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 |
|---|---|---|---|---|
tools.js | lowest;
},
// returns float with 2 decimals
calculateAvgPlusHighThreshold: function(avg_for_period, high_threshold) {
return parseFloat((avg_for_period * (1 + high_threshold)).toFixed(2));
},
// returns float
calculateAvgMinusLowThreshold: function(avg_for_period, low_threshold) {
return parseFloat((avg_f... | }
else { | random_line_split | |
tools.js | this.sum - this.sum_last + data_to_be_tested[len - 1].value_avg
}
this.sum_last = data_to_be_tested[0].value_avg;
return parseFloat((this.sum/len).toFixed(2));
},
// return highest sell price
// *****IT IS USING BUY PRICE! which should it be?
calculateHigh: function(data_to_be_tested) {
var highest = 0... | else {
return;
}
if (sell) {
return 'sell';
} else if (buy) {
return 'buy';
} else {
return 'do_nothing';
}
},
calculateValuesForGivenPeriod: function(hrs_in_period, interval_in_minutes) {
return ((hrs_in_period * 60) / interval_in_minutes); // 144 10-min incremetns in a 24 hr period)
},... | {
var high_for_period = this.calculateHigh(data_to_be_tested) // get avg for period
var low_for_period = this.calculateLow(data_to_be_tested) // get avg for period
var high_minus_high_threshold = (high_for_period * (1 - high_threshold)).toFixed(2);
var low_plus_low_threshold = (low_for_... | conditional_block |
lib.rs | pub struct Keys<'a, K, V> {
inner: Iter<'a, K, V>,
}
impl<'a, K, V> Iterator for Keys<'a, K, V> {
type Item = &'a K;
#[inline]
fn next(&mut self) -> Option<&'a K> {
self.inner.next().map(|(k, _)| k)
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
self.inner.size_... | // use alloc::vec::Vec;
/// Iterator over the keys | random_line_split | |
lib.rs | Map`.
#[inline]
pub fn new() -> Self {
Map::<K, V, AHasher>::default()
}
/// Create a `Map` with a given capacity
#[inline]
pub fn with_capacity(capacity: usize) -> Self {
Map {
store: Vec::with_capacity(capacity),
hasher: PhantomData,
}
}
}
... | (&self) -> Keys<'_, K, V> {
Keys { inner: self.iter() }
}
/// An iterator visiting all values in arbitrary order.
/// The iterator element type is `&'a V`.
pub fn values(&self) -> Values<'_, K, V> {
Values { inner: self.iter() }
}
/// Inserts a key-value pair into the map.
... | keys | identifier_name |
lib.rs | : self.store.iter_mut(),
}
}
/// Creates a raw entry builder for the HashMap.
///
/// Raw entries provide the lowest level of control for searching and
/// manipulating a map. They must be manually initialized with a hash and
/// then manually searched. After this, insertions into a vac... | {
IterMut {
inner: [].iter_mut(),
}
} | identifier_body | |
lib.rs | Hasher::default();
// let mut hasher = rustc_hash::FxHasher::default();
let mut hasher = H::default();
key.hash(&mut hasher);
hasher.finish()
}
/// An iterator visiting all key-value pairs in insertion order.
/// The iterator element type is `(&K, &V)`.
///
/// # E... | {
continue;
} | conditional_block | |
main_api_sentence.py | :param max_seq_length:
:param tokenizer: 初始化后的tokenizer
:param label_list:
:return:
"""
examples = []
for guid, content in enumerate(contents):
examples.append(
InputExample(guid=guid, text_a=content))
features = convert_examples_to_features(examples, label_list, ma... |
def load_examples(contents, max_seq_length, tokenizer, label_list, reverse_truncate=False):
"""
:param contents: eg: [('苹果很好用', '苹果')] 或者 [('苹果很好用', '苹果', '积极')] | random_line_split | |
main_api_sentence.py | = argparse.ArgumentParser()
args = parser.parse_args()
args.output_encoded_layers = True
args.output_attention_layers = True
args.output_att_score = True
args.output_att_sum = True
self.learning_rate = 2e-05
#学习率 warmup的比例
self.warmup_proportion = 0.1
... | dataset, sampler=eval_sampler, batch_size=self.predict_batch_size)
model.eval()
model.to(self.device)
# 起始时间
start_time = time.time()
# 存储预测值
pred_logits = []
for batch in tqdm(eval_dataloader, desc="评估中", disable=True):
input_ids, input_mask, segment_... | val_sampler = SequentialSampler(eval_dataset)
eval_dataloader = DataLoader(eval_ | conditional_block |
main_api_sentence.py | 最大的概率label
preds = np.argmax(pred_logits, axis=1)
if self.verbose:
print(f"preds: {preds}")
predictids = preds.tolist()
#获取最大概率的可能性，即分数
pred_logits_softmax = scipy.special.softmax(pred_logits, axis=1)
probability = np.max(pred_logits_softmax, axis=1)
p... | identifier_name | ||
main_api_sentence.py | parser = argparse.ArgumentParser()
args = parser.parse_args()
args.output_encoded_layers = True
args.output_attention_layers = True
args.output_att_score = True
args.output_att_sum = True
self.learning_rate = 2e-05
#学习率 warmup的比例
self.warmup_proportion = ... | print(
f"--- 评估{len(eval_dataset)}条数据的总耗时是 {cost_time} seconds, 每条耗时 {cost_time / len(eval | = segment_ids.to(self.device)
with torch.no_grad():
logits = model(input_ids, input_mask, segment_ids)
cpu_logits = logits.detach().cpu()
for i in range(len(cpu_logits)):
pred_logits.append(cpu_logits[i].numpy())
pred_logits = np.array(pred_lo... | identifier_body |
tf_train_loop.py | df_baseline = df_baseline.combine_first(truepos)
else:
df_baseline['latDeg'] = df_baseline['baseLatDeg']
df_baseline['lngDeg'] = df_baseline['baseLngDeg']
df_baseline['heightAboveWgs84EllipsoidM'] = df_baseline['baseHeightAboveWgs84EllipsoidM']
baseline_times = []
baseli... | phone_glob = next(os.walk(folder+"/"+track))[1]
print(folder, track, end=' ')
phones = {}
phone_names = []
if "train" in folder:
df_baseline = pd.read_csv("data/baseline_locations_train.csv")
else:
df_baseline = pd.read_csv("data/baseline_locations_test.csv")
df... | identifier_body | |
tf_train_loop.py | df_baseline = df_baseline.combine_first(truepos)
else:
df_baseline['latDeg'] = df_baseline['baseLatDeg']
df_baseline['lngDeg'] = df_baseline['baseLngDeg']
df_baseline['heightAboveWgs84EllipsoidM'] = df_baseline['baseHeightAboveWgs84EllipsoidM']
baseline_times = []
baseline_ecef_coo... |
shift_loss = tf.reduce_mean(tf.abs(shift1-shift2)) * 0.01
accel = derivative(speed)
accel = tf.squeeze(accel)
accel = tf.transpose(accel)
accs_loss_large = tf.reduce_mean(tf.nn.relu(tf.abs(accel) - 4))
accs_loss_small = ... | shift2 = speed*0.5 | random_line_split |
tf_train_loop.py | data_file = pickle.load(f)
except:
data_file = None
for phonepath in phone_glob:
phone = phonepath
phones[phone] = len(phones)
phone_names.append(phone)
print(phone, end=' ')
if False: #data_file != None:
model, times = tf_phone_model.createGpsPhone... | physics = 1. | conditional_block | |
tf_train_loop.py | _baseline = df_baseline.combine_first(truepos)
else:
df_baseline['latDeg'] = df_baseline['baseLatDeg']
df_baseline['lngDeg'] = df_baseline['baseLngDeg']
df_baseline['heightAboveWgs84EllipsoidM'] = df_baseline['baseHeightAboveWgs84EllipsoidM']
baseline_times = []
baseline_ecef_coords... | (optimizer, physics):
for _ in range(16):
with tf.GradientTape(persistent=True) as tape:
total_loss_psevdo = 0
total_loss_delta = 0
accs_loss_large = 0
accs_loss_small = 0
speed_loss_small = 0
for i in r... | train_step_gnss | identifier_name |
dashboard.go | ", err)
return nil, err
}
jsonBody, err := gabs.ParseJSON(bodyBuf)
if err != nil |
// 'set-cookie': ['t=UpnUzNztGWO7K8A%2BCYihZz056Bk%3D; Path=/; Expires=Sat, 16 Nov 2013 06:27:19 GMT',
// 'un=mgoff%40appcelerator.com; Path=/; Expires=Sat, 16 Nov 2013 06:27:19 GMT',
// 'sid=33f33a6b7f8fef7b0fc649654187d467; Path=/; Expires=Sat, 16 Nov 2013 06:27:19 GMT',
// 'dvid=2019bea3-9e7b-48e3-890f-00e3... | {
log.Errorf("Failed to parse response body. %v", err)
return nil, err
} | conditional_block |
dashboard.go | := bson.M{
"username": username,
"sid_360": sid_360,
"cookie": cookie,
}
return saveDashboardSession(db_session)
}
func getAndVerifyOrgInfoFrom360(username, sid string) (haveAccess bool, orgs []models.Org, err error) {
// reqTimeout := 20000; //20s
//curl -i -b connect.sid=s%3AaJaL7IWQ_cDvmVBeQRY997hf.... | findDashboardSession | identifier_name | |
dashboard.go | Vary: Accept-Encoding
Access-Control-Allow-Origin: *
Access-Control-Allow-Methods: GET, POST, PUT, PATCH, DELETE
Access-Control-Allow-Headers: Content-Type, api_key
Content-Type: application/json; charset=utf-8
Content-Length: 59
Set-Cookie: connect.sid=s%3AIEpzWmzs4MQJGJMEcLmjlZm_.Cyi4LlO8gP%2... | {
log.Debugf("save dashboard session for user %v", session["username"])
_, err := mongo.UpsertDocument(mongo.STRATUS_DASHBOARD_SESSIONS_COLL,
bson.M{"username": session["username"]}, session)
if err != nil {
log.Errorf("Failed to save dashboard session. %v", err)
return err
}
log.Debugf("Upserted %v into ... | identifier_body | |
dashboard.go | , err error) {
// reqTimeout := 20000; //20s
//curl -i -b connect.sid=s%3AaJaL7IWQ_cDvmVBeQRY997hf.vVzLV2aFvrYiEKmfdTARTuHessesQ0Xm87JvFESaus http://dashboard.appcelerator.com/api/v1/user/organizations
/*
response for invalid session
HTTP/1.1 401 Unauthorized
X-Frame-Options: SAMEORIGIN
Cache-Contr... |
if err != nil {
log.Errorf("Failed to find dashboard session. %v", err) | random_line_split | |
lib.rs | ();
//!
//! // start some readers
//! let readers: Vec<_> = (0..4).map(|_| {
//! let r = book_reviews_r.clone();
//! thread::spawn(move || {
//! loop {
//! let l = r.len();
//! if l == 0 {
//! thread::yield_now();
//! } else {
//! // th... | assert_stable | identifier_name | |
lib.rs | is atomic.
//! assert_eq!(l, 4);
//! break;
//! }
//! }
//! })
//! }).collect();
//!
//! // do some writes
//! book_reviews_w.insert("Adventures of Huckleberry Finn", "My favorite book.");
//! book_reviews_w.insert("Grimms' Fairy Tales", "Masterp... | {
Inner::with_capacity_and_hasher(self.meta, cap, self.hasher)
} | conditional_block | |
lib.rs | `.
//!
//! ```
//! use std::thread;
//! let (mut book_reviews_w, book_reviews_r) = evmap::new();
//!
//! // start some readers
//! let readers: Vec<_> = (0..4).map(|_| {
//! let r = book_reviews_r.clone();
//! thread::spawn(move || {
//! loop {
//! let l = r.len();
//! if l == 0 ... | /// same inputs. For keys of type `K`, the result must also be consistent between different clones | random_line_split | |
lib.rs | book_reviews_w.insert("Grimms' Fairy Tales", "Masterpiece.");
//! book_reviews_w.insert("Pride and Prejudice", "Very enjoyable.");
//! book_reviews_w.insert("The Adventures of Sherlock Holmes", "Eye lyked it alot.");
//! // expose the writes
//! book_reviews_w.publish();
//!
//! // you can ... | {
let inner = if let Some(cap) = self.capacity {
Inner::with_capacity_and_hasher(self.meta, cap, self.hasher)
} else {
Inner::with_hasher(self.meta, self.hasher)
};
let (mut w, r) = left_right::new_from_empty(inner);
w.append(write::Operation::MarkReady);... | identifier_body | |
results.js | (options) {
// allow jQuery object to be passed in
// in case a different version of jQuery is needed from the one globally defined
$ = options.jQuery || $;
// Init data
// remove group not needed for the following visualizations
var work_ = options.work;
var groups_ = options.groups.filter(function(d) {... | AlmViz | identifier_name | |
results.js | @return {JQueryObject}
*/
var addSource_ = function(source, label, results, sourceTotalValue, group, subgroup, $groupRow) {
var $row, $countLabel, $count,
total = sourceTotalValue;
$row = $groupRow
.append("div")
.attr("class", "alm-source")
.attr("id", "source-" + source.id + "... | viz.svg.append("g")
.attr("class", "y axis"); | random_line_split | |
results.js | .attr("class", "alert alert-info")
.text("There are currently no results");
return;
}
// Init basic options
var baseUrl_ = options.baseUrl;
var minItems_ = options.minItemsToShowGraph;
var formatNumber_ = d3.format(",d");
// extract publication date
// Construct date object from date par... | {
// allow jQuery object to be passed in
// in case a different version of jQuery is needed from the one globally defined
$ = options.jQuery || $;
// Init data
// remove group not needed for the following visualizations
var work_ = options.work;
var groups_ = options.groups.filter(function(d) { return d.... | identifier_body | |
results.js | } else |
// look to make sure browser support SVG
var hasSVG_ = document.implementation.hasFeature("http://www.w3.org/TR/SVG11/feature#BasicStructure", "1.1");
// to track if any metrics have been found
var metricsFound_;
/**
* Initialize the visualization.
* NB: needs to be accessible from the outside for i... | {
vizDiv = d3.select("#alm");
} | conditional_block |
provider.go | : true,
DefaultFunc: schema.EnvDefaultFunc("ARM_ENVIRONMENT", "public"),
},
"skip_provider_registration": {
Type: schema.TypeBool,
Optional: true, | DefaultFunc: schema.EnvDefaultFunc("ARM_SKIP_PROVIDER_REGISTRATION", false),
},
},
DataSourcesMap: map[string]*schema.Resource{
"azurerm_client_config": dataSourceArmClientConfig(),
},
ResourcesMap: map[string]*schema.Resource{
// These resources use the Azure ARM SDK
"azurerm_availability_set... | random_line_split | |
provider.go | StorageQueue(),
"azurerm_storage_table": resourceArmStorageTable(),
"azurerm_subnet": resourceArmSubnet(),
"azurerm_template_deployment": resourceArmTemplateDeployment(),
"azurerm_traffic_manager_endpoint": resourceArmTrafficManagerEndpoint(),
"azurerm_traffic_manage... | {
switch s := v.(type) {
case string:
s = base64Encode(s)
hash := sha1.Sum([]byte(s))
return hex.EncodeToString(hash[:])
default:
return ""
}
} | identifier_body | |
provider.go | : true,
DefaultFunc: schema.EnvDefaultFunc("ARM_ENVIRONMENT", "public"),
},
"skip_provider_registration": {
Type: schema.TypeBool,
Optional: true,
DefaultFunc: schema.EnvDefaultFunc("ARM_SKIP_PROVIDER_REGISTRATION", false),
},
},
DataSourcesMap: map[string]*schema.Resource{
... | (providerList []resources.Provider, client resources.ProvidersClient) error {
var err error
providerRegistrationOnce.Do(func() {
providers := map[string]struct{}{
"Microsoft.Compute": struct{}{},
"Microsoft.Cache": struct{}{},
"Microsoft.ContainerRegistry": struct{}{},
"Microsoft.C... | registerAzureResourceProvidersWithSubscription | identifier_name |
provider.go | : true,
DefaultFunc: schema.EnvDefaultFunc("ARM_ENVIRONMENT", "public"),
},
"skip_provider_registration": {
Type: schema.TypeBool,
Optional: true,
DefaultFunc: schema.EnvDefaultFunc("ARM_SKIP_PROVIDER_REGISTRATION", false),
},
},
DataSourcesMap: map[string]*schema.Resource{
... |
client.StopContext = p.StopContext()
// replaces the context between tests
p.MetaReset = func() error {
client.StopContext = p.StopContext()
return nil
}
// List all the available providers and their registration state to avoid unnecessary
// requests. This also lets us check if the provider crede... | {
return nil, err
} | conditional_block |
saver.go | time.Time // Time the connection was initiated.
Sequence int // Typically zero, but increments for long running connections.
Expiration time.Time // Time we will swap files and increment Sequence.
Writer io.WriteCloser
}
func newConnection(info *inetdiag.InetDiagMsg, timestamp time.Time) *Connection {
... | MarshalChans []MarshalChan
Done *sync.WaitGroup // All marshallers will call Done on this.
Connections map[uint64]*Connection
ClosingStats map[uint64]TcpStats // BytesReceived and BytesSent for connections that are closing.
ClosingTotals TcpStats
cache *cache.Cache
stats stats
eventSer... | // TODO - just export an interface, instead of the implementation.
type Saver struct {
Host string // mlabN
Pod string // 3 alpha + 2 decimal
FileAgeLimit time.Duration | random_line_split |
saver.go | .Time // Time the connection was initiated.
Sequence int // Typically zero, but increments for long running connections.
Expiration time.Time // Time we will swap files and increment Sequence.
Writer io.WriteCloser
}
func newConnection(info *inetdiag.InetDiagMsg, timestamp time.Time) *Connection |
// Rotate opens the next writer for a connection.
// Note that long running connections will have data in multiple directories,
// because, for all segments after the first one, we choose the directory
// based on the time Rotate() was called, and not on the StartTime of the
// connection. Long-running connections wi... | {
conn := Connection{Inode: info.IDiagInode, ID: info.ID.GetSockID(), UID: info.IDiagUID, Slice: "", StartTime: timestamp, Sequence: 0,
Expiration: time.Now()}
return &conn
} | identifier_body |
saver.go | .StartTime,
},
}
// FIXME: Error handling
bytes, _ := json.Marshal(msg)
conn.Writer.Write(bytes)
conn.Writer.Write([]byte("\n"))
}
type stats struct {
TotalCount int64
NewCount int64
DiffCount int64
ExpiredCount int64
}
func (s *stats) IncTotalCount() {
atomic.AddInt64(&s.TotalCount, 1)
}
func (... | {
idm, err := ar.RawIDM.Parse()
if err != nil {
log.Println("Closed:", ar.Timestamp.Format("15:04:05.000"), cookie, "idm parse error", stats)
} else {
log.Println("Closed:", ar.Timestamp.Format("15:04:05.000"), cookie, tcp.State(idm.IDiagState), stats)
}
closeLogCount--
} | conditional_block | |
saver.go | .Time // Time the connection was initiated.
Sequence int // Typically zero, but increments for long running connections.
Expiration time.Time // Time we will swap files and increment Sequence.
Writer io.WriteCloser
}
func newConnection(info *inetdiag.InetDiagMsg, timestamp time.Time) *Connection {
conn... | (host string, pod string, numMarshaller int, srv eventsocket.Server, anon anonymize.IPAnonymizer, ex *netlink.ExcludeConfig) *Saver {
m := make([]MarshalChan, 0, numMarshaller)
c := cache.NewCache()
// We start with capacity of 500. This will be reallocated as needed, but this
// is not a performance concern.
con... | NewSaver | identifier_name |
physical_plan.rs | (&self) -> Arc<Schema>;
/// Specifies how data is partitioned across different nodes in the cluster
fn output_partitioning(&self) -> Partitioning {
Partitioning::UnknownPartitioning(0)
}
/// Specifies the data distribution requirements of all the children for this operator
fn required_chil... |
pub fn memory_size(&self) -> usize {
self.columns.values().map(|c| c.memory_size()).sum()
}
}
macro_rules! build_literal_array {
($LEN:expr, $BUILDER:ident, $VALUE:expr) => {{
let mut builder = $BUILDER::new($LEN);
for _ in 0..$LEN {
builder.append_value($VALUE)?;
... | } | random_line_split |
physical_plan.rs | _literal_array!(*n, StringBuilder, value),
other => Err(ballista_error(&format!(
"Unsupported literal type {:?}",
other
))),
},
}
}
pub fn memory_size(&self) -> usize {
//TODO delegate to Arrow once https://issu... | compile_aggregate_expressions | identifier_name | |
transaction.go | once = br.ReadU32LE()
t.SystemFee = int64(br.ReadU64LE())
t.NetworkFee = int64(br.ReadU64LE())
t.ValidUntilBlock = br.ReadU32LE()
nsigners := br.ReadVarUint()
if br.Err != nil {
return
}
if nsigners > MaxAttributes {
br.Err = errors.New("too many signers")
return
} else if nsigners == 0 {
br.Err = error... | isValid | identifier_name | |
transaction.go | VarUint()
if nattrs > MaxAttributes-nsigners {
br.Err = errors.New("too many attributes")
return
}
t.Attributes = make([]Attribute, nattrs)
for i := 0; i < int(nattrs); i++ {
t.Attributes[i].DecodeBinary(br)
}
t.Script = br.ReadVarBytes(MaxScriptLength)
if br.Err == nil {
br.Err = t.isValid()
}
if buf ... | {
if t.Signers[i].Account.Equals(t.Signers[j].Account) {
return ErrNonUniqueSigners
}
} | conditional_block | |
transaction.go | Version uint8
// Random number to avoid hash collision.
Nonce uint32
// Fee to be burned.
SystemFee int64
// Fee to be distributed to consensus nodes.
NetworkFee int64
// Maximum blockchain height exceeding which
// transaction should fail verification.
ValidUntilBlock uint32
// Code to run in NeoVM for... | // The trading version which is currently 0. | random_line_split | |
transaction.go | Attributes []Attribute
// Transaction signers list (starts with Sender).
Signers []Signer
// The scripts that comes with this transaction.
// Scripts exist out of the verification script
// and invocation script.
Scripts []Witness
// size is transaction's serialized size.
size int
// Hash of the transactio... |
// GetAttributes returns the list of transaction's attributes of the given type.
// Returns nil in case if attributes not found.
func (t *Transaction) GetAttributes(typ AttrType) []Attribute {
var result []Attribute
for _, attr := range t.Attributes {
if attr.Type == typ {
result = append(result, attr)
}
}
... | {
for i := range t.Attributes {
if t.Attributes[i].Type == typ {
return true
}
}
return false
} | identifier_body |
time_zones.rs | Formatter) -> fmt::Result {
write!(formatter, "LocalTimeConversionError")
}
}
/// Implemented for time zones where `LocalTimeConversionError` never occurs,
/// namely for `Utc` and `FixedOffsetFromUtc`.
///
/// Any UTC-offset change in a time zone creates local times that either don’t occur or occur twice.... | FixedOffsetFromUtc {
FixedOffsetFromUtc::from_hours_and_minutes(1, 0)
}
fn offset_during_dst(&self) -> FixedOffsetFromUtc {
FixedOffsetFromUtc::from_hours_and_minutes(2, 0)
}
fn is_in_dst(&self, t: UnixTimestamp) -> bool {
use Month::*;
let d = DateTime::from_timestamp... | ide_dst(&self) -> | identifier_name |
time_zones.rs | fn to_timestamp(&self, d: &NaiveDateTime) -> Result<UnixTimestamp, LocalTimeConversionError>;
}
/// When a time zone makes clock jump forward or back at any instant in time
/// (for example twice a year with daylight-saving time, a.k.a. summer-time period)
/// This error is returned when either:
///
/// * Clocks w... |
pub trait TimeZone {
fn from_timestamp(&self, t: UnixTimestamp) -> NaiveDateTime; | random_line_split | |
selector.rs | Err(io::Error::new(
io::ErrorKind::InvalidInput,
"Most-significant bit of token must remain unset.",
));
}
Ok(match reg_type {
RegType::Fd => key,
RegType::Handle => key | msb,
})
}
fn token_and_type_from_key(key: u64) -> (Token, RegType) {
let msb = 1u... | .push(Event::new(epoll_event_to_ready(events), token));
Ok(false)
}
}
}
/// Register event interests for the given IO handle with the OS
pub fn register_fd(
&self,
handle: &zircon::Handle,
fd: &EventedFd,
token: Token,
... | random_line_split | |
selector.rs | (io::Error::new(
io::ErrorKind::InvalidInput,
"Most-significant bit of token must remain unset.",
));
}
Ok(match reg_type {
RegType::Fd => key,
RegType::Handle => key | msb,
})
}
fn token_and_type_from_key(key: u64) -> (Token, RegType) {
let msb = 1u64 <... | (&self) -> &Arc<zircon::Port> {
&self.port
}
/// Reregisters all registrations pointed to by the `tokens_to_rereg` list
/// if `has_tokens_to_rereg`.
fn reregister_handles(&self) -> io::Result<()> {
// We use `Ordering::Acquire` to make sure that we see all `tokens_to_rereg`
// ... | port | identifier_name |
selector.rs | (io::Error::new(
io::ErrorKind::InvalidInput,
"Most-significant bit of token must remain unset.",
));
}
Ok(match reg_type {
RegType::Fd => key,
RegType::Handle => key | msb,
})
}
fn token_and_type_from_key(key: u64) -> (Token, RegType) {
let msb = 1u64 <... |
None => zircon::ZX_TIME_INFINITE,
};
let packet = match self.port.wait(deadline) {
Ok(packet) => packet,
Err(zircon::Status::ErrTimedOut) => return Ok(false),
Err(e) => Err(e)?,
};
let observed_signals = match packet.contents() {
... | {
let nanos = duration
.as_secs()
.saturating_mul(1_000_000_000)
.saturating_add(duration.subsec_nanos() as u64);
zircon::deadline_after(nanos)
} | conditional_block |
selector.rs | RegType) {
let msb = 1u64 << 63;
(
Token((key & !msb) as usize),
if (key & msb) == 0 {
RegType::Fd
} else {
RegType::Handle
},
)
}
/// Each Selector has a globally unique(ish) ID associated with it. This ID
/// gets tracked by `TcpStream`, `TcpListen... | {
self.token_to_fd.lock().unwrap().remove(&token);
// We ignore NotFound errors since oneshots are automatically deregistered,
// but mio will attempt to deregister them manually.
self.port
.cancel(&*handle, token.0 as u64)
.map_err(io::Error::from)
.... | identifier_body | |
policy_distillation.py | _size, self.hidden_size),
nn.ReLU(inplace=True),
nn.Linear(self.hidden_size, self.output_size)
)
def forward(self, input):
input = input.view(-1, self.input_size)
return F.softmax(self.fc(input), dim=1)
... | (self, save_path, _locals=None):
assert self.model is not None, "Error: must train or load model before use"
with open(save_path, "wb") as f:
pickle.dump(self.__dict__, f)
@classmethod
def load(cls, load_path, args=None):
with open(load_path, "rb") as f:
class_di... | save | identifier_name |
policy_distillation.py | , img_shape=img_shape)
def forward(self, input):
return F.softmax(self.model(input), dim=1)
class PolicyDistillationModel(BaseRLObject):
"""
Implementation of PolicyDistillation
"""
def __init__(self):
super(PolicyDistillationModel, self).__init__()
def save(self, save_path, ... | param.requires_grad = True
learnable_params += [param for param in self.srl_model.model.parameters()]
learning_rate = 1e-3 | random_line_split | |
policy_distillation.py | _size, self.hidden_size),
nn.ReLU(inplace=True),
nn.Linear(self.hidden_size, self.output_size)
)
def forward(self, input):
input = input.view(-1, self.input_size)
return F.softmax(self.fc(input), dim=1)
... |
def getActionProba(self, observation, dones=None, delta=0):
"""
returns the action probability distribution, from a given observation.
:param observation: (numpy int or numpy float)
:param dones: ([bool])
:param delta: (numpy float or float) The exploration noise applied to... | parser.add_argument('--nothing4instance', help='Number of population (each one has 2 threads)', type=bool,
default=True)
return parser | identifier_body |
policy_distillation.py | _size, self.hidden_size),
nn.ReLU(inplace=True),
nn.Linear(self.hidden_size, self.output_size)
)
def forward(self, input):
input = input.view(-1, self.input_size)
return F.softmax(self.fc(input), dim=1)
... |
observation = th.from_numpy(observation).float().requires_grad_(False).to(self.device)
if sample:
proba_actions = self.model.forward(observation).detach().cpu().numpy().flatten()
return np.random.choice(range(len(proba_actions)), 1, p=proba_actions)
else:
re... | observation = np.transpose(observation, (0, 3, 2, 1)) | conditional_block |
WarpController.ts | Name: 'InitialReporterRedeemed' },
{ databaseName: 'InitialReportSubmitted' },
{ databaseName: 'InitialReporterTransferred' },
{ databaseName: 'MarketCreated' },
{ databaseName: 'MarketFinalized' },
{ databaseName: 'MarketMigrated' },
{ databaseName: 'MarketParticipantsDisavowed' },
{ databaseName: 'Marke... | {
return this.db.warpCheckpoints.getMostRecentCheckpoint();
} | identifier_body | |
WarpController.ts | { Checkpoints } from './Checkpoints';
export const WARPSYNC_VERSION = '1';
const FILE_FETCH_TIMEOUT = 30000; // 10 seconds
type NameOfType<T, R> = {
[P in keyof T]: T[P] extends R ? P : never;
}[keyof T];
type AllDBNames = NameOfType<DB, Dexie.Table<Log, unknown>>;
type AllDbs = {
[P in AllDBNames]: DB[P] exten... |
await this.db.warpCheckpoints.createInitialCheckpoint(
await this.provider.getBlock(this.uploadBlockNumber),
market
);
}
}
async destroyAndRecreateDB() {
await this.db.delete();
await this.db.initializeDB();
}
async createCheckpoint(endBlock: Block): Promise<IpfsInfo>... | {
console.log(
`Warp sync market not initialized for current universe ${this.augur.contracts.universe.address}.`
);
return;
} | conditional_block |
WarpController.ts | { Checkpoints } from './Checkpoints';
export const WARPSYNC_VERSION = '1';
const FILE_FETCH_TIMEOUT = 30000; // 10 seconds
type NameOfType<T, R> = {
[P in keyof T]: T[P] extends R ? P : never;
}[keyof T];
type AllDBNames = NameOfType<DB, Dexie.Table<Log, unknown>>;
type AllDbs = {
[P in AllDBNames]: DB[P] exten... | }
onNewBlock = async (newBlock: Block): Promise<string | void> => {
await this.createInitialCheckpoint();
/*
0. Base case: need to have created initial warp checkpoint.
1. Check if we need to create warp sync
1. This will happen if the active market endTime has elapsed
2. Check if... |
async getIpfs(): Promise<IPFS> {
return this.ipfs; | random_line_split |
WarpController.ts | { Checkpoints } from './Checkpoints';
export const WARPSYNC_VERSION = '1';
const FILE_FETCH_TIMEOUT = 30000; // 10 seconds
type NameOfType<T, R> = {
[P in keyof T]: T[P] extends R ? P : never;
}[keyof T];
type AllDBNames = NameOfType<DB, Dexie.Table<Log, unknown>>;
type AllDbs = {
[P in AllDBNames]: DB[P] exten... | () {
await this.db.delete();
await this.db.initializeDB();
}
async createCheckpoint(endBlock: Block): Promise<IpfsInfo> {
const logs = [];
for (const { databaseName } of databasesToSync) {
// Awaiting here to reduce load on db.
logs.push(
await this.db[databaseName]
.w... | destroyAndRecreateDB | identifier_name |
worker.go | if it is not, it is not clear
// why, because the name is delegated to this server according to the parent zone, so we assume that this server
// is broken, but there might be other reasons for this that I can't think off from the top of my head.
return nil, errors.NewErrorStack(fmt.Errorf("resolveFromWith: got ... | random_line_split | ||
worker.go | about all other records that might resides here.
return nameresolver.NewAliasEntry(w.req.Name(), rr.Target), nil
}
}
}
// We now query for the AAAA records to also get the IPv6 addresses
clnt = new(dns.Client)
clnt.Net = proto
maaaa := new(dns.Msg)
maaaa.SetEdns0(4096, false)
maaaa.SetQuestion(w.req.... | {
err.Push(fmt.Errorf("resolve: error while getting zone cut info of %s for %s", reqName, w.req.Name()))
return nil, err
} | conditional_block | |
worker.go |
// newWorker builds a new worker instance and returns it.
// The worker is started and will resolve the request from a cache file.
func newWorkerWithCachedResult(req *nameresolver.Request, nrHandler func(*nameresolver.Request) *errors.ErrorStack, zcHandler func(*zonecut.Request) *errors.ErrorStack, cf *nameresolver.C... | {
w := initNewWorker(req, nrHandler, zcHandler, conf)
w.start()
return w
} | identifier_body | |
worker.go | to the requested topic, or an
// definitive error that happened during the resolution.
func (w *worker) resolveFromWith(ip net.IP, proto string) (*nameresolver.Entry, *errors.ErrorStack) {
var ipList []net.IP
// We first query about the IPv4 addresses associated to the request topic.
clnt := new(dns.Client)
clnt.... | resolveFromGluelessNameSrvs | identifier_name | |
project_tasks.py | from ConfigParser import ConfigParser, NoSectionError
# noinspection PyUnresolvedReferences
from herring.herring_app import task, HerringFile
# noinspection PyUnresolvedReferences
from herringlib.simple_logger import info, debug
# noinspection PyUnresolvedReferences
from herringlib.local_shell import LocalShell
#... | ():
"""Show all project settings with descriptions"""
keys = Project.__dict__.keys()
for key in sorted(keys):
value = Project.__dict__[key]
if key in ATTRIBUTES:
attrs = ATTRIBUTES[key]
required = False
if 'required' in attrs:
if attrs['req... | describe | identifier_name |
project_tasks.py | from ConfigParser import ConfigParser, NoSectionError
# noinspection PyUnresolvedReferences
from herring.herring_app import task, HerringFile
# noinspection PyUnresolvedReferences
from herringlib.simple_logger import info, debug
# noinspection PyUnresolvedReferences
from herringlib.local_shell import LocalShell
#... |
@task(namespace='project', configured='optional')
def describe():
"""Show all project settings with descriptions"""
keys = Project.__dict__.keys()
for key in sorted(keys):
value = Project.__dict__[key]
if key in ATTRIBUTES:
attrs = ATTRIBUTES[key]
required = False
... | """Show all project settings"""
info(str(Project)) | identifier_body |
project_tasks.py | from ConfigParser import ConfigParser, NoSectionError
# noinspection PyUnresolvedReferences
from herring.herring_app import task, HerringFile
# noinspection PyUnresolvedReferences
from herringlib.simple_logger import info, debug
# noinspection PyUnresolvedReferences
from herringlib.local_shell import LocalShell
#... |
@task(namespace='project', configured='optional')
def show():
"""Show all project settings"""
info(str(Project))
@task(namespace='project', configured='optional')
def describe():
"""Show all project settings with descriptions"""
keys = Project.__dict__.keys()
for key in sorted(keys):
va... | defaults = _project_defaults()
template = Template()
for template_dir in [os.path.abspath(os.path.join(herringlib, 'herringlib', 'templates'))
for herringlib in HerringFile.herringlib_paths]:
info("template directory: %s" % template_dir)
# noinspec... | conditional_block |
project_tasks.py | except ImportError:
# python2
# noinspection PyUnresolvedReferences,PyCompatibility
from ConfigParser import ConfigParser, NoSectionError
# noinspection PyUnresolvedReferences
from herring.herring_app import task, HerringFile
# noinspection PyUnresolvedReferences
from herringlib.simple_logger import info,... | try:
# python3
# noinspection PyUnresolvedReferences,PyCompatibility
from configparser import ConfigParser, NoSectionError | random_line_split | |
container.go | &Container{
logger: logger,
Name: name,
runtime: runtime,
client: client,
}
}
// MakeContainer constructs a suitable Container object.
//
// The runtime used is determined by the runtime flag.
//
// Containers will check flags for profiling requests.
func MakeContainer(ctx context.Context, logger testut... | (r RunOpts, args []string) *container.Config {
ports := nat.PortSet{}
for _, p := range r.Ports {
port := nat.Port(fmt.Sprintf("%d", p))
ports[port] = struct{}{}
}
env := append(r.Env, fmt.Sprintf("RUNSC_TEST_NAME=%s", c.Name))
return &container.Config{
Image: testutil.ImageByName(r.Image),
Cmd: ... | config | identifier_name |
container.go | &Container{
logger: logger,
Name: name,
runtime: runtime,
client: client,
}
}
// MakeContainer constructs a suitable Container object.
//
// The runtime used is determined by the runtime flag.
//
// Containers will check flags for profiling requests.
func MakeContainer(ctx context.Context, logger testut... | return makeContainer(ctx, logger, unsandboxedRuntime)
}
// Spawn is analogous to 'docker run -d'.
func (c *Container) Spawn(ctx context.Context, r RunOpts, args ...string) error {
if err := c.create(ctx, r.Image, c.config(r, args), c.hostConfig(r), nil); err != nil {
return err
}
return c.Start(ctx)
}
// SpawnP... | func MakeNativeContainer(ctx context.Context, logger testutil.Logger) *Container {
unsandboxedRuntime := "runc"
if override, found := os.LookupEnv("UNSANDBOXED_RUNTIME"); found {
unsandboxedRuntime = override
} | random_line_split |
container.go | Container{
logger: logger,
Name: name,
runtime: runtime,
client: client,
}
}
// MakeContainer constructs a suitable Container object.
//
// The runtime used is determined by the runtime flag.
//
// Containers will check flags for profiling requests.
func MakeContainer(ctx context.Context, logger testutil... |
return nil
}
// Stop is analogous to 'docker stop'.
func (c *Container) Stop(ctx context.Context) error {
return c.client.ContainerStop(ctx, c.id, container.StopOptions{})
}
// Pause is analogous to'docker pause'.
func (c *Container) Pause(ctx context.Context) error {
return c.client.ContainerPause(ctx, c.id)
}
... | {
if err := c.profile.Start(c); err != nil {
c.logger.Logf("profile.Start failed: %v", err)
}
} | conditional_block |
container.go | Container{
logger: logger,
Name: name,
runtime: runtime,
client: client,
}
}
// MakeContainer constructs a suitable Container object.
//
// The runtime used is determined by the runtime flag.
//
// Containers will check flags for profiling requests.
func MakeContainer(ctx context.Context, logger testutil... |
// RootDirectory returns an educated guess about the container's root directory.
func (c *Container) RootDirectory() (string, error) {
// The root directory of this container's runtime.
rootDir := fmt.Sprintf("/var/run/docker/runtime-%s/moby", c.runtime)
_, err := os.Stat(rootDir)
if err == nil {
return rootDir... | {
return c.id
} | identifier_body |
combine.py |
# If nothing was found then don't continue, this can happen if no mp4 files are found or if only the joined file is found
if( len(file_infos) <= 0 ):
print( "No mp4 video files found matching '{0}'".format(args.match))
sys.exit(0)
print("Found {0} files".format(len(file_infos)))
# If the... | file_infos.append(m4b_fileinfo) | conditional_block | |
combine.py | dur']
# Do we have a proposed cut duration, if so then we must use this info
# to correct the chapter locations
if not cuts is None and file_name in cuts and 't' in cuts[file_name]:
file_info_dur = timedelta(seconds=cuts[file_name]['t'])
chapters.append({"name": Path(file_info['f... | print("Command {0} returned non-zero exit status {1}.".format(proc_cmd, ret.returncode))
print("File {0} will be skipped".format(file_name))
return None
#ret.check_returncode()
# Computed Duration 00:23:06.040 - Indicated Duration 00:23:06.040
match = regex_mp4box_duration.search( ret.stdout )
hrs ... | random_line_split | |
combine.py | error
raise ValueError('Could not locate FFMPEG install, please use the --ffmpeg switch to specify the path to the ffmpeg.exe file on your system.')
#
# Returns an array of files matching the grep string passed in
def getFileNamesFromGrepMatch(grep_match, path_out_file):
in_files = glob.glob(grep_match.replace("... | path_video_file.exists():
raise ValueError("Video file {0} could not be found. Nothing was split.".format(path_video_file))
# Construct the args to mp4box
prog_args = [mp4box_path]
# Specify the maximum split size
prog_args.append("-splits")
prog_args.append(str(max_out_size_kb))
# Overwrite the def... | identifier_body | |
combine.py | CombinedVideoFile(video_files, chapters, cumulative_dur, cumulative_size, mp4exec, ffmpegexec, path_out_file, path_chapters_file, args.overwrite, cuts, args.videosize, args.burnsubs, max_out_size_kb, args.noaudio )
print(Colors.success("Script completed successfully, bye!"))
finally:
deinit() #Deinitiali... | getFileNamesFromGrepMatch | identifier_name | |
window.rs | new(
grid_id: u64,
window_type: WindowType,
anchor_info: Option<AnchorInfo>,
grid_position: (f64, f64),
grid_size: (u64, u64),
draw_command_batcher: Arc<DrawCommandBatcher>,
) -> Window {
let window = Window {
grid_id,
grid: CharacterG... |
pub fn redraw(&self) {
self.send_command(WindowDrawCommand::Clear);
// Draw the lines from the bottom up so that underlines don't get overwritten by the line
// below.
for row in (0..self.grid.height).rev() {
self.redraw_line(row);
}
}
pub fn hide(&self... | {
self.grid.clear();
self.send_command(WindowDrawCommand::Clear);
} | identifier_body |
window.rs | new(
grid_id: u64,
window_type: WindowType,
anchor_info: Option<AnchorInfo>,
grid_position: (f64, f64),
grid_size: (u64, u64),
draw_command_batcher: Arc<DrawCommandBatcher>,
) -> Window {
let window = Window {
grid_id,
grid: CharacterG... | (&self, command: WindowDrawCommand) {
self.draw_command_batcher
.queue(DrawCommand::Window {
grid_id: self.grid_id,
command,
})
.ok();
}
fn send_updated_position(&self) {
self.send_command(WindowDrawCommand::Position {
... | send_command | identifier_name |
window.rs | new(
grid_id: u64,
window_type: WindowType,
anchor_info: Option<AnchorInfo>,
grid_position: (f64, f64),
grid_size: (u64, u64),
draw_command_batcher: Arc<DrawCommandBatcher>,
) -> Window {
let window = Window {
grid_id,
grid: CharacterG... |
self.redraw_line(row);
if row > 0 {
self.redraw_line(row - 1);
}
} else {
warn!("Draw command out of bounds");
}
}
pub fn scroll_region(
&mut self,
top: u64,
bottom: u64,
left: u64,
right: u... | {
self.redraw_line(row + 1);
} | conditional_block |
window.rs | fn new(
grid_id: u64,
window_type: WindowType,
anchor_info: Option<AnchorInfo>,
grid_position: (f64, f64),
grid_size: (u64, u64),
draw_command_batcher: Arc<DrawCommandBatcher>,
) -> Window {
let window = Window {
grid_id,
grid: Charact... | }
let line_fragment = LineFragment {
text,
window_left: start,
window_top: row_index,
width,
style: style.clone(),
};
(start + width, line_fragment)
}
// Redraw line by calling build_line_fragment starting at 0
//... | }
// Add the grid cell to the cells to render.
text.push_str(character); | random_line_split |
Projeto.py | icao, s tem de ser str
# de tamanho 1, e verificacao_letras_mgc tem de ser verdadeiro
if not e_pos (p) or not isinstance (s, str) or len(s) != 1 or not verificacao_letras_mgc (letras, mgc):
raise ValueError ('gera_chave_espiral: argumentos errados')
# Transforma em lista para poder ser... | (arg):
''' para ser do tipo chave tem de ser uma lista constituida por 5 listas cada uma com 5 elementos
que sejam letras maiusculas unicas'''
if len (arg) != | e_chave | identifier_name |
Projeto.py |
return c
# RECONHECEDORES
# e_chave: arg --> Boolean
# e_chave(arg): devolve True se o argumento arg for do tipo chave e Falso caso contrario
def e_chave (arg):
''' para ser do tipo chave tem de ser uma lista constituida por 5 listas cada uma com 5 elementos
que sejam letras maiusculas unicas'''
if ... | # codifica_r: posicao + posicao --> posicao + posicao
# codifica_r (pos1, pos2) recebe dois argumentos, pos1, pos2, consistindo nas
# posicoes das letras de um digrama numa chave. Estas posicoes encontra-se | random_line_split | |
Projeto.py | Verifica cada caracter dentro de mgc
for i in range (len( mgc)):
# Testa se o caracter nao esta ja em r e se esta em letras
if not mgc[i] in r and mgc[i] in letras:
# Se sim, junta-o a r
r += [mgc[i]]
# Remove de letras esse car... | if not ( 64 < ord(b) < 91):
return False | conditional_block | |
Projeto.py | :
return ('r',) + t
# codifica_l: posicao + posicao + {-1,1} --> posicao + posicao
# codifica_l (pos1, pos2, inc) recebe tres argumentos, pos1, pos2,
# consistindo nas posicoes das letras de um digrama na mesma linha de uma
# chave, e o inteiro inc, que podera ser 1 (encriptar) ou -1 (desencriptar... | mens = digramas (mens)
r = ''
# Codifica os caracteres dois a dois
for i in range (0, len(mens)-1, 2):
# Chama codifica_digrama que devolve dois caracteres codificados
r += codifica_digrama (mens[i:i+2], chave, inc)
return r | identifier_body | |
NEF_tester.py | ")
plotrange(lambda x: target(valtopair(x)),xmin,xmax,resolution,"target values")
# plotrange(lambda x:Error(layer.getaverage(valtopair(x)),target(valtopair(x)),1),xmin,xmax,resolution,"error")
ervals = [SQError(layer.getaverage(valtopair(x)),target(valtopair(x)),1) for x in [x/float(resolution) for x in ran... |
def initplot(layer):
x = -2
t = target(x)
for a in range(int(0.5/deltaT)):
tvals.append(a*deltaT)
xhatvals.append(layer.Process(x,deltaT))
x = -1
for a in range(int(0.5/deltaT)):
tvals.append(0.5+a*deltaT)
xhatvals.append(layer.Process(x,deltaT))
x = 1
for a... | yvals = [neuron.a(x) for x in xvals]
vallist = zip(map(pairtoval,xvals),yvals)
vallist.sort(key = lambda x:x[0])
xvals = [x[0] for x in vallist]
yvals = [x[1] for x in vallist]
plt.plot(xvals,yvals) | identifier_body |
NEF_tester.py | (p,target,deltaT):
return -(target-p)**2
def sigmoid(er):
return er
# return (2.0/(1.0+exp(-2*er))-1.0)
targetname = "target"
def weight_histogram(layer,binnum=None):
weights = [reduce(lambda x,synapse:x+synapse.inhibitory*synapse.Pval(),neuron.synapses,0) for neuron in layer.layer]
if(binnum =... | SQError | identifier_name | |
NEF_tester.py | ")
plotrange(lambda x: target(valtopair(x)),xmin,xmax,resolution,"target values")
# plotrange(lambda x:Error(layer.getaverage(valtopair(x)),target(valtopair(x)),1),xmin,xmax,resolution,"error")
ervals = [SQError(layer.getaverage(valtopair(x)),target(valtopair(x)),1) for x in [x/float(resolution) for x in ran... | plt.show()
if(presolve):
NEF.LeastSquaresSolve(xvals,target,layer,regularization=1000)
if(lstsq):
weight_histogram(layer,binnum=50)
plt.savefig("weight-histogram-"+str(numxvals)+"samples-"+str(layersize)+"neurons")
plt.show()
plotavs(layer,-400,400,1,savename = "cm-agnostic-decode-"+str(numxvals)... | if(lstsq):
plt.savefig("noisytuning-"+str(numxvals)+"samples-"+str(layersize)+"neurons") | random_line_split |
NEF_tester.py | plt.title("Noisy Tuning Curves")
if(lstsq):
plt.savefig("noisytuning-"+str(numxvals)+"samples-"+str(layersize)+"neurons")
plt.show()
if(presolve):
NEF.LeastSquaresSolve(xvals,target,layer,regularization=1000)
if(lstsq):
weight_histogram(layer,binnum=50)
plt.savefig("weight-histogram-"+str(numxvals)+"... | v = "0p4" | conditional_block | |
main.py | SPAM_DATA/trec07p/data'.format("/media/sumeet/147A710C7A70EBBC")
_SPAM_EMAIL_LABELS_PATH = '{}/SPAM_DATA/trec07p/full/index'.format("/media/sumeet/147A710C7A70EBBC")
_CACHED_FEATURE_INDEX_NAME_TEMPLATE = 'feature_matrix_cache/{}-{}-feature_index.json'
_CACHED_FEATURES_FILE_PATH_TEMPLATE = 'feature_matrix_ca... | (min_df=0.02, max_df=0.95):
min_df_value = int(min_df * len(corpus))
max_df_value = int(max_df * len(corpus))
_valid_ngrams = set()
for ngram, no_of_documents in all_ngrams.items():
if min_df_value < no_of_documents < max_df_value:
_val... | _get_valid_ngrams | identifier_name |
main.py | SPAM_DATA/trec07p/data'.format("/media/sumeet/147A710C7A70EBBC")
_SPAM_EMAIL_LABELS_PATH = '{}/SPAM_DATA/trec07p/full/index'.format("/media/sumeet/147A710C7A70EBBC")
_CACHED_FEATURE_INDEX_NAME_TEMPLATE = 'feature_matrix_cache/{}-{}-feature_index.json'
_CACHED_FEATURES_FILE_PATH_TEMPLATE = 'feature_matrix_ca... |
else:
_helper(body)
return parsed_email
@classmethod
def _get_email_contents_and_labels(cls, email_files, labels_dict, token_filter):
ix = 1
email_contents = []
labels = []
for cleaned_email in cls._get_emails(email_files):
ix += 1
... | _helper(part) | conditional_block |
main.py | import random
import re
import string
from collections import defaultdict
from typing import Dict
import numpy as np
from bs4 import BeautifulSoup
from nltk import SnowballStemmer
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
from scipy.sparse import csr_matrix
from sklearn.datasets import ... | import os | random_line_split | |
main.py | SPAM_DATA/trec07p/data'.format("/media/sumeet/147A710C7A70EBBC")
_SPAM_EMAIL_LABELS_PATH = '{}/SPAM_DATA/trec07p/full/index'.format("/media/sumeet/147A710C7A70EBBC")
_CACHED_FEATURE_INDEX_NAME_TEMPLATE = 'feature_matrix_cache/{}-{}-feature_index.json'
_CACHED_FEATURES_FILE_PATH_TEMPLATE = 'feature_matrix_ca... |
@classmethod
def _clean_email(cls, raw_email: Email) -> Email:
raw_email.cleaned_subject_tokens = cls._text_cleaning_helper(raw_email.subject)
raw_email.cleaned_body_tokens = cls._text_cleaning_helper(raw_email.body)
return raw_email
@classmethod
def _get_emails(cls, email_fil... | cleaned_tokens = []
tokens = word_tokenize(text_to_clean)
for token in tokens:
lowered_token = token.lower()
stripped_token = lowered_token.translate(cls._PUNCTUATION_TABLE)
if stripped_token.isalpha() and stripped_token not in cls._STOPWORDS_SET:
clea... | identifier_body |
func.py |
def rankdata(arr, axis=None):
"Slow rankdata function used for unaccelerated ndim/dtype combinations."
arr = np.asarray(arr)
if axis is None:
arr = arr.ravel()
axis = 0
elif axis < 0:
axis = range(arr.ndim)[axis]
y = np.empty(arr.shape)
itshape = list(arr.shape)
its... | "Slow nanargmax function used for unaccelerated ndim/dtype combinations."
with warnings.catch_warnings():
warnings.simplefilter("ignore")
return np.nanargmax(arr, axis=axis) | identifier_body | |
func.py | itshape):
ijslice = list(ij[:axis]) + [slice(None)] + list(ij[axis:])
x1d = arr[ijslice].astype(float)
mask1d = ~np.isnan(x1d)
x1d[mask1d] = scipy_rankdata(x1d[mask1d])
y[ijslice] = x1d
return y
def ss(arr, axis=0):
"Slow sum of squares used for unaccelerated ndim/dtype ... |
return a_min, a_max, | var *= non_nans / d | conditional_block |
func.py | _max = np.nanmin(arr), np.nanmax(arr)
if weights is None:
nans = np.sum(np.isnan(arr))
non_nans = len(arr) - nans
mean = np.nansum(arr) / non_nans
var = np.nansum((arr - mean) ** 2) / (non_nans - 1)
else:
tot_w = np.sum(weights)
nan... | _chk_asarray | identifier_name | |
func.py | itshape):
ijslice = list(ij[:axis]) + [slice(None)] + list(ij[axis:])
x1d = arr[ijslice].astype(float)
mask1d = ~np.isnan(x1d)
x1d[mask1d] = scipy_rankdata(x1d[mask1d])
y[ijslice] = x1d
return y
def ss(arr, axis=0):
"Slow sum of squares used for unaccelerated ndim/dtype ... | d = d.sum(axis)
idx = np.argmin(d)
return np.sqrt(d[idx]), idx
def partsort(arr, n, axis=-1):
"Slow partial sort used for unaccelerated ndim/dtype combinations."
return np.sort(arr, axis)
def argpartsort(arr, n, axis=-1):
"Slow partial argsort used for unaccelerated ndim/dtype combinations."
... | random_line_split | |
yintai.js | },400);
animate(shangzuos[0],{width:x},400);
animate(xiayous[0],{width:x},400);
}
zw4s.onmouseout=function(){
animate(zuoshangs[0],{height:0},400);
animate(youxias[0],{height:0},400);
animate(shangzuos[0],{width:0},400);
animate(xiayous[0],{width:0},400);
}
}
// 热门品牌动画
var zw4s=$('.zhengwen4')
for (v... | var wxs=$('.shouji')[0];
var hys=$(".shoujji")[0]; | random_line_split | |
yintai.js | {index=0};
// 循环遍历
for (var i = 0; i < as.length; i++) {
// 先把所有照片层级调低，轮播点的颜色为空
as[i].style.zIndex=0;
bodiandiv[i].style.background='';
};
as[index].style.zIndex=10;
bodiandiv[index].style.background='#e5004f';
}
box[0].onmouseover=function(){
clearInterval(t);
lrclickbox.style... | th) | identifier_name | |
yintai.js | };
// 时尚名品无缝轮播模式图模式
var box=$('.shishang7');
for(var i=0;i<box.length;i++){
fengzhuang(box[i])
}
function fengzhuang(box){
var n=0;
var next=0;
var boximg=$('.imgbox',box)[0]
var img=$("a",box);
img[0].style.left='0';
var anniu=$('.sh7a',box);
anniu[0].style.back... | 页脚的三个标志
var yj=$(".yj")[0];
var yjimg=$("a",yj);
for (var i = 0; i < yjimg.length; i++) {
yejiao(yjimg[i])
};
function yejiao(aa){
hover( | identifier_body | |
yintai.js | as[j].style.zIndex=0;
}
as[this.index].style.zIndex=10;
bodiandiv[this.index].style.background='#e5004f';
| 0].onmouseover=function(){
rightclick[0].style.background='#cc477a';
}
rightclick[0].onmouseout=function(){
rightclick[0].style.background='';
}
leftclick[0].onmouseover=function(){
leftclick[0].style.background='#cc477a';
}
leftclick[0].onmouseout=function(){
leftclick[0].style.background='';
... | }
};
rightclick[0].onclick=function(){
move();
};
rightclick[ | conditional_block |
manager.py | :`~budget.Note` :class:`~pandas.Series` using a connection to a SQL database using
Parameters
----------
con : SQLAlchemy connectable, :class:`str`, or :mod:`sqlite3` connection
SQL connection
Returns
-------
:class:`~pandas.Series`
"""
# ... | (self, id: str, note: str, drop_dups: bool = True):
"""Parses a string into a :class:`~budget.Note` object and adds it to the :class:`~budget.notes.NoteManager` using
:class:`~pandas.Series.append` and optionally uses :class:`~pandas.Series.drop_duplicates`
Parameters
----------
... | add_note | identifier_name |
manager.py | :`~budget.Note` :class:`~pandas.Series` using a connection to a SQL database using
Parameters
----------
con : SQLAlchemy connectable, :class:`str`, or :mod:`sqlite3` connection
SQL connection
Returns
-------
:class:`~pandas.Series`
"""
# ... |
if isinstance(input, str):
for nt in note_types:
try:
if nt._tag in input:
res = nt(id, input)
break
except AttributeError:
raise AttributeError('Notes must have a _tag attribute... | try:
note_types.append(add_note_types)
except:
note_types.extend(add_note_types) | conditional_block |
manager.py | :`~budget.Note` :class:`~pandas.Series` using a connection to a SQL database using
Parameters
----------
con : SQLAlchemy connectable, :class:`str`, or :mod:`sqlite3` connection
SQL connection
Returns
-------
:class:`~pandas.Series`
"""
# ... | def validate_notes(self, ids: pd.Series) -> bool:
"""Checks to make sure that all of the :class:`~budget.Note`s are contained in the ids
Parameters
----------
ids : set or like-like
:class:`list` or something that can be used in :meth:`~pandas.Series.isin`
Retur... | raise TypeError(f'unknown type of note: {type(input)}')
| random_line_split |
manager.py | Parameters
----------
con : SQLAlchemy connectable, :class:`str`, or :mod:`sqlite3` connection
SQL connection
Returns
-------
:class:`~pandas.Series`
"""
# Read the whole table of notes
notes = pd.read_sql_query(sql=f'select * from {s... | """Class to handle higher-level :class:`~budget.Note` manipulation
Attributes
----------
notes : :class:`~pandas.DataFrame`
:class:`~pandas.DataFrame` of the :class:`~budget.Note` objects. `Index` is the :class:`str` ID of the
transaction that each :class:`~budget.Note` is linked to
""... | identifier_body | |
payment.component.ts | EventEmitter, NgZone } from '@angular/core';
import { Http, Response, RequestOptions, Headers } from '@angular/http';
import { Router, ActivatedRoute } from '@angular/router';
import { AppService } from '../app-service.service';
import { AlertService } from '../alert.service';
import { LoaderService } from '../loader.... | },
handler: (response) => {
vm.ngZone.run(() => {
data.PAYMENT_ID = response.razorpay_payment_id;
data.PAYMENT_SOURCE = 'RAZOR_PAY';
data.PLAN_START_DATE = vm.billingAmount.planStartDate;
... | },
theme: {
color: '#3D78E0' | random_line_split |
payment.component.ts | , NgZone } from '@angular/core';
import { Http, Response, RequestOptions, Headers } from '@angular/http';
import { Router, ActivatedRoute } from '@angular/router';
import { AppService } from '../app-service.service';
import { AlertService } from '../alert.service';
import { LoaderService } from '../loader.service';
imp... | implements OnInit {
// @Input() tab: string;
// @Input() user;
@Output() renewalDateUpdated: EventEmitter<any> = new EventEmitter();
@Output() planTypeUpdated: EventEmitter<any> = new EventEmitter();
httpOptions: RequestOptions;
session: any;
billingAmount: any;
invoices: any;
envi... | PaymentComponent | identifier_name |
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