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

#pytorch #typeconversion #type #to

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*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')

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

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