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108 lines
3.9 KiB
108 lines
3.9 KiB
""" Model Registry
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Hacked together by / Copyright 2020 Ross Wightman
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"""
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import sys
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import re
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import fnmatch
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from collections import defaultdict
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__all__ = ['list_models', 'is_model', 'model_entrypoint', 'list_modules', 'is_model_in_modules']
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_module_to_models = defaultdict(set) # dict of sets to check membership of model in module
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_model_to_module = {} # mapping of model names to module names
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_model_entrypoints = {} # mapping of model names to entrypoint fns
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_model_has_pretrained = set() # set of model names that have pretrained weight url present
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def register_model(fn):
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# lookup containing module
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mod = sys.modules[fn.__module__]
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module_name_split = fn.__module__.split('.')
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module_name = module_name_split[-1] if len(module_name_split) else ''
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# add model to __all__ in module
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model_name = fn.__name__
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if hasattr(mod, '__all__'):
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mod.__all__.append(model_name)
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else:
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mod.__all__ = [model_name]
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# add entries to registry dict/sets
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_model_entrypoints[model_name] = fn
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_model_to_module[model_name] = module_name
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_module_to_models[module_name].add(model_name)
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has_pretrained = False # check if model has a pretrained url to allow filtering on this
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if hasattr(mod, 'default_cfgs') and model_name in mod.default_cfgs:
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# this will catch all models that have entrypoint matching cfg key, but miss any aliasing
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# entrypoints or non-matching combos
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has_pretrained = 'url' in mod.default_cfgs[model_name] and 'http' in mod.default_cfgs[model_name]['url']
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if has_pretrained:
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_model_has_pretrained.add(model_name)
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return fn
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def _natural_key(string_):
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return [int(s) if s.isdigit() else s for s in re.split(r'(\d+)', string_.lower())]
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def list_models(filter='', module='', pretrained=False, exclude_filters=''):
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""" Return list of available model names, sorted alphabetically
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Args:
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filter (str) - Wildcard filter string that works with fnmatch
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module (str) - Limit model selection to a specific sub-module (ie 'gen_efficientnet')
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pretrained (bool) - Include only models with pretrained weights if True
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exclude_filters (str or list[str]) - Wildcard filters to exclude models after including them with filter
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Example:
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model_list('gluon_resnet*') -- returns all models starting with 'gluon_resnet'
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model_list('*resnext*, 'resnet') -- returns all models with 'resnext' in 'resnet' module
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"""
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if module:
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models = list(_module_to_models[module])
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else:
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models = _model_entrypoints.keys()
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if filter:
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models = fnmatch.filter(models, filter) # include these models
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if exclude_filters:
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if not isinstance(exclude_filters, list):
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exclude_filters = [exclude_filters]
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for xf in exclude_filters:
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exclude_models = fnmatch.filter(models, xf) # exclude these models
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if len(exclude_models):
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models = set(models).difference(exclude_models)
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if pretrained:
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models = _model_has_pretrained.intersection(models)
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return list(sorted(models, key=_natural_key))
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def is_model(model_name):
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""" Check if a model name exists
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"""
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return model_name in _model_entrypoints
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def model_entrypoint(model_name):
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"""Fetch a model entrypoint for specified model name
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"""
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return _model_entrypoints[model_name]
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def list_modules():
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""" Return list of module names that contain models / model entrypoints
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"""
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modules = _module_to_models.keys()
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return list(sorted(modules))
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def is_model_in_modules(model_name, module_names):
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"""Check if a model exists within a subset of modules
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Args:
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model_name (str) - name of model to check
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module_names (tuple, list, set) - names of modules to search in
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"""
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assert isinstance(module_names, (tuple, list, set))
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return any(model_name in _module_to_models[n] for n in module_names)
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