diff --git a/classifier_bare_huggingface.py b/classifier_bare_huggingface.py
index 22c0509031653b1a9978438fa2d78758ab5b7a5f..bf1e7203cb8a0c1e10a6de3021546907259d03b7 100644
--- a/classifier_bare_huggingface.py
+++ b/classifier_bare_huggingface.py
@@ -16,7 +16,7 @@ from utils import *
device = torch.device("cuda")
-print('\n\nwith Language token - eng + Corpus (no framework) \n')
+# print('\n\nwith Language token - eng + Corpus (no framework) \n')
# ---------------------------------------------------------------------------------------------------
args = parse_args()
@@ -41,10 +41,6 @@ mappings, inv_mappings = open_mappings(args.mappings_file)
# Open sentences
train_sentences, dev_dict_sentences, test_dict_sentences, _ = open_sentences(args.data_path, mappings)
-print('\nCheck encodings:\n')
-print(train_sentences[0])
-
-
# make pandas dataframes
file_header = ['text', 'labels']
diff --git a/classifier_bare_pytorch.py b/classifier_bare_pytorch.py
index b1ee85aa96ec57acf0ccd90cac805908b146d2b5..d802a097c6e1a086d27dfb9603945fb9caa870c0 100644
--- a/classifier_bare_pytorch.py
+++ b/classifier_bare_pytorch.py
@@ -26,7 +26,7 @@ substitutions_file = 'mappings/substitutions.txt'
# mapping_classes = args.mappings_file[:-4].split('-')[-1]
# specific_results = open_specific_results('mappings/specific_results.txt')['B']
-print('ZERO-SHOT LANG: '+ args.langs_to_use)
+print('\nlangs to use: '+ args.langs_to_use + '\n')
set_seed(42)
torch.manual_seed(42)
@@ -80,8 +80,6 @@ tokenizer = AutoTokenizer.from_pretrained(args.transformer_model)
train_sentences, dev_dict_sentences, test_dict_sentences, framework_labels = open_sentences(args.data_path, mappings)
-
-print(framework_labels, flush=True)
# Determine linear size (= number of classes in the sets + 1)
num_labels = len(set(sent[-1] for sent in train_sentences)) + 1
diff --git a/configure.py b/configure.py
index 0eb23b91d67ac8a936c1305be187fc29ab18d8a0..52ecdbdfc3af336e742e2c848482049c7e619bdf 100644
--- a/configure.py
+++ b/configure.py
@@ -53,7 +53,7 @@ def parse_args():
help="Change order of sentences when the direction of relations is 1<2 to 2>1.")
# only specific languages/corpora
- parser.add_argument("--langs_to_use", default='', type=str,
+ parser.add_argument("--langs_to_use", default='@', type=str,
help="List of languages/corpora to use, a str separated by ;")
diff --git a/get_predictions.sh b/get_predictions.sh
deleted file mode 100644
index 8c5f7ddf38399331949c3787fe395c9506883863..0000000000000000000000000000000000000000
--- a/get_predictions.sh
+++ /dev/null
@@ -1,26 +0,0 @@
-#!/usr/bin/env bash
-
-#SBATCH --job-name=model-LC
-
-#SBATCH --ntasks=1
-#SBATCH --cpus-per-task=4
-#SBATCH --partition=GPUNodes
-#SBATCH --gres=gpu:1
-
-
-# tests tests
-
-
-# srun singularity exec /logiciels/containerCollections/CUDA10/pytorch.sif python3 xml-roberta-classifier.py \
-# --batch_size 4 \
-# --gradient_accumulation_steps 32 \
-# --num_epochs 6 \
-# --data_path '/users/melodi/emetheni/clean_data' \
-# --mappings_file 'mappings/mappings_substitutions.tsv' \
-# --transformer_model "xlm-roberta-base"
-
-
-srun singularity exec /logiciels/containerCollections/CUDA10/pytorch.sif python3 open_finetuned_model.py \
- --data_path '/users/melodi/emetheni/clean_data' \
- --mappings_file 'mappings/mappings_substitutions.tsv' \
- --transformer_model 'results/models/run_xlm-roberta-base/checkpoint-13500'
diff --git a/make_mappings_zero-shot.py b/make_mappings_zero-shot.py
index 14b05a6b31b50e80c52394a7f32391f6aa16f124..c2fd034201d102175663a529dbb948217577094d 100644
--- a/make_mappings_zero-shot.py
+++ b/make_mappings_zero-shot.py
@@ -29,23 +29,23 @@ for label, num in mappings.items():
# -----------------------------------
-# define which language to NOT use with the arguments
-not_language = args.langs_to_use
+# define which language to use with the arguments
+languages = args.langs_to_use.split(';')
-corpora = [folder for folder in os.listdir(args.data_path)
- if not not_language in folder]
+corpora = [folder
+ for folder in os.listdir(args.data_path)
+ if any(l in folder for l in languages)]
files = ['/'.join([args.data_path, corpus, f])
for corpus in corpora
- for f in os.listdir(args.data_path + '/' + corpus)
- ]
+ for f in os.listdir(args.data_path + '/' + corpus)]
# open the files
def read_file(file):
''' Open the relations file. '''
relations = []
-
+ sub_rels = []
with open(file, 'r', encoding='utf-8') as f:
next(f)
for line in f:
@@ -53,50 +53,48 @@ def read_file(file):
l = line.strip().split('\t')
if not l[11].lower() in subs:
relations.append(l[11].lower())
+ else:
+ sub_rels.append(l[11].lower())
except IndexError:
pass
- return relations
+ return relations, sub_rels
rel_files = [f for f in files if any (x in f for x in ['train', 'test', 'dev'])]
-rels = []
+good_rels = []
+sub_rels = []
for f in rel_files:
- temp = read_file(f)
- if temp != []:
- rels += temp
+ x, y = read_file(f)
+ good_rels += x
+ sub_rels += y
-dict_labels = dict(enumerate(list(set(rels))))
-inv_labels = {v:k for k, v in dict_labels.items()}
+dict_labels = dict(enumerate(list(set(good_rels))))
+corpora_labels = {v:k for k, v in dict_labels.items()}
-leftovers = []
-for sub in subs:
- if sub not in inv_labels:
- try:
- inv_labels[sub] = inv_labels[subs[sub]]
- except KeyError:
- leftovers.append(sub)
- else:
- leftovers.append(sub)
-for mapping in mappings:
- if mapping not in inv_labels:
- leftovers.append(mapping)
-counter = len(inv_labels) -1
-for i in leftovers:
- counter += 1
- inv_labels[i] = counter
-
+leftovers = []
+
+# for mapping in mappings:
+# if mapping not in corpora_labels and mapping not in subs:
+# leftovers.append(mapping)
-# # save the new labels
-print('-'*20)
-print(not_language)
-print(len(inv_labels))
+# counter = max(list(corpora_labels.values())) -1
+# for i in leftovers:
+# counter += 1
+# corpora_labels[i] = counter
+for sub in sub_rels:
+ try:
+ corpora_labels[sub] = corpora_labels[subs[sub]]
+ except KeyError:
+ corpora_labels[subs[sub]] = max(list(corpora_labels.values())) + 1
+ corpora_labels[sub] = corpora_labels[subs[sub]]
+# print(corpora_labels)
-with open('mappings/zero-shot/' + not_language + '_zero-shot.tsv', 'w') as f:
+with open('mappings/jaccard/' + 'por.rst' + '.tsv', 'w') as f:
f.write('LABEL\tMAPPING\n')
- for k, v in inv_labels.items():
+ for k, v in corpora_labels.items():
f.write(k + '\t' + str(v) + '\n')
\ No newline at end of file
diff --git a/utils.py b/utils.py
index 3880be60ded41aef92cdfabed33a6aa261e613d4..393bfcb9727bfe1765fd5f60c5d94062daacd6bb 100644
--- a/utils.py
+++ b/utils.py
@@ -18,8 +18,9 @@ def open_mappings(mappings_file):
mappings = {}
with open(mappings_file, 'r') as f:
next(f)
- for l in f:
- mappings[l.split('\t')[0]] = int(l.strip().split('\t')[-1])
+ for line in f:
+ l = line.strip().split('\t')
+ mappings[l[0]] = int(l[-1])
inv_mappings = {}
# for label, num in mappings.items():
@@ -163,10 +164,13 @@ def open_sentences(path_to_corpora, mappings_dict):
- dict of sentences for TEST: each test set categorized per corpus
- ** NEW ** : dict of labels per framework
'''
-
+ langs_to_use = args.langs_to_use.split(';')
corpora = [folder for folder in os.listdir(path_to_corpora)
if not any(i in folder for i in ['.md', 'DS_', 'utils', 'ipynb'])
+ # langs here
+ #if any(l in folder for l in langs_to_use)
]
+
# ---------------------
train_sentences = []
@@ -186,8 +190,9 @@ def open_sentences(path_to_corpora, mappings_dict):
train_file = ['/'.join([path_to_corpora, corpus, x])
for x in os.listdir(path_to_corpora + '/' + corpus)
if 'train' in x and 'rels' in x
- # attention! we block training for some languages if we want HERE
- if not args.langs_to_use in x][0]
+ # attention! we ALLOW training for some corpora if we want HERE
+# if any(l in x for l in langs_to_use)
+ ][0]
temp = open_file(train_file, mappings_dict)
# train_sentences += open_file_with_lang(train_file, mappings_dict)
train_sentences += temp
@@ -216,9 +221,9 @@ def open_sentences(path_to_corpora, mappings_dict):
all_labels[framework] += [l[-1] for l in temp]
# test_dict_sentences[corpus] += open_file_with_lang(test_file, mappings_dict)
- labels = {framework:set(all_labels[framework]) for framework in all_labels}
+ corpus_labels = {framework:set(all_labels[framework]) for framework in all_labels}
- return train_sentences, dev_dict_sentences, test_dict_sentences, labels
+ return train_sentences, dev_dict_sentences, test_dict_sentences, corpus_labels
def open_sentences_with_lang(path_to_corpora, mappings_dict):
@@ -237,7 +242,8 @@ def open_sentences_with_lang(path_to_corpora, mappings_dict):
train_sentences = []
dev_dict_sentences = {}
test_dict_sentences = {}
-
+ corpus_labels = []
+
for corpus in corpora:
try:
@@ -267,7 +273,7 @@ def open_sentences_with_lang(path_to_corpora, mappings_dict):
# test_dict_sentences[corpus] += open_file_with_lang(test_file, mappings_dict)
- return train_sentences, dev_dict_sentences, test_dict_sentences
+ return train_sentences, dev_dict_sentences, test_dict_sentences, corpus_labels
@@ -333,7 +339,7 @@ def get_predictions_huggingface(trainer,
'''
results = trainer.predict(test_set)
- preds = np.softmax(results.predictions, axis=1)
+# preds = np.softmax(results.predictions, axis=1)
top_preds = np.argmax(results.predictions, axis=1)
results = results.label_ids
test_acc = round(accuracy_score(top_preds, results), 4)
@@ -341,7 +347,7 @@ def get_predictions_huggingface(trainer,
if print_results:
print(corpus, '\t', test_acc, '\n')
- return preds
+# return preds
def get_better_predictions(model,