[pytorch] difference between torch.Tensor and torch.LongTensor

A [torch.Tensor] is a multiple dimensional matrix containing elements of a single data type.

[torch.Tensor] is same as [torch.FloatTensor].

look at this table.

Data type	dtype	CPU tensor	GPU tensor
32-bit floating point	torch.float32 or torch.float	torch.FloatTensor	torch.cuda.FloatTensor
64-bit floating point	torch.float64 or torch.double	torch.DoubleTensor	torch.cuda.DoubleTensor
16-bit floating point	torch.float16 or torch.half	torch.HalfTensor	torch.cuda.HalfTensor
8-bit integer (unsigned)	torch.uint8	torch.ByteTensor	torch.cuda.ByteTensor
8-bit integer (signed)	torch.int8	torch.CharTensor	torch.cuda.CharTensor
16-bit integer (signed)	torch.int16 or torch.short	torch.ShortTensor	torch.cuda.ShortTensor
32-bit integer (signed)	torch.int32 or torch.int	torch.IntTensor	torch.cuda.IntTensor
64-bit integer (signed)	torch.int64 or torch.long	torch.LongTensor	torch.cuda.LongTensor

- <pytorch.org/docs/stable/tensors.html>

So, when we define a value as [torch.Tensor], it's a float type value.

[torch.LongTensor] is an int64 data type value.

[torch.Tensor] is a float32 data type value.