id stringlengths 3 8 | content stringlengths 100 981k |
|---|---|
192956 | import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import warnings
warnings.filterwarnings("ignore")
import yfinance as yf
yf.pdr_override()
import datetime as dt
symbol = 'AMD'
market = 'SPY'
num_of_years = 1
start = dt.date.today() - dt.timedelta(days=365*num_of_years)
end... |
192958 | import unittest
import numpy as np
import tensorflow as tf
import tensorflow_probability
import mvg_distributions.covariance_representations as cov_rep
from mvg_distributions.sqrt_gamma_gaussian import SqrtGammaGaussian, SparseSqrtGammaGaussian
from mvg_distributions.test.test_losses_base import LossesTestBase
tfd =... |
193002 | from delphi.GrFN.networks import GroundedFunctionNetwork
# -----------------------------------------------------------------------------
#
# -----------------------------------------------------------------------------
print('Running demo_generate_grfn.py')
source_fortran_file = 'DiscreteSIR-noarrays.f'
print(f' ... |
193006 | import requests
import pickle
from os import path
from pkg_resources import resource_filename
codechefs_languages_map = dict()
# leetcodes_supported_languages = ["cpp", "java", "python", "python3", "c", "csharp", "javascript", "ruby", "swift", "kotlin", "scala", "bash", "go"]
leetcodes_languages_map = dict()
# geeks... |
193019 | import torch
import torch.nn as nn
from models.baseModule import FuseBlock, BaseNet, Interp
class FuseNet(BaseNet):
def __init__(self):
super(FuseNet, self).__init__()
self.ConvIn = nn.Conv2d(in_channels=512, out_channels=512, kernel_size=1, stride=1, bias=False)
self.AADBlk1 = FuseBlock(c... |
193028 | import numpy as np
from tqdm.autonotebook import tqdm
import gc
import warnings
import sklearn.utils
_remove_cache = {}
def remove_retrain(nmask, X_train, y_train, X_test, y_test, attr_test, model_generator, metric, trained_model, random_state):
""" The model is retrained for each test sample with the important f... |
193068 | from __future__ import print_function
from __future__ import with_statement
from os.path import exists
from twisted.python import log, failure
from twisted.trial import unittest
from twisted.test import proto_helpers
from twisted.internet import defer, error
from txtorcon import TorControlProtocol, TorProtocolFactor... |
193154 | from typing import Dict
from botocore.paginate import Paginator
class ListEndpointsByPlatformApplication(Paginator):
def paginate(self, PlatformApplicationArn: str, PaginationConfig: Dict = None) -> Dict:
"""
Creates an iterator that will paginate through responses from :py:meth:`SNS.Client.list_e... |
193160 | from os import listdir, stat
from os.path import isfile, join
ignored=['websetup.html', 'jquery.js', 'selfarchive.py', 'boot.py', 'hal.py', 'run.sh']
for file in listdir('./'):
if file!='version.py' and file[0] != '.' and file not in ignored:
if not isfile(file):
continue
else:
... |
193185 | import logging
from surrortg.game_io import ConfigType
from .aruco_filter import ArucoFilter
from .aruco_source import ArucoDetector
DEFAULT_CAMERA = "/dev/video21"
CUSTOM_KEY = "custom"
NUM_MARKERS_KEY = "Number of aruco markers to find"
MIN_DISTANCE_KEY = "Minimum distance for detection (0 for any distance)"
IN_O... |
193201 | import torch
import logging
from utils.io import KeyphraseDataset
from torch.utils.data import DataLoader
def load_vocab(opt):
# load vocab
logging.info("Loading vocab from disk: %s" % (opt.vocab))
if not opt.custom_vocab_filename_suffix:
word2idx, idx2word, vocab = torch.load(opt.vocab + '/vocab.... |
193212 | import gym
import portfolio_management
import portfolio_management.paths as p
from portfolio_management.io_utilities import pickle_dump
def test_episode(download_and_pickle: bool = True):
database_name = 'test_episode'
if download_and_pickle:
from portfolio_management.data.manager import Manager
... |
193234 | from unittest import mock
import graphene
from django.utils.functional import SimpleLazyObject
from freezegun import freeze_time
from .....shipping.error_codes import ShippingErrorCode
from .....shipping.models import ShippingZone
from .....webhook.event_types import WebhookEventAsyncType
from .....webhook.payloads i... |
193249 | from typing import Optional # NOQA
import chainer
import numpy # NOQA
class GraphConvPredictor(chainer.Chain):
"""Wrapper class that combines a graph convolution and MLP."""
def __init__(
self,
graph_conv, # type: chainer.Link
mlp=None, # type: Optional[chainer.Link]
... |
193274 | import re
# a subset of PEP 440
_VERSION_REGEX = re.compile(
r"""
^\s*
v?
(?P<major>\d+)
(?:\.(?P<minor>\d+))?
(?:\.(?P<patch>\d+))?
\s*$
""",
re.VERBOSE | re.IGNORECASE,
)
class Version:
"""
Represents a major.minor.patch version string
"""
def __init__(self, major,... |
193296 | import pickle
'''
This module contains functions for saving and
loading .pkl files
'''
def save(object_, file_name):
'''
Saves an object into a file.
Parameters
----------
object_ : object
The object to save
file_name : str
The name of the file to save the object in.
Rai... |
193318 | from setuptools import find_packages
from setuptools import setup
import pymt5adapter
with open('README.md') as f:
readme = f.read()
with open('LICENSE') as f:
license = f.read()
setup(
name='pymt5adapter',
version=pymt5adapter.__version__.get('pymt5adapter'),
description='A drop in replacement w... |
193342 | from django.conf.urls import url
from . import views
urlpatterns = [
url(r'^daily_logs$', views.get_daily_logs, name='get_daily_logs'),
url(r'^logs_sample$', views.get_preview_data, name='get_preview_data'),
url(r'^date_range$', views.get_date_range, name='get_date_range'),
url(r'^column_data$', views... |
193428 | from socketclusterclient import Socketcluster
def onconnect(socket):
print "on connect got called"
def ondisconnect(socket):
print "on disconnect got called"
def onConnectError(socket, error):
print "On connect error got called"
def onSetAuthentication(socket, token):
print "Token received " + t... |
193436 | import rps.robotarium as robotarium
from rps.utilities import *
from rps.utilities.barrier_certificates import *
from rps.utilities.controllers import *
from rps.utilities.transformations import *
from reachGoal import reachGoal
from matplotlib import patches
import numpy as np
import time
N = 1
initial_conditions = n... |
193495 | import gym
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
from ray.rllib.utils import try_import_torch
from ray.rllib.utils.annotations import override
torch, nn = try_import_torch()
class OnlineLinearRegression(nn.Module):
def __init__(self, feature_d... |
193496 | from __future__ import division
import os
import numpy as np
import pprint
import tensorflow as tf
import tensorflow.contrib.slim as slim
import pickle, csv
from utils import *
from model import UNet3D, SurvivalVAE
flags = tf.app.flags
flags.DEFINE_integer("epoch", 4, "Epoch to train [4]")
flags.DEFINE_string("train_... |
193530 | from sklearn.linear_model import SGDClassifier
sgd = SGDClassifier(loss='modified_huber',shuffle=True,random_state=101)
sgd.fit(XA,yA)
yP = sgd.predict(XB) |
193559 | from setuptools import find_packages, setup
console_scripts = """
[console_scripts]
mapswipe_workers=mapswipe_workers.mapswipe_workers:cli
ms=mapswipe_workers.mapswipe_workers:cli
"""
with open("requirements.txt") as f:
requirements = f.read().splitlines()
setup(
name="mapswipe-workers",
... |
193615 | import pytest
from yt.data_objects.static_output import Dataset
from yt.geometry.grid_geometry_handler import GridIndex
from yt.loaders import load, load_simulation
from yt.utilities.exceptions import (
YTAmbiguousDataType,
YTSimulationNotIdentified,
YTUnidentifiedDataType,
)
from yt.utilities.object_regis... |
193650 | import os
import glob
import h5py
import tensorflow as tf
from utils.common import Notify
from .base_dataset import BaseDataset
class Imw2020(BaseDataset):
default_config = {
'num_parallel_calls': 10, 'truncate': None
}
def _init_dataset(self, **config):
print(Notify.INFO, "Initializing ... |
193658 | from collections import defaultdict
class Graph :
def __init__(self):
self.graph = defaultdict(list)
def add_edge(self , u , v):
self.graph[u].append(v)
def dfsUtil(self , s , vis):
stack = []
stack.append(s)
while(stack):
# Pop
... |
193690 | from os.path import dirname, join, realpath
import pytest
from numpy import array, dtype, nan
from numpy.testing import assert_array_equal, assert_equal
from pandas_plink import example_file_prefix, read_plink, read_plink1_bin
def test_read_plink():
datafiles = join(dirname(realpath(__file__)), "data_files")
... |
193705 | import six
import re
import logging
try:
import urllib.request as urllib2
except ImportError:
import urllib2
try:
import urllib.parse as urllib
except ImportError:
import urllib
try:
from http.cookiejar import CookieJar
except ImportError:
from cookielib import CookieJar
class Downloader(objec... |
193706 | import time
class FailUntilSucceeds:
ROBOT_LIBRARY_SCOPE = 'TESTCASE'
def __init__(self, times_to_fail=0):
self.times_to_fail = int(times_to_fail)
def set_times_to_fail(self, times_to_fail):
self.__init__(times_to_fail)
def fail_until_retried_often_enough(self, message="Hello", slee... |
193722 | import datetime
import os
import torch
import torch.nn.functional as F
from torch.utils.data import DataLoader
from tqdm import tqdm, trange
from common.evaluators.bow_evaluator import BagOfWordsEvaluator
from datasets.bow_processors.abstract_processor import StreamingSparseDataset
class BagOfWordsTrainer(object):
... |
193739 | from dlcliche.image import *
from lib_fat2019 import *
APPNAME = 'final'
conf.DURATION = 1
conf.AUG_LEVEL = 1
conf.CV = 0
conf.RELABEL = 'COOC_PROB'
conf.DATA = Path('/mnt/dataset/freesound-audio-tagging-2019')
conf.ROOT = Path('/mnt/dataset/fat2019_files')
conf.WORK = Path('/mnt/dataset/work/fat2019')
conf.MODEL =... |
193789 | import numpy as np
import unittest
import os
from openmdao.api import Problem, Group
from openmdao.utils.assert_utils import assert_near_equal, assert_check_partials
from pycycle.elements.shaft import Shaft
fpath = os.path.dirname(os.path.realpath(__file__))
ref_data = np.loadtxt(fpath + "/reg_data/shaft.csv",
... |
193798 | from torch.nn import CrossEntropyLoss
from torchkit.loss.dist_softmax import DistCrossEntropy
from torchkit.loss.focal import FocalLoss
from torchkit.loss.ddl import DDL
_loss_dict = {
'Softmax': CrossEntropyLoss(),
'DistCrossEntropy': DistCrossEntropy(),
'FocalLoss': FocalLoss(),
'DDL': DDL()
}
def ... |
193841 | from copy import deepcopy
import torch
from torch import nn, optim
import torch.nn.functional as F
from transformers import AdamW, BertConfig, BertForSequenceClassification
from model.scapt import SCAPT
class LabelSmoothLoss(nn.Module):
def __init__(self, smoothing=0.0):
super(LabelSmoothLos... |
193844 | import keras.layers
import tensorflow as tf
import runai.mp
import runai.utils
from . import coordinator
class Parallelised(keras.layers.Layer):
""" A helper class for MP-supported Keras layers
"""
def add_weights(self, name, shape, **kwargs):
""" Declare parallelised weights
# Argument... |
193869 | a=int(input("Enter a number"))
if a%2==0:
print(a,"is an Even Number")
else:
print(a,"is an Odd Number")
|
193874 | import logging
from dbnd._core.constants import TaskType
from dbnd._core.errors.friendly_error.task_execution import (
failed_to_assign_result,
failed_to_process_non_empty_result,
)
from dbnd._core.task.pipeline_task import PipelineTask
from dbnd._core.task.python_task import PythonTask
from dbnd._core.task.ta... |
193878 | import pytest
from kgx.graph.nx_graph import NxGraph
from kgx.graph_operations import (
remove_singleton_nodes,
fold_predicate,
unfold_node_property,
remap_edge_property,
remap_node_property,
remap_node_identifier,
)
def get_graphs1():
"""
Returns instances of defined graphs.
"""
... |
193881 | import numpy as np
import torch
import torch.nn as nn
from collections import OrderedDict
def summary(model, x, *args, **kwargs):
"""Summarize the given input model.
Summarized information are 1) output shape, 2) kernel shape,
3) number of the parameters and 4) operations (Mult-Adds)
Args:
mo... |
193983 | from shapes.square import Square
# Discover plugins
import offshoot
offshoot.discover("Shape", globals())
|
194062 | import pytest
import shutil
from common.version import DigitDotVersion
from indy_common.constants import APP_NAME
from indy_common.version import src_version_cls
from indy_node.utils.node_control_utils import (
NodeControlUtil, ShellError, DebianVersion
)
# TODO
# - conditionally skip all tests for non-debian sy... |
194128 | from enum import Enum
from typing import Any, List
class Err(Enum):
# temporary errors. Don't blacklist
DOES_NOT_EXTEND = -1
BAD_HEADER_SIGNATURE = -2
MISSING_FROM_STORAGE = -3
INVALID_PROTOCOL_MESSAGE = -4
SELF_CONNECTION = -5
INVALID_HANDSHAKE = -6
INVALID_ACK = -7
INCOMPATIBLE_P... |
194173 | import tkinter as tk
import traceback
import threading
import matplotlib
matplotlib.use('Agg')
import matplotlib.figure as figure
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
class Widget(tk.Frame):
def __init__(self, parent):
super().__init__(parent)
self.var = tk.S... |
194189 | import copy
import logging, os
import gettext as _gettext
from gettext import NullTranslations, GNUTranslations
import warnings
import tg
from tg.util import lazify
from tg._compat import PY3, string_type
log = logging.getLogger(__name__)
class LanguageError(Exception):
"""Exception raised when a problem occurs ... |
194234 | import collections
import sys
import character
iterations = int(sys.argv[1])
for msg, gen in [('With Thieves', character.Character),
('Without Thieves', character.LBBCharacter)]:
dist = collections.Counter(gen(testing=True).character_class['name']
for _ in range(iterations)... |
194244 | import matplotlib.pyplot as plt
import numpy as np
def inverse_normalization(X):
return X * 255.0
def plot_generated_batch(X_full, X_sketch, generator_model, epoch_num, dataset_name, batch_num):
# Generate images
X_gen = generator_model.predict(X_sketch)
X_sketch = inverse_normalization(X_sketch)
... |
194257 | from fasteve.io.base import Client, ConnectionException, DataLayer
from fasteve.core import config
from fastapi import HTTPException
from fasteve.resource import Resource
from pymongo.collection import Collection
from motor.motor_asyncio import AsyncIOMotorClient
from fasteve.core.utils import log, ObjectID
from typing... |
194262 | from django import forms
class SantaLogInputForm(forms.Form):
path = forms.CharField(initial="/var/db/santa/santa.log")
def get_filebeat_input(self):
return {"type": "log",
"paths": [self.cleaned_data["path"]]}
inputs = {"santa_log": {"name": "santa.log",
"fo... |
194299 | import os
import sys
from scripts.common.util import RunRemoteRepo, import_server_list
def main():
server_list_path = sys.argv[1]
server_list = import_server_list(server_list_path)
with RunRemoteRepo(server_list[0], 'dev') as rrr:
rrr.run("bash ~/PipeSwitch/scripts/figures/figure9/stop_next_resn... |
194317 | from rubicon_ml.client import Rubicon as SyncRubicon
from rubicon_ml.client.asynchronous import Config, Project
from rubicon_ml.exceptions import RubiconException
class Rubicon(SyncRubicon):
"""The asynchronous `rubicon` client's entry point.
Creates a `Config` and injects it into the client level
object... |
194363 | import twint
c = twint.Config()
c.Search = "twitter" # comment if you want to search a user instead
# c.Username = "dril" # comment out if want to search a user instead
c.Limit = 20 # must be multiple of 20
# c.Min_retweets = 50
c.Links = "exclude"
c.Verified = True
c.Lang = "en"
c.Popular_tweets = True
c.Custom... |
194388 | import pytest
import taichi as ti
@ti.test(experimental_real_function=True)
def test_function_without_return():
x = ti.field(ti.i32, shape=())
@ti.func
def foo(val: ti.i32):
x[None] += val
@ti.kernel
def run():
foo(40)
foo(2)
x[None] = 0
run()
assert x[None]... |
194423 | def insertion_sort(arr):
for i in range(1, len(arr)):
key = arr[i]
j = i - 1
while(j>=0 and arr[j]>key):
arr[j+1]=arr[j]
j = j - 1
arr[j+1] = key
return arr
def main():
arr = [6, 5, 8, 9, 3, 1, 4, 7, 2]
sorted_arr = insertion_sort(arr)
... |
194459 | from django import forms
from django.conf import settings
from django.contrib import admin
from django.core.exceptions import ValidationError
from django.db import transaction
from django.utils.translation import gettext_lazy as _
from geotrek.common.mixins import MergeActionMixin
from .models import (
Practice, D... |
194465 | from netgrasp import netgrasp
from netgrasp.database import database
from netgrasp.utils import pretty
def start(ng):
import os
pid = ng.is_running()
if pid:
ng.debugger.critical("Netgrasp is already running with pid %d.", (pid,))
ng.debugger.warning("Starting netgrasp...")
if os.getuid(... |
194469 | import torch
import torch.nn as nn
import torch.nn.functional as F
# import numpy as np
'''
reference from: https://github.com/auspicious3000/autovc/blob/master/model_vc.py
'''
class LinearNorm(torch.nn.Module):
def __init__(self, in_dim, out_dim, bias=True, w_init_gain='linear'):
super(LinearNorm, self)._... |
194505 | import os
import time
import traceback
from .pin import *
import logging
class Thingpin(object):
"""
Monitor GPIO pins and report to AWS IoT.
Each GPIO pin is associated with an AWS IoT Thing. As the GPIO pin
state changes the AWS IoT Thing state is published via MQTT. An example
is a GPIO pin co... |
194508 | import copy
import logging
import math
import pathlib
import types
from unittest import mock
import pytest
from connexion.apis.flask_api import Jsonifier
from connexion.exceptions import InvalidSpecification
from connexion.json_schema import resolve_refs
from connexion.middleware.security import SecurityOperation
from... |
194539 | import json, sys, os
sys.path.append("/opt/src")
from connectors.redis.redis_wrapper import RedisWrapper
class BaseRedisApplication:
def __init__(self, name, redis_address, port, redis_queue, logger, request_key_name=None, response_key_name=None, debug=False):
self.m_name = name
... |
194590 | import torch
import torch.nn as nn
from torchvision import datasets, transforms
IMAGES_PATH = 'image_path'
transform = transforms.Compose([transforms.Resize(256),
transforms.RandomCrop(224),
transforms.ToTensor()])
trainset = datasets.ImageFolder(IMAGES... |
194592 | import unittest
import torch
import torch.nn as nn
from torch.autograd import Variable
from wavenet.layers import *
from test.models import *
import numpy as np
class Test_dilation(unittest.TestCase):
def test_dilate(self):
input = Variable(torch.arange(0, 13).view(1, 1, 13))
dilated, _ = dilate(i... |
194601 | from base_learner import BaseLearner
from sklearn.svm import SVC
from sklearn.svm import LinearSVC
from sklearn.metrics import classification_report
from torch.utils.data import DataLoader
from smoke_video_dataset import SmokeVideoFeatureDataset
import joblib
import uuid
from util import *
import numpy as np
import tor... |
194605 | class Point(object):
def __init__(self, x, y):
self.x, self.y = x, y
class PointHash(object):
def __init__(self, x, y):
self.x, self.y = x, y
def __hash__(self):
return hash((self.x, self.y))
def __eq__(self, other):
return self.x == other.x and self.y == other.y
if... |
194621 | import numpy as np
from controller import Controller
from wrappers import visualize
from collections import defaultdict
from math import pi
GRID_SIZE = 0.5
ROTATION_STEPS = 4
def move_position(position, rotation):
if rotation == 0:
return (position[0] + 1, position[1])
elif rotation == 1:
retu... |
194644 | import torch, os
import yaml
from IPython import embed
def get_config(args):
configuration = dict(
SEED=1337, # random seed for reproduce results
INPUT_SIZE=[112, 112], # support: [112, 112] and [224, 224]
EMBEDDING_SIZE=512, # feature dimension
)
if args.workers_id == 'cpu' or... |
194654 | import numpy as np
from .other import clip_boxes
from .text_proposal_graph_builder import TextProposalGraphBuilder
class TextProposalConnector:
def __init__(self):
self.graph_builder=TextProposalGraphBuilder()
def group_text_proposals(self, text_proposals, scores, im_size):
graph=self... |
194662 | from typing import List
import numpy as np
import pandas as pd
from category_encoders.backward_difference import BackwardDifferenceEncoder
from category_encoders.cat_boost import CatBoostEncoder
from category_encoders.helmert import HelmertEncoder
from category_encoders.james_stein import JamesSteinEncoder
from catego... |
194754 | import numpy as np
import sys,os
import cv2
caffe_root = '/home/yaochuanqi/work/tmp/ssd/'
sys.path.insert(0, caffe_root + 'python')
import caffe
net_file= 'ssdlite/coco/deploy.prototxt'
caffe_model='ssdlite/deploy.caffemodel'
test_dir = "images"
caffe.set_mode_cpu()
net = caffe.Net(net_file,caffe_model,caf... |
194778 | from poop.hfdp.command.simpleremote.light import Light
class LightOffCommand:
def __init__(self, light: Light) -> None:
self.__light = light
def execute(self) -> None:
self.__light.off()
|
194810 | from unittest import mock
from kinto.core import authentication, utils
from kinto.core.testing import DummyRequest, unittest
from .support import BaseWebTest
class AuthenticationPoliciesTest(BaseWebTest, unittest.TestCase):
def test_basic_auth_is_accepted_by_default(self):
self.app.get(self.plural_url, ... |
194817 | from vnpy.api.oes.vnoes import OesApi_GetErrorMsg, OesApi_GetLastError
def error_to_str(code: int):
try:
# return error_codes[code]
return OesApi_GetErrorMsg(code)
except KeyError:
return "Unknown error code!"
def get_last_error():
code = OesApi_GetLastError()
return OesApi_G... |
194860 | import subprocess, re, os
import gzip, shutil
from smsgateway.config import *
def _logging_namer(name):
return name + ".gz"
def _logging_rotater(source, dest):
with open(source, "rb") as sf:
# data = sf.read()
# compressed = zlib.compress(data, 9)
with gzip.open(dest, 'wb') as df:
... |
194907 | f = open("io/data/file1")
print(f.readline())
print(f.readline(3))
print(f.readline(4))
print(f.readline(5))
print(f.readline())
# readline() on writable file
f = open("io/data/file1", "ab")
try:
f.readline()
except OSError:
print("OSError")
f.close()
|
194926 | import FWCore.ParameterSet.Config as cms
muonCSCStubPSet = cms.PSet(
#csc CLCT, central BX 7
cscCLCT = cms.PSet(
verbose = cms.int32(0),
inputTag = cms.InputTag("simCscTriggerPrimitiveDigis"),
minBX = cms.int32(6),
maxBX = cms.int32(8),
minNHitsChamber = cms.int32(4),
... |
194961 | import torch
from torchdiffeq import odeint_adjoint
from deprecated.anode.adjoint import odesolver_adjoint
from .dynamics import InversedDynamics, LossDynamics, DensityDynamics
class Flow(torch.nn.Module):
def forward(self, x, inverse=False):
pass
class StackedFlow(torch.nn.Module):
def __init__(se... |
194983 | BLOCKCHAIN = {
'class': 'thenewboston_node.business_logic.blockchain.file_blockchain.FileBlockchain',
'kwargs': {},
}
BLOCKCHAIN_URL_PATH_PREFIX = '/blockchain/'
|
194997 | import unittest
import numpy as np
import numpy.testing as npt
import wisdem.drivetrainse.layout as lay
import wisdem.drivetrainse.drive_structure as ds
from wisdem.commonse import gravity
npts = 12
class TestDirectStructure(unittest.TestCase):
def setUp(self):
self.inputs = {}
self.outputs = {}... |
195037 | from invoke import task
from os.path import basename
from faasmcli.util.endpoints import get_upload_host_port
from faasmcli.util.upload_util import curl_file
@task(default=True)
def upload(ctx, in_path, shared_path):
"""
Upload a shared file to Faasm
"""
host, port = get_upload_host_port()
url ... |
195057 | from base_model.ResNet import resnet101 as Resnet
from base_model.Classifier import Classifier_Module as Classifier
import torch.nn.functional as F
import torch
import torch.nn as nn
__ALL__ = ['Generator']
class Generator(nn.Module):
def __init__(self):
super().__init__()
self.base_model = Res... |
195066 | from django.shortcuts import get_object_or_404
from django.http import HttpResponseRedirect
from django.core.urlresolvers import reverse
from micro_admin.models import User
from django.contrib.auth.mixins import LoginRequiredMixin
class UserPermissionRequiredMixin(LoginRequiredMixin):
def dispatch(self, request,... |
195067 | import numpy as np
import tensorflow as tf
interpreter = tf.lite.Interpreter(model_path="hair_segmentation_512x512_float32.tflite")
# interpreter = tf.lite.Interpreter(model_path="hair_segmentation_512x512_weight_quant.tflite")
interpreter.allocate_tensors()
input_details = interpreter.get_input_details()
output_detai... |
195073 | import asyncio
import aiorpcx
# Handlers are declared as normal python functions. aiorpcx automatically checks RPC
# arguments, including named arguments, and returns errors as appropriate
async def handle_echo(message):
return message
async def handle_sum(*values):
return sum(values, 0)
handlers = {
... |
195120 | from datetime import datetime
filenames = ['aes128cbc', 'aes128gcm', 'aes256cbc', 'aes256gcm']
for filename in filenames:
with open(filename, 'r') as f:
lines = f.readlines()
first_split = lines[0].strip('\n').split()
last_split = lines[-1].strip('\n').split()
prev_datetime = datetime.strptim... |
195151 | import sys
import unittest
from ctypes import *
class MemFunctionsTest(unittest.TestCase):
## def test_overflow(self):
## # string_at and wstring_at must use the Python calling
## # convention (which acquires the GIL and checks the Python
## # error flag). Provoke an error and catch it... |
195175 | from typing import Any, Callable, List, Type, cast, Optional, Union
from . import CRUDGenerator, NOT_FOUND
from ._types import DEPENDENCIES, PAGINATION, PYDANTIC_SCHEMA as SCHEMA
CALLABLE = Callable[..., SCHEMA]
CALLABLE_LIST = Callable[..., List[SCHEMA]]
class MemoryCRUDRouter(CRUDGenerator[SCHEMA]):
def __ini... |
195201 | import GRT
import sys
import argparse
def main():
'''GRT KMeansQuantizer Example
This examples demonstrates how to use the KMeansQuantizer module.
The KMeansQuantizer module quantizes the N-dimensional input vector to a 1-dimensional discrete
value. This value will be between [0 K-1], where K ... |
195230 | import os
import re
import attr
import tempfile
from avalon import aftereffects
import pyblish.api
from openpype.settings import get_project_settings
from openpype.lib import abstract_collect_render
from openpype.lib.abstract_collect_render import RenderInstance
@attr.s
class AERenderInstance(RenderInstance):
#... |
195238 | from .glob import global_add_pool, global_mean_pool, global_max_pool
from .glob import GlobalPooling
from .sort import global_sort_pool
from .attention import GlobalAttention
from .gmt import GraphMultisetTransformer
__all__ = [
'global_add_pool',
'global_mean_pool',
'global_max_pool',
'GlobalPooling',... |
195251 | import sacrebleu
from .base import EvaluationMetricBase
class BLEUTranslation(EvaluationMetricBase):
def __init__(self):
super(BLEUTranslation, self).__init__()
def calculate_scores(self, ground_truth, predict):
"""
The standard BLEU calculation function for translation. It will ... |
195266 | from aws_cdk.aws_ec2 import SubnetType
from aws_cdk import (
aws_ec2 as ec2,
aws_autoscaling as autoscaling,
aws_elasticloadbalancingv2 as elbv2,
core
)
class ASGStack(core.Stack):
def __init__(self, scope: core.Construct, id: str, props, **kwargs) -> None:
super().__init__(scope, id,... |
195269 | import bpy, blf, bgl, os, gpu
from gpu_extras.batch import batch_for_shader
class ViewportDraw:
def __init__(self, context, text):
bakefile = "TLM_Overlay.png"
scriptDir = os.path.dirname(os.path.realpath(__file__))
bakefile_path = os.path.abspath(os.path.join(scriptDir, '..', '..', 'asse... |
195283 | from conans import ConanFile, tools
from conans.errors import ConanInvalidConfiguration
import os
class MathterConan(ConanFile):
name = "mathter"
license = "MIT"
homepage = "https://github.com/petiaccja/Mathter"
url = "https://github.com/conan-io/conan-center-index/"
description = "Powerful 3D math... |
195293 | import zmq
import json
import time
import sys
def get_nodes(model):
node_set = set()
node_list = []
for layer in model['layers']:
if layer['bottom_nodes']:
for node in layer['bottom_nodes']:
if node not in node_set:
node_set.add(node)
... |
195295 | from django.apps import AppConfig
class CustomThemeDemoAppConfig(AppConfig):
name = 'django_cradmin.demo.custom_theme_demo'
verbose_name = "Django CRadmin custom theme demo"
def ready(self):
from django_cradmin.apps.cradmin_kss_styleguide import styleguide_registry
styleguide = styleguid... |
195296 | from footmark.market.productobject import TaggedPRODUCTObject
class Product(TaggedPRODUCTObject):
def __init__(self, connection=None):
super(Product, self).__init__(connection)
def __repr__(self):
return 'Product:%s' % self.id
def __getattr__(self, name):
if name == 'price':
... |
195307 | from kobin import Kobin, request, Response, TemplateResponse, load_config_from_pyfile
config = load_config_from_pyfile('config.py')
app = Kobin(config=config)
@app.route('/')
def index():
return TemplateResponse(
'hello_jinja2.html', name='Kobin', headers={'foo': 'bar'}
)
@app.route('/user/{name}')... |
195355 | from django.contrib.auth import get_user_model
from django.utils.translation import ugettext_lazy as _
from rest_framework import serializers, validators
from user_management.utils.validators import validate_password_strength
User = get_user_model()
class UniqueEmailValidator(validators.UniqueValidator):
def f... |
195425 | import pandas as pd
import numpy as np
import gc
import os
# read data
col_dict = {'mjd': np.float64, 'flux': np.float32, 'flux_err': np.float32, 'object_id': np.int32, 'passband': np.int8,
'detected': np.int8}
train_meta = pd.read_csv(os.path.join('data', 'training_set_metadata.csv'))
train = p... |
195434 | import torch
import numpy as np
import math
from scipy.stats import norm
import matplotlib.pyplot as plt
def plot_gaussian_mixture_1d(var, weights, mu=None):
"""
Visualize 1D Gaussian mixture
"""
if mu is None:
mu = np.zeros_like(var)
x = np.linspace(start = -10, stop = 10, num = 2000)
y_cum = np.zeros... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.