Consider the following lines of code. How many Parameters does the object model have?12from torch.nn import Linearmodel=Linear(in_features=1,out_features=1)1 point123None of the above

Question 2How many dimensions is the input for the following neural network object:45678910111213321        self.linear1=nn.Linear(D_in,H)        self.linear2=nn.Linear(H,D_out)             def forward(self,x):        x=torch.sigmoid(self.linear1(x))          x=torch.sigmoid(self.linear2(x))        return x        model=Net(4,10,1)        super(Net,self).__init__()    def __init__(self,D_in,H,D_out):class Net(nn.Module):

How would you create a linear object with ten input features?1 pointmodel=nn.Linear(1,10)model=nn.Linear(10,1)

5. Assume we store the values for nl in an array called layer_dims, as follows: layer_dims = [NI, ,4,3,2,1]. So layer 11 pointhas four hidden units, layer 2 has 3 hidden units, and so on. Which of the following for-loops will allow you toinitialize the parameters for the model?for i in range(len(layer_dims)-1):parameter['W + str(i+1)] = p.random.randn(layer_dims[i+1],layer_dims[i])*0.0144:51parameter['b' + str(i+1)] = hp.random.randn(layer_dims[i+1],1)*0.01for i in range(len(layer_dims)-1):parameter['W + str(i+1)] = p.random.randn(layer_dims[i], layer_dims[i+1])*0.01parameter['b' + str(i+1)] p.random.randn(layer_dims[i+1],1)*0.01.for i in range(1, len(layer_dims)/2):parameter['V + str(i)] np.random.randn(layer_dims[i],layer_dims[i-1])*0.01parameter['b' + str(i)] Ip.random.randn(layer_dims[i],1)*0.01for i in range(len(layer_dims)):parameter["W" + str(i+1)] = np.random.randn(layer_dims[i+1],layer_dims[i])*0.01parameter['b' str(i+1)] Inp.random.randn(layer_dims[i+1],1)*0.03

# Find the output of the following:tensor_A = torch.tensor([[1, 2], [3, 4], [5, 6]], dtype=torch.float32)tensor_B = torch.tensor([[7, 10], [8, 11], [9, 12]], dtype=torch.float32)torch.matmul(tensor_A, tensor_B) )[[58,64],[139,154]][[27,30,33],[61,68,75],[95,106,117]]value errornone of the above

Consider the following code:1a=torch.tensor([[0,1,1],[1,0,1]])What is the output of a.size() and a.ndimension()?