This should provide you sufficient info to you help debug this issue.Input size(1,3,224,224)
Module class
!pip install efficientnet_pytorch
from efficientnet_pytorch import EfficientNet
model = EfficientNet.from_pretrained(‘efficientnet-b5’, num_classes=5)
class efficient(nn.Module):
    
    
  
    def __init__(self,m):
        super().__init__()
        
        l=nn.Sequential()
        fc=nn.Sequential()
        l.add_module('conv_stem',m._conv_stem)
        l.add_module('_bn0',m._bn0)
        l.add_module('_blocks',m._blocks)
        l.add_module('_conv_head',m._conv_head)
        
        self.add_module('feature',l)
        fc.add_module('_bn1',m._bn1)
        fc.add_module('_fc',m._fc)
        
        self.add_module('fc',fc)
         
         
        
         
    def forward(self, x):
         
        x1=self.feature(x)
        x1= self.fc(x1)
        #x1=self._blocks(x1)
        #x1=self._conv_head(x1)
        #x1=self._bn1(x1)
        #x = x.view(x.size(0), -1)
         
        #x=self.l1(x)
       # x = self.x_unet(x, self.sfs[0].features)
        #x1 = self.fc(x)
        return x1

m=efficient(model)
m(x)
Gives Not implemented error
result = self.forward(*input, **kwargs)
494         for hook in self._forward_hooks.values():
495             hook_result = hook(self, input, result)
/opt/conda/lib/python3.6/site-packages/torch/nn/modules/container.py in forward(self, input)
90     def forward(self, input):
91         for module in self._modules.values():
—> 92             input = module(input)
93         return input
94
/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py in call(self, *input, **kwargs)
491             result = self._slow_forward(*input, **kwargs)
492         else:
–> 493             result = self.forward(*input, **kwargs)
494         for hook in self._forward_hooks.values():
495             hook_result = hook(self, input, result)
/opt/conda/lib/python3.6/site-packages/torch/nn/modules/container.py in forward(self, input)
90     def forward(self, input):
91         for module in self._modules.values():
—> 92             input = module(input)
93         return input
94
/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py in call(self, *input, **kwargs)
491             result = self._slow_forward(*input, **kwargs)
492         else:
–> 493             result = self.forward(*input, **kwargs)
494         for hook in self._forward_hooks.values():
495             hook_result = hook(self, input, result)
/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py in forward(self, *input)
86             registered hooks while the latter silently ignores them.
87         “”"
—> 88         raise NotImplementedError