Paulo Mann paulomann
paulomann
/ quantizable_resnet.py
Last active
October 31, 2019 01:12
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| class Bottleneck(nn.Module): | |
| ''' Standard bottleneck block | |
| input = inplanes * H * W | |
| middle = planes * H/stride * W/stride | |
| output = 4*planes * H/stride * W/stride | |
| ''' | |
| expansion = 4 | |
| def __init__(self, inplanes, planes, stride=1, dilation=1, downsample=None): | |
| super(Bottleneck, self).__init__() |
paulomann
/ training_LSTM.py
Created
June 28, 2019 17:10
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| class Trainer(): | |
| def __init__(self, model, dataloaders, dataset_sizes, criterion, optimizer, | |
| scheduler, num_epochs=100, threshold=0.5): | |
| self.acc_loss = {"train": {"loss": [], "acc": []}, | |
| "val": {"loss": [], "acc": []}} | |
| self.device = torch.device( | |
| "cuda:0" if torch.cuda.is_available() else "cpu") | |
| self.model = model.to(self.device) | |
| print("Using device ", self.device) |