qml.data.DatasetSparseArray¶
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class
DatasetSparseArray
(value=<UnsetType.UNSET: 'UNSET'>, info=None, *, bind=None, parent_and_key=None)[source]¶ Bases:
Generic
[pennylane.data.attributes.sparse_array.SparseT
],pennylane.data.base.attribute.DatasetAttribute
[collections.abc.MutableMapping
,pennylane.data.attributes.sparse_array.SparseT
,pennylane.data.attributes.sparse_array.SparseT
]Attribute type for Scipy sparse arrays. Can accept values of any type in
scipy.sparse
. Arrays are serialized using the CSR format.Attributes
Returns the HDF5 object that contains this attribute’s data.
Returns the
AttributeInfo
for this attribute.Maps type_ids to their DatasetAttribute classes.
Returns the class of sparse array that will be returned by the
get_value()
method.Maps types to their default DatasetAttribute
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bind
¶ Returns the HDF5 object that contains this attribute’s data.
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info
¶ Returns the
AttributeInfo
for this attribute.
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registry
: Mapping[str, Type[DatasetAttribute]] = mappingproxy({'dataset': <class 'pennylane.data.base.dataset._DatasetAttributeType'>, 'array': <class 'pennylane.data.attributes.array.DatasetArray'>, 'dict': <class 'pennylane.data.attributes.dictionary.DatasetDict'>, 'json': <class 'pennylane.data.attributes.json.DatasetJSON'>, 'list': <class 'pennylane.data.attributes.list.DatasetList'>, 'molecule': <class 'pennylane.data.attributes.molecule.DatasetMolecule'>, 'none': <class 'pennylane.data.attributes.none.DatasetNone'>, 'operator': <class 'pennylane.data.attributes.operator.operator.DatasetOperator'>, 'scalar': <class 'pennylane.data.attributes.scalar.DatasetScalar'>, 'sparse_array': <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, 'string': <class 'pennylane.data.attributes.string.DatasetString'>, 'tuple': <class 'pennylane.data.attributes.tuple.DatasetTuple'>, 'pytree': <class 'pennylane.data.attributes.pytree.DatasetPyTree'>})¶ Maps type_ids to their DatasetAttribute classes.
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sparse_array_class
¶ Returns the class of sparse array that will be returned by the
get_value()
method.
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type_consumer_registry
: Mapping[type, Type[DatasetAttribute]] = mappingproxy({<class 'pennylane.qchem.molecule.Molecule'>: <class 'pennylane.data.attributes.molecule.DatasetMolecule'>, <class 'NoneType'>: <class 'pennylane.data.attributes.none.DatasetNone'>, <class 'scipy.sparse._bsr.bsr_array'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._coo.coo_array'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._csc.csc_array'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._csr.csr_array'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._dia.dia_array'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._dok.dok_array'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._lil.lil_array'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._csc.csc_matrix'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._csr.csr_matrix'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._bsr.bsr_matrix'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._coo.coo_matrix'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._dia.dia_matrix'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._dok.dok_matrix'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._lil.lil_matrix'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'str'>: <class 'pennylane.data.attributes.string.DatasetString'>, <class 'tuple'>: <class 'pennylane.data.attributes.tuple.DatasetTuple'>})¶ Maps types to their default DatasetAttribute
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type_id
: ClassVar[str] = 'sparse_array'¶
Methods
Returns an iterable of types for which this should be the default codec.
Deserializes the mapped value from
bind
, and also perform a ‘deep-copy’ of any nested values contained inbind
.Returns a valid default value for this type, or
UNSET
if this type must be initialized with a value.Deserializes the mapped value from
bind
.hdf5_to_value
(bind)Parses bind into Python object.
py_type
(value_type)The module path of sparse array types is private, e.g
scipy.sparse._csr.csr_array
.value_to_hdf5
(bind_parent, key, value)Converts value into a HDF5 Array or Group under bind_parent[key].
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classmethod
consumes_types
()[source]¶ Returns an iterable of types for which this should be the default codec. If a value of one of these types is assigned to a Dataset without specifying a type_id, this type will be used.
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copy_value
()¶ Deserializes the mapped value from
bind
, and also perform a ‘deep-copy’ of any nested values contained inbind
.
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classmethod
default_value
()¶ Returns a valid default value for this type, or
UNSET
if this type must be initialized with a value.
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get_value
()¶ Deserializes the mapped value from
bind
.
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