import torch
from .base import doc_from_base, func_treelize
__all__ = [
'dot', 'matmul', 'mm',
]
# noinspection PyShadowingBuiltins
[docs]@doc_from_base()
@func_treelize()
def dot(input, other, *args, **kwargs):
"""
In ``treetensor``, you can get the dot product of 2 tree tensors with :func:`treetensor.torch.dot`.
Examples::
>>> import torch
>>> import treetensor.torch as ttorch
>>> ttorch.dot(torch.tensor([1, 2]), torch.tensor([2, 3]))
tensor(8)
>>> ttorch.dot(
... ttorch.tensor({
... 'a': [1, 2, 3],
... 'b': {'x': [3, 4]},
... }),
... ttorch.tensor({
... 'a': [5, 6, 7],
... 'b': {'x': [1, 2]},
... })
... )
<Tensor 0x7feac55bde50>
├── a --> tensor(38)
└── b --> <Tensor 0x7feac55c9250>
└── x --> tensor(11)
"""
return torch.dot(input, other, *args, **kwargs)
# noinspection PyShadowingBuiltins
[docs]@doc_from_base()
@func_treelize()
def matmul(input, other, *args, **kwargs):
"""
In ``treetensor``, you can create a matrix product with :func:`treetensor.torch.matmul`.
Examples::
>>> import torch
>>> import treetensor.torch as ttorch
>>> ttorch.matmul(
... torch.tensor([[1, 2], [3, 4]]),
... torch.tensor([[5, 6], [7, 2]]),
... )
tensor([[19, 10],
[43, 26]])
>>> ttorch.matmul(
... ttorch.tensor({
... 'a': [[1, 2], [3, 4]],
... 'b': {'x': [3, 4, 5, 6]},
... }),
... ttorch.tensor({
... 'a': [[5, 6], [7, 2]],
... 'b': {'x': [4, 3, 2, 1]},
... }),
... )
<Tensor 0x7f2e74883f40>
├── a --> tensor([[19, 10],
│ [43, 26]])
└── b --> <Tensor 0x7f2e74886430>
└── x --> tensor(40)
"""
return torch.matmul(input, other, *args, **kwargs)
# noinspection PyShadowingBuiltins
[docs]@doc_from_base()
@func_treelize()
def mm(input, mat2, *args, **kwargs):
"""
In ``treetensor``, you can create a matrix multiplication with :func:`treetensor.torch.mm`.
Examples::
>>> import torch
>>> import treetensor.torch as ttorch
>>> ttorch.mm(
... torch.tensor([[1, 2], [3, 4]]),
... torch.tensor([[5, 6], [7, 2]]),
... )
tensor([[19, 10],
[43, 26]])
>>> ttorch.mm(
... ttorch.tensor({
... 'a': [[1, 2], [3, 4]],
... 'b': {'x': [[3, 4, 5], [6, 7, 8]]},
... }),
... ttorch.tensor({
... 'a': [[5, 6], [7, 2]],
... 'b': {'x': [[6, 5], [4, 3], [2, 1]]},
... }),
... )
<Tensor 0x7f2e7489f340>
├── a --> tensor([[19, 10],
│ [43, 26]])
└── b --> <Tensor 0x7f2e74896e50>
└── x --> tensor([[44, 32],
[80, 59]])
"""
return torch.mm(input, mat2, *args, **kwargs)