6084915af8
Adds support for GD models, courtesy of some maths from openai.
Also:
- Fixes requirement for eval{} even when it isn't being used
- Adds support for denormalizing an imagenet norm
65 lines
2.2 KiB
Python
65 lines
2.2 KiB
Python
import importlib
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import inspect
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import pkgutil
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import re
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import sys
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import torch.nn
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# Base class for all other injectors.
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class Injector(torch.nn.Module):
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def __init__(self, opt, env):
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super(Injector, self).__init__()
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self.opt = opt
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self.env = env
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if 'in' in opt.keys():
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self.input = opt['in']
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self.output = opt['out']
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# This should return a dict of new state variables.
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def forward(self, state):
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raise NotImplementedError
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def format_injector_name(name):
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# Formats by converting from CamelCase to snake_case and removing trailing "_injector"
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name = re.sub('(.)([A-Z][a-z]+)', r'\1_\2', name)
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name = re.sub('([a-z0-9])([A-Z])', r'\1_\2', name).lower()
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return name.replace("_injector", "")
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# Works by loading all python modules in the injectors/ directory and sniffing out subclasses of Injector.
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# field will be properly populated.
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def find_registered_injectors(base_path="trainer/injectors"):
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module_iter = pkgutil.walk_packages([base_path])
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results = {}
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for mod in module_iter:
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if mod.ispkg:
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EXCLUSION_LIST = []
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if mod.name not in EXCLUSION_LIST:
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results.update(find_registered_injectors(f'{base_path}/{mod.name}'))
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else:
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mod_name = f'{base_path}/{mod.name}'.replace('/', '.')
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importlib.import_module(mod_name)
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classes = inspect.getmembers(sys.modules[mod_name], inspect.isclass)
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for name, obj in classes:
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if 'Injector' in [mro.__name__ for mro in inspect.getmro(obj)]:
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results[format_injector_name(name)] = obj
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return results
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class CreateInjectorError(Exception):
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def __init__(self, name, available):
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super().__init__(f'Could not find the specified injector name: {name}. Available injectors:'
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f'{available}')
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# Injectors are a way to synthesize data within a step that can then be used (and reused) by loss functions.
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def create_injector(opt_inject, env):
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injectors = find_registered_injectors()
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type = opt_inject['type']
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if type not in injectors.keys():
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raise CreateInjectorError(type, list(injectors.keys()))
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return injectors[opt_inject['type']](opt_inject, env)
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