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import csv, os
import pandas as pd
import gradio as gr
from abc import ABC
from modules.utils import DateLogs
from typing import List, Tuple, Any
from modules.module_WordExplorer import WordExplorer
from modules.module_BiasExplorer import WEBiasExplorer2Spaces, WEBiasExplorer4Spaces
from modules.module_word2Context import Word2Context
from modules.module_rankSents import RankSents
from modules.module_crowsPairs import CrowsPairs
from modules.module_ErrorManager import ErrorManager
class Connector(ABC):
def __init__(
self,
lang: str
) -> None:
self.datalog = DateLogs()
self.log_folder = 'logs'
if not hasattr(Connector, 'errorManager'):
Connector.errorManager = ErrorManager(
path=f"modules/error_messages/{lang}.json"
)
def parse_word(
self,
word: str
) -> str:
return word.lower().strip()
def parse_words(
self,
array_in_string: str
) -> List[str]:
words = array_in_string.strip()
if not words:
return []
words = [
self.parse_word(word)
for word in words.split(',') if word.strip() != ''
]
return words
def logs_save(
self,
file_name: str,
headers: List[str]=None,
*data: List[Any]
) -> None:
if file_name is None:
return None
if not os.path.exists(self.log_folder):
print(f"Creating logs folder '{self.log_folder}' ...")
os.mkdir(self.log_folder)
file_path = os.path.join(self.log_folder, file_name+'.csv')
f_out = None
if not os.path.exists(file_path):
print(f"Creating new '{file_name}' logs file...")
with open(file_path, mode='w', encoding='UTF8') as f_out:
# Create the csv writer
writer = csv.writer(f_out)
# Write the header
if headers is None:
headers = [
"input_" + str(ith)
for ith,_ in enumerate(data)
]
headers = headers + ["datatime"]
writer.writerow(headers)
with open(file_path, mode='a', encoding='UTF8') as f_out:
# Create the csv writer
writer = csv.writer(f_out)
# Write a row to the csv file
data = list(data) + [ self.datalog.full() ]
writer.writerow(data)
print(f"Logs: '{file_path}' successfully saved!")
class WordExplorerConnector(Connector):
def __init__(
self,
**kwargs
) -> None:
Connector.__init__(self, kwargs.get('lang', 'en'))
embedding = kwargs.get('embedding', None)
self.logs_file_name = kwargs.get('logs_file_name', None)
self.headers = [
"word_list_to_diagnose",
"word_list_1",
"word_list_2",
"word_list_3",
"word_list_4"
]
if embedding is None:
raise KeyError
self.word_explorer = WordExplorer(
embedding=embedding,
errorManager=self.errorManager
)
def plot_proyection_2d(
self,
wordlist_0: str,
wordlist_1: str,
wordlist_2: str,
wordlist_3: str,
wordlist_4: str,
color_wordlist_0: str,
color_wordlist_1: str,
color_wordlist_2: str,
color_wordlist_3: str,
color_wordlist_4: str,
n_alpha: float,
fontsize: int,
n_neighbors: int
) -> Tuple:
err = ""
neighbors_method = 'sklearn'
wordlist_0 = self.parse_words(wordlist_0)
wordlist_1 = self.parse_words(wordlist_1)
wordlist_2 = self.parse_words(wordlist_2)
wordlist_3 = self.parse_words(wordlist_3)
wordlist_4 = self.parse_words(wordlist_4)
if not (wordlist_0 or wordlist_1 or wordlist_2 or wordlist_1 or wordlist_4):
err = self.errorManager.process(['CONECTION_NO_WORD_ENTERED'])
return None, err
err = self.word_explorer.check_oov(
[wordlist_0, wordlist_1, wordlist_2, wordlist_3, wordlist_4]
)
if err:
return None, err
# Save inputs in logs file
self.logs_save(
self.logs_file_name,
self.headers,
wordlist_0,
wordlist_1,
wordlist_2,
wordlist_3,
wordlist_4,
)
fig = self.word_explorer.plot_projections_2d(
wordlist_0,
wordlist_1,
wordlist_2,
wordlist_3,
wordlist_4,
color_wordlist_0=color_wordlist_0,
color_wordlist_1=color_wordlist_1,
color_wordlist_2=color_wordlist_2,
color_wordlist_3=color_wordlist_3,
color_wordlist_4=color_wordlist_4,
n_alpha=n_alpha,
fontsize=fontsize,
n_neighbors=n_neighbors,
nn_method = neighbors_method
)
return fig, err
class BiasWordExplorerConnector(Connector):
def __init__(
self,
**kwargs
) -> None:
Connector.__init__(self, kwargs.get('lang', 'en'))
embedding = kwargs.get('embedding', None)
self.logs_file_name = kwargs.get('logs_file_name', None)
self.headers = [
"word_list_to_diagnose",
"word_list_1",
"word_list_2",
"word_list_3",
"word_list_4",
"plot_space"
]
if embedding is None:
raise KeyError
self.bias_word_explorer_2_spaces = WEBiasExplorer2Spaces(
embedding=embedding,
errorManager=self.errorManager
)
self.bias_word_explorer_4_spaces = WEBiasExplorer4Spaces(
embedding=embedding,
errorManager=self.errorManager
)
def calculate_bias_2d(
self,
wordlist_1: str,
wordlist_2: str,
to_diagnose_list: str
) -> Tuple:
err = ""
wordlist_1 = self.parse_words(wordlist_1)
wordlist_2 = self.parse_words(wordlist_2)
to_diagnose_list = self.parse_words(to_diagnose_list)
word_lists = [wordlist_1, wordlist_2, to_diagnose_list]
for _list in word_lists:
if not _list:
err = self.errorManager.process(['BIASEXPLORER_NOT_ENOUGH_WORD_2_KERNELS'])
if err:
return None, err
err = self.bias_word_explorer_2_spaces.check_oov(word_lists)
if err:
return None, err
# Save inputs in logs file
self.logs_save(
self.logs_file_name,
self.headers,
to_diagnose_list,
wordlist_1,
wordlist_2,
"",
"",
"2d"
)
fig = self.bias_word_explorer_2_spaces.calculate_bias(
to_diagnose_list,
wordlist_1,
wordlist_2
)
return fig, err
def calculate_bias_4d(
self,
wordlist_1: str,
wordlist_2: str,
wordlist_3: str,
wordlist_4: str,
to_diagnose_list: str
) -> Tuple:
err = ""
wordlist_1 = self.parse_words(wordlist_1)
wordlist_2 = self.parse_words(wordlist_2)
wordlist_3 = self.parse_words(wordlist_3)
wordlist_4 = self.parse_words(wordlist_4)
to_diagnose_list = self.parse_words(to_diagnose_list)
wordlists = [wordlist_1, wordlist_2, wordlist_3, wordlist_4, to_diagnose_list]
for _list in wordlists:
if not _list:
err = self.errorManager.process(['BIASEXPLORER_NOT_ENOUGH_WORD_4_KERNELS'])
if err:
return None, err
err = self.bias_word_explorer_4_spaces.check_oov(wordlists)
if err:
return None, err
# Save inputs in logs file
self.logs_save(
self.logs_file_name,
self.headers,
to_diagnose_list,
wordlist_1,
wordlist_2,
wordlist_3,
wordlist_4,
"4d"
)
fig = self.bias_word_explorer_4_spaces.calculate_bias(
to_diagnose_list,
wordlist_1,
wordlist_2,
wordlist_3,
wordlist_4
)
return fig, err
class Word2ContextExplorerConnector(Connector):
def __init__(
self,
**kwargs
) -> None:
Connector.__init__(self, kwargs.get('lang', 'en'))
vocabulary = kwargs.get('vocabulary', None)
context = kwargs.get('context', None)
self.logs_file_name = kwargs.get('logs_file_name', None)
self.headers = [
"word",
"subsets_choice"
]
if vocabulary is None or context is None:
raise KeyError
self.word2context_explorer = Word2Context(
context,
vocabulary,
errorManager=self.errorManager
)
def get_word_info(
self,
word: str
) -> Tuple:
word = self.parse_word(word)
err = ""
contexts = pd.DataFrame([], columns=[''])
subsets_info = ""
distribution_plot = None
word_cloud_plot = None
subsets_choice = gr.CheckboxGroup.update(choices=[])
err = self.word2context_explorer.errorChecking(word)
if err:
return err, contexts, subsets_info, distribution_plot, word_cloud_plot, subsets_choice
subsets_info, subsets_origin_info = self.word2context_explorer.getSubsetsInfo(word)
clean_keys = [key.split(" ")[0].strip() for key in subsets_origin_info]
subsets_choice = gr.CheckboxGroup.update(choices=clean_keys)
distribution_plot = self.word2context_explorer.genDistributionPlot(word)
word_cloud_plot = self.word2context_explorer.genWordCloudPlot(word)
return err, contexts, subsets_info, distribution_plot, word_cloud_plot, subsets_choice
def get_word_context(
self,
word: str,
n_context: int,
subset_choice: List[str]
) -> Tuple:
word = self.parse_word(word)
err = ""
contexts = pd.DataFrame([], columns=[''])
err = self.word2context_explorer.errorChecking(word)
if err:
return err, contexts
if len(subset_choice) > 0:
ds = self.word2context_explorer.findSplits(word, subset_choice)
else:
err = self.errorManager.process(['WORD2CONTEXT_WORDS_OR_SET_MISSING'])
return err, contexts
# Save inputs in logs file
self.logs_save(
self.logs_file_name,
self.headers,
word,
subset_choice
)
list_of_contexts = self.word2context_explorer.getContexts(word, n_context, ds)
contexts = pd.DataFrame(list_of_contexts, columns=['#','contexto','conjunto'])
contexts["buscar"] = contexts.contexto.apply(lambda text: self.word2context_explorer.genWebLink(text))
return err, contexts
class PhraseBiasExplorerConnector(Connector):
def __init__(
self,
**kwargs
) -> None:
Connector.__init__(self, kwargs.get('lang', 'en'))
language_model = kwargs.get('language_model', None)
lang = kwargs.get('lang', None)
self.logs_file_name = kwargs.get('logs_file_name', None)
self.headers = [
"sent",
"word_list"
]
if language_model is None or lang is None:
raise KeyError
self.phrase_bias_explorer = RankSents(
language_model=language_model,
lang=lang,
errorManager=self.errorManager
)
def rank_sentence_options(
self,
sent: str,
interest_word_list: str,
banned_word_list: str,
exclude_articles: bool,
exclude_prepositions: bool,
exclude_conjunctions: bool,
n_predictions: int=5
) -> Tuple:
sent = " ".join(sent.strip().replace("*"," * ").split())
err = self.phrase_bias_explorer.errorChecking(sent)
if err:
return err, "", ""
interest_word_list = self.parse_words(interest_word_list)
banned_word_list = self.parse_words(banned_word_list)
# Save inputs in logs file
self.logs_save(
self.logs_file_name,
self.headers,
sent,
interest_word_list
)
all_plls_scores = self.phrase_bias_explorer.rank(
sent,
interest_word_list,
banned_word_list,
exclude_articles,
exclude_prepositions,
exclude_conjunctions,
n_predictions
)
all_plls_scores = self.phrase_bias_explorer.Label.compute(all_plls_scores)
return err, all_plls_scores, ""
class CrowsPairsExplorerConnector(Connector):
def __init__(
self,
**kwargs
) -> None:
Connector.__init__(self, kwargs.get('lang', 'en'))
language_model = kwargs.get('language_model', None)
self.logs_file_name = kwargs.get('logs_file_name', None)
self.headers = [
"sent_1",
"sent_2",
"sent_3",
"sent_4",
"sent_5",
"sent_6",
]
if language_model is None:
raise KeyError
self.crows_pairs_explorer = CrowsPairs(
language_model=language_model,
errorManager=self.errorManager
)
def compare_sentences(
self,
sent0: str,
sent1: str,
sent2: str,
sent3: str,
sent4: str,
sent5: str
) -> Tuple:
sent_list = [sent0, sent1, sent2, sent3, sent4, sent5]
err = self.crows_pairs_explorer.errorChecking(
sent_list
)
if err:
return err, "", ""
# Save inputs in logs file
self.logs_save(
self.logs_file_name,
self.headers,
sent_list
)
all_plls_scores = self.crows_pairs_explorer.rank(
sent_list
)
all_plls_scores = self.crows_pairs_explorer.Label.compute(all_plls_scores)
return err, all_plls_scores, "" |