diff --git a/python/dune/codegen/loopy/transformations/performance.py b/python/dune/codegen/loopy/transformations/performance.py
index b8995e32687078aa8272086f210b6da5e088e916..02644e80c3c0f782309a165c050949e0f1d71cb2 100644
--- a/python/dune/codegen/loopy/transformations/performance.py
+++ b/python/dune/codegen/loopy/transformations/performance.py
@@ -1,6 +1,7 @@
from dune.codegen.options import get_form_option
from dune.codegen.sumfact.transformations import sumfact_performance_transformations
+
def performance_transformations(kernel, signature):
if get_form_option("sumfact"):
kernel = sumfact_performance_transformations(kernel, signature)
diff --git a/python/dune/codegen/loopy/transformations/remove_reductions.py b/python/dune/codegen/loopy/transformations/remove_reductions.py
index f53816126686fc8407c468503b4dd59694faab19..dd083951ef87bd8f0ded85aba38949021a916c26 100644
--- a/python/dune/codegen/loopy/transformations/remove_reductions.py
+++ b/python/dune/codegen/loopy/transformations/remove_reductions.py
@@ -2,6 +2,7 @@ import loopy as lp
import pymbolic.primitives as prim
+
def remove_reduction(knl, match):
"""Removes all matching reductions and do direct accumulation in assignee instead"""
@@ -21,7 +22,7 @@ def remove_reduction(knl, match):
knl = lp.remove_instructions(knl, set([instr.id]))
# Add instruction that sets assignee to zero
- id_zero = instr.id + '_set_zero'
+ id_zero = instr.id + '_set_zero'
instructions.append(lp.Assignment(instr.assignee,
0,
within_inames=instr.within_inames,
@@ -41,7 +42,6 @@ def remove_reduction(knl, match):
depends_on=frozenset((id_zero,) + tuple(depends_on)),
tags=('assignment',)))
-
knl = knl.copy(instructions=knl.instructions + instructions)
for dep in depending:
diff --git a/python/dune/codegen/sumfact/autotune.py b/python/dune/codegen/sumfact/autotune.py
index e89f13c271ae6517baab92afbde305994c4c965f..a8dfd4ac2183e493012d61fa1811f988b498c040 100644
--- a/python/dune/codegen/sumfact/autotune.py
+++ b/python/dune/codegen/sumfact/autotune.py
@@ -19,6 +19,7 @@ from dune.codegen.sumfact.realization import realize_sumfact_kernel_function
from dune.codegen.options import get_option, set_option
from dune.codegen.error import CodegenAutotuneError
+
def get_cmake_cache_entry(entry):
for line in open(os.path.join(get_option("project_basedir"), "CMakeCache.txt"), "r"):
match = re.match("{}:[INTERNAL|FILEPATH|BOOL|STRING|PATH|UNINITIALIZED|STATIC]+=(.*)".format(entry), line)
@@ -319,7 +320,7 @@ def generate_standalone_kernel_code(kernel, signature, filename):
# Get a list of the function argument names
assert len(signature) == 1
sig = signature[0]
- arguments = sig[sig.find('(') +1:sig.find(')')].split(',')
+ arguments = sig[sig.find('(') + 1:sig.find(')')].split(',')
arguments = [a.split(' ')[-1] for a in arguments]
global_args = [a for a in kernel.args if a.name not in arguments]
@@ -338,7 +339,7 @@ def generate_standalone_kernel_code(kernel, signature, filename):
# Generate function we want to benchmark
f.write('\n')
- f.write(sig[0:sig.find(')')+1])
+ f.write(sig[0:sig.find(')') + 1])
f.writelines(lp.generate_body(kernel))
f.write('\n\n')
diff --git a/python/dune/codegen/sumfact/realization.py b/python/dune/codegen/sumfact/realization.py
index 38171bdb05554b00e050bd0fc8899cf585c19e61..461f5b0a3ace21e09a7a3707c4849aa1c36e6972 100644
--- a/python/dune/codegen/sumfact/realization.py
+++ b/python/dune/codegen/sumfact/realization.py
@@ -65,6 +65,7 @@ def _max_sum_factorization_buffer_size(sf):
product(m.basis_size for m in sf.matrix_sequence_cost_permuted) * sf.vector_width)
return size
+
@kernel_cached
def _realize_sum_factorization_kernel(sf):
insn_dep = sf.insn_dep
@@ -145,7 +146,7 @@ class BufferSwitcher(object):
# sure it is big enough.
assert sf
size = _max_sum_factorization_buffer_size(sf)
- globalarg(bs, shape=(size,), alignment=alignment, dim_tags=['f',])
+ globalarg(bs, shape=(size,), alignment=alignment, dim_tags=['f', ])
temporary_variable(name,
managed=True,
diff --git a/python/dune/codegen/sumfact/transformations.py b/python/dune/codegen/sumfact/transformations.py
index ffe5ca4181843233b9693ddda9bc117afae2d54f..bbc6c4f7c4459608fb5bdd17602249cb2cf47a37 100644
--- a/python/dune/codegen/sumfact/transformations.py
+++ b/python/dune/codegen/sumfact/transformations.py
@@ -10,6 +10,7 @@ from dune.codegen.options import get_form_option, get_option
from dune.codegen.pdelab.geometry import world_dimension
from dune.codegen.error import CodegenAutotuneError
+
def move_zero_assignment_up(kernel, move_up_inames):
if len(move_up_inames) == 0:
return kernel
@@ -23,9 +24,9 @@ def move_zero_assignment_up(kernel, move_up_inames):
instr_iname_set = set(i.assignee.index_tuple)
if move_iname_set.issubset(instr_iname_set):
# There should be only one matching instruction
- assert (instr==None)
+ assert instr is None
instr = i
- assert (instr!=None)
+ assert instr is not None
# Remove it
kernel = lp.remove_instructions(kernel, set([instr.id]))
@@ -70,7 +71,7 @@ def move_zero_assignment_up(kernel, move_up_inames):
instructions.append(instr.copy(assignee=assignee,
within_inames=frozenset(within_inames)))
kernel = kernel.copy(instructions=kernel.instructions + instructions,
- domains=domains)
+ domains=domains)
# Add dependency to inner assignment instructions
cond = lp.match.Tagged('assignment')
@@ -80,7 +81,7 @@ def move_zero_assignment_up(kernel, move_up_inames):
instr_iname_set = set(i.assignee.index_tuple)
if move_iname_set.issubset(instr_iname_set):
# There should be only one matching instruction
- assert (instr==None)
+ assert instr is None
instr = i
id_zero = instructions[0].id
@@ -120,18 +121,18 @@ def reorder_loops_in_tensor_contraction(kernel, iname_order):
# TODO: In principle there is no need to be dimension dependent. I'm just
# not sure how to pass the iname_order in the general case. This probably
# needs a rework anyway so I just do the 3D case first.
- assert dim==3
+ assert dim == 3
kernel = remove_all_reductions(kernel)
# TODO: Doc after rewrite
reduction_iname = 'j'
- iname_dict = { 'l' : 'sf_out_inames_2',
- 'k' : 'sf_out_inames_1',
- 'i' : 'sf_out_inames_0',
- 'j' : 'sf_red'}
+ iname_dict = {'l': 'sf_out_inames_2',
+ 'k': 'sf_out_inames_1',
+ 'i': 'sf_out_inames_0',
+ 'j': 'sf_red'}
reduction_index = iname_order.index(reduction_iname)
- move_up_inames = list(map(lambda x: iname_dict[x], iname_order[reduction_index+1:]))
+ move_up_inames = list(map(lambda x: iname_dict[x], iname_order[reduction_index + 1:]))
# cond = lp.match.Tagged('set_zero')
cond = lp.match.Tagged('assignment')
@@ -155,7 +156,6 @@ def reorder_loops_in_tensor_contraction(kernel, iname_order):
reduction_index = reduction_index.pop()
reduction_iname = 'sf_red_{}'.format(reduction_index)
-
prefered_iname_order = []
for i in inames:
if i not in current_move_up_inames and i.find('vec') == -1: