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import torch
import numpy as np
#Input (temp,rainfall,humidity)
inputs=np.array([
    [73,67,43],
    [91,88,64],
    [87,134,58],
    [102,43,37],
    [69,96,70]], dtype='float32')
inputs
array([[ 73.,  67.,  43.],
       [ 91.,  88.,  64.],
       [ 87., 134.,  58.],
       [102.,  43.,  37.],
       [ 69.,  96.,  70.]], dtype=float32)
#Taregt (apples,oranges)
targets=np.array([
    [56,70],
    [81,101],
    [119,133],
    [22,37],
    [103,119]],dtype='float32')
targets
array([[ 56.,  70.],
       [ 81., 101.],
       [119., 133.],
       [ 22.,  37.],
       [103., 119.]], dtype=float32)
#convert inputs and targets into tensors
inputs=torch.from_numpy(inputs)
targets=torch.from_numpy(targets)
print(inputs)
print(targets)
tensor([[ 73., 67., 43.], [ 91., 88., 64.], [ 87., 134., 58.], [102., 43., 37.], [ 69., 96., 70.]]) tensor([[ 56., 70.], [ 81., 101.], [119., 133.], [ 22., 37.], [103., 119.]]) 
#Weight and Biases
w=torch.randn(2,3,requires_grad=True)
b=torch.randn(2,requires_grad=True)
print(w)
print(b)
tensor([[-0.1534, -0.6423, 2.4070], [ 1.2565, -0.5321, -0.1870]], requires_grad=True) tensor([-0.8002, 1.3235], requires_grad=True)