<commit_before>from __future__ import print_function
# -*- coding: utf-8 -*-

# Author: <NAME> <<EMAIL>>
#         (mostly translation, see implementation details)
# Licence: BSD 3 clause

import numpy as np
from scipy import linalg, optimize, rand

from ..base import BaseEstimator, RegressorMixin
from ..metrics.pairwise import manhattan_distances
from ..utils import array2d, check_random_state
from . import regression_models as regression
from . import correlation_models as correlation

MACHINE_EPSILON = np.finfo(np.double).eps
if hasattr(linalg, 'solve_triangular'):
    # only in scipy since 0.9
    solve_triangular = linalg.solve_triangular
else:
    # slower, but works
    def solve_triangular(x, y, lower=True):
        return linalg.solve(x, y)

<commit_msg>Move __future__ import after license text<commit_after># -*- coding: utf-8 -*-

# Author: <NAME> <<EMAIL>>
#         (mostly translation, see implementation details)
# Licence: BSD 3 clause

from __future__ import print_function

import numpy as np
from scipy import linalg, optimize, rand

from ..base import BaseEstimator, RegressorMixin
from ..metrics.pairwise import manhattan_distances
from ..utils import array2d, check_random_state
from . import regression_models as regression
from . import correlation_models as correlation

MACHINE_EPSILON = np.finfo(np.double).eps
if hasattr(linalg, 'solve_triangular'):
    # only in scipy since 0.9
    solve_triangular = linalg.solve_triangular
else:
    # slower, but works
    def solve_triangular(x, y, lower=True):
        return linalg.solve(x, y)


{'fraction_non_alphanumeric': 0.08634920634920636, 'fraction_numerical': 0.006349206349206349, 'mean_word_length': 4.342372881355932, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, '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': '7579694', 'n_tokens_mistral': 507, 'n_tokens_neox': 491, 'n_words': 156}