Metadata-Version: 2.1
Name: torchlit
Version: 0.1.0
Summary: torchlit - thin wrappers for Pytorch
Home-page: https://github.com/himanshu-dutta/torchlit
Author: Himanshu Dutta
Author-email: meet.himanshu.dutta@gmail.com
License: MIT License
Description: # torchlit
        
        `torchlit` is an in progress collection of Pytorch utilities and thin wrappers which can be used for various purposes.
        
        With every project, I intend to add functionalities that are fairly genralized to be put as a boilerplate for different utilities.
        
        ## Sample usage
        
        ```python
        import torch.nn as nn
        import torch.nn.functional as F
        
        import torchlit
        
        class Net(torchlit.Model):
            def __init__(self):
                super(Net, self).__init__(F.cross_entropy, record=True, verbose=True)
                self.conv1 = nn.Conv2d(1, 20, 5)
                self.conv2 = nn.Conv2d(20, 20, 5)
        
            def forward(self, x):
                x = F.relu(self.conv1(x))
                return F.relu(self.conv2(x))
        
        train_ds = Dataset()
        val_ds = Dataset()
        
        train_dl = DataLoader()
        val_dl = DataLoader()
        
        EPOCH = 100
        model = Net()
        
        for epoch in range(EPOCHS):
            for xb in train_dl:
                model.train_step(xb)
        
            for xb in val_dl:
                model.val_step(xb)
        
            model.epoch_end()
        ```
        
Platform: linux
Platform: unix
Requires-Python: >3.5.2
Description-Content-Type: text/markdown
