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Source code for quaterion.train.xbm.xbm_buffer

from typing import Tuple

import torch
from torch import LongTensor, Tensor

from quaterion.train.xbm.xbm_config import XbmConfig, XbmDevice


[docs]class XbmBuffer: """A buffer implementation to hold recent N embeddings and target values. Inspired by https://github.com/msight-tech/research-xbm/blob/master/ret_benchmark/modeling/xbm.py Args: config: Config class to configure XBM settings. embedding_size: Output dimension of `EncoderHead` configured for this model. """ def __init__(self, config: XbmConfig, embedding_size: int): if config.device == XbmDevice.AUTO: device = "cuda" if torch.cuda.is_available() else "cpu" else: device = config.device self._cfg = config self._embeddings = torch.zeros((self._cfg.buffer_size, embedding_size)).to( device ) self._targets = torch.zeros(self._cfg.buffer_size, dtype=torch.long).to(device) self._pointer = 0 self._is_full = False @property def is_full(self) -> bool: return self._is_full
[docs] def get(self) -> Tuple[Tensor, LongTensor]: if self.is_full: return self._embeddings, self._targets else: return self._embeddings[: self._pointer], self._targets[: self._pointer]
[docs] def queue(self, embeddings: Tensor, targets: LongTensor) -> None: """Queue batch embeddings and targets in the buffer. Args: embeddings: Output embeddings in the batch. targets: Target values in the batch. """ batch_size = len(targets) temp_size = self._pointer + batch_size if temp_size > self._cfg.buffer_size: excess = temp_size - self._cfg.buffer_size self._embeddings[-(batch_size - excess) :] = embeddings[excess:] self._targets[-(batch_size - excess) :] = targets[excess:] self._embeddings[:excess] = embeddings[:excess] self._targets[:excess] = targets[:excess] self._pointer = excess elif temp_size == self._cfg.buffer_size: self._embeddings[-batch_size:] = embeddings self._targets[-batch_size:] = targets self._pointer = 0 else: self._embeddings[self._pointer : self._pointer + batch_size] = embeddings self._targets[self._pointer : self._pointer + batch_size] = targets self._pointer += batch_size if temp_size >= self._cfg.buffer_size and not self.is_full: self._is_full = True

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