Metadata-Version: 2.1
Name: extorch
Version: 1.0.3
Summary: An useful extension library of PyTorch.
Home-page: https://github.com/A-LinCui/Extorch
Author: Junbo Zhao
Author-email: zhaojunbo2012@sina.cn
License: MIT License
Description: ![](https://img.shields.io/badge/version-1.0.3-yellow)
        ## Extorch: An useful extension library of PyTorch.
        
        [**Extorch**](https://github.com/A-LinCui/Extorch) is an extension library of [**PyTorch**](https://github.com/pytorch/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](https://extorch.readthedocs.io/en/latest/).
        
        
        🚀 Quickstart
        --------------
        As the API of this project may alter frequently in its early days, we recommand use the newest version at the [GitHub](https://github.com/A-LinCui/Extorch) 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.
        
Keywords: PyTorch
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Description-Content-Type: text/markdown
