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Updated 5 years ago
import jovian
jovian.commit()
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import numpy as np
import pandas as pd
import torch
# make zhe data
inputes = np.array([[73,67, 43],
[91, 88, 64],
[87, 134, 58],
[102, 43, 37],
[69, 96, 70]],dtype="float32"
)
targets = np.array([[56, 70],
[81, 101],
[119, 133],
[22, 37],
[103, 119]],dtype="float32"
)
inputes = torch.from_numpy(inputes)
targets = torch.from_numpy(targets)
# initialize the weight and biase
# w = np.random.randn(2,3)
# b = np.random.randn(5,2)
w = torch.randn(2,3, requires_grad=True)
b = torch.randn(2, requires_grad=True)