round() can round the zero or more elements of a 0D or more D tensor as shown below:
*Memos:
- round() can be called both from torch and a tensor.
- Only zero or more floating-point numbers or integers can be used so zero or more complex numbers or boolean values cannot be used.
- The 2nd argument with
torch
or the 1st argument with a tensor is a decimal place(decimals
). *You must usedecimals=
to set a decimal place. - Zero or more integers cannot be used with
decimals=
.
import torch
my_tensor = torch.tensor([4.7352, -2.3706, 9.1648, -7.7054])
torch.round(my_tensor)
my_tensor.round()
torch.round(my_tensor, decimals=0)
my_tensor.round(decimals=0)
# tensor([5., -2., 9., -8.])
torch.round(my_tensor, decimals=1)
my_tensor.round(decimals=1)
# tensor([4.7000, -2.4000, 9.2000, -7.7000])
torch.round(my_tensor, decimals=2)
my_tensor.round(decimals=2)
# tensor([4.7400, -2.3700, 9.1600, -7.7100])
torch.round(my_tensor, decimals=3)
my_tensor.round(decimals=3)
# tensor([4.7350, -2.3710, 9.1650, -7.7050])
torch.round(my_tensor, decimals=4)
my_tensor.round(decimals=4)
# tensor([4.7352, -2.3706, 9.1648, -7.7054])
my_tensor = torch.tensor([4, -2, 9, -7])
torch.round(my_tensor)
my_tensor.round()
# tensor([4, -2, 9, -7])
ceil() can round up the zero or more elements of a 0D or more D tensor as shown below:
*Memos:
-
ceil()
can be called both fromtorch
and a tensor. - Only zero or more floating-point numbers or integers can be used so zero or more complex numbers or boolean values cannot be used.
-
ceil()
doesn't havedecimals
argument.
import torch
my_tensor = torch.tensor([4.7352, -2.3706, 9.1648, -7.7054])
torch.ceil(my_tensor)
my_tensor.ceil()
# tensor([5., -2., 10., -7.])
my_tensor = torch.tensor([4, -2, 9, -7])
torch.ceil(my_tensor)
my_tensor.ceil()
# tensor([4, -2, 9, -7])
floor() can round down the zero or more elements of a 0D or more D tensor as shown below:
*Memos:
-
floor()
can be called both fromtorch
and a tensor. - Only zero or more floating-point numbers or integers can be used so zero or more complex numbers or boolean values cannot be used.
-
floor()
doesn't havedecimals
argument.
import torch
my_tensor = torch.tensor([4.7352, -2.3706, 9.1648, -7.7054])
torch.floor(my_tensor)
my_tensor.floor()
# tensor([4., -3., 9., -8.])
my_tensor = torch.tensor([4, -2, 9, -7])
torch.floor(my_tensor)
my_tensor.floor()
# tensor([4, -2, 9, -7])
trunc() can truncate the decimal part of zero or more elements of a 0D or more D tensor as shown below:
*Memos:
-
trunc()
can be called both fromtorch
and a tensor. - Only zero or more floating-point numbers or integers can be used so zero or more complex numbers or boolean values cannot be used.
-
trunc()
doesn't havedecimals
argument.
import torch
my_tensor = torch.tensor([4.7352, -2.3706, 9.1648, -7.7054])
torch.trunc(my_tensor)
my_tensor.trunc()
# tensor([4., -2., 9., -7.])
my_tensor = torch.tensor([4, -2, 9, -7])
torch.trunc(my_tensor)
my_tensor.trunc()
# tensor([4, -2, 9, -7])
frac() can get the decimal part of zero or more elements of a 0D or more D tensor as shown below:
*Memos:
-
frac()
can be called both fromtorch
and a tensor. - Only zero or more floating-point numbers can be used so zero or more integers, complex numbers or boolean values cannot be used.
-
frac()
doesn't havedecimals
argument.
import torch
my_tensor = torch.tensor([4.7352, -2.3706, 9.1648, -7.7054])
torch.frac(my_tensor)
my_tensor.frac()
# tensor([0.7352, -0.3706, 0.1648, -0.7054])
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