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merged 7 commits into from
Jul 30, 2025
Merged

Add the basic parity tensor class and its arithmetic operators. #2

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6bf1100
Add the basic parity tensor class and its arithmetic operators.
hzhangxyz Jul 30, 2025
40ba62a
Update parity_tensor/parity_tensor.py
hzhangxyz Jul 30, 2025
4ee3380
Update parity_tensor/parity_tensor.py
hzhangxyz Jul 30, 2025
93e2bb8
Update parity_tensor/parity_tensor.py
hzhangxyz Jul 30, 2025
bee4047
Add annotation for return type of functions.
hzhangxyz Jul 30, 2025
6453b41
Merge branch 'main' into dev/add-simple-arithmetic-operators
hzhangxyz Jul 30, 2025
ae6aaf9
Add typing for arithmetic operator rhs.
hzhangxyz Jul 30, 2025
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3 changes: 2 additions & 1 deletion parity_tensor/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@
A parity tensor package.
"""

__all__ = ["__version__"]
__all__ = ["__version__", "ParityTensor"]

from .version import __version__
from .parity_tensor import ParityTensor
173 changes: 173 additions & 0 deletions parity_tensor/parity_tensor.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,173 @@
"""
A parity tensor class.
"""

from __future__ import annotations

__all__ = ["ParityTensor"]

import dataclasses
import typing
import torch


@dataclasses.dataclass
class ParityTensor:
"""
A parity tensor class, which stores a tensor along with information about its edges.
Each dimension of the tensor is composed of an even and an odd part, represented as a pair of integers.
"""

edges: tuple[tuple[int, int], ...]
tensor: torch.Tensor

def __post_init__(self) -> None:
assert len(self.edges) == self.tensor.dim(), f"Edges length ({len(self.edges)}) must match tensor dimensions ({self.tensor.dim()})."
for dim, (even, odd) in zip(self.tensor.shape, self.edges):
assert even >= 0 and odd >= 0 and dim == even + odd, f"Dimension {dim} must equal sum of even ({even}) and odd ({odd}) parts, and both must be non-negative."
Comment on lines +25 to +27
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Using assert statements for input validation in production code is not recommended as they can be disabled with the -O flag. Consider raising a ValueError instead for more robust error handling.

Suggested change
assert len(self.edges) == self.tensor.dim(), f"Edges length ({len(self.edges)}) must match tensor dimensions ({self.tensor.dim()})."
for dim, (even, odd) in zip(self.tensor.shape, self.edges):
assert even >= 0 and odd >= 0 and dim == even + odd, f"Dimension {dim} must equal sum of even ({even}) and odd ({odd}) parts, and both must be non-negative."
if len(self.edges) != self.tensor.dim():
raise ValueError(f"Edges length ({len(self.edges)}) must match tensor dimensions ({self.tensor.dim()}).")
for dim, (even, odd) in zip(self.tensor.shape, self.edges):
if even < 0 or odd < 0 or dim != even + odd:
raise ValueError(f"Dimension {dim} must equal sum of even ({even}) and odd ({odd}) parts, and both must be non-negative.")

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Comment on lines +25 to +27
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Using assert statements for input validation in production code is not recommended as they can be disabled with the -O flag. Consider raising a ValueError instead for more robust error handling.

Suggested change
assert len(self.edges) == self.tensor.dim(), f"Edges length ({len(self.edges)}) must match tensor dimensions ({self.tensor.dim()})."
for dim, (even, odd) in zip(self.tensor.shape, self.edges):
assert even >= 0 and odd >= 0 and dim == even + odd, f"Dimension {dim} must equal sum of even ({even}) and odd ({odd}) parts, and both must be non-negative."
if len(self.edges) != self.tensor.dim():
raise ValueError(f"Edges length ({len(self.edges)}) must match tensor dimensions ({self.tensor.dim()}).")
for dim, (even, odd) in zip(self.tensor.shape, self.edges):
if even < 0 or odd < 0 or dim != even + odd:
raise ValueError(f"Dimension {dim} must equal sum of even ({even}) and odd ({odd}) parts, and both must be non-negative.")

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def _validate_edge_compatibility(self, other: ParityTensor) -> None:
"""
Validate that the edges of two ParityTensor instances are compatible for arithmetic operations.
"""
assert self.edges == other.edges, f"Edges must match for arithmetic operations. Got {self.edges} and {other.edges}."
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Using assert statements for input validation in production code is not recommended as they can be disabled with the -O flag. Consider raising a ValueError instead for more robust error handling.

Suggested change
assert self.edges == other.edges, f"Edges must match for arithmetic operations. Got {self.edges} and {other.edges}."
if self.edges != other.edges:
raise ValueError(f"Edges must match for arithmetic operations. Got {self.edges} and {other.edges}.")

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def __pos__(self) -> ParityTensor:
return ParityTensor(
edges=self.edges,
tensor=+self.tensor,
)

def __neg__(self) -> ParityTensor:
return ParityTensor(
edges=self.edges,
tensor=-self.tensor,
)

def __add__(self, other: typing.Any) -> ParityTensor:
if isinstance(other, ParityTensor):
self._validate_edge_compatibility(other)
return ParityTensor(
edges=self.edges,
tensor=self.tensor + other.tensor,
)
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No input validation is performed on the 'other' parameter before attempting tensor operations. This could lead to unexpected behavior or errors if 'other' is not a valid operand for tensor arithmetic.

Suggested change
)
)
if not isinstance(other, (int, float, torch.Tensor)):
raise TypeError(f"Unsupported operand type(s) for +: 'ParityTensor' and '{type(other).__name__}'")

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result = self.tensor + other
if isinstance(result, torch.Tensor):
return ParityTensor(
edges=self.edges,
tensor=result,
)
return NotImplemented

def __radd__(self, other: typing.Any) -> ParityTensor:
result = other + self.tensor
if isinstance(result, torch.Tensor):
return ParityTensor(
edges=self.edges,
tensor=result,
)
return NotImplemented

def __iadd__(self, other: typing.Any) -> ParityTensor:
if isinstance(other, ParityTensor):
self._validate_edge_compatibility(other)
self.tensor += other.tensor
else:
self.tensor += other
return self

def __sub__(self, other: typing.Any) -> ParityTensor:
if isinstance(other, ParityTensor):
self._validate_edge_compatibility(other)
return ParityTensor(
edges=self.edges,
tensor=self.tensor - other.tensor,
)
result = self.tensor - other
if isinstance(result, torch.Tensor):
return ParityTensor(
edges=self.edges,
tensor=result,
)
return NotImplemented

def __rsub__(self, other: typing.Any) -> ParityTensor:
result = other - self.tensor
if isinstance(result, torch.Tensor):
return ParityTensor(
edges=self.edges,
tensor=result,
)
return NotImplemented

def __isub__(self, other: typing.Any) -> ParityTensor:
if isinstance(other, ParityTensor):
self._validate_edge_compatibility(other)
self.tensor -= other.tensor
else:
self.tensor -= other
return self

def __mul__(self, other: typing.Any) -> ParityTensor:
if isinstance(other, ParityTensor):
self._validate_edge_compatibility(other)
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Element-wise multiplication between ParityTensors with the same edges may not preserve the parity structure. Consider whether multiplication should validate edge compatibility or if it should have different behavior than addition/subtraction.

Suggested change
self._validate_edge_compatibility(other)
self._validate_edge_compatibility(other)
self._validate_parity_structure(other)

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return ParityTensor(
edges=self.edges,
tensor=self.tensor * other.tensor,
)
result = self.tensor * other
if isinstance(result, torch.Tensor):
return ParityTensor(
edges=self.edges,
tensor=result,
)
return NotImplemented

def __rmul__(self, other: typing.Any) -> ParityTensor:
result = other * self.tensor
if isinstance(result, torch.Tensor):
return ParityTensor(
edges=self.edges,
tensor=result,
)
return NotImplemented

def __imul__(self, other: typing.Any) -> ParityTensor:
if isinstance(other, ParityTensor):
self._validate_edge_compatibility(other)
self.tensor *= other.tensor
else:
self.tensor *= other
return self

def __truediv__(self, other: typing.Any) -> ParityTensor:
if isinstance(other, ParityTensor):
self._validate_edge_compatibility(other)
return ParityTensor(
edges=self.edges,
tensor=self.tensor / other.tensor,
)
Comment on lines +146 to +149
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Element-wise division between ParityTensors with the same edges may not preserve the parity structure. Consider whether division should validate edge compatibility or if it should have different behavior than addition/subtraction.

Suggested change
return ParityTensor(
edges=self.edges,
tensor=self.tensor / other.tensor,
)
result = ParityTensor(
edges=self.edges,
tensor=self.tensor / other.tensor,
)
result._validate_parity_preservation()
return result

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result = self.tensor / other
if isinstance(result, torch.Tensor):
return ParityTensor(
edges=self.edges,
tensor=result,
)
return NotImplemented

def __rtruediv__(self, other: typing.Any) -> ParityTensor:
result = other / self.tensor
if isinstance(result, torch.Tensor):
return ParityTensor(
edges=self.edges,
tensor=result,
)
return NotImplemented

def __itruediv__(self, other: typing.Any) -> ParityTensor:
if isinstance(other, ParityTensor):
self._validate_edge_compatibility(other)
self.tensor /= other.tensor
else:
self.tensor /= other
return self
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