From 2db208cdd5c912c99b3afda3e47901e69fa1da65 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Radek=20Hu=C5=A1ek?= <husek@iuuk.mff.cuni.cz>
Date: Sun, 12 Sep 2021 07:34:06 +0200
Subject: [PATCH] improve memory consumption
---
graph_tools/base.py | 5 +++--
graph_tools/misc.py | 7 ++++---
2 files changed, 7 insertions(+), 5 deletions(-)
diff --git a/graph_tools/base.py b/graph_tools/base.py
index 4954de5..9693fbe 100644
--- a/graph_tools/base.py
+++ b/graph_tools/base.py
@@ -136,13 +136,14 @@ def _init_():
return (p.finalize(ret), self.enumerate(ret))
@staticmethod
- def join(gadgets, joins, outs):
+ def join(gadgets, joins, outs, *, no_cache=False):
assert all( isinstance(g, Gadget) for g in gadgets ), \
"Not all gadgets are instance of Gadget: %s" % gadgets
assert sorted(list(chain.from_iterable(joins)) + outs) == \
[ (i+1, j+1) for i in range(len(gadgets)) for j in range(gadgets[i].size()) ]
info = (tuple(gadgets), tuple(joins), tuple(outs))
+ if no_cache: return JoinGadget(*info)
return Gadget._gadget_cache.get(info, lambda: JoinGadget(*info))
class FakeGadget(Gadget):
@@ -191,7 +192,7 @@ def _init_():
def do_eval():
ret = parameter.eval_join(
- [ g.eval_gadget(parameter, track_origins=track_origins) for g in gadgets ],
+ [ g.eval_gadget(parameter, track_origins=track_origins, no_cache=no_cache) for g in gadgets ],
joins, outs, self.offsets, track_origins
)
return ret
diff --git a/graph_tools/misc.py b/graph_tools/misc.py
index 42d6c3c..bc737e9 100644
--- a/graph_tools/misc.py
+++ b/graph_tools/misc.py
@@ -161,21 +161,22 @@ def _init_():
def edge_model_join(g1 : Gadget, g2 : Gadget):
assert g1.size() == g2.size()
joins = [ ((1, i+1), (2, i+1)) for i in range(g1.size()) ]
- return Gadget.join([ g1, g2 ], joins, [])
+ return Gadget.join([ g1, g2 ], joins, [], no_cache=True)
def parameter_matrix(P, gadgets):
from sage.all import matrix, QQ
- m = matrix(QQ, len(gadgets), len(gadgets))
+ m = matrix(QQ, len(gadgets), len(gadgets), sparse=True)
for r, gr in enumerate(gadgets):
for c, gc in enumerate(gadgets):
- m[r, c] = edge_model_join(gr, gc).eval(P)
+ m[r, c] = edge_model_join(gr, gc).eval(P, no_cache=True)
return m
+ # FIXME k cemu je to dobry?
def edge_model_join_matrix(P, k):
BG = [ FakeGadget(k, [ BoundaryValue(b, 1) ]) for b in P.enumerate_boundaries(k) ]
return parameter_matrix(P, BG)
--
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