or :class:`colossalai.context.colossalai.context.Config`): information
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used in the construction of the return object.
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registry (:class:`Registry`): A registry specifying the type of the return object
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Returns:
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A Python object specified by `registry`.
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Raises:
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Exception: Raises an Exception if an error occurred when building from registry.
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"""
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config_ = config.copy() # keep the original config untouched
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assert isinstance(registry, Registry), f'Expected type Registry but got {type(registry)}'
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mod_type = config_.pop('type')
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assert registry.has(mod_type), f'{mod_type} is not found in registry {registry.name}'
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try:
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obj = registry.get_module(mod_type)(**config_)
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except Exception as e:
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print(f'An error occurred when building {mod_type} from registry {registry.name}', flush=True)
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raise e
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return obj
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def build_gradient_handler(config, model, optimizer):
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"""Returns a gradient handler object of :class:`BaseGradientHandler` constructed from `config`,
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`model` and `optimizer`.
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Args:
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config (dict or :class:`colossalai.context.Config`): A python dict or
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a :class:`colossalai.context.Config` object containing information
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used in the construction of the ``GRADIENT_HANDLER``.
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model (:class:`nn.Module`): A model containing parameters for the gradient handler
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optimizer (:class:`torch.optim.Optimizer`): An optimizer object containing parameters for the gradient handler
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Returns:
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An object of :class:`colossalai.legacy.engine.BaseGradientHandler`
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"""
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config_ = config.copy()
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config_['model'] = model
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config_['optimizer'] = optimizer
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return build_from_registry(config_, GRADIENT_HANDLER)
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