class SetupModel(object):
model = classification_model()
labels = get_labels(os.environ['LABELS_PATH'])
def __init__(self, f):
self.f = f
file_path = f'/tmp/{STATE_DICT_NAME}'
download_file(BUCKET_NAME, STATE_DICT_NAME, file_path)
state_dict = torch.load(file_path, map_location=lambda storage, loc: storage)
self.model.load_state_dict(state_dict), self.model.eval()
os.remove(file_path)
def __call__(self, *args, **kwargs):
return self.f(*args, **kwargs)
class SetupModel(object):
model = classification_model()
labels = list(label_dict.values())
tfms = tfms_from_stats(STATS, SZ)[-1]
def __init__(self, f):
self.f = f
file_path = f'/tmp/{STATE_DICT_NAME}'
download_file(BUCKET_NAME, STATE_DICT_NAME, file_path)
state_dict = torch.load(file_path, map_location=lambda storage, loc: storage)
self.model.load_state_dict(state_dict)
self.model.eval()
os.remove(file_path)
def __call__(self, *args, **kwargs):
return self.f(*args, **kwargs)