dist_transpose.py

# 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

from .common import DistributedOperatorImplContainer
from .common import DistributedOperatorImpl
from .common import register_distributed_operator_impl_container
from .common import register_distributed_operator_impl
from ..utils import is_dim_shard
from ..utils import is_dim_replicate
from ..utils import is_valid_list_index
from ..utils import compute_compatible_dim_mapping
from ..utils import compute_compatible_dims_mapping
from ..utils import compute_compatible_and_update_dim_mapping


class DistributedTranspose2(DistributedOperatorImplContainer):
    def __init__(self, name):
        super(DistributedTranspose2, self).__init__()
        self._name = name


register_distributed_operator_impl_container(
    "transpose2", DistributedTranspose2("transpose2"))


class DistributedTranspose2Impl(DistributedOperatorImpl):
    def __init__(self, name):
        super(DistributedTranspose2Impl, self).__init__()
        self._name = name
        self._forward_implemented = False
        self._backward_implemented = True

    def is_input_compatible(self, dist_op):
        return True

    def is_output_compatible(self, dist_op):
        return True

    def is_auto_compatible(self, dist_op):
        op_desc = dist_op.serial_op.desc
        op_dist_attr = dist_op.dist_attr
        perm = op_desc.attr('axis')
        x_name = op_desc.input('X')[0]
        out_name = op_desc.output('Out')[0]
        x_shape_name = op_desc.output('XShape')[0]
        x_shape_dims_mapping = op_dist_attr.get_output_dims_mapping(
            x_shape_name)
        x_dims_mapping = op_dist_attr.get_input_dims_mapping(x_name)
        out_dims_mapping = op_dist_attr.get_output_dims_mapping(out_name)
        new_dims_mapping = [-1 for i in range(len(x_dims_mapping))]
        for i in range(len(x_dims_mapping)):
            new_dims_mapping[i] = x_dims_mapping[perm[i]]

        if len(x_dims_mapping) != len(out_dims_mapping):
            return False

        if new_dims_mapping != out_dims_mapping:
            return False

        if x_shape_dims_mapping[0] != -1:
            return False

        if x_shape_dims_mapping[1:] != x_dims_mapping[:]:
            return False

        return True

    def update_dims_mapping(self, dist_op):
        changed = False
        op_desc = dist_op.serial_op.desc
        op_dist_attr = dist_op.dist_attr
        x_name = op_desc.input('X')[0]
        out_name = op_desc.output('Out')[0]
        x_shape_name = op_desc.output('XShape')[0]
        x_dims_mapping = op_dist_attr.get_input_dims_mapping(x_name)
        out_dims_mapping = op_dist_attr.get_output_dims_mapping(out_name)
        x_shape_dims_mapping = op_dist_attr.get_output_dims_mapping(
            x_shape_name)
        perm = op_desc.attr('axis')

        assert len(x_dims_mapping) == len(perm)

        new_dims_mapping = [-1 for i in range(len(x_dims_mapping))]
        for i in range(len(x_dims_mapping)):
            new_dims_mapping[i] = x_dims_mapping[perm[i]]

        for i in range(len(out_dims_mapping)):
            dim_changed = compute_compatible_and_update_dim_mapping(
                [new_dims_mapping, out_dims_mapping], [i, i])
            if dim_changed:
                changed = True

        for i in range(len(x_dims_mapping)):
            if x_dims_mapping[perm[i]] != new_dims_mapping[i]:
                x_dims_mapping[perm[i]] = new_dims_mapping[i]
                changed = True

        for i in range(len(x_dims_mapping)):
            x_shape_dims_mapping[i + 1] = x_dims_mapping[i]

        return changed

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


register_distributed_operator_impl(
    "transpose2", DistributedTranspose2Impl("same_mapping_transpose"))