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| import torch | |
| import torchvision | |
| from torch import nn | |
| from helper import setAllSeeds | |
| def getEffNetModel(seed,numClasses): | |
| setAllSeeds(seed) | |
| effNetWeights = torchvision.models.EfficientNet_B2_Weights.DEFAULT | |
| effNetTransforms = effNetWeights.transforms() | |
| effNet = torchvision.models.efficientnet_b2(weights=effNetWeights) | |
| for param in effNet.parameters(): | |
| param.requires_grad = False | |
| effNet.classifier = nn.Sequential( | |
| nn.Dropout(p=0.3,inplace=True), | |
| nn.Linear(1408,numClasses,bias=True) | |
| ) | |
| return effNet,effNetTransforms | |