Working on lab 1.

2 files changed, 62 insertions, 0 deletions

diff --git a/src/text_recognizer/datasets/__init__.py b/src/text_recognizer/datasets/__init__.py
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+++ b/src/text_recognizer/datasets/__init__.py
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+"""Dataset modules."""
+# from .emnist_dataset import fetch_dataloader
diff --git a/src/text_recognizer/datasets/emnist_dataset.py b/src/text_recognizer/datasets/emnist_dataset.py
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+++ b/src/text_recognizer/datasets/emnist_dataset.py
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+"""Fetches a DataLoader for EMNIST dataset with PyTorch."""
+from typing import Callable
+
+from torch.utils.data import DataLoader
+from torchvision.datasets import EMNIST
+
+
+def fetch_dataloader(
+    root: str,
+    split: str,
+    train: bool,
+    download: bool,
+    transform: Callable = None,
+    target_transform: Callable = None,
+    batch_size: int = 128,
+    shuffle: bool = False,
+    num_workers: int = 0,
+    cuda: bool = True,
+) -> DataLoader:
+    """Down/load the EMNIST dataset and return a PyTorch DataLoader.
+
+    Args:
+        root (str): Root directory of dataset where EMNIST/processed/training.pt and EMNIST/processed/test.pt
+            exist.
+        split (str): The dataset has 6 different splits: byclass, bymerge, balanced, letters, digits and mnist.
+            This argument specifies which one to use.
+        train (bool): If True, creates dataset from training.pt, otherwise from test.pt.
+        download (bool): If true, downloads the dataset from the internet and puts it in root directory. If
+            dataset is already downloaded, it is not downloaded again.
+        transform (Callable): A function/transform that takes in an PIL image and returns a transformed version.
+            E.g, transforms.RandomCrop.
+        target_transform (Callable): A function/transform that takes in the target and transforms it.
+        batch_size (int): How many samples per batch to load (the default is 128).
+        shuffle (bool): Set to True to have the data reshuffled at every epoch (the default is False).
+        num_workers (int): How many subprocesses to use for data loading. 0 means that the data will be loaded in
+            the main process (default: 0).
+        cuda (bool): If True, the data loader will copy Tensors into CUDA pinned memory before returning them.
+
+    Returns:
+        DataLoader: A PyTorch DataLoader with emnist characters.
+
+    """
+    dataset = EMNIST(
+        root=root,
+        split=split,
+        train=train,
+        download=download,
+        transform=transform,
+        target_transform=target_transform,
+    )
+
+    data_loader = DataLoader(
+        dataset=dataset,
+        batch_size=batch_size,
+        shuffle=shuffle,
+        num_workers=num_workers,
+        pin_memory=cuda,
+    )
+
+    return data_loader