Easily manipulate torch.Tensors inside highly nested data-structures.
Project description
torch-nested
Easily manipulate torch.Tensors inside highly nested data-structures.
You may want to consider using torch.nested,
but if you are working with nested dicts, lists, tuples, etc. of torch.Tensors,
here is the package for you.
A proper documentation is coming. Until then, a basic example is shown below, and you can look at the docstrings or tests of this package for more information.
Basic usage
Given a nested structure that contains torch.Tensor, this package makes it easy to access these Tensors and
work with them:
import torch
from torch_nested import NestedTensors
INPUT_DATA = [
(
torch.ones(3),
torch.zeros(2)
),
torch.ones((2, 2, 2)),
{
"foo": torch.ones(2),
"bar": [],
"har": "rar"
},
1
]
tensors = NestedTensors(INPUT_DATA)
# Original data preserved in .data-member
assert tensors.data == INPUT_DATA
# Simple accessing and setting
for i, tensor in enumerate(tensors):
tensors[i] = tensor + i
# Has basic dunders
assert len(tensors) == 4
assert torch.all(next(tensors) == torch.ones(3))
Calling print(tensors.shape()) would yield:
torch_nested.Size(
[
(
torch.Size([3]),
torch.Size([2])
),
torch.Size([2, 2, 2]),
{
foo: torch.Size([2]),
bar: None,
har: None
},
None
]
)
Supported data-structures
The following data-structures are supported so far:
torch.TensordictlisttupleNone- Any class with a
.tensors-attribute - Any class with a
.data-attribute, even if it isn't atorch.Tensor
For example
class ObjWithTensors:
tensors = [torch.ones(2), torch.zeros(2)]
class ObjWithData:
data = [torch.ones(2), torch.zeros(2)]
tensors = NestedTensors([ObjWithTensors(), ObjWithData()])
Running print(tensors.size()) would result in the following output:
NestedSize(
[
ObjWithTensors(
tensors: [
torch.Size([2]),
torch.Size([2])
]
),
ObjWithData(
data: [
torch.Size([2]),
torch.Size([2])
]
)
]
)
More data-structures will be supported in the future. Any data that is of an unsupported type
will not have its Tensors readable or writable, and NestedShape will show None there.
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