explorar_relaciones_entre_palabras.py

import matplotlib as mpl
mpl.use('Agg')

from audioop import bias
import gradio as gr

from modules_sesgo_en_palabras import  WEBiasExplorer2d, Embedding
from examples import examples_explorar_relaciones_entre_palabras
import matplotlib.pyplot as plt

from tool_info import TOOL_INFO

plt.rcParams.update({'font.size': 14})

LABEL_WORD_LIST_1 = 'Lista de palabras 1'
LABEL_WORD_LIST_2 = 'Lista de palabras 2'
LABEL_WORD_LIST_3 = 'Lista de palabras 3'
LABEL_WORD_LIST_4 = 'Lista de palabras 4'
LABEL_WORD_LIST_DIAGNOSE = 'Lista de palabras a diagnosticar'

word_vectors_path = 'fasttext-sbwc.100k.vec'
we = Embedding(word_vectors_path)
we.load_we_as_keyed_vectors(word_vectors_path)


we_bias_2d = WEBiasExplorer2d(we.wv)

explorar_relaciones_entre_palabras_interface = gr.Blocks()
with explorar_relaciones_entre_palabras_interface:
    gr.Markdown("Escribi algunas palabras para visualizar sus palabras relacionadas")
    with gr.Row():
        with gr.Column(scale=3):
            with gr.Row(equal_height=True):
                with gr.Column(scale=5):
                    diagnose_list = gr.Textbox(lines=2, label=LABEL_WORD_LIST_DIAGNOSE)
                with gr.Column(scale=1,min_width=10):
                    color_wordlist = gr.ColorPicker(label="",value='#000000',)
            with gr.Row():
                with gr.Column(scale=5): 
                    wordlist_1 = gr.Textbox(lines=2, label=LABEL_WORD_LIST_1)
                with gr.Column(scale=1,min_width=10): 
                    color_wordlist_1 = gr.ColorPicker(label="",value='#1f78b4')
            with gr.Row():
                with gr.Column(scale=5): 
                    wordlist_2 = gr.Textbox(lines=2, label=LABEL_WORD_LIST_2)
                with gr.Column(scale=1,min_width=10):     
                    color_wordlist_2 = gr.ColorPicker(label="",value='#33a02c')
            with gr.Row():
                with gr.Column(scale=5):    
                    wordlist_3 = gr.Textbox(lines=2, label=LABEL_WORD_LIST_3)
                with gr.Column(scale=1,min_width=10): 
                    color_wordlist_3 = gr.ColorPicker(label="",value='#e31a1c')
            with gr.Row():
                with gr.Column(scale=5):    
                    wordlist_4 = gr.Textbox(lines=2, label=LABEL_WORD_LIST_4)
                with gr.Column(scale=1,min_width=10): 
                    color_wordlist_4 = gr.ColorPicker(label="",value='#6a3d9a')
        with gr.Column(scale=4):
            with gr.Row():
                with gr.Row():
                    plot_neighbors = gr.Checkbox(label='Graficar palabras relacionadas')
                with gr.Row():
                    alpha = gr.Slider(minimum=0.1,maximum=0.9, value=0.3, step=0.1,label='Transparencia')
                with gr.Row():
                    fontsize=gr.Number(value=18, label='Tamaño de fuente')
                with gr.Row():
                    btn_plot = gr.Button('¡Graficar en el espacio!')
            with gr.Row(): 
                err_msg = gr.Markdown(label="", visible=True)
            with gr.Row():
                word_proyections = gr.Image(shape=(10, 10))

    with gr.Row():
        examples = gr.Examples(
            fn=we_bias_2d.plot_projections_2d,
            inputs=[diagnose_list,wordlist_1,wordlist_2,wordlist_3,wordlist_4],
            outputs=[word_proyections,err_msg],
            examples=examples_explorar_relaciones_entre_palabras
        )

    with gr.Row():
        gr.Markdown(TOOL_INFO)
    btn_plot.click(
    fn=we_bias_2d.plot_projections_2d,
    inputs=[
        diagnose_list,
        wordlist_1,
        wordlist_2,
        wordlist_3,
        wordlist_4,
        color_wordlist,
        color_wordlist_1,
        color_wordlist_2,
        color_wordlist_3,
        color_wordlist_4,
        plot_neighbors,
        alpha,
        fontsize
        ],
    outputs=[word_proyections,err_msg]
    )


explorar_relaciones_entre_palabras_interface.queue(concurrency_count=10)
explorar_relaciones_entre_palabras_interface.launch()