def run(fns_in, fnout, tile_json_fn, verbose=False):
# modified in place
tilej = json.load(open(tile_json_fn, 'r'))
for fnin in fns_in:
Ads, bs = loadc_Ads_bs([fnin], ico=True)
bounds = Ads2bounds(Ads, bs)
for tile in tilej['tiles'].values():
pips = tile['pips']
for k, v in pips.items():
pips[k] = bounds.get('PIP_' + v, [None, None, None, None])
wires = tile['wires']
for k, v in wires.items():
wires[k] = bounds.get('WIRE_' + v, [None, None, None, None])
timfuz.tilej_stats(tilej)
json.dump(
tilej,
open(fnout, 'w'),
sort_keys=True,
indent=4,
separators=(',', ': '))
def gen_flat(fns_in, sub_json, corner=None):
Ads, bs = loadc_Ads_bs(fns_in, ico=True)
bounds = Ads2bounds(Ads, bs)
zeros = set()
nonzeros = set()
for bound_name, bound_bs in bounds.items():
sub = sub_json['subs'].get(bound_name, None)
if sub:
# put entire delay into pivot
pivot = sub_json['pivots'][bound_name]
assert pivot not in zeros
nonzeros.add(pivot)
non_pivot = set(sub.keys() - set([pivot]))
#for name in non_pivot:
# assert name not in nonzeros, (pivot, name, nonzeros)
zeros.update(non_pivot)
yield pivot, bound_bs
else:
nonzeros.add(bound_name)
yield bound_name, bound_bs
# non-pivots can appear multiple times, but they should always be zero
# however, due to substitution limitations, just warn
violations = zeros.intersection(nonzeros)
if len(violations):
print('WARNING: %s non-0 non-pivot' % (len(violations)))
# XXX: how to best handle these?
# should they be fixed 0?
if corner:
zero_row = [None, None, None, None]
zero_row[corner_s2i[corner]] = 0
for zero in zeros - violations:
yield zero, zero_row
def gen_flat(fns_in, sub_json, corner=None):
Ads, bs = loadc_Ads_bs(fns_in)
bounds = Ads2bounds(Ads, bs)
# Elements with zero delay assigned due to sub group
group_zeros = set()
# Elements with a concrete delay
nonzeros = set()
if corner:
zero_row = [None, None, None, None]
zero_row[corner_s2i[corner]] = 0
else:
zero_row = None
for bound_name, bound_bs in bounds.items():
sub = sub_json['subs'].get(bound_name, None)
if bound_name in sub_json['zero_names']:
if zero_row:
yield bound_name, 0
elif sub:
#print('sub', sub)
# put entire delay into pivot
pivot = sub_json['pivots'][bound_name]
assert pivot not in group_zeros
nonzeros.add(pivot)
non_pivot = set(sub.keys() - set([pivot]))
#for name in non_pivot:
# assert name not in nonzeros, (pivot, name, nonzeros)
group_zeros.update(non_pivot)
#print('yield PIVOT', pivot)
yield pivot, bound_bs
else:
nonzeros.add(bound_name)
yield bound_name, bound_bs
# non-pivots can appear multiple times, but they should always be zero
# however, due to substitution limitations, just warn
violations = group_zeros.intersection(nonzeros)
if len(violations):
print('WARNING: %s non-0 non-pivot' % (len(violations)))
# XXX: how to best handle these?
# should they be fixed 0?
if zero_row:
# ZERO names should always be zero
#print('ZEROs: %u' % len(sub_json['zero_names']))
for zero in sub_json['zero_names']:
#print('yield ZERO', zero)
yield zero, zero_row
real_zeros = group_zeros - violations
print(
'Zero candidates: %u w/ %u non-pivot conflicts => %u zeros as solved'
% (len(group_zeros), len(violations), len(real_zeros)))
# Only yield elements not already yielded
for zero in real_zeros:
#print('yield solve-0', zero)
yield zero, zero_row
def run(fns_in, fnout, tile_json_fn, verbose=False):
# modified in place
tilej = json.load(open(tile_json_fn, 'r'))
for fnin in fns_in:
Ads, bs = loadc_Ads_bs([fnin])
bounds = Ads2bounds(Ads, bs)
bounds_pw, bounds_sites = sep_bounds(bounds)
print(len(bounds), len(bounds_pw), len(bounds_sites))
add_pip_wire(tilej, bounds_pw)
add_sites(tilej, bounds_sites)
timfuz.tilej_stats(tilej)
json.dump(tilej,
open(fnout, 'w'),
sort_keys=True,
indent=4,
separators=(',', ': '))
def run(fns_in,
corner,
run_corner,
sub_json=None,
bounds_csv=None,
dedup=True,
massage=False,
outfn=None,
verbose=False,
**kwargs):
print('Loading data')
Ads, b = loadc_Ads_b(fns_in, corner, ico=True)
# Remove duplicate rows
# is this necessary?
# maybe better to just add them into the matrix directly
if dedup:
oldn = len(Ads)
iold = instances(Ads)
Ads, b = simplify_rows(Ads, b, corner=corner)
print('Simplify %u => %u rows' % (oldn, len(Ads)))
print('Simplify %u => %u instances' % (iold, instances(Ads)))
if sub_json:
print('Sub: %u rows' % len(Ads))
iold = instances(Ads)
names_old = index_names(Ads)
run_sub_json(Ads, sub_json, verbose=verbose)
names = index_names(Ads)
print("Sub: %u => %u names" % (len(names_old), len(names)))
print('Sub: %u => %u instances' % (iold, instances(Ads)))
else:
names = index_names(Ads)
'''
Substitution .csv
Special .csv containing one variable per line
Used primarily for multiple optimization passes, such as different algorithms or additional constraints
'''
if bounds_csv:
Ads2, b2 = loadc_Ads_b([bounds_csv], corner, ico=True)
bounds = Ads2bounds(Ads2, b2)
assert len(bounds), 'Failed to load bounds'
rows_old = len(Ads)
Ads, b = filter_bounds(Ads, b, bounds, corner)
print('Filter bounds: %s => %s + %s rows' %
(rows_old, len(Ads), len(Ads2)))
Ads = Ads + Ads2
b = b + b2
assert len(Ads) or allow_zero_eqns()
assert len(Ads) == len(b), 'Ads, b length mismatch'
if verbose:
print
print_eqns(Ads, b, verbose=verbose)
#print
#col_dist(A_ubd, 'final', names)
if massage:
try:
Ads, b = massage_equations(Ads, b, corner=corner)
except SimplifiedToZero:
if not allow_zero_eqns():
raise
print('WARNING: simplified to zero equations')
Ads = []
b = []
print('Converting to numpy...')
names, Anp = A_ds2np(Ads)
run_corner(Anp,
np.asarray(b),
names,
corner,
outfn=outfn,
verbose=verbose,
**kwargs)