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# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
# Copyright 2019 Kakao Brain
#
# 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.
"""Provides phony for arbitrary dependency in a autograd graph."""
from typing import Dict, List, Tuple
import torch
from torch import Tensor
from .stream import default_stream, use_stream
__all__: List[str] = []
_phonies: Dict[Tuple[torch.device, bool], Tensor] = {}
def get_phony(device: torch.device, *, requires_grad: bool) -> Tensor:
"""Gets a phony. Phony is tensor without space. It is useful to make
arbitrary dependency in a autograd graph because it doesn't require any
gradient accumulation.
.. note::
Phonies for each device are cached. If an autograd function gets a phony
internally, the phony must be detached to be returned. Otherwise, the
autograd engine will mutate the cached phony in-place::
class Phonify(torch.autograd.Function):
@staticmethod
def forward(ctx, input):
phony = get_phony(input.device, requires_grad=False)
return phony.detach() # detach() is necessary.
"""
key = (device, requires_grad)
try:
phony = _phonies[key]
except KeyError:
with use_stream(default_stream(device)):
# Creating phony with size 1 instead of zero, since currently
# tensorpipe does not work with tensors of size zero.
phony = torch.empty(1, device=device, requires_grad=requires_grad)
_phonies[key] = phony
return phony
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