<commit_before>"""
a simple general csv dataset wrapper for pylearn2 
can do automatic one-hot encoding based on labels present in a file
"""
__authors__ = "<NAME>"
__copyright__ = "Copyright 2013, <NAME>"
__credits__ = ["<NAME>"]
__license__ = "3-clause BSD"
__maintainer__ = "?"
__email__ = "<EMAIL>"

import csv
import numpy as np
import os

from pylearn2.datasets.dense_design_matrix import DenseDesignMatrix<commit_msg>UTF fix<commit_after>"""
a simple general csv dataset wrapper for pylearn2 
can do automatic one-hot encoding based on labels present in a file
"""
__authors__ = "<NAME>"
__copyright__ = "Copyright 2013, <NAME>"
__credits__ = ["<NAME>"]
__license__ = "3-clause BSD"
__maintainer__ = "?"
__email__ = "<EMAIL>"

import csv
import numpy as np
import os

from pylearn2.datasets.dense_design_matrix import DenseDesignMatrix
{'fraction_non_alphanumeric': 0.1021377672209026, 'fraction_numerical': 0.0166270783847981, 'mean_word_length': 5.798387096774194, 'pattern_counts': {'":': 0, '<': 11, '<?xml version=': 0, '>': 11, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '342221', 'n_tokens_mistral': 284, 'n_tokens_neox': 265, 'n_words': 94}