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"""Model settings.""" | ||
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model = dict( | ||
type="CascadeRCNN", | ||
# num_stages=3, | ||
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"""Default runtime config.""" | ||
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import pathlib | ||
import os | ||
import yaml | ||
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"""BaseComponent.""" | ||
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from abc import ABC, abstractmethod | ||
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"""BaseCurator.""" | ||
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import re | ||
from abc import abstractmethod | ||
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"""Curator.""" | ||
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import glob | ||
import logging | ||
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@@ -103,6 +103,7 @@ def clean(self, df): | |
Args: | ||
df (A pandas dataframe) | ||
""" | ||
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# map kpi to question | ||
def map_kpi(r): | ||
try: | ||
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"""Processing nq curator.""" | ||
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import logging | ||
import os | ||
from ast import literal_eval | ||
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"""NQExtractor.""" | ||
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import json | ||
import logging | ||
import os | ||
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"""PDFTextExtractor.""" | ||
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import glob | ||
import io | ||
import json | ||
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"""TextCurator.""" | ||
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import ast | ||
import json | ||
import logging | ||
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"""NQ utils.""" | ||
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import re | ||
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"""Data collection module.""" | ||
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from .s3_communication import S3FileType, S3Communication # noqa F401 |
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"""Data collection code.""" | ||
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import click | ||
import logging | ||
from pathlib import Path | ||
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"""S3 communication tools.""" | ||
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import os | ||
import pathlib | ||
import os.path as osp | ||
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"""FARM Trainer.""" | ||
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import logging | ||
import os | ||
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"""QA Farm trainer.""" | ||
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import logging | ||
import json | ||
import os | ||
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"""RelevanceInfer.""" | ||
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import json | ||
import logging | ||
import os | ||
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