Type conversion with type(), to() and a tensor in PyTorch

Buy Me a Coffee☕

*My post explains how to create and acceess a tensor.

type(), to() or a tensor can do type conversion as shown below:

*Memos:

• type() or to() can be used with a tensor but not with torch.
• The 1st argument with a tensor is dtype(Required-Type:dtype): *Memos:
  • type() can also accept legacy constructors(str) such as 'torch.LongTensor', 'torch.FloatTensor', 'torch.ComplexFloatTensor' and 'torch.BoolTensor'.
  • to() can also accept int(), float() and bool() but not complex() which python built-in functions.
• You can check long(), float(), cfloat() and bool() in PyTorch.
• tensor.dtype can get dtype.
• tensor.type() can get the legacy constructor which is an old dtype.

int to float, complex and bool:

import torch

tensor1 = torch.tensor([7, 0, 4])

tensor1, tensor1.dtype, tensor1.dtype
# (tensor([7, 0, 4]), torch.int64, torch.int64)

tensor2 = tensor1.type(dtype=torch.float32)
tensor2 = tensor1.type(dtype=torch.float)
tensor2 = tensor1.type(dtype='torch.FloatTensor')
tensor2 = tensor1.to(dtype=torch.float32)
tensor2 = tensor1.to(dtype=torch.float)
tensor2 = tensor1.float()

tensor2, tensor2.dtype, tensor2.type()
# (tensor([7., 0., 4.]), torch.float32, 'torch.FloatTensor')

tensor2 = tensor1.to(dtype=float)

tensor2, tensor2.dtype, tensor2.type()
# (tensor([7., 0., 4.], dtype=torch.float64),
#  torch.float64,
#  'torch.DoubleTensor')

tensor2 = tensor1.type(dtype=torch.complex64)
tensor2 = tensor1.type(dtype=torch.cfloat)
tensor2 = tensor1.type(dtype='torch.ComplexFloatTensor')
tensor2 = tensor1.to(dtype=torch.complex64)
tensor2 = tensor1.to(dtype=torch.cfloat)
tensor2 = tensor1.cfloat()

tensor2, tensor2.dtype, tensor2.type()
# (tensor([7.+0.j, 0.+0.j, 4.+0.j]),
#  torch.complex64,
#  'torch.ComplexFloatTensor')

tensor2 = tensor1.type(dtype=torch.bool)
tensor2 = tensor1.type(dtype='torch.BoolTensor')
tensor2 = tensor1.to(dtype=torch.bool)
tensor2 = tensor1.to(dtype=bool)
tensor2 = tensor1.bool()

tensor2, tensor2.dtype, tensor2.type()
# (tensor([True, False, True]), torch.bool, 'torch.BoolTensor')

float to int, complex and bool:

import torch

tensor1 = torch.tensor([7., 0., 4.])

tensor1, tensor1.dtype, tensor1.dtype
# (tensor([7., 0., 4.]), torch.float32, torch.float32)

tensor2 = tensor1.type(dtype=torch.int64)
tensor2 = tensor1.type(dtype=torch.long)
tensor2 = tensor1.type(dtype='torch.LongTensor')
tensor2 = tensor1.to(dtype=torch.int64)
tensor2 = tensor1.to(dtype=torch.long)
tensor2 = tensor1.to(dtype=int)
tensor2 = tensor1.long()

tensor2, tensor2.dtype, tensor2.type()
# (tensor([7, 0, 4]), torch.int64, 'torch.LongTensor')

tensor2 = tensor1.type(dtype=torch.complex64)
tensor2 = tensor1.type(dtype=torch.cfloat)
tensor2 = tensor1.type(dtype='torch.ComplexFloatTensor')
tensor2 = tensor1.to(dtype=torch.complex64)
tensor2 = tensor1.to(dtype=torch.cfloat)
tensor2 = tensor1.cfloat()

tensor2, tensor2.dtype, tensor2.type()
# (tensor([7.+0.j, 0.+0.j, 4.+0.j]),
#  torch.complex64,
#  'torch.ComplexFloatTensor')

tensor2 = tensor1.type(dtype=torch.bool)
tensor2 = tensor1.type(dtype='torch.BoolTensor')
tensor2 = tensor1.to(dtype=torch.bool)
tensor2 = tensor1.to(dtype=bool)
tensor2 = tensor1.bool()

tensor2, tensor2.dtype, tensor2.type()
# (tensor([True, False, True]), torch.bool, 'torch.BoolTensor')

complex to int, float and bool:

import torch

tensor1= torch.tensor([7.+0.j, 0.+0.j, 4.+0.j])

tensor1, tensor1.dtype, tensor1.dtype
# (tensor([7.+0.j, 0.+0.j, 4.+0.j]), torch.complex64, torch.complex64)

tensor2 = tensor1.type(dtype=torch.int64)
tensor2 = tensor1.type(dtype=torch.long)
tensor2 = tensor1.type(dtype='torch.LongTensor')
tensor2 = tensor1.to(dtype=torch.int64)
tensor2 = tensor1.to(dtype=torch.long)
tensor2 = tensor1.to(dtype=int)
tensor2 = tensor1.long()

tensor2, tensor2.dtype, tensor2.type()
# (tensor([7, 0, 4]), torch.int64, 'torch.LongTensor')

tensor2 = tensor1.type(dtype=torch.float32)
tensor2 = tensor1.type(dtype=torch.float)
tensor2 = tensor1.type(dtype='torch.FloatTensor')
tensor2 = tensor1.to(dtype=torch.float32)
tensor2 = tensor1.to(dtype=torch.float)
tensor2 = tensor1.float()

tensor2, tensor2.dtype, tensor2.type()
# (tensor([7., 0., 4.]), torch.float32, 'torch.FloatTensor')

tensor2 = tensor1.to(dtype=float)

tensor2, tensor2.dtype, tensor2.type()
# (tensor([7., 0., 4.], dtype=torch.float64),
#  torch.float64,
#  'torch.DoubleTensor')

tensor2 = tensor1.type(dtype=torch.bool)
tensor2 = tensor1.type(dtype='torch.BoolTensor')
tensor2 = tensor1.to(dtype=torch.bool)
tensor2 = tensor1.to(dtype=bool)
tensor2 = tensor1.bool()

tensor2, tensor2.dtype, tensor2.type()
# (tensor([True, False, True]), torch.bool, 'torch.BoolTensor')

bool to int, float and complex:

import torch

tensor1 = torch.tensor([True, False, True])

tensor1, tensor1.dtype, tensor1.dtype
# (tensor([True, False, True]), torch.bool, torch.bool)

tensor2 = tensor1.type(dtype=torch.int64)
tensor2 = tensor1.type(dtype=torch.long)
tensor2 = tensor1.type(dtype='torch.LongTensor')
tensor2 = tensor1.to(dtype=torch.int64)
tensor2 = tensor1.to(dtype=torch.long)
tensor2 = tensor1.to(dtype=int)
tensor2 = tensor1.long()

tensor2, tensor2.dtype, tensor2.type()
# (tensor([1, 0, 1]), torch.int64, 'torch.LongTensor')

tensor2 = tensor1.type(dtype=torch.float32)
tensor2 = tensor1.type(dtype=torch.float)
tensor2 = tensor1.type(dtype='torch.FloatTensor')
tensor2 = tensor1.to(dtype=torch.float32)
tensor2 = tensor1.to(dtype=torch.float)
tensor2 = tensor1.float()

tensor2, tensor2.dtype, tensor2.type()
# (tensor([1., 0., 1.]), torch.float32, 'torch.FloatTensor')

tensor2 = tensor1.to(dtype=float)

tensor2, tensor2.dtype, tensor2.type()
# (tensor([1., 0., 1.], dtype=torch.float64),
#  torch.float64,
#  'torch.DoubleTensor')

tensor2 = tensor1.type(dtype=torch.complex64)
tensor2 = tensor1.type(dtype=torch.cfloat)
tensor2 = tensor1.type(dtype='torch.ComplexFloatTensor')
tensor2 = tensor1.to(dtype=torch.complex64)
tensor2 = tensor1.to(dtype=torch.cfloat)
tensor2 = tensor1.cfloat()

tensor2, tensor2.dtype, tensor2.type()
# (tensor([1.+0.j, 0.+0.j, 1.+0.j]),
#  torch.complex64,
#  'torch.ComplexFloatTensor')