# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import paddle
import paddle.nn as nn
import paddle.nn.functional as F
from utils import index_sample


class ParserCriterion(nn.Layer):
    def __init__(self, *args, **kwargs):
        super(ParserCriterion, self).__init__(*args, **kwargs)

    def __call__(self, s_arc, s_rel, arcs, rels, mask):

        arcs = paddle.masked_select(arcs, mask)
        rels = paddle.masked_select(rels, mask)

        select = paddle.nonzero(mask)
        s_arc = paddle.gather_nd(s_arc, select)
        s_rel = paddle.gather_nd(s_rel, select)

        s_rel = index_sample(s_rel, paddle.unsqueeze(arcs, axis=1))

        arc_cost = F.cross_entropy(s_arc, arcs)
        rel_cost = F.cross_entropy(s_rel, rels)

        avg_cost = paddle.mean(arc_cost + rel_cost)
        return avg_cost
