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<|fim_prefix|># repo: djfurman/serverless-suspense path: /serverless_suspense/base.py class ServerlessSuspense: def __init__(self): pass <|fim_suffix|> raise NotImplementedError("Must implement method to fetch status") def is_suspended(self): raise NotImplementedError("Must implement s...
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{ "lang": "python", "repo": "djfurman/serverless-suspense", "path": "/serverless_suspense/base.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> def validation_test(self): self.assertFalse(valid_iso8601("1547138099")) self.assertTrue(valid_iso8601("2019-01-10T16:34:59Z"))<|fim_prefix|># repo: crazyrex/conan path: /conans/test/unittests/client/util/time_test.py import datetime import unittest from conans.util.dates import from...
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{ "lang": "python", "repo": "crazyrex/conan", "path": "/conans/test/unittests/client/util/time_test.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: crazyrex/conan path: /conans/test/unittests/client/util/time_test.py import datetime import unittest from conans.util.dates import from_timestamp_to_iso8601, from_iso8601_to_datetime, valid_iso8601 class TimeTest(unittest.TestCase): def time_conversions_test(self): <|fim_suffix|> a...
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{ "lang": "python", "repo": "crazyrex/conan", "path": "/conans/test/unittests/client/util/time_test.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def get_encryption_info(self): return {'method': self._encryption_method} if self._encryption_method != 'no encryption' else {} def extract_cover_internal(self, working_dir): tmp_dir = mkdtemp(dir=working_dir) BookMobi(self.file).unpackMobi(tmp_dir + '/bookmobi') t...
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{ "lang": "python", "repo": "Aladex/sopds-fb2sax-sqlalchemy", "path": "/book_tools/format/mobi.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Aladex/sopds-fb2sax-sqlalchemy path: /book_tools/format/mobi.py import os, shutil from tempfile import mkdtemp from book_tools.pymobi.mobi import BookMobi from book_tools.format.bookfile import BookFile from book_tools.format.mimetype import Mimetype class Mobipocket(BookFile): def __init_...
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{ "lang": "python", "repo": "Aladex/sopds-fb2sax-sqlalchemy", "path": "/book_tools/format/mobi.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>ge="preds", summarize=10) # Add these preds to the inputs decoder_inputs = tf.concat([decoder_inputs, preds], axis=1) decoder_outputs = tf.concat([decoder_outputs, output], axis=1) i = tf.add(i, 1) return i, decoder_inputs, decoder_outputs<|fim_prefix|># repo: fenshion/instacorrect path: /Model/test.py #...
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{ "lang": "python", "repo": "fenshion/instacorrect", "path": "/Model/test.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: fenshion/instacorrect path: /Model/test.py # Embed the characters decoder_inputs = tf.Print(decoder_inputs, [decoder_inputs], message="decoder_inputs") decoder_outputs = tf.Print(decoder_outputs, [decoder_outputs], message="decoder_outputs") inputs = tf.nn.embedding_lookup(embeddin<|fim_suffix|>e...
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{ "lang": "python", "repo": "fenshion/instacorrect", "path": "/Model/test.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: brianchiang-tw/Code-wars path: /Human Readable Time/human_readable_time.py ''' Description: Write a function, which takes a non-negative integer (seconds) as input and returns the time in a human-readable format (HH:MM:SS) HH = hours, padded to 2 digits, range: 00 - 99 MM = minutes, padded to ...
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{ "lang": "python", "repo": "brianchiang-tw/Code-wars", "path": "/Human Readable Time/human_readable_time.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> # formatted output as specified in description return f'{h:02}:{m:02}:{s:02}' def test_bench(): test_data = [ 5, 61, 121, 3599, 3601, 7201] # expected output: ''' 00:00:05 00:01:01 00:02:01 00:59:59 01:00:01 02:00:01 ''' for second_string in test_...
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{ "lang": "python", "repo": "brianchiang-tw/Code-wars", "path": "/Human Readable Time/human_readable_time.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: eyadgaran/SimpleML path: /simpleml/save_patterns/locations/__init__.py """ Persistence Locations These are the primary classes responsible for tra<|fim_suffix|>thon objects into the system temp folder first and then call a location transporter to copy to the final storage place """ __author__ =...
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{ "lang": "python", "repo": "eyadgaran/SimpleML", "path": "/simpleml/save_patterns/locations/__init__.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|>thon objects into the system temp folder first and then call a location transporter to copy to the final storage place """ __author__ = "Elisha Yadgaran"<|fim_prefix|># repo: eyadgaran/SimpleML path: /simpleml/save_patterns/locations/__init__.py """ Persistence Locations These are the primary classes r...
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{ "lang": "python", "repo": "eyadgaran/SimpleML", "path": "/simpleml/save_patterns/locations/__init__.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: epigos/AutoML_Alex path: /automl_alex/automl_alex.py gpu=self._gpu, random_state=self._random_state, type_of_estimator=self.type_of_estimator ) return(model) def _opt_model(self, trial): ''' now we can choose models in optimizat...
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{ "lang": "python", "repo": "epigos/AutoML_Alex", "path": "/automl_alex/automl_alex.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: epigos/AutoML_Alex path: /automl_alex/automl_alex.py e_opt=self._combined_score_opt, metric_round=self._metric_round, model_param=model_param, wrapper_params=wrapper_params, gpu=self._gpu, random_state=self._random_state, t...
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{ "lang": "python", "repo": "epigos/AutoML_Alex", "path": "/automl_alex/automl_alex.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> class StackingClassifier(Stacking): type_of_estimator='classifier' __name__ = 'StackingClassifier' class StackingRegressor(Stacking): type_of_estimator='regression' __name__ = 'StackingRegressor' ##################################### AutoML ######################################### ...
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{ "lang": "python", "repo": "epigos/AutoML_Alex", "path": "/automl_alex/automl_alex.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|># format list of events print(f"{len(events)} matching events") for event in events: props = event.properties time = props.time.date().isoformat() print(f"{time} - M{props.mag:.1f} {props.place}")<|fim_prefix|># repo: jmfee-usgs/python-typing-pydantic-oop path: /examples/using_pydantic/exampl...
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{ "lang": "python", "repo": "jmfee-usgs/python-typing-pydantic-oop", "path": "/examples/using_pydantic/example.py", "mode": "spm", "license": "LicenseRef-scancode-warranty-disclaimer", "source": "the-stack-v2" }
<|fim_prefix|># repo: jmfee-usgs/python-typing-pydantic-oop path: /examples/using_pydantic/example.py from dateutil.parser import isoparse from .get_catalog import get_catalog <|fim_suffix|># format list of events print(f"{len(events)} matching events") for event in events: props = event.properties time = p...
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{ "lang": "python", "repo": "jmfee-usgs/python-typing-pydantic-oop", "path": "/examples/using_pydantic/example.py", "mode": "psm", "license": "LicenseRef-scancode-warranty-disclaimer", "source": "the-stack-v2" }
<|fim_suffix|>x1 = ParticleA.pCM.dot(N.x) y1 = ParticleA.pCM.dot(N.y) KE = system.KE PE = system.getPEGravity(pNA)-system.getPESprings() pynamics.tic() print('solving dynamics...') f,ma = system.getdynamics() print('creating second order function...') func1 = system.state_space_post_invert(f,ma) print('integrating...
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{ "lang": "python", "repo": "rkhodambashi/code_pynamics", "path": "/python/pynamics/examples/single_dof_bouncer.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: rkhodambashi/code_pynamics path: /python/pynamics/examples/single_dof_bouncer.py # -*- coding: utf-8 -*- """ Written by Daniel M. Aukes Email: danaukes<at>gmail.com Please see LICENSE for full license. """ import pynamics from pynamics.frame import Frame from pynamics.variable_types import Diff...
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{ "lang": "python", "repo": "rkhodambashi/code_pynamics", "path": "/python/pynamics/examples/single_dof_bouncer.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>initialvalues = {} initialvalues[x]=0 initialvalues[x_d]=.1 initialvalues[y]=.1 initialvalues[y_d]=0 statevariables = system.get_q(0)+system.get_q(1) ini = [initialvalues[item] for item in statevariables] N = Frame('N') system.set_newtonian(N) pNA=0*N.x pAcm=pNA+x*N.x+y*N.y vAcm = pAcm.time_derivativ...
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{ "lang": "python", "repo": "rkhodambashi/code_pynamics", "path": "/python/pynamics/examples/single_dof_bouncer.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: mingxiaoh/chainercv path: /chainercv/utils/testing/generate_random_bbox.py import numpy as np def generate_random_bbox(n, img_size, min_length, max_length): """Generate valid bounding boxes with random position and shape. Args: n (int): The number of bounding boxes. img...
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{ "lang": "python", "repo": "mingxiaoh/chainercv", "path": "/chainercv/utils/testing/generate_random_bbox.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """ H, W = img_size y_min = np.random.uniform(0, H - max_length, size=(n,)) x_min = np.random.uniform(0, W - max_length, size=(n,)) y_max = y_min + np.random.uniform(min_length, max_length, size=(n,)) x_max = x_min + np.random.uniform(min_length, max_length, size=(n,)) bbox = n...
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{ "lang": "python", "repo": "mingxiaoh/chainercv", "path": "/chainercv/utils/testing/generate_random_bbox.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>ose_name='Title', blank=True), ), migrations.AddField( model_name='homepage', name='photo_album', field=models.ForeignKey(related_name='+', on_delete=django.db.models.deletion.PROTECT, blank=True, to='album.Album', null=True), ), migratio...
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{ "lang": "python", "repo": "PARINetwork/pari", "path": "/core/migrations/0012_auto_20170417_1303.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: PARINetwork/pari path: /core/migrations/0012_auto_20170417_1303.py # -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion import wagtail.images.models import wagtail.core.fields import wagtail.core.blocks class ...
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{ "lang": "python", "repo": "PARINetwork/pari", "path": "/core/migrations/0012_auto_20170417_1303.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> @click.command() @add_common_options(COMMON_GEN_FEATURE_OPTIONS) def generate_feature(dataset_path, output_path, num_threads): """Extract the feature of the whole dataset for training.""" settings = BeatSettings() if output_path is not None: settings.dataset.feature_save_path = outpu...
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{ "lang": "python", "repo": "Music-and-Culture-Technology-Lab/omnizart", "path": "/omnizart/cli/beat/generate_feature.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Music-and-Culture-Technology-Lab/omnizart path: /omnizart/cli/beat/generate_feature.py import click from omnizart.cli.common_options import add_common_options, COMMON_GEN_FEATURE_OPTIONS from omnizart.setting_loaders import BeatSettings from omnizart.utils import LazyLoader <|fim_suffix|> if...
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{ "lang": "python", "repo": "Music-and-Culture-Technology-Lab/omnizart", "path": "/omnizart/cli/beat/generate_feature.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """Extract the feature of the whole dataset for training.""" settings = BeatSettings() if output_path is not None: settings.dataset.feature_save_path = output_path beat.app.generate_feature(dataset_path, beat_settings=settings, num_threads=num_threads)<|fim_prefix|># repo: Music-...
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{ "lang": "python", "repo": "Music-and-Culture-Technology-Lab/omnizart", "path": "/omnizart/cli/beat/generate_feature.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> <warning descr="'abc.abstractproperty' is deprecated since Python 3.3. Use 'property' with 'abc.abstractmethod' instead">@ap</warning> def prop(self): pass import abc as foo class D(metaclass=abc.ABCMeta): <warning descr="'abc.abstractproperty' is deprecated since Python 3.3. Use '...
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{ "lang": "python", "repo": "JetBrains/intellij-community", "path": "/python/testData/deprecation/abcDeprecatedAbstracts.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: JetBrains/intellij-community path: /python/testData/deprecation/abcDeprecatedAbstracts.py import abc class A(metaclass=abc.ABCMeta): <warning descr="'abc.abstractproperty' is deprecated since Python 3.3. Use 'property' with 'abc.abstractmethod' instead">@abc.abstractproperty</warning> d...
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{ "lang": "python", "repo": "JetBrains/intellij-community", "path": "/python/testData/deprecation/abcDeprecatedAbstracts.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def getById(self, id_goals): """ Get Goals Object By it id :param id_goals: id of Goals Object :return: Goals Object """ lparam = [id_goals] rep = AbstractDAO._read(self, R_READBYID, lparam) return self.__fetch_to_object(rep, True) d...
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{ "lang": "python", "repo": "ChatNoir76/Championnat", "path": "/model/dao/sqlite/dao_goals.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: ChatNoir76/Championnat path: /model/dao/sqlite/dao_goals.py from model.dao.abstractdao import AbstractDAO from model.dao.daoexception import DAOException from model.goals import Goals R_INSERT = """ INSERT INTO But VALUES (null, ?, ?, ?, ?, ?)""" R_UPDATE = """ UPDATE But SET commentaire_b...
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{ "lang": "python", "repo": "ChatNoir76/Championnat", "path": "/model/dao/sqlite/dao_goals.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: jdvala/pipgrip path: /tests/test_pipper.py import os import subprocess import pytest import pipgrip.pipper from pipgrip.pipper import _download_wheel, _get_available_versions @pytest.mark.parametrize( "package, pip_output, expected", [ ( ".[all]", """ ...
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{ "lang": "python", "repo": "jdvala/pipgrip", "path": "/tests/test_pipper.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> monkeypatch.setattr( pipgrip.pipper.os, "walk", patch_os_walk, ) monkeypatch.setattr( pipgrip.pipper.os.path, "getmtime", patch_getmtime, ) monkeypatch.setattr( pipgrip.pipper, "stream_bash_command", patch_pip_output, ) assert _download_wheel( p...
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{ "lang": "python", "repo": "jdvala/pipgrip", "path": "/tests/test_pipper.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> NL = NormalizedLevenshtein() vectors = pd.DataFrame([[NL.distance(i, j) for j in arr2] for i in arr1]) clusters = 5 agg = AgglomerativeClustering(affinity='euclidean', compute_full_tree='auto', connectivity=None, linkage='ward', memory=None, n_clusters=clusters, pooling_func='deprec...
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{ "lang": "python", "repo": "lucky7-capstone/Lucky7-Capstone", "path": "/ML/Agglomerative.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> for i in range(clusters): print("Cluster " + str(i) + ":") print(pd.Series(arr1[agg.labels_==i])) print('\n') if __name__ == "__main__": main()<|fim_prefix|># repo: lucky7-capstone/Lucky7-Capstone path: /ML/Agglomerative.py import sys import numpy as np import pandas as pd from si...
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{ "lang": "python", "repo": "lucky7-capstone/Lucky7-Capstone", "path": "/ML/Agglomerative.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: lucky7-capstone/Lucky7-Capstone path: /ML/Agglomerative.py import sys import numpy as np import pandas as pd from similarity.normalized_levenshtein import NormalizedLevenshtein from sklearn.cluster import AgglomerativeClustering from sklearn.cluster import KMeans def main(): <|fim_suffix|> df =...
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{ "lang": "python", "repo": "lucky7-capstone/Lucky7-Capstone", "path": "/ML/Agglomerative.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: warppoint42/Mahjong221 path: /stats.py import csv stats = dict() with open('unifiedroundlog.csv', 'r') as csvfile: reader = csv.DictReader(csvfile, ('AI', 'gameID', 'end', 'win', 'feed', 'riichi')) for row in reader: if row['AI'] not in stats: stats[row['AI']] = dict...
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{ "lang": "python", "repo": "warppoint42/Mahjong221", "path": "/stats.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> for row in reader: stats[row['AI']].setdefault('1', 0) stats[row['AI']].setdefault('2', 0) stats[row['AI']].setdefault('3', 0) stats[row['AI']].setdefault('4', 0) stats[row['AI']].setdefault('totp', 0) stats[row['AI']].setdefault('totn', 0) stats...
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{ "lang": "python", "repo": "warppoint42/Mahjong221", "path": "/stats.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: kucars/semantic_victim_localization path: /script/victim_detection_using_ssd_keras.py #! /usr/bin/python import rospy import std_msgs.msg import cv2 import keras import tensorflow as tf from keras.applications.imagenet_utils import preprocess_input from keras.backend.tensorflow_backend import se...
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{ "lang": "python", "repo": "kucars/semantic_victim_localization", "path": "/script/victim_detection_using_ssd_keras.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> top_conf = det_conf[top_indices] top_label_indices = det_label[top_indices].tolist() top_xmin = det_xmin[top_indices] top_ymin = det_ymin[top_indices] top_xmax = det_xmax[top_indices] top_ymax = det_ymax[top_indices] p...
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{ "lang": "python", "repo": "kucars/semantic_victim_localization", "path": "/script/victim_detection_using_ssd_keras.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> top_label_indices = det_label[top_indices].tolist() top_xmin = det_xmin[top_indices] top_ymin = det_ymin[top_indices] top_xmax = det_xmax[top_indices] top_ymax = det_ymax[top_indices] print(conf) for i in range(top_conf....
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{ "lang": "python", "repo": "kucars/semantic_victim_localization", "path": "/script/victim_detection_using_ssd_keras.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> if addl_env_vars is not None: addl_env_vars.update(dict(os.environ)) for command in tools.get(args.tool).get("commands"): # run all commands required to install the tool # print each command being run self.async_aler...
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{ "lang": "python", "repo": "hellor00t/recon-pipeline", "path": "/recon-pipeline.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: hellor00t/recon-pipeline path: /recon-pipeline.py #!/usr/bin/env python # stdlib imports import os import sys import shlex import pickle import selectors import threading import subprocess import webbrowser from pathlib import Path # fix up the PYTHONPATH so we can simply execute the shell from ...
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{ "lang": "python", "repo": "hellor00t/recon-pipeline", "path": "/recon-pipeline.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def _to_ranks_by_group(dat, group, formula, exclude_cols=[]): """ Covert predictors to ranks separately for each group for use in rank Lmer. Any columns not in the model formula or in exclude_cols will not be converted to ranks. Used by models.Lmer Args: dat (pd.DataFrame): dataframe...
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{ "lang": "python", "repo": "turbach/pymer4", "path": "/pymer4/utils.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: turbach/pymer4 path: /pymer4/utils.py # Degrees of freedom adjustment to HC0 V = V * X.shape[0] / (X.shape[0] - X.shape[1]) elif robust_estimator == "hc2": # Rather than dof correction, weight residuals by reciprocal of "leverage values" in the hat-matrix ...
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{ "lang": "python", "repo": "turbach/pymer4", "path": "/pymer4/utils.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> return columns, index def pandas2R(df): """Local conversion of pandas dataframe to R dataframe as recommended by rpy2""" with localconverter(robjects.default_converter + pandas2ri.converter): data = robjects.conversion.py2rpy(df) return data def result_to_table( model, ...
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{ "lang": "python", "repo": "turbach/pymer4", "path": "/pymer4/utils.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> async_describe_event( DOMAIN, EVENT_AUTOMATION_TRIGGERED, async_describe_logbook_event )<|fim_prefix|># repo: tchellomello/home-assistant path: /homeassistant/components/automation/logbook.py """Describe logbook events.""" from homeassistant.const import ATTR_ENTITY_ID, ATTR_NAME from hom...
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{ "lang": "python", "repo": "tchellomello/home-assistant", "path": "/homeassistant/components/automation/logbook.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: tchellomello/home-assistant path: /homeassistant/components/automation/logbook.py """Describe logbook events.""" from homeassistant.const import ATTR_ENTITY_ID, ATTR_NAME from homeassistant.core import callback <|fim_suffix|> @callback def async_describe_logbook_event(event): # type: ign...
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{ "lang": "python", "repo": "tchellomello/home-assistant", "path": "/homeassistant/components/automation/logbook.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: Kriztoper/deep-koalarization path: /colorization/training_utils.py import pickle import time from os.path import join import matplotlib import numpy as np import cv2 from skimage import color from PIL import Image, ImageChops import tensorboard from tensorboard import summary as summary_lib fr...
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{ "lang": "python", "repo": "Kriztoper/deep-koalarization", "path": "/colorization/training_utils.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>def image_colorfulness(image): # split the image into its respective RGB components (B, G, R) = cv2.split(image.astype("float")) # compute rg = R - G rg = np.absolute(R - G) # compute yb = 0.5 * (R + G) - B yb = np.absolute(0.5 * (R + G) - B) # compute the mean and standard ...
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{ "lang": "python", "repo": "Kriztoper/deep-koalarization", "path": "/colorization/training_utils.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: rpranav22/Chatbot_Flask path: /TestCode.py # Code that can be used for custom payload quick replies response = {} response["payload"] = { "google": { "expectUserResponse": "true", "richResponse": { "items": [ ...
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{ "lang": "python", "repo": "rpranav22/Chatbot_Flask", "path": "/TestCode.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|># Using card in fulfillmentMessages card = { "card": { "title": "card title", "subtitle": "card text", "imageUri": "https://assistant.google.com/static/images/molecule/Molecule-Formation-stop.png", "buttons": [...
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{ "lang": "python", "repo": "rpranav22/Chatbot_Flask", "path": "/TestCode.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>UPLOAD_FOLDER = IMAGES_DIR SECRET_KEY = os.environ.get("SECRET_KEY", "dev")<|fim_prefix|># repo: prajwalcr/AutoCompose path: /src/config.py from dotenv import load_dotenv import os load_dotenv(".env") <|fim_middle|>IMAGES_DIR = os.path.join('../static', 'images')
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{ "lang": "python", "repo": "prajwalcr/AutoCompose", "path": "/src/config.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: prajwalcr/AutoCompose path: /src/config.py from dotenv import load_dotenv import os load_dotenv(".env") <|fim_suffix|>UPLOAD_FOLDER = IMAGES_DIR SECRET_KEY = os.environ.get("SECRET_KEY", "dev")<|fim_middle|>IMAGES_DIR = os.path.join('../static', 'images')
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{ "lang": "python", "repo": "prajwalcr/AutoCompose", "path": "/src/config.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>IMAGES_DIR = os.path.join('../static', 'images') UPLOAD_FOLDER = IMAGES_DIR SECRET_KEY = os.environ.get("SECRET_KEY", "dev")<|fim_prefix|># repo: prajwalcr/AutoCompose path: /src/config.py from dotenv import load_dotenv import os <|fim_middle|>load_dotenv(".env")
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{ "lang": "python", "repo": "prajwalcr/AutoCompose", "path": "/src/config.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> for key in self.pre_conf_dict.keys(): if self.pre_conf_dict[key][0] == 'tenant': for tenant in self.post_conf_dict.keys(): if len(tenant) == 32: for vm in self.post_conf_dict[tenant]: index = self._...
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{ "lang": "python", "repo": "abochkarev/CloudFerry", "path": "/devlab/tests/test_group_verification.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: abochkarev/CloudFerry path: /devlab/tests/test_group_verification.py # Copyright (c) 2015 Mirantis Inc. # # Licensed under the Apache License, Version 2.0 (the License); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apa...
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{ "lang": "python", "repo": "abochkarev/CloudFerry", "path": "/devlab/tests/test_group_verification.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def network_verification_scenario(self, verify_vm_state=False): neutron = self.src_cloud.neutronclient for key in self.pre_conf_dict.keys(): if self.pre_conf_dict[key][0] == 'network': user_defined_groups_list = self.pre_conf_dict.keys() for ...
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{ "lang": "python", "repo": "abochkarev/CloudFerry", "path": "/devlab/tests/test_group_verification.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def _set_client(self, client): self.client = client def onConnect(self, *args, **kw): d = self.factory.store.create_client(self.on_publish) return d.addCallback(self._set_client) def onClose(self, wasClea, code, reason): if self.client is not None: ...
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{ "lang": "python", "repo": "praekelt/echidna", "path": "/echidna/server.py", "mode": "spm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: praekelt/echidna path: /echidna/server.py """hedley marker""" import json import datetime from twisted.web.resource import Resource from twisted.web import server from twisted.internet import defer, reactor from twisted.python import log from autobahn.twisted.websocket import (WebSocketServerFa...
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{ "lang": "python", "repo": "praekelt/echidna", "path": "/echidna/server.py", "mode": "psm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_suffix|> class SubscriptionProtocol(WebSocketServerProtocol): def __init__(self): # WebSocketServerProtocol.__init__(self) self.client = None def _set_client(self, client): self.client = client def onConnect(self, *args, **kw): d = self.factory.store.create_client(se...
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{ "lang": "python", "repo": "praekelt/echidna", "path": "/echidna/server.py", "mode": "spm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_suffix|> self.c += 1 return tuple_[0] + self.v, @spl.map() class M2(object): def __init__(self, v): self.c = 0 self.v = v def __call__(self, *tuple_): self.c += 1 return tuple_[0] + self.v, def __getstate__(self): return {'c': ...
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{ "lang": "python", "repo": "IBMStreams/streamsx.topology", "path": "/test/python/spl/tests/ops_dill.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: IBMStreams/streamsx.topology path: /test/python/spl/tests/ops_dill.py # coding=utf-8 # Licensed Materials - Property of IBM # Copyright IBM Corp. 2018 from streamsx.spl import spl @spl.filter() class F1(object): def __init__(self, v): self.c = 0 self.v = v def __call__(s...
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{ "lang": "python", "repo": "IBMStreams/streamsx.topology", "path": "/test/python/spl/tests/ops_dill.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> """Inverse check; succeeds only if the given check fails. """ def __init__(self, name, check, with_error=None): Service.__init__(self, name) self._check = check self._with_error = set() for error in with_error: if isinstance(error, basestring): ...
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{ "lang": "python", "repo": "pombredanne/timyd", "path": "/timyd/checks/utils.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: pombredanne/timyd path: /timyd/checks/utils.py from timyd import Service, CheckFailure class InvertedCheckPassed(CheckFailure): pass class InvertedCheckUnexpectedError(CheckFailure): def __init__(self, error): self._error = error def __str__(self): return str(self...
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{ "lang": "python", "repo": "pombredanne/timyd", "path": "/timyd/checks/utils.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> Service.__init__(self, name) self._check = check self._with_error = set() for error in with_error: if isinstance(error, basestring): self._with_error.add(error) elif isinstance(error, type) and issubclass(error, Exception): ...
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{ "lang": "python", "repo": "pombredanne/timyd", "path": "/timyd/checks/utils.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: gusibi/py-realtime-sdk path: /realtime/bind.py #! -*- coding: utf-8 -*- import re import hmac import six from six.moves.urllib.parse import quote from .oauth2 import OAuth2Request from .json_import import json re_path_template = re.compile('{\w+}') def encode_string(value): return valu...
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{ "lang": "python", "repo": "gusibi/py-realtime-sdk", "path": "/realtime/bind.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> self.api = api self.return_json = kwargs.pop('return_json', True) self.parameters = {} self._build_parameters(args, kwargs) self._build_path() def _build_parameters(self, args, kwargs): for index, value in enumerate(args): ...
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{ "lang": "python", "repo": "gusibi/py-realtime-sdk", "path": "/realtime/bind.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: dcragusa/LeetCode path: /100-199/140-149/145.py """ Given the root of a binary tree, return the postorder traversal of its nodes' values. Example 1: Input: root = [1, None, 2, 3], Output: [3, 2, 1] 1 \ 2 / 3 Example 2: Input: root = [], Output: [] Example 3: Input: root = [...
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{ "lang": "python", "repo": "dcragusa/LeetCode", "path": "/100-199/140-149/145.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> assert postorder_traversal(list_to_tree([1, None, 2, 3])) == [3, 2, 1] assert postorder_traversal(list_to_tree([])) == [] assert postorder_traversal(list_to_tree([1])) == [1] assert postorder_traversal(list_to_tree([1, 2])) == [2, 1] assert postorder_traversal(list_to_tree([1, None, 2])) == [2, 1]<|fim_p...
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{ "lang": "python", "repo": "dcragusa/LeetCode", "path": "/100-199/140-149/145.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> helper(root) return results assert postorder_traversal(list_to_tree([1, None, 2, 3])) == [3, 2, 1] assert postorder_traversal(list_to_tree([])) == [] assert postorder_traversal(list_to_tree([1])) == [1] assert postorder_traversal(list_to_tree([1, 2])) == [2, 1] assert postorder_traversal(list_to...
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{ "lang": "python", "repo": "dcragusa/LeetCode", "path": "/100-199/140-149/145.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> return self.name class Interview(models.Model): """ Model for uploading interviews with experts or students. The interview model only has fields for interviewee, date, and interviewer. Responses are stored in the Excerpt model which has a many-to-one relationship with the Inte...
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{ "lang": "python", "repo": "kevincwebb/conceptum", "path": "/conceptum/interviews/models.py", "mode": "spm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_suffix|> response = models.TextField() #Concept Tag (doesn't exist, entered by interviewer) + #Text Justification(response) + ability level ranking + importance ranking + #Interviewee + topic tag (can be multiple) class ConceptExcerpt(models.Model): interview = models.ForeignKey(Interview) re...
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{ "lang": "python", "repo": "kevincwebb/conceptum", "path": "/conceptum/interviews/models.py", "mode": "spm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: kevincwebb/conceptum path: /conceptum/interviews/models.py from django.conf import settings from django.db import models from django.contrib.contenttypes.models import ContentType from django.contrib.contenttypes import generic from django.core.urlresolvers import reverse class DummyConcept(mode...
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{ "lang": "python", "repo": "kevincwebb/conceptum", "path": "/conceptum/interviews/models.py", "mode": "psm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_suffix|> return self.score.difference @property def score_ratio(self) -> float: return self.score.ratio def __eq__(self, other: object) -> bool: if not isinstance(other, StandingsEntry): return False if self.points != other.points: ret...
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{ "lang": "python", "repo": "Jardo72/AWS-Sandbox", "path": "/S3-Notifications-Lambda/model.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: Jardo72/AWS-Sandbox path: /S3-Notifications-Lambda/model.py # # Copyright 2021 Jaroslav Chmurny # # This file is part of AWS Sandbox. # # AWS Sandbox is free software developed for educational purposes. It # is licensed under the Apache License, Version 2.0 (the "License"); # you may not u...
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{ "lang": "python", "repo": "Jardo72/AWS-Sandbox", "path": "/S3-Notifications-Lambda/model.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> @property def score_ratio(self) -> float: return self.score.ratio def __eq__(self, other: object) -> bool: if not isinstance(other, StandingsEntry): return False if self.points != other.points: return False if self.score_differe...
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{ "lang": "python", "repo": "Jardo72/AWS-Sandbox", "path": "/S3-Notifications-Lambda/model.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> return self._ssh_quiet(self.rsync_to_command(flags, src_dir, dest_dir)) def create_file(self, path, contents): tmp = tempfile.NamedTemporaryFile(delete=False) local_name = tmp.name tmp.write(contents) tmp.close() self.scp_to(local_name, path) os...
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{ "lang": "python", "repo": "xvrl/ducktape", "path": "/ducktape/cluster/remoteaccount.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> """Check if output is available and possibly wait until the availability is known. 1) If there is output available, return true 2) If there is no output available (i.e. EOF), return false 3) If it is unknown whether output is available - If timeout_sec is not spe...
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{ "lang": "python", "repo": "xvrl/ducktape", "path": "/ducktape/cluster/remoteaccount.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: xvrl/ducktape path: /ducktape/cluster/remoteaccount.py # Copyright 2014 Confluent Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/license...
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{ "lang": "python", "repo": "xvrl/ducktape", "path": "/ducktape/cluster/remoteaccount.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> # promethues metrics global rateReq global rateLat global e2eRateLat # update req counter rateReq.inc() # parse request data = json.loads(request.text()) video_id = data['video'] user_id = data['user'] comment = data['comment'] score = data['score'] send...
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{ "lang": "python", "repo": "delimitrou/DeathStarBench", "path": "/daprApps_v1/video-sharing/video-frontend/server.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: delimitrou/DeathStarBench path: /daprApps_v1/video-sharing/video-frontend/server.py buckets=pyutil.latBuckets() ) rateLat = prometheus_client.Histogram( 'video_frontend_rate_lat_hist', 'Latency (ms) histogram of video-frontend rate requests', buckets=pyutil.latBuckets() ) getRateLat ...
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{ "lang": "python", "repo": "delimitrou/DeathStarBench", "path": "/daprApps_v1/video-sharing/video-frontend/server.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: delimitrou/DeathStarBench path: /daprApps_v1/video-sharing/video-frontend/server.py str(util_path)) import pyutil warnings.filterwarnings("ignore") # global variables serviceAddress = int(os.getenv('ADDRESS', '5005')) promAddress = int(os.getenv('PROM_ADDRESS', '8084')) videoPubsub = os.ge...
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{ "lang": "python", "repo": "delimitrou/DeathStarBench", "path": "/daprApps_v1/video-sharing/video-frontend/server.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: linkml/schema-automator path: /schema_automator/generalizers/generalizer.py from abc import ABC from collections.abc import Collection, Set from dataclasses import dataclass, field from typing import List import inflect from linkml_runtime.linkml_model import SchemaDefinition, Prefix DEFAULT_CL...
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{ "lang": "python", "repo": "linkml/schema-automator", "path": "/schema_automator/generalizers/generalizer.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> def add_additional_info(self, schema: SchemaDefinition) -> None: for s in self.identifier_slots: schema.slots[s].identifier = True<|fim_prefix|># repo: linkml/schema-automator path: /schema_automator/generalizers/generalizer.py from abc import ABC from collections.abc import Colle...
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{ "lang": "python", "repo": "linkml/schema-automator", "path": "/schema_automator/generalizers/generalizer.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: dquail/GVFMinecraft path: /python/CreateModel.py from builtins import range import MalmoPython import os import sys import time import numpy as np import json import pickle import cv2 from PIL import ImageTk from PIL import Image from constants import * from simpleMission import * if sys.versio...
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{ "lang": "python", "repo": "dquail/GVFMinecraft", "path": "/python/CreateModel.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def updateStateDictionaryWithState(self, state): print("Creating grid object from state.") #Get the object from dictionary for given x,y if state.number_of_observations_since_last_state > 0: for observation in state.observations: msg = observation.text obs = json.loads...
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{ "lang": "python", "repo": "dquail/GVFMinecraft", "path": "/python/CreateModel.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: ltiao/bore-experiments path: /bin/drivers/sequential/run_tpe.py import sys import click import yaml from hyperopt import fmin, tpe, STATUS_OK, Trials from pathlib import Path from bore_experiments.benchmarks import make_benchmark from bore_experiments.utils import make_name, HyperOptLogs @cli...
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{ "lang": "python", "repo": "ltiao/bore-experiments", "path": "/bin/drivers/sequential/run_tpe.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> trials = Trials() best = fmin(objective, space=space, algo=tpe.suggest, max_evals=num_iterations, trials=trials) data = HyperOptLogs(trials).to_frame() data.to_csv(output_path.joinpath(f"{run_i...
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{ "lang": "python", "repo": "ltiao/bore-experiments", "path": "/bin/drivers/sequential/run_tpe.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """ Simple decorator to show whether or not a user is a valid member of Online. """ def check_membership(request, *args, **kwargs): if request.user.is_member: return view_func(request, *args, **kwargs) # Raise 403 error if user does not have access ...
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{ "lang": "python", "repo": "frecar/onlineweb4", "path": "/apps/authentication/decorators.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: frecar/onlineweb4 path: /apps/authentication/decorators.py # -*- coding: utf-8 -*- from middleware.http import Http403 <|fim_suffix|> """ Simple decorator to show whether or not a user is a valid member of Online. """ def check_membership(request, *args, **kwargs): i...
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{ "lang": "python", "repo": "frecar/onlineweb4", "path": "/apps/authentication/decorators.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> self.name = "WASHTUBS" self.definitions = washtub self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.basic = ['washtub']<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/otherforms/_washtubs.py #calss header class _WASHTUBS(): <|fim_middle|> def...
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{ "lang": "python", "repo": "cash2one/xai", "path": "/xai/brain/wordbase/otherforms/_washtubs.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/otherforms/_washtubs.py #calss header class _WASHTUBS(): <|fim_suffix|> self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.basic = ['washtub']<|fim_middle|> def __init__(self,): self.name = "WASHTUBS" self.defi...
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{ "lang": "python", "repo": "cash2one/xai", "path": "/xai/brain/wordbase/otherforms/_washtubs.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>mple.midi", tempo=100, beats_per_chord=2, instrument=4)) prog.to_pdf(filename="example.pdf")<|fim_prefix|># repo: jonathangjertsen/jchord path: /examples/basic.py # fmt: off from jchord import ChordProgression, MidiConversionSettings prog = ChordProgression.from_string("C -- Fm7 -- C -- G7 -- C -- E...
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{ "lang": "python", "repo": "jonathangjertsen/jchord", "path": "/examples/basic.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>og.transpose(+2) print(prog.to_string()) prog.to_midi(MidiConversionSettings(filename="example.midi", tempo=100, beats_per_chord=2, instrument=4)) prog.to_pdf(filename="example.pdf")<|fim_prefix|># repo: jonathangjertsen/jchord path: /examples/basic.py # fmt: off from jchord import ChordProgression, ...
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{ "lang": "python", "repo": "jonathangjertsen/jchord", "path": "/examples/basic.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: jonathangjertsen/jchord path: /examples/basic.py # fmt: off from jchord import ChordProgression, MidiConversionSettings prog = ChordProgr<|fim_suffix|>mple.midi", tempo=100, beats_per_chord=2, instrument=4)) prog.to_pdf(filename="example.pdf")<|fim_middle|>ession.from_string("C -- Fm7 -- C -...
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{ "lang": "python", "repo": "jonathangjertsen/jchord", "path": "/examples/basic.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> user = dao_get_user_by_id(user_id) return jsonify(user.serialize()), 200 @user_blueprint.errorhandler(IntegrityError) def handle_integrity_error(exc): """ Handle integrity errors caused by the unique constraint on users_email_key """ if 'users_email_key' in str(exc): ret...
code_fim
hard
{ "lang": "python", "repo": "NewAcropolis/api", "path": "/app/routes/users/rest.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: NewAcropolis/api path: /app/routes/users/rest.py import werkzeug werkzeug.cached_property = werkzeug.utils.cached_property from flask import ( Blueprint, current_app, jsonify, request ) from flask_jwt_extended import jwt_required from sqlalchemy.exc import IntegrityError from ap...
code_fim
hard
{ "lang": "python", "repo": "NewAcropolis/api", "path": "/app/routes/users/rest.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: liaoweixia/SimpleChinese2 path: /simplechinese/__init__.py from . import preprocessing from .preprocessing import * <|fim_suffix|># from . import synonyms # from .synonyms import * __version__ = "0.2.11"<|fim_middle|>from . import representation from .representation import * from . import visu...
code_fim
hard
{ "lang": "python", "repo": "liaoweixia/SimpleChinese2", "path": "/simplechinese/__init__.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>from . import conversion from .conversion import * from . import pinyin from .pinyin import * # from . import synonyms # from .synonyms import * __version__ = "0.2.11"<|fim_prefix|># repo: liaoweixia/SimpleChinese2 path: /simplechinese/__init__.py from . import preprocessing from .preprocessing import...
code_fim
easy
{ "lang": "python", "repo": "liaoweixia/SimpleChinese2", "path": "/simplechinese/__init__.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>from . import pinyin from .pinyin import * # from . import synonyms # from .synonyms import * __version__ = "0.2.11"<|fim_prefix|># repo: liaoweixia/SimpleChinese2 path: /simplechinese/__init__.py from . import preprocessing from .preprocessing import * from . import representation from .representatio...
code_fim
easy
{ "lang": "python", "repo": "liaoweixia/SimpleChinese2", "path": "/simplechinese/__init__.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }