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# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import uuid
from typing import Dict, Optional
from torch import Tensor
class FairseqIncrementalState(object):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.init_incremental_state()
def init_incremental_state(self):
self._incremental_state_id = str(uuid.uuid4())
def _get_full_incremental_state_key(self, key: str) -> str:
return "{}.{}".format(self._incremental_state_id, key)
def get_incremental_state(
self,
incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]],
key: str,
) -> Optional[Dict[str, Optional[Tensor]]]:
"""Helper for getting incremental state for an nn.Module."""
full_key = self._get_full_incremental_state_key(key)
if incremental_state is None or full_key not in incremental_state:
return None
return incremental_state[full_key]
def set_incremental_state(
self,
incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]],
key: str,
value: Dict[str, Optional[Tensor]],
) -> Optional[Dict[str, Dict[str, Optional[Tensor]]]]:
"""Helper for setting incremental state for an nn.Module."""
if incremental_state is not None:
full_key = self._get_full_incremental_state_key(key)
incremental_state[full_key] = value
return incremental_state
def with_incremental_state(cls):
cls.__bases__ = (FairseqIncrementalState,) + tuple(
b for b in cls.__bases__ if b != FairseqIncrementalState
)
return cls
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