def _init_anserini():
global anserini_monkey
if anserini_monkey:
return
# jnius monkypatching
import jnius_config
anserini_found = False
for j in jnius_config.get_classpath():
if "anserini" in j:
anserini_found = True
break
assert anserini_found, 'Anserini jar not found: you should start PyTerrier, e.g. with '\
+ 'pt.init(boot_packages=["io.anserini:anserini:0.9.2:fatjar"])'
jnius_config.set_classpath = lambda x: x
anserini_monkey = True
#this is the Anserini early rank cutoff rule
from matchpy import Wildcard, ReplacementRule, Pattern
from .transformer import RankCutoffTransformer, rewrite_rules
x = Wildcard.dot('x')
_brAnserini = Wildcard.symbol('_brAnserini', AnseriniBatchRetrieve)
def set_k(_brAnserini, x):
_brAnserini.k = int(x.value)
return _brAnserini
rewrite_rules.append(ReplacementRule(
Pattern(RankCutoffTransformer(_brAnserini, x) ),
set_k
))
from matchpy import (
CustomConstraint,
Pattern,
ReplacementRule,
Wildcard,
replace_all,
)
logger = logging.getLogger(__name__)
# a_true = Wildcard.dot('a_true', BoolTrue)
# a_false = Wildcard.dot('a_false', BoolFalse)
a_num = Wildcard.symbol('a_num', Value)
b_num = Wildcard.symbol('b_num', Value)
a = Wildcard.dot('a')
b = Wildcard.dot('b')
c = Wildcard.dot('c')
d = Wildcard.dot('d')
e = Wildcard.dot('e')
f = Wildcard.dot('f')
star = Wildcard.star('star')
star_a = Wildcard.star('star_a')
star_b = Wildcard.star('star_b')
plus = Wildcard.plus('plus')
plus_a = Wildcard.plus('plus_a')
θ = Theta
def setup_rewrites():
from .batchretrieve import BatchRetrieve, FeaturesBatchRetrieve
#three arbitrary "things".
x = Wildcard.dot('x')
xs = Wildcard.plus('xs')
y = Wildcard.dot('y')
z = Wildcard.dot('z')
# two different match retrives
_br1 = Wildcard.symbol('_br1', BatchRetrieve)
_br2 = Wildcard.symbol('_br2', BatchRetrieve)
_fbr = Wildcard.symbol('_fbr', FeaturesBatchRetrieve)
# batch retrieves for the same index
BR_index_matches = CustomConstraint(lambda _br1, _br2: _br1.indexref == _br2.indexref)
BR_FBR_index_matches = CustomConstraint(lambda _br1, _fbr: _br1.indexref == _fbr.indexref)
# rewrite nested binary feature unions into one single polyadic feature union
rewrite_rules.append(ReplacementRule(
Pattern(FeatureUnionPipeline(x, FeatureUnionPipeline(y,z)) ),
lambda x, y, z: FeatureUnionPipeline(x,y,z)
))
rewrite_rules.append(ReplacementRule(
Pattern(FeatureUnionPipeline(FeatureUnionPipeline(x,y), z) ),
lambda x, y, z: FeatureUnionPipeline(x,y,z)
))
rewrite_rules.append(ReplacementRule(
Pattern(FeatureUnionPipeline(FeatureUnionPipeline(x,y), xs) ),
lambda x, y, xs: FeatureUnionPipeline(*[x,y]+list(xs))
))
# rewrite nested binary compose into one single polyadic compose
rewrite_rules.append(ReplacementRule(
Pattern(ComposedPipeline(x, ComposedPipeline(y,z)) ),
lambda x, y, z: ComposedPipeline(x,y,z)
))
rewrite_rules.append(ReplacementRule(
Pattern(ComposedPipeline(ComposedPipeline(x,y), z) ),
lambda x, y, z: ComposedPipeline(x,y,z)
))
rewrite_rules.append(ReplacementRule(
Pattern(ComposedPipeline(ComposedPipeline(x,y), xs) ),
lambda x, y, xs: ComposedPipeline(*[x,y]+list(xs))
))
# rewrite batch a feature union of BRs into an FBR
rewrite_rules.append(ReplacementRule(
Pattern(FeatureUnionPipeline(_br1, _br2), BR_index_matches),
lambda _br1, _br2: FeaturesBatchRetrieve(_br1.indexref, ["WMODEL:" + _br1.controls["wmodel"], "WMODEL:" + _br2.controls["wmodel"]])
))
def push_fbr_earlier(_br1, _fbr):
#TODO copy more attributes
_fbr.controls["wmodel"] = _br1.controls["wmodel"]
return _fbr
# rewrite a BR followed by a FBR into a FBR
rewrite_rules.append(ReplacementRule(
Pattern(ComposedPipeline(_br1, _fbr), BR_FBR_index_matches),
push_fbr_earlier
))
global rewrites_setup
rewrites_setup = True
from matchpy import Wildcard, Pattern, ReplacementRule, is_match, replace_all, ManyToOneReplacer
from operation import Int, Mul, Add, Pow, Log
from symbol import VariableSymbol, ConstantSymbol
from constraint import FreeQ, NonzeroQ
a, b, c, d, e, f, g, h, x = map(VariableSymbol, 'abcdefghx')
n, m = map(VariableSymbol, 'nm')
a_, b_, c_, d_, e_, f_, g_, h_ = map(Wildcard.dot, 'abcdefgh')
n_, m_ = map(Wildcard.dot, 'nm')
x_ = Wildcard.symbol('x')
u_ = Wildcard.symbol('u')
one = ConstantSymbol(1)
m_one = ConstantSymbol(-1)
pattern1 = Pattern(Int(Mul(a_, Pow(x_, -1)), x), FreeQ((a, ), x))
rule1 = ReplacementRule(pattern1, lambda a, x: Mul(a, Log(x)))
pattern2 = Pattern(Int(Pow(x_, m_), x), FreeQ((m, ), x),
NonzeroQ(Add(m_, one), (m, )))
rule2 = ReplacementRule(
pattern2, lambda m, x: Mul(Pow(x, Add(m, one)), Pow(Add(m, one), m_one)))
rubi = ManyToOneReplacer(rule1)
rubi.add(rule2)
test = [[
Int(Pow(x, one), x),
Mul(Pow(Add(one, one), m_one), Pow(x, Add(one, one)))
