def _image_dl_estimator(one_classifier=False, functional=False, **kwargs):
sess = None
wildcard = False
classifier_list = None
if kwargs.get("wildcard") is not None:
if kwargs.get("wildcard") is True:
wildcard = True
del kwargs["wildcard"]
if framework == "keras":
if wildcard is False and functional is False:
if functional:
classifier_list = [
get_image_classifier_kr_functional(**kwargs)
]
else:
classifier_list = [get_image_classifier_kr(**kwargs)]
if framework == "tensorflow":
if wildcard is False and functional is False:
classifier, sess = get_image_classifier_tf(**kwargs)
classifier_list = [classifier]
if framework == "pytorch":
if wildcard is False and functional is False:
classifier_list = [get_image_classifier_pt(**kwargs)]
if framework == "scikitlearn":
logging.warning(
"{0} doesn't have an image classifier defined yet".format(
framework))
classifier_list = None
if framework == "kerastf":
if wildcard:
classifier_list = [
get_image_classifier_kr_tf_with_wildcard(**kwargs)
]
else:
if functional:
classifier_list = [
get_image_classifier_kr_tf_functional(**kwargs)
]
else:
classifier_list = [get_image_classifier_kr_tf(**kwargs)]
if framework == "mxnet":
if wildcard is False and functional is False:
classifier_list = [get_image_classifier_mx_instance(**kwargs)]
if classifier_list is None:
return None, None
if one_classifier:
return classifier_list[0], sess
return classifier_list, sess
def _image_dl_estimator(functional=False, **kwargs):
sess = None
wildcard = False
classifier = None
if kwargs.get("wildcard") is not None:
if kwargs.get("wildcard") is True:
wildcard = True
del kwargs["wildcard"]
if framework == "keras":
if wildcard is False and functional is False:
if functional:
classifier = get_image_classifier_kr_functional(**kwargs)
else:
try:
classifier = get_image_classifier_kr(**kwargs)
except NotImplementedError:
raise ARTTestFixtureNotImplemented(
"This combination of loss function options is currently not supported.",
image_dl_estimator.__name__,
framework,
)
if framework == "tensorflow1" or framework == "tensorflow2":
if wildcard is False and functional is False:
classifier, sess = get_image_classifier_tf(**kwargs)
return classifier, sess
if framework == "pytorch":
if not wildcard:
if functional:
classifier = get_image_classifier_pt_functional(**kwargs)
else:
classifier = get_image_classifier_pt(**kwargs)
if framework == "kerastf":
if wildcard:
classifier = get_image_classifier_kr_tf_with_wildcard(**kwargs)
else:
if functional:
classifier = get_image_classifier_kr_tf_functional(
**kwargs)
else:
classifier = get_image_classifier_kr_tf(**kwargs)
if framework == "mxnet":
if wildcard is False and functional is False:
classifier = get_image_classifier_mx_instance(**kwargs)
if classifier is None:
raise ARTTestFixtureNotImplemented(
"no test deep learning estimator available",
image_dl_estimator.__name__, framework)
return classifier, sess
