Category : pytorch

I have a simple NN: import torch import torch.nn as nn import torch.optim as optim class Model(nn.Module): def __init__(self): super(Model, self).__init__() self.fc1 = nn.Linear(1, 5) self.fc2 = nn.Linear(5, 10) self.fc3 = nn.Linear(10, 1) def forward(self, x): x = self.fc1(x) x = torch.relu(x) x = torch.relu(self.fc2(x)) x = self.fc3(x) return x net = Model() opt = ..

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I am running Alexnet on CIFAR10 dataset using Pytorch Lightning, here is my model: class SelfSupervisedModel(pl.LightningModule): def __init__(self, hparams=None, num_classes=10, batch_size=128): super(SelfSupervisedModel, self).__init__() self.batch_size = batch_size self.loss_fn = nn.CrossEntropyLoss() self.hparams["lr"] = ModelHelper.Hyperparam.Learning_rate self.model = torchvision.models.alexnet(pretrained=False) def forward(self, x): return self.model(x) def training_step(self, train_batch, batch_idx): inputs, targets = train_batch predictions = self(inputs) loss = self.loss_fn(predictions, targets) ..

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I am trying to train a neural network with pyTorch, but I get the error in the title. I followed this tutorial, I just applied some small changes to meet my needs. Here’s the network: class ChordClassificationNetwork(nn.Module): def __init__(self, train_model=False): super(ChordClassificationNetwork, self).__init__() self.train_model = train_model self.flatten = nn.Flatten() self.firstConv = nn.Conv2d(3, 64, (3, 3)) self.secondConv ..

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The PyTorch previously installed in the remote Linux system is problematic (version 1.8.0). It is in the system folders so I don’t have privilege to uninstall or upgrade it because I am not a super user. As a result, I installed another PyTorch in my user space using command pip3 install –user –ignore-installed torch There ..

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