def clusterize(exprs):
"""
Group a sequence of :class:`ir.Eq`s into one or more :class:`Cluster`s.
"""
clusters = ClusterGroup()
flowmap = detect_flow_directions(exprs)
prev = None
for idx, e in enumerate(exprs):
if e.is_Tensor:
scalars = [i for i in exprs[prev:idx] if i.is_Scalar]
# Iteration space
ispace = IterationSpace.merge(e.ispace, *[i.ispace for i in scalars])
# Enforce iteration directions
fdirs, _ = force_directions(flowmap, lambda d: ispace.directions.get(d))
ispace = IterationSpace(ispace.intervals, ispace.sub_iterators, fdirs)
# Data space
dspace = DataSpace.merge(e.dspace, *[i.dspace for i in scalars])
# Prepare for next range
prev = idx
clusters.append(PartialCluster(scalars + [e], ispace, dspace))
# Group PartialClusters together where possible
clusters = groupby(clusters)
# Introduce conditional PartialClusters
clusters = guard(clusters)
return clusters.finalize()
def squash(self, other):
"""Concatenate the expressions in ``other`` to those in ``self``.
``self`` and ``other`` must have same ``ispace``. Duplicate
expressions are dropped. The :class:`DataSpace` is updated
accordingly."""
assert self.ispace.is_compatible(other.ispace)
self.exprs.extend([i for i in other.exprs if i not in self.exprs])
self.dspace = DataSpace.merge(self.dspace, other.dspace)
self.ispace = IterationSpace.merge(self.ispace, other.ispace)
def squash(self, other):
"""
Concatenate the expressions in ``other`` to those in ``self``.
``self`` and ``other`` must have same ``ispace``. Duplicate expressions
are dropped. The DataSpace is updated accordingly.
"""
assert self.ispace.is_compatible(other.ispace)
self.exprs.extend([i for i in other.exprs
if i not in self.exprs or i.is_Increment])
self.dspace = DataSpace.merge(self.dspace, other.dspace)
self.ispace = IterationSpace.merge(self.ispace, other.ispace)
def from_clusters(cls, *clusters):
"""
Build a new Cluster from a sequence of pre-existing Clusters with
compatible IterationSpace.
"""
assert len(clusters) > 0
root = clusters[0]
assert all(root.ispace.is_compatible(c.ispace) for c in clusters)
exprs = chain(*[c.exprs for c in clusters])
ispace = IterationSpace.merge(*[c.ispace for c in clusters])
dspace = DataSpace.merge(*[c.dspace for c in clusters])
return Cluster(exprs, ispace, dspace)
def dspace(self):
"""Return the DataSpace of this ClusterGroup."""
return DataSpace.merge(*[i.dspace for i in self])
def dspace(self):
"""Return the cumulative :class:`DataSpace` of this ClusterGroup."""
return DataSpace.merge(*[i.dspace for i in self])
def dspace(self):
"""Return the DataSpace of this ClusterGroup."""
return DataSpace.merge(*[i.dspace for i in self])
