if tuple(options.explain) in tested:
continue
tested.add(tuple(options.explain))
print('sample {0}: {1}'.format(i, ','.join(s.split(','))))
# first, compute a valid explanation to guarantee
# that an explanation of this size exists
expl = xgb2.explain(options.explain)
# calling lime
timer = resource.getrusage(resource.RUSAGE_CHILDREN).ru_utime + \
resource.getrusage(resource.RUSAGE_SELF).ru_utime
expl = xgb.explain(options.explain, use_lime=lime_call, nof_feats=len(expl))
print('expl1:', expl)
print('szex1:', len(expl))
timer = resource.getrusage(resource.RUSAGE_CHILDREN).ru_utime + \
resource.getrusage(resource.RUSAGE_SELF).ru_utime - timer
ltimes.append(timer)
# validating explanation of lime
timer = resource.getrusage(resource.RUSAGE_CHILDREN).ru_utime + \
resource.getrusage(resource.RUSAGE_SELF).ru_utime
coex = xgb.validate(options.explain, expl)
timer = resource.getrusage(resource.RUSAGE_CHILDREN).ru_utime + \
errors = []
reduced = 0
for i, s in enumerate(lines):
options.explain = [float(v.strip()) for v in s.split(',')]
if tuple(options.explain) in tested:
continue
tested.add(tuple(options.explain))
print('sample {0}: {1}'.format(i, ','.join(s.split(','))))
# calling anchor
timer = resource.getrusage(resource.RUSAGE_CHILDREN).ru_utime + \
resource.getrusage(resource.RUSAGE_SELF).ru_utime
expl = xgb.explain(options.explain, use_anchor=anchor_call)
print('expl1:', expl)
print('szex1:', len(expl))
timer = resource.getrusage(resource.RUSAGE_CHILDREN).ru_utime + \
resource.getrusage(resource.RUSAGE_SELF).ru_utime - timer
atimes.append(timer)
# validating explanation of anchor
timer = resource.getrusage(resource.RUSAGE_CHILDREN).ru_utime + \
resource.getrusage(resource.RUSAGE_SELF).ru_utime
coex = xgb.validate(options.explain, expl)
timer = resource.getrusage(resource.RUSAGE_CHILDREN).ru_utime + \
xgb = XGBooster(options, from_data=data)
train_accuracy, test_accuracy, model = xgb.train()
# read a sample from options.explain
if options.explain:
options.explain = [
float(v.strip()) for v in options.explain.split(',')
]
if options.encode:
if not xgb:
xgb = XGBooster(options, from_model=options.files[0])
# encode it and save the encoding to another file
xgb.encode(test_on=options.explain)
if options.explain:
if not xgb:
# abduction-based approach requires an encoding
xgb = XGBooster(options, from_encoding=options.files[0])
if (options.encode == "ortools"):
expl = xgb.explain_ortools(options.explain)
else:
# exp0lain using anchor or the abduction-based approach
expl = xgb.explain(options.explain)
# here we take only first explanation if case enumeration was done
if options.xnum != 1:
expl = expl[0]
def enumerate_all(options, xtype, xnum, smallest, usecld, usemhs, useumcs,
prefix):
# setting the right preferences
options.xtype = xtype
options.xnum = xnum
options.reduce = 'lin'
options.smallest = smallest
options.usecld = usecld
options.usemhs = usemhs
options.useumcs = useumcs
# reading all unique samples
with open('../bench/nlp/spam/quant/spam10.samples', 'r') as fp:
lines = fp.readlines()
# timers and other variables
times, calls = [], []
xsize, exlen = [], []
# doing everything incrementally is expensive;
# let's restart the solver for every 10% of instances
tested = set()
for i, s in enumerate(lines):
if i % (len(lines) / 10) == 0:
# creating a new XGBooster
xgb = XGBooster(
options,
from_model=
'../temp/spam10_data/spam10_data_nbestim_50_maxdepth_3_testsplit_0.2.mod.pkl'
)
# encode it and save the encoding to another file
xgb.encode()
options.explain = [float(v.strip()) for v in s.split(',')]
if tuple(options.explain) in tested:
continue
tested.add(tuple(options.explain))
print(prefix, 'sample {0}: {1}'.format(i, ','.join(s.split(','))))
# calling anchor
timer = resource.getrusage(resource.RUSAGE_CHILDREN).ru_utime + \
resource.getrusage(resource.RUSAGE_SELF).ru_utime
expls = xgb.explain(options.explain)
timer = resource.getrusage(resource.RUSAGE_CHILDREN).ru_utime + \
resource.getrusage(resource.RUSAGE_SELF).ru_utime - timer
times.append(timer)
print(prefix, 'expls:', expls)
print(prefix, 'nof x:', len(expls))
print(prefix, 'timex: {0:.2f}'.format(timer))
print(prefix, 'calls:', xgb.x.calls)
print(prefix, 'Msz x:', max([len(x) for x in expls]))
print(prefix, 'msz x:', min([len(x) for x in expls]))
print(
prefix,
'asz x: {0:.2f}'.format(sum([len(x) for x in expls]) / len(expls)))
print('')
calls.append(xgb.x.calls)
xsize.append(sum([len(x) for x in expls]) / float(len(expls)))
exlen.append(len(expls))
print('')
print('all samples:', len(lines))
# reporting the time spent
print('{0} total time: {1:.2f}'.format(prefix, sum(times)))
print('{0} max time per instance: {1:.2f}'.format(prefix, max(times)))
print('{0} min time per instance: {1:.2f}'.format(prefix, min(times)))
print('{0} avg time per instance: {1:.2f}'.format(prefix,
sum(times) / len(times)))
print('{0} total oracle calls: {1}'.format(prefix, sum(calls)))
print('{0} max oracle calls per instance: {1}'.format(prefix, max(calls)))
print('{0} min oracle calls per instance: {1}'.format(prefix, min(calls)))
print('{0} avg oracle calls per instance: {1:.2f}'.format(
prefix,
float(sum(calls)) / len(calls)))
print('{0} avg number of explanations per instance: {1:.2f}'.format(
prefix,
float(sum(exlen)) / len(exlen)))
print('{0} avg explanation size per instance: {1:.2f}'.format(
prefix,
float(sum(xsize)) / len(xsize)))
print('')
mcalls = []
smem = []
mxmem = []
#with open("/tmp/texture.samples", 'r') as fp:
# insts = [line.strip() for line in fp.readlines()]
for i, inst in enumerate(insts):
if i == nof_insts:
break
# processing the instance
soptions.explain = [float(v.strip()) for v in inst.split(',')]
moptions.explain = [float(v.strip()) for v in inst.split(',')]
expl1 = sxgb.explain(soptions.explain)
print(f'i: {inst}', file=slog)
print(f's: {len(expl1)}', file=slog)
print(f't: {sxgb.x.time:.3f}', file=slog)
print('', file=slog)
smem.append(round(sxgb.x.used_mem / 1024.0, 3))
stimes.append(sxgb.x.time)
slog.flush()
sys.stdout.flush()
expl2 = mxgb.explain(moptions.explain)
print(f'i: {inst}', file=mlog)
print(f's: {len(expl2[0])}', file=mlog)
if options.encode:
if not xgb:
xgb = XGBooster(options, from_model=options.files[0])
# encode it and save the encoding to another file
xgb.encode(test_on=options.explain)
if options.explain:
if not xgb:
if options.uselime or options.useanchor or options.useshap:
xgb = XGBooster(options, from_model=options.files[0])
else:
# abduction-based approach requires an encoding
xgb = XGBooster(options, from_encoding=options.files[0])
# checking LIME or SHAP should use all features
if not options.limefeats:
options.limefeats = len(data.names) - 1
# explain using anchor or the abduction-based approach
expl = xgb.explain(
options.explain,
use_lime=lime_call if options.uselime else None,
use_anchor=anchor_call if options.useanchor else None,
use_shap=shap_call if options.useshap else None,
nof_feats=options.limefeats)
if (options.uselime or options.useanchor
or options.useshap) and options.validate:
xgb.validate(options.explain, expl)
