file_name large_stringlengths 4 140 | prefix large_stringlengths 0 12.1k | suffix large_stringlengths 0 12k | middle large_stringlengths 0 7.51k | fim_type large_stringclasses 4
values |
|---|---|---|---|---|
main.go | .Redirect(w, r, url, http.StatusFound)
}
// oauth2callback is the handler to which Google's OAuth service redirects the
// user after they have granted the appropriate permissions.
func oauth2callbackHandler(w http.ResponseWriter, r *http.Request) {
// Create an oauth transport with a urlfetch.Transport embedded insi... | w.WriteHeader(500)
LogPrintf("oauth: json marshal")
return
}
storeCredential(userId, tok, string(userSer))
http.Redirect(w, r, fullUrl, http.StatusFound)
}
func SetupHandler(w http.ResponseWriter, r *http.Request) {
userId, err := userID(r)
if err != nil || userId == "" {
w.WriteHeader(400)
LogPrintf("s... | }
userSer, err := json.Marshal(u)
if err != nil { | random_line_split |
main.go | (w, r, url, http.StatusFound)
}
// oauth2callback is the handler to which Google's OAuth service redirects the
// user after they have granted the appropriate permissions.
func oauth2callbackHandler(w http.ResponseWriter, r *http.Request) {
// Create an oauth transport with a urlfetch.Transport embedded inside.
t :=... | (conn *picarus.Conn, svc *mirror.Service, trans *oauth.Transport, t *mirror.TimelineItem) ([]byte, error) {
a, err := svc.Timeline.Attachments.Get(t.Id, t.Attachments[0].Id).Do()
if err != nil {
LogPrintf("getattachment: metadata")
return nil, err
}
req, err := http.NewRequest("GET", a.ContentUrl, nil)
if err ... | getImageAttachment | identifier_name |
snapshots.go | "Content upload reference to use",
},
cli.BoolFlag{
Name: "keep",
Usage: "Keep diff content. up to creator to delete it.",
},
}, commands.LabelFlag),
Action: func(context *cli.Context) error {
var (
idA = context.Args().First()
idB = context.Args().Get(1)
)
if idA == "" {
return errors.Ne... | Flags: []cli.Flag{
cli.StringFlag{
Name: "target, t",
Usage: "Mount target path, will print mount, if provided",
},
cli.BoolFlag{
Name: "mounts",
Usage: "Print out snapshot mounts as JSON",
},
},
Action: func(context *cli.Context) error {
if narg := context.NArg(); narg < 1 || narg > 2 {
r... | ArgsUsage: "[flags] <key> [<parent>]", | random_line_split |
snapshots.go | "target, t",
Usage: "Mount target path, will print mount, if provided",
},
cli.BoolFlag{
Name: "mounts",
Usage: "Print out snapshot mounts as JSON",
},
},
Action: func(context *cli.Context) error {
if narg := context.NArg(); narg < 1 || narg > 2 {
return cli.ShowSubcommandHelp(context)
}
var... | {
// FIXME: This is specific to Unix
for _, m := range mounts {
fmt.Printf("mount -t %s %s %s -o %s\n", m.Type, m.Source, filepath.Join(target, m.Target), strings.Join(m.Options, ","))
}
} | identifier_body | |
snapshots.go | )
}
return nil
},
}
var viewCommand = cli.Command{
Name: "view",
Usage: "Create a read-only snapshot from a committed snapshot",
ArgsUsage: "[flags] <key> [<parent>]",
Flags: []cli.Flag{
cli.StringFlag{
Name: "target, t",
Usage: "Mount target path, will print mount, if provided",
},
cli... | printMounts | identifier_name | |
snapshots.go | (ctx, id)
if err != nil {
return ocispec.Descriptor{}, err
}
if info.Kind == snapshots.KindActive {
mounts, err = sn.Mounts(ctx, id)
if err != nil {
return ocispec.Descriptor{}, err
}
} else {
key := fmt.Sprintf("%s-view-key", id)
mounts, err = sn.View(ctx, key, id)
if err != nil {
return ocispe... | {
return err
} | conditional_block | |
server.py | shake( | v):
key = base64.b64encode(hashlib.sha1(v + '258EAFA5-E914-47DA-95CA-C5AB0DC85B11').digest())
response = 'HTTP/1.1 101 Switching Protocols\r\n' \
'Upgrade: websocket\r\n' \
'Connection: Upgrade\r\n' \
'Sec-WebSocket-Accept:' + key + '\r\n\... | self, conn, | identifier_name |
server.py | shake(self, conn, v):
key = base64.b64encode(hashlib.sha1(v + '258EAFA5-E914-47DA-95CA-C5AB0DC85B11').digest())
response = 'HTTP/1.1 101 Switching Protocols\r\n' \
'Upgrade: websocket\r\n' \
'Connection: Upgrade\r\n' \
'Sec-WebSocket-Accept... | length = len_flag
ret = ''
for cnt, d in enumerate(raw):
ret += chr(ord(d) ^ ord(mask[cnt % 4]))
if not ret:
pass
# logging.debug("frame info FIN %d Opcode %d mask %d length %d " % (FIN, Opcode, is_mask, length))
# hexstr = binas... | raw = data[14:]
length = reduce(lambda y, z: y * 256 + z, map(lambda x: ord(x), data[2:9]))
else:
mask = data[2:6]
raw = data[6:]
| random_line_split |
server.py | shake(self, conn, v):
key = base64.b64encode(hashlib.sha1(v + '258EAFA5-E914-47DA-95CA-C5AB0DC85B11').digest())
response = 'HTTP/1.1 101 Switching Protocols\r\n' \
'Upgrade: websocket\r\n' \
'Connection: Upgrade\r\n' \
'Sec-WebSocket-Accept... | ey]['no']))
elif msg['a'] == 'f':
logging.info('a %s s %d e %d n %d' % (msg['a'], msg['s'], msg['e'], msg['n']))
start, end = msg['s'], msg['e']
length = end - start
if msg['n'] != session['no']:
if msg['n'] < session[... | self.session[sesskey]['filebuffer'] = []
self.session[sesskey]['no'] = 0
self.session[sesskey]['file'] = open(
os.path.join(os.path.dirname(__file__), 'upload', msg['name']), 'ab')
elif msg['a'] == 'ping':
self.ws_send(conn, "ok:%d"... | conditional_block |
server.py | Server:
socket = None
socket_list = set()
port = 7000
buffersize = 1024*1024
timeout = 20
content = dict()
session = dict()
def __init__(self):
filelist = ['test.html', 'upload.js', 'spark-md5.min.js']
for i in filelist:
with open(i, 'r') as f:
... | b.md5()
while True:
data = f.read(block_size)
if not data:
break
md5.update(data)
return md5.hexdigest()
class | identifier_body | |
rol_common.js | fdid = $(this).parent().find(".folder_id").val();
var fdname = $(this).parent().find(".folder_name").val();
var parent = $(this).parent();
setTimeout(function(){
//添加焦点事件
parent.addClass("left_nav_infolink_high");
var edit_div = $('#float_edit');
edit_div.css("display","block");
edit_div.css("t... | function show_msg_tips_newdiv(type,msg,id){
if(!type || !msg)
return;
var time=3000;
if('success'==type || 'yes'==type)
$.scmtips.show("success",msg,null,time);
if('warn'==type || 'warning'==type)
$.scmtips.show("warn",msg,null,time);
if('error'==type || 'wrong'==type)
$.scmtips.show("error",msg,null,time)... |
//在弹出框中显示提示信息 | random_line_split |
rol_common.js | nav_open");
}
}
//左边菜单展开，关闭替换图标
function replaceImg(obj){
var img = $(obj).find("img");
var src = img.attr("src");
if(src.indexOf('open')>0){
img.attr("src",src.replace("open","close"));
}else{
img.attr("src",src.replace("close","open"));
}
}
//打开左侧菜单，根据设置的.info样式
function open_left_nav(){
$("#left_nav"... | $(obj).css("zIndex",1000);
$(obj).css("height",$(obj).find(".float_div_content").height()+70)
},100);
}else{
$(obj).hide();
}
}
//左菜单展开，关闭
function switch_left_nav(obj){
var div = $(obj).parent();
if($(obj).hasClass("left_nav_open"))
{
div.find(">div:not(div:first-child)").hide();
$(obj).removeClass("le... | conditional_block | |
rol_common.js | fdid = $(this).parent().find(".folder_id").val();
var fdname = $(this).parent().find(".folder_name").val();
var parent = $(this).parent();
setTimeout(function(){
//添加焦点事件
parent.addClass("left_nav_infolink_high");
var edit_div = $('#float_edit');
edit_div.css("display","block");
edit_div.css("t... | rror",msg,null,time);
}
function show_msg_tips(type,msg,width){
if(!type || !msg)
return;
var time=1000;
if('success'==type || 'yes'==type)
$.scmtips.show("success",msg, width,time);
if('warn'==type || 'warning'==type)
$.scmtips.show("warn",msg, width,time);
if('error'==type || 'wrong'==type)
$.scmtips.sh... | cmtips.show("warn",msg,null,time);
if('error'==type || 'wrong'==type)
$.scmtips.show("e | identifier_body |
rol_common.js | ,null,time);
}
function show_msg_tips(type,msg,width){
if(!type || !msg)
return;
var time=1000;
if('success'==type || 'yes'==type)
$.scmtips.show("success",msg, width,time);
if('warn'==type || 'warning'==type)
$.scmtips.show("warn",msg, width,time);
if('error'==type || 'wrong'==type)
$.scmtips.show("error... | break;
| identifier_name | |
ranker_ltr.py | ):
"""
Trains a model and saves it to a file.
- This function currently only supports GBRT.
Args:
inss: erd.ml.CERInstances, train instances
model_file: A file to save the model. For None value, the model will not be saved
Returns:
ranker, th... |
return self.ml.apply_model(inss, model)
def rank_queries(self, queries, time_log_file=None): # commonness_th, filter=True,
"""
Ranks entities for the given queries using the trained model.
:param queries: a dictionary, {q_id: q_content, ...}
:param time_log_file: file nam... | model = self.model | conditional_block |
ranker_ltr.py | ):
"""
Trains a model and saves it to a file.
- This function currently only supports GBRT.
Args:
inss: erd.ml.CERInstances, train instances
model_file: A file to save the model. For None value, the model will not be saved
Returns:
ranker, th... | (self, queries, time_log_file=None): # commonness_th, filter=True,
"""
Ranks entities for the given queries using the trained model.
:param queries: a dictionary, {q_id: q_content, ...}
:param time_log_file: file name to save time log
:return erd.ml.CERInstances, Ranked instanc... | rank_queries | identifier_name |
ranker_ltr.py | ):
"""
Trains a model and saves it to a file.
- This function currently only supports GBRT.
Args:
inss: erd.ml.CERInstances, train instances
model_file: A file to save the model. For None value, the model will not be saved
Returns:
ranker, th... | inss_list.append(q_inss)
# time log
e_t = datetime.now()
diff = e_t - s_t
total_time += diff.total_seconds()
time_log = "Execution time(min):\t" + str(round(total_time/60, 4)) + "\n"
time_log += "Avg. time per query:\t" + str(round(total_time/len(queries), 4)... | """
Ranks entities for the given queries using the trained model.
:param queries: a dictionary, {q_id: q_content, ...}
:param time_log_file: file name to save time log
:return erd.ml.CERInstances, Ranked instances
"""
print "Ranking queries ..."
total_time = 0.0
... | identifier_body |
ranker_ltr.py | model: the trained model
"""
def __init__(self, commonness_th=None, sf_source=None, filter=True, model=None, config={}):
self.commonness_th = commonness_th
self.sf_source = sf_source
self.filter = filter
self.config = config
self.model = model
self.ml = ML... | random_line_split | ||
opentuna-stack.ts | extends cdk.Stack {
constructor(scope: cdk.Construct, id: string, props: OpenTunaStackProps) {
super(scope, id, props);
const stack = cdk.Stack.of(this);
const domainName = this.node.tryGetContext('domainName');
const domainZoneName = this.node.tryGetContext('domainZone');
const iamCertId = thi... | OpentunaStack | identifier_name | |
opentuna-stack.ts | const tunaManagerALBSG = new ec2.SecurityGroup(this, "TunaManagerALBSG", {
vpc,
description: "SG of ALB of Tuna Manager",
allowAllOutbound: false,
});
const tunaWorkerSG = new ec2.SecurityGroup(this, "TunaWorkerSG", {
vpc,
description: "SG of Tuna Worker",
allowAllOutboun... | {
// ACM cert
cloudfrontProps = {
aliasConfiguration: {
acmCertRef: cloudfrontCert.certificateArn,
names: [domainName],
},
...cloudfrontProps
}
} | conditional_block | |
opentuna-stack.ts | } else if (!stack.region.startsWith('cn-')) {
// Try to use ACM certificate in us-east-1 for CloudFront
cloudfrontCert = new acm.DnsValidatedCertificate(this, 'CloudFrontCertificate', {
domainName: domainName,
hostedZone: domainZone,
validation: acm.CertificateValidat... | {
super(scope, id, props);
const stack = cdk.Stack.of(this);
const domainName = this.node.tryGetContext('domainName');
const domainZoneName = this.node.tryGetContext('domainZone');
const iamCertId = this.node.tryGetContext('iamCertId');
let useHTTPS = false;
let domainZone: r53.IHostedZone... | identifier_body | |
opentuna-stack.ts | cloudfrontCert: acm.Certificate | string | null = null;
if (domainName && domainZoneName) {
domainZone = r53.HostedZone.fromLookup(this, 'HostedZone', {
domainName: domainZoneName,
});
useHTTPS = true;
if (iamCertId !== undefined) {
// Use IAM first when specified
cl... | allowAllOutbound: true,
});
const tunaManagerALBSG = new ec2.SecurityGroup(this, "TunaManagerALBSG", {
vpc,
description: "SG of ALB of Tuna Manager",
allowAllOutbound: false,
});
const tunaWorkerSG = new ec2.SecurityGroup(this, "TunaWorkerSG", {
vpc,
description: "SG ... |
const tunaManagerSG = new ec2.SecurityGroup(this, "TunaManagerSG", {
vpc,
description: "SG of Tuna Manager", | random_line_split |
L.IM_RoutingControl.js | );transform:scale(-1.3, 1.3)"></i>'+
'</span>',
tooltip: 'right',
marker_style_origen: {
icon : '',
markerColor : 'green',
divColor:'transparent',
iconAnchor : new L.Point(14, 42),
iconSize : new L.Point(28, 42),
iconColor : '#000000',
prefix : 'fa',
isCanvas:false,
radius:6,
opacity... | else {
return L.marker(wp.latLng, {
draggable: true,
icon: puntIntermig
});
}
};
this._plan = new this._reversablePlan([], {
geocoder: L.Control.Geocoder.icgc(),
routeWhileDragging: true,
language: lang,
createMarker: createM... | return L.marker(wp.latLng, {
draggable: true,
icon: puntDesti
});
}
| conditional_block |
L.IM_RoutingControl.js | '<i class="t-square-rounded" style="-webkit-transform:scale(1.25) scale(0.65) rotate(45deg);-moz-transform:scale(1.25) scale(0.65) rotate(45deg);transform:scale(1.25) scale(0.65) rotate(45deg)"></i>'+
'<i class="t-turn-90-l t-c-white" style="-webkit-transform:scale(-1.3, 1.3);-moz-transform:scale(-1.3, 1.3);transfo... | random_line_split | ||
views.py |
from students.forms import CourseEnrollForm
from .models import Course, Module, Content, Subject
from .forms import ModuleFormSet
class OwnerMixin(object):
"""
Миксин переопределяющий метод get_queryset
во всех дочерних классах.
Может взаимодействовать со всеми моделями
у которых есть атрибут owner.
"""
def g... |
c
lass CourseUpdateView(PermissionRequiredMixin, OwnerCourseEditMixin, UpdateView):
"""
Используется для изменения Course
"""
# PermissionRequiredMixin проверяет если у пользователя указанный permission_required
permission_required = "courses.change_course"
class CourseDeleteView(PermissionRequiredMixin, Owne... | age_course_list')
template_name = "courses/manage/course/form.html"
class ManageCourseListView(OwnerCourseMixin, ListView):
"""
Используя наследование от OwnerCourseMixin, ListView
этот класс также будет содержать все поля и методы из
OwnerCourseMixin, ListView, OwnerMixin
"""
template_name = "courses/manage/c... | identifier_body |
views.py | from .models import Course, Module, Content, Subject
from .forms import ModuleFormSet
class OwnerMixin(object):
"""
Миксин переопределяющий метод get_queryset
во всех дочерних классах.
Может взаимодействовать со всеми моделями
у которых есть атрибут owner.
"""
def get_queryset(self):
"""
вернуть объекты со... | ериализирует response
"""
def post(self, request):
for id, order in self.request_json.items():
print('id', id, ' -- ', order)
for id, order in self.request_json.items():
Content.objects.filter(id=id, module__course__owner=request.user).update(order=order)
return self.render_json_response({'sa | conditional_block | |
views.py | apps
from students.forms import CourseEnrollForm
from .models import Course, Module, Content, Subject
from .forms import ModuleFormSet
class OwnerMixin(object):
"""
Миксин переопределяющий метод get_queryset
во всех дочерних классах.
Может взаимодействовать со всеми моделями
у которых есть атрибут owner.
"""
... | content.content_object.delete()
content.delete()
# возвращаемся к списку контента модуля
return redirect('module_content_list', module.id)
class ModuleContentListView(TemplateResponseMixin, View):
template_name = "courses/manage/module/content_list.html"
def get(self, request, module_id):
module = get_ob... | id=id,
module__course__owner=request.user)
module = content.module | random_line_split |
views.py |
from students.forms import CourseEnrollForm
from .models import Course, Module, Content, Subject
from .forms import ModuleFormSet
class OwnerMixin(object):
"""
Миксин переопределяющий метод get_queryset
во всех дочерних классах.
Может взаимодействовать со всеми моделями
у которых есть атрибут owner.
"""
def g... | ы)
задается владелец этого объекта.
"""
form.instance.owner = self.request.user
return super(OwnerEditMixin, self).form_valid(form)
class OwnerCourseMixin(OwnerMixin, LoginRequiredMixin):
"""
Указание модели для queryset во всех дочерних классах
"""
model = Course
class OwnerCourseEditMixin(OwnerCourseM... | верждение форм | identifier_name |
CKEditor_media_tab.js | /dialogs/image.js
*/
function _eatlas_media_frame_ckeditor_create_media_tab() {
// As defined in imageDialog function
var IMAGE = 1,
LINK = 2,
PREVIEW = 4,
CLEANUP = 8;
var IMAGESTYLE_CLASS_PREFIX = 'img__view_mode__';
var IMAGEID_CLASS_PREFIX = 'img__fid__';
var onMediaStyleChange = function() ... | else {
inputEl.setAttribute('readonly', true);
inputEl.addClass('disabled');
}
};
var imageStyles = [
['Original', 'media_original'],
['Link', 'media_link'],
['Preview', 'media_preview'],
['Large', 'media_large']
];
// NOTE: Drupal.settings.eatlas_media_frame_filter.drupal_custom_image... | {
inputEl.removeAttribute('readonly');
inputEl.removeClass('disabled');
} | conditional_block |
CKEditor_media_tab.js | /image/dialogs/image.js
*/
function _eatlas_media_frame_ckeditor_create_media_tab() {
// As defined in imageDialog function
var IMAGE = 1,
LINK = 2,
PREVIEW = 4,
CLEANUP = 8;
var IMAGESTYLE_CLASS_PREFIX = 'img__view_mode__';
var IMAGEID_CLASS_PREFIX = 'img__fid__';
var onMediaStyleChange = funct... |
// Remove previous 'image style' class and find the image ID
var newClasses = [];
for (var i=0, len=classes.length; i<len; i++) {
if (classes[i].substring(0, IMAGESTYLE_CLASS_PREFIX.length) !== IMAGESTYLE_CLASS_PREFIX) {
newClasses.push(classes[i]);
}
}
// Add new 'image style' class
ne... | // API: dialog.getValueOf(pageId, elementId);
var classes = dialog.getValueOf('advanced', 'txtGenClass');
classes = classes ? classes.split(/\s+/) : []; | random_line_split |
CKEditor_media_tab.js | El = dialog.getContentElement('media', inputID).getInputElement();
if (active) {
inputEl.removeAttribute('readonly');
inputEl.removeClass('disabled');
} else {
inputEl.setAttribute('readonly', true);
inputEl.addClass('disabled');
}
};
var imageStyles = [
['Original', 'media_original'],
... | {
return $('<div/>').html(str).text();
} | identifier_body | |
CKEditor_media_tab.js | };
var toggleInput = function(dialog, inputID, active) {
var inputEl = dialog.getContentElement('media', inputID).getInputElement();
if (active) {
inputEl.removeAttribute('readonly');
inputEl.removeClass('disabled');
} else {
inputEl.setAttribute('readonly', true);
inputEl.addClass('disabled... | _decode | identifier_name | |
lib.rs | RuntimeOrigin> +
IsType<<<Self as frame_system::Config>::RuntimeOrigin as frame_support::traits::OriginTrait>::PalletsOrigin>;
/// Weight information for extrinsics in this pallet.
type WeightInfo: WeightInfo;
}
#[pallet::event]
#[pallet::generate_deposit(pub(super) fn deposit_event)]
pub enum Event {
//... |
}
#[pallet::hooks]
impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
fn integrity_test() {
// If you hit this error, you need to try to `Box` big dispatchable parameters.
assert!(
sp_std::mem::size_of::<<T as Config>::RuntimeCall>() as u32 <= CALL_ALIGN,
"Call enum size should be smaller tha... | {
let allocator_limit = sp_core::MAX_POSSIBLE_ALLOCATION;
let call_size = ((sp_std::mem::size_of::<<T as Config>::RuntimeCall>() as u32 +
CALL_ALIGN - 1) / CALL_ALIGN) *
CALL_ALIGN;
// The margin to take into account vec doubling capacity.
let margin_factor = 3;
allocator_limit / margin_factor /... | identifier_body |
lib.rs | RuntimeOrigin> +
IsType<<<Self as frame_system::Config>::RuntimeOrigin as frame_support::traits::OriginTrait>::PalletsOrigin>;
/// Weight information for extrinsics in this pallet.
type WeightInfo: WeightInfo;
}
#[pallet::event]
#[pallet::generate_deposit(pub(super) fn deposit_event)]
pub enum Event {
//... | () {
// If you hit this error, you need to try to `Box` big dispatchable parameters.
assert!(
sp_std::mem::size_of::<<T as Config>::RuntimeCall>() as u32 <= CALL_ALIGN,
"Call enum size should be smaller than {} bytes.",
CALL_ALIGN,
);
}
}
#[pallet::error]
pub enum Error<T> {
/// Too many ca... | integrity_test | identifier_name |
lib.rs | _constants]
impl<T: Config> Pallet<T> {
/// The limit on the number of batched calls.
fn batched_calls_limit() -> u32 {
let allocator_limit = sp_core::MAX_POSSIBLE_ALLOCATION;
let call_size = ((sp_std::mem::size_of::<<T as Config>::RuntimeCall>() as u32 +
CALL_ALIGN - 1) / CALL_ALIGN) *
CALL_ALIGN;
... | {
return Err(BadOrigin.into())
} | conditional_block | |
lib.rs | >::RuntimeOrigin> +
IsType<<<Self as frame_system::Config>::RuntimeOrigin as frame_support::traits::OriginTrait>::PalletsOrigin>;
/// Weight information for extrinsics in this pallet.
type WeightInfo: WeightInfo;
}
#[pallet::event]
#[pallet::generate_deposit(pub(super) fn deposit_event)]
pub enum Event {
... | /// event is deposited. If a call failed and the batch was interrupted, then the
/// `BatchInterrupted` event is deposited, along with the number of successful calls made
/// and the error of the failed call. If all were successful, then the `BatchCompleted`
/// event is deposited.
#[pallet::call_index(0)]
... | /// - O(C) where C is the number of calls to be batched.
///
/// This will return `Ok` in all circumstances. To determine the success of the batch, an | random_line_split |
main.py | True,
'input_dim':2048}
else:
warnings.warn('=> You did not choose a global image representation method!')
representation = None # which for original vgg or alexnet
model = get_model(args.arch,
representation,
args.num_classe... | __init__ | identifier_name | |
main.py | .parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay})
params_list.append({'params': model.classifier.parameters(),
'lr': args.lr*args.classifier_factor,
'weight_decay': 0. if args.arch.startswith('vgg') else args.weight_... | lr_factor, lr = self.log(params, total_epoch) | conditional_block | |
main.py | -trained model')
parser.add_argument('--world-size', default=1, type=int,
help='number of distributed processes')
parser.add_argument('--dist-url', default='tcp://224.66.41.62:23456', type=str,
help='url used to set up distributed training')
parser.add_argument('--dist-backend', ... | loss = criterion(output, target)
# measure accuracy and record loss
prec1, prec5 = accuracy(output, target, topk=(1, 5))
losses.update(loss.item(), input.size(0))
top1.update(prec1[0], input.size(0))
top5.update(prec5[0], input.size(0))
# compute gradient and do... | batch_time = AverageMeter()
data_time = AverageMeter()
losses = AverageMeter()
top1 = AverageMeter()
top5 = AverageMeter()
# switch to train mode
model.train()
end = time.time()
for i, (input, target) in enumerate(train_loader):
# measure data loading time
data_time.upd... | identifier_body |
main.py | -trained model')
parser.add_argument('--world-size', default=1, type=int,
help='number of distributed processes') | help='url used to set up distributed training')
parser.add_argument('--dist-backend', default='gloo', type=str,
help='distributed backend')
parser.add_argument('--seed', default=None, type=int,
help='seed for initializing training. ')
parser.add_argument('--gp... | parser.add_argument('--dist-url', default='tcp://224.66.41.62:23456', type=str, | random_line_split |
shlex.go | nil || b == nil {
return false
}
if a.tokenType != b.tokenType {
return false
}
return a.value == b.value
}
const (
RUNE_CHAR string = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789._-,/@$*()+=><:;&^%~|!?[]{}"
RUNE_SPACE string = " \t\r\n"
RUNE_ESCAPING_QUOTE st... |
func (classifier *TokenClassifier) ClassifyRune(rune int32) RuneTokenType {
return classifier.typeMap[rune]
}
/*
A type for turning an input stream in to a sequence of strings. Whitespace and
comments are skipped.
*/
type Lexer struct {
tokenizer *Tokenizer
}
/*
Create a new lexer.
*/
func NewLexer(r io.Reader) (... | {
typeMap := map[int32]RuneTokenType{}
addRuneClass(&typeMap, RUNE_CHAR, RUNETOKEN_CHAR)
addRuneClass(&typeMap, RUNE_SPACE, RUNETOKEN_SPACE)
addRuneClass(&typeMap, RUNE_ESCAPING_QUOTE, RUNETOKEN_ESCAPING_QUOTE)
addRuneClass(&typeMap, RUNE_NONESCAPING_QUOTE, RUNETOKEN_NONESCAPING_QUOTE)
addRuneClass(&typeMap, RUNE... | identifier_body |
shlex.go | never equal another token.
*/
func (a *Token) Equal(b *Token) bool {
if a == nil || b == nil {
return false
}
if a.tokenType != b.tokenType {
return false
}
return a.value == b.value
}
const (
RUNE_CHAR string = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789._-,/@$*()+=><:;&^%~|... | random_line_split | ||
shlex.go | nil || b == nil {
return false
}
if a.tokenType != b.tokenType {
return false
}
return a.value == b.value
}
const (
RUNE_CHAR string = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789._-,/@$*()+=><:;&^%~|!?[]{}"
RUNE_SPACE string = " \t\r\n"
RUNE_ESCAPING_QUOTE st... | (r io.Reader) (*Lexer, error) {
tokenizer, err := NewTokenizer(r)
if err != nil {
return nil, err
}
lexer := &Lexer{tokenizer: tokenizer}
return lexer, nil
}
/*
Return the next word, and an error value. If there are no more words, the error
will be io.EOF.
*/
func (l *Lexer) NextWord() (string, error) {
var t... | NewLexer | identifier_name |
shlex.go | for turning an input stream in to a sequence of strings. Whitespace and
comments are skipped.
*/
type Lexer struct {
tokenizer *Tokenizer
}
/*
Create a new lexer.
*/
func NewLexer(r io.Reader) (*Lexer, error) {
tokenizer, err := NewTokenizer(r)
if err != nil {
return nil, err
}
lexer := &Lexer{tokenizer: toke... | {
word, err := l.NextWord()
if err != nil {
if err == io.EOF {
return subStrings, nil
}
return subStrings, err
}
subStrings = append(subStrings, word)
} | conditional_block | |
mod.rs | sequences from `tail` until either (1) `tail` is
// exhausted, or (2) the display width of the result would exceed `display_width`.
//
// 3. If tail was exhausted, then contribute graphemes and ANSI escape sequences from `s` until the
// display_width of the result would exceed `display_width`.
pub fn truncate_s... | asure_text_width_osc_hyperlink_non_ascii() {
assert_eq!(measure_text_width("\x1b[38;5;4m\x1b]8;;file:///Users/dan/src/delta/src/ansi/mod.rs\x1b\\src/ansi/modバー.rs\x1b]8;;\x1b\\\x1b[0m"),
measure_text_width("src/ansi/modバー.rs"));
}
#[test]
fn test_parse_first_style() {
let... | _text_width("\x1b[38;5;4m\x1b]8;;file:///Users/dan/src/delta/src/ansi/mod.rs\x1b\\src/ansi/mod.rs\x1b]8;;\x1b\\\x1b[0m"),
measure_text_width("src/ansi/mod.rs"));
}
#[test]
fn test_me | identifier_body |
mod.rs | sequences from `tail` until either (1) `tail` is
// exhausted, or (2) the display width of the result would exceed `display_width`.
//
// 3. If tail was exhausted, then contribute graphemes and ANSI escape sequences from `s` until the
// display_width of the result would exceed `display_width`.
pub fn truncate_s... | ure_text_width("\x1b[38;5;4m\x1b]8;;file:///Users/dan/src/delta/src/ansi/mod.rs\x1b\\src/ansi/modバー.rs\x1b]8;;\x1b\\\x1b[0m"),
measure_text_width("src/ansi/modバー.rs"));
}
#[test]
fn test_parse_first_style() {
let minus_line_from_unconfigured_git = "\x1b[31m-____\x1b[m\n";
... | hyperlink_non_ascii() {
assert_eq!(meas | identifier_name |
mod.rs | sequences from `tail` until either (1) `tail` is
// exhausted, or (2) the display width of the result would exceed `display_width`.
//
// 3. If tail was exhausted, then contribute graphemes and ANSI escape sequences from `s` until the
// display_width of the result would exceed `display_width`.
pub fn truncate_s... |
}
Cow::from(format!("{result}{result_tail}"))
}
pub fn parse_style_sections(s: &str) -> Vec<(ansi_term::Style, &str)> {
let mut sections = Vec::new();
let mut curr_style = Style::default();
for element in AnsiElementIterator::new(s) {
match element {
Element::Text(start, end) ... | {
result.push_str(t);
} | conditional_block |
mod.rs | escape sequences from `tail` until either (1) `tail` is
// exhausted, or (2) the display width of the result would exceed `display_width`.
//
// 3. If tail was exhausted, then contribute graphemes and ANSI escape sequences from `s` until the
// display_width of the result would exceed `display_width`.
pub fn tru... | measure_text_width("src/ansi/mod.rs"));
}
#[test]
fn test_measure_text_width_osc_hyperlink_non_ascii() {
assert_eq!(measure_text_width("\x1b[38;5;4m\x1b]8;;file:///Users/dan/src/delta/src/ansi/mod.rs\x1b\\src/ansi/modバー.rs\x1b]8;;\x1b\\\x1b[0m"),
measure_text_w... | random_line_split | |
main.rs | : u32;
static __DATA_END: u32;
static mut __DATA_START: u32;
static mut __BSS_START: u32;
static mut __BSS_END: u32;
}
let data_load = &__DATA_LOAD;
let data_start = &mut __DATA_START;
let data_end = &__DATA_END;
let bss_start = &mut __BSS_START;
let bss_end = &__... | let drag_color = Color::from_hex(0x000000);
let grid_color = Color::from_hex(0x444444);
// lcd controller
let mut lcd = lcd::init(ltdc, rcc, &mut gpio);
touch::check_family_id(&mut i2c_3).unwrap();
loop {
SYSCLOCK.reset();
lcd.clear_screen();
lcd.set_background_color(Color::from_h... | gpio::Resistor::NoPull)
.expect("Could not configure pwm pin");
let axis_color = Color::from_hex(0xffffff); | random_line_split |
main.rs | u32;
static __DATA_END: u32;
static mut __DATA_START: u32;
static mut __BSS_START: u32;
static mut __BSS_END: u32;
}
let data_load = &__DATA_LOAD;
let data_start = &mut __DATA_START;
let data_end = &__DATA_END;
let bss_start = &mut __BSS_START;
let bss_end = &__B... | (hw: board::Hardware) -> ! {
let board::Hardware {
rcc,
pwr,
flash,
fmc,
ltdc,
gpio_a,
gpio_b,
gpio_c,
gpio_d,
gpio_e,
gpio_f,
gpio_g,
gpio_h,
gpio_i,
gpio_j,
gpio_k,
spi_2,
... | main | identifier_name |
main.rs | // enable floating point unit
let scb = stm32f7::cortex_m::peripheral::scb_mut();
scb.cpacr.modify(|v| v | 0b1111 << 20);
asm!("DSB; ISB;"::::"volatile"); // pipeline flush
main(board::hw());
}
// WORKAROUND: rust compiler will inline & reorder fp instructions into
#[inline(ne... | {
extern "C" {
static __DATA_LOAD: u32;
static __DATA_END: u32;
static mut __DATA_START: u32;
static mut __BSS_START: u32;
static mut __BSS_END: u32;
}
let data_load = &__DATA_LOAD;
let data_start = &mut __DATA_START;
let data_end = &__DATA_END;
let bss_s... | identifier_body | |
navtreeindex22.js | 8h.htm#gaeb0fca7dd680f3f8863edb56b5ce0e5b":[4,0,72,21],
"token-stack_8h.htm#gaeb9bc13c387e34deb35e981dd9c1a276":[4,0,72,10],
"token-stack_8h.htm#gaec433bb494f14daea12eb32616d685a8":[4,0,72,30],
"token-stack_8h.htm#gaed1a0a2b07a388b3c94cfc512dfa8335":[4,0,72,39],
"token-stack_8h.htm#gaee5596e09a93afc50340f794e61a64d4":[... | "zigbee-device-common_8h.htm#gaf8e641f05f5b8359571fa677ccb8c4b3":[4,0,76,0],
"zigbee-device-common_8h_source.htm":[4,0,76],
"zigbee-device-host_8h.htm":[4,0,77], | random_line_split | |
index.ts | utOptions: InputOptions, plugin: Plugin) {
if (plugin.options) return plugin.options(inputOptions) || inputOptions;
return inputOptions;
}
function getInputOptions(rawInputOptions: GenericConfigObject): any {
if (!rawInputOptions) {
throw new Error('You must supply an options object to rollup');
}
// inputOpti... | yOptionHook(inp | identifier_name | |
index.ts | (!rawInputOptions) {
throw new Error('You must supply an options object to rollup');
}
// inputOptions: input 从命令行或配置文件与默认配置合并
// deprecations: 过时的参数列表，过时的参数，仍然会写入正确的地方
// optionError: 错误信息
let { inputOptions, deprecations, optionError } = mergeOptions({
config: rawInputOptions,
deprecateConfig: { input: tr... | .then(addons => {
// pre-render all chunks
for (const chunk of chunks) {
if (!inputOptions.experimentalPreserveModules)
chunk.generateInternalExports(outputOptions);
if (chunk.isEntryModuleFacade)
chunk.exportMode = getExportMode(chunk, outputOptions);
}
... | random_line_split | |
index.ts | function checkInputOptions(options: InputOptions) {
if (options.transform || options.load || options.resolveId || options.resolveExternal) {
throw new Error(
'The `transform`, `load`, `resolveId` and `resolveExternal` options are deprecated in favour of a unified plugin API. See https://rollupjs.org/guide/en#plug... | {
const message = `The following options have been renamed — please update your config: ${deprecations
.map(option => `${option.old} -> ${option.new}`)
.join(', ')}`;
warn({
code: 'DEPRECATED_OPTIONS',
message,
deprecations
});
}
| identifier_body | |
index.ts |
function checkOutputOptions(options: OutputOptions) {
if (<string>options.format === 'es6') {
error({
message: 'The `es6` output format is deprecated – use `es` instead',
url: `https://rollupjs.org/guide/en#output-format-f-format`
});
}
if (!options.format) {
error({
message: `You must specify outp... | throw new Error(
'The `transform`, `load`, `resolveId` and `resolveExternal` options are deprecated in favour of a unified plugin API. See https://rollupjs.org/guide/en#plugins'
);
}
} | conditional_block | |
model_probabilistic.py | ization(
self.MLP_SIZE,
activation = mlp_activation,
)
layer_0_act = self.layer_0(self.x_ph)
layer_0_out = tf.layers.dropout(layer_0_act, rate = self.DROP, training = self.is_training)
self.layer_1 = tfp.layers.DenseLocalReparameterization(
self.MLP_SIZE,
act... |
input_scaled = self.get_scaled_features(input_raw)
| random_line_split | |
model_probabilistic.py | [key] for key in details}
self.features_shape = self.scaling['features_shape']
self.targets_shape = self.scaling['targets_shape']
def get_scaled_features(self, features):
if self.config['feature_rescaling'] == 'standardization':
scaled = (features - self.scaling['mean_features']) / self.scaling['std_featur... |
return raw
def set_hyperparameters(self, hyperparam_dict):
for key, value in hyperparam_dict.items():
setattr(self, key, value)
def construct_graph(self):
act_funcs = {
'linear': lambda y: y,
'leaky_relu': lambda y: tf.nn.leaky_relu(y, 0.2),
'relu': lambda y: tf.nn.relu(y),
'so... | raw = targets | conditional_block |
model_probabilistic.py | self.targets_shape[1]])
self.layer_0 = tfp.layers.DenseLocalReparameterization(
self.MLP_SIZE,
activation = mlp_activation,
)
layer_0_act = self.layer_0(self.x_ph)
layer_0_out = tf.layers.dropout(layer_0_act, rate = self.DROP, training = self.is_training)
self.layer_1 ... | if not self.is_graph_constructed: self.construct_inference()
self.sess = tf.compat.v1.Session(graph = self.graph)
self.saver = tf.compat.v1.train.Saver()
try:
self.saver.restore(self.sess, model_path)
return True
except AttributeError:
return False | identifier_body | |
model_probabilistic.py | (self, graph, dataset_details, config, scope, batch_size, max_iter = 10**8):
self.graph = graph
self.scope = scope
self.config = config
self.batch_size = batch_size
self.dataset_details = dataset_details
self.max_iter = max_iter
self.is_graph_constructed = False
... | __init__ | identifier_name | |
walk.py |
self.console_stream = console_stream
def printer(self, message, stream=False):
if not stream:
if self.console_output:
print('\t' + message)
else:
if self.console_stream:
print('\t' + message)
def pool_process(func, iterable, process... | (path_list):
"""Pool process file hashing."""
return pool_process(md5_tuple, path_list, 'MD5 hashing')
def remover(file_path):
"""Delete a file or directory path only if it exists."""
if os.path.isfile(file_path):
os.remove(file_path)
return True
elif os.path.isdir(file_path):
... | pool_hash | identifier_name |
walk.py |
self.console_stream = console_stream
def printer(self, message, stream=False):
if not stream:
if self.console_output:
print('\t' + message)
else:
if self.console_stream:
print('\t' + message)
def pool_process(func, iterable, process... |
class DirPaths:
def __init__(self,
directory,
full_paths=False,
topdown=True,
to_include=None,
to_exclude=None,
min_level=0,
max_level=inf,
filters=None,
non_e... | """Pool process file creation dates."""
return pool_process(creation_date_tuple, path_list, 'File creation dates') | identifier_body |
walk.py |
self.console_stream = console_stream
def printer(self, message, stream=False):
if not stream:
if self.console_output:
print('\t' + message)
else:
if self.console_stream:
print('\t' + message)
def pool_process(func, iterable, process... |
else:
self.filters = False
self.console_output = console_output
self.console_stream = console_stream
self._hash_files = hash_files
self._printer = Printer(console_output, console_stream).printer
self._printer('DIRPATHS')
# Check that parallelizatio... | self.filters = PathFilters(to_include, to_exclude, min_level, max_level, filters, non_empty_folders) | conditional_block |
walk.py | _output
self.console_stream = console_stream
def printer(self, message, stream=False):
if not stream:
if self.console_output:
print('\t' + message)
else:
if self.console_stream:
print('\t' + message)
def pool_process(func, iterable, ... | return str(self.tree_dict)
@property
def dict(self):
return self.tree_dict
def _filter(self, folders, folder_or_file):
for index in range(0, len(folders)):
filters = self.branches[index][folder_or_file]
if filters:
exclude = filters.get
... | def __iter__(self):
return iter(self.tree_dict.items())
def __str__(self): | random_line_split |
utils.py | 1].plot(range(total_epochs), bnn.fit_history.history["val_{}".format(this_metric)], '-o', label="validation")
axes[i+1].legend()
axes[i+1].set_ylabel(this_metric)
axes[i+1].set_xlabel("epoch")
plt.tight_layout()
return fig, axes
def make_1d2d(arr):
assert arr.ndim == 1
return arr.reshape(arr.shape[0], 1)... | pred_proba_samples: array of predicted probability samples with shape
(n_mc_samples, n_examples, n_classes)/(n_mc_samples, n_examples)
for multiclass/binary classification. (This is the shape returned by BNN_Classifier.predict).
labels: array of one-hot encoded labels with shape (n_examples, n_clas... | Get the sampled accuracies over the entire test set from logit samples.
Args: | random_line_split |
utils.py | 1].plot(range(total_epochs), bnn.fit_history.history["val_{}".format(this_metric)], '-o', label="validation")
axes[i+1].legend()
axes[i+1].set_ylabel(this_metric)
axes[i+1].set_xlabel("epoch")
plt.tight_layout()
return fig, axes
def make_1d2d(arr):
assert arr.ndim == 1
return arr.reshape(arr.shape[0], 1)... |
return roc_curve_df
def load_mnist(fashion, onehot_encode=True, flatten_x=False, crop_x=0, classes=None):
"""
Load the MNIST dataset
Args:
onehot_encode: Boolean indicating whether to one-hot encode training
and test labels (default True)
flatten_x: Boolean indicating whether to flatten the training... | for repeat_idx in range(np.amax(variable_importances["repeat_idx"].unique()+1)):
df = variable_importances.loc[
(variable_importances["method"]==method) &
(variable_importances["repeat_idx"]==repeat_idx) &
(variable_importances[... | conditional_block |
utils.py | if len(df)==0:
continue
preds, labels = df["value"].values, df["causal"].values.astype(float)
fpr, tpr, _ = roc_curve(labels, np.abs(preds))
interp_tpr = np.interp(base_fpr, fpr, tpr)
auroc = auc(fpr, tpr)
... | compute_power | identifier_name | |
utils.py | 1].plot(range(total_epochs), bnn.fit_history.history["val_{}".format(this_metric)], '-o', label="validation")
axes[i+1].legend()
axes[i+1].set_ylabel(this_metric)
axes[i+1].set_xlabel("epoch")
plt.tight_layout()
return fig, axes
def make_1d2d(arr):
assert arr.ndim == 1
return arr.reshape(arr.shape[0], 1)... |
if crop_x > 0:
x_train = crop(x_train, crop_x)
x_test = crop(x_test, crop_x)
# Flatten to 2d arrays (each example 1d)
def flatten_image(X):
return X.reshape(X.shape[0], X.shape[1]*X.shape[1])
if flatten_x:
x_train = flatten_image(x_train)
x_test = flatten_image(x_test)
if onehot_encode:
y_train ... | assert crop_x < X.shape[1]/2
assert crop_x < X.shape[2]/2
return X[:,crop_size:-crop_size,crop_size:-crop_size] | identifier_body |
analysis.py | :param data: Data in which to detect outliers. Take care that n_samples > n_features ** 2 .
:type data: pandas.DataFrame
:param contamination: The amount of contamination of the data set, i.e. the proportion of outliers in the data set.
Range is (0, 0.5).
:type contamination: float
:returns: Dec... |
return vectors
def get_pca_vectors_by(dataframe, by=None):
""" Get principal components for each group as vectors. Vectors can then be used to annotate graphs.
:param dataframe: Data holding 'df1' and 'df2' values as columns.
:type dataframe: pandas.DataFrame
:param by: Column to group data... | v = row[['x', 'y']].values * np.sqrt(row['var_expl']) * 3 # Scale up for better visibility.
mean = row[['meanx', 'meany']].values
mean_offset = (mean, mean + v)
vectors.append(mean_offset) | conditional_block |
analysis.py | frame with columns mean, var, count and column names of data as rows.
:rtype: pandas.Dataframe
"""
# There's a bug in pandas 1.0.4 where you can't use custom numpy functions in agg anymore (ValueError).
# Note that the variance of projections is usually divided by (n-d) for Vucm and d for Vort. Both are... | " 3 x (3) Two-way split-plot ANOVA with between-factor condition and within-factor block.
:param dataframe: Aggregated data containing Fisher-z-transformed synergy index.
:type dataframe: pandas.DataFrame
:return: mixed-design ANOVA results.
:rtype: pandas.DataFrame
"""
if dataframe['condit... | identifier_body | |
analysis.py | try:
# df1 and df2 have the same scale. No need to standardize. Standardizing might actually distort PCA here.
pca.fit(x)
except ValueError:
# Return empty.
df = pd.DataFrame(columns=['var_expl', 'var_expl_ratio', 'x', 'y', 'meanx', 'meany'])
else:
df = pd.DataFrame({... | try:
dV = n * (variances['parallel']/(n-d) - variances['orthogonal']/d) \ | random_line_split | |
analysis.py | :param data: Data in which to detect outliers. Take care that n_samples > n_features ** 2 .
:type data: pandas.DataFrame
:param contamination: The amount of contamination of the data set, i.e. the proportion of outliers in the data set.
Range is (0, 0.5).
:type contamination: float
:returns: Dec... | (dataframe):
""" Get principal components as vectors. Vectors can then be used to annotate graphs.
:param dataframe: Tabular PCA data.
:type dataframe: pandas.DataFrame
:return: Principal components as vector pairs in input space with mean as origin first and offset second.
:rtype: list
"""... | get_pca_vectors | identifier_name |
system_information.rs | fn parts(&self) -> &'a UndefinedStruct {
self.parts
}
}
impl<'a> SMBiosSystemInformation<'a> {
/// Manufacturer
pub fn manufacturer(&self) -> Option<String> {
self.parts.get_field_string(0x04)
}
/// Product name
pub fn product_name(&self) -> Option<String> {
self.pa... | Self { parts }
}
| identifier_body | |
system_information.rs | up.
pub fn wakeup_type(&self) -> Option<SystemWakeUpTypeData> {
self.parts
.get_field_byte(0x18)
.map(|raw| SystemWakeUpTypeData::from(raw))
}
/// SKU Number
///
/// This text string identifies a particular computer
/// configuration for sale. It is sometimes al... | /// Raw value
///
/// _raw_ is most useful when _value_ is None.
/// This is most likely to occur when the standard was updated but
/// this library code has not been updated to match the current
/// standard.
pub raw: u8,
/// The contained [SystemWakeUpType] value
pub value: SystemW... |
/// # System - Wake-up Type Data
pub struct SystemWakeUpTypeData { | random_line_split |
system_information.rs | .
pub fn wakeup_type(&self) -> Option<SystemWakeUpTypeData> {
self.parts
.get_field_byte(0x18)
.map(|raw| SystemWakeUpTypeData::from(raw))
}
/// SKU Number
///
/// This text string identifies a particular computer
/// configuration for sale. It is sometimes also
... | >(&self, serializer: S) -> Result<S::Ok, S::Error>
where
S: Serializer,
{
serializer.serialize_str(format!("{}", self).as_str())
}
}
/// # System - Wake-up Type Data
pub struct SystemWakeUpTypeData {
/// Raw value
///
/// _raw_ is most useful when _value_ is None.
/// This i... | rialize<S | identifier_name |
loader.rs | = data.fullname;
self.source = data.source;
self.source_other = data.source_other;
}
}
struct ImageData {
filename: String,
fullname: Option<String>,
source: Option<String>,
source_other: Option<String>,
// align
// frameDuration
}
#[derive(Debug, Default)]
pub struct PackInfo {
name: String,
author: Op... | println!("Unknown song field {}", name.local_name);
xml_skip_tag(&mut reader).unwrap();
State::Song(None)
}
},
XmlEvent::EndElement { .. } => {
if song_rhythm.is_empty() {
// TODO: be graceful
panic!("Empty rhythm");
}
let song = SongData {
name: song_nam... | "buildup" => State::Song(Some(SongField::Buildup)),
"buildupRhythm" => State::Song(Some(SongField::BuildupRhythm)),
_ => { | random_line_split |
loader.rs | {
pub info: PackInfo,
pub images: Vec<ImageLoader>,
pub songs: Vec<Song>,
}
pub struct ImageLoader {
//data: SurfaceContext
pub name: String,
pub fullname: Option<String>,
pub data: Surface,
pub source: Option<String>,
pub source_other: Option<String>,
}
pub struct SongData {
pub name: String,
pub title: ... | ResPack | identifier_name | |
lib.rs | NewLiability(
T::Index,
TechnicsFor<T>,
EconomicsFor<T>,
T::AccountId,
T::AccountId,
),
/// Liability report published.
NewReport(T::Index, ReportFor<T>),
}
#[pallet::error]
pub enum Error<T> {
/// Agreement proof... | (
uri: &str,
technics: & | get_params_proof | identifier_name |
lib.rs |
/// How to report of agreement execution.
type Report: dispatch::Parameter + Report<Self::Index, Self::AccountId>;
/// The overarching event type.
type Event: From<Event<Self>> + IsType<<Self as frame_system::Config>::Event>;
}
pub type TechnicsFor<T> =
<<T as Config>:... | /// How to make and process agreement between two parties.
type Agreement: dispatch::Parameter + Processing + Agreement<Self::AccountId>; | random_line_split | |
vrf.go | v *VRF) Disable() {
if v.enabled {
v.router.disable()
v.tap.disable()
if v.hostif != nil {
v.hostif.disable()
}
v.enabled = false
}
}
// Name returns the name of the VRF.
func (v *VRF) Name() string {
return v.name
}
func (v *VRF) String() string {
return v.name
}
// Index returns a unique identifie... | {
return fmt.Errorf("Adding a rule to %v failed for L3 tunnel: %v", vif, err)
} | conditional_block | |
vrf.go | := range remotes {
ft := NewFiveTuple()
ft.SrcIP = CreateIPAddr(remote)
ft.DstIP = CreateIPAddr(local)
ft.DstPort = dstPort
ft.Proto = proto
fiveTuples[i] = ft
}
return fiveTuples
}
func (v *VRF) addL3Tunnel(vif *VIF) error {
t := vif.Tunnel()
if t == nil {
return fmt.Errorf("%v is not tunnel.", vif... | GetVRFByName | identifier_name | |
vrf.go |
// should be called with lock held
func (vm *vrfManager) releaseIndex(vrf *VRF) {
vm.byIndex[int(vrf.index)] = nil
}
// NewVRF creates a VRF instance.
func NewVRF(name string) (*VRF, error) {
if !vrfMgr.re.MatchString(name) {
return nil, fmt.Errorf("Invalid VRF name: '%v'", name)
}
vrfMgr.mutex.Lock()
defer ... | {
// try from the nextIndex to the end
if vm.findSlot(vrf, vm.nextIndex, len(vm.byIndex)) {
return true
}
// try from the head to the nextIndex
return vm.findSlot(vrf, 0, vm.nextIndex)
} | identifier_body | |
vrf.go | return nil
}
if err = vif.setVRF(v); err != nil {
return err
}
// router -> VIF
if err = v.router.addVIF(vif); err != nil {
goto error1
}
// ICMP -> VIF
if err = v.tap.connect(vif.Outbound(), MatchOutVIF, vif); err != nil {
goto error2
}
// VIF -> router (DST_SELF)
if err = vif.connect(v.router.i... | if t.Security() == SecurityIPSec {
for _, nat := range createFiveTuples(t.remotes, t.local, IPP_UDP, PortRange{Start: 4500}) {
v.router.disconnect(Match5Tuple, nat)
}
} | random_line_split | |
brush.rs | fn depth_stencil_state() -> Option<wgpu::DepthStencilState> {
WorldPipelineBase::depth_stencil_state()
}
// NOTE: if the vertex format is changed, this descriptor must also be changed accordingly.
fn vertex_buffer_layouts() -> Vec<wgpu::VertexBufferLayout<'static>> {
vec![wgpu::VertexBu... | lightmap: Cow::Borrowed(lightmap.data()),
});
| random_line_split | |
brush.rs |
pub fn pipeline(&self) -> &wgpu::RenderPipeline {
&self.pipeline
}
pub fn bind_group_layouts(&self) -> &[wgpu::BindGroupLayout] {
&self.bind_group_layouts
}
pub fn bind_group_layout(&self, id: BindGroupLayoutId) -> &wgpu::BindGroupLayout {
assert!(id as usize >= BindGroupL... |
let layout_refs: Vec<_> = world_bind_group_layouts
.iter()
.chain(self.bind_group_layouts.iter())
.collect();
self.pipeline = BrushPipeline::recreate(device, compiler, &layout_refs, sample_count);
}
| identifier_body | |
brush.rs | BrushRendererBuilder {
BrushRendererBuilder {
bsp_data: bsp_model.bsp_data().clone(),
face_range: bsp_model.face_id..bsp_model.face_id + bsp_model.face_count,
leaves: if worldmodel {
Some(
bsp_model
.iter_leaves()
... |
let primary_frames: Vec<_> = primary
.iter()
.map(|f| {
self.create_brush_texture_frame(
state,
f.mipmap(BspTextureMipmap::Full),
width,
... | conditional_block | |
brush.rs | &self) -> &[wgpu::BindGroupLayout] {
&self.bind_group_layouts
}
pub fn bind_group_layout(&self, id: BindGroupLayoutId) -> &wgpu::BindGroupLayout {
assert!(id as usize >= BindGroupLayoutId::PerTexture as usize);
&self.bind_group_layouts[id as usize - BindGroupLayoutId::PerTexture as usiz... | ind_group_layouts( | identifier_name | |
glsl3.rs | : GLuint,
batch: Batch,
}
impl Glsl3Renderer {
pub fn new() -> Result<Self, Error> {
info!("Using OpenGL 3.3 renderer");
let program = TextShaderProgram::new(ShaderVersion::Glsl3)?;
let mut vao: GLuint = 0;
let mut ebo: GLuint = 0;
let mut vbo_instance: GLuint = 0;
... |
unsafe {
self.program.set_rendering_pass(RenderingPass::Background);
gl::DrawElementsInstanced(
gl::TRIANGLES,
6,
gl::UNSIGNED_INT,
ptr::null(),
self.batch.len() as GLsizei,
);
self.... | {
unsafe {
gl::BindTexture(gl::TEXTURE_2D, self.batch.tex());
}
*self.active_tex = self.batch.tex();
} | conditional_block |
glsl3.rs | ,
ptr::null(),
gl::STREAM_DRAW,
);
let mut index = 0;
let mut size = 0;
macro_rules! add_attr {
($count:expr, $gl_type:expr, $type:ty) => {
gl::VertexAttribPointer(
index,
... | /// Rendering is split into two passes; one for backgrounds, and one for text.
u_rendering_pass: GLint,
} | random_line_split | |
glsl3.rs | : GLuint,
batch: Batch,
}
impl Glsl3Renderer {
pub fn new() -> Result<Self, Error> {
info!("Using OpenGL 3.3 renderer");
let program = TextShaderProgram::new(ShaderVersion::Glsl3)?;
let mut vao: GLuint = 0;
let mut ebo: GLuint = 0;
let mut vbo_instance: GLuint = 0;
... | <'a> {
active_tex: &'a mut GLuint,
batch: &'a mut Batch,
atlas: &'a mut Vec<Atlas>,
current_atlas: &'a mut usize,
program: &'a mut TextShaderProgram,
}
impl<'a> TextRenderApi<Batch> for RenderApi<'a> {
fn batch(&mut self) -> &mut Batch {
self.batch
}
fn render_batch(&mut self) ... | RenderApi | identifier_name |
glsl3.rs | ::GenBuffers(1, &mut vbo_instance);
gl::BindVertexArray(vao);
// ---------------------
// Set up element buffer
// ---------------------
let indices: [u32; 6] = [0, 1, 3, 1, 2, 3];
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, ebo);
gl::Bu... | {
self.instances.len()
} | identifier_body | |
service.rs | /// A future that orchestrates the entire aggregator service.
// TODO: maybe add a HashSet or HashMap of clients who already
// uploaded their weights to prevent a client from uploading weights
// multiple times. Or we could just remove that ID from the
// `allowed_ids` map.
// TODO: maybe add a HashSet for clients th... | random_line_split | ||
service.rs | the aggregations.
aggregator: A,
/// A client for the coordinator RPC service.
rpc_client: coordinator::rpc::Client,
requests: ServiceRequests<A>,
aggregation_future: Option<AggregationFuture<A>>,
model_number: usize,
}
/// This trait defines the methods that an aggregator should
/// implem... | {
Self {
upload: self.upload.clone(),
download: self.download.clone(),
aggregate: self.aggregate.clone(),
select: self.select.clone(),
}
} | identifier_body | |
service.rs | that having it here would
// make it easier to bypass the HTTP layer, which is convenient
// for testing because we can simulate client with just
// AggregatorHandles. But maybe that's just another layer of
// complexity that is not worth it.
global_weights: Bytes,
/// The aggregator itself, w... | (&mut self, request: SelectRequest<A>) {
info!("handling select request");
let SelectRequest {
credentials,
response_tx,
} = request;
let (id, token) = credentials.into_parts();
self.allowed_ids.insert(id, token);
if response_tx.send(Ok(())).is_err... | handle_select_request | identifier_name |
service.rs | that having it here would
// make it easier to bypass the HTTP layer, which is convenient
// for testing because we can simulate client with just
// AggregatorHandles. But maybe that's just another layer of
// complexity that is not worth it.
global_weights: Bytes,
/// The aggregator itself, w... |
pin.poll_aggregation(cx);
Poll::Pending
}
}
pub struct ServiceRequests<A>(Pin<Box<dyn Stream<Item = Request<A>> + Send>>)
where
A: Aggregator;
impl<A> Stream for ServiceRequests<A>
where
A: Aggregator,
{
type Item = Request<A>;
fn poll_next(mut self: Pin<&mut Self>, cx: &mut Co... | {
return Poll::Ready(());
} | conditional_block |
utils.py | )
for args in
zip(names_list, thickness_list))
res = np.array(res)
Rs, Ts, As = res[:, 0, :], res[:, 1, :], res[:, 2, :]
return Rs, Ts, As
def merge_layers(categories, thicknesses):
'''
Merges consecutive layers with th... |
class TMM_sim():
def __init__(self, mats=['Ge'], wavelength=np.arange(0.38, 0.805, 0.01), substrate='Cr', substrate_thick=500):
'''
This class returns the spectrum given the designed structures.
'''
self.mats = mats
# include substrate
self.all_mats = mats + [substr... | for i in range(len(progress)):
print(progress[i], 0)
progress[i] = ['|'.join([l + ' ' + str(d) + ' nm' for l, d in zip(progress[i][0], progress[i][1])]), progress[i][2]]
return progress | identifier_body |
utils.py |
res = Parallel(n_jobs=num_workers)(delayed(spectrum)(args)
for args in
zip(names_list, thickness_list))
res = np.array(res)
Rs, Ts, As = res[:, 0, :], res[:, 1, :], res[:, 2, :]
return Rs, Ts, As
def merge_layers(categorie... | random_line_split | ||
utils.py | )
for args in
zip(names_list, thickness_list))
res = np.array(res)
Rs, Ts, As = res[:, 0, :], res[:, 1, :], res[:, 2, :]
return Rs, Ts, As
def merge_layers(categories, thicknesses):
'''
Merges consecutive layers with th... |
return progress
class TMM_sim():
def __init__(self, mats=['Ge'], wavelength=np.arange(0.38, 0.805, 0.01), substrate='Cr', substrate_thick=500):
'''
This class returns the spectrum given the designed structures.
'''
self.mats = mats
# include substrate
self.all_... | print(progress[i], 0)
progress[i] = ['|'.join([l + ' ' + str(d) + ' nm' for l, d in zip(progress[i][0], progress[i][1])]), progress[i][2]] | conditional_block |
utils.py | )
for args in
zip(names_list, thickness_list))
res = np.array(res)
Rs, Ts, As = res[:, 0, :], res[:, 1, :], res[:, 2, :]
return Rs, Ts, As
def | (categories, thicknesses):
'''
Merges consecutive layers with the same material types.
'''
thicknesses = thicknesses[1:-1]
c_output = [categories[0]]
t_output = [thicknesses[0]]
for i, (c, d) in enumerate(zip(categories[1:], thicknesses[1:])):
if c == c_output[-1]:
t_ou... | merge_layers | identifier_name |
ImpConcat-Recall.py | desired confounds from the confounds_regressors.tsv file from fmriprep, trim the columns corresponding to trimmed volumes, and save as a .txt file.
starttime = time.time()
confounds=[]
confounds_all=[]
mc_all=[]
ntr=[]
ntr=np.zeros((n_runs_recall,1))
for r in range(firstrun,lastrun+1):
fname='_ses-01_task-recall... |
# In[18]:
#truncate first n_trunc TRs
#confounds_trunc=confounds_selected[3:end]
epi_trunc=[]
#https://github.com/INCF/BrainImagingPipelines/blob/master/bips/workflows/gablab/wips/scripts/modular_nodes.py
print('Number of runs to concatenate:', n_runs_recall)
for run in range(firstrun,lastrun+1):#lastrun+1
ou... | import nipype.interfaces.fsl as fsl
import nipype.interfaces.freesurfer as fs
import os
if smooth_type == 'susan':
if fwhm == 0:
return in_file
smooth = create_susan_smooth()
smooth.base_dir = out_dir#os.getcwd()
smooth.inputs.inputnode.fwhm = fwhm
smooth.... | identifier_body |
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