diff --git a/code/config_global_1.2.json b/code/config_global_1.2.json
index 4b5133336367dcfe435400b7b67faacb913bc81d..8cfbf46448bcb18611089df54b86b308fc63b7d9 100644
--- a/code/config_global_1.2.json
+++ b/code/config_global_1.2.json
@@ -30,16 +30,18 @@
"validation_data_path": null
}
},
- "evaluation": false,
"gold_test_data_path": null
},
"output":{
- "file":{
- "tab_to_bracket": true,
- "conllu":true,
- "metadata": true
+ "conll_file":{
+ "to_do": true,
+ "metadata": true,
+ "with_gold_labels": true
},
- "scores":false
+ "txt_file":{
+ "to_do": true,
+ "metadata": true
+ }
}
}
diff --git a/code/config_global_1.21.json b/code/config_global_1.21.json
index 1e8c4a92ea30cea09445fafac64523cf0939d0fa..21351a824b3bbaf6558f3f1b307911bd3af3c570 100644
--- a/code/config_global_1.21.json
+++ b/code/config_global_1.21.json
@@ -30,16 +30,18 @@
"validation_data_path": null
}
},
- "evaluation": false,
"gold_test_data_path": null
},
"output":{
- "file":{
- "conllu":true,
+ "conll_file":{
+ "to_do": true,
"metadata": true,
- "tab_to_bracket": false
+ "with_gold_labels": true
},
- "scores":false
+ "txt_file":{
+ "to_do": true,
+ "metadata": true
+ }
}
}
diff --git a/code/config_global_2.2.json b/code/config_global_2.2.json
new file mode 100644
index 0000000000000000000000000000000000000000..afc2e1f77059016fd1ee08f4b7ee825eeb3883a6
--- /dev/null
+++ b/code/config_global_2.2.json
@@ -0,0 +1,49 @@
+{
+ "usecase_description": "Config file for usecase_2 : from a gold text, make predictions with an existing model, compare gold and predictions with metrics.",
+ "data_raw": {
+ "name": "fra.sdrt.annodis_dev",
+ "exte": ".conllu",
+ "language": "fr",
+ "existing_metadata": true
+ },
+ "steps":{
+ "main": "test",
+ "pre-processing": {
+ "to_do": false,
+ "syntactic_tool": "stanza",
+ "sentence_split": true,
+ "tokenization": true,
+ "syntactic_parsing": true,
+ "create_metadata": {
+ "to_do": false,
+ "line": "paragraph",
+ "sent": "sent"
+ }
+ },
+ "discourse_segmenter": {
+ "model": "tony",
+ "training": {
+ "toolkit": null,
+ "pre_trained_lm": null,
+ "config_file": null,
+ "train_data_path": null,
+ "validation_data_path": null
+ }
+ },
+ "gold_test_data_path": null
+ },
+ "output":{
+ "conll_file":{
+ "to_do": true,
+ "metadata": true,
+ "with_gold_labels": true
+ },
+ "txt_file":{
+ "to_do": true,
+ "metadata": true
+ }
+ }
+}
+
+
+
diff --git a/code/discut22_2.py b/code/discut22_2.py
index 543cd4d7f38beb0fddd0054490da25234f8f7492..a10bc31571a037f5e5ce46ece487ad6ec0be35b5 100644
--- a/code/discut22_2.py
+++ b/code/discut22_2.py
@@ -12,11 +12,12 @@ from datetime import datetime
import os
import re
import json
-import utils_2.syntactic_parsing as synt_pars
+import utils.syntactic_parsing as synt_pars
import utils.conv2ner as conv_to_ner # TODO clean it
import utils.json2conll as json_to_connl # TODO clean it
import utils.training_allennlp as tr_allen
import utils.conll2bracket as c2bracket
+import utils.seg_eval as seg_eval
@@ -26,6 +27,7 @@ class Data:
self.lang = infos['language']
self.path = f"../data/{self.name}"
self.exte = infos['exte']
+ self.raw = f"{self.path}/{self.name}{self.exte}"
self.stamp = stamp
self.conv = f"{self.path}/data_converted_{stamp}"
self.resu = f"{self.path}/results_{stamp}"
@@ -33,11 +35,14 @@ class Data:
def create_folders(self): # -> can be rtansfor into method of class
for it in [self.conv, self.resu]:
+ print(f"----> Checking/creating folder {it}.")
if not os.path.isdir(it):
os.mkdir(it)
+ my_logs['folders'] = f"{self.conv}, {self.resu}"
def pre_processing(self, steps):
- file_in = f"{self.path}/{self.name}{self.exte}"
+ print("----> Preprocessing input data.")
+ file_in = self.raw
if steps.pre_process_to_do == True:
file_out = f"{self.conv}/{self.name}.conll"
if steps.synt_tool == "stanza":
@@ -70,21 +75,38 @@ class Data:
OUTPUT: Tokenized text with just 4 columns.
"""
self.ner = f"{self.preprocessed}.ner"
+ self.ner = f"{self.conv}/{self.name}.conll.ner"
+ print(f"----> Making NER format {self.ner}.")
conv_to_ner.main(self.preprocessed, self.ner, "conll") # <-- TODO faire en relatif#TODO add same for train/dev/test for config train
my_logs['data_ner'] = self.ner
def make_predictions(self, steps):
self.pred_json = f"{self.resu}/{self.name}_pred.json"
cmd = f"allennlp predict --use-dataset-reader --output-file {self.pred_json} {steps.model_path} {self.ner} &> {self.resu}/logs_predictions.txt"
+ print(f"----> Making predictions: {cmd}.")
os.system(cmd)
+ my_logs['predictions_cmd'] = cmd
- def pred_json_to_conll_with_metadata(self):
- self.pred_meta_conll = f"{self.resu}/{self.name}_pred_n_meta.conll"
+
+ def pred_json_to_conll_w_metadata_w_gold(self): # here and 3 below..sorry..factorsation TBD
+ self.pred_conll_meta_gold = f"{self.resu}/{self.name}_pred_meta_gold.conll"
+ json_to_connl.js2conllNmetaNgold(self.pred_json, self.pred_conll_meta_gold, "conll", self.preprocessed)
+ return self.pred_conll_meta_gold
+
+ def pred_json_to_conll_w_metadata(self):
+ self.pred_meta_conll = f"{self.resu}/{self.name}_pred_meta.conll"
json_to_connl.js2conllNmeta(self.pred_json, self.pred_meta_conll, "conll", self.preprocessed)
+ return self.pred_meta_conll
+
+ def pred_json_to_conll_w_gold(self):
+ self.pred_conll_gold = f"{self.resu}/{self.name}_pred_gold.conll"
+ json_to_connl.js2conll(self.pred_json, self.pred_conll_gold, "conll")
+ return self.pred_conll_gold
def pred_json_to_conll(self):
self.pred_conll = f"{self.resu}/{self.name}_pred.conll"
json_to_connl.js2conll(self.pred_json, self.pred_conll, "conll")
+ return self.pred_conll
def brackets_txt(self):
self.brack = f"{self.resu}/{self.name}_brac.txt"
@@ -95,6 +117,44 @@ class Data:
c2bracket.conll2brackets_with_meta(self.pred_meta_conll, self.brack_meta)
+ def evaluation(self, prod):
+ self.basic_metrics = f"{self.resu}/Evaluation_metrics.json"
+
+ if self.exte == ".conll" or self.exte == ".conllu": # get gold file
+ gold = self.raw
+ else:
+ gold = self.preprocessed
+
+ if prod.conll_todo == False: # get pred_file
+ pred = self.pred_json_to_conll()
+ else:
+ if prod.conll_meta == True:
+ if prod.conll_w_gold == True:
+ pred = self.pred_json_to_conll_w_metadata_w_gold()
+ else:
+ pred = self.pred_json_to_conll_w_metadata()
+ else:
+ if prod.conll_w_gold == True:
+ pred = self.pred_json_to_conll_w_gold()
+ else:
+ pred = self.pred_json_to_conll()
+
+ print(f"----> Predictions to file {pred}")
+ print(f"----> Evaluation scores to file {self.basic_metrics}")
+ scores_dict = seg_eval.get_scores(gold, pred)
+ with open(self.basic_metrics, 'w') as fo:
+ json.dump(scores_dict, fo)
+
+
+class Output:
+ def __init__(self, infos):
+ self.conll_todo = infos['conll_file']['to_do']
+ self.conll_meta = infos['conll_file']['metadata']
+ self.conll_w_gold = infos['conll_file']['with_gold_labels']
+ self.txt_todo = infos['txt_file']['to_do']
+ self.txt_meta = infos['txt_file']['metadata']
+
+
class Process:
def __init__(self, infos):
@@ -109,7 +169,6 @@ class Process:
self.meta_line = infos['pre-processing']['create_metadata']['line']
self.meta_sent = infos['pre-processing']['create_metadata']['sent']
-
#if self.main == "train":
#if self.ner_init == True : # à faire en relatif !! split truc
# self.train_data = f"{self.data.path}/{self.data.name}_train.ner{self.data.file}"
@@ -120,14 +179,14 @@ class Process:
self.toolkit = infos['discourse_segmenter']['training']['toolkit']
self.tr_config = infos['discourse_segmenter']['training']['config_file']
self.pretr_lm = infos['discourse_segmenter']['training']['pre_trained_lm']
-
self.model = infos['discourse_segmenter']['model'] # ezpz for Tony
- #self.post_tab = infos['post-processing']['json_to_tab']
-
- self.eval = infos['evaluation']
self.test_data = infos['gold_test_data_path']
+ def get_evaluation_status(self):
+ if self.main == "test":
+ self.eval = True
+ #elif self.main == "train":
def get_model(self):
self.model_path = ""
@@ -138,21 +197,12 @@ class Process:
os.system(dl)
self.model_path = f"../model/tony/{arch}"
else:
- print("Tony already in place !")
+ print("----> Tony already in place !")
self.model_path = f"../model/tony/{arch}"
else:
self.model_path = self.model
-
-
-class Output:
- def __init__(self, infos):
- self.prod_bracket = infos['file']['tab_to_bracket']
- self.prod_conll = infos['file']['conllu']
- self.metadata = infos['file']['metadata']
-
-
def get_stamp():
now = datetime.now()
stamp = re.sub('[\s:]', '_', str(now))
@@ -168,14 +218,14 @@ def get_config_infos(config, stamp):
return data, steps, prod
-def print_logs():
+def print_logs(dict_logs):
file_logs = f"{data.resu}/processes_logs.json"
- print(my_logs) # <-- ahaha TBD
+ with open(file_logs, 'w') as fi:
+ json.dump(dict_logs, fi, indent=4)
-
if __name__ == '__main__':
my_logs = {}
stamp = get_stamp()
@@ -191,32 +241,15 @@ if __name__ == '__main__':
data.create_folders()
data.pre_processing(steps)
data.make_ner_format()
- #TEST data_preprocessed = "/home/lriviere/andiamo/discut22/data/edgar_poe_short/data_converted_vendredi/edgar_poe_short.conll"
steps.get_model()
if steps.main == "annotation" or steps.main == "test":
- data.make_predictions(steps)
- #data_pred_json = "/home/lriviere/andiamo/discut22/data/edgar_poe_short/results_vendredi/edgar_poe_short_pred.json"
-
- data.pred_json_to_conll()
-
- if prod.metadata == True:
- data.pred_json_to_conll_with_metadata()
-
- if prod.prod_bracket == True:
- if data.exte != ".txt":
- exit("pb")
- else:
- data.brackets_txt()
- data.brackets_txt_with_metadata()
-
-
+ data.make_predictions(steps) # output allennlp JSON
#elif steps.main == "train":
+ steps.get_evaluation_status()
+ if steps.eval == True:
+ data.evaluation(prod)
-
-
- #scores = compare_pred_gold()
-
- #print_logs()
\ No newline at end of file
+ print_logs(my_logs) # <-- attention variable globale !
\ No newline at end of file
diff --git a/code/utils/conv2ner.py b/code/utils/conv2ner.py
index 71216dfba9ba10c25eeaf65fcbfcb414bb2471f5..4e6edbe72cf1c10f45b9206262887747e78efdb7 100644
--- a/code/utils/conv2ner.py
+++ b/code/utils/conv2ner.py
@@ -110,8 +110,8 @@ def conversion2ner(input, output, params=None):
# then, previous token label is set to B-E to signal end of previous segment
res[-1][-1] = "B-E"
start_doc = False
- if label not in maptags:
- print("warning, strange label ",label,file=sys.stderr)
+ #if label not in maptags:
+ #print("warning, strange label ",label,file=sys.stderr)
res.append([w,pos,"O",tag])
for line in res:
diff --git a/code/utils/json2conll.py b/code/utils/json2conll.py
index 73e16469176a74801d98641684c3bfd8671b417f..37c5a0fb1894348d7ebf1ed22332b75961172e91 100644
--- a/code/utils/json2conll.py
+++ b/code/utils/json2conll.py
@@ -5,6 +5,7 @@ conll format
import json
import sys
+import re
#filepath = sys.argv[1]
#config = sys.argv[2]
@@ -60,7 +61,8 @@ def js2conllNmeta(data_pred_json, data_out, config, data_meta):
tag = data[sent_pred_count]['tags'][tok]
tok += 1
#print(f"tok: {tok}, tag: {tag}, word: {word}, line : {line}")
- fo.write(f"{line}\t{map[tag]}\n")
+ new_line = re.sub('\t[^\t]+$', '', line)
+ fo.write(f"{new_line}\t{map[tag]}\n")
#if int(line.split("\t")[0]) == tok and line.split("\t")[1] == word:
# fo.write(f"{line}\t{tag}\n")
@@ -68,4 +70,29 @@ def js2conllNmeta(data_pred_json, data_out, config, data_meta):
#print(f"sentpred : {sent_pred}\n")
#print(f"word n tag : {word}:::{tag}\n")
-
\ No newline at end of file
+
+def js2conllNmetaNgold(data_pred_json, data_out, config, gold_n_meta):
+ data = []
+ sent_pred_count = 0
+ tok = 0
+ for line in open(data_pred_json, 'r'):
+ data.append(json.loads(line))
+
+ with open(data_out, 'w', encoding='utf-8') as fo, open(gold_n_meta, 'r') as fm:
+
+ # id
+ for line in fm:
+ line = line.strip()
+ if line.startswith("#"):
+ fo.write(f"{line}\n")
+ elif line == "":
+ sent_pred_count += 1
+ tok = 0
+ fo.write(f"{line}\n")
+ else:
+ sent_pred = data[sent_pred_count]
+ word = data[sent_pred_count]['words'][tok]
+ tag = data[sent_pred_count]['tags'][tok]
+ tok += 1
+ #print(f"tok: {tok}, tag: {tag}, word: {word}, line : {line}")
+ fo.write(f"{line}\t{map[tag]}\n")
\ No newline at end of file
diff --git a/code/utils/seg_eval.py b/code/utils/seg_eval.py
index 1808782d74c9c5c9e8961409fa558af9a07bce1f..d61d2efbcae5898e586d3ecfdfb2e3126a3d9ecf 100644
--- a/code/utils/seg_eval.py
+++ b/code/utils/seg_eval.py
@@ -68,9 +68,9 @@ Arguments:
"""
-__author__ = "Amir Zeldes"
+#__author__ = "Amir Zeldes"
__license__ = "Apache 2.0"
-__version__ = "1.0.1"
+#__version__ = "1.0.1"
def parse_data(infile, string_input=False):
if not string_input:
@@ -222,22 +222,3 @@ def get_scores(gold_file, pred_file, string_input=False):
return score_dict
-
-if __name__ == "__main__":
- p = argparse.ArgumentParser()
-
- p.add_argument("goldfile",help="Shared task gold file in .tok or .conll format")
- p.add_argument("predfile",help="Corresponding file with system predictions")
- p.add_argument("-s","--string_input",action="store_true",help="Whether inputs are file names or strings")
-
- opts = p.parse_args()
-
- score_dict = get_scores(opts.goldfile,opts.predfile,opts.string_input)
-
- print("File: " + score_dict["doc_name"])
- print("o Total tokens: " + str(score_dict["tok_count"]))
- print("o Gold " +score_dict["seg_type"]+": " + str(score_dict["gold_seg_count"]))
- print("o Predicted "+score_dict["seg_type"]+": " + str(score_dict["pred_seg_count"]))
- print("o Precision: " + str(score_dict["prec"]))
- print("o Recall: " + str(score_dict["rec"]))
- print("o F-Score: " + str(score_dict["f_score"]))
diff --git a/code/utils_2/syntactic_parsing.py b/code/utils/syntactic_parsing.py
similarity index 100%
rename from code/utils_2/syntactic_parsing.py
rename to code/utils/syntactic_parsing.py
diff --git a/code/utils_2/__init__.py b/code/utils_2/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/code/utils_2/__pycache__/__init__.cpython-37.pyc b/code/utils_2/__pycache__/__init__.cpython-37.pyc
deleted file mode 100644
index cefb68a0f66c85292395518615b5064b13104453..0000000000000000000000000000000000000000
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diff --git a/code/utils_2/__pycache__/syntactic_parsing.cpython-37.pyc b/code/utils_2/__pycache__/syntactic_parsing.cpython-37.pyc
deleted file mode 100644
index 14dde82debc911172ec9de77498bcdab8b0d87a4..0000000000000000000000000000000000000000
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