def index_mode(self):
index_mode = []
for i, fi in zip(self, self.findices):
if is_integer(i) or q_affine(i, fi):
index_mode.append('regular')
else:
dims = {i for i in i.free_symbols if isinstance(i, Dimension)}
try:
# There's still hope it's regular if a DerivedDimension is used
candidate = dims.pop()
if candidate.parent == fi and q_affine(i, candidate):
index_mode.append('regular')
continue
except (KeyError, AttributeError):
pass
index_mode.append('irregular')
return tuple(index_mode)
def index_mode(self):
index_mode = []
for i, fi in zip(self, self.findices):
if is_integer(i):
index_mode.append('regular')
elif q_affine(i, fi):
index_mode.append('regular')
else:
index_mode.append('irregular')
return tuple(index_mode)
def aindices(self):
aindices = []
for i, fi in zip(self, self.findices):
if is_integer(i):
aindices.append(None)
elif q_affine(i, fi):
aindices.append(fi)
else:
dims = {i for i in i.free_symbols if isinstance(i, Dimension)}
aindices.append(dims.pop() if len(dims) == 1 else None)
return tuple(aindices)
def index_mode(self):
retval = []
for i, fi in zip(self, self.findices):
dims = {j for j in i.free_symbols if isinstance(j, Dimension)}
if len(dims) == 0 and q_constant(i):
retval.append(AFFINE)
elif len(dims) == 1:
candidate = dims.pop()
if fi in candidate._defines and q_affine(i, candidate):
retval.append(AFFINE)
else:
retval.append(IRREGULAR)
else:
retval.append(IRREGULAR)
return tuple(retval)
def _extract_nonaffine_indices(self, cluster, template, **kwargs):
"""
Extract non-affine array indices, and assign them to temporaries.
"""
make = lambda: Scalar(name=template(), dtype=np.int32).indexify()
mapper = OrderedDict()
for e in cluster.exprs:
for indexed in retrieve_indexed(e):
for i, d in zip(indexed.indices, indexed.base.function.indices):
if not (q_affine(i, d) or i.is_Number):
mapper[i] = make()
processed = [Eq(v, k) for k, v in mapper.items()]
processed.extend([e.xreplace(mapper) for e in cluster.exprs])
return cluster.rebuild(processed)
def _extract_nonaffine_indices(self, cluster, template, **kwargs):
"""
Extract non-affine array indices, and assign them to temporaries.
"""
make = lambda: Scalar(name=template(), dtype=np.int32).indexify()
mapper = OrderedDict()
for e in cluster.exprs:
# Note: using mode='all' and then checking for presence in the mapper
# (a few lines below), rather retrieving unique indexeds only (a set),
# is the key to deterministic code generation
for indexed in retrieve_indexed(e, mode='all'):
for i, d in zip(indexed.indices, indexed.function.indices):
if q_affine(i, d) or q_scalar(i):
continue
elif i not in mapper:
mapper[i] = make()
processed = [Eq(v, k) for k, v in mapper.items()]
processed.extend([e.xreplace(mapper) for e in cluster.exprs])
return cluster.rebuild(processed)
def _extract_nonaffine_indices(self, cluster, template, **kwargs):
"""
Extract non-affine array indices, and assign them to temporaries.
"""
make = lambda: Scalar(name=template(), dtype=np.int32).indexify()
mapper = OrderedDict()
for e in cluster.exprs:
# Note: using mode='all' and then checking for presence in the mapper
# (a few lines below), rather retrieving unique indexeds only (a set),
# is the key to deterministic code generation
for indexed in retrieve_indexed(e, mode='all'):
for i, d in zip(indexed.indices, indexed.function.indices):
if q_affine(i, d) or q_scalar(i):
continue
elif i not in mapper:
mapper[i] = make()
processed = [Eq(v, k) for k, v in mapper.items()]
processed.extend([e.xreplace(mapper) for e in cluster.exprs])
return cluster.rebuild(processed)
def index_mode(self):
return ['regular' if (is_integer(i) or q_affine(i, fi)) else 'irregular'
for i, fi in zip(self, self.findices)]
