Method get_tuple

dataloader/triplet_dataloader.py:69–124

hard_neg: bool, add hard negative? other_neg: bool, add other negatives?(quadra loss fuction required)

(self, dict_value, hard_neg=None, other_neg=False)

        self.data_count = 0

    def get_tuple(self, dict_value, hard_neg=None, other_neg=False):
        '''
        hard_neg: bool, add hard negative?
        other_neg: bool, add other negatives?(quadra loss fuction required)
        '''
        if hard_neg is None:
            hard_neg = []
        possible_negs = []

        num_pos = self.config.TRAINING.BATCH.POSITIVES_PER_QUERY
        num_neg = self.config.TRAINING.BATCH.NEGATIVES_PER_QUERY
        random.shuffle(dict_value["positives"])
        pos_files = []
        for i in range(num_pos):
            pos_files.append(self.queries[dict_value["positives"][i]]["query"])

        neg_files = []
        neg_indices = []
        if len(hard_neg) == 0:
            random.shuffle(dict_value["negatives"])
            for i in range(num_neg):
                neg_files.append(self.queries[dict_value["negatives"][i]]["query"])
                neg_indices.append(dict_value["negatives"][i])
        else:
            random.shuffle(dict_value["negatives"])
            for i in hard_neg:
                neg_files.append(self.queries[i]["query"])
                neg_indices.append(i)
            j = 0
            while len(neg_files) < num_neg:
                if not dict_value["negatives"][j] in hard_neg:
                    neg_files.append(self.queries[dict_value["negatives"][j]]["query"])
                    neg_indices.append(dict_value["negatives"][j])
                j += 1
        if other_neg:
            # get neighbors of negatives and query
            neighbors = []
            for pos in dict_value["positives"]:
                neighbors.append(pos)
            for neg in neg_indices:
                for pos in self.queries[neg]["positives"]:
                    neighbors.append(pos)
            possible_negs = list(set(self.queries.keys()) - set(neighbors))
            random.shuffle(possible_negs)

        query = self.load_file_func(dict_value["query"])  # Nx3
        query = np.expand_dims(query, axis=0)
        positives = self.load_files_func(pos_files)
        negatives = self.load_files_func(neg_files)

        output = [query, positives, negatives]
        if other_neg:
            neg2 = self.load_file_func(self.queries[possible_negs[0]]["query"])
            neg2 = np.expand_dims(neg2, axis=0)
            output.append(neg2)
        return output

    @abstractmethod