From b58b07e75c5466fa0ad6503523167ae78344dcac Mon Sep 17 00:00:00 2001 From: Patrice Billaut Date: Mon, 26 May 2025 21:20:16 +0200 Subject: [PATCH] feat(dataset): add dataset and data loader for tokenized text processing --- llm/dataset.py | 49 +++++ pyproject.toml | 4 + tests/test_data_loader.py | 24 +++ uv.lock | 394 ++++++++++++++++++++++++++++++++++++++ 4 files changed, 471 insertions(+) create mode 100644 llm/dataset.py create mode 100644 tests/test_data_loader.py diff --git a/llm/dataset.py b/llm/dataset.py new file mode 100644 index 0000000..fe605e5 --- /dev/null +++ b/llm/dataset.py @@ -0,0 +1,49 @@ +import tiktoken +import torch +from tiktoken import Encoding +from torch.utils.data import DataLoader, Dataset + + +def create_data_loader( + text: str, + max_length: int, + stride: int, + batch_size: int, + shuffle: bool, + drop_last: bool = True, + num_workers: int = 0, +) -> DataLoader: + tokenizer = tiktoken.get_encoding("gpt2") + dataset = GptDatasetV1( + text=text, + tokenizer=tokenizer, + max_length=max_length, + stride=stride, + ) + return DataLoader( + dataset=dataset, + batch_size=batch_size, + shuffle=shuffle, + drop_last=drop_last, + num_workers=num_workers, + ) + + +class GptDatasetV1(Dataset): + def __init__(self, text: str, tokenizer: Encoding, max_length: int, stride: int): + self.input_ids = [] + self.target_ids = [] + + token_ids = tokenizer.encode(text) + + for i in range(0, len(token_ids) - max_length, stride): + input_chunk = token_ids[i : i + max_length] + target_chunk = token_ids[i + 1 : i + max_length + 1] + self.input_ids.append(torch.tensor(input_chunk)) + self.target_ids.append(torch.tensor(target_chunk)) + + def __len__(self) -> int: + return len(self.input_ids) + + def __getitem__(self, index: int) -> tuple[int, int]: + return self.input_ids[index], self.target_ids[index] diff --git a/pyproject.toml b/pyproject.toml index a724607..6111436 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -3,6 +3,10 @@ name = "largelanguagemodel" version = "0.1.0" description = "Experimenting with LLMs" requires-python = ">=3.13" +dependencies = [ + "tiktoken>=0.9.0", + "torch>=2.7.0", +] [dependency-groups] dev = [ diff --git a/tests/test_data_loader.py b/tests/test_data_loader.py new file mode 100644 index 0000000..170e182 --- /dev/null +++ b/tests/test_data_loader.py @@ -0,0 +1,24 @@ +from pathlib import Path + +import torch + +from llm.dataset import create_data_loader + + +def test_data_loader(resource: Path): + path = resource / "the-verdict.txt" + text = path.read_text(encoding="utf-8") + + data_loader = create_data_loader( + text=text, + batch_size=1, + max_length=4, + stride=1, + shuffle=False, + ) + + data_iter = iter(data_loader) + inputs, targets = next(data_iter) + + assert torch.equal(inputs, torch.tensor([[40, 367, 2885, 1464]])) + assert torch.equal(targets, torch.tensor([[367, 2885, 1464, 1807]])) diff --git a/uv.lock b/uv.lock index a807ffb..0e1e550 100644 --- a/uv.lock +++ b/uv.lock @@ 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