def __init__(
self,
name,
dtype=None,
shape=(),
is_local=auto,
dim_tags=None,
offset=0,
strides=None,
order=None,
base_indices=None,
storage_shape=None,
):
"""
:arg dtype: :class:`loopy.auto` or a :class:`numpy.dtype`
:arg shape: :class:`loopy.auto` or a shape tuple
:arg base_indices: :class:`loopy.auto` or a tuple of base indices
"""
if is_local is None:
raise ValueError("is_local is None is no longer supported. " "Use loopy.auto.")
if base_indices is None:
base_indices = (0,) * len(shape)
ArrayBase.__init__(
self,
name=name,
dtype=dtype,
shape=shape,
dim_tags=dim_tags,
order="C",
base_indices=base_indices,
is_local=is_local,
storage_shape=storage_shape,
)
def __init__(self, name, dtype=None, shape=(), address_space=None,
dim_tags=None, offset=0, dim_names=None, strides=None, order=None,
base_indices=None, storage_shape=None,
base_storage=None, initializer=None, read_only=False,
_base_storage_access_may_be_aliasing=False, **kwargs):
"""
:arg dtype: :class:`loopy.auto` or a :class:`numpy.dtype`
:arg shape: :class:`loopy.auto` or a shape tuple
:arg base_indices: :class:`loopy.auto` or a tuple of base indices
"""
scope = kwargs.pop("scope", None)
if scope is not None:
warn("Passing 'scope' is deprecated. Use 'address_space' instead.",
DeprecationWarning, stacklevel=2)
if address_space is not None:
raise ValueError("only one of 'scope' and 'address_space' "
"may be specified")
else:
address_space = scope
del scope
if address_space is None:
address_space = auto
if address_space is None:
raise LoopyError(
"temporary variable '%s': "
"address_space must not be None"
% name)
if initializer is None:
pass
elif isinstance(initializer, np.ndarray):
if offset != 0:
raise LoopyError(
"temporary variable '%s': "
"offset must be 0 if initializer specified"
% name)
from loopy.types import NumpyType, to_loopy_type
if dtype is auto or dtype is None:
dtype = NumpyType(initializer.dtype)
elif to_loopy_type(dtype) != to_loopy_type(initializer.dtype):
raise LoopyError(
"temporary variable '%s': "
"dtype of initializer does not match "
"dtype of array."
% name)
if shape is auto:
shape = initializer.shape
else:
raise LoopyError(
"temporary variable '%s': "
"initializer must be None or a numpy array"
% name)
if order is None:
order = "C"
if base_indices is None:
base_indices = (0,) * len(shape)
if not read_only and initializer is not None:
raise LoopyError(
"temporary variable '%s': "
"read-write variables with initializer "
"are not currently supported "
"(did you mean to set read_only=True?)"
% name)
if base_storage is not None and initializer is not None:
raise LoopyError(
"temporary variable '%s': "
"base_storage and initializer are "
"mutually exclusive"
% name)
if base_storage is None and _base_storage_access_may_be_aliasing:
raise LoopyError(
"temporary variable '%s': "
"_base_storage_access_may_be_aliasing option, but no "
"base_storage given!"
% name)
ArrayBase.__init__(self, name=intern(name),
dtype=dtype, shape=shape, strides=strides,
dim_tags=dim_tags, offset=offset, dim_names=dim_names,
order=order,
base_indices=base_indices,
address_space=address_space,
storage_shape=storage_shape,
base_storage=base_storage,
initializer=initializer,
read_only=read_only,
_base_storage_access_may_be_aliasing=(
_base_storage_access_may_be_aliasing),
**kwargs)
def __init__(self, name, dtype=None, shape=(), address_space=None,
dim_tags=None, offset=0, dim_names=None, strides=None, order=None,
base_indices=None, storage_shape=None,
base_storage=None, initializer=None, read_only=False,
_base_storage_access_may_be_aliasing=False, **kwargs):
"""
:arg dtype: :class:`loopy.auto` or a :class:`numpy.dtype`
:arg shape: :class:`loopy.auto` or a shape tuple
:arg base_indices: :class:`loopy.auto` or a tuple of base indices
"""
scope = kwargs.pop("scope", None)
if scope is not None:
warn("Passing 'scope' is deprecated. Use 'address_space' instead.",
DeprecationWarning, stacklevel=2)
if address_space is not None:
raise ValueError("only one of 'scope' and 'address_space' "
"may be specified")
else:
address_space = scope
del scope
if address_space is None:
address_space = auto
if address_space is None:
raise LoopyError(
"temporary variable '%s': "
"address_space must not be None"
% name)
if initializer is None:
pass
elif isinstance(initializer, np.ndarray):
if offset != 0:
raise LoopyError(
"temporary variable '%s': "
"offset must be 0 if initializer specified"
% name)
from loopy.types import NumpyType, to_loopy_type
if dtype is auto or dtype is None:
dtype = NumpyType(initializer.dtype)
elif to_loopy_type(dtype) != to_loopy_type(initializer.dtype):
raise LoopyError(
"temporary variable '%s': "
"dtype of initializer does not match "
"dtype of array."
% name)
if shape is auto:
shape = initializer.shape
else:
raise LoopyError(
"temporary variable '%s': "
"initializer must be None or a numpy array"
% name)
if order is None:
order = "C"
if base_indices is None:
base_indices = (0,) * len(shape)
if not read_only and initializer is not None:
raise LoopyError(
"temporary variable '%s': "
"read-write variables with initializer "
"are not currently supported "
"(did you mean to set read_only=True?)"
% name)
if base_storage is not None and initializer is not None:
raise LoopyError(
"temporary variable '%s': "
"base_storage and initializer are "
"mutually exclusive"
% name)
if base_storage is None and _base_storage_access_may_be_aliasing:
raise LoopyError(
"temporary variable '%s': "
"_base_storage_access_may_be_aliasing option, but no "
"base_storage given!"
% name)
ArrayBase.__init__(self, name=intern(name),
dtype=dtype, shape=shape, strides=strides,
dim_tags=dim_tags, offset=offset, dim_names=dim_names,
order=order,
base_indices=base_indices,
address_space=address_space,
storage_shape=storage_shape,
base_storage=base_storage,
initializer=initializer,
read_only=read_only,
_base_storage_access_may_be_aliasing=(
_base_storage_access_may_be_aliasing),
**kwargs)
def __init__(self,
name,
dtype=None,
shape=(),
scope=auto,
dim_tags=None,
offset=0,
dim_names=None,
strides=None,
order=None,
base_indices=None,
storage_shape=None,
base_storage=None,
initializer=None,
read_only=False,
**kwargs):
"""
:arg dtype: :class:`loopy.auto` or a :class:`numpy.dtype`
:arg shape: :class:`loopy.auto` or a shape tuple
:arg base_indices: :class:`loopy.auto` or a tuple of base indices
"""
if initializer is None:
pass
elif isinstance(initializer, np.ndarray):
if offset != 0:
raise LoopyError("temporary variable '%s': "
"offset must be 0 if initializer specified" %
name)
from loopy.types import NumpyType, to_loopy_type
if dtype is auto or dtype is None:
dtype = NumpyType(initializer.dtype)
elif to_loopy_type(dtype) != to_loopy_type(initializer.dtype):
raise LoopyError("temporary variable '%s': "
"dtype of initializer does not match "
"dtype of array." % name)
if shape is auto:
shape = initializer.shape
else:
raise LoopyError("temporary variable '%s': "
"initializer must be None or a numpy array" %
name)
if order is None:
order = "C"
if base_indices is None:
base_indices = (0, ) * len(shape)
if not read_only and initializer is not None:
raise LoopyError("temporary variable '%s': "
"read-write variables with initializer "
"are not currently supported "
"(did you mean to set read_only=True?)" % name)
if base_storage is not None and initializer is not None:
raise LoopyError("temporary variable '%s': "
"base_storage and initializer are "
"mutually exclusive" % name)
ArrayBase.__init__(self,
name=intern(name),
dtype=dtype,
shape=shape,
dim_tags=dim_tags,
offset=offset,
dim_names=dim_names,
order=order,
base_indices=base_indices,
scope=scope,
storage_shape=storage_shape,
base_storage=base_storage,
initializer=initializer,
read_only=read_only,
**kwargs)