Learn practical skills, build real-world projects, and advance your career
Created 3 years ago
import torch
import numpy as np
the training data can be represented using 2 matrices: inputs
and targets
, each with one row per observation and one column per variable.
#input (temp, rainfall, humidity)
inputs = np.array([[73, 67, 43],
[91, 88, 64],
[87, 134, 58],
[102, 43, 37],
[69, 96, 70]], dtype = 'float32')
# targets (apples, oranges)
targets = np.array([[56, 70],
[81, 101],
[119, 133],
[22, 37],
[103, 119]], dtype = 'float32')
#converting numpy to PyTorch
inputs = torch.from_numpy(inputs)
targets = torch.tensor(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.]])