def get_names_probs(predict_output, cat_to_name, class_to_idx):
	"""Return the names and probabilities of the predicted classes
	
	Args:
		predict_output (obj): A ``torch.tensor`` object from typically with 2 tensors
		cat_to_name (dict): A dictionary containing key to category  mapping of each category in the cat_to_name file
		class_to_idx (dict): Class to id mapping of the train data

	Returns:
		tuple: Returns a tuple of
			``flower_names`` - Name of the flowers predicted
			``flower_probs`` - Probabilities associated with each predicted flower

	"""
	idx_to_class = {v: k for k, v in class_to_idx.items()}
	flower_names = [cat_to_name[idx_to_class[x.item()]] for x in predict_output[1][0]]
	flower_probs = [x.item() for x in predict_output[0][0]]
	return flower_names, flower_probs