I am doing SGD on linear regression. I referred to this book, https://github.com/fastai/fastai/blob/master/courses/dl1/lesson6-sgd.ipynb

It gives me below error, while I do exact code in python module/source file. I checked it multiple time to see if I missed an obvious thing.

Traceback (most recent call last):

File “C:/Users/Mahesh.Bhosale/PycharmProjects/Pytorch_learning/pytorch_tutorials/linear_regression.py”, line 22, in

a = V(np.random.randn(1), requires_grad=True)

TypeError: V() got an unexpected keyword argument ‘requires_grad’

Hers my code:

#matplotlib inline

from fastai.learner import *def lin(a, b, x):

return a * x + bdef gen_fake_data(n, a, b):

x = np.random.uniform(0, 1, n)

y = lin(a, b, x) + 0.1 * np.random.normal(0, 3, n)

return x, ydef mse(pred, y): return ((pred - y) ** 2).mean()

def mse_loss(a, b, x, y): return mse(lin(a, b, x), y)

if

__name__ == ‘__main__’:

a = V(np.random.randn(1), requires_grad=True)

b = V(np.random.randn(1), requires_grad=True)

x, y = gen_fake_data(100000, 3., 8.)

x, y = V(x), V(y)

lr = 1e-3

loss = mse_loss(a, b, x, y)

print(type(loss))

for t in range(10000):

loss = mse_loss(a, b, x, y)

if t % 1000 == 0: print(loss.data[0])

loss.backword()