| import torch | |
| from torch.utils.data import DataLoader, TensorDataset | |
| import torch.nn as nn | |
| import torch.optim as optim | |
| class SimpleANN(nn.Module): | |
| def __init__(self): | |
| super(SimpleANN, self).__init__() | |
| self.hidden = nn.Linear(16, 8) | |
| self.output = nn.Linear(8, 1) | |
| self.sigmoid = nn.Sigmoid() | |
| def forward(self, x): | |
| x = torch.relu(self.hidden(x)) | |
| x = self.sigmoid(self.output(x)) | |
| return x | |
| # model = SimpleANN() | |
| # model.load_state_dict(torch.load(r'D:\yowov2V7\YOWOv2\model_weights.pth')) | |
| # model.eval() | |
| # outputs = model(X_batch) # đưa cái chuỗi 16 cái có hay ko vô đây | |
| # predicted = outputs.round() |