split() in PyTorch
Tags: pytorch, split, tensor, function
Published: 2024-05-23 11:22:52

*Memos:
- [My post](https://dev.to/hyperkai/vsplit-in-pytorch-4915) explains [vsplit()](https://pytorch.org/docs/stable/generated/torch.vsplit.html).
- [My post](https://dev.to/hyperkai/hsplit-in-pytorch-4b1d) explains [hsplit()](https://pytorch.org/docs/stable/generated/torch.hsplit.html).
- [My post](https://dev.to/hyperkai/dsplit-in-pytorch-594c) explains [dsplit()](https://pytorch.org/docs/stable/generated/torch.dsplit.html).
- [My post](https://dev.to/hyperkai/tensorsplit-in-pytorch-30m5) explains [tensor_split()](https://pytorch.org/docs/stable/generated/torch.tensor_split.html).
- [My post](https://dev.to/hyperkai/chunk-in-pytorch-30f5) explains [chunk()](https://pytorch.org/docs/stable/generated/torch.chunk.html).
- [My post](https://dev.to/hyperkai/unbind-in-pytorch-3lk9) explains [unbind()](https://pytorch.org/docs/stable/generated/torch.unbind.html).

[split()](https://pytorch.org/docs/stable/generated/torch.split.html) can get the one or more 1D or more D tensors of zero or more splitted elements from the 1D or more D tensor of zero or more elements as shown below:

*Memos:
- `split()` can be used with [torch](https://pytorch.org/docs/stable/torch.html) and a tensor.
- The 1st argument with `torch` or using a tensor is `tensor`(Required-Type:`tensor` of `int`, `float`, `complex` or `bool`).
- The 2nd argument with `torch` or the 1st argument with a tensor is `split_size_or_sections`(Required-Type:`int`, `tuple` of `int` or `list` of `int`). *Don't use `split_size_or_sections=` with a tensor.
- The 3rd argument with `torch` or the 2nd argument with a tensor is `dim`(Optional-Default:`0`-Type:`int`).
- The total number of the zero or more elements of one or more returned tensors changes.
- One or more returned tensors keep the dimension of `tensor`.

```python
import torch

my_tensor = torch.tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]])

torch.split(tensor=my_tensor, split_size_or_sections=1)
my_tensor.split(1)
torch.split(tensor=my_tensor, split_size_or_sections=1, dim=0)
torch.split(tensor=my_tensor, split_size_or_sections=1, dim=-2)
# (tensor([[0, 1, 2, 3]]),
#  tensor([[4, 5, 6, 7]]),
#  tensor([[8, 9, 10, 11]]))

torch.split(tensor=my_tensor, split_size_or_sections=1, dim=1)
torch.split(tensor=my_tensor, split_size_or_sections=1, dim=-1)
# (tensor([[0], [4], [8]]),
#  tensor([[1], [5], [9]]),
#  tensor([[2], [6], [10]]),
#  tensor([[3], [7], [11]]))

torch.split(tensor=my_tensor, split_size_or_sections=2)
torch.split(tensor=my_tensor, split_size_or_sections=2, dim=0)
torch.split(tensor=my_tensor, split_size_or_sections=2, dim=-2)
# (tensor([[0, 1, 2, 3], [4, 5, 6, 7]]),
#  tensor([[8, 9, 10, 11]]))

torch.split(tensor=my_tensor, split_size_or_sections=2, dim=1)
torch.split(tensor=my_tensor, split_size_or_sections=2, dim=-1)
# (tensor([[0, 1], [4, 5], [8, 9]]),
#  tensor([[2, 3], [6, 7], [10, 11]]))

torch.split(tensor=my_tensor, split_size_or_sections=3)
torch.split(tensor=my_tensor, split_size_or_sections=3, dim=0)
torch.split(tensor=my_tensor, split_size_or_sections=3, dim=-2)
# (tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]),)

torch.split(tensor=my_tensor, split_size_or_sections=3, dim=1)
torch.split(tensor=my_tensor, split_size_or_sections=3, dim=-1)
# (tensor([[0, 1, 2], [4, 5, 6], [8, 9, 10]]),
#  tensor([[3], [7], [11]]))

torch.split(tensor=my_tensor, split_size_or_sections=(0, 3))
torch.split(tensor=my_tensor, split_size_or_sections=(0, 3), dim=0)
torch.split(tensor=my_tensor, split_size_or_sections=(0, 3), dim=-2)
# (tensor([], size=(0, 4), dtype=torch.int64),
#  tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]))

torch.split(tensor=my_tensor, split_size_or_sections=(1, 2))
torch.split(tensor=my_tensor, split_size_or_sections=(1, 2), dim=0)
torch.split(tensor=my_tensor, split_size_or_sections=(1, 2), dim=-2)
# (tensor([[0, 1, 2, 3]]),
#  tensor([[4, 5, 6, 7], [8, 9, 10, 11]]))

torch.split(tensor=my_tensor, split_size_or_sections=(2, 1))
torch.split(tensor=my_tensor, split_size_or_sections=(2, 1), dim=0)
torch.split(tensor=my_tensor, split_size_or_sections=(2, 1), dim=-2)
# (tensor([[0, 1, 2, 3], [4, 5, 6, 7]]),
#  tensor([[8, 9, 10, 11]]))

torch.split(tensor=my_tensor, split_size_or_sections=(3, 0))
torch.split(tensor=my_tensor, split_size_or_sections=(3, 0), dim=0)
# (tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]),
#  tensor([], size=(0, 4), dtype=torch.int64))

torch.split(tensor=my_tensor, split_size_or_sections=(1, 1, 1))
torch.split(tensor=my_tensor, split_size_or_sections=(1, 1, 1), dim=0)
torch.split(tensor=my_tensor, split_size_or_sections=(1, 1, 1), dim=-2)
# (tensor([[0, 1, 2, 3]]),
#  tensor([[4, 5, 6, 7]]), 
#  tensor([[ 8,  9, 10, 11]]))

my_tensor = torch.tensor([[0., 1., 2., 3.],
                          [4., 5., 6., 7.],
                          [8., 9., 10., 11.]])
torch.split(tensor=my_tensor, split_size_or_sections=1)
# (tensor([[0., 1., 2., 3.]]),
#  tensor([[4., 5., 6., 7.]]),
#  tensor([[8., 9., 10., 11.]]))

my_tensor = torch.tensor([[0.+0.j, 1.+0.j, 2.+0.j, 3.+0.j],
                          [4.+0.j, 5.+0.j, 6.+0.j, 7.+0.j],
                          [8.+0.j, 9.+0.j, 10.+0.j, 11.+0.j]])
torch.split(tensor=my_tensor, split_size_or_sections=1)
# (tensor([[0.+0.j, 1.+0.j, 2.+0.j, 3.+0.j]]),
#  tensor([[4.+0.j, 5.+0.j, 6.+0.j, 7.+0.j]]),
#  tensor([[8.+0.j, 9.+0.j, 10.+0.j, 11.+0.j]]))

my_tensor = torch.tensor([[True, False, True, False],
                          [False, True, False, True],
                          [True, False, True, False]])
torch.split(tensor=my_tensor, split_size_or_sections=1)
# (tensor([[True, False, True, False]]),
#  tensor([[False, True, False, True]]),
#  tensor([[True, False, True, False]]))
```