def get_default_config(cls) -> Dict[str, Any]:
"""
Generate and return a default configuration dictionary for this class.
This will be primarily used for generating what the configuration
dictionary would look like for this class without instantiating it.
By default, we observe what this class's constructor takes as
arguments, turning those argument names into configuration dictionary
keys. If any of those arguments have defaults, we will add those values
into the configuration dictionary appropriately. The dictionary
returned should only contain JSON compliant value types.
It is not be guaranteed that the configuration dictionary returned
from this method is valid for construction of an instance of this
class.
:return: Default configuration dictionary for the class.
:rtype: dict
"""
default = super(LSHNearestNeighborIndex, cls).get_default_config()
lf_default = make_default_config(LshFunctor.get_impls())
default['lsh_functor'] = lf_default
di_default = make_default_config(DescriptorSet.get_impls())
default['descriptor_set'] = di_default
hi_default = make_default_config(HashIndex.get_impls())
default['hash_index'] = hi_default
h2u_default = make_default_config(KeyValueStore.get_impls())
default['hash2uuids_kvstore'] = h2u_default
return default
def get_default_config(cls) -> Dict[str, Any]:
"""
Generate and return a default configuration dictionary for this class.
This will be primarily used for generating what the configuration
dictionary would look like for this class without instantiating it.
By default, we observe what this class's constructor takes as
arguments, turning those argument names into configuration dictionary
keys. If any of those arguments have defaults, we will add those
values into the configuration dictionary appropriately. The dictionary
returned should only contain JSON compliant value types.
It is not be guaranteed that the configuration dictionary returned
from this method is valid for construction of an instance of this
class.
:return: Default configuration dictionary for the class.
"""
default = super(FaissNearestNeighborsIndex, cls).get_default_config()
data_element_default_config = \
make_default_config(DataElement.get_impls())
default['index_element'] = data_element_default_config
default['index_param_element'] = deepcopy(data_element_default_config)
di_default = make_default_config(DescriptorSet.get_impls())
default['descriptor_set'] = di_default
kvs_default = make_default_config(KeyValueStore.get_impls())
default['idx2uid_kvs'] = kvs_default
default['uid2idx_kvs'] = deepcopy(kvs_default)
return default
def get_default_config(cls) -> Dict[str, Any]:
default = super(CaffeDescriptorGenerator, cls).get_default_config()
data_elem_impl_set = DataElement.get_impls()
# Need to make copies of dict so changes to one does not effect others.
default['network_prototxt'] = \
make_default_config(data_elem_impl_set)
default['network_model'] = make_default_config(data_elem_impl_set)
default['image_mean'] = make_default_config(data_elem_impl_set)
return default
def get_default_config(cls) -> Dict[str, Any]:
default = super(MRPTNearestNeighborsIndex, cls).get_default_config()
di_default = make_default_config(DescriptorSet.get_impls())
default['descriptor_set'] = di_default
return default
def get_config(self) -> Dict[str, Any]:
# Recursively get config from data element if we have one.
if self._cache_element is not None:
elem_config = to_config_dict(self._cache_element)
else:
# No cache element, output default config with no type.
elem_config = make_default_config(DataElement.get_impls())
return {'cache_element': elem_config}
def test_make_default_config() -> None:
"""
Test expected normal operation of ``make_default_config``.
"""
expected = {
'type': None,
'tests.test_configuration.T1': T1.get_default_config(),
'tests.test_configuration.T2': T2.get_default_config(),
}
assert make_default_config(T_CLASS_SET) == expected
def get_default_config(cls):
c = super(ClassifierCollection, cls).get_default_config()
# We list the label-classifier mapping on one level, so remove the
# nested map parameter that can optionally be used in the constructor.
del c['classifiers']
# Add slot of a list of classifier plugin specifications
c[cls.EXAMPLE_KEY] = make_default_config(Classifier.get_impls())
return c
def get_default_config(cls) -> Dict[str, Any]:
"""
Generate and return a default configuration dictionary for this class.
This will be primarily used for generating what the configuration
dictionary would look like for this class without instantiating it.
It is not be guaranteed that the configuration dictionary returned
from this method is valid for construction of an instance of this class.
:return: Default configuration dictionary for the class.
"""
return make_default_config(DescriptorElement.get_impls())
def get_default_config(cls) -> Dict[str, Any]:
default = super(ItqFunctor, cls).get_default_config()
# Cache element parameters need to be split out into sub-configurations
data_element_default_config = \
make_default_config(DataElement.get_impls())
default['mean_vec_cache'] = data_element_default_config
# Need to deepcopy source to prevent modifications on one sub-config
# from reflecting in the other.
default['rotation_cache'] = deepcopy(data_element_default_config)
return default
def get_default_config(cls) -> Dict:
"""
Generate and return a default configuration dictionary for this class.
It is not be guaranteed that the configuration dictionary returned
from this method is valid for construction of an instance of this class.
:return: Default configuration dictionary for the class.
:rtype: dict
"""
c = super(KVSDataSet, cls).get_default_config()
c['kvstore'] = merge_dict(
make_default_config(KeyValueStore.get_impls()),
to_config_dict(c['kvstore']))
return c
def get_default_config(cls) -> Dict[str, Any]:
"""
Generate and return a default configuration dictionary for this class.
This will be primarily used for generating what the configuration
dictionary would look like for this class without instantiating it.
It is not be guaranteed that the configuration dictionary returned
from this method is valid for construction of an instance of this class.
:return: Default configuration dictionary for the class.
:rtype: dict
"""
default = super(MemoryKeyValueStore, cls).get_default_config()
default['cache_element'] = make_default_config(DataElement.get_impls())
return default
def get_default_config(cls) -> Dict[str, Any]:
"""
Generate and return a default configuration dictionary for this class.
This will be primarily used for generating what the configuration
dictionary would look like for this class without instantiating it.
By default, we observe what this class's constructor takes as arguments,
turning those argument names into configuration dictionary keys. If any
of those arguments have defaults, we will add those values into the
configuration dictionary appropriately. The dictionary returned should
only contain JSON compliant value types.
It is not be guaranteed that the configuration dictionary returned
from this method is valid for construction of an instance of this class.
:return: Default configuration dictionary for the class.
"""
c = super(MemoryDescriptorSet, cls).get_default_config()
c['cache_element'] = make_default_config(DataElement.get_impls())
return c
def get_default_config(cls) -> Dict[str, Any]:
c = super().get_default_config()
c['classifier_inst'] = \
make_default_config(ClassifyDescriptorSupervised.get_impls())
return c
def get_default_config(cls) -> Dict[str, Any]:
c = super().get_default_config()
rr_default = make_default_config(RankRelevancy.get_impls())
return dict(c, rank_relevancy=rr_default)
def get_default_config(cls) -> Dict[str, Any]:
cfg = super().get_default_config()
cfg['perturber'] = make_default_config(PerturbImage.get_impls())
cfg['generator'] = make_default_config(GenerateClassifierConfidenceSaliency.get_impls())
return cfg
