mirror of https://github.com/hpcaitech/ColossalAI
69 lines
2.2 KiB
Python
69 lines
2.2 KiB
Python
#!/usr/bin/env python
|
|
from dataclasses import dataclass
|
|
from typing import Callable
|
|
|
|
__all__ = ['ModelZooRegistry', 'ModelAttributem', 'model_zoo']
|
|
|
|
|
|
@dataclass
|
|
class ModelAttribute:
|
|
"""
|
|
Attributes of a model.
|
|
|
|
Args:
|
|
has_control_flow (bool): Whether the model contains branching in its forward method.
|
|
has_stochastic_depth_prob (bool): Whether the model contains stochastic depth probability. Often seen in the torchvision models.
|
|
"""
|
|
has_control_flow: bool = False
|
|
has_stochastic_depth_prob: bool = False
|
|
|
|
|
|
class ModelZooRegistry(dict):
|
|
"""
|
|
A registry to map model names to model and data generation functions.
|
|
"""
|
|
|
|
def register(self,
|
|
name: str,
|
|
model_fn: Callable,
|
|
data_gen_fn: Callable,
|
|
output_transform_fn: Callable,
|
|
model_attribute: ModelAttribute = None):
|
|
"""
|
|
Register a model and data generation function.
|
|
|
|
Examples:
|
|
>>> # Register
|
|
>>> model_zoo = ModelZooRegistry()
|
|
>>> model_zoo.register('resnet18', resnet18, resnet18_data_gen)
|
|
>>> # Run the model
|
|
>>> data = resnresnet18_data_gen() # do not input any argument
|
|
>>> model = resnet18() # do not input any argument
|
|
>>> out = model(**data)
|
|
|
|
Args:
|
|
name (str): Name of the model.
|
|
model_fn (callable): A function that returns a model. **It must not contain any arguments.**
|
|
output_transform_fn (callable): A function that transforms the output of the model into Dict.
|
|
data_gen_fn (callable): A function that returns a data sample in the form of Dict. **It must not contain any arguments.**
|
|
model_attribute (ModelAttribute): Attributes of the model. Defaults to None.
|
|
"""
|
|
self[name] = (model_fn, data_gen_fn, output_transform_fn, model_attribute)
|
|
|
|
def get_sub_registry(self, keyword: str):
|
|
"""
|
|
Get a sub registry with models that contain the keyword.
|
|
|
|
Args:
|
|
keyword (str): Keyword to filter models.
|
|
"""
|
|
new_dict = dict()
|
|
|
|
for k, v in self.items():
|
|
if keyword in k:
|
|
new_dict[k] = v
|
|
return new_dict
|
|
|
|
|
|
model_zoo = ModelZooRegistry()
|