# -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""Base drift compensation for inference."""
from typing import Tuple, TYPE_CHECKING
from torch import Tensor
from torch.autograd import no_grad
if TYPE_CHECKING:
from aihwkit.simulator.tiles.inference import InferenceTileWithPeriphery
[docs]
class BaseDriftCompensation:
"""Base class for drift compensations."""
def __init__(self) -> None:
pass
[docs]
@no_grad()
def init_baseline(self, tile: "InferenceTileWithPeriphery") -> Tuple[Tensor, Tensor]:
"""Initialize the base line for applying the compensation.
Uses a all one tensor for read_out.
Args:
tile: forward output of the read out vector to compensate
Returns:
reference tensor readout
"""
forward_output = tile._forward_drift_readout_tensor(True, exact_reference=False)
ref_value = self.readout(forward_output)
return ref_value
[docs]
@no_grad()
def get_readout_tensor(self, in_size: int) -> Tensor:
"""Return the read-out tensor.
Called once during :meth:`~init_baseline`.
"""
raise NotImplementedError
[docs]
@no_grad()
def readout(self, out_tensor: Tensor) -> Tensor:
"""Implement the read out math."""
raise NotImplementedError
[docs]
@no_grad()
def apply(self, forward_output: Tensor, ref_value: Tensor) -> Tensor:
"""Read out the current value from the output of the forward
pass and returns the drift compensation alpha scale."""
current_value = self.readout(forward_output)
ratio = ref_value / current_value
return ratio