TensorFlowSparseArray
Provides a SparseArray implementation that uses TensorFlow as the backend
__init__(self, data, dtype=None):
@property
shape(self):
Provides the shape of the sparse array
:returns
:tuple[int]
to_state(self, serializer=None):
Provides just the state that is needed to serialize the object
serializer
:Any
:returns
:_
from_state(state, serializer=None):
Loads from the stored state
serializer
:Any
:returns
:_
empty(shape, dtype=None, **kw):
Returns an empty SparseArray with the appropriate shape and dtype
shape
:Any
dtype
:Any
kw
:Any
:returns
:_
@property
block_data(self):
Returns the row and column indices and vector of values that the sparse array is storing
:returns
:Tuple[np.ndarray, Iterable[np.ndarray]]
transpose(self, axes):
Returns a transposed version of the tensor
axes
:Any
:returns
:_
ascoo(self):
Converts the tensor into a scipy COO matrix…
:returns
:sp.coo_matrix
ascsr(self):
Converts the tensor into a scipy COO matrix…
:returns
:sp.coo_matrix
reshape(self, newshape):
Returns a reshaped version of the tensor
axes
:Any
:returns
:_
__truediv__(self, other):
__rtruediv__(self, other):
__rmul__(self, other):
__mul__(self, other):
true_multiply(self, other):
Multiplies self and other
other
:Any
:returns
:_
dot(self, other):
Takes a regular dot product of self and other
other
:Any
axes
:Any
:returns
:_