```
self.hidden_layer_1 = torch.nn.Linear(50,78)
self.output = torch.nn.Linear(78, 2)
```

```
def forward(self, input):
H1 = self.hidden_layer_1(input)
H1 = self.ReLU(H1)
final_inputs = self.output(H1)
# not applying activation on final_inputs because CrossEntropyLoss does that
return final_inputs
```

input shape = (2425727, 50)

```
weights = np.load('./w.npy')
bias = np.load('./b.npy')
print(weights.shape,bias.shape)# (50, 78) (78,)
self.hidden_layer_1.weight = torch.nn.Parameter(torch.from_numpy(weights))
self.hidden_layer_1.bias = torch.nn.Parameter(torch.from_numpy(bias))
```

Error - RuntimeError: The expanded size of the tensor (50) must match the existing size (78) at non-singleton dimension 1. Target sizes: [1024, 50]. Tensor sizes: [78]