seq_id string | text string | repo_name string | sub_path string | file_name string | file_ext string | file_size_in_byte int64 | program_lang string | lang string | doc_type string | stars int64 | dataset string | pt string | api list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
260450377 | #!/usr/bin/env python
# coding: utf-8
# # Tournois de Tennis
# In[1]:
class Joueur():
def __init__(self, nom, prénom, classement):
self.nom = nom
self.prénom = prénom
self.classement = classement
def __str__(self):
return "{} {} ({})".format(self.nom, self.prénom, se... | null | Tournois.py | Tournois.py | py | 8,284 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "random.choices",
"line_number": 69,
"usage_type": "call"
},
{
"api_name": "graphviz.Digraph",
"line_number": 82,
"usage_type": "call"
},
{
"api_name": "{'Digraph': 'graphviz.Digraph'}",
"line_number": 121,
"usage_type": "call"
},
{
"api_name": "{'Di... |
528508951 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
class Migration(migrations.Migration):
dependencies = [
('shelf', '0004_auto_20161202_0020'),
]
operations = [
migrations.AlterField(
model_name='book',
name=... | null | shelf/migrations/0005_auto_20161202_1254.py | 0005_auto_20161202_1254.py | py | 430 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.db.migrations.Migration",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "django.db.migrations",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "django.db.migrations.AlterField",
"line_number": 14,
"usage_type": "call"
},
{... |
225098200 | class Solution:
def findSubstring(self, s: str, words: List[str]) -> List[int]:
if s == "" or words == []: return []
n = len(s)
l_word = len(words[0])
length = len(words)*l_word
flag = True
out = []
# 哈希表1
hash1 = {}
hash2 = {}
for word... | null | Qustion Code/30. 串联所有单词的子串.py | 30. 串联所有单词的子串.py | py | 1,722 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "collections.Counter",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "collections.Counter",
"line_number": 41,
"usage_type": "call"
}
] |
168236688 | import numpy as np
import matplotlib.pyplot as plt
from cv2 import cv2
from math import sqrt, log
from scipy.spatial.distance import squareform, pdist
scalar = 5
""" Helper Functions """
"""======================================================"""
def scatter(img,x,y):
half_size = 3
for i in range(x-half_si... | null | CS270-Digital-Image-Processing/hw1/question2image/hw1-part2.py | hw1-part2.py | py | 4,235 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.zeros",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "numpy.int32",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "numpy.zeros",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "numpy.int32",
"line_numb... |
438079620 | from itertools import islice
from datapackage import Resource
from .. import DataStreamProcessor, schema_validator
class set_type(DataStreamProcessor):
def __init__(self, name, **options):
super(set_type, self).__init__()
self.name = name
self.options = options
self.resource = Non... | null | dataflows/processors/set_type.py | set_type.py | py | 1,150 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "itertools.islice",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "datapackage.Resource",
"line_number": 28,
"usage_type": "call"
}
] |
230105070 | import gc
import json
import time
import datetime
from django.utils import timezone
from dataminer.models import *
class Worker():
def __init__(self):
self.start_time = timezone.now()
def run(self):
infos_count = PairInfo.objects.all().count()
count_on_party = 100
count_o... | null | daven/dataminer/fixers/content.py | content.py | py | 1,176 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.utils.timezone.now",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "django.utils.timezone",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "gc.collect",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "json.loads... |
164623729 | """
Tests for the base formatter implementation
"""
import typing
import unittest
import packer.errors
import packer.formatters
class TestFormatter(unittest.TestCase):
"""
Tests for the base formatter implementation
"""
def test_register_hook(self):
"""
Tests that formatters are auto... | null | tests/small/formatters/test_base.py | test_base.py | py | 1,896 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "unittest.TestCase",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "packer.errors.formatters",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "packer.errors",
"line_number": 23,
"usage_type": "name"
},
{
"api_name": "pa... |
574675683 | # -*- coding: utf-8 -*-
from __future__ import print_function
import base64
import logging
import json
import processor.core as core
import lambdautils.utils as utils
from processor.exceptions import KinesisError, FirehoseError
# Tell humilis to pre-process the file using Jinja2
# preprocessor:jinja2
OUTPUT_STREAM ... | null | humilis_filter/lambda_function/processor/main.py | main.py | py | 2,661 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "logging.getLogger",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "processor.core.transform_events",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "p... |
260865104 | import json
from django.template.loader import render_to_string
from activity.handlers import BasicActionHandler
class NewProjectPhotoHandler(BasicActionHandler):
def __init__(
self, template_name='projects/new_photo_action.html'
):
self.template_name = template_name
def get_html_outpu... | null | hackbox/hackbox/apps/projects/activity_handlers.py | activity_handlers.py | py | 971 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "activity.handlers.BasicActionHandler",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "projects.models.ProjectPhoto.objects.get",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "projects.models.ProjectPhoto.objects",
"line_number": 21,
"u... |
523151474 | """
Storage object used to store data scanned from text corpus. This object has
methods to save and load to/from a file.
Data structure:
{
(Predictor_word_1, ... Predictor_word_n) : [Word_option_1, Word_option_2]
}
"""
import sqlite3
import os
class MarkovStorage(object):
def __init__(self, markov_order, ... | null | storage_object.py | storage_object.py | py | 3,815 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sqlite3.connect",
"line_number": 71,
"usage_type": "call"
},
{
"api_name": "os.utime",
"line_number": 91,
"usage_type": "call"
},
{
"api_name": "sqlite3.connect",
"line_number": 105,
"usage_type": "call"
},
{
"api_name": "sqlite3.OperationalError",
... |
350275204 | import sys
import signal
from PyQt5 import QtWidgets
from Application.application import Application
from Application.threadapplication import ThreadApplication
from Camera.camera import Camera
from Camera.threadcamera import ThreadCamera
import config
import comm
signal.signal(signal.SIGINT, signal.SIG_DFL)
if _... | null | guitest.py | guitest.py | py | 1,471 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "signal.signal",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "signal.SIGINT",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "signal.SIG_DFL",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "PyQt5.QtWidgets.... |
465120747 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.shortcuts import render, redirect, get_object_or_404
from django.db import connection
from cadastros.models import Instituicoes, Canais, Deficiencia, Responsavel, Evento, Atividade, Grupo_Atividade,Agendamentos
from cadastros.forms import Insti... | null | cadastros/views_cadastro.py | views_cadastro.py | py | 20,209 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "visite_mv.funcoes.constantes.QTD_ITEMS_PER_PAGE_LISTAGENS",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "visite_mv.funcoes.constantes",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "visite_mv.funcoes.Util.Util",
"line_number": 23,
... |
266433014 | import asyncio
from config import *
from spider import Spider
class Tasker:
def __init__(self):
self.redis_client = REDIS_CLIENT_DB2
self.start_page = START_PAGE
self.stop_page = STOP_PAGE
self.start_per_step = START_PER_STEP
self.stop_per_step = STOP_PER_STEP
def get_... | null | celery+asyncio/tasker.py | tasker.py | py | 1,199 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "spider.Spider",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "asyncio.ensure_future",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "spider.parse",
"line_number": 35,
"usage_type": "call"
}
] |
250890036 |
from __future__ import print_function
from __future__ import absolute_import
import fnmatch
import torch
class ConstraintModule(object):
def __init__(self, constraints):
self.constraints = constraints
self.batch_constraints = [c for c in self.constraints if c.unit == 'batch']
self.epoc... | null | torchsample/constraints.py | constraints.py | py | 3,031 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "fnmatch.fnmatch",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "torch.norm",
"line_number": 61,
"usage_type": "call"
},
{
"api_name": "torch.norm",
"line_number": 91,
"usage_type": "call"
}
] |
68686991 | """Purpose of this script is to initialise all the model parameters"""
# Import libraries
import numpy as np
import pandas as pd
import os
from hurst import compute_Hc
from scipy import stats
from pyabc import Distribution, RV, ABCSMC, UniformAcceptor
from hft_abm_smc_abc.config import DELTA_TRUE, MU_TRUE, ALPHA_TRU... | null | hft_abm_smc_abc/SMC_ABC_init.py | SMC_ABC_init.py | py | 5,400 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "hurst.compute_Hc",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "scipy.stats.ks_2samp",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "scipy.stats",
"line_number": 46,
"usage_type": "name"
},
{
"api_name": "numpy.ravel",
"... |
480505051 | import os
import cv2
import numpy as np
import math
from numpy import linalg as LA
import matplotlib.pyplot as plt
import mahotas
# link data
city_path = './data/city'
forest_path = './data/forest'
sea_path = './data/sea'
# link image
city_image_path = [os.path.join(city_path,i) for i in os.listdir(city_path)]
forest_... | null | landscape/exm.py | exm.py | py | 5,121 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.path.join",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "os.listdir",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number"... |
448597454 | #!/usr/bin/env python3
import argparse
import os
import yaml
import sys
import tensorflow as tf
from tfprocess import TFProcess
START_FROM = 0
def main(cmd):
cfg = yaml.safe_load(cmd.cfg.read())
print(yaml.dump(cfg, default_flow_style=False))
root_dir = os.path.join(cfg['training']['path'], cfg['name'])
... | null | tf/update_steps.py | update_steps.py | py | 1,391 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "yaml.safe_load",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "yaml.dump",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 15... |
428749933 | #
# Compute Ontario Summer School
# Neural Networks with Python I
# 26 June 2019
# Erik Spence
#
# This file, plotting_routines.py, contains some simple plotting
# routines.
#
#######################################################################
"""
plotting_routines.py contains two routines for plotting the class... | null | Summer School Scinet/nn1_code/nn1_code/plotting_routines.py | plotting_routines.py | py | 3,674 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.array",
"line_number": 67,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.scatter",
"line_number": 71,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 71,
"usage_type": "name"
},
{
"api_name": "matplotlib.py... |
212117866 | from django.template import Library
from ...order import OrderStatus
register = Library()
ERRORS = {}
SUCCESSES = {OrderStatus.SHIPPED,}
LABEL_DANGER = 'danger'
LABEL_SUCCESS = 'success'
LABEL_DEFAULT = 'default'
@register.inclusion_tag('status_label.html')
def render_status(status, status_display=None):
if... | null | saleor/core/templatetags/status.py | status.py | py | 554 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.template.Library",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "order.OrderStatus.SHIPPED",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "order.OrderStatus",
"line_number": 9,
"usage_type": "name"
}
] |
523882197 | #!/usr/bin/env python3
'''
Euler angle order needs to be ZXY for consistent stability
Follows Right hand convention. X is forward Z is right Y is up in drone frame
TODO: Possible issues with Optitrack environment alignment on initialization. May need a calibration protocol
'''
import rospy
from acsi_controller.msg i... | null | src/ACSI_package/acsi_controller/nodes/position_control_node.py | position_control_node.py | py | 9,207 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "geometry_msgs.msg.PoseArray",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "acsi_pid.pid.PID",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "acsi_pid.pid",
"line_number": 29,
"usage_type": "name"
},
{
"api_name": "acsi_observ... |
154521661 | """
A module defining a list of fixture functions that are shared across all the skabase
tests.
"""
import mock
import pytest
import importlib
from tango.test_context import DeviceTestContext
@pytest.fixture(scope="class")
def tango_context(request):
"""Creates and returns a TANGO DeviceTestContext object.
... | null | skabase/conftest.py | conftest.py | py | 1,297 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "importlib.import_module",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "tango.test_context.DeviceTestContext",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "mock.Mock",
"line_number": 31,
"usage_type": "call"
},
{
"api_name":... |
419943514 | import csv
import json
import time
import requests
from bs4 import BeautifulSoup
from fake_useragent import UserAgent
def fetch_data(result_id):
url = f"https://www.speedtest.net/result/{result_id}"
ua = UserAgent()
header = {'User-Agent': str(ua.chrome)}
url_data = requests.get(url,... | null | web_crawler.py | web_crawler.py | py | 2,679 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "fake_useragent.UserAgent",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "requests.get",
"... |
523823973 | import glob
import numpy as np
from scipy import misc
from tqdm import tqdm, trange
singFiles = glob.glob("./answers/sing*")
pkls = glob.glob("./pkls/*.pkl")
pkls = [name.split('/')[-1] for name in pkls]
training_list_path = "./pkls/training.csv"
validation_list_path = "./pkls/validation.csv"
img = np.zeros(shape... | null | processing/data_split.py | data_split.py | py | 763 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "glob.glob",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "glob.glob",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "numpy.float32",
"line_number": 13,
... |
249302894 | import requests
from bs4 import BeautifulSoup
import csv
def isolate_secondary_structure(string):
structure_marks = ""
for char in string:
if char == '<' or '>' or '.':
structure_marks += char
return structure_marks
def edit_name (tRNA_name):
new_parts = []
tRN... | null | tRNA_scraper.py | tRNA_scraper.py | py | 7,886 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "csv.reader",
"line_number": 143,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 156,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 163,
"usage_type": "call"
}
] |
50837484 | ################################################################
# Author : yiorgosynkl (find me in Github: https://github.com/yiorgosynkl)
# Date created : 20220903
# Problem link : https://leetcode.com/contest/biweekly-contest-86/problems/maximum-rows-covered-by-columns/
#########################... | null | biweekly_contest_86/2397-maximum-rows-covered-by-columns.py | 2397-maximum-rows-covered-by-columns.py | py | 1,612 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "itertools.combinations",
"line_number": 15,
"usage_type": "call"
}
] |
421489460 | from django.urls import reverse
from .factories import CaseWithVariantSetFactory
from .helpers import ApiViewTestBase
# TODO: add tests that include permission testing
def transmogrify_pedigree(pedigree):
return [
{{"patient": "name"}.get(key, key): value for key, value in m.items()} for m in pedigree
... | null | variants/tests/test_views_api.py | test_views_api.py | py | 5,885 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "helpers.ApiViewTestBase",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "factories.CaseWithVariantSetFactory.get",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "factories.CaseWithVariantSetFactory",
"line_number": 21,
"usage_type": "n... |
393722571 |
from bot_admin import models
from django.contrib.auth.models import User
def save_notification(request):
notification_type = request.POST.get('type', '')
notification = models.Notify(type=notification_type,
activity=get_boolean_from_html(request.POST.get('activity', F... | null | bot_admin/functions.py | functions.py | py | 3,592 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "bot_admin.models.Notify",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "bot_admin.models",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "django.contrib.auth.models.User.objects.get",
"line_number": 10,
"usage_type": "call"
},
{
... |
130417881 | from __future__ import print_function
import nvidia_smi
import sys, os, time
import random
import math
import cv2 as cv
from PIL import Image
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import torch.backends.cudnn as cudnn
from torchvision import datasets, transform... | null | myTest.py | myTest.py | py | 9,208 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "torch.zeros",
"line_number": 65,
"usage_type": "call"
},
{
"api_name": "torch.sort",
"line_number": 69,
"usage_type": "call"
},
{
"api_name": "opts.parse_opts",
"line_number": 83,
"usage_type": "call"
},
{
"api_name": "cfg.parse_cfg",
"line_numb... |
341184755 | import torch
from torch import nn
from torch.nn import functional as F
from torch.multiprocessing import Pool
import numpy as np
from inner import Inner
from copy import deepcopy
class Outer(nn.Module):
"""
Meta learner for the outer loop
"""
def __init__(self, args, config=None):
"""
... | null | outer.py | outer.py | py | 8,640 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "torch.nn.Module",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "torch.nn.functional.mse_loss",
"line_number": 28,
"usage_type": "attribute"
},
{
"api_name": "torch.n... |
575796004 | # -*- coding: utf-8 -*-
import sys, os, sqlite3 as db, requests, json
from bottle import route, run, template, static_file, get, post, request
from elasticsearch import Elasticsearch
connection = db.connect('database/test.db')
connection.text_factory = str
es = Elasticsearch([{'host': 'localhost', 'port': 9200}])
IND... | null | server2.py | server2.py | py | 7,972 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sqlite3.connect",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "elasticsearch.Elasticsearch",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "os.path.isfile",
"line_number": 69,
"usage_type": "call"
},
{
"api_name": "os.path",
... |
517107283 | import torch
import torch.nn as nn
import torchvision.models as models
import torch.nn.functional as F
class ConvNet(nn.Module):
"""EmbeddingNet using ResNet-101."""
def __init__(self):
"""Initialize EmbeddingNet model."""
super(ConvNet, self).__init__()
# Use ResNet for ConvNet
... | null | net.py | net.py | py | 2,508 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "torch.nn.Module",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "torchvision.models.resnet101",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "torchvision.... |
361518871 | ##############################################################################
#
# Copyright (c) 2005 Zope Corporation and Contributors.
# All Rights Reserved.
#
# This software is subject to the provisions of the Zope Public License,
# Version 2.1 (ZPL). A copy of the ZPL should accompany this distribution.
# THIS SO... | null | zf.zscp/trunk/src/zf/zscp/fields.py | fields.py | py | 957 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "zope.schema.schema",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "zope.schema",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "datetime.date",
"line_number": 27,
"usage_type": "call"
}
] |
394480075 | import os
import glob
import torch
import torch.nn as nn
from inference.torch_model.dendiffcnn.denoising_diffusion_mysc import Unet_encoder
from inference.torch_model.dendiffcnn.denoising_diffusion_mysc import Unet_decoder
from inference.torch_model.transformer.transformer import cnnTransformer
class InferenceModel(nn... | null | inference/inference_model.py | inference_model.py | py | 1,914 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "torch.nn.Module",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "inference.torch_model.dendiffcnn.denoising_diffusion_mysc.Unet_encoder",
"line_number": 19,
"usage_type": "ca... |
631550763 | from utils import TreeNode
from typing import List, Optional
class Solution:
def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode':
if p.val > q.val:
p, q = q, p
return self.travseral(root, p.val, q.val)
def travseral(self, node, p, ... | null | source code/235. Lowest Common Ancestor of a Binary Search Tree.py | 235. Lowest Common Ancestor of a Binary Search Tree.py | py | 996 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "utils.TreeNode.build_by_str",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "utils.TreeNode",
"line_number": 31,
"usage_type": "name"
},
{
"api_name": "utils.TreeNode",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "utils.TreeN... |
485117751 | import pytest
import numpy as np
from jina.executors.evaluators.encode.cosine import CosineEvaluator
@pytest.mark.parametrize(
'doc_embedding, gt_embedding, expected',
[
([0, 1], [0, 1], 0.0),
([0, 1], [1, 0], 1.0),
([1, 0], [0, 1], 1.0),
([1, 0], [1, 0], 0.0),
([0, -1... | null | tests/unit/executors/evaluators/encode/test_cosine.py | test_cosine.py | py | 1,374 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "jina.executors.evaluators.encode.cosine.CosineEvaluator",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "pytest.mark.parametrize",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "pytest.mark",
"line_number": 7,
"usage_type": "attribute"
... |
125129333 | from django.shortcuts import render_to_response
from News.models import News
from django.template import RequestContext
#form django.views.generic import DetailView
def index(request):
items = News.objects.all()[:10]
q = RequestContext(request, {
'item':items
})
... | null | News/views.py | views.py | py | 714 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "News.models.News.objects.all",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "News.models.News.objects",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "News.models.News",
"line_number": 9,
"usage_type": "name"
},
{
"api_name... |
605069822 | '''Takes a list of URLs, and returns a list of formatted complaints.'''
import datetime
import logging
import urllib2
import time
import json
def pull_and_format(list_of_urls):
formatted_complaints = []
pull_timestamp = datetime.datetime.now()
for url in list_of_urls:
logging.info('Pul... | null | pull_json.py | pull_json.py | py | 1,082 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "datetime.datetime.now",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "logging.info",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "urllib2.url... |
616838292 |
import requests
from pybyte.endpoints import Endpoints
import json
import pathlib
from loguru import logger
from pybyte.session import ByteSession
from pybyte.user import ByteAccount, ByteUser
from pybyte.post import BytePost
from ffprobe import FFProbe
from ffmpy import FFmpeg
class Byte(object):
@staticmet... | null | pybyte/byte.py | byte.py | py | 8,811 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "json.dumps",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "loguru.logger.error",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "loguru.logger",
"line_number": 36,
"usage_type": "name"
},
{
"api_name": "loguru.logger.error",
... |
235493435 | import gym
from lake2 import LakeLoadEnv
import matplotlib.pyplot as plt
from Net import NeuralNetwork
import numpy as np
ALPHA = 0.3
GAMMA = 0.9 #Discount Rate
EPSILON = 0.1 #Epsilon for Epsilon-Greedy
NUM_EPISODES = 20 #Number of total episodes
NUM_MOVES = 500 #Numb... | null | Q_Agent.py | Q_Agent.py | py | 5,798 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "Net.NeuralNetwork",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "numpy.random.random_sample",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "numpy.random... |
80334310 | import cv2
import numpy as np
import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
import matplotlib.pyplot as plt
pixelAverage=0
counter=0
flag=0
#method for sending mail
def email_trigger(number):
msg = MIMEMultipart()
msg['Subject'] = 'Human Fall'
msg['Fro... | null | Source Code/main.py | main.py | py | 5,601 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "email.mime.multipart.MIMEMultipart",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "email.mime.text.MIMEText",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "smtplib.SMTP",
"line_number": 23,
"usage_type": "call"
},
{
"api_name... |
317138689 | from django_cron import CronJobBase, Schedule
from .models import OpenExchange
import requests
from datetime import datetime
import logging
logger = logging.getLogger(__name__)
class MyCronJob(CronJobBase):
RUN_EVERY_MINS = 60
schedule = Schedule(run_every_mins=RUN_EVERY_MINS)
code = 'my_app.my_cron_job... | null | koytola/product/cron.py | cron.py | py | 1,469 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "logging.getLogger",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "django_cron.CronJobBase",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "django_cron.Schedule",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "request... |
367836242 | # Copyright 2019 Pants project contributors (see CONTRIBUTORS.md).
# Licensed under the Apache License, Version 2.0 (see LICENSE).
from __future__ import annotations
import logging
from dataclasses import dataclass
from pathlib import Path
from textwrap import dedent
from typing import List, Type
from pants.core.goa... | null | src/python/pants/core/goals/fmt_test.py | fmt_test.py | py | 6,514 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pants.engine.fs.FileContent",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "pants.engine.fs.FileContent",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "pants.engine.target.MultipleSourcesField",
"line_number": 27,
"usage_type": "name... |
74276638 | # 신경망학습: 미니 배치(mini-batch)
import os
import sys
import numpy as np
from pathlib import Path
try:
sys.path.append(os.path.join(Path(os.getcwd()).parent, 'lib'))
from mnist import load_mnist
from common import cross_entropy_error
except ImportError:
print('Library Module Can Not Found')
# test1
(train_x,... | null | 02.neural-network/06.neural-network-training/ex03.py | ex03.py | py | 1,195 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sys.path.append",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": ... |
616788963 | import datetime
import numpy
import numpy as np
import pandas as pd
from keras.layers import Dense, Dropout
from keras.models import Sequential
from keras.wrappers.scikit_learn import KerasClassifier
from sklearn.model_selection import StratifiedKFold
from sklearn.preprocessing import StandardScaler
from models.tools... | null | models/nn_deep.py | nn_deep.py | py | 4,546 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "models.tools.load_data",
"line_number": 62,
"usage_type": "call"
},
{
"api_name": "sklearn.preprocessing.StandardScaler",
"line_number": 65,
"usage_type": "call"
},
{
"api_name": "keras.models.Sequential",
"line_number": 75,
"usage_type": "call"
},
{
... |
132153834 | from PIL import Image, ImageDraw, ImageFont
'''ImageDraw生成一个可操作的图像对象，Imagefont是字体对象。
在本段代码中，ImageDraw提供在图片上写字的方法，Imagefont提供字体对象，控制字的大小'''
im = Image.open("lsp.jpg")
im_draw = ImageDraw.Draw(im)
im_size = im.im_size
font_size = min(im_size) // 11#确定字的大小
my_font = ImageFont.truetype("font.tff", size=font_size)
font_l... | null | code/q0.py | q0.py | py | 615 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "PIL.Image.open",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "PIL.ImageDraw.Draw",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "PIL.ImageDraw",
"line_nu... |
375177697 | import requests
TOKEN = ''
source_user = 577250478
target_user = 355405083
list_users = []
class User:
def __init__(self, user_id):
self.user_id = user_id
def __str__(self):
return str(f'https://vk.com/id{self.user_id}')
def __and__(self, other):
response = requests.get(
... | null | netology_basic_python_tasks/12_work_in_class_api_vk/task_get_mutual.py | task_get_mutual.py | py | 829 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "requests.get",
"line_number": 18,
"usage_type": "call"
}
] |
319579854 | import os
from flask import send_file, request, redirect, url_for, jsonify
from dadd.master import app
from dadd.master.files import FileStorage
@app.route('/')
def index():
return redirect(url_for('admin.index'))
@app.route('/files/<path:path>', methods=['PUT', 'GET'])
def files(path):
storage = FileStor... | null | dadd/master/handlers.py | handlers.py | py | 882 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "flask.redirect",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "flask.url_for",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "dadd.master.app.route",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "dadd.master.app",
... |
149427017 | #!/usr/bin/env python
# coding: utf-8
# In[2]:
import numpy,sys,time
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import Dropout
from keras.layers import Flatten
from keras.layers import LSTM
from keras.callbacks import ModelCheckpoint
from keras.utils import np_utils
import s... | null | generate_by_rnn.py | generate_by_rnn.py | py | 6,013 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "string.punctuation",
"line_number": 28,
"usage_type": "attribute"
},
{
"api_name": "gensim.models.Word2Vec",
"line_number": 84,
"usage_type": "call"
},
{
"api_name": "gensim.models",
"line_number": 84,
"usage_type": "attribute"
},
{
"api_name": "num... |
596125085 | #dataを使う
#各、ランダムクロップ
import tensorflow as tf
import numpy as np
import pandas as pd
import datetime
import time
import os
import glob
import math
import argparse
import sys
import random
import cv2
parser = argparse.ArgumentParser()
parser.add_argument("--load_model", action='store_true', help="test is do --load... | null | bunkatu_re_1.py | bunkatu_re_1.py | py | 11,632 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "tensorflow_hub.Module",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "tensorflow_hub.Module",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "t... |
458112978 | #! /usr/bin/env python
# Copyright (c) 2019 Uber Technologies, 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/licenses/LICENSE-2.0
#
# Unless required by a... | null | ludwig/data/dataset/ray.py | ray.py | py | 11,169 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "distutils.version.LooseVersion",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "ray.__version__",
"line_number": 41,
"usage_type": "attribute"
},
{
"api_name": "ludwig.constants.BINARY",
"line_number": 44,
"usage_type": "name"
},
{
"api_n... |
614948598 | import PIL.Image
from torchvision import transforms
import torch
import numpy as np
import cv2
import os
import random
from torch.utils.data import Dataset
import pdb
cuda = torch.cuda.is_available()
class LinemodDataset(Dataset):
def __init__(self,
base_dir='data/linemod',
objec... | null | lib/datasets/linemod.py | linemod.py | py | 8,872 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "torch.cuda.is_available",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "torch.utils.data.Dataset",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "nump... |
563339349 | # -*- coding: utf-8 -*-
"""
Created on Fri Jun 2 13:09:20 2017
@author: 凯风
"""
import nltk # 英文
import jieba # 中文
'''
不说人话的翻译...
如何理解呢...
英文名称 中文翻译 理解
token 令牌 每一个词的起始字符位置和结束位置
tokenize 令牌化 对一个字符串的句子，生成每个词的令牌
... | null | Text_Operation/Basic_Operation/tokenize.py | tokenize.py | py | 1,252 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "jieba.tokenize",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "nltk.ReppTokenizer",
"line_number": 32,
"usage_type": "call"
}
] |
235160243 | from sqlalchemy import (create_engine, String, Integer, Column)
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
from data_db import db_info
from contextlib import contextmanager
Base = declarative_base() # 创建一个基础类
# 创建连接数据库引擎 （适配器采用mysql-connector-python）
engine = create... | null | data_db/create_db.py | create_db.py | py | 1,280 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sqlalchemy.ext.declarative.declarative_base",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.create_engine",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "data_db.db_info.info",
"line_number": 8,
"usage_type": "attribute"
}... |
81427839 | # Under MIT license, see LICENSE.txt
from typing import List
from RULEngine.Game.OurPlayer import OurPlayer
from RULEngine.Util.Pose import Pose
from ai.states.game_state import GameState
from ai.STA.Tactic.tactic import Tactic
from ai.STA.Tactic.tactic_constants import Flags
from ai.STA.Action.MoveToPosition import ... | null | ai/STA/Tactic/go_to_position_pathfinder.py | go_to_position_pathfinder.py | py | 1,797 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "ai.STA.Tactic.tactic.Tactic",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "ai.states.game_state.GameState",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "RULEngine.Game.OurPlayer.OurPlayer",
"line_number": 15,
"usage_type": "name"
... |
566680484 | from PyQt5.QtWidgets import (QApplication, QWidget, QHBoxLayout, QVBoxLayout,
QScrollArea, QTableWidget, QTableWidgetItem, QLabel,
QPushButton, QAbstractItemView, QMessageBox, QLineEdit,
QFormLayout)
from PyQt5.QtCore import Qt
impor... | null | OperatorPanelUi.py | OperatorPanelUi.py | py | 12,991 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "matplotlib.use",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "PyQt5.QtWidgets.QScrollArea",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "PyQt5.QtWidgets.QLabel",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "PyQt... |
520046802 | """Add scan
Revision ID: 184924ecd052
Revises: 8be0b8538d61
Create Date: 2021-03-07 16:15:30.259925
"""
import sqlalchemy as sa
from alembic import op
from sqlalchemy.dialects import postgresql
# revision identifiers, used by Alembic.
revision = "184924ecd052"
down_revision = "8be0b8538d61"
branch_labels = None
depe... | null | redata/alembic/versions/184924ecd052_add_scan.py | 184924ecd052_add_scan.py | py | 1,627 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "alembic.op.create_table",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "alembic.op",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "sqlalchemy.Column",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.Integ... |
451352490 |
# In[1]:
import numpy as np
import cv2
import matplotlib.image as mpimg
from matplotlib import pyplot as plt
from sklearn.cluster import KMeans
get_ipython().run_line_magic('matplotlib', 'inline')
# In[2]:
def centroid_histogram(clt):
# grab the number of different clusters and create a histogram
... | null | cluster_4color_detect.py | cluster_4color_detect.py | py | 2,305 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.arange",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "numpy.unique",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "numpy.histogram",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_num... |
528563169 | from TikTokApi import TikTokapi
# Starts The Api Class
api = TikTokapi("browsermob-proxy/bin/browsermob-proxy")
# The Number of trending TikToks you want to be displayed
results = 10
# The TikTok user's ID, can be found in the JSON from trending
id = "7119601"
trending = api.userPosts(id, count=results)
for tiktok... | null | examples/getAUsersVideos.py | getAUsersVideos.py | py | 450 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "TikTokApi.TikTokapi",
"line_number": 4,
"usage_type": "call"
}
] |
123532169 | __author__ = 'btciavol'
__date__ = '3/20/12'
#---- Library Imports ---------------------------------------------------------
import xml.etree.ElementTree as et
import copy
#---- 3rd Party Imports --------------------------------------------------------
import traits.api as tr
#---- Local Imports --------------------... | null | repo/catalog.py | catalog.py | py | 8,949 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "traits.api.List",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "traits.api",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "traits.api.Instance",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "drawables.Drawable",
... |
397370316 | import os
import json
from django.shortcuts import render
from django.http import JsonResponse, HttpRequest, HttpResponse
from teamstudyCodingChallenge import settings
def index(request):
with open(os.path.join(settings.BASE_DIR, "notes/notes.json")) as notes_file:
data = json.load(notes_file)
re... | null | backend/teamstudyCodingChallenge/notes/views.py | views.py | py | 839 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.path.join",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "teamstudyCodingChallenge.settings.BASE_DIR",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_nam... |
431949942 | import json
from django.core.urlresolvers import reverse
from django.shortcuts import get_object_or_404
from django.test import TestCase
from google.appengine.ext import testbed
from ingredients.models import Ingredient
class TestIngredientViews(TestCase):
def setUp(self):
""" Initialize GAE test stubs... | null | ingredients/tests/test_views.py | test_views.py | py | 4,716 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.test.TestCase",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "google.appengine.ext.testbed.Testbed",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "google.appengine.ext.testbed",
"line_number": 15,
"usage_type": "name"
},
{... |
293738876 | # Copying Holly Grimm's solution https://github.com/hollygrimm/cs294-homework/blob/master/hw1/bc.py
# Copy and pasting and merging it into a copy of my behavior_cloner.py code.
import argparse
import pickle
import os
import sys
import tensorflow.compat.v1 as tf
import numpy as np
from sklearn.model_selection import tr... | null | hw1/hollygrimm_behavior_cloner.py | hollygrimm_behavior_cloner.py | py | 7,913 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "mlflow.tensorflow.tensorflow.autolog",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "mlflow.tensorflow.tensorflow",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "mlflow.tensorflow",
"line_number": 21,
"usage_type": "name"
},
... |
558160972 | # f = open(r'E:\Jmeter\fee.txt','r')
# lines = f.readlines()
# print(lines)
#
# for line in lines:
# print(line.split(',')[0])
from io import StringIO
# write to StringIO:
f = StringIO()
f.write('hello')
f.write(' ')
f.write('world!')
print(f.getvalue())
# read from StringIO:
f = StringIO('水面细风生，\n菱歌慢慢声。\n客亭临小市，\... | null | Common/Py_Study/String_io.py | String_io.py | py | 461 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "io.StringIO",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "io.StringIO",
"line_number": 17,
"usage_type": "call"
}
] |
624781286 | '''
Copyright(C) 2015 Intel Corporation and Jaak Simm KU Leuven
All rights reserved.
Redistribution and use in source and binary forms, with or without modification,
are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice,
this list of con... | null | chemo/chemo_db.py | chemo_db.py | py | 4,390 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "struct.unpack_from",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "struct.unpack",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "struct.pack",
"line_number": 61,
"usage_type": "call"
},
{
"api_name": "enum.Enum",
"line_nu... |
515998488 | import numpy as np
import matplotlib.pyplot as plt
import plottools
import os
from ModelSelection import ModelSelection
# Read data
ms = ModelSelection()
optimizer_method = ms.read_pareto_curve()
# Generate Pareto curve
plt.rcParams.update({'font.size': 20})
fig, ax = plt.subplots(1, 1, figsize = (15, 7.5), dpi = 300... | null | SIR Compartmental/SINDy/Pareto.py | Pareto.py | py | 1,815 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "ModelSelection.ModelSelection",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.rcParams.update",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.rcParams",
"line_number": 12,
"usage_type": "attribute"
... |
185436227 | # coding: utf-8
from django.core.management.base import BaseCommand
from main.models import City, CountryCode
from django.db import transaction
class Command(BaseCommand):
help = "Заносим данные в дазу банных"
@transaction.atomic()
def handle(self, *args, **options):
file_path = '/home... | null | main/management/commands/filldatabase.py | filldatabase.py | py | 1,030 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.core.management.base.BaseCommand",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "main.models.City",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "main.models.CountryCode.objects.get_or_create",
"line_number": 20,
"usage_type": ... |
607022221 | """test IEMRE stuff"""
import datetime
try:
from zoneinfo import ZoneInfo
except ImportError:
from backports.zoneinfo import ZoneInfo
import numpy as np
from pyiem.util import utc, get_dbconn
from pyiem import iemre
def test_ncname():
"""Test the responses for get_names."""
assert iemre.get_daily_nc... | null | tests/test_iemre.py | test_iemre.py | py | 3,543 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pyiem.iemre.get_daily_ncname",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pyiem.iemre",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "pyiem.iemre.get_hourly_ncname",
"line_number": 17,
"usage_type": "call"
},
{
"api_name":... |
521625076 | ''' A class defining the nodes in our Differentially Private Random Decision Forest '''
from collections import defaultdict
import random
import numpy as np
import math
from scipy import stats # for Exponential Mechanism
class node:
def __init__(self, parent_node, split_value_from_parent, splitting_attribute, t... | null | src/private_tree/node.py | node.py | py | 4,334 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "collections.defaultdict",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "numpy.random.RandomState",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 25,
"usage_type": "attribute"
},
{
"api_name": "ma... |
159649914 | # In [1]
import time, sys, os
tbegin = time.time()
import h5py
import numpy as np
import matplotlib.pyplot as plt
# In [2]
import fsps
import sedpy
import prospect
import emcee
import sg_params as params
from corner import quantile
# more imports
from matplotlib.backends.backend_pdf import PdfPages
from sg_likelihood... | null | hst/PROSPECTOR/prospect_ssp.py | prospect_ssp.py | py | 18,967 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "time.time",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_number": 25,
"usage_type": "attribute"
},
{
"api_name": "astropy.table.Table",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "astropy.table.Column",
... |
442535435 | # Copyright (c) 2015-2016 Tigera, Inc. All rights reserved.
#
# 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/licenses/LICENSE-2.0
#
# Unless required by applicabl... | null | tests/st/bgp/test_bgp_config.py | test_bgp_config.py | py | 4,774 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "tests.st.test_base.TestBase",
"line_number": 41,
"usage_type": "name"
},
{
"api_name": "tests.st.utils.docker_host.DockerHost",
"line_number": 47,
"usage_type": "call"
},
{
"api_name": "tests.st.utils.exceptions.CommandExecError",
"line_number": 52,
"usage_... |
262534530 | import pandas as pd
import numpy as np
from scipy import sparse as sps
import math
import csv
def load_data(path="../ml-20m/ratings.csv"):
df = pd.read_csv(path)
userIds = df.userId.unique()
del df
user_data = []
movie_data = []
rating_data = []
## Missing movie ids in dataset - we co... | null | hw1/datahandler.py | datahandler.py | py | 2,674 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pandas.read_csv",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "csv.reader",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "scipy.sparse.coo_matrix",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "scipy.sparse",
... |
554027439 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# diskCache.py
import os
import sys
import zlib
import time
import logging as logger
import urlparse
from datetime import datetime, timedelta
try:
import cPickle as pickle
except ImportError:
logger.info ("cPickle module not available")
import pickle
sy... | null | database/diskCache.py | diskCache.py | py | 3,668 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "logging.info",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "sys.setrecursionlimit",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "datetime.timedelta",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "os.path.exists"... |
600593333 | # code for this partially borrowed from tjcsl/cslbot
import git
import json
import requests
import plugins
from ghinfo import *
from links import *
from control import *
from urllib.parse import quote as sanitize
def _initialise():
plugins.register_admin_command(['pull', 'issue', 'commit'])
plugins.register_u... | null | hangupsbot/plugins/github.py | github.py | py | 6,392 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "plugins.register_admin_command",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "plugins.register_user_command",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "urllib.parse.quote",
"line_number": 28,
"usage_type": "call"
},
{
"a... |
80055497 | import game_settings as gs
import numpy as np
import random
from readchar import readchar
import time
replay = True
lost = False
score = 0
print("\n" + ("*"*35))
print("Python Guessing Game.\n\nContinue by pressing any key...")
print("\n" + ("*"*35))
readchar()
while replay:
guess_count = 0
print("\nGame S... | null | main_game.py | main_game.py | py | 2,458 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "readchar.readchar",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "game_settings.game_start",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "game_settings.get_game_word",
"line_number": 23,
"usage_type": "call"
},
{
"api_name":... |
644042012 | import sys
import os
import pandas as pd
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("-d", "--dof", type=str, help="DOF file", required=True)
parser.add_argument("-i", "--inputdir", type=str, help="Inputdir", required=True)
parser.add_argument("-o", "--outputfile", type=str, help="Output f... | null | PileupMC/joinStripWeights.py | joinStripWeights.py | py | 909 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "pandas.concat"... |
66416233 | # SANDBOX
# FLASK
from flask import Flask, request, redirect, url_for, Response
import re
import docx2html
import os
from werkzeug.utils import secure_filename
app_instructions = """
<br>
<h2>FORMATTING</h2>
<ul>
<li> for each chunk of content, use hashtag "#" and the type of block in caps (INSTRUCTION, TIP, CHINESE... | null | apps/post_parser/post_parser_web_app.py | post_parser_web_app.py | py | 14,869 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "flask.Flask",
"line_number": 101,
"usage_type": "call"
},
{
"api_name": "flask.request.method",
"line_number": 123,
"usage_type": "attribute"
},
{
"api_name": "flask.request",
"line_number": 123,
"usage_type": "name"
},
{
"api_name": "flask.request.... |
107805310 | from __future__ import print_function
import json
import datetime
import time
import boto3
print('Loading function')
def lambda_handler(event, context):
AUTO_SCALLING_GROUP = 'Hayes-Test-ASG'
LC = 'LC-micro'
print("Received event: " + json.dumps(event, indent=2))
# get autoscaling client
clien... | null | 4-lc-sg-lambda-update-one.py | 4-lc-sg-lambda-update-one.py | py | 1,039 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "json.dumps",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "boto3.client",
"line_number": 18,
"usage_type": "call"
}
] |
384104947 | #task_master.py
import random,time,queue,threading
from multiprocessing.managers import BaseManager
from multiprocessing import freeze_support
from task_worker import worker
task_queue=queue.Queue()
result_queue=queue.Queue()
class QueueManager(BaseManager):
pass
def task_q():
return task_queue
def result_... | null | task_master.py | task_master.py | py | 1,165 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "queue.Queue",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "queue.Queue",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "multiprocessing.managers.BaseManager",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "random.ran... |
288536244 | """Train (basic) densely-connected oracle."""
import os
import time
import multiprocessing as mp
import pandas as pd
import torch
from torch import optim
from torch.utils.data import DataLoader, Subset, TensorDataset, WeightedRandomSampler
from profit.dataset.splitters import split_method_dict
from profit.models.to... | null | examples/gb1/train_oracle.py | train_oracle.py | py | 5,919 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "time.strftime",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "time.gmtime",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "torch.device",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "torch.cuda.is_available",
... |
233337743 | # The second file for exploratory modelling as the first one got over-written
#Import relevant libraries
import pandas as pd
import os
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.ensemble import RandomForestClassifier
from sklearn.externals import joblib
from sklearn.model_sel... | null | Exploratory_Modelling_2.py | Exploratory_Modelling_2.py | py | 12,669 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pandas.options",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "os.getcwd",
"line_n... |
112534418 | #!/usr/bin/python
# -*- coding:utf-8 -*-
import sys
sys.path.append(r'../lib')
import epd1in54
import epdconfig
import time
from PIL import Image,ImageDraw,ImageFont
import traceback
try:
print("epd1in54 Demo")
epd = epd1in54.EPD()
print("init and Clear")
epd.init(epd.lut_full_update)
epd.Cle... | null | python3/test_demo/python3/examples/epd_1in54_test.py | epd_1in54_test.py | py | 2,573 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sys.path.append",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "epd1in54.EPD",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "PIL.Image.new",
"line_nu... |
595530228 | import os
import sqlite3
conn = sqlite3.connect('programs.db')
cursor = conn.cursor()
try:
cursor.execute('''CREATE TABLE programs(file text, way text) ''')
except sqlite3.OperationalError:
pass
def add(file, way):
cursor.execute("INSERT INTO programs (file,way) VALUES ('%s','%s')"%(file,way))
conn.commit()
def o... | null | main.py | main.py | py | 751 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sqlite3.connect",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "sqlite3.OperationalError",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "os.startfile",
"line_number": 19,
"usage_type": "call"
}
] |
6253659 | import numpy as np
import cv2
colors = {
'green': (0, 255, 0),
'pink': (255, 0, 255),
'blue': (0, 0, 255)
}
def get_calibration_cam_to_image(cab_f):
for line in open(cab_f):
if 'P2:' in line:
cam_to_img = line.strip().split(' ')
cam_to_img = np.asarray([float(number) for ... | null | draw_3dbox.py | draw_3dbox.py | py | 3,442 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.asarray",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.reshape",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "numpy.pi",
"line_number": 31,
"usage_type": "attribute"
},
{
"api_name": "numpy.arctan",
"line_nu... |
585795105 | """Database module
This module declares Database Models of User and Group Resources.
User Resource is internally stored in User class object.
Group Resource is internally stored in Group class object.
db, an instance of SQLAlchemy from Flask-SQLAlchemy is declared here and
is initialized in Application Factory funct... | null | appusers/database.py | database.py | py | 8,719 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "flask_sqlalchemy.SQLAlchemy",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.text",
"line_number": 99,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.text",
"line_number": 101,
"usage_type": "call"
},
{
"api_name": "sqlalche... |
324482778 | #!/usr/bin/env python
"""An ivyprobe script for ivy-python
"""
import os, string, sys, time, getopt
#sys.path.append ("F:\ivy-python-2.1")
from ivy.std_api import *
from ModeleCompteBon import *
from VueCompteBon import *
from random import randint
#On cree la vue en global
root = Tk()
app = Application(ro... | null | PILS/Ivy/ivy-python-2.1/IvySniffCompteBon.py | IvySniffCompteBon.py | py | 15,853 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "random.randint",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "os.path.basename",
"line_number": 48,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 48,
"usage_type": "attribute"
},
{
"api_name": "ivy.ivy.IvyRegexpAdded",... |
544666754 | # module imports
import pygame
import gamedefs
import math
import os
# class for player sprite
class Blob(pygame.sprite.Sprite):
# sprite for the player
def __init__(self, x, y):
pygame.sprite.Sprite.__init__(self)
# get os-independent folder name
root_dir = os.path.dirname(__file__)
... | null | blobclass.py | blobclass.py | py | 753 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pygame.sprite",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "pygame.sprite.Sprite.__init__",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "pygame.sprite",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "os... |
259048315 | from elasticsearch import Elasticsearch, helpers
import request_rss as rrss
import json
def createIndex(index_name, mapping_file):
with open(mapping_file) as source:
mapping = json.load(source)
es = Elasticsearch()
return es.indices.create(index_name , body = mapping)
def putBulk(feed_dict):
e... | null | es_config.py | es_config.py | py | 865 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "json.load",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "elasticsearch.Elasticsearch",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "elasticsearch.Elasticsearch",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "elast... |
74881622 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('sites', '0001_initial'),
('mezzanine_blocks', '0001_initial'),
]
operations = [
mig... | null | mezzanine_blocks/migrations/0002_auto_20150719_2213.py | 0002_auto_20150719_2213.py | py | 1,797 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.db.migrations.Migration",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "django.db.migrations",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "django.db.migrations.CreateModel",
"line_number": 16,
"usage_type": "call"
},
... |
277835100 | import pytest
from numpy import newaxis, inf, nan
from numpy.random import RandomState
from numpy.testing import assert_allclose
from glimix_core.lmm import LMM
from numpy_sugar.linalg import economic_qs_linear
def test_lmm_interface():
random = RandomState(0)
y = random.randn(4)
X = random.randn(5, 2)
... | null | glimix_core/lmm/test/test_lmm_interface.py | test_lmm_interface.py | py | 1,355 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.random.RandomState",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy_sugar.linalg.economic_qs_linear",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pytest.raises",
"line_number": 17,
"usage_type": "call"
},
{
"api_... |
355627062 | import pymysql,logging,os
import time
import json
class amendMoneyApi():
def connectdb(self):
# db = pymysql.connect("jintcadev.mysql.rds.aliyuncs.com","huyuanji","RBWfQQOm0foX","bizpay")
db = pymysql.connect("121.40.73.49","h5","h5@123","bikeca")
return db
#修改虚拟卡状态为可用
def querydb(s... | null | mySql/connectMysql.py | connectMysql.py | py | 1,623 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pymysql.connect",
"line_number": 7,
"usage_type": "call"
}
] |
621074452 |
import argparse
import re
import os, glob, datetime, time
import numpy as np
import torch
import torch.nn as nn
import torch.nn.init as init
from torch.utils.data import DataLoader
import torch.optim as optim
from torch.optim.lr_scheduler import MultiStepLR
import data_generator as dg
from data_generator import Denois... | null | train/main_train_fourier_sep.py | main_train_fourier_sep.py | py | 8,720 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "torch.cuda.is_available",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line_number": 34,
"usage_type": "attribute"
},
{
"api_name": "numpy... |
628159796 | from glob import glob
import subprocess
import re
import dateparser
import csv
from iso4217 import Currency
from itertools import tee
from os import path
DATE_CLUES = ['statement date', 'as at']
CURRENCIES = set([c.code for c in Currency])
CURRENCY_AMOUNT_REGEX = '({} \d+[\.|,|\d]*\d+)'
def parse_statement_date(lin... | null | cleaning/pdf-mining/pdftotxt.py | pdftotxt.py | py | 3,389 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "iso4217.Currency",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "dateparser.parse",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "re.search",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "re.IGNORECASE",
"line... |
378871116 | import torch
import torch.nn as nn
from utils import intersection_over_union
class YOLOloss(nn.Module):
def __init__(self):
super().__init__()
self.mean_sqrt_err = nn.MSELoss()
self.bce = nn.BCEWithLogitsLoss()
self.entropy = nn.CrossEntropyLoss()
self.sigmoid = nn.Sigmoid(... | null | loss.py | loss.py | py | 1,631 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "torch.nn.Module",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "torch.nn.MSELoss",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_numb... |
341825250 | import engine
from pandas import DataFrame
from math import e
from matplotlib import pyplot as plt
def approx(b, x):
return 2 / (1+e**(-b*x))-1
def qerror(b, x):
return engine.quad_error(approx, b, x)
def average_quadratic_error(b):
return engine.integrate(qerror, b, 0, 5, 0.01)/5
def graph_error(min, m... | null | src/logarithmic_approx.py | logarithmic_approx.py | py | 1,195 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "math.e",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "engine.quad_error",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "engine.integrate",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.plot",
... |
486426982 | import os
import re
import sys
import json
import urllib
# figure out where we'll be making the build
for line in open( "SConstruct" ).readlines() :
if re.search( "gaffer[A-Za-z]*Version = ", line ) :
exec( line.strip() )
platform = "osx" if sys.platform == "darwin" else "linux"
buildDir = "build/gaffer-%d.%d.%... | null | config/travis/installDependencies.py | installDependencies.py | py | 1,019 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "re.search",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sys.platform",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "json.load",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "urllib.urlopen",
"line_numb... |
4143864 | from django.conf.urls import url
from . import views
app_name = 'general'
urlpatterns = [
url(r'^$', view=views.index, name='index'),
url(r'^construction/', view=views.construction, name='construction'),
url(r'^contact/', view=views.contact, name='contact'),
url(r'^login$', view=views.log... | null | apps/general/urls.py | urls.py | py | 400 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.conf.urls.url",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "django.conf.urls.url",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "django.conf.urls.url",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "django.c... |
209348806 | import itertools
import pytest
import main
def test_update():
config = {
'ginger': {
'django': 2,
'flask': 3,
},
'cucumber': {
'flask': 1,
},
}
main.update(config, 'pylons', 7)
assert config == {
'ginger': {
'djang... | null | test.py | test.py | py | 1,385 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "main.update",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "main.update",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "main.update",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "itertools.permutations",
"lin... |
341060032 | import numpy as np
from tools import add_intercept
def predict_(x, theta) -> np.ndarray:
"""Computes the vector of prediction y_hat from two non-empty numpy.ndarray.
Args:
x: has to be an numpy.ndarray, a vector of dimension m * 1.
theta: has to be an numpy.ndarray, a vector of dimension 2 * 1.
Returns:
y_hat a... | null | day00/ex07/prediction.py | prediction.py | py | 890 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.matmul",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "tools.add_intercept",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "numpy.ndarray",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "numpy.arange",
... |
69235868 | # coding: utf-8
import os
import time
import random
import logging
import argparse
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from torchvision import datasets
from torch.autograd import Variable
from lr_scheduler import *
from model import *
from da... | null | main.py | main.py | py | 4,673 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "torch.manual_seed",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "torch.cuda.manual_seed",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line_number": 25,
"usage_type": "attribute"
},
{
"api_name": "numpy.random... |
175654195 | #!/usr/bin/env python3
# Evaluate relation annotations in standoff data.
import sys
import os
from collections import defaultdict
from logging import error
# Relation types to treat as symmetric
SYMMETRIC_RELATION_TYPES = set([
'Complex_formation'
])
def argparser():
from argparse import ArgumentParser
... | null | TensorFlow/LanguageModeling/BERT/evalsorel.py | evalsorel.py | py | 13,976 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "logging.error",
"line_number": 261,
"usage_type": "call"
},
{
"api_name": "os.listdir",
"line_number": 289,
"usage_type": "call"
},
{
"api_name": "os.path.splitext",... |
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