file_name large_stringlengths 4 140 | prefix large_stringlengths 0 39k | suffix large_stringlengths 0 36.1k | middle large_stringlengths 0 29.4k | fim_type large_stringclasses 4
values |
|---|---|---|---|---|
ledger_cleanup_service.rs | //! The `ledger_cleanup_service` drops older ledger data to limit disk space usage
use solana_ledger::blockstore::Blockstore;
use solana_ledger::blockstore_db::Result as BlockstoreResult;
use solana_measure::measure::Measure;
use solana_metrics::datapoint_debug;
use solana_sdk::clock::Slot;
use std::string::ToString;
... |
//send a signal to kill all but 5 shreds, which will be in the newest slots
let mut last_purge_slot = 0;
sender.send(50).unwrap();
LedgerCleanupService::cleanup_ledger(&receiver, &blockstore, 5, &mut last_purge_slot, 10)
.unwrap();
//check that 0-40 don't exist
... | let blockstore = Arc::new(blockstore);
let (sender, receiver) = channel(); | random_line_split |
space_group.py | # Copyright 2021 The NetKet Authors - All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... |
return PermutationGroup(perms, degree=self.lattice.n_nodes)
@struct.property_cached
def rotation_group(self) -> PermutationGroup:
"""The group of rotations (i.e. point group symmetries with determinant +1)
as a `PermutationGroup` acting on the sites of `self.lattice`."""
perms ... | perm = self.lattice.id_from_position(p.preimage(self.lattice.positions))
perms.append(Permutation(perm, name=str(p))) | conditional_block |
space_group.py | # Copyright 2021 The NetKet Authors - All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... |
def translation_group(
self, axes: Optional[Union[int, Sequence[int]]] = None
) -> PermutationGroup:
"""
The group of valid translations of `self.lattice` as a `PermutationGroup`
acting on the sites of the same.
"""
if axes is None:
return self._full... | """
The group of valid translations of `self.lattice` as a `PermutationGroup`
acting on the sites of the same.
"""
return reduce(
PermutationGroup.__matmul__,
[self._translations_along_axis(i) for i in range(self.lattice.ndim)],
) | identifier_body |
space_group.py | # Copyright 2021 The NetKet Authors - All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... | (self, permutation: Array, displacement: Array):
r"""
Creates a `Translation` from a permutation array and a displacement vector
Arguments:
permutation: a 1D array listing :math:`g^{-1}(x)` for all
:math:`0\le x < N` (i.e., `V[permutation]` permutes the
... | __init__ | identifier_name |
space_group.py | # Copyright 2021 The NetKet Authors - All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... | if isinstance(p, Identity):
perms.append(Identity())
else:
# note that we need the preimages in the permutation
perm = self.lattice.id_from_position(p.preimage(self.lattice.positions))
perms.append(Permutation(perm, name=str(p)))
... | """
perms = []
for p in self.point_group_: | random_line_split |
basic_model.py | from collections import defaultdict
# from torchtext.vocab import Vocab
from torch.utils.data.dataset import Dataset, TensorDataset
from pathlib import Path
from collections import Counter
import pandas as pd
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as opt... | # taken from the paper
MLP_HIDDEN_DIM = 100
EPOCHS = 150
WORD_EMBEDDING_DIM = 100
POS_EMBEDDING_DIM = 25
HIDDEN_DIM = 125
LEARNING_RATE = 0.01
EARLY_STOPPING = 10 # num epochs with no validation acc improvement to stop training
PATH = "./basic_model_best_params"
cross_entropy_loss = nn.CrossEntropyLoss(reduction='me... | import matplotlib.pyplot as plt
from chu_liu_edmonds import *
from os import path
| random_line_split |
basic_model.py | from collections import defaultdict
# from torchtext.vocab import Vocab
from torch.utils.data.dataset import Dataset, TensorDataset
from pathlib import Path
from collections import Counter
import pandas as pd
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as opt... | (self, lstm_dim, mlp_hidden_dim):
super(MLP, self).__init__()
self.first_mlp = SplittedMLP(lstm_dim, mlp_hidden_dim)
self.non_linearity = nn.Tanh()
self.second_mlp = nn.Linear(mlp_hidden_dim, 1, bias=True) # will output a score of a pair
def forward(self, lstm_out):
senten... | __init__ | identifier_name |
basic_model.py | from collections import defaultdict
# from torchtext.vocab import Vocab
from torch.utils.data.dataset import Dataset, TensorDataset
from pathlib import Path
from collections import Counter
import pandas as pd
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as opt... |
else:
main() | hyper_parameter_tuning() | conditional_block |
basic_model.py | from collections import defaultdict
# from torchtext.vocab import Vocab
from torch.utils.data.dataset import Dataset, TensorDataset
from pathlib import Path
from collections import Counter
import pandas as pd
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as opt... |
class MLP(nn.Module):
def __init__(self, lstm_dim, mlp_hidden_dim):
super(MLP, self).__init__()
self.first_mlp = SplittedMLP(lstm_dim, mlp_hidden_dim)
self.non_linearity = nn.Tanh()
self.second_mlp = nn.Linear(mlp_hidden_dim, 1, bias=True) # will output a score of a pair
de... | heads_hidden = self.fc_h(lstm_out)
mods_hidden = self.fc_m(lstm_out)
return heads_hidden, mods_hidden | identifier_body |
main.go | package main
import (
"encoding/json"
"fmt"
"math"
"math/rand"
"net/http"
"os"
"sort"
"strings"
"time"
m3o "github.com/micro/services/clients/go"
db "github.com/micro/services/clients/go/db"
user "github.com/micro/services/clients/go/user"
uuid "github.com/satori/go.uuid"
)
var client = m3o.NewClient(os... |
func main() {
http.HandleFunc("/upvotePost", voteWrapper(true, false))
http.HandleFunc("/downvotePost", voteWrapper(false, false))
http.HandleFunc("/upvoteComment", voteWrapper(true, true))
http.HandleFunc("/downvoteComment", voteWrapper(false, true))
http.HandleFunc("/posts", posts)
http.HandleFunc("/post", po... | {
if err != nil {
w.WriteHeader(500)
fmt.Println(err)
}
if i == nil {
i = map[string]interface{}{}
}
if err != nil {
i = map[string]interface{}{
"error": err.Error(),
}
}
bs, _ := json.Marshal(i)
fmt.Fprintf(w, fmt.Sprintf("%v", string(bs)))
} | identifier_body |
main.go | package main
import (
"encoding/json"
"fmt"
"math"
"math/rand"
"net/http"
"os"
"sort"
"strings"
"time"
m3o "github.com/micro/services/clients/go"
db "github.com/micro/services/clients/go/db"
user "github.com/micro/services/clients/go/user"
uuid "github.com/satori/go.uuid"
)
var client = m3o.NewClient(os... |
func post(w http.ResponseWriter, req *http.Request) {
if cors(w, req) {
return
}
decoder := json.NewDecoder(req.Body)
var t PostRequest
err := decoder.Decode(&t)
if err != nil {
respond(w, nil, err)
return
}
if t.Post.Sub == "" || t.Post.Title == "" {
respond(w, nil, fmt.Errorf("both title and sub are... | }, err)
} | random_line_split |
main.go | package main
import (
"encoding/json"
"fmt"
"math"
"math/rand"
"net/http"
"os"
"sort"
"strings"
"time"
m3o "github.com/micro/services/clients/go"
db "github.com/micro/services/clients/go/db"
user "github.com/micro/services/clients/go/user"
uuid "github.com/satori/go.uuid"
)
var client = m3o.NewClient(os... |
order := math.Log10(math.Max(math.Abs(score), 1))
var created int64
switch v := m["created"].(type) {
case string:
t, err := time.Parse(time.RFC3339, v)
if err != nil {
fmt.Println(err)
}
created = t.Unix()
case float64:
created = int64(v)
case int64:
created = v
}
seconds := created - 11340280... | {
sign = -1
} | conditional_block |
main.go | package main
import (
"encoding/json"
"fmt"
"math"
"math/rand"
"net/http"
"os"
"sort"
"strings"
"time"
m3o "github.com/micro/services/clients/go"
db "github.com/micro/services/clients/go/db"
user "github.com/micro/services/clients/go/user"
uuid "github.com/satori/go.uuid"
)
var client = m3o.NewClient(os... | (w http.ResponseWriter, i interface{}, err error) {
if err != nil {
w.WriteHeader(500)
fmt.Println(err)
}
if i == nil {
i = map[string]interface{}{}
}
if err != nil {
i = map[string]interface{}{
"error": err.Error(),
}
}
bs, _ := json.Marshal(i)
fmt.Fprintf(w, fmt.Sprintf("%v", string(bs)))
}
func... | respond | identifier_name |
tcp.rs | // "Tifflin" Kernel - Networking Stack
// - By John Hodge (thePowersGang)
//
// Modules/network/tcp.rs
//! Transmission Control Protocol (Layer 4)
use shared_map::SharedMap;
use kernel::sync::Mutex;
use kernel::lib::ring_buffer::{RingBuf,AtomicRingBuf};
use core::sync::atomic::{AtomicUsize, Ordering};
use crate::nic::S... | ConnectionState::Finished => return,
};
self.state_update(quad, new_state);
}
fn state_update(&mut self, quad: &Quad, new_state: ConnectionState)
{
if self.state != new_state
{
log_trace!("{:?} {:?} -> {:?}", quad, self.state, new_state);
self.state = new_state;
// TODO: If transitioning to `Fi... | ConnectionState::TimeWait => self.state,
| random_line_split |
tcp.rs | // "Tifflin" Kernel - Networking Stack
// - By John Hodge (thePowersGang)
//
// Modules/network/tcp.rs
//! Transmission Control Protocol (Layer 4)
use shared_map::SharedMap;
use kernel::sync::Mutex;
use kernel::lib::ring_buffer::{RingBuf,AtomicRingBuf};
use core::sync::atomic::{AtomicUsize, Ordering};
use crate::nic::S... |
else if hdr.flags & FLAG_FIN != 0 {
// FIN received, start a clean shutdown
self.next_rx_seq += 1;
// TODO: Signal to user that the connection is closing (EOF)
ConnectionState::CloseWait
}
else {
if pkt.remain() == 0 {
// Pure ACK, no change
if hdr.flags == FLAG_ACK {
log_t... | {
// RST received, do an unclean close (reset by peer)
// TODO: Signal to user that the connection is closing (error)
ConnectionState::ForceClose
} | conditional_block |
tcp.rs | // "Tifflin" Kernel - Networking Stack
// - By John Hodge (thePowersGang)
//
// Modules/network/tcp.rs
//! Transmission Control Protocol (Layer 4)
use shared_map::SharedMap;
use kernel::sync::Mutex;
use kernel::lib::ring_buffer::{RingBuf,AtomicRingBuf};
use core::sync::atomic::{AtomicUsize, Ordering};
use crate::nic::S... | (local_addr: Address, local_port: u16, remote_addr: Address, remote_port: u16) -> Quad
{
Quad {
local_addr, local_port, remote_addr, remote_port
}
}
fn send_packet(&self, seq: u32, ack: u32, flags: u8, window_size: u16, data: &[u8])
{
// Make a header
// TODO: Any options required?
let options_bytes =... | new | identifier_name |
tcp.rs | // "Tifflin" Kernel - Networking Stack
// - By John Hodge (thePowersGang)
//
// Modules/network/tcp.rs
//! Transmission Control Protocol (Layer 4)
use shared_map::SharedMap;
use kernel::sync::Mutex;
use kernel::lib::ring_buffer::{RingBuf,AtomicRingBuf};
use core::sync::atomic::{AtomicUsize, Ordering};
use crate::nic::S... |
fn send_packet(&self, seq: u32, ack: u32, flags: u8, window_size: u16, data: &[u8])
{
// Make a header
// TODO: Any options required?
let options_bytes = &[];
let opts_len_rounded = ((options_bytes.len() + 3) / 4) * 4;
let hdr = PktHeader {
source_port: self.local_port,
dest_port: self.remote_port,
... | {
Quad {
local_addr, local_port, remote_addr, remote_port
}
} | identifier_body |
kegweblib.py | from builtins import str
import pytz
from django.conf import settings
from django.template import (
Library,
Node,
TemplateSyntaxError,
Variable,
VariableDoesNotExist,
)
from django.template.defaultfilters import pluralize
from django.urls import reverse
from django.utils import timezone
from djang... | (parser, token):
"""{% timeago <timestamp> %}"""
tokens = token.contents.split()
if len(tokens) != 2:
raise TemplateSyntaxError("%s requires 2 tokens" % tokens[0])
return TimeagoNode(tokens[1])
class TimeagoNode(Node):
def __init__(self, timestamp_varname):
self._timestamp_varname ... | timeago | identifier_name |
kegweblib.py | from builtins import str
import pytz
from django.conf import settings
from django.template import (
Library,
Node,
TemplateSyntaxError,
Variable,
VariableDoesNotExist,
)
from django.template.defaultfilters import pluralize
from django.urls import reverse
from django.utils import timezone
from djang... |
@classmethod
def format(cls, amount, units, make_badge=False):
if amount < 0:
amount = 0
ctx = {
"units": units,
"amount": amount,
"title": "%s %s" % (amount, units),
"extra_css": "badge " if make_badge else "",
}
retu... | tv = Variable(self._volume_varname)
try:
num = float(tv.resolve(context))
except (VariableDoesNotExist, ValueError):
num = "unknown"
unit = "mL"
make_badge = "badge" in self._extra_args
return self.format(num, unit, make_badge) | identifier_body |
kegweblib.py | from builtins import str
import pytz
from django.conf import settings
from django.template import (
Library,
Node,
TemplateSyntaxError,
Variable,
VariableDoesNotExist,
)
from django.template.defaultfilters import pluralize
from django.urls import reverse
from django.utils import timezone
from djang... |
return context["guest_info"]["name"]
# chart
@register.tag("chart")
def chart(parser, tokens):
"""{% chart <charttype> <obj> width height %}"""
tokens = tokens.contents.split()
if len(tokens) < 4:
raise TemplateSyntaxError("chart requires at least 4 arguments")
charttype = tokens[1]... | return '<a href="%s">%s</a>' % (
reverse("kb-drinker", args=[user.username]),
user.get_full_name(),
) | conditional_block |
kegweblib.py | from builtins import str
import pytz
from django.conf import settings
from django.template import (
Library,
Node,
TemplateSyntaxError,
Variable,
VariableDoesNotExist,
)
from django.template.defaultfilters import pluralize
from django.urls import reverse
from django.utils import timezone
from djang... | c = {}
if not hasattr(picture_or_pictures, "__iter__"):
c["gallery_pictures"] = [picture_or_pictures]
else:
c["gallery_pictures"] = picture_or_pictures
c["thumb_size"] = thumb_size
c["gallery_id"] = gallery_id
return c
@register.inclusion_tag("kegweb/badge.html")
def badge(amou... | @register.inclusion_tag("kegweb/picture-gallery.html")
def gallery(picture_or_pictures, thumb_size="span2", gallery_id=""): | random_line_split |
ddpg-per.py | import tensorflow as tf
import numpy as np
import gym
import os
##################### hyper parameters ####################
# Hyper Parameters
ENV_NAME = 'Pendulum-v0'
EPISODE = 200
STEP = 200
TEST = 5
LR_A = 0.001 # learning rate for actor
LR_C = 0.002 # learning rate for critic
MEMORY_SIZE = 10000
steps = []
ep... | date_target_q_network(self, episode):
# update target Q netowrk by soft_replace
if episode % REPLACE_TARGET_FREQ == 0:
self.sess.run(self.soft_replace)
# print('episode '+str(episode) +', target Q network params replaced!')
def load_network(self, saver, load_path):
c... | able_scope(scope):
n_l1 = 30
w1_s = tf.get_variable('w1_s', [self.s_dim, n_l1], trainable=trainable)
w1_a = tf.get_variable('w1_a', [self.a_dim, n_l1], trainable=trainable)
b1 = tf.get_variable('b1', [1, n_l1], trainable=trainable)
net = tf.nn.relu(tf.matmul(s... | identifier_body |
ddpg-per.py | import tensorflow as tf
import numpy as np
import gym
import os
##################### hyper parameters ####################
# Hyper Parameters
ENV_NAME = 'Pendulum-v0'
EPISODE = 200
STEP = 200
TEST = 5
LR_A = 0.001 # learning rate for actor
LR_C = 0.002 # learning rate for critic
MEMORY_SIZE = 10000
steps = []
ep... | r, s_):
transition = np.hstack((s, a, r, s_))
self.memory.store(transition)
self.pointer += 1
def _build_a(self, s, scope, trainable):
with tf.variable_scope(scope):
net = tf.layers.dense(s, 30, activation=tf.nn.relu, name='l1', trainable=trainable)
# new_ac... | tion(self, s, a, | identifier_name |
ddpg-per.py | import tensorflow as tf
import numpy as np
import gym
import os
##################### hyper parameters ####################
# Hyper Parameters
ENV_NAME = 'Pendulum-v0'
EPISODE = 200
STEP = 200
TEST = 5
LR_A = 0.001 # learning rate for actor
LR_C = 0.002 # learning rate for critic
MEMORY_SIZE = 10000
steps = []
ep... | for episode in range(EPISODE):
state = env.reset()
ep_reward = 0
# train
for step in range(STEP):
if RENDER:
env.render()
action = agent.choose_action(state, with_noise)
action = np.clip(np.random.normal(action, var), -2, 2)
... |
agent = DDPG(a_dim, s_dim, a_bound)
total_steps = 0
var = 3 | random_line_split |
ddpg-per.py | import tensorflow as tf
import numpy as np
import gym
import os
##################### hyper parameters ####################
# Hyper Parameters
ENV_NAME = 'Pendulum-v0'
EPISODE = 200
STEP = 200
TEST = 5
LR_A = 0.001 # learning rate for actor
LR_C = 0.002 # learning rate for critic
MEMORY_SIZE = 10000
steps = []
ep... | lf.learn_step += 1
def store_transition(self, s, a, r, s_):
transition = np.hstack((s, a, r, s_))
self.memory.store(transition)
self.pointer += 1
def _build_a(self, s, scope, trainable):
with tf.variable_scope(scope):
net = tf.layers.dense(s, 30, activation=tf.nn.re... | tch_memory, ISWeights = self.memory.sample(self.per_batch_size) # sample for learning
batch_states = batch_memory[:,0:3]
batch_actions = batch_memory[:,3:4]
batch_rewards = [data[4] for data in batch_memory]
batch_states_ = batch_memory[:,5:8]
bs = np.array(b... | conditional_block |
bot.js | (function () {
"use strict";
const fs = require("fs");
const request = require("request");
require("/code/keys/load-keys.js")();
const Utils = require("/code/global-modules/utils.js");
let CytubeConstructor = require("./my-modules/cytube.js")(Utils);
const DiscordConstructor = require("./my-modules/discord.js"... | + (client.BAN_EVASION_FLAGS[chan] ? client.CFG.BAN_EVASION_CHARACTER : "");
if (Utils.globalCheck(msg, client.CFG.GLOBAL_BANPHRASES)) {
for (const phrase of client.CFG.GLOBAL_BANPHRASES) {
msg = msg.replace(new RegExp(phrase, "gi"), "[REDACTED]");
}
}
this._reply("send", Utils.saf... | random_line_split | |
bot.js | (function () {
"use strict";
const fs = require("fs");
const request = require("request");
require("/code/keys/load-keys.js")();
const Utils = require("/code/global-modules/utils.js");
let CytubeConstructor = require("./my-modules/cytube.js")(Utils);
const DiscordConstructor = require("./my-modules/discord.js"... | if (command.blacklist && command.blacklist.some(i => i === chan)) {
evt.reply("This command cannot be executed in this channel.");
console.log("CMD REQUEST FAILED - CHANNEL BLACKLISTED");
}
else if (command.whitelist && !command.whitelist.some(i => i === chan)) {
evt.reply("This command cannot be executed... | t.reply(":z message too long.");
console.log("CMD REQUEST FAILED - MESSAGE TOO LONG", args.join(" ").length);
}
else | conditional_block |
jpt_location.py | import dataclasses
import time
from typing import Optional, List, Tuple
import jpt
import numpy as np
import pybullet
import tf
import pycram.designators.location_designator
import pycram.task
from pycram.costmaps import OccupancyCostmap, plot_grid
from pycram.plan_failures import PlanFailure
class JPTCostmapLocati... | (self, sample: np.ndarray) -> Location:
"""
Convert a numpy array sampled from the JPT to a costmap-location
:param sample: The drawn sample
:return: The usable costmap-location
"""
sample_dict = {variable.name: value for variable, value in zip(self.model.variables, samp... | sample_to_location | identifier_name |
jpt_location.py | import dataclasses
import time
from typing import Optional, List, Tuple
import jpt
import numpy as np
import pybullet
import tf
import pycram.designators.location_designator
import pycram.task
from pycram.costmaps import OccupancyCostmap, plot_grid
from pycram.plan_failures import PlanFailure
class JPTCostmapLocati... |
# load model from path
if path:
self.model = jpt.trees.JPT.load(path)
# initialize member for visualized objects
self.visual_ids: List[int] = []
def evidence_from_occupancy_costmap(self) -> List[jpt.variables.LabelAssignment]:
"""
Create a list of boxe... | self.model = model | conditional_block |
jpt_location.py | import dataclasses
import time
from typing import Optional, List, Tuple
import jpt
import numpy as np
import pybullet
import tf
import pycram.designators.location_designator
import pycram.task
from pycram.costmaps import OccupancyCostmap, plot_grid
from pycram.plan_failures import PlanFailure
class JPTCostmapLocati... |
def sample(self, amount: int = 1) -> np.ndarray:
"""
Sample from the locations that fit the CostMap and are not occupied.
:param amount: The amount of samples to draw
:return: A numpy array containing the samples drawn from the tree.
"""
evidence = self.create_evid... | """
Create evidence usable for JPTs where type and status are set if wanted.
:param use_success: Rather to set success or not
:return: The usable label-assignment
"""
evidence = dict()
evidence["type"] = {self.target.type}
if use_success:
evidence["... | identifier_body |
jpt_location.py | import dataclasses
import time
from typing import Optional, List, Tuple
import jpt | import pycram.designators.location_designator
import pycram.task
from pycram.costmaps import OccupancyCostmap, plot_grid
from pycram.plan_failures import PlanFailure
class JPTCostmapLocation(pycram.designators.location_designator.CostmapLocation):
"""Costmap Locations using Joint Probability Trees (JPTs).
JPT... | import numpy as np
import pybullet
import tf
| random_line_split |
main.go | package core
import (
"context"
"crypto/tls"
"fmt"
genesisUploader "github.com/MinterTeam/explorer-genesis-uploader/core"
genesisEnv "github.com/MinterTeam/explorer-genesis-uploader/env"
"github.com/MinterTeam/minter-explorer-api/v2/coins"
"github.com/MinterTeam/minter-explorer-extender/v2/address"
"github.com... |
func (ext *Extender) saveTransactions(blockHeight uint64, blockCreatedAt time.Time, transactions []*api_pb.TransactionResponse) {
// Save transactions
err := ext.transactionService.HandleTransactionsFromBlockResponse(blockHeight, blockCreatedAt, transactions)
if err != nil {
ext.log.Panic(err)
}
}
func (ext *E... | {
if response.Height == 1 {
return
}
var links []*models.BlockValidator
for _, v := range response.Validators {
vId, err := ext.validatorRepository.FindIdByPk(helpers.RemovePrefix(v.PublicKey))
if err != nil {
ext.log.Error(err)
}
helpers.HandleError(err)
link := models.BlockValidator{
ValidatorID... | identifier_body |
main.go | package core
import (
"context"
"crypto/tls"
"fmt"
genesisUploader "github.com/MinterTeam/explorer-genesis-uploader/core"
genesisEnv "github.com/MinterTeam/explorer-genesis-uploader/env"
"github.com/MinterTeam/minter-explorer-api/v2/coins"
"github.com/MinterTeam/minter-explorer-extender/v2/address"
"github.com... | if result > critical {
bigQueryLog, err := os.OpenFile("big_query.log", os.O_APPEND|os.O_CREATE|os.O_RDWR, 0666)
if err != nil {
eh.log.Error("error opening file: %v", err)
}
// don't forget to close it
defer bigQueryLog.Close()
eh.log.SetReportCaller(false)
eh.log.SetFormatter(&logrus.JSONFormatter{}... | random_line_split | |
main.go | package core
import (
"context"
"crypto/tls"
"fmt"
genesisUploader "github.com/MinterTeam/explorer-genesis-uploader/core"
genesisEnv "github.com/MinterTeam/explorer-genesis-uploader/env"
"github.com/MinterTeam/minter-explorer-api/v2/coins"
"github.com/MinterTeam/minter-explorer-extender/v2/address"
"github.com... | (response *api_pb.BlockResponse) {
// Save validators if not exist
err := ext.validatorService.HandleBlockResponse(response)
if err != nil {
ext.log.Panic(err)
}
// Save block
err = ext.blockService.HandleBlockResponse(response)
if err != nil {
ext.log.Panic(err)
}
ext.linkBlockValidator(response)
//fi... | handleBlockResponse | identifier_name |
main.go | package core
import (
"context"
"crypto/tls"
"fmt"
genesisUploader "github.com/MinterTeam/explorer-genesis-uploader/core"
genesisEnv "github.com/MinterTeam/explorer-genesis-uploader/env"
"github.com/MinterTeam/minter-explorer-api/v2/coins"
"github.com/MinterTeam/minter-explorer-extender/v2/address"
"github.com... |
}
func (ext *Extender) handleEventResponse(blockHeight uint64, response *api_pb.BlockResponse) {
if len(response.Events) > 0 {
//Save events
err := ext.eventService.HandleEventResponse(blockHeight, response)
if err != nil {
ext.log.Fatal(err)
}
}
}
func (ext *Extender) linkBlockValidator(response *api_p... | {
start := ext.env.TxChunkSize * i
end := start + ext.env.TxChunkSize
if end > len(response.Transactions) {
end = len(response.Transactions)
}
layout := "2006-01-02T15:04:05Z"
blockTime, err := time.Parse(layout, response.Time)
if err != nil {
ext.log.Panic(err)
}
ext.saveTransactions(response... | conditional_block |
utils.py | import numbers
import torch
import torch.nn as nn
import torchvision
import torchvision.transforms as transforms
from numpy import asarray
import numpy as np
from numpy.lib.stride_tricks import as_strided
from skimage import feature
from skimage.filters import threshold_otsu
from sklearn.utils import check_random_stat... |
else:
s_h, s_w = stride
step = (s_h, s_w, n_colors)
extracted_patches = _extract_patches(image,
patch_shape=(p_h, p_w, n_colors),
extraction_step=step)
n_patches = _compute_n_patches(i_h, i_w, p_h, p_w, stri... | step = stride
s_h = stride
s_w = stride | conditional_block |
utils.py | import numbers
import torch
import torch.nn as nn
import torchvision
import torchvision.transforms as transforms
from numpy import asarray
import numpy as np
from numpy.lib.stride_tricks import as_strided
from skimage import feature
from skimage.filters import threshold_otsu
from sklearn.utils import check_random_stat... |
def clean_patches(patches, th=2000):
indices = []
for i, patch in enumerate(patches):
if patch.shape[-1] == 3:
patch = patch / 255
num_features = feature.canny(patch.mean(axis=2), sigma=2).sum()
else:
num_features = feature.canny(patch, sigma=2).sum()
... | if isinstance(stride, numbers.Number):
s_h = stride
s_w = stride
else:
s_h, s_w = stride
n_h = (i_h - p_h) // s_h + 1
n_w = (i_w - p_w) // s_w + 1
all_patches = n_h * n_w
if max_patches:
if (isinstance(max_patches, numbers.Integral)
and max_patches <... | identifier_body |
utils.py | import numbers
import torch
import torch.nn as nn
import torchvision
import torchvision.transforms as transforms
from numpy import asarray
import numpy as np
from numpy.lib.stride_tricks import as_strided
from skimage import feature
from skimage.filters import threshold_otsu
from sklearn.utils import check_random_stat... | patches = extracted_patches
patches = patches.reshape(-1, p_h, p_w, n_colors)
# remove the color dimension if useless
if patches.shape[-1] == 1:
patches = patches.reshape((n_patches, p_h, p_w))
# return clean_patches(patches, th)
return patches
def _compute_n_patches(i_h, i_w, p_... | random_line_split | |
utils.py | import numbers
import torch
import torch.nn as nn
import torchvision
import torchvision.transforms as transforms
from numpy import asarray
import numpy as np
from numpy.lib.stride_tricks import as_strided
from skimage import feature
from skimage.filters import threshold_otsu
from sklearn.utils import check_random_stat... | (Dataset):
def __init__(self, dataset, col_transform=None, bin_transform=None):
self.dataset = dataset
self.col_transform = col_transform
self.bin_transform = bin_transform
def __getitem__(self, index):
x1, y1 = self.dataset[index]
if self.bin_transform:
x2 ... | BinColorDataset | identifier_name |
reaper-rush.rs | #[macro_use]
extern crate clap;
use rand::prelude::*;
use rust_sc2::prelude::*;
use std::{cmp::Ordering, collections::HashSet};
#[bot]
#[derive(Default)]
struct ReaperRushAI {
reapers_retreat: HashSet<u64>,
last_loop_distributed: u32,
}
impl Player for ReaperRushAI {
fn on_start(&mut self) -> SC2Result<()> {
if... | }
}
if self.counter().all().count(UnitTypeId::Barracks) < 4
&& self.can_afford(UnitTypeId::Barracks, false)
{
if let Some(location) = self.find_placement(
UnitTypeId::Barracks,
main_base,
PlacementOptions {
step: 4,
..Default::default()
},
) {
if let Some(builder) = self... | builder.build(UnitTypeId::SupplyDepot, location, false);
self.subtract_resources(UnitTypeId::SupplyDepot, false);
return;
} | random_line_split |
reaper-rush.rs | #[macro_use]
extern crate clap;
use rand::prelude::*;
use rust_sc2::prelude::*;
use std::{cmp::Ordering, collections::HashSet};
#[bot]
#[derive(Default)]
struct ReaperRushAI {
reapers_retreat: HashSet<u64>,
last_loop_distributed: u32,
}
impl Player for ReaperRushAI {
fn on_start(&mut self) -> SC2Result<()> {
if... | (&mut self) {
if self.minerals < 50 || self.supply_left == 0 {
return;
}
if self.supply_workers < 22 && self.can_afford(UnitTypeId::SCV, true) {
if let Some(cc) = self
.units
.my
.townhalls
.iter()
.find(|u| u.is_ready() && u.is_almost_idle())
{
cc.train(UnitTypeId::SCV, false);
... | train | identifier_name |
reaper-rush.rs | #[macro_use]
extern crate clap;
use rand::prelude::*;
use rust_sc2::prelude::*;
use std::{cmp::Ordering, collections::HashSet};
#[bot]
#[derive(Default)]
struct ReaperRushAI {
reapers_retreat: HashSet<u64>,
last_loop_distributed: u32,
}
impl Player for ReaperRushAI {
fn on_start(&mut self) -> SC2Result<()> {
if... | else {
None
};
for u in &idle_workers {
if let Some(closest) = deficit_geysers.closest(u) {
let tag = closest.tag();
deficit_geysers.remove(tag);
u.gather(tag, false);
} else if let Some(closest) = deficit_minings.closest(u) {
u.gather(
mineral_fields
.closer(11.0, closest)
... | {
let minerals = mineral_fields.filter(|m| bases.iter().any(|base| base.is_closer(11.0, *m)));
if minerals.is_empty() {
None
} else {
Some(minerals)
}
} | conditional_block |
reaper-rush.rs | #[macro_use]
extern crate clap;
use rand::prelude::*;
use rust_sc2::prelude::*;
use std::{cmp::Ordering, collections::HashSet};
#[bot]
#[derive(Default)]
struct ReaperRushAI {
reapers_retreat: HashSet<u64>,
last_loop_distributed: u32,
}
impl Player for ReaperRushAI {
fn on_start(&mut self) -> SC2Result<()> {
if... |
fn throw_mine(&self, reaper: &Unit, target: &Unit) -> bool {
if reaper.has_ability(AbilityId::KD8ChargeKD8Charge)
&& reaper.in_ability_cast_range(AbilityId::KD8ChargeKD8Charge, target, 0.0)
{
reaper.command(
AbilityId::KD8ChargeKD8Charge,
Target::Pos(target.position()),
false,
);
true
}... | {
if self.minerals < 50 || self.supply_left == 0 {
return;
}
if self.supply_workers < 22 && self.can_afford(UnitTypeId::SCV, true) {
if let Some(cc) = self
.units
.my
.townhalls
.iter()
.find(|u| u.is_ready() && u.is_almost_idle())
{
cc.train(UnitTypeId::SCV, false);
self.sub... | identifier_body |
p_test.go | package p
import (
"strings"
"testing"
"github.com/lSimul/php2go/lang"
"github.com/lSimul/php2go/p/test"
"github.com/z7zmey/php-parser/node"
"github.com/z7zmey/php-parser/node/expr"
"github.com/z7zmey/php-parser/node/name"
"github.com/z7zmey/php-parser/node/stmt"
"github.com/z7zmey/php-parser/php7"
)
func ... | tests := []struct {
source []byte
expected string
}{
// Sandbox
{
source: []byte(`<?php
function fc() {
$a = 1 + 2;
}
`),
expected: `func fc() {
a := 1 + 2
}`,
},
// examples/04.php
{
source: []byte(`<?php
function fc() {
$a = 2 + 3 + 4 * 2;
echo $a * $a;
}
... | tt.Helper()
| random_line_split |
p_test.go | package p
import (
"strings"
"testing"
"github.com/lSimul/php2go/lang"
"github.com/lSimul/php2go/p/test"
"github.com/z7zmey/php-parser/node"
"github.com/z7zmey/php-parser/node/expr"
"github.com/z7zmey/php-parser/node/name"
"github.com/z7zmey/php-parser/node/stmt"
"github.com/z7zmey/php-parser/php7"
)
func ... |
}
func unaryOp(t *testing.T) {
t.Helper()
parent := lang.NewCode(nil)
parser := fileParser{parser: &parser{}}
for _, n := range []node.Node{
test.Plus(test.String(`"test"`)),
test.Plus(test.String(`""`)),
} {
e := parser.expression(parent, n)
if e.Parent() != parent {
t.Error("Parent not set.")
}
... | {
expr := parser.expression(nil, test.BinaryOp(left, c.op, right))
op, ok := expr.(*lang.BinaryOp)
if !ok {
t.Fatal("Expected binary operation, something else found.")
}
if op.Operation != c.op {
t.Errorf("'%s' expected, '%s' found.", c.op, op.Operation)
}
if !op.Type().Equal(c.ret) {
t.Errorf("'... | conditional_block |
p_test.go | package p
import (
"strings"
"testing"
"github.com/lSimul/php2go/lang"
"github.com/lSimul/php2go/p/test"
"github.com/z7zmey/php-parser/node"
"github.com/z7zmey/php-parser/node/expr"
"github.com/z7zmey/php-parser/node/name"
"github.com/z7zmey/php-parser/node/stmt"
"github.com/z7zmey/php-parser/php7"
)
func ... | (tt *testing.T) {
tt.Helper()
tests := []struct {
source []byte
expected string
}{
// Sandbox
{
source: []byte(`<?php
function fc() {
$a = 1 + 2;
}
`),
expected: `func fc() {
a := 1 + 2
}`,
},
// examples/04.php
{
source: []byte(`<?php
function fc() {
$a = 2 + 3 +... | testMain | identifier_name |
p_test.go | package p
import (
"strings"
"testing"
"github.com/lSimul/php2go/lang"
"github.com/lSimul/php2go/p/test"
"github.com/z7zmey/php-parser/node"
"github.com/z7zmey/php-parser/node/expr"
"github.com/z7zmey/php-parser/node/name"
"github.com/z7zmey/php-parser/node/stmt"
"github.com/z7zmey/php-parser/php7"
)
func ... | {
r := strings.Split(ref, "\n")
o := strings.Split(out, "\n")
i, j := 0, 0
for i < len(r) && j < len(o) {
c := true
s1 := strings.TrimLeft(r[i], "\t")
if s1 == "" {
i++
c = false
}
s2 := strings.TrimLeft(o[j], "\t")
if s2 == "" {
j++
c = false
}
if !c {
continue
}
if s1 != s2 {
... | identifier_body | |
repo_polling.go | package polling
import (
"database/sql"
"encoding/json"
"errors"
"fmt"
"math/rand"
"regexp"
"strings"
"sync"
"time"
"github.com/ovh/cds/engine/api/application"
"github.com/ovh/cds/engine/api/cache"
"github.com/ovh/cds/engine/api/database"
"github.com/ovh/cds/engine/api/pipeline"
"github.com/ovh/cds/engi... |
var quit chan bool
var atLeastOne bool
for i := range pollers {
p := &pollers[i]
b, _ := repositoriesmanager.CheckApplicationIsAttached(db, p.Name, w.ProjectKey, p.Application.Name)
if !b || p.Application.RepositoriesManager == nil || p.Application.RepositoryFullname == "" {
continue
}
if !p.Applicatio... | if err != nil {
return false, nil, err
} | random_line_split |
repo_polling.go | package polling
import (
"database/sql"
"encoding/json"
"errors"
"fmt"
"math/rand"
"regexp"
"strings"
"sync"
"time"
"github.com/ovh/cds/engine/api/application"
"github.com/ovh/cds/engine/api/cache"
"github.com/ovh/cds/engine/api/database"
"github.com/ovh/cds/engine/api/pipeline"
"github.com/ovh/cds/engi... |
}
//LoadExecutions returns all executions in database
func LoadExecutions(db database.QueryExecuter) ([]WorkerExecution, error) {
query := `
select poller_execution.id, application.name, pipeline.name, poller_execution.execution_date, poller_execution.status, poller_execution.data
from poller_execution, applicat... | {
db := database.DB()
if db == nil {
time.Sleep(30 * time.Minute)
continue
}
execs, _ := LoadExecutions(db)
for i := range execs {
tenDaysAGo := time.Now().Add(-10 * 24 * time.Hour)
if execs[i].Execution.Before(tenDaysAGo) {
deleteExecution(db, &execs[i])
}
}
time.Sleep(1 * time.Hour)... | conditional_block |
repo_polling.go | package polling
import (
"database/sql"
"encoding/json"
"errors"
"fmt"
"math/rand"
"regexp"
"strings"
"sync"
"time"
"github.com/ovh/cds/engine/api/application"
"github.com/ovh/cds/engine/api/cache"
"github.com/ovh/cds/engine/api/database"
"github.com/ovh/cds/engine/api/pipeline"
"github.com/ovh/cds/engi... |
func deleteExecution(db database.QueryExecuter, e *WorkerExecution) error {
query := `
delete from poller_execution where id = $1
`
if _, err := db.Exec(query, e.ID); err != nil {
return err
}
return nil
}
//ExecutionCleaner is globale goroutine to remove all old polling traces
func ExecutionCleaner() {
f... | {
query := `
update poller_execution set status = $2, data = $3 where id = $1
`
data, _ := json.Marshal(e.Events)
if _, err := db.Exec(query, e.ID, e.Status, data); err != nil {
return err
}
return nil
} | identifier_body |
repo_polling.go | package polling
import (
"database/sql"
"encoding/json"
"errors"
"fmt"
"math/rand"
"regexp"
"strings"
"sync"
"time"
"github.com/ovh/cds/engine/api/application"
"github.com/ovh/cds/engine/api/cache"
"github.com/ovh/cds/engine/api/database"
"github.com/ovh/cds/engine/api/pipeline"
"github.com/ovh/cds/engi... | (tx *sql.Tx, rm *sdk.RepositoriesManager, poller *sdk.RepositoryPoller, e sdk.VCSPushEvent, projectData *sdk.Project) (bool, error) {
client, err := repositoriesmanager.AuthorizedClient(tx, projectData.Key, rm.Name)
if err != nil {
return false, err
}
// Create pipeline args
var args []sdk.Parameter
args = appe... | TriggerPipeline | identifier_name |
keycap.js | import Vue from 'vue/dist/vue.js'
import KeyCustomizer from './components/KeyCustomizer.vue'
import KeySelector from './components/KeySelector.vue'
import NavBar from './components/NavBar.vue'
import KeycapProductInfo from './components/KeycapProductInfo'
Vue.config.productionTip = false
var customKey = new Vue({
e... |
var selectKey = function (e) {
var target = e.target;
if (target.className){
if (target.classList.contains('key-face')) {
customKey.changeKey(target.getAttribute('name'))
}
}
e.stopPropagation()
}
document.body.addEventListener('click', selectKey, false);
document.body.addEventListener('touch', s... | {
var surface = document.querySelector('.restrictRect').getBoundingClientRect()
interact('.moveableText')
.draggable({
onmove: window.dragMoveListener,
snap: {
targets: [{}],
range:20,
relativePoints: [
//{ x: 0 , y: 0 } // snap relative to the element's top... | identifier_body |
keycap.js | import Vue from 'vue/dist/vue.js'
import KeyCustomizer from './components/KeyCustomizer.vue'
import KeySelector from './components/KeySelector.vue'
import NavBar from './components/NavBar.vue'
import KeycapProductInfo from './components/KeycapProductInfo'
Vue.config.productionTip = false
var customKey = new Vue({
e... | () {
return {transform: 'translate(' + this.surfaces[this.currentView].img.x + 'px,' + this.surfaces[this.currentView].img.y + 'px)'}
}
},
mounted: function () {
var self = this;
fetch('https://us-central1-hotsguide-188315.cloudfunctions.net/function-1?board=keyboard-104&sides=true'... | transformImg | identifier_name |
keycap.js | import Vue from 'vue/dist/vue.js'
import KeyCustomizer from './components/KeyCustomizer.vue'
import KeySelector from './components/KeySelector.vue'
import NavBar from './components/NavBar.vue'
import KeycapProductInfo from './components/KeycapProductInfo'
Vue.config.productionTip = false
var customKey = new Vue({
e... | canvg('canvas', svg_xml, {useCORS: true});
var context = canvas.getContext('2d');
console.log(img.width)
console.log(img.height)
context.drawImage(img, self.surfaces[thisSurface].img.x, self.surfaces[thisSurface].img.y, self.surfaces[thi... | var thisSurface = surface
img.onload = function () {
var svg_xml = (new XMLSerializer()).serializeToString(newSvg); | random_line_split |
keycap.js | import Vue from 'vue/dist/vue.js'
import KeyCustomizer from './components/KeyCustomizer.vue'
import KeySelector from './components/KeySelector.vue'
import NavBar from './components/NavBar.vue'
import KeycapProductInfo from './components/KeycapProductInfo'
Vue.config.productionTip = false
var customKey = new Vue({
e... | else {
itemsSpan = document.createElement('span')
itemsSpan.innerHTML = ' ('+cartItems.length+')'
itemsSpan.setAttribute('style','color:blue;')
cartLink.appendChild(itemsSpan)
}
})
},
setColor: function(color) {
document.querySelector('.key... | {
itemsSpan.innerHTML = ' ('+cartItems.length+')'
} | conditional_block |
replicator.go | // Copyright (c) 2016-2018 iQIYI.com. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required b... |
func (r *Replicator) replicateLocal(
policy int, device *ring.Device, partition string, nodes *NodeChain) {
rehashed, localHash := r.getLocalHash(policy, device.Device, partition, nil)
r.stat.rehashed += rehashed
attempts := int(r.rings[policy].ReplicaCount()) - 1
for node := nodes.Next(); node != nil && attemp... | {
url := fmt.Sprintf("http://%s:%d/%s/%s",
node.Ip, node.Port, node.Device, partition)
if len(suffixes) > 0 {
url = fmt.Sprintf("%s/%s", url, strings.Join(suffixes, "-"))
}
req, err := http.NewRequest(common.REPLICATE, url, nil)
if err != nil {
r.logger.Error("unable to create diff request",
zap.String(... | identifier_body |
replicator.go | // Copyright (c) 2016-2018 iQIYI.com. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required b... | (
policy int, device *ring.Device, partition string, nodes *NodeChain) {
rehashed, localHash := r.getLocalHash(policy, device.Device, partition, nil)
r.stat.rehashed += rehashed
attempts := int(r.rings[policy].ReplicaCount()) - 1
for node := nodes.Next(); node != nil && attempts > 0; node = nodes.Next() {
attem... | replicateLocal | identifier_name |
replicator.go | // Copyright (c) 2016-2018 iQIYI.com. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required b... | msg := &SyncMsg{
LocalDevice: device.Device,
Host: node.Ip,
Port: int32(node.Port),
Device: node.Device,
Policy: uint32(policy),
Partition: partition,
Suffixes: suffixes,
}
ctx, cancel := context.WithCancel(context.Background())
defer cancel()
reply, err := r... | if remoteHash[s] != h {
suffixes = append(suffixes, s)
}
}
| random_line_split |
replicator.go | // Copyright (c) 2016-2018 iQIYI.com. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required b... |
}
return hashes, nil
}
func (r *Replicator) replicateLocal(
policy int, device *ring.Device, partition string, nodes *NodeChain) {
rehashed, localHash := r.getLocalHash(policy, device.Device, partition, nil)
r.stat.rehashed += rehashed
attempts := int(r.rings[policy].ReplicaCount()) - 1
for node := nodes.Nex... | {
hashes[suff.(string)] = ""
} | conditional_block |
fleet.go | package cbcluster
import (
"bytes"
"encoding/json"
"fmt"
"html/template"
"io/ioutil"
"log"
"net/http"
"path"
"path/filepath"
"strings"
"time"
"github.com/coreos/fleet/schema"
"github.com/coreos/go-systemd/unit"
"github.com/tleyden/go-etcd/etcd"
)
const (
UNIT_NAME_NODE = "couchbase_node"
UNIT_NAM... | (allUnits bool) error {
ttlSeconds := uint64(300)
_, err := c.etcdClient.Set(KEY_REMOVE_REBALANCE_DISABLED, "true", ttlSeconds)
if err != nil {
return err
}
// call ManipulateUnits with a function that will stop them
unitDestroyer := func(unit *schema.Unit) error {
// stop the unit by updating desiredState... | DestroyUnits | identifier_name |
fleet.go | package cbcluster
import (
"bytes"
"encoding/json"
"fmt"
"html/template"
"io/ioutil"
"log"
"net/http"
"path"
"path/filepath"
"strings"
"time"
"github.com/coreos/fleet/schema"
"github.com/coreos/go-systemd/unit"
"github.com/tleyden/go-etcd/etcd"
)
const (
UNIT_NAME_NODE = "couchbase_node"
UNIT_NAM... |
func (c CouchbaseFleet) GenerateUnits(outputDir string) error {
// generate node unit
nodeFleetUnit, err := c.generateNodeFleetUnitFile()
if err != nil {
return err
}
filename := fmt.Sprintf("%v@.service", UNIT_NAME_NODE)
path := filepath.Join(outputDir, filename)
if err := ioutil.WriteFile(path, []byte(n... | {
stringContainsAny := func(s string, filters []string) bool {
for _, filter := range filters {
if strings.Contains(s, filter) {
return true
}
}
return false
}
for _, unit := range units {
if stringContainsAny(unit.Name, filters) {
filteredUnits = append(filteredUnits, unit)
}
}
return f... | identifier_body |
fleet.go | package cbcluster
import (
"bytes"
"encoding/json"
"fmt"
"html/template"
"io/ioutil"
"log"
"net/http"
"path"
"path/filepath"
"strings"
"time"
"github.com/coreos/fleet/schema"
"github.com/coreos/go-systemd/unit"
"github.com/tleyden/go-etcd/etcd"
)
const (
UNIT_NAME_NODE = "couchbase_node"
UNIT_NAM... |
// dirty hack to solve problem: the cluster might have
// 2 nodes which just finished rebalancing, and a third node
// that joins and triggers another rebalance. thus, it will briefly
// go into "no rebalances happening" state, followed by a rebalance.
// if we see the "no rebalances happening state", we'll be ... | {
return err
} | conditional_block |
fleet.go | package cbcluster
import (
"bytes"
"encoding/json"
"fmt"
"html/template"
"io/ioutil"
"log"
"net/http"
"path"
"path/filepath"
"strings"
"time"
"github.com/coreos/fleet/schema"
"github.com/coreos/go-systemd/unit"
"github.com/tleyden/go-etcd/etcd"
)
const (
UNIT_NAME_NODE = "couchbase_node"
UNIT_NAM... | // generate sidekick unit
sidekickFleetUnit, err := c.generateSidekickFleetUnitFile("%i")
if err != nil {
return err
}
filename = fmt.Sprintf("%v@.service", UNIT_NAME_SIDEKICK)
path = filepath.Join(outputDir, filename)
if err := ioutil.WriteFile(path, []byte(sidekickFleetUnit), 0644); err != nil {
return e... | random_line_split | |
aplicacao.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#####################################################
# Camada Física da Computação
# Henry Rocha
# 11/08/2019
# Exemplo de uso do ArgParse e do TkInter.
#####################################################
import sys
import time
import argparse
from enlace import *
fro... |
while True:
# Faz a recepção dos dados
print("\n[LOG] Recebendo dados...")
keywordRecognized = False
receiveBuffer = bytearray()
# Espera até receber uma keyword.
while not keywordRecognized:
rxBuffer, nRx = com.getData(1)
re... | com.enable()
# LOG
print("[LOG] Comunicação inicializada.")
print("[LOG] Porta: {}".format(com.fisica.name)) | random_line_split |
aplicacao.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#####################################################
# Camada Física da Computação
# Henry Rocha
# 11/08/2019
# Exemplo de uso do ArgParse e do TkInter.
#####################################################
import sys
import time
import argparse
from enlace import *
fro... |
def __init__(self, serialName, debug=False):
self.com = enlace(serialName)
self.com.enable()
self.debug = debug
self.fileName = None
self.results = []
if debug:
print("[LOG] Comunicação inicializada.")
print("[LOG] Porta: {}".format(self.com.... | ent(): | identifier_name |
aplicacao.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#####################################################
# Camada Física da Computação
# Henry Rocha
# 11/08/2019
# Exemplo de uso do ArgParse e do TkInter.
#####################################################
import sys
import time
import argparse
from enlace import *
fro... | enlace... variável COM possui todos os métodos e propriedades do enlace, que funciona em threading
com = enlace("/dev/ttyACM1") # Repare que o metodo construtor recebe um string (nome)
# Ativa comunicacão
com.enable()
# LOG
print("[LOG] Comunicação inicializada.")
print("[LOG] Porta: {}".fo... | ame) # Repare que o metodo construtor recebe um string (nome)
# Ativa comunicacão
com.enable()
# LOG
print("[LOG] Comunicação inicializada.")
print("[LOG] Porta: {}".format(com.fisica.name))
shouldClose = False
while not shouldClose:
# Verifica se o arquivo a ser transferido foi pa... | identifier_body |
aplicacao.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#####################################################
# Camada Física da Computação
# Henry Rocha
# 11/08/2019
# Exemplo de uso do ArgParse e do TkInter.
#####################################################
import sys
import time
import argparse
from enlace import *
fro... | ualiza dados da transmissão.
txSize = com.tx.getStatus()
print("[LOG] Transmitido...............{} bytes.".format(int(txSize)))
# Esperando pela resposta. Sabemos que ela deve ser o tamanho da arquivo.
print("[LOG] Esperando pela resposta do servidor com o tamanho do arquivo.")
... | # At | conditional_block |
lib.rs | //! A slab allocator implementation for small objects
//! (< architecture page size).
//!
//! The organization is as follows (top-down):
//!
//! * A `ZoneAllocator` manages many `SCAllocator` and can
//! satisfy requests for different allocation sizes.
//! * A `SCAllocator` allocates objects of exactly one size.
/... |
/// Check if the current `idx` is allocated.
///
/// # Notes
/// In case `idx` is 3 and allocation size of slab is
/// 8. The corresponding object would start at &data + 3 * 8.
fn is_allocated(&mut self, idx: usize) -> bool {
let base_idx = idx / 64;
let bit_idx = idx % 64;
... | {
unsafe {
for (base_idx, b) in self.bitfield.iter().enumerate() {
let bitval = *b;
if bitval == u64::max_value() {
continue;
} else {
let negated = !bitval;
let first_free = negated.trailing_... | identifier_body |
lib.rs | //! A slab allocator implementation for small objects
//! (< architecture page size).
//!
//! The organization is as follows (top-down):
//!
//! * A `ZoneAllocator` manages many `SCAllocator` and can
//! satisfy requests for different allocation sizes.
//! * A `SCAllocator` allocates objects of exactly one size.
/... | (current_size: usize) -> Option<usize> {
match current_size {
0...8 => Some(8),
9...16 => Some(16),
17...32 => Some(32),
33...64 => Some(64),
65...128 => Some(128),
129...256 => Some(256),
257...512 => Some(512),
513... | get_max_size | identifier_name |
lib.rs | //! A slab allocator implementation for small objects
//! (< architecture page size).
//!
//! The organization is as follows (top-down):
//!
//! * A `ZoneAllocator` manages many `SCAllocator` and can
//! satisfy requests for different allocation sizes.
//! * A `SCAllocator` allocates objects of exactly one size.
/... |
}
ptr::null_mut()
}
/// Allocates a block of memory with respect to `alignment`.
///
/// In case of failure will try to grow the slab allocator by requesting
/// additional pages and re-try the allocation once more before we give up.
pub fn allocate<'b>(&'b mut self, layout: L... | {
continue;
} | conditional_block |
lib.rs | //! A slab allocator implementation for small objects
//! (< architecture page size).
//!
//! The organization is as follows (top-down):
//!
//! * A `ZoneAllocator` manages many `SCAllocator` and can
//! satisfy requests for different allocation sizes.
//! * A `SCAllocator` allocates objects of exactly one size.
/... | SCAllocator::new(32, pager),
SCAllocator::new(64, pager),
SCAllocator::new(128, pager),
SCAllocator::new(256, pager),
SCAllocator::new(512, pager),
SCAllocator::new(1024, pager),
SCAllocator::new(2048, pager)... | ZoneAllocator {
pager: pager,
slabs: [
SCAllocator::new(8, pager),
SCAllocator::new(16, pager), | random_line_split |
ip6.py | # $Id: ip6.py 87 2013-03-05 19:41:04Z andrewflnr@gmail.com $
# -*- coding: utf-8 -*-
"""Internet Protocol, version 6."""
from __future__ import print_function
from __future__ import absolute_import
from . import dpkt
from . import ip
from .compat import compat_ord
class IP6(dpkt.Packet):
"""Internet Protocol, ve... | self.length = (self.len + 1) * 8
options = []
index = 0
while index < self.length - 2:
opt_type = compat_ord(self.data[index])
# PAD1 option
if opt_type == 0:
index += 1
continue
opt_length = compat_ord(s... | ('len', 'B', 0) # option data length in 8 octect units (ignoring first 8 octets) so, len 0 == 64bit header
)
def unpack(self, buf):
dpkt.Packet.unpack(self, buf) | random_line_split |
ip6.py | # $Id: ip6.py 87 2013-03-05 19:41:04Z andrewflnr@gmail.com $
# -*- coding: utf-8 -*-
"""Internet Protocol, version 6."""
from __future__ import print_function
from __future__ import absolute_import
from . import dpkt
from . import ip
from .compat import compat_ord
class IP6(dpkt.Packet):
"""Internet Protocol, ve... |
next_ext_hdr = self.nxt
while next_ext_hdr in ext_hdrs:
ext = ext_hdrs_cls[next_ext_hdr](buf)
self.extension_hdrs[next_ext_hdr] = ext
self.all_extension_headers.append(ext)
buf = buf[ext.length:]
next_ext_hdr = getattr(ext, 'nxt', None)
... | buf = self.data | conditional_block |
ip6.py | # $Id: ip6.py 87 2013-03-05 19:41:04Z andrewflnr@gmail.com $
# -*- coding: utf-8 -*-
"""Internet Protocol, version 6."""
from __future__ import print_function
from __future__ import absolute_import
from . import dpkt
from . import ip
from .compat import compat_ord
class IP6(dpkt.Packet):
"""Internet Protocol, ve... |
def test_ip6_extension_headers():
p = (b'\x60\x00\x00\x00\x00\x3c\x2b\x40\x20\x48\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
b'\xde\xca\x20\x47\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\xca\xfe\x06\x04\x00\x02'
b'\x00\x00\x00\x00\x20\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x... | s = (b'\x00\x00\x01\x00\x00\x00\x00\x44\xe2\x4f\x9e\x68\xf3\xcd\xb1\x5f\x61\x65\x42\x8b\x78\x0b'
b'\x4a\xfd\x13\xf0\x15\x98\xf5\x55\x16\xa8\x12\xb3\xb8\x4d\xbc\x16\xb2\x14\xbe\x3d\xf9\x96'
b'\xd4\xa0\x39\x1f\x85\x74\x25\x81\x83\xa6\x0d\x99\xb6\xba\xa3\xcc\xb6\xe0\x9a\x78\xee\xf2'
b'\xaf\x9a')... | identifier_body |
ip6.py | # $Id: ip6.py 87 2013-03-05 19:41:04Z andrewflnr@gmail.com $
# -*- coding: utf-8 -*-
"""Internet Protocol, version 6."""
from __future__ import print_function
from __future__ import absolute_import
from . import dpkt
from . import ip
from .compat import compat_ord
class IP6(dpkt.Packet):
"""Internet Protocol, ve... | (self):
return (self._v_fc_flow >> 20) & 0xff
@fc.setter
def fc(self, v):
self._v_fc_flow = (self._v_fc_flow & ~0xff00000) | (v << 20)
@property
def flow(self):
return self._v_fc_flow & 0xfffff
@flow.setter
def flow(self, v):
self._v_fc_flow = (self._v_fc_flow ... | fc | identifier_name |
schema.go | // Copyright (c) 2017-2018 Uber Technologies, Inc.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicabl... | tableSchema.Lock()
m.RUnlock()
enumDict, columnExist := tableSchema.EnumDicts[columnName]
if !columnExist {
tableSchema.Unlock()
return
}
enumDict.Dict[newEnumCase] = len(enumDict.ReverseDict)
enumDict.ReverseDict = append(enumDict.ReverseDict, newEnumCase)
tableSchema.EnumDicts[columnName] = enumDict
tab... | return
}
| random_line_split |
schema.go | // Copyright (c) 2017-2018 Uber Technologies, Inc.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicabl... |
tableSchema.createEnumDict(column.Name, enumCases)
newEnumColumns = append(newEnumColumns, column.Name)
}
}
var oldPreloadingDays int
newPreloadingDays := column.Config.PreloadingDays
// preloading will be triggered if
// 1. this is a new column and PreloadingDays > 0
// 2. this is a ol... | {
enumCases = append(enumCases, *column.DefaultValue)
// default value is already appended, start watching from 1
startEnumID = 1
} | conditional_block |
schema.go | // Copyright (c) 2017-2018 Uber Technologies, Inc.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicabl... | (table *metaCom.Table) *TableSchema {
tableSchema := &TableSchema{
Schema: *table,
ColumnIDs: make(map[string]int),
EnumDicts: make(map[string]EnumDict),
ValueTypeByColumn: make([]memCom.DataType, len(table.Columns)),
PrimaryKeyColumnTypes: make([]memCom.DataType, l... | NewTableSchema | identifier_name |
schema.go | // Copyright (c) 2017-2018 Uber Technologies, Inc.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicabl... |
// GetArchivingSortColumns makes a copy of the Schema.ArchivingSortColumns so
// callers don't have to hold a read lock to access it.
func (t *TableSchema) GetArchivingSortColumns() []int {
t.RLock()
defer t.RUnlock()
return t.Schema.ArchivingSortColumns
}
// FetchSchema fetches schema from metaStore and updates ... | {
nonNilDefaultByColumn := make([]bool, len(t.Schema.Columns))
for columnID, column := range t.Schema.Columns {
nonNilDefaultByColumn[columnID] = column.DefaultValue != nil
}
return nonNilDefaultByColumn
} | identifier_body |
util.py | # Copyright 2018 The TensorFlow Authors All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
# Depth evaluation utils
# Mostly based on the code written by Clement Godard:
# https://github.com/mrharicot/monodepth/blob/master/utils/evaluation_utils.py
def compute_errors(gt, pred):
thresh = np.maximum((gt / pred), (pred / gt))
a1 = (thresh < 1.25).mean()
a2 = (thresh < 1.25 ** 2).mean()
a3 =... | """Pack depth predictions as a single .npy file"""
test_images = read_text_lines(test_file)
save_name = 'pred_depth.npy'
output_file = os.path.join(pred_dir, save_name)
img_height = 128
img_width = 416
all_pred = np.zeros((len(test_images), img_height, img_width))
for i, img_path in enum... | identifier_body |
util.py | # Copyright 2018 The TensorFlow Authors All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | (path):
# taken from https://github.com/hunse/kitti
float_chars = set("0123456789.e+- ")
data = {}
with open(path, 'r') as f:
for line in f.readlines():
key, value = line.split(':', 1)
value = value.strip()
data[key] = value
if float_chars.issupers... | read_calib_file | identifier_name |
util.py | # Copyright 2018 The TensorFlow Authors All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
else:
return 'Empty list.'
elif isinstance(obj, tuple):
if obj:
return 'Tuple of %d... %s' % (len(obj), info(obj[0]))
else:
return 'Empty tuple.'
else:
if is_a_numpy_array(obj):
return 'Array with shape: %s, dtype: %s' % (obj.shape... | return 'List of %d... %s' % (len(obj), info(obj[0])) | conditional_block |
util.py | # Copyright 2018 The TensorFlow Authors All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | gt_files = []
gt_calib = []
im_sizes = []
im_files = []
cams = []
num_probs = 0
for filename in files:
filename = filename.split()[0]
splits = filename.split('/')
# camera_id = filename[-1] # 2 is left, 3 is right
date = splits[0]
im_id = spl... | def read_file_data(files, data_root): | random_line_split |
gogo_fast_api.pb.go | // Code generated by protoc-gen-gogo. DO NOT EDIT.
// source: gogo_fast_api.proto
package gogoapi
import (
fmt "fmt"
proto "github.com/gogo/protobuf/proto"
types "github.com/gogo/protobuf/types"
math "math"
)
// Reference imports to suppress errors if they are not otherwise used.
var _ = proto.Marshal
var _ = fm... |
func (m *Http) GetFullyDecodeReservedExpansion() bool {
if m != nil {
return m.FullyDecodeReservedExpansion
}
return false
}
func (m *Http) GetAnyData() *types.Any {
if m != nil {
return m.AnyData
}
return nil
}
// HttpRule .
type HttpRule struct {
Selector string `protobuf:"bytes,1,opt,name=selector,pro... | {
if m != nil {
return m.Rules
}
return nil
} | identifier_body |
gogo_fast_api.pb.go | // Code generated by protoc-gen-gogo. DO NOT EDIT.
// source: gogo_fast_api.proto
package gogoapi
import (
fmt "fmt"
proto "github.com/gogo/protobuf/proto"
types "github.com/gogo/protobuf/types"
math "math"
)
// Reference imports to suppress errors if they are not otherwise used.
var _ = proto.Marshal
var _ = fm... |
return nil
}
func (m *Http) GetFullyDecodeReservedExpansion() bool {
if m != nil {
return m.FullyDecodeReservedExpansion
}
return false
}
func (m *Http) GetAnyData() *types.Any {
if m != nil {
return m.AnyData
}
return nil
}
// HttpRule .
type HttpRule struct {
Selector string `protobuf:"bytes,1,opt,nam... | {
return m.Rules
} | conditional_block |
gogo_fast_api.pb.go | // Code generated by protoc-gen-gogo. DO NOT EDIT.
// source: gogo_fast_api.proto
package gogoapi
import (
fmt "fmt"
proto "github.com/gogo/protobuf/proto"
types "github.com/gogo/protobuf/types"
math "math"
)
// Reference imports to suppress errors if they are not otherwise used.
var _ = proto.Marshal
var _ = fm... | func (m *HttpRule) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
return xxx_messageInfo_HttpRule.Marshal(b, m, deterministic)
}
func (m *HttpRule) XXX_Merge(src proto.Message) {
xxx_messageInfo_HttpRule.Merge(m, src)
}
func (m *HttpRule) XXX_Size() int {
return xxx_messageInfo_HttpRule.Size(m)
}
func (... | return xxx_messageInfo_HttpRule.Unmarshal(m, b)
} | random_line_split |
gogo_fast_api.pb.go | // Code generated by protoc-gen-gogo. DO NOT EDIT.
// source: gogo_fast_api.proto
package gogoapi
import (
fmt "fmt"
proto "github.com/gogo/protobuf/proto"
types "github.com/gogo/protobuf/types"
math "math"
)
// Reference imports to suppress errors if they are not otherwise used.
var _ = proto.Marshal
var _ = fm... | () string {
if m != nil {
return m.Selector
}
return ""
}
func (m *HttpRule) GetGet() string {
if x, ok := m.GetPattern().(*HttpRule_Get); ok {
return x.Get
}
return ""
}
func (m *HttpRule) GetPut() string {
if x, ok := m.GetPattern().(*HttpRule_Put); ok {
return x.Put
}
return ""
}
func (m *HttpRule)... | GetSelector | identifier_name |
app.js | /**
* Created by yj on 16/4/29.
*/
/**
* 最小堆
*/
class MinHeap{
constructor(cmp){
this.cmp = cmp;
this.queue = []
}
push(val){
this.queue.push(val);
}
peek(){
if(this.empty()){
throw new Error("Can't peek an empty heap");
}
return this.... | (let i = 0; i < rows; i++) {
html += '<tr>';
for (let j = 0; j < cols; j++) {
html += '<td class="map-box" data-type="empty">';
}
html += '</tr>';
}
this.rows = rows;
this.cols = cols;
this.$el.innerHTML = html;
this... | for | identifier_name |
app.js | /**
* Created by yj on 16/4/29.
*/
/**
* 最小堆
*/
class MinHeap{
constructor(cmp){
this.cmp = cmp;
this.queue = []
}
push(val){
this.queue.push(val);
}
peek(){
if(this.empty()){
throw new Error("Can't peek an empty heap");
}
return this.... |
this.$el.style.top = y * 20 + 'px';
}
getPos() {
return {x: this.x, y: this.y};
}
}
/**
* 玩家类
*/
class Player extends Character{
constructor(selector) {
super(selector)
}
/**
* 异步移动,实现动画效果
* @param pos
*/
goto(pos) {
this.x = pos.x;
t... | this.$el.style.left = x * 20 + 'px'; | conditional_block |
app.js | /**
* Created by yj on 16/4/29.
*/
/**
* 最小堆
*/
class MinHeap{
constructor(cmp){
this.cmp = cmp;
this.queue = []
}
push(val){
this.queue.push(val);
}
peek(){
if(this.empty()){
throw new Error("Can't peek an empty heap");
}
return this.... | run_async(handler, args) {
let promise = new Promise((resolve, reject)=> {
this.queue.push({
handler, args,
callback: function (err, data) {
if (err) {
reject(err);
} else {
resolv... | [next])
.catch(err =>{
console.error(err)
})
}
let target = this.target.getPos()
if(dst.x == target.x && dst.y == target.y) {
this.run_async(function(){
this.fire('gameover'); // 游戏结束加载下一关卡
});
}
... | identifier_body |
app.js | /**
* Created by yj on 16/4/29.
*/
/**
* 最小堆
*/
class MinHeap{
constructor(cmp){
this.cmp = cmp;
this.queue = []
}
push(val){
this.queue.push(val);
}
peek(){
if(this.empty()){
throw new Error("Can't peek an empty heap");
}
return this.... | throw new Error('map is full');
}
Utils.shuffle(positions);
let player = positions[0];
let target = positions[1];
this.player.setPos(player);
this.target.setPos(target);
}
setEnemy(){
}
/**
* 随机的修建障碍物 //todo 建筑迷宫算法
*/
randBuild()... | }
}
let len = positions.length;
if (len < 2) { | random_line_split |
parse_tweet_data.py | # ______________________________________________________________________________________________________________________
# this code is **************************************(U) UNCLASSIFIED***************************************************
# ____________________________________________________________________________... |
df['stripped_tweet'] = edit_tweets
df['tweet_length'] = df['tweet_text'].str.len()
df['include_topic_model'] = include
df['stripped_tweet_length'] = df['include_topic_model'].str.len()
sub_df = df.loc[df['include_topic_model'] == '1']
outfile = path_split[1] + '_' + path_split[3] + '_sorted_... | include.append('0') | conditional_block |
parse_tweet_data.py | # ______________________________________________________________________________________________________________________
# this code is **************************************(U) UNCLASSIFIED***************************************************
# ____________________________________________________________________________... | (df, num=30):
'''Takes an input data frame and creates inventories for that data frame, sorted by date. First automatically calls
the sort function to sort the data frame by the default (date).
Inputs: Pandas data frame imported from *.csv or *.pkl file
Number of inventories to split into. ... | split_df | identifier_name |
parse_tweet_data.py | # ______________________________________________________________________________________________________________________
# this code is **************************************(U) UNCLASSIFIED***************************************************
# ____________________________________________________________________________... | outfile = path_split[1] + '_' + path_split[3] + '_sorted_strip_' + lang + '_' + today + '.pkl'
# save new data frame under *.pkl file
ext_path = os.path.join(path, '1_DataFrames')
sub_df.to_pickle(os.path.join(ext_path, outfile))
return sub_df
def extract_content(df, label='All_Languages'):
'... | df['stripped_tweet_length'] = df['include_topic_model'].str.len()
sub_df = df.loc[df['include_topic_model'] == '1']
| random_line_split |
parse_tweet_data.py | # ______________________________________________________________________________________________________________________
# this code is **************************************(U) UNCLASSIFIED***************************************************
# ____________________________________________________________________________... |
def main():
print('Start time: ' + str(datetime.now()))
infile = 'Twitter_Russia_1906_sorted_strip_en_200929.pkl'
inpath = os.path.join(path, '1_DataFrames')
infilepath = os.path.join(inpath, infile)
stripped_en = pd.read_pickle(infilepath)
print(stripped_en.head()['unique_id_ida'])
# ... | '''Takes an input data frame and generates a histogram of number of tweets binned by month.
Inputs: Pandas data frame imported from *.csv or *.pkl file
Input parameter called "increment", which determined by what time interval the tweets are organized
Outputs: Histogram
'''
date_bounds = p... | identifier_body |
09_XGBC_img.py | # -*- coding: utf-8 -*-
"""
Created on Sun Jul 28 19:17:34 2019
@author: Logan Rowe
"""
import numpy as np
import os
import sys
import pandas as pd
from pandas.plotting import scatter_matrix
from sklearn.ensemble import RandomForestClassifier
from sklearn.preprocessing import StandardScaler
from sklearn.pipeline imp... |
# =============================================================================
# Run again with more estimators and early stopping to check for over fitting
# =============================================================================
params['n_estimators']=100
clf=xgboost.XGBClassifier(**params)
eval_set=[(... | X=dp.numpy_to_pd(X_raw,column_names)
# =============================================================================
# SPLIT DATA INTO TEST AND TRAIN BOTH BALANCED
# WITH RESPECT TO (NON)BOWTIES
# =============================================================================
split=S... | conditional_block |
09_XGBC_img.py | # -*- coding: utf-8 -*-
"""
Created on Sun Jul 28 19:17:34 2019
@author: Logan Rowe
"""
import numpy as np
import os
import sys
import pandas as pd
from pandas.plotting import scatter_matrix
from sklearn.ensemble import RandomForestClassifier
from sklearn.preprocessing import StandardScaler
from sklearn.pipeline imp... |
seeking=True
if seeking:
X=dp.numpy_to_pd(X_raw,column_names)
# =============================================================================
# SPLIT DATA INTO TEST AND TRAIN BOTH BALANCED
# WITH RESPECT TO (NON)BOWTIES
# ==============================================================... | column_names=c1+c2+c3+c4
| random_line_split |
data_tensorboard.py | import tensorflow as tf
from tensorflow import keras
import numpy as np
import os
import cv2
from tensorflow.keras.preprocessing.image import ImageDataGenerator
"""
crop_top takes as an input img which is an array of shape (x, y, 3) and
percentage of picture to crop
"""
def crop_top(img, percent=0.15):
offset =... |
return batch_x, batch_y, weights
def __len__(self):
return int(np.ceil(len(self.datasets[0]) / float(self.batch_size))) # returns the numer of batches that we will have
def on_epoch_end(self):
'Updates indexes after each epoch'
if self.shuffle == True:
for v in se... | self.on_epoch_end() # schuffle traing set
self.n = 0 # set to zero | conditional_block |
data_tensorboard.py | import tensorflow as tf
from tensorflow import keras
import numpy as np
import os
import cv2
from tensorflow.keras.preprocessing.image import ImageDataGenerator
"""
crop_top takes as an input img which is an array of shape (x, y, 3) and
percentage of picture to crop
"""
def | (img, percent=0.15):
offset = int(img.shape[0] * percent) #cut the top portion of image
return img[offset:] # return image
"""
central_crop takes as an input img which is an array of shape (x, y, 3)
"""
def central_crop(img):
size = min(img.shape[0], img.shape[1]) # min of x and y
offset_h = int((img.s... | crop_top | identifier_name |
data_tensorboard.py | import tensorflow as tf
from tensorflow import keras
import numpy as np
import os
import cv2
from tensorflow.keras.preprocessing.image import ImageDataGenerator
"""
crop_top takes as an input img which is an array of shape (x, y, 3) and
percentage of picture to crop
"""
def crop_top(img, percent=0.15):
offset =... |
"""
_process_csv_file take as an input a file in our case these are train_split.txt and test_split.txt (names may differ)
"""
def _process_csv_file(file):
with open(file, 'r') as fr: # open file
files = fr.readlines() # read lines
return files
class BalanceCovidDataset(keras.utils.Sequence):
'G... | img = random_ratio_resize(img) #defina above
img = _augmentation_transform.random_transform(img) # Applies a random transformation to an image.
return img | identifier_body |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.