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Fix inverse token mask concatenation error and add support for mps devices #5

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Fix inverse token mask concatenation error and add support for mps devices #5

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8ab27d8
fix: fixed inverse token mask concatenation error
EigenTom Feb 3, 2024
f4b2eb3
feat: added mps acceleration support for Apple Silicon devices
EigenTom Feb 3, 2024
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4 changes: 2 additions & 2 deletions bert/dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,7 @@
from torchtext.data.utils import get_tokenizer


device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
device = torch.device("cuda" if torch.cuda.is_available() else ("mps" if torch.backends.mps.is_available() else "cpu"))


class IMDBBertDataset(Dataset):
Expand Down Expand Up @@ -194,7 +194,7 @@ def _select_false_nsp_sentences(self, sentences: typing.List[str]):
return sentences[sentence_index], sentences[next_sentence_index]

def _preprocess_sentence(self, sentence: typing.List[str], should_mask: bool = True):
inverse_token_mask = None
inverse_token_mask = []
if should_mask:
sentence, inverse_token_mask = self._mask_sentence(sentence)
sentence, inverse_token_mask = self._pad_sentence([self.CLS] + sentence, [True] + inverse_token_mask)
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2 changes: 1 addition & 1 deletion bert/model.py
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Expand Up @@ -4,7 +4,7 @@
import torch.nn.functional as f


device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
device = torch.device("cuda" if torch.cuda.is_available() else ("mps" if torch.backends.mps.is_available() else "cpu"))


class JointEmbedding(nn.Module):
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2 changes: 1 addition & 1 deletion bert/trainer.py
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Expand Up @@ -11,7 +11,7 @@
from bert.dataset import IMDBBertDataset
from bert.model import BERT

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
device = torch.device("cuda" if torch.cuda.is_available() else ("mps" if torch.backends.mps.is_available() else "cpu"))


def percentage(batch_size: int, max_index: int, current_index: int):
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2 changes: 1 addition & 1 deletion main.py
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Expand Up @@ -21,7 +21,7 @@
timestamp = datetime.datetime.utcnow().timestamp()
LOG_DIR = BASE_DIR.joinpath(f'data/logs/bert_experiment_{timestamp}')

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
device = torch.device("cuda" if torch.cuda.is_available() else ("mps" if torch.backends.mps.is_available() else "cpu"))

if torch.cuda.is_available():
torch.cuda.empty_cache()
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