text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> tls = Tools()
cr = redis.StrictRedis(host='192.168.99.100', port=6379, db=0)
tojsde_json = str(json)
cr.set('cr_task_0',tojsde_json)<|fim_prefix|># repo: galena503/SCR path: /flask/flask_controller.py
from manipulator.tools import Tools
import redis
<|fim_middle|>class F... | code_fim | easy | {
"lang": "python",
"repo": "galena503/SCR",
"path": "/flask/flask_controller.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: galena503/SCR path: /flask/flask_controller.py
from manipulator.tools import Tools
import redis
<|fim_suffix|>
def timer_change(self,json):
tls = Tools()
cr = redis.StrictRedis(host='192.168.99.100', port=6379, db=0)
tojsde_json = str(json)
cr.set('cr_task_0'... | code_fim | easy | {
"lang": "python",
"repo": "galena503/SCR",
"path": "/flask/flask_controller.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def encode(self, detections: List[Detection], img: np.ndarray):
imgs = []
for detection in detections:
box = detection.box
patch = crop(img, (box[0] + box[2]) / 2, (box[1] + box[3]) / 2, int(max(box[2] - box[0], box[3] - box[1])))
patch = cv2.resize(... | code_fim | hard | {
"lang": "python",
"repo": "linkinpark213/online-mot-by-detection",
"path": "/mot/encode/patch.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, resize_to: Tuple[int, int], name: str = 'patch', **kwargs):
super(ImagePatchEncoder, self).__init__()
self.resize_to: Tuple[int, int] = resize_to
self.name: str = name
def encode(self, detections: List[Detection], img: np.ndarray):
imgs = []
... | code_fim | medium | {
"lang": "python",
"repo": "linkinpark213/online-mot-by-detection",
"path": "/mot/encode/patch.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: linkinpark213/online-mot-by-detection path: /mot/encode/patch.py
import cv2
import numpy as np
from typing import List, Tuple
from mot.utils import crop
from mot.structures import Detection
from .encode import Encoder, ENCODER_REGISTRY
<|fim_suffix|> super(ImagePatchEncoder, self).__init... | code_fim | medium | {
"lang": "python",
"repo": "linkinpark213/online-mot-by-detection",
"path": "/mot/encode/patch.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return transport.source.type == fis_types[name]
is_identify = Signal()
is_dma_activate = Signal()
read_ndwords = Signal(max=sectors2dwords(2**16))
dwords_counter = Counter(max=sectors2dwords(2**16))
self.submodules += dwords_counter
read_done = Signal()
self.sync += \
If(from_tx.read... | code_fim | hard | {
"lang": "python",
"repo": "mogorman/misoc",
"path": "/misoclib/mem/litesata/core/command/__init__.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> d2h_error = Signal()
clr_d2h_error = Signal()
set_d2h_error = Signal()
self.sync += \
If(clr_d2h_error,
d2h_error.eq(0)
).Elif(set_d2h_error,
d2h_error.eq(1)
)
read_error = Signal()
clr_read_error = Signal()
set_read_error = Signal()
self.sync += \
If(clr_read_error,
... | code_fim | hard | {
"lang": "python",
"repo": "mogorman/misoc",
"path": "/misoclib/mem/litesata/core/command/__init__.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mogorman/misoc path: /misoclib/mem/litesata/core/command/__init__.py
from misoclib.mem.litesata.common import *
tx_to_rx = [
("write", 1),
("read", 1),
("identify", 1),
("count", 16)
]
rx_to_tx = [
("dma_activate", 1),
("d2h_error", 1)
]
class LiteSATACommandTX(Module):
def __init__(sel... | code_fim | hard | {
"lang": "python",
"repo": "mogorman/misoc",
"path": "/misoclib/mem/litesata/core/command/__init__.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> 1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in
the documentation and/o... | code_fim | hard | {
"lang": "python",
"repo": "elephant-track/elephant-server",
"path": "/elephant-core/elephant/util/ellipsoid.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: elephant-track/elephant-server path: /elephant-core/elephant/util/ellipsoid.py
# Copyright (c) 2020, Ko Sugawara
# 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. Redi... | code_fim | hard | {
"lang": "python",
"repo": "elephant-track/elephant-server",
"path": "/elephant-core/elephant/util/ellipsoid.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> bounding_shape = lower_right_top - upper_left_bottom + 1
d_lim, r_lim, c_lim = np.ogrid[0:float(bounding_shape[0]),
0:float(bounding_shape[1]),
0:float(bounding_shape[2])]
d_org, r_org, c_org = scaled_ce... | code_fim | hard | {
"lang": "python",
"repo": "elephant-track/elephant-server",
"path": "/elephant-core/elephant/util/ellipsoid.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chaostoolkit-attic/chaosplatform-auth path: /tests/fixtures/fake_storage.py
from typing import Any, Dict, NoReturn
<|fim_suffix|>
class MyAuthStorage(BaseAuthStorage):
def __init__(self, config: Dict[str, Any]):
self.some_flag = True
def release(self) -> NoReturn:
self.s... | code_fim | medium | {
"lang": "python",
"repo": "chaostoolkit-attic/chaosplatform-auth",
"path": "/tests/fixtures/fake_storage.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.some_flag = True
def release(self) -> NoReturn:
self.some_flag = False<|fim_prefix|># repo: chaostoolkit-attic/chaosplatform-auth path: /tests/fixtures/fake_storage.py
from typing import Any, Dict, NoReturn
from chaosplt_auth.storage.interface import BaseAuthStorage
__all__ = ... | code_fim | medium | {
"lang": "python",
"repo": "chaostoolkit-attic/chaosplatform-auth",
"path": "/tests/fixtures/fake_storage.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def release(self) -> NoReturn:
self.some_flag = False<|fim_prefix|># repo: chaostoolkit-attic/chaosplatform-auth path: /tests/fixtures/fake_storage.py
from typing import Any, Dict, NoReturn
from chaosplt_auth.storage.interface import BaseAuthStorage
<|fim_middle|>__all__ = ["MyAuthStorage"]... | code_fim | medium | {
"lang": "python",
"repo": "chaostoolkit-attic/chaosplatform-auth",
"path": "/tests/fixtures/fake_storage.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Signals that a message or object failed to validate."""
pass<|fim_prefix|># repo: SecConNet/mahiru path: /mahiru/definitions/errors.py
"""Different kinds of errors that may occur."""
<|fim_middle|>
class ValidationError(Exception):
| code_fim | easy | {
"lang": "python",
"repo": "SecConNet/mahiru",
"path": "/mahiru/definitions/errors.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SecConNet/mahiru path: /mahiru/definitions/errors.py
"""Different kinds of errors that may occur."""
<|fim_suffix|> """Signals that a message or object failed to validate."""
pass<|fim_middle|>class ValidationError(Exception):
| code_fim | easy | {
"lang": "python",
"repo": "SecConNet/mahiru",
"path": "/mahiru/definitions/errors.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aurule/npc path: /legacy/npc/npc/linters/human.py
"""
Linter for verifying human character files
Checks for a number of problems that are specific to human characters. The only
public entry point is the lint function.
"""
<|fim_suffix|> """
Verify the more complex elements in a human she... | code_fim | medium | {
"lang": "python",
"repo": "aurule/npc",
"path": "/legacy/npc/npc/linters/human.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Args:
character (dict): Character data to lint
fix (bool): Whether to automatically correct certain problems
strict (bool): Whether to report non-critical errors and omissions
Returns:
List of problem descriptions. If no problems were found, the list will
b... | code_fim | medium | {
"lang": "python",
"repo": "aurule/npc",
"path": "/legacy/npc/npc/linters/human.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Check that they have a vice and a virtue
if strict:
problems.extend(nwod.lint_vice_virtue(data))
if dirty and data:
with open(character.path, 'w', newline='\n') as char_file:
char_file.write(data)
return problems<|fim_prefix|># repo: aurule/npc path: /legac... | code_fim | hard | {
"lang": "python",
"repo": "aurule/npc",
"path": "/legacy/npc/npc/linters/human.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: danielyoung/pancake-hipchat-bot path: /src/bot.py
import requests
import re
import random
import inspect
import json
from time import time,sleep
from ec2_helper import EC2Helper
from simple_hipchat import HipChat
from urllib2 import HTTPError
# For Arnold
from _arnold_phrases import ARNOLD_PHRAS... | code_fim | hard | {
"lang": "python",
"repo": "danielyoung/pancake-hipchat-bot",
"path": "/src/bot.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self.postMessage(room_name, 'Something went wrong')
def __cmdGetRandomChuckPhrase(self, room_name):
message = "Can't connect to Chuck API =("
params = {'limitTo': '[nerdy]'}
r = requests.get('http://api.icndb.com/jokes/random', params=params)
if r.stat... | code_fim | hard | {
"lang": "python",
"repo": "danielyoung/pancake-hipchat-bot",
"path": "/src/bot.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.postMessage(room_name, message)
def __cmdGetRandomCatGIF(self, room_name):
message = "Can't connect to cat API =("
params = {'format': 'xml', 'type': 'gif'}
r = requests.get('http://thecatapi.com/api/images/get', params=params)
if r.status_code == 200:
... | code_fim | hard | {
"lang": "python",
"repo": "danielyoung/pancake-hipchat-bot",
"path": "/src/bot.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bmeg/cwltool path: /mypy-stubs/networkx/algorithms/flow/maxflow.pyi
# Stubs for networkx.algorithms.flow.maxflow (Python 3.5)
#
# NOTE: This dynamically typed stub was automatically generated by stubgen.
from typing import Any, Optional
from .preflowpush import preflow_push
<|fim_suffix|> f... | code_fim | hard | {
"lang": "python",
"repo": "bmeg/cwltool",
"path": "/mypy-stubs/networkx/algorithms/flow/maxflow.pyi",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def minimum_cut_value(
flowG, _s, _t, capacity: str = ..., flow_func: Optional[Any] = ..., **kwargs
): ...<|fim_prefix|># repo: bmeg/cwltool path: /mypy-stubs/networkx/algorithms/flow/maxflow.pyi
# Stubs for networkx.algorithms.flow.maxflow (Python 3.5)
#
# NOTE: This dynamically typed stub was autom... | code_fim | hard | {
"lang": "python",
"repo": "bmeg/cwltool",
"path": "/mypy-stubs/networkx/algorithms/flow/maxflow.pyi",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: flaurencin/UbiquitiManager path: /UbiquitiManager/UbiConfigManager.py
import time
import string
import random
from io import StringIO
from crypt import crypt
from functools import reduce
from UbiquitiManager.UbiExceptions import UbiConfigTest
from UbiquitiManager.UbiExceptions import UbiBadFirmwa... | code_fim | hard | {
"lang": "python",
"repo": "flaurencin/UbiquitiManager",
"path": "/UbiquitiManager/UbiConfigManager.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return reduce(lambda data, key: data[key], k_list, self.config_dict)
def _set_to_dict(self, k_list, value):
self._get_from_dict(k_list[:-1])[k_list[-1]] = value
def config_text_to_dict(self):
'''
Takes the text configuation and convert it to dict.
'''
... | code_fim | hard | {
"lang": "python",
"repo": "flaurencin/UbiquitiManager",
"path": "/UbiquitiManager/UbiConfigManager.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: City-of-Helsinki/parkkihubi path: /parkings/migrations/0025_parking_check.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11.22 on 2019-07-13 07:49
from __future__ import unicode_literals
from django.contrib.gis.db.models.fields import PointField
from django.contrib.postgres.fields.jsonb impo... | code_fim | hard | {
"lang": "python",
"repo": "City-of-Helsinki/parkkihubi",
"path": "/parkings/migrations/0025_parking_check.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
('parkings', '0024_permitlookupitem_index'),
]
operations = [
migrations.CreateModel(
name='ParkingCheck',
fields=[
('id', models.AutoField(
auto_created=True, primary_key=True,
se... | code_fim | hard | {
"lang": "python",
"repo": "City-of-Helsinki/parkkihubi",
"path": "/parkings/migrations/0025_parking_check.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Assuming model_checkpoint_path looks something like:
# /my-favorite-path/eye_train/model.ckpt-0,
# extract global_step from it.
global_step = ckpt.model_checkpoint_path.split('/')[-1].split('-')[-1]
else:
print('No checkpoint file found')
_, top_indices = sess.ru... | code_fim | hard | {
"lang": "python",
"repo": "callofdutyops/YXH2016724098982",
"path": "/predict_one.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: callofdutyops/YXH2016724098982 path: /predict_one.py
from PIL import Image
import tensorflow as tf
import eye_model_predict
FLAGS = tf.app.flags.FLAGS
tf.app.flags.DEFINE_string('checkpoint_dir', '/tmp/eye_train',
"""Directory where to read model checkpoints.""")
width... | code_fim | hard | {
"lang": "python",
"repo": "callofdutyops/YXH2016724098982",
"path": "/predict_one.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>@tingbot.every(seconds=5)
def refresh():
reqUrl = baseUrl
response = urllib.urlopen(reqUrl)
state['stats'] = json.loads(response.read())
def showMain():
screen.fill(color=(26,26,26))
screen.rectangle(
xy=(0,16),
align='left',
size=(320,31),
color... | code_fim | hard | {
"lang": "python",
"repo": "tlk999/tingbot",
"path": "/sabnzb.tingapp/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tlk999/tingbot path: /sabnzb.tingapp/main.py
# coding: utf-8
# v1.0.1
import tingbot
from tingbot import *
import urllib, json
from datetime import datetime
import time
state = {}
screenList = {
0: 'main'
}
currentScreen = 0
state['screen'] = screenList[currentScreen]
baseUrl = "http://" ... | code_fim | hard | {
"lang": "python",
"repo": "tlk999/tingbot",
"path": "/sabnzb.tingapp/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> reqUrl = baseUrl
response = urllib.urlopen(reqUrl)
state['stats'] = json.loads(response.read())
def showMain():
screen.fill(color=(26,26,26))
screen.rectangle(
xy=(0,16),
align='left',
size=(320,31),
color=(255,165,0),
)
screen.text(... | code_fim | hard | {
"lang": "python",
"repo": "tlk999/tingbot",
"path": "/sabnzb.tingapp/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# # Reshape for simplicity. Merge first two dimensions into one.
# target_c_i = i_true
# predicted_c_i = i_pred
# target_shape = tf.shape(target_c_i)
# pred_shape = tf.shape(predicted_c_i)
#
# print("t shape", target_c_i)
# print("p shape", predicted_c_i)
#
# # Permute pred... | code_fim | hard | {
"lang": "python",
"repo": "GianKiMoon/Mask_RCNN",
"path": "/synthpod/loss.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# # Reshape for simplicity. Merge first two dimensions into one.
# target_c_i = i_true
# predicted_c_i = i_pred
# target_shape = tf.shape(target_c_i)
# pred_shape = tf.shape(predicted_c_i)
#
# print("t shape", target_c_i)
# print("p shape", predicted_c_i)
#
# # Permu... | code_fim | hard | {
"lang": "python",
"repo": "GianKiMoon/Mask_RCNN",
"path": "/synthpod/loss.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GianKiMoon/Mask_RCNN path: /synthpod/loss.py
import keras.backend as K
import keras
import tensorflow as tf
from keras.utils import to_categorical
def m_loss(x_true, x_pred):
return K.mean(K.categorical_crossentropy(x_true, x_pred))
def i_loss(i_true, i_pred):
# # Flat tensors
# i... | code_fim | hard | {
"lang": "python",
"repo": "GianKiMoon/Mask_RCNN",
"path": "/synthpod/loss.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == 'gsdl2.tests':
from gsdl2.tests.test_utils.run_tests import run
elif __name__ == '__main__':
import os
import sys
pkg_dir = os.path.split(os.path.abspath(__file__))[0]
parent_dir, pkg_name = os.path.split(pkg_dir)
is_pygame_pkg = (pkg_name == 'tests' and
... | code_fim | hard | {
"lang": "python",
"repo": "Yardanico/gsdl2",
"path": "/test/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Yardanico/gsdl2 path: /test/__init__.py
"""gsdl2 unit test suite package
Exports function run()
A quick way to run the test suite package from the command line
is by importing the go submodule:
python -m "import gsdl2.tests" [<test options>]
Command line option --help displays a usage message... | code_fim | hard | {
"lang": "python",
"repo": "Yardanico/gsdl2",
"path": "/test/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>"""
if __name__ == 'gsdl2.tests':
from gsdl2.tests.test_utils.run_tests import run
elif __name__ == '__main__':
import os
import sys
pkg_dir = os.path.split(os.path.abspath(__file__))[0]
parent_dir, pkg_name = os.path.split(pkg_dir)
is_pygame_pkg = (pkg_name == 'tests' and
... | code_fim | hard | {
"lang": "python",
"repo": "Yardanico/gsdl2",
"path": "/test/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>9m/xGk5W01jSpYc8NMZI2x9ArD9a73wH8DdL8LX0OqardDU9QiIeFfL2xRN64OSxHYnGPTODXrGc0tACYrlvGnw+0LxzZLFqkLLcRAiG6hOJI/bPcexzXVUUAfNV3+zf4iSU/YtZ0qaPs03mRn8grfzq5p37NmoPIp1TxDbRJnkW0LSE/i23H5GvonFFADXdY0Z3IVVGSSeAK+CrW1lvbuG1t1LzTyLHGo/iZiAB+Zr7j8R6Odf8ADt/pIu5LQXkJhaaNQWVTwRg+oyPoa8v+H/wSk8I+MxrF/qNvfQ28bfZQkZRhI... | code_fim | hard | {
"lang": "python",
"repo": "fabioued/imageme",
"path": "/imageme.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fabioued/imageme path: /imageme.py
PER_ROW = 3
## Width in pixels of thumnbails generated with PIL
THUMBNAIL_WIDTH = 800
## Base64 data for an image notifying user of an unsupported image type
UNSUPPORTED_IMAGE_TYPE_DATA = 'data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgcGBQgHBwcJ... | code_fim | hard | {
"lang": "python",
"repo": "fabioued/imageme",
"path": "/imageme.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fabioued/imageme path: /imageme.py
rs, force_no_processing=False):
"""
Create an index file in the given location, supplying known lists of
present image files and subdirectories.
@param {String} root_dir - The root directory of the entire crawl. Used to
ascertain whether... | code_fim | hard | {
"lang": "python",
"repo": "fabioued/imageme",
"path": "/imageme.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>))
hh3cAFCNotifyPrefix = MibIdentifier((1, 3, 6, 1, 4, 1, 25506, 2, 85, 2, 0))
hh3cDDosAttackStart = NotificationType((1, 3, 6, 1, 4, 1, 25506, 2, 85, 2, 0, 1)).setObjects(("HH3C-AFC-MIB", "hh3cDDosAttackTargetIP"), ("HH3C-AFC-MIB", "hh3cDDosAttackType"), ("HH3C-AFC-MIB", "hh3cDDosAttackPolicy"), ("HH3C-A... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp-with-texts/HH3C-AFC-MIB.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: agustinhenze/mibs.snmplabs.com path: /pysnmp-with-texts/HH3C-AFC-MIB.py
#
# PySNMP MIB module HH3C-AFC-MIB (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/HH3C-AFC-MIB
# Produced by pysmi-0.3.4 at Wed May 1 13:25:34 2019
# On host DAVWANG4-M-1475 plat... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp-with-texts/HH3C-AFC-MIB.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> emat = exp_mat.todense()
l1 = np.sum(emat, axis=1)
l2 = np.sqrt(np.sum(np.square(emat), axis=1))
del(emat)
weight_est = (1/(mz_range**0.5))*np.sum(gradient_time**0.5 - (l1/(l2+1e-6)))/(gradient_time**0.5 -1)
return np.around(weight_est, 5)<|fim_prefix|># repo: pasrawin/ProteomicMSD path: /mNMF... | code_fim | hard | {
"lang": "python",
"repo": "pasrawin/ProteomicMSD",
"path": "/mNMF07_WeightEstimation.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pasrawin/ProteomicMSD path: /mNMF07_WeightEstimation.py
from __future__ import division
import numpy as np
def weight_estimation(exp_mat, prot_peptcount, globalparam_list):
<|fim_suffix|> emat = exp_mat.todense()
l1 = np.sum(emat, axis=1)
l2 = np.sqrt(np.sum(np.square(emat), axis=1))
d... | code_fim | hard | {
"lang": "python",
"repo": "pasrawin/ProteomicMSD",
"path": "/mNMF07_WeightEstimation.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> fake_logits = discriminator_fn(fake_data)
if isinstance(fake_logits, (list, tuple)):
fake_logits = fake_logits[0]
fake_loss = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(
logits=fake_logits, labels=tf.zeros_like(fake_logits)))
d_loss = real_loss + fake_loss
... | code_fim | hard | {
"lang": "python",
"repo": "arita37/texar",
"path": "/texar/tf/losses/adv_losses.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: arita37/texar path: /texar/tf/losses/adv_losses.py
# Copyright 2018 The Texar Authors. 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
#
# htt... | code_fim | hard | {
"lang": "python",
"repo": "arita37/texar",
"path": "/texar/tf/losses/adv_losses.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> Returns:
A tuple `(generator_loss, discriminator_loss)` each of which is
a scalar Tensor, loss to be minimized.
"""
real_logits = discriminator_fn(real_data)
if isinstance(real_logits, (list, tuple)):
real_logits = real_logits[0]
real_loss = tf.reduce_mean(tf.nn... | code_fim | hard | {
"lang": "python",
"repo": "arita37/texar",
"path": "/texar/tf/losses/adv_losses.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def vm_start(self, params: dict) -> Tuple["Status", dict]:
"""
Start a VM.
Parameters
----------
params : dict
Flat dictionary of (key, value) pairs of tunable parameters.
Returns
-------
result : (Status, dict={})
... | code_fim | hard | {
"lang": "python",
"repo": "microsoft/MLOS",
"path": "/mlos_bench/mlos_bench/services/types/vm_provisioner_type.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: microsoft/MLOS path: /mlos_bench/mlos_bench/services/types/vm_provisioner_type.py
#
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
#
"""
Protocol interface for VM provisioning operations.
"""
from typing import Tuple, Protocol, runtime_checkable, TYPE_CHECKING
if TYPE_... | code_fim | hard | {
"lang": "python",
"repo": "microsoft/MLOS",
"path": "/mlos_bench/mlos_bench/services/types/vm_provisioner_type.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Get the portfolio weights for hierarachical risk parity method.
@param covariance: list/ndarray
The covariance matrix.
@param order: list
The order represented by the linkage matrix.
@return weights: ndarray
portfolio weights for hierar... | code_fim | hard | {
"lang": "python",
"repo": "Karagul/Hierarchical-Portfolio-Construction",
"path": "/Supplied code/Hierarchical_Risk_Parity.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Karagul/Hierarchical-Portfolio-Construction path: /Supplied code/Hierarchical_Risk_Parity.py
# Standard imports.
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from scipy import stats
from scipy.cluster.hierarchy import dendrogram, linkage
from scipy.spatial.distance ... | code_fim | hard | {
"lang": "python",
"repo": "Karagul/Hierarchical-Portfolio-Construction",
"path": "/Supplied code/Hierarchical_Risk_Parity.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert host.package('ansible').is_installed<|fim_prefix|># repo: ssato/ansible-role-nw-backup-config path: /molecule/default/tests/test_default.py
import os
import testinfra.utils.ansible_runner
<|fim_middle|>testinfra_hosts = testinfra.utils.ansible_runner.AnsibleRunner(
os.environ['MOLECULE_I... | code_fim | hard | {
"lang": "python",
"repo": "ssato/ansible-role-nw-backup-config",
"path": "/molecule/default/tests/test_default.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ssato/ansible-role-nw-backup-config path: /molecule/default/tests/test_default.py
import os
import testinfra.utils.ansible_runner
<|fim_suffix|> assert host.package('ansible').is_installed<|fim_middle|>testinfra_hosts = testinfra.utils.ansible_runner.AnsibleRunner(
os.environ['MOLECULE_I... | code_fim | hard | {
"lang": "python",
"repo": "ssato/ansible-role-nw-backup-config",
"path": "/molecule/default/tests/test_default.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>## TODO: change the imports in jupyer notebook<|fim_prefix|># repo: keli95566/svd-with-threshold path: /setup.py
from setuptools import setup
from Cython.Build import cythonize
eigen_path = ['/usr/local/include/eigen3']
<|fim_middle|>setup(
name="tSVD",
version=" 0.1 ",
ext_modules=cythoniz... | code_fim | medium | {
"lang": "python",
"repo": "keli95566/svd-with-threshold",
"path": "/setup.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: keli95566/svd-with-threshold path: /setup.py
from setuptools import setup
from Cython.Build import cythonize
eigen_path = ['/usr/local/include/eigen3']
<|fim_suffix|>## TODO: change the imports in jupyer notebook<|fim_middle|>setup(
name="tSVD",
version=" 0.1 ",
ext_modules=cythoniz... | code_fim | medium | {
"lang": "python",
"repo": "keli95566/svd-with-threshold",
"path": "/setup.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pabigot/pyxb path: /pyxb/__init__.py
http://www.w3.org/XML/Schema>} Bindings, and is pronounced
"pixbee". It enables translation between XML instance documents and
Python objects following rules specified by an XML Schema document.
This is the top-level entrypoint to the PyXB system. Importing... | code_fim | hard | {
"lang": "python",
"repo": "pabigot/pyxb",
"path": "/pyxb/__init__.py",
"mode": "psm",
"license": "Python-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pabigot/pyxb path: /pyxb/__init__.py
translation between XML instance documents and
Python objects following rules specified by an XML Schema document.
This is the top-level entrypoint to the PyXB system. Importing this
gets you all the L{exceptions<pyxb.exceptions_.PyXBException>}, and
L{pyxb... | code_fim | hard | {
"lang": "python",
"repo": "pabigot/pyxb",
"path": "/pyxb/__init__.py",
"mode": "psm",
"license": "Python-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """C{True} iff validation should be performed when creating a document
from a binding instance.
This applies at invocation of
L{toDOM()<pyxb.binding.basis._TypeBinding_mixin.toDOM>}.
L{toxml()<pyxb.binding.basis._TypeBinding_mixin.toDOM>} invokes C{toDOM()}."""
... | code_fim | hard | {
"lang": "python",
"repo": "pabigot/pyxb",
"path": "/pyxb/__init__.py",
"mode": "spm",
"license": "Python-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bsc-wdc/compss path: /compss/programming_model/bindings/python/src/pycompss/tests/unittests/runtime/test_object_tracker.py
#!/usr/bin/python
#
# Copyright 2002-2022 Barcelona Supercomputing Center (www.bsc.es)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not us... | code_fim | hard | {
"lang": "python",
"repo": "bsc-wdc/compss",
"path": "/compss/programming_model/bindings/python/src/pycompss/tests/unittests/runtime/test_object_tracker.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_clean_object_tracker():
object_tracker = ObjectTracker()
do = DummyObject()
_, _ = object_tracker.track(do)
object_tracker.clean_object_tracker()
assert len(object_tracker.pending_to_synchronize) == 0
assert len(object_tracker.file_names) == 0
assert len(object_tracke... | code_fim | hard | {
"lang": "python",
"repo": "bsc-wdc/compss",
"path": "/compss/programming_model/bindings/python/src/pycompss/tests/unittests/runtime/test_object_tracker.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_pending_to_synchronize():
object_tracker = ObjectTracker()
do = DummyObject()
do_id, _ = object_tracker.track(do)
# The object is being tracked
pending = object_tracker.is_pending_to_synchronize(do_id)
assert (
pending is True
), "The object must be pending to... | code_fim | hard | {
"lang": "python",
"repo": "bsc-wdc/compss",
"path": "/compss/programming_model/bindings/python/src/pycompss/tests/unittests/runtime/test_object_tracker.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>### convert sources into objects
def Automatic_Object_Helper(env,source,libraries):
if type(source)!=str: return source # assume it's already an object
cppdefines_reversed=env['CPPDEFINES'][::-1]
cpppath_reversed=env['CPPPATH_HIDDEN'][::-1]
for lib in libraries:
if lib['filter'].s... | code_fim | hard | {
"lang": "python",
"repo": "alekamca/mgpcg-poisson",
"path": "/src/Scripts/scons/SConstruct",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alekamca/mgpcg-poisson path: /src/Scripts/scons/SConstruct
nment.Clone,'Copy')
## override platform specific library names
if env['PLATFORM'].startswith('win32'):
env.Replace(compile_headers=0)
### platform
if env['ARCH']=='':
if os.environ.has_key('PLATFORM'): env['ARCH']=os.environ['P... | code_fim | hard | {
"lang": "python",
"repo": "alekamca/mgpcg-poisson",
"path": "/src/Scripts/scons/SConstruct",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> b,d=os.path.abspath(base).split(os.sep),os.path.abspath(directory).split(os.sep)
i=0
while i<len(b) and i<len(d) and b[i]==d[i]: i+=1
path=map(lambda x:'..',b[i:])+d[i:]
if len(path)==0: return "."
return os.path.join(*path)
template_file,binary,paths=so... | code_fim | hard | {
"lang": "python",
"repo": "alekamca/mgpcg-poisson",
"path": "/src/Scripts/scons/SConstruct",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>image = utils.get_env('ISO',
os.path.join(consts.IMAGE_FOLDER, f'{env_variables["cluster_name"]}-installer-image.iso')).strip()
env_variables["iso_download_path"] = image
env_variables["num_nodes"] = env_variables["num_workers"] + env_variables["num_masters"]
@pytest.fixture(scope... | code_fim | hard | {
"lang": "python",
"repo": "skramling/assisted-test-infra",
"path": "/discovery-infra/tests/conftest.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: skramling/assisted-test-infra path: /discovery-infra/tests/conftest.py
import logging
import os
from distutils import util
from pathlib import Path
import pytest
from test_infra import assisted_service_api, consts, utils
qe_env = False
# TODO changes it
if os.environ.get('NODE_ENV') == 'QE_VM'... | code_fim | hard | {
"lang": "python",
"repo": "skramling/assisted-test-infra",
"path": "/discovery-infra/tests/conftest.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@pytest.fixture(scope="session")
def api_client():
logging.info(f'--- SETUP --- api_client\n')
yield get_api_client()
def get_api_client(offline_token=env_variables['offline_token'], **kwargs):
url = env_variables['remote_service_url']
if not url:
url = utils.get_local_assisted_... | code_fim | medium | {
"lang": "python",
"repo": "skramling/assisted-test-infra",
"path": "/discovery-infra/tests/conftest.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_save_image(self):
self.image.save_image()
images = Image.objects.all()
self.assertTrue(len(images) > 0)
def test_delete_image(self):
self.image.save_image()
self.image.delete_image()
images = Image.objects.all()
... | code_fim | hard | {
"lang": "python",
"repo": "Anabella1109/MyGram",
"path": "/mygram/tests.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def setUp(self):
self.profile=Profile(id=123,photo='Rwanda',bio='Kigali')
self.image=Image(id=1,image='@heroo',name='koko',caption="koko koko koko okruuuuuu",likes=2,profile=self.profile)
self.comment=Comment(id=1,comment='food',image=self.image)
... | code_fim | hard | {
"lang": "python",
"repo": "Anabella1109/MyGram",
"path": "/mygram/tests.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Anabella1109/MyGram path: /mygram/tests.py
from django.test import TestCase
from .models import Image,Profile,Comment
class ImageTestClass(TestCase):
def setUp(self):
self.profile=Profile(id=1,photo='Rwanda',bio='Kigali')
self.image=Image(id=1,image='@heroo'... | code_fim | hard | {
"lang": "python",
"repo": "Anabella1109/MyGram",
"path": "/mygram/tests.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> eval_results.append(
[eval_game.total_positive_reward,
eval_game.total_step_to_positive_reward])
eval_logs.append(eval_log_in_episode)
eval_res = self.agg_eval_results(eval_results)
# collect and save evaluation results
np.s... | code_fim | hard | {
"lang": "python",
"repo": "yinxusen/dqn-zork",
"path": "/python/deepdnd/agent.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # start training
t = start_t
cnt_action = np.zeros(self.hp.n_actions)
# count visited room during whole training process
self.debug("master room name: {}".format(room_name))
assert room_name != "", "initial room name is empty"
if self.visited_rooms i... | code_fim | hard | {
"lang": "python",
"repo": "yinxusen/dqn-zork",
"path": "/python/deepdnd/agent.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yinxusen/dqn-zork path: /python/deepdnd/agent.py
trainable_vars)
else:
pass
else:
pass
for variable in trainable_vars:
# shape is an array of tf.Dimension
shape = variable.get_s... | code_fim | hard | {
"lang": "python",
"repo": "yinxusen/dqn-zork",
"path": "/python/deepdnd/agent.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self._entries[signature]
def signatures_by_last_lemma(self, lemma):
return self._bylast.get(lemma) or ()
def shortest_path_decoding(self, sentence_lemmas, start=0, in_gap=False, max_gap_length=None):
'''
Use Dijkstra's algorithm to search a sentence... | code_fim | hard | {
"lang": "python",
"repo": "nelson-liu/lexical-semantic-recognition",
"path": "/scripts/streusle2.0_scripts/pyutil/corpus/mwe_lexicons.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def load(self, entries):
iln = 1
for entry in entries:
self._read_entry(entry)
iln += 1
self._bylast = dict(self._bylast) # convert from defaultdict
def loadJSON(self, jsonF, more=False):
iln = 1
for ln in jsonF:
en... | code_fim | hard | {
"lang": "python",
"repo": "nelson-liu/lexical-semantic-recognition",
"path": "/scripts/streusle2.0_scripts/pyutil/corpus/mwe_lexicons.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nelson-liu/lexical-semantic-recognition path: /scripts/streusle2.0_scripts/pyutil/corpus/mwe_lexicons.py
'''
Created on Jul 19, 2013
@author: Nathan Schneider (nschneid)
'''
from __future__ import print_function, division, absolute_import
import sys, os, re, fileinput, codecs, json
from collecti... | code_fim | hard | {
"lang": "python",
"repo": "nelson-liu/lexical-semantic-recognition",
"path": "/scripts/streusle2.0_scripts/pyutil/corpus/mwe_lexicons.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert len(data) == 7
assert list(data.x.size()) == [data.num_nodes, 3703]
assert list(data.y.size()) == [data.num_nodes]
assert data.y.max() + 1 == 6
assert data.train_mask.sum() == 6 * 20
assert data.val_mask.sum() == 500
assert data.test_mask.sum(... | code_fim | hard | {
"lang": "python",
"repo": "Cyanogenoid/fspool",
"path": "/graphs/test/datasets/test_planetoid.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert data.contains_isolated_nodes()
assert not data.contains_self_loops()
assert data.is_undirected()
shutil.rmtree(root)<|fim_prefix|># repo: Cyanogenoid/fspool path: /graphs/test/datasets/test_planetoid.py
import sys
import random
import os.path as osp
import shutil
from... | code_fim | hard | {
"lang": "python",
"repo": "Cyanogenoid/fspool",
"path": "/graphs/test/datasets/test_planetoid.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Cyanogenoid/fspool path: /graphs/test/datasets/test_planetoid.py
import sys
import random
import os.path as osp
import shutil
from torch_geometric.datasets import Planetoid
from torch_geometric.data import DataLoader
<|fim_suffix|> root = osp.join('/', 'tmp', str(random.randrange(sys.maxsiz... | code_fim | medium | {
"lang": "python",
"repo": "Cyanogenoid/fspool",
"path": "/graphs/test/datasets/test_planetoid.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TheEagerLearner/Simple-Programs path: /Python-Programs/Internshala-course-data-scraper/program.py
from bs4 import BeautifulSoup
import requests
data=requests.get("https://trainings.internshala.com/?utm_source=is_web_internshala-menu-dropdown1").text
<|fim_suffix|>div=soup.find_all("div",class_=... | code_fim | easy | {
"lang": "python",
"repo": "TheEagerLearner/Simple-Programs",
"path": "/Python-Programs/Internshala-course-data-scraper/program.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>for i in div:
print(i.find("h4").text+" - "+i.find("p").text)
print()<|fim_prefix|># repo: TheEagerLearner/Simple-Programs path: /Python-Programs/Internshala-course-data-scraper/program.py
from bs4 import BeautifulSoup
import requests
<|fim_middle|>data=requests.get("https://trainings.internshal... | code_fim | medium | {
"lang": "python",
"repo": "TheEagerLearner/Simple-Programs",
"path": "/Python-Programs/Internshala-course-data-scraper/program.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NVIDIA/aistore path: /python/tests/botocore_common.py
#
# Copyright (c) 2018-2022, NVIDIA CORPORATION. All rights reserved.
#
# pylint: disable=missing-module-docstring
import io
import logging
import unittest
import boto3
from moto import mock_s3
from botocore.exceptions import ClientError
fr... | code_fim | hard | {
"lang": "python",
"repo": "NVIDIA/aistore",
"path": "/python/tests/botocore_common.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> with MightRedirect(self.redirect_errors_expected):
stream_str = io.BytesIO()
self.s3.download_fileobj(
self.control_bucket, self.control_object, stream_str
)
self.assertEqual(
stream_str.getvalue().decode(UTF_ENCODING)... | code_fim | hard | {
"lang": "python",
"repo": "NVIDIA/aistore",
"path": "/python/tests/botocore_common.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Args:
topo_file:
"""
try:
with open(topo_file) as jfile:
self._topology = json.loads(jfile.read())
except Exception as error:
print("Error %s " % error)
return
for switch in self._... | code_fim | hard | {
"lang": "python",
"repo": "amlight/ofp_sniffer",
"path": "/libs/core/topo_reader.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: amlight/ofp_sniffer path: /libs/core/topo_reader.py
"""
Class to read the topology.json file in use at AmLight
"""
import json
from libs.core.singleton import Singleton
class TopoReader(metaclass=Singleton):
"""
Under construction
"""
def __init__(self):
self.... | code_fim | hard | {
"lang": "python",
"repo": "amlight/ofp_sniffer",
"path": "/libs/core/topo_reader.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_link_aliases(self, dp_a, port_a, dp_z, port_z, option="Full"):
"""
:param dp_a:
:param port_a:
:param dp_z:
:param port_z:
:param option:
:return:
"""
dp_a = self.clear_dpid(dp_a)
dp_z = self.clear_dpid(dp_z)
... | code_fim | hard | {
"lang": "python",
"repo": "amlight/ofp_sniffer",
"path": "/libs/core/topo_reader.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ClydeSpace-GroundStation/GroundStation path: /GNURadio/Test_Files/Message_Test/top_block.py
#!/usr/bin/env python2
##################################################
# GNU Radio Python Flow Graph
# Title: Top Block
# Generated: Tue Mar 29 15:54:19 2016
############################################... | code_fim | hard | {
"lang": "python",
"repo": "ClydeSpace-GroundStation/GroundStation",
"path": "/GNURadio/Test_Files/Message_Test/top_block.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ##################################################
# Blocks
##################################################
self.ccsds_asm_deframer_pdu_0 = ccsds.asm_deframer_pdu(0, 1, False, 255)
self.blocks_vector_source_x_0_0 = blocks.vector_source_b(range(255)+range(255), Fa... | code_fim | hard | {
"lang": "python",
"repo": "ClydeSpace-GroundStation/GroundStation",
"path": "/GNURadio/Test_Files/Message_Test/top_block.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>for i in data:
try:
if int(i) > 16777215:
addr = socket.inet_ntoa(struct.pack("!I", int(i)))
else: raise
except:
continue
orig_data = orig_data.replace(i, addr)
print orig_data<|fim_prefix|># repo: vesche/snippets path: /python/cw/intip.py
#!/usr/bin/... | code_fim | medium | {
"lang": "python",
"repo": "vesche/snippets",
"path": "/python/cw/intip.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vesche/snippets path: /python/cw/intip.py
#!/usr/bin/env python
import re
import socket
import struct
import sys
<|fim_suffix|> orig_data = orig_data.replace(i, addr)
print orig_data<|fim_middle|>with open(sys.argv[1]) as f:
orig_data = f.read()
data = orig_data.split()
for i in da... | code_fim | hard | {
"lang": "python",
"repo": "vesche/snippets",
"path": "/python/cw/intip.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> orig_data = orig_data.replace(i, addr)
print orig_data<|fim_prefix|># repo: vesche/snippets path: /python/cw/intip.py
#!/usr/bin/env python
import re
import socket
import struct
import sys
with open(sys.argv[1]) as f:
orig_data = f.read()
data = orig_data.split()
<|fim_middle|>for i in da... | code_fim | medium | {
"lang": "python",
"repo": "vesche/snippets",
"path": "/python/cw/intip.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: french-ai/reinforcement path: /blobrl/networks/base_dueling_network.py
import abc
from blobrl.networks import BaseNetwork
class BaseDuelingNetwork(BaseNetwork):
@abc.abstractmethod
def __init__(self, network):
"""
:param network: network when we add Value head
... | code_fim | medium | {
"lang": "python",
"repo": "french-ai/reinforcement",
"path": "/blobrl/networks/base_dueling_network.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if isinstance(layers, list):
return [map_forward(layers, last_tensor, value_outputs) for layers in layers]
advantage = layers(last_tensor)
value = value_outputs(last_tensor)
return value + advantage - advantage.mean()
return map_forw... | code_fim | medium | {
"lang": "python",
"repo": "french-ai/reinforcement",
"path": "/blobrl/networks/base_dueling_network.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.last_range = new_range
def on_set_action(self, action_name, entities):
action = getattr(self, action_name, None)
result = None
if action is not None:
result = action(entities)
return result
def on_action(self, action_name, entities):... | code_fim | hard | {
"lang": "python",
"repo": "Veides/veidesbot_ros_example",
"path": "/veidesbot_platform/src/veidesbot_platform/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Veides/veidesbot_ros_example path: /veidesbot_platform/src/veidesbot_platform/__init__.py
import rospy
from geometry_msgs.msg import Twist
from veides_agent_ros.msg import Fact, Action, Trail
from veides_agent_ros.srv import (
TrailsRequest,
EventRequest,
)
from veidesbot_platform.states ... | code_fim | hard | {
"lang": "python",
"repo": "Veides/veidesbot_ros_example",
"path": "/veidesbot_platform/src/veidesbot_platform/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # TODO: reimplement to be odometry based
self.stop()
speed = self.speed_level * 200
angular_speed = speed * PI / 180
msg = self._create_twist()
msg.angular.z = direction * angular_speed
start_time = rospy.Time.now()
current_angle = 0
... | code_fim | hard | {
"lang": "python",
"repo": "Veides/veidesbot_ros_example",
"path": "/veidesbot_platform/src/veidesbot_platform/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class CreateLinkedRightFold(bpy.types.Operator, CreateFoldMixin):
"""Create right-side fold on selected edge (linked to previous fold)"""
bl_idname = "object.create_fold_linked_right"
bl_label = "Create Linked Right Fold"
@classmethod
def poll(cls, context):
return context.obj... | code_fim | hard | {
"lang": "python",
"repo": "Olliebrown/blender-origami-fold",
"path": "/foldOps.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Olliebrown/blender-origami-fold path: /foldOps.py
# Import system and blender modules
import bpy
# Import our own custom modules
from . import foldUtils
class CreateFoldMixin:
"""Create Fold Mixin Base"""
# Static class level variable
foldBones = []
foldCount = 0
def getSe... | code_fim | hard | {
"lang": "python",
"repo": "Olliebrown/blender-origami-fold",
"path": "/foldOps.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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