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]