Gluon sgd

from mxnet import nd,autograd,init,gluon from mxnet.gluon import data as gdata,loss as gloss,nn num_inputs = 2 num_examples = 1000 true_w = [2,-3.4] true_b = 4.2 features = nd.random.normal(scale=1,

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