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setting up zero-shot experiments (done and tested for MuseGen)

This commit is contained in:
andrea 2021-02-02 12:57:27 +01:00
parent 10bed81916
commit 7f493da0f8
3 changed files with 53 additions and 24 deletions
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24
main.py
View File

@ -15,23 +15,14 @@ def main(args):
print('Running generalized funnelling...')
data = MultilingualDataset.load(args.dataset)
data.set_view(languages=['it', 'da'])
data.set_view(languages=['it', 'da', 'nl'])
data.show_dimensions()
lX, ly = data.training()
# Testing zero shot experiments
# zero_shot_setting = True
# if zero_shot_setting:
# # _lX = {}
# _ly = {}
# train_langs = ['it']
# for train_lang in train_langs:
# # _lX[train_lang] = lX[train_lang]
# _ly[train_lang] = ly[train_lang]
# ly = _ly
lXte, lyte = data.test()
zero_shot = True
zscl_train_langs = ['it'] # Todo: testing zero shot
# Init multilingualIndex - mandatory when deploying Neural View Generators...
if args.gru_embedder or args.bert_embedder:
multilingualIndex = MultilingualIndex()
@ -45,7 +36,8 @@ def main(args):
embedder_list.append(posteriorEmbedder)
if args.muse_embedder:
museEmbedder = MuseGen(muse_dir=args.muse_dir, n_jobs=args.n_jobs, zero_shot=True)
museEmbedder = MuseGen(muse_dir=args.muse_dir, n_jobs=args.n_jobs,
zero_shot=zero_shot, train_langs=zscl_train_langs) # Todo: testing zero shot
embedder_list.append(museEmbedder)
if args.wce_embedder:
@ -82,6 +74,8 @@ def main(args):
# Testing ----------------------------------------
print('\n[Testing Generalized Funnelling]')
time_te = time.time()
# Zero shot scenario -> setting first tier learners zero_shot param to False
gfun.set_zero_shot(val=False)
ly_ = gfun.predict(lXte)
l_eval = evaluate(ly_true=lyte, ly_pred=ly_)
time_te = round(time.time() - time_te, 3)
@ -111,7 +105,7 @@ def main(args):
microf1=microf1,
macrok=macrok,
microk=microk,
notes=f'Train langs: {sorted(lX.keys())}')
notes=f'Train langs: {sorted(zscl_train_langs)}' if zero_shot else '')
print('Averages: MF1, mF1, MK, mK', np.round(np.mean(np.array(metrics), axis=0), 3))
overall_time = round(time.time() - time_init, 3)

13
src/funnelling.py
View File

@ -48,14 +48,17 @@ class DocEmbedderList:
for embedder in self.embedders:
lZ = embedder.transform(lX)
for lang in langs:
for lang in sorted(lZ.keys()):
Z = lZ[lang]
if lZparts[lang] is None:
lZparts[lang] = Z
else:
lZparts[lang] += Z
n_embedders = len(self.embedders)
return {lang: lZparts[lang]/n_embedders for lang in langs} # Averaging feature spaces
# Zero shot experiments: removing k:v if v is None (i.e, it is a lang that will be used in zero shot setting)
lZparts = {k: v for k, v in lZparts.items() if v is not None}
return {lang: lZparts[lang]/n_embedders for lang in sorted(lZparts.keys())} # Averaging feature spaces
def fit_transform(self, lX, ly):
return self.fit(lX, ly).transform(lX)
@ -122,3 +125,9 @@ class Funnelling:
lZ = self.first_tier.transform(lX)
ly = self.meta.predict(lZ)
return ly
def set_zero_shot(self, val: bool):
for embedder in self.first_tier.embedders:
embedder.embedder.set_zero_shot(val)
return

40
src/view_generators.py
View File

@ -93,13 +93,18 @@ class VanillaFunGen(ViewGen):
def fit_transform(self, lX, ly):
return self.fit(lX, ly).transform(lX)
def set_zero_shot(self, val: bool):
self.zero_shot = val
print('# TODO: PosteriorsGen has not been configured for zero-shot experiments')
return
class MuseGen(ViewGen):
"""
View Generator (m): generates document representation via MUSE embeddings (Fasttext multilingual word
embeddings). Document embeddings are obtained via weighted sum of document's constituent embeddings.
"""
def __init__(self, muse_dir='../embeddings', zero_shot=False, n_jobs=-1):
def __init__(self, muse_dir='../embeddings', zero_shot=False, train_langs: list = None, n_jobs=-1):
"""
Init the MuseGen.
:param muse_dir: string, path to folder containing muse embeddings
@ -111,7 +116,11 @@ class MuseGen(ViewGen):
self.langs = None
self.lMuse = None
self.vectorizer = TfidfVectorizerMultilingual(sublinear_tf=True, use_idf=True)
# Zero shot parameters
self.zero_shot = zero_shot
if train_langs is None:
train_langs = ['it']
self.train_langs = train_langs
def fit(self, lX, ly):
"""
@ -138,6 +147,7 @@ class MuseGen(ViewGen):
"""
# Testing zero-shot experiments
if self.zero_shot:
lX = self.zero_shot_experiments(lX)
lX = {l: self.vectorizer.vectorizer[l].transform(lX[l]) for l in self.langs if lX[l] is not None}
else:
lX = self.vectorizer.transform(lX)
@ -148,22 +158,23 @@ class MuseGen(ViewGen):
return lZ
def fit_transform(self, lX, ly):
print('## NB: Calling fit_transform!')
if self.zero_shot:
return self.fit(lX, ly).transform(self.zero_shot_experiments(lX))
return self.fit(lX, ly).transform(lX)
def zero_shot_experiments(self, lX, train_langs: list = ['it']):
print(f'# Zero-shot setting! Training langs will be set to: {sorted(train_langs)}')
def zero_shot_experiments(self, lX):
print(f'# Zero-shot setting! Training langs will be set to: {sorted(self.train_langs)}')
_lX = {}
for lang in self.langs:
if lang in train_langs:
if lang in self.train_langs:
_lX[lang] = lX[lang]
else:
_lX[lang] = None
lX = _lX
return lX
def set_zero_shot(self, val: bool):
self.zero_shot = val
return
class WordClassGen(ViewGen):
"""
@ -214,6 +225,11 @@ class WordClassGen(ViewGen):
def fit_transform(self, lX, ly):
return self.fit(lX, ly).transform(lX)
def set_zero_shot(self, val: bool):
self.zero_shot = val
print('# TODO: WordClassGen has not been configured for zero-shot experiments')
return
class RecurrentGen(ViewGen):
"""
@ -335,6 +351,11 @@ class RecurrentGen(ViewGen):
def fit_transform(self, lX, ly):
return self.fit(lX, ly).transform(lX)
def set_zero_shot(self, val: bool):
self.zero_shot = val
print('# TODO: RecurrentGen has not been configured for zero-shot experiments')
return
class BertGen(ViewGen):
"""
@ -405,3 +426,8 @@ class BertGen(ViewGen):
def fit_transform(self, lX, ly):
# we can assume that we have already indexed data for transform() since we are first calling fit()
return self.fit(lX, ly).transform(lX)
def set_zero_shot(self, val: bool):
self.zero_shot = val
print('# TODO: BertGen has not been configured for zero-shot experiments')
return