/
_base.py
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/
_base.py
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# Copyright 2021 The JAX Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Base JAX Sparse object."""
import abc
from typing import Sequence, Tuple
from jax import core
import jax.numpy as jnp
from jax._src import util
from jax._src.typing import Array
class JAXSparse(abc.ABC):
"""Base class for high-level JAX sparse objects."""
data: jnp.ndarray
shape: Tuple[int, ...]
nse: property
dtype: property
# Ignore type because of https://github.com/python/mypy/issues/4266.
__hash__ = None # type: ignore
@property
def size(self) -> int:
return util.prod(self.shape)
@property
def ndim(self) -> int:
return len(self.shape)
def __init__(self, args: Tuple[Array, ...], *, shape: Sequence[int]):
self.shape = tuple(shape)
def __repr__(self):
name = self.__class__.__name__
try:
nse = self.nse
dtype = self.dtype
shape = list(self.shape)
except:
repr_ = f"{name}(<invalid>)"
else:
repr_ = f"{name}({dtype}{shape}, {nse=})"
if isinstance(self.data, core.Tracer):
repr_ = f"{type(self.data).__name__}[{repr_}]"
return repr_
@abc.abstractmethod
def tree_flatten(self):
...
@classmethod
@abc.abstractmethod
def tree_unflatten(cls, aux_data, children):
...
@abc.abstractmethod
def transpose(self, axes=None):
...
@property
def T(self):
return self.transpose()
def block_until_ready(self):
for arg in self.tree_flatten()[0]:
arg.block_until_ready()
return self
# Not abstract methods because not all sparse classes implement them
def sum(self, *args, **kwargs):
raise NotImplementedError(f"{self.__class__}.sum")
def __neg__(self):
raise NotImplementedError(f"{self.__class__}.__neg__")
def __pos__(self):
raise NotImplementedError(f"{self.__class__}.__pos__")
def __matmul__(self, other):
raise NotImplementedError(f"{self.__class__}.__matmul__")
def __rmatmul__(self, other):
raise NotImplementedError(f"{self.__class__}.__rmatmul__")
def __mul__(self, other):
raise NotImplementedError(f"{self.__class__}.__mul__")
def __rmul__(self, other):
raise NotImplementedError(f"{self.__class__}.__rmul__")
def __add__(self, other):
raise NotImplementedError(f"{self.__class__}.__add__")
def __radd__(self, other):
raise NotImplementedError(f"{self.__class__}.__radd__")
def __sub__(self, other):
raise NotImplementedError(f"{self.__class__}.__sub__")
def __rsub__(self, other):
raise NotImplementedError(f"{self.__class__}.__rsub__")
def __getitem__(self, item):
raise NotImplementedError(f"{self.__class__}.__getitem__")