text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|>@main.route("/<address>")
def user_dashboard(address=None):
if len(address) != 34:
abort(404)
stats = collect_user_stats(address)
# reorganize/create the recently viewed
recent = session.get('recent_users', [])
if address in recent:
recent.remove(address)
recent.i... | code_fim | hard | {
"lang": "python",
"repo": "palon7/simplemona",
"path": "/simplecoin/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sreetamparida/Hiraishin path: /Elements/MapRed/MRResult.py
import os
class MRResult:
def __init__(self, config, columns, timeTaken):
self.mrResult = {}
self.queryResult = []
self.config = config
self.columns = columns
self.timeTaken = timeTaken
<|fi... | code_fim | hard | {
"lang": "python",
"repo": "sreetamparida/Hiraishin",
"path": "/Elements/MapRed/MRResult.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> cleanDirectory = self.config['clean_directory']
cleanHDFS = self.config['clean_hdfs']
os.system(cleanDirectory)
os.system(cleanHDFS)
return self.mrResult<|fim_prefix|># repo: sreetamparida/Hiraishin path: /Elements/MapRed/MRResult.py
import os
class MRResult:
... | code_fim | hard | {
"lang": "python",
"repo": "sreetamparida/Hiraishin",
"path": "/Elements/MapRed/MRResult.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: saiihamza/open_data_parsing path: /product/product_compositions.py
class ProductCompositions(object):
def __init__(self):
self.IngredientsTextAllergens = ''
self.AllergensFr = ''
self.Traces = ''
self.TracesTags = ''
self.TracesFr = ''
<|fim_suff... | code_fim | hard | {
"lang": "python",
"repo": "saiihamza/open_data_parsing",
"path": "/product/product_compositions.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>ThatMayBeFromPalmOilTags = ''
self.NutritionGradeFr = ''
self.NovaGroup = ''
self.PnnsGroups1 = ''
self.PnnsGroups2 = ''
def __str__(self):
return self.IngredientsTextAllergens<|fim_prefix|># repo: saiihamza/open_data_parsing path: /product/product_composition... | code_fim | hard | {
"lang": "python",
"repo": "saiihamza/open_data_parsing",
"path": "/product/product_compositions.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>from models.runbagofwords import BagofWords<|fim_prefix|># repo: andrew-lockwood/lab-project path: /context.py
import os
import sys
sys.path.insert(0, os.path.abspath('..'))
from util.settings import settings
from util.progressbar import ProgressBar
<|fim_middle|>from corpus.data_loader import DataLoa... | code_fim | medium | {
"lang": "python",
"repo": "andrew-lockwood/lab-project",
"path": "/context.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>from corpus.data_loader import DataLoader
from corpus.document_iterator import Documents
from corpus.sentence_iterator import LabeledSentences
from models.runbagofwords import BagofWords<|fim_prefix|># repo: andrew-lockwood/lab-project path: /context.py
import os
import sys
sys.path.insert(0, os.path.a... | code_fim | medium | {
"lang": "python",
"repo": "andrew-lockwood/lab-project",
"path": "/context.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: andrew-lockwood/lab-project path: /context.py
import os
import sys
sys.path.insert(0, os.path.abspath('..'))
from util.settings import settings
from util.progressbar import ProgressBar
<|fim_suffix|>from models.runbagofwords import BagofWords<|fim_middle|>from corpus.data_loader import DataLoa... | code_fim | medium | {
"lang": "python",
"repo": "andrew-lockwood/lab-project",
"path": "/context.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # switch to train mode
model.train()
epoch_stats = []
for batch_idx, (data, target) in enumerate(train_loader):
data, target = data.to(device), target.to(device)
# compute output
output = model(data)
losses_ = F.nll_loss(output, target, reduction='none')
... | code_fim | hard | {
"lang": "python",
"repo": "lanadeji/blog-code",
"path": "/pr-lr/cifar.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lanadeji/blog-code path: /pr-lr/cifar.py
import argparse
import os
import shutil
import time
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.optim
import torch.utils.data
import torch... | code_fim | hard | {
"lang": "python",
"repo": "lanadeji/blog-code",
"path": "/pr-lr/cifar.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
('facilities', '0005_dhisauth'),
('facilities', '0008_merge_20170911_0851'),
]
operations = [
]<|fim_prefix|># repo: SteveWaweru/mfl_api path: /facilities/migrations/0009_merge_20190828_1929.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2019-08... | code_fim | easy | {
"lang": "python",
"repo": "SteveWaweru/mfl_api",
"path": "/facilities/migrations/0009_merge_20190828_1929.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class Migration(migrations.Migration):
dependencies = [
('facilities', '0005_dhisauth'),
('facilities', '0008_merge_20170911_0851'),
]
operations = [
]<|fim_prefix|># repo: SteveWaweru/mfl_api path: /facilities/migrations/0009_merge_20190828_1929.py
# -*- coding: utf-8 ... | code_fim | easy | {
"lang": "python",
"repo": "SteveWaweru/mfl_api",
"path": "/facilities/migrations/0009_merge_20190828_1929.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SteveWaweru/mfl_api path: /facilities/migrations/0009_merge_20190828_1929.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2019-08-28 19:29
from __future__ import unicode_literals
<|fim_suffix|>
dependencies = [
('facilities', '0005_dhisauth'),
('facilities', '0008_me... | code_fim | medium | {
"lang": "python",
"repo": "SteveWaweru/mfl_api",
"path": "/facilities/migrations/0009_merge_20190828_1929.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 0xbadcoffe/home-automation path: /ti_IOT/testing/pagelayout.py
import kivy
# base Class of your App inherits from the App class.
# app:always refers to the instance of your application
from kivy.app import App
# The PageLayout class is used to create
# a simple multi-page lay... | code_fim | hard | {
"lang": "python",
"repo": "0xbadcoffe/home-automation",
"path": "/ti_IOT/testing/pagelayout.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
build function here
"""
layout = GridLayout(cols=2)
button_lightON = Button(text="Light ON",background_color=red)
button_lightOFF = Button(text="Light OFF",background_color=green)
button_fanON = Button(text="Fan ON",background_color=blue)
... | code_fim | hard | {
"lang": "python",
"repo": "0xbadcoffe/home-automation",
"path": "/ti_IOT/testing/pagelayout.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class PageLayout(PageLayout):
"""
Define class PageLayout here
"""
def __init__(self):
# The super function in Python can be
# used to gain access to inherited methods
# which is either from a parent or sibling class.
super(PageLayout, ... | code_fim | hard | {
"lang": "python",
"repo": "0xbadcoffe/home-automation",
"path": "/ti_IOT/testing/pagelayout.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.hi_here = tk.Button(frame,text='hi',fg='blue',command=self.say_hi)
self.hi_here.pack()# set the position of frame
self.exit = tk.Button(frame,text='exit',fg='blue',command=exit)
self.exit.pack()# set the position of frame
def say_hi(self):
print('Hello wo... | code_fim | medium | {
"lang": "python",
"repo": "4ever-blessed/Github_python3_code",
"path": "/python_tkinter_study/tk之添加按钮执行命令.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 4ever-blessed/Github_python3_code path: /python_tkinter_study/tk之添加按钮执行命令.py
# conda_python3_code
import tkinter as tk
class APP:
def __init__(self,master):
frame = tk.Frame(master)
frame.pack(side=tk.LEFT,padx=100,pady=100) # set the position of frame
self.hi_here ... | code_fim | medium | {
"lang": "python",
"repo": "4ever-blessed/Github_python3_code",
"path": "/python_tkinter_study/tk之添加按钮执行命令.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> the input
print(palindrome.is_palindrome(question))<|fim_prefix|># repo: PingryPython-2017/black_team_palindrome path: /main.py
import palindrome
# Ask the user for a input.
questi<|fim_middle|>on = raw_input("Yo my guy, dish me a string and I will tell you if it is a palindrome or not! ")
# Test | code_fim | medium | {
"lang": "python",
"repo": "PingryPython-2017/black_team_palindrome",
"path": "/main.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PingryPython-2017/black_team_palindrome path: /main.py
import palindrome
# Ask the user for a input.
questi<|fim_suffix|>ll tell you if it is a palindrome or not! ")
# Test the input
print(palindrome.is_palindrome(question))<|fim_middle|>on = raw_input("Yo my guy, dish me a string and I wi | code_fim | easy | {
"lang": "python",
"repo": "PingryPython-2017/black_team_palindrome",
"path": "/main.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: anishkarki/timeseries path: /test.py
def count(n):
count=0
for i in<|fim_suffix|>.count('7')
count=count+value
print ("count:",count)
count(100)<|fim_middle|> range(n+1):
value=str(i) | code_fim | easy | {
"lang": "python",
"repo": "anishkarki/timeseries",
"path": "/test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print ("count:",count)
count(100)<|fim_prefix|># repo: anishkarki/timeseries path: /test.py
def count(n):
count=0
for i in range(n+1):
value=str(i)<|fim_middle|>.count('7')
count=count+value
| code_fim | easy | {
"lang": "python",
"repo": "anishkarki/timeseries",
"path": "/test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: anishkarki/timeseries path: /test.py
def count(n):
count=0
for i in range(n+1):
value=str(i)<|fim_suffix|> print ("count:",count)
count(100)<|fim_middle|>.count('7')
count=count+value
| code_fim | easy | {
"lang": "python",
"repo": "anishkarki/timeseries",
"path": "/test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Sceptre/sceptre-core path: /sceptre/file_manager/__init__.py
import copy
import fnmatch
import logging
import re
import os
from sceptre.file_manager.file_handler import FileHandler
from sceptre.file_manager import strategies
class FileManager:
def __init__(self, context):
self.log... | code_fim | hard | {
"lang": "python",
"repo": "Sceptre/sceptre-core",
"path": "/sceptre/file_manager/__init__.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __walk(self, root, pattern):
items = []
for directory_name, sub_directories, files in os.walk(
root, topdown=False, followlinks=True):
for filename in fnmatch.filter(files, '*.yaml'):
if re.match(pattern, filename):
it... | code_fim | hard | {
"lang": "python",
"repo": "Sceptre/sceptre-core",
"path": "/sceptre/file_manager/__init__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: iblislin/pyvalid path: /pyvalid/__exceptions.py
class InvalidArgumentNumberError(ValueError):
"""Raised when the number or position of arguments supplied to a function
is incorrect.
"""
def __init__(self, func_name):
self.error = 'Invalid number or position of arguments fo... | code_fim | medium | {
"lang": "python",
"repo": "iblislin/pyvalid",
"path": "/pyvalid/__exceptions.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.error = 'Invalid return type {} for {}()'.format(
return_type, func_name
)
def __str__(self):
return self.error<|fim_prefix|># repo: iblislin/pyvalid path: /pyvalid/__exceptions.py
class InvalidArgumentNumberError(ValueError):
"""Raised when the number or... | code_fim | hard | {
"lang": "python",
"repo": "iblislin/pyvalid",
"path": "/pyvalid/__exceptions.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> #test------------------------------------softmax
for i in range(0,len(score_res)):
score_res[i]=1 / (1 + math.exp(-score_res[i]))
test_label1 = np.array(score_res)
barSoftMax=0.5
ind_pos1 = test_label1 >= barSoftMax
ind_neg1 = test_label1... | code_fim | hard | {
"lang": "python",
"repo": "ayushgoyaal/GAN_With_Content_And_Structure",
"path": "/src/evaluation/eval_link_prediction.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ayushgoyaal/GAN_With_Content_And_Structure path: /src/evaluation/eval_link_prediction.py
"""
The class is used for evaluating the application of link prediction
"""
import numpy as np
from sklearn.metrics import precision_score,recall_score,f1_score
from sklearn.metrics import accuracy_score
imp... | code_fim | hard | {
"lang": "python",
"repo": "ayushgoyaal/GAN_With_Content_And_Structure",
"path": "/src/evaluation/eval_link_prediction.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#Install all flows in table
def prepareRIDTable(dp,ranges,servers,numOfClients):
for i in range(0, len(ranges)):
dp.send_msg(createFourthTableFlow(ranges[i], i, dp,servers,numOfClients))<|fim_prefix|># repo: lironsc/ORange path: /ORange1_LoadBalancers/Project1/Controller/Split/RidsTable.p... | code_fim | hard | {
"lang": "python",
"repo": "lironsc/ORange",
"path": "/ORange1_LoadBalancers/Project1/Controller/Split/RidsTable.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lironsc/ORange path: /ORange1_LoadBalancers/Project1/Controller/Split/RidsTable.py
import Flow,Range
from ryu.ofproto import ofproto_v1_3
#This file contains all the logic for populating the last table, used for the balancing of traffic
<|fim_suffix|> ofproto=ofproto_v1_3
parser = datapa... | code_fim | medium | {
"lang": "python",
"repo": "lironsc/ORange",
"path": "/ORange1_LoadBalancers/Project1/Controller/Split/RidsTable.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: warehouse-picking-automation-challenges/team_pfn path: /json-examples/item_distribution_generator.py
# Copyright 2016 Preferred Networks, 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 ... | code_fim | hard | {
"lang": "python",
"repo": "warehouse-picking-automation-challenges/team_pfn",
"path": "/json-examples/item_distribution_generator.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>bins = ["bin_A","bin_B","bin_C","bin_D","bin_E","bin_F","bin_G","bin_H","bin_I","bin_J","bin_K","bin_L"]
nums = [2,7,4,1,4,3,2,9,5,2,3,4]
for piyo in range(100):
items = np.random.permutation(items)
nums = np.random.permutation(nums)
hoge = {}
hoge['bin_contents'] = {}
cnt = 0
... | code_fim | hard | {
"lang": "python",
"repo": "warehouse-picking-automation-challenges/team_pfn",
"path": "/json-examples/item_distribution_generator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def execute_running(self):
win_eval = robocup.WindowEvaluator(main.context())
win_eval.debug = True
windows, best = win_eval.eval_pt_to_our_goal(main.ball().pos)<|fim_prefix|># repo: tcontis/robocup-software path: /soccer/gameplay/plays/testing/debug_window_evaluator.py
import... | code_fim | medium | {
"lang": "python",
"repo": "tcontis/robocup-software",
"path": "/soccer/gameplay/plays/testing/debug_window_evaluator.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> super().__init__(continuous=True)
self.add_transition(behavior.Behavior.State.start,
behavior.Behavior.State.running, lambda: True,
'immediately')
def execute_running(self):
win_eval = robocup.WindowEvaluator(main.contex... | code_fim | medium | {
"lang": "python",
"repo": "tcontis/robocup-software",
"path": "/soccer/gameplay/plays/testing/debug_window_evaluator.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tcontis/robocup-software path: /soccer/gameplay/plays/testing/debug_window_evaluator.py
import play
import behavior
import main
import robocup
import constants
import time
import math
<|fim_suffix|> self.add_transition(behavior.Behavior.State.start,
behavior.Be... | code_fim | hard | {
"lang": "python",
"repo": "tcontis/robocup-software",
"path": "/soccer/gameplay/plays/testing/debug_window_evaluator.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: thanhchatvn/addons path: /hw_escpos_network_printer/controllers/main.py
# -*- coding: utf-8 -*-
import logging
import time
from odoo import http
from . import hw_escpos as hwEscpos
try:
from ..escpos import escpos as Escpos, exceptions as E, printer as Printer
except ImportError:
Escp... | code_fim | hard | {
"lang": "python",
"repo": "thanhchatvn/addons",
"path": "/hw_escpos_network_printer/controllers/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ define the printer to connect to """
connected = {'ip': self.ip, 'port': self.port}
return connected
def get_escpos_printer(self):
printers = None
if self.ip and self.port:
printers = self.connected_network_devices()
if printers:
... | code_fim | hard | {
"lang": "python",
"repo": "thanhchatvn/addons",
"path": "/hw_escpos_network_printer/controllers/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kaityo256/lammps_position path: /generate_config.py
import numpy as np
class Atom:
def __init__(self, x, y, z):
self.x = x
self.y = y
self.z = z
self.type = 1
self.vx = 0.0
self.vy = 0.0
self.vz = 0.0
<|fim_suffix|>if __n... | code_fim | hard | {
"lang": "python",
"repo": "kaityo256/lammps_position",
"path": "/generate_config.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> with open(filename, "w") as f:
f.write("Position Data\n\n")
f.write("{} atoms\n".format(len(atoms)))
f.write("1 atom types\n\n")
f.write(f"{lo} {hi} xlo xhi\n")
f.write(f"{lo} {hi} ylo yhi\n")
f.write(f"{lo} {hi} zlo zhi\n")
f.write("\n")
... | code_fim | medium | {
"lang": "python",
"repo": "kaityo256/lammps_position",
"path": "/generate_config.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chemprop/chemprop path: /scripts/examine_split_balance.py
import os
import pickle
from pprint import pprint
import sys
from typing_extensions import Literal
import numpy as np
from tap import Tap # pip install typed-argument-parser (https://github.com/swansonk14/typed-argument-parser)
sys.path... | code_fim | hard | {
"lang": "python",
"repo": "chemprop/chemprop",
"path": "/scripts/examine_split_balance.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def examine_split_balance(split_type: str):
results = []
for dataset in DATASETS:
# Load task names for the dataset
data_path = os.path.join(BASE, dataset, f'{dataset}.csv')
data = get_data(data_path)
# Get class balance ratios for full dataset
ratios = c... | code_fim | hard | {
"lang": "python",
"repo": "chemprop/chemprop",
"path": "/scripts/examine_split_balance.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> nonlocal calls
start = datetime.now()
result = func(*args, **kwargs)
print('Call ' + str(calls) + ' of ' + func.__name__, datetime.now() - start)
calls = calls + 1
return result
return wrapper<|fim_prefix|># repo: adrianoff/python_learning path: /fluent... | code_fim | easy | {
"lang": "python",
"repo": "adrianoff/python_learning",
"path": "/fluent_python_book/07-decorators/time_decorator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: adrianoff/python_learning path: /fluent_python_book/07-decorators/time_decorator.py
from datetime import datetime
def my_timeit(func):
calls = 1
<|fim_suffix|> nonlocal calls
start = datetime.now()
result = func(*args, **kwargs)
print('Call ' + str(calls) + '... | code_fim | easy | {
"lang": "python",
"repo": "adrianoff/python_learning",
"path": "/fluent_python_book/07-decorators/time_decorator.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Remediator that calls another Lambda function to remediate an alert.
"""
def __init__(self, lambda_client, alert_to_function_mapping):
self.lambda_client = lambda_client
self.alert_to_function_mapping = alert_to_function_mapping
def can_remediate(self, alert_notif... | code_fim | medium | {
"lang": "python",
"repo": "pimlock/macie-remediation-sam",
"path": "/code/src/macie_remediation/remediators.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pimlock/macie-remediation-sam path: /code/src/macie_remediation/remediators.py
import logging
from abc import abstractmethod
logger = logging.getLogger(__name__)
class Remediator:
"""
Interface for remediator.
It decides which alerts it can handle and then provides option to handl... | code_fim | hard | {
"lang": "python",
"repo": "pimlock/macie-remediation-sam",
"path": "/code/src/macie_remediation/remediators.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: shubham3121/PySyft-TensorFlow path: /syft_tensorflow/syft_types/tensor.py
import weakref
import tensorflow as tf
import syft
from syft.generic.tensor import AbstractTensor
from syft.workers.base import BaseWorker
from syft.generic.pointers.pointer_tensor import PointerTensor
from syft.exceptio... | code_fim | hard | {
"lang": "python",
"repo": "shubham3121/PySyft-TensorFlow",
"path": "/syft_tensorflow/syft_types/tensor.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> big_repr = False
if self.tags is not None and len(self.tags):
big_repr = True
out += "\n\tTags: "
for tag in self.tags:
out += str(tag) + " "
if self.description is not None:
big_repr ... | code_fim | hard | {
"lang": "python",
"repo": "shubham3121/PySyft-TensorFlow",
"path": "/syft_tensorflow/syft_types/tensor.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return out
@classmethod
def handle_func_command(cls, command):
"""
Operates as a router for functions. A function call always starts
by being handled here and 3 scenarii must be considered:
Real TensorFlow tensor:
The arguments of the funct... | code_fim | hard | {
"lang": "python",
"repo": "shubham3121/PySyft-TensorFlow",
"path": "/syft_tensorflow/syft_types/tensor.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == "__main__":
reader = BarCodeReader(0x03eb, 0x6201, 84, 6, should_reset=True)
reader.initialize()
print(reader.read().strip())
reader.disconnect()<|fim_prefix|># repo: hacker-h/pyusb-keyboard-alike path: /lindy_bar_code_scanner.py
from keyboard_alike import reader
class Ba... | code_fim | hard | {
"lang": "python",
"repo": "hacker-h/pyusb-keyboard-alike",
"path": "/lindy_bar_code_scanner.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hacker-h/pyusb-keyboard-alike path: /lindy_bar_code_scanner.py
from keyboard_alike import reader
class BarCodeReader(reader.Reader):
<|fim_suffix|>
if __name__ == "__main__":
reader = BarCodeReader(0x03eb, 0x6201, 84, 6, should_reset=True)
reader.initialize()
print(reader.read().str... | code_fim | hard | {
"lang": "python",
"repo": "hacker-h/pyusb-keyboard-alike",
"path": "/lindy_bar_code_scanner.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: grvsmth/anno2-storage path: /anno2/urls.py
"""anno2 URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/1.10/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a U... | code_fim | hard | {
"lang": "python",
"repo": "grvsmth/anno2-storage",
"path": "/anno2/urls.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>urlpatterns = [
url(r'^accounts/', include('registration.backends.default.urls')),
url(r'^admin/', admin.site.urls),
url(r'^auth/token$', views.token, name='token'),
url(r'^store/', include(router.urls)),
url(
r'^api-auth/',
include('rest_framework.urls', namespace='res... | code_fim | hard | {
"lang": "python",
"repo": "grvsmth/anno2-storage",
"path": "/anno2/urls.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if opçãoInicial == "4":
print('Certo, você escolheu a opção: "Atualizar cadastro"\n')
id4 = input("Qual o ID do cadastro que você quer atualizar? ")
resposta4 = input("Qual informação você quer atualizar? \n1 - Nome\n2 - Idade\n3 - Endereço\n4 - Whatsapp\n\nResponda:")
cursor4 = "UPD... | code_fim | hard | {
"lang": "python",
"repo": "tiagodevss/CRUD-python",
"path": "/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tiagodevss/CRUD-python path: /main.py
#imports
import pymysql
import InterfaceCRUD
#PySimpleGUI
InterfaceCRUD
#MySQL
conexão = pymysql.connect(
host = "localhost",
user = "root",
password = "",
database = "clientes"
)
cursor = conexão.cursor()
#script
print("\n... | code_fim | hard | {
"lang": "python",
"repo": "tiagodevss/CRUD-python",
"path": "/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Parameters
----------
url : str
URL to the dataset in CSV format.
Returns
-------
pandas.DataFrame
The dataset.
"""
print(f'fetching dataset at {url}')
return pandas_impl.read_csv(url)<|fim_prefix|># repo: dfarrow0/delphi-epidata path: /src/acquisition/co... | code_fim | hard | {
"lang": "python",
"repo": "dfarrow0/delphi-epidata",
"path": "/src/acquisition/covid_hosp/network.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dfarrow0/delphi-epidata path: /src/acquisition/covid_hosp/network.py
# third party
import pandas
import requests
class Network:
METADATA_URL = (
'https://healthdata.gov/api/3/action/package_show'
'?id=83b4a668-9321-4d8c-bc4f-2bef66c49050&page=0'
)
def fetch_metadata(requests_imp... | code_fim | medium | {
"lang": "python",
"repo": "dfarrow0/delphi-epidata",
"path": "/src/acquisition/covid_hosp/network.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print(f'fetching metadata at {Network.METADATA_URL}')
return requests_impl.get(Network.METADATA_URL).json()
def fetch_dataset(url, pandas_impl=pandas):
"""Download and return a dataset.
Parameters
----------
url : str
URL to the dataset in CSV format.
Returns
---... | code_fim | medium | {
"lang": "python",
"repo": "dfarrow0/delphi-epidata",
"path": "/src/acquisition/covid_hosp/network.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: KaloyankerR/python-fundamentals-repository path: /Assignments/Lists Basics/Exercise/06. Survival of the Biggest.py
int_list = input().split(' ')
n = int(input())
<|fim_suffix|>for i in range(n):
int_list.remove(min(int_list))
print(int_list)<|fim_middle|>for i in range(0, len(int_list)):
... | code_fim | medium | {
"lang": "python",
"repo": "KaloyankerR/python-fundamentals-repository",
"path": "/Assignments/Lists Basics/Exercise/06. Survival of the Biggest.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>for i in range(n):
int_list.remove(min(int_list))
print(int_list)<|fim_prefix|># repo: KaloyankerR/python-fundamentals-repository path: /Assignments/Lists Basics/Exercise/06. Survival of the Biggest.py
int_list = input().split(' ')
n = int(input())
<|fim_middle|>for i in range(0, len(int_list)):
... | code_fim | medium | {
"lang": "python",
"repo": "KaloyankerR/python-fundamentals-repository",
"path": "/Assignments/Lists Basics/Exercise/06. Survival of the Biggest.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: data61/MP-SPDZ path: /compile.py
#!/usr/bin/env python3
# ===== Compiler usage instructions =====
#
# ./compile.py input_file
#
# will compile Programs/Source/input_file.mpc onto
# Programs/Bytecode/input_file.bc and Programs/Schedules/input_file.sch
#
# (run with --help for more options)
#... | code_fim | medium | {
"lang": "python",
"repo": "data61/MP-SPDZ",
"path": "/compile.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> compiler.prep_compile()
if compiler.options.profile:
import cProfile
p = cProfile.Profile().runctx("compilation(compiler)", globals(), locals())
p.dump_stats(compiler.args[0] + ".prof")
p.print_stats(2)
else:
compilation(compiler)
if __name__ == "__ma... | code_fim | hard | {
"lang": "python",
"repo": "data61/MP-SPDZ",
"path": "/compile.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: steinitzu/spoffy path: /spoffy/io/requests.py
from typing import Optional
import requests
from spoffy.models import Token
from spoffy.client.base import SyncClient, ClientCommon
from spoffy.sansio import Request, Response
from spoffy.spotify import SyncSpotify
class RequestsClient(SyncClient)... | code_fim | hard | {
"lang": "python",
"repo": "steinitzu/spoffy",
"path": "/spoffy/io/requests.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> resp = self.session.request(
method=request.method,
url=request.url,
data=request.body,
headers=request.headers,
)
response = Response(
request, resp.status_code, resp.headers, resp.content
)
response.raise... | code_fim | hard | {
"lang": "python",
"repo": "steinitzu/spoffy",
"path": "/spoffy/io/requests.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> *,
session: Optional[requests.Session] = None,
access_token: Optional[str] = None,
token: Optional[Token] = None,
client_id: Optional[str] = None,
client_secret: Optional[str] = None,
redirect_uri: Optional[str] = None,
scope: Optional[str] = None,
state: Optional[str] ... | code_fim | hard | {
"lang": "python",
"repo": "steinitzu/spoffy",
"path": "/spoffy/io/requests.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> #let external paint program go
syncf=open(AppFiles.sync_filepath, 'w')
syncf.write("extpaint")
syncf.close()
return {'PASS_THROUGH'}
### Switch Modes
class IMAGE_OT_blenderextpaint_autorefresh_switch_mode(bpy.types.O... | code_fim | hard | {
"lang": "python",
"repo": "zNightlord/Blender-ExternalPaintReloaded",
"path": "/Blender/Paint_Operators.py",
"mode": "spm",
"license": "Zlib",
"source": "the-stack-v2"
} |
<|fim_suffix|> #make sure autorefresh is not already active
if context.scene.blenderextpaint_autorefresh_active==True: return {'CANCELLED'}
context.scene.blenderextpaint_autorefresh_active=True
IMAGE_OT_blenderextpaint_autorefresh_status.status = "Active: external paint"
#setup fi... | code_fim | hard | {
"lang": "python",
"repo": "zNightlord/Blender-ExternalPaintReloaded",
"path": "/Blender/Paint_Operators.py",
"mode": "spm",
"license": "Zlib",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zNightlord/Blender-ExternalPaintReloaded path: /Blender/Paint_Operators.py
import os
import bpy
from mathutils import *
#from .UI_Panel import IMAGEUI_PT_Paint
### Helper things
##########################
#class that sets up files
##########################
class AppFiles:
sync... | code_fim | hard | {
"lang": "python",
"repo": "zNightlord/Blender-ExternalPaintReloaded",
"path": "/Blender/Paint_Operators.py",
"mode": "psm",
"license": "Zlib",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: otus-devops-2019-02/devopscourses_infra path: /venv/lib/python2.7/site-packages/yamllint/rules/document_start.py
# -*- coding: utf-8 -*-
# Copyright (C) 2016 Adrien Vergé
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public Licens... | code_fim | hard | {
"lang": "python",
"repo": "otus-devops-2019-02/devopscourses_infra",
"path": "/venv/lib/python2.7/site-packages/yamllint/rules/document_start.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> this:
is: [a, document]
...
the following code snippet would **FAIL**:
::
---
this:
is: [a, document]
...
"""
import yaml
from yamllint.linter import LintProblem
ID = 'document-start'
TYPE = 'token'
CONF = {'present': bool}
DEFAULT = {'present': True}
def che... | code_fim | hard | {
"lang": "python",
"repo": "otus-devops-2019-02/devopscourses_infra",
"path": "/venv/lib/python2.7/site-packages/yamllint/rules/document_start.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @abstractmethod
def update(self, model: Model):
pass<|fim_prefix|># repo: df424/ml path: /modules/optimizers/optimizer.py
from abc import ABC, abstractmethod
from ml.models import Model
<|fim_middle|>class Optimizer(ABC):
| code_fim | easy | {
"lang": "python",
"repo": "df424/ml",
"path": "/modules/optimizers/optimizer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: df424/ml path: /modules/optimizers/optimizer.py
from abc import ABC, abstractmethod
from ml.models import Model
<|fim_suffix|> @abstractmethod
def update(self, model: Model):
pass<|fim_middle|>class Optimizer(ABC):
| code_fim | easy | {
"lang": "python",
"repo": "df424/ml",
"path": "/modules/optimizers/optimizer.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> pass
# TODO: parameter types:
# sess is of type Session
# global_step is of type Tensor or integer
def save(self,
sess: Any,
save_path: str,
global_step: Any = None,
latest_filename: Optional[str]=None,
meta_gr... | code_fim | medium | {
"lang": "python",
"repo": "acvander/tensorflow-stubs",
"path": "/tensorflow-stubs/train/__init__.pyi",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: acvander/tensorflow-stubs path: /tensorflow-stubs/train/__init__.pyi
from typing import Any, Optional
def import_meta_graph(path: str) -> Any:
pass
# Saver class defined here
# https://github.com/tensorflow/tensorflow/blob/28340a4b12e286fe14bb7ac08aebe325c3e150b4/tensorflow/python/training... | code_fim | medium | {
"lang": "python",
"repo": "acvander/tensorflow-stubs",
"path": "/tensorflow-stubs/train/__init__.pyi",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.chain = [Block(None, Transaction(100, "genesis", "satoshi"))]
def lastBlock(self):
return self.chain[-1]
def addBlock(self, transaction: Transaction, senderPublicKey: str, signature: str):
self.verifier = hashlib.sha256(senderPublicKey, signature)
newB... | code_fim | hard | {
"lang": "python",
"repo": "karan-ksrk/Block-Chain",
"path": "/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: karan-ksrk/Block-Chain path: /main.py
import datetime
import hashlib
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.primitives.asymmetric import rsa
class Transaction:
def __init__(self, amount, sender, receiver):
self.amount = amount
... | code_fim | medium | {
"lang": "python",
"repo": "karan-ksrk/Block-Chain",
"path": "/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self.chain[-1]
def addBlock(self, transaction: Transaction, senderPublicKey: str, signature: str):
self.verifier = hashlib.sha256(senderPublicKey, signature)
newBlock = Block(self.lastBlock().hash, transaction)
self.chain.append(newBlock)
class Wallet:... | code_fim | hard | {
"lang": "python",
"repo": "karan-ksrk/Block-Chain",
"path": "/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: leokarlin/LaSO path: /oneshot/cnnvisualizer/tightcrop.py
# coding: utf-8
# In[ ]:
# Awesome image patch finder,
# Due to http://stackoverflow.com/questions/9525313
import os
import sys
import numpy
import random
import numpy as np
import scipy.ndimage as ndimage
import scipy.spatial as spati... | code_fim | hard | {
"lang": "python",
"repo": "leokarlin/LaSO",
"path": "/oneshot/cnnvisualizer/tightcrop.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def input_image_filename(basename, iter, zunit):
# return ('/data/vision/torralba/gigaSUN/www/unit_annotation/result_segments_iterations' +
return ('/data/vision/torralba/scratch2/davidbau/iccv' +
'/%s_iter_%d/html/image/conv5-%04d.jpg' % (basename, iter, zunit))
def output_image_filename... | code_fim | hard | {
"lang": "python",
"repo": "leokarlin/LaSO",
"path": "/oneshot/cnnvisualizer/tightcrop.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def slice_to_bbox(slices):
for s in slices:
dy, dx = s[:2]
yield BBox(dx.start, dy.start, dx.stop+1, dy.stop+1)
def remove_overlaps(bboxes):
'''
Return a set of BBoxes which contain the given BBoxes.
When two BBoxes overlap, replace both with the minimal BBox that contains... | code_fim | hard | {
"lang": "python",
"repo": "leokarlin/LaSO",
"path": "/oneshot/cnnvisualizer/tightcrop.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self):
pass<|fim_prefix|># repo: danrg/RGT-tool path: /src/RGT/gridMng/template/session/resultRatingWeightTableData.py
class ResultRatingWeightTableData(object):
<|fim_middle|> headers = None
table = None
weights = None
weightColorMap = None
tableHead = N... | code_fim | medium | {
"lang": "python",
"repo": "danrg/RGT-tool",
"path": "/src/RGT/gridMng/template/session/resultRatingWeightTableData.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: danrg/RGT-tool path: /src/RGT/gridMng/template/session/resultRatingWeightTableData.py
class ResultRatingWeightTableData(object):
<|fim_suffix|> def __init__(self):
pass<|fim_middle|> headers = None
table = None
weights = None
weightColorMap = None
tableHead = N... | code_fim | medium | {
"lang": "python",
"repo": "danrg/RGT-tool",
"path": "/src/RGT/gridMng/template/session/resultRatingWeightTableData.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Since this .pth-file does not reside on a site-dir, we need to add
# it manually
import sys
if not getattr(sys, 'frozen', None):
import site
import os
site.addsitedir(os.path.join(os.path.dirname(__file__), 'nspkg2-pkg'))
import nspkg2.aaa
import nspkg2.bbb.zzz
import nspkg2.ccc<|fim_prefix... | code_fim | medium | {
"lang": "python",
"repo": "dvt32/mypymodoro",
"path": "/resources/PyInstaller-3.0/tests/old_suite/import/test_nspkg2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dvt32/mypymodoro path: /resources/PyInstaller-3.0/tests/old_suite/import/test_nspkg2.py
#-----------------------------------------------------------------------------
# Copyright (c) 2013, PyInstaller Development Team.
#
# Distributed under the terms of the GNU General Public License with excepti... | code_fim | medium | {
"lang": "python",
"repo": "dvt32/mypymodoro",
"path": "/resources/PyInstaller-3.0/tests/old_suite/import/test_nspkg2.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> num_covered = 0
# embedding for special symbols
init_embedding[0][:] = np.zeros(emblen)
for word in vocab:
if word in word2vec_map:
vec = word2vec_map[word]
if len(vec) != emblen:
raise ValueError("word2vec dimension doesn't match.")
... | code_fim | hard | {
"lang": "python",
"repo": "czyssrs/GloREPlus",
"path": "/code/data_utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: czyssrs/GloREPlus path: /code/data_utils.py
import itertools
import numpy as np
import random
import os
import yaml
import gzip
import unicodedata
import gensim
import tensorflow as tf
import codecs
import operator
import zipfile
from gensim.models import KeyedVectors
from hyperparams import Hype... | code_fim | hard | {
"lang": "python",
"repo": "czyssrs/GloREPlus",
"path": "/code/data_utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # embedding for special symbols
init_embedding[0][:] = np.zeros(emblen)
for word in vocab:
if word in word2vec_map:
vec = word2vec_map[word]
if len(vec) != emblen:
raise ValueError("word2vec dimension doesn't match.")
init_embedding[... | code_fim | hard | {
"lang": "python",
"repo": "czyssrs/GloREPlus",
"path": "/code/data_utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return rtl_estimator
def visualize(estimator, input_img_path, output_dir):
"""Visualizes trained estimator."""
# This example pulls one channel, also would make sense to convert to gray
im = plt.imread(input_img_path)[:, :, 2]
im_pixels = _pixels(im)
input_fn = tf.compat.v1.estimator.inputs... | code_fim | hard | {
"lang": "python",
"repo": "neilteng/lattice",
"path": "/examples/image_compression.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: neilteng/lattice path: /examples/image_compression.py
# Copyright 2018 The TensorFlow Lattice Authors.
#
# 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://w... | code_fim | hard | {
"lang": "python",
"repo": "neilteng/lattice",
"path": "/examples/image_compression.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> data_quality_job_input = {
"endpointInput": {
"endpointName": Endpoint.outputs["sagemaker_resource_name"],
"localPath": "/opt/ml/processing/input/endpoint",
"s3DataDistributionType": "FullyReplicated",
"s3InputMode": "File",
}
}
... | code_fim | hard | {
"lang": "python",
"repo": "kubeflow/pipelines",
"path": "/samples/contrib/aws-samples/hosting_model_monitor_pipeline/hosting_model_monitor_pipeline.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> monitoring_schedule_config = {
"monitoringType": "DataQuality",
"scheduleConfig": {"scheduleExpression": "cron(0 * ? * * *)"},
"monitoringJobDefinitionName": DataQualityJobDefinition.outputs[
"sagemaker_resource_name"
],
}
MonitoringSchedule = sagem... | code_fim | hard | {
"lang": "python",
"repo": "kubeflow/pipelines",
"path": "/samples/contrib/aws-samples/hosting_model_monitor_pipeline/hosting_model_monitor_pipeline.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kubeflow/pipelines path: /samples/contrib/aws-samples/hosting_model_monitor_pipeline/hosting_model_monitor_pipeline.py
#!/usr/bin/env python3
import kfp
import sagemaker
import os
from kfp import components
from kfp import dsl
from datetime import datetime
sagemaker_Model_op = components.load_c... | code_fim | hard | {
"lang": "python",
"repo": "kubeflow/pipelines",
"path": "/samples/contrib/aws-samples/hosting_model_monitor_pipeline/hosting_model_monitor_pipeline.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.name = "LIGHTNINGS"
self.definitions = lightning
self.parents = []
self.childen = []
self.properties = []
self.jsondata = {}
self.basic = ['lightning']<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/otherforms/_lightnings.py
#calss header
class _LIGHTNINGS():
<|fim_mi... | code_fim | easy | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/otherforms/_lightnings.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/otherforms/_lightnings.py
#calss header
class _LIGHTNINGS():
<|fim_suffix|> self.parents = []
self.childen = []
self.properties = []
self.jsondata = {}
self.basic = ['lightning']<|fim_middle|> def __init__(self,):
self.name = "LIGHTNINGS"
s... | code_fim | medium | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/otherforms/_lightnings.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vaxin/facenet path: /facenet/align/align.py
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from scipy import misc
import sys
import os
import argparse
import tensorflow as tf
import numpy as np
from facenet import facenet
from facenet... | code_fim | medium | {
"lang": "python",
"repo": "vaxin/facenet",
"path": "/facenet/align/align.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> try:
img = misc.imread(image_path)
except (IOError, ValueError, IndexError) as e:
errorMessage = '{}: {}'.format(image_path, e)
print(errorMessage)
else:
if img.ndim < 2:
print('Unable to align "%s"' % image_path)
return
if img.ndim == 2:
img = facenet.to_rgb(i... | code_fim | hard | {
"lang": "python",
"repo": "vaxin/facenet",
"path": "/facenet/align/align.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># count number of total missclassified
miss_classified = 0
miss_classified_list = []
test_data.iat[0, 5]
for i in range(0, test_data_input.shape[0]):
test_prediction1 = perceptron.predict(test_data_input[i])
miss_classified_list.append(test_prediction1)
if test_prediction1 != test_data.iat[i, ... | code_fim | medium | {
"lang": "python",
"repo": "AlparslanErol/Perceptron",
"path": "/Perceptron.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AlparslanErol/Perceptron path: /Perceptron.py
import numpy as np
import pandas as pd
class Perceptron(object):
def __init__(self, no_of_inputs, threshold=100, learning_rate=0.01):
self.threshold = threshold
self.learning_rate = learning_rate
self.weights = np.zeros... | code_fim | hard | {
"lang": "python",
"repo": "AlparslanErol/Perceptron",
"path": "/Perceptron.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># take a input from user (UI input of Data)
listFromUser = [0, 0, 0, 0]
for i in range(0, 4):
userData = float(input('enter i th value : '))
listFromUser[i] = userData
print('the data you have Provided is\n=> ', listFromUser)
output_prediction = perceptron.predict(listFromUser)
if output_predict... | code_fim | hard | {
"lang": "python",
"repo": "AlparslanErol/Perceptron",
"path": "/Perceptron.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
:ivar inputs: list[Artifact]
:ivar outputs: list[Artifact]
"""
def __init__(self, inputs, outputs):
self.inputs = inputs
self.outputs = outputs
@property
def output(self):
"""
:type: Artifact
:raise Exception: If there are multiple o... | code_fim | hard | {
"lang": "python",
"repo": "SemaphoreSolutions/s4-clarity-lib",
"path": "/s4/clarity/iomaps.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
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