dist_softmax.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
from .dist_default import DistributedDefaultImpl0


class DistributedSoftmax(DistributedOperatorImplContainer):

    def __init__(self, op_type):
        super(DistributedSoftmax, self).__init__(op_type)


register_distributed_operator_impl_container(DistributedSoftmax("softmax"))


class DistributedSoftmaxImpl(DistributedOperatorImpl):

    def __init__(self, name):
        super(DistributedSoftmaxImpl, self).__init__(name)
        self._forward_implemented = False
        self._backward_implemented = False

    def is_input_compatible(self, dist_op):
        op_desc = dist_op.serial_op.desc
        op_dist_attr = dist_op.dist_attr
        x_name = op_desc.input('X')[0]
        axis = op_desc.attr('axis')
        x_dims_mapping = op_dist_attr.get_input_dims_mapping(x_name)

        # if axis != -1 and axis != len(x_dims_mapping) - 1:
        #     return False

        if is_dim_shard(x_dims_mapping[axis]):
            return False

        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]
        axis = op_desc.attr('axis')
        out_dims_mapping = op_dist_attr.get_output_dims_mapping(out_name)

        # if axis != -1 and axis != len(out_dims_mapping) - 1:
        #     return False

        if is_dim_shard(out_dims_mapping[axis]):
            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

        op_desc = dist_op.serial_op.desc
        op_dist_attr = dist_op.dist_attr
        x_name = op_desc.input('X')[0]
        axis = op_desc.attr('axis')
        out_name = op_desc.output('Out')[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)
        # if axis != -1 and axis != len(x_dims_mapping) - 1:
        #     return False

        if x_dims_mapping != out_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_dims_mapping = op_dist_attr.get_input_dims_mapping(x_name)
        out_dims_mapping = op_dist_attr.get_output_dims_mapping(out_name)

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

        return changed

    @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(
    "softmax", DistributedSoftmaxImpl("replicate_last_axis"))