# Copyright (c) 2022 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.

from .common import DistributedOperatorImplContainer
from .common import DistributedOperatorImpl
from .common import register_distributed_operator_impl_container
from .common import register_distributed_operator_impl
from .dist_default import DistributedDefaultImpl0
from ..utils import is_dim_shard


class DistributedShape(DistributedOperatorImplContainer):
    def __init__(self, op_type):
        super(DistributedShape, self).__init__(op_type)


register_distributed_operator_impl_container(DistributedShape("shape"))


class DistributedShapeImpl(DistributedOperatorImpl):
    def __init__(self, name):
        super(DistributedShapeImpl, self).__init__(name)
        self._forward_implemented = True
        self._backward_implemented = True

    def is_input_compatible(self, dist_op):
        return True

    def is_output_compatible(self, dist_op):
        op_desc = dist_op.serial_op.desc
        op_dist_attr = dist_op.dist_attr
        out_name = op_desc.output('Out')[0]
        out_dims_mapping = op_dist_attr.get_output_dims_mapping(out_name)

        assert len(out_dims_mapping) == 1
        if is_dim_shard(out_dims_mapping[0]):
            return False

        return True

    def is_auto_compatible(self, dist_op):
        if (not self.is_input_compatible(dist_op)) or (
            not self.is_output_compatible(dist_op)
        ):
            return False

        return True

    def update_dims_mapping(self, dist_op):
        return False

    @staticmethod
    def forward(ctx, *args, **kwargs):
        DistributedDefaultImpl0.forward(ctx, *args, **kwargs)

    @staticmethod
    def backward(ctx, *args, **kwargs):
        DistributedDefaultImpl0.backward(ctx, *args, **kwargs)


register_distributed_operator_impl("shape", DistributedShapeImpl("shape"))
