Skip to main content

Extorch: An useful extension library of PyTorch.

Extorch is an extension library of PyTorch that lets you easily build deep learning systems with PyTorch.

📖 Documentation

  • Tutorial: If you are looking for a tutorial, check out examples under ./example.
  • Documentation: The API documentation can be found on ReadTheDocs.

🚀 Quickstart

As the API of this project may alter frequently in its early days, we recommand use the newest version at the GitHub following two steps below.

Step 1: git clone https://github.com/A-LinCui/Extorch

Step 2: bash install.sh

If you'd like to use the previous stable version. Simply run pip install extorch in the command line.

🎉 Example

    import extorch.vision.dataset as dataset
    import torch.utils.data as data

    BATCH_SIZE = 128
    NUM_WORKERS = 2

    data_dir = "~/data" # Path to load the dataset
    datasets = dataset.CIFAR10(data_dir) # Construct the CIFAR10 dataset with standard transforms.

    trainloader = data.DataLoader(dataset = datasets.splits()["train"], \
            batch_size = BATCH_SIZE, num_workers = NUM_WORKERS, shuffle = True)
    testloader = data.DataLoader(dataset = datasets.splits()["test"], \
            batch_size = BATCH_SIZE, num_workers = NUM_WORKERS, shuffle = False)

More examples can be found in the ./example folder.

👍 Contributions

We welcome contributions of all kind.

Release files for extorch 1.0.4

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for extorch 1.0.4
File Interpreter ABI Platform
extorch-1.0.4-py3-none-any.whl Python 3 none any Details

Release files / extorch-1.0.4-py3-none-any.whl

Download URL extorch-1.0.4-py3-none-any.whl
Size 40.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
a3ea05a702d44af525dc04aabdca36b58f5a15416bee4298be3bec79520d44d9
BLAKE2b-256 checksum
How to use checksums
67bdc4067611c834c2b4325c02a8e8a0ccc6495fb62f26373fb08067a4b0c8dd
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.24.0 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.5

Release history Release notifications | RSS feed

This release

1.0.4 This release

1 release file

1.0.3

3 release files

1.0.2

2 release files

1.0.1

2 release files

1.0

3 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page