utils.py 文件源码

def get_epoch_indexes(self):
        B = self.batch_size
        K = self.num_classes
        M = self.num_per_class
        N = K * M  # number of total examples
        num_batches = M * int(K // B)  # number of batches per epoch

        indexes = np.arange(N, dtype=np.int32).reshape(K, M)
        epoch_indexes = []
        for m in range(M):
            perm = np.random.permutation(K)
            c_batches = np.array_split(perm, num_batches // M)
            for c_batch in c_batches:
                b = len(c_batch)  # actual number of examples of this batch
                indexes_anchor = M * c_batch + m

                positive_candidates = np.delete(indexes[c_batch], m, axis=1)
                indexes_positive = positive_candidates[
                    range(b), np.random.choice(M - 1, size=b)]

                epoch_indexes.append((indexes_anchor, indexes_positive))

        return epoch_indexes