full() can create a 1D or more D tensor filled with the zero or more integers, floating-point numbers, complex numbers or boolean values as shown below:
*Memos:
-
full()can be used with torch but not with a tensor. - The 1st argument(
tupleofint,listofintortorch.Size) issize(Required). - The 2nd argument(
int,float,complexorbool) isfill_value(Required).
import torch
torch.full(size=(0,), fill_value=5)
# tensor([], dtype=torch.int64)
torch.full(size=(3,), fill_value=5)
# tensor([5, 5, 5])
torch.full(size=(3, 2), fill_value=5)
# tensor([[5, 5], [5, 5], [5, 5]])
torch.full(size=(3, 2, 4), fill_value=5)
# tensor([[[5, 5, 5, 5], [5, 5, 5, 5]],
# [[5, 5, 5, 5], [5, 5, 5, 5]],
# [[5, 5, 5, 5], [5, 5, 5, 5]]])
torch.full(size=(3, 2, 4), fill_value=5.)
# tensor([[[5., 5., 5., 5.], [5., 5., 5., 5.]],
# [[5., 5., 5., 5.], [5., 5., 5., 5.]],
# [[5., 5., 5., 5.], [5., 5., 5., 5.]]])
torch.full(size=(3, 2, 4), fill_value=5+6j)
# tensor([[[5.+6.j, 5.+6.j, 5.+6.j, 5.+6.j],
# [5.+6.j, 5.+6.j, 5.+6.j, 5.+6.j]],
# [[5.+6.j, 5.+6.j, 5.+6.j, 5.+6.j],
# [5.+6.j, 5.+6.j, 5.+6.j, 5.+6.j]],
# [[5.+6.j, 5.+6.j, 5.+6.j, 5.+6.j],
# [5.+6.j, 5.+6.j, 5.+6.j, 5.+6.j]]])
torch.full(size=(3, 2, 4), fill_value=True)
# tensor([[[True, True, True, True],
# [True, True, True, True]],
# [[True, True, True, True],
# [True, True, True, True]],
# [[True, True, True, True],
# [True, True, True, True]]])
full_like() can replace the zero or more integers, floating-point numbers, complex numbers or boolean values of 0D or more D tensor with the zero or more integers, floating-point numbers, complex numbers or boolean values as shown below:
*Memos:
-
full_like()can be used withtorchbut not with a tensor. - The 2nd argument(
int,float,complexorbool) isfill_value(Required).
import torch
my_tensor = torch.tensor(7)
torch.full_like(my_tensor, fill_value=5)
# tensor(5)
my_tensor = torch.tensor([7, 4, 5])
torch.full_like(my_tensor, fill_value=5)
# tensor([5, 5, 5])
my_tensor = torch.tensor([[7, 4, 5],
[2, 8, 3]])
torch.full_like(my_tensor, fill_value=5)
# tensor([[5, 5, 5], [5, 5, 5]])
my_tensor = torch.tensor([[[7, 4, 5], [2, 8, 3]],
[[6, 0, 1], [5, 9, 4]]])
torch.full_like(my_tensor, fill_value=5)
# tensor([[[5, 5, 5], [5, 5, 5]],
# [[5, 5, 5], [5, 5, 5]]])
my_tensor = torch.tensor([[[7., 4., 5.], [2., 8., 3.]],
[[6., 0., 1.], [5., 9., 4.]]])
torch.full_like(my_tensor, fill_value=5.)
# tensor([[[5., 5., 5.], [5., 5., 5.]],
# [[5., 5., 5.], [5., 5., 5.]]])
my_tensor = torch.tensor([[[7+4j, 4+2j, 5+3j], [2+5j, 8+1j, 3+9j]],
[[6+9j, 0+3j, 1+8j], [5+3j, 9+4j, 4+6j]]])
torch.full_like(my_tensor, fill_value=5+3j)
# tensor([[[5.+3.j, 5.+3.j, 5.+3.j], [5.+3.j, 5.+3.j, 5.+3.j]],
# [[5.+3.j, 5.+3.j, 5.+3.j], [5.+3.j, 5.+3.j, 5.+3.j]]])
my_tensor = torch.tensor([[[True, False, True],
[False, True, False]],
[[True, False, True],
[False, True, False]]])
torch.full_like(my_tensor, fill_value=False)
# tensor([[[False, False, False],
# [False, False, False]],
# [[False, False, False],
# [False, False, False]]])
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