PoliBa-DeepLearning/NanoSocrates
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WIP NanoSocratesEmbedder for batching

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This commit is contained in:
GassiGiuseppe 2025-10-06 21:41:45 +02:00
parent 56d438f01a
commit 14b810c451
1 changed files with 5 additions and 3 deletions
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8
Project_Model/Libs/Embedder/Classes/NanoSocratesEmbedder.py
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@ -1,5 +1,7 @@
import torch
from ..Utils import fixed_positional_encoding
# WIP FOR BATCHING
class NanoSocratesEmbedder(torch.nn.Module):
def __init__(
@ -13,20 +15,20 @@ class NanoSocratesEmbedder(torch.nn.Module):
embedding_size
)
def forward(self, tokenized_sentence: list[int]) -> torch.Tensor:
def forward(self, tokenized_sentence: list[list[int]]) -> torch.Tensor:
TOKENIZED_TENSOR = torch.tensor(tokenized_sentence)
computed_embeddings: torch.Tensor = self.__embedder(TOKENIZED_TENSOR)
SENTENCE_LENGHT, EMBEDDING_SIZE = computed_embeddings.shape
_ ,SENTENCE_LENGHT, EMBEDDING_SIZE = computed_embeddings.shape # for batching
POSITIONAL_ENCODINGS = fixed_positional_encoding(
SENTENCE_LENGHT,
EMBEDDING_SIZE
)
computed_embeddings = computed_embeddings + POSITIONAL_ENCODINGS
computed_embeddings = computed_embeddings + POSITIONAL_ENCODINGS.unsqueeze(0) # for batching
return computed_embeddings