[PyTorch] torch 함수

Function 1 — torch.tensor

t1 = torch.tensor([[21,39],[31,30],[23,43],[11,46],[26,46],[31,25],[21,38],[22,39],[22,19],[18, 14]])
t1

t2 = torch.tensor([])
t2
t2.size()

Function 2 — torch.from_numpy

a1 = np.array([[1,2,3],[4,5,6]])
a1.dtype
t1 = torch.from_numpy(a1)
t1.dtype

Hight_Weight = np.array([[161,67],[154,76],[172, 61]])
Heart_Rate = np.array([78,89,72])
(Hight_Weight.dtype, Heart_Rate.dtype)

l2 = (Hight_Weight, Heart_Rate)            
for i in l2 :
  tensor = torch.from_numpy(i)
  print("Type of the element\n {}\n is {}\n".format(i, tensor.dtype))

 

 

A NumPy array containing string elements cannot be converted to a tensor. The only supported types for a tensor are : float64, float32, float16, complex64, complex128, int64, int32, int16, int8, uint8, and bool.

 

Function 6 — torch.eye

torch.eye(n=4, m=5)
torch.eye(n=3)

 

Function 7 — torch.full

torch.full(size=(3,2), fill_value=10)
torch.full(size=[2, 3, 4], fill_value=5)

 

Function 11 — torch.view 

# Example 1 - working
random_tensor = torch.arange(1., 17.)
print(random_tensor)
random_tensor.view(8,2)

tensor([ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13., 14.,
        15., 16.])
tensor([[ 1.,  2.],
        [ 3.,  4.],
        [ 5.,  6.],
        [ 7.,  8.],
        [ 9., 10.],
        [11., 12.],
        [13., 14.],
        [15., 16.]])
z = x.view(-1, 8)

 

 

 

[Pytorch] torch 유용한 함수 정리하기