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 |
|---|---|---|---|---|
tax_task.py | #!/usr/bin/env python
# encoding: utf-8
import os
import time
import argparse
import sys
sys.path.append('..')
sys.path.append('.')
import tensorflow as tf
from sklearn.utils import shuffle
from keras.callbacks import TensorBoard
from keras.models import Model, load_model
from keras.utils.vis_utils import plot_model... | (config):
# model save path
model_save_dir = os.path.join("../model/tax-task", model_name, time_str)
if not os.path.exists(model_save_dir):
os.makedirs(model_save_dir)
# log save path
log_save_dir = os.path.join("../logs/tax-task", model_name, time_str)
if not os.path.exists(log_save_di... | train | identifier_name |
tax_task.py | #!/usr/bin/env python
# encoding: utf-8
import os
import time
import argparse
import sys
sys.path.append('..')
sys.path.append('.')
import tensorflow as tf
from sklearn.utils import shuffle
from keras.callbacks import TensorBoard
from keras.models import Model, load_model
from keras.utils.vis_utils import plot_model... | .replace(".h5", "_best.h5"))
print("train done. best epoch: %d, best: f1: %f, model path: %s" % (best_epoch, best_f1, best_model))
file.write("train done. best epoch: %d, best: f1: %f, model path: %s\n" % (best_epoch, best_f1, best_model))
CallBack.on_train_end(None)
file.close()
# evaluate
def model_... | ata_train)
start_time = time.time()
llprint("Epoch %d/%d\n" % (epoch + 1, config["epochs"]))
losses = []
train_pred_output_prob = []
train_pred_output = []
train_real_output = []
file.write("Epoch: %d/%d\n" % ((epoch + 1), config["epochs"]))
for patient_... | conditional_block |
tax_task.py | #!/usr/bin/env python
# encoding: utf-8
import os
import time
import argparse
import sys
sys.path.append('..')
sys.path.append('.')
import tensorflow as tf
from sklearn.utils import shuffle
from keras.callbacks import TensorBoard
from keras.models import Model, load_model
from keras.utils.vis_utils import plot_model... |
CallBack = TensorBoard(log_dir=('../tb-logs/tax-task/%s/%s' %(model_name, time_str)), # log dir
histogram_freq=0,
write_graph=True,
write_grads=True,
write_images=True,
embeddings_freq=0,
... | for name, value in zip(names, logs):
summary = tf.Summary()
summary_value = summary.value.add()
summary_value.simple_value = value
summary_value.tag = name
callback.writer.add_summary(summary, epoch_no)
callback.writer.flush() | identifier_body |
tax_task.py | #!/usr/bin/env python
# encoding: utf-8
import os
import time
import argparse
import sys
sys.path.append('..')
sys.path.append('.')
import tensorflow as tf
from sklearn.utils import shuffle
from keras.callbacks import TensorBoard
from keras.models import Model, load_model
from keras.utils.vis_utils import plot_model... |
if __name__ == "__main__":
print("#####################args#####################")
print(args)
config = {
"datapath": args.datapath,
"run_mode": args.run_mode,
"debug": args.debug,
"use_tensorboard": not args.no_tensorboard,
"has_position_embed": not args.no_positio... | roc_auc = roc_auc_non_multi(eval_real_output, eval_pred_output_prob)
prauc = prc_auc_non_multi(eval_real_output, eval_pred_output_prob)
return acc, prec, recall, f1, prauc, roc_auc | random_line_split |
nn.rs | //! Neural networks
use crate::matrix::*;
/// a network
#[derive(Debug)]
pub struct Network {
// activation functions
activations: Vec<Box<dyn Activation>>,
// topology
topology: Vec<usize>,
// weights
weights: Vec<Matrix>
}
impl Network {
/// create a new random network with the given top... |
/// back propagation
pub fn backward(&mut self, inputs :&[f64], outputs :Vec<Vec<f64>>, target :&[f64], learning_rate: f64 ) {
debug!("Error: {}", error(target, outputs.last().expect("outputs")));
let l = outputs.len();
let mut new_weights = self.weights.clone();
let mut new_ta... | {
assert_eq!(self.topology[0],inputs.len());
let mut m = Matrix::new(1,inputs.len(),inputs);
let mut all_results = Vec::with_capacity(self.topology.len() - 1);
self.weights.iter().enumerate().for_each(| (ix,wm) | {
add_column(&mut m,vec!(1.0));
m = mul(&m,wm);
... | identifier_body |
nn.rs | //! Neural networks
use crate::matrix::*;
/// a network
#[derive(Debug)]
pub struct Network {
// activation functions
activations: Vec<Box<dyn Activation>>,
// topology
topology: Vec<usize>,
// weights
weights: Vec<Matrix>
}
impl Network {
/// create a new random network with the given top... |
}
}
/// Softmax activation function
#[derive(Debug)]
pub struct Softmax{}
impl Activation for Softmax {
fn activate(&self, inputs: &[f64]) -> Vec<f64> {
softmax(inputs)
}
fn derive(&self, outputs: &[f64], index: usize) -> f64 {
let s: f64 = outputs.iter().sum();
let el = out... | {0.0} | conditional_block |
nn.rs | //! Neural networks
use crate::matrix::*;
/// a network
#[derive(Debug)]
pub struct Network {
// activation functions
activations: Vec<Box<dyn Activation>>,
// topology
topology: Vec<usize>,
// weights
weights: Vec<Matrix>
}
impl Network {
/// create a new random network with the given top... | inputs
};
let previous_size = size(&weights).0;
debug!("previous size: {}",previous_size);
debug!("weights to update: {:?}",size(&weights));
new_targets.push(vec!(0.0; previous_size));
for (i,o) in outputs[rev_order]... | } else { | random_line_split |
nn.rs | //! Neural networks
use crate::matrix::*;
/// a network
#[derive(Debug)]
pub struct Network {
// activation functions
activations: Vec<Box<dyn Activation>>,
// topology
topology: Vec<usize>,
// weights
weights: Vec<Matrix>
}
impl Network {
/// create a new random network with the given top... | (&self, inputs :&[f64]) -> Vec<Vec<f64>> {
assert_eq!(self.topology[0],inputs.len());
let mut m = Matrix::new(1,inputs.len(),inputs);
let mut all_results = Vec::with_capacity(self.topology.len() - 1);
self.weights.iter().enumerate().for_each(| (ix,wm) | {
add_column(&mut m,ve... | forward | identifier_name |
vm.rs | #![allow(clippy::arithmetic_side_effects)]
// Derived from uBPF <https://github.com/iovisor/ubpf>
// Copyright 2015 Big Switch Networks, Inc
// (uBPF: VM architecture, parts of the interpreter, originally in C)
// Copyright 2016 6WIND S.A. <quentin.monnet@6wind.com>
// (Translation to Rust, MetaBuff/multiple ... | {
/// Contains the register state at every instruction in order of execution
pub trace_log: Vec<TraceLogEntry>,
/// Maximal amount of instructions which still can be executed
pub remaining: u64,
}
impl ContextObject for TestContextObject {
fn trace(&mut self, state: [u64; 12]) {
self.trace... | TestContextObject | identifier_name |
vm.rs | #![allow(clippy::arithmetic_side_effects)]
// Derived from uBPF <https://github.com/iovisor/ubpf>
// Copyright 2015 Big Switch Networks, Inc
// (uBPF: VM architecture, parts of the interpreter, originally in C)
// Copyright 2016 6WIND S.A. <quentin.monnet@6wind.com>
// (Translation to Rust, MetaBuff/multiple ... |
}
#[cfg(test)]
mod tests {
use super::*;
use crate::syscalls;
#[test]
fn test_program_result_is_stable() {
let ok = ProgramResult::Ok(42);
assert_eq!(unsafe { *(&ok as *const _ as *const u64) }, 0);
let err = ProgramResult::Err(Box::new(EbpfError::JitNotCompiled));
ass... | {
let mut registers = [0u64; 12];
// R1 points to beginning of input memory, R10 to the stack of the first frame, R11 is the pc (hidden)
registers[1] = ebpf::MM_INPUT_START;
registers[ebpf::FRAME_PTR_REG] = self.stack_pointer;
registers[11] = executable.get_entrypoint_instruction... | identifier_body |
vm.rs | #![allow(clippy::arithmetic_side_effects)]
// Derived from uBPF <https://github.com/iovisor/ubpf>
// Copyright 2015 Big Switch Networks, Inc
// (uBPF: VM architecture, parts of the interpreter, originally in C)
// Copyright 2016 6WIND S.A. <quentin.monnet@6wind.com>
// (Translation to Rust, MetaBuff/multiple ... |
impl<'a, C: ContextObject> EbpfVm<'a, C> {
/// Creates a new virtual machine instance.
pub fn new(
config: &Config,
sbpf_version: &SBPFVersion,
context_object: &'a mut C,
mut memory_mapping: MemoryMapping<'a>,
stack_len: usize,
) -> Self {
let stack_pointer =... | pub debug_port: Option<u16>,
} | random_line_split |
vm.rs | #![allow(clippy::arithmetic_side_effects)]
// Derived from uBPF <https://github.com/iovisor/ubpf>
// Copyright 2015 Big Switch Networks, Inc
// (uBPF: VM architecture, parts of the interpreter, originally in C)
// Copyright 2016 6WIND S.A. <quentin.monnet@6wind.com>
// (Translation to Rust, MetaBuff/multiple ... | ;
let instruction_count = if config.enable_instruction_meter {
self.context_object_pointer.consume(due_insn_count);
initial_insn_count.saturating_sub(self.context_object_pointer.get_remaining())
} else {
0
};
let mut result = ProgramResult::Ok(0);
... | {
#[cfg(all(feature = "jit", not(target_os = "windows"), target_arch = "x86_64"))]
{
let compiled_program = match executable
.get_compiled_program()
.ok_or_else(|| Box::new(EbpfError::JitNotCompiled))
{
O... | conditional_block |
ed25519.rs | // -*- mode: rust; -*-
//
// This file is part of ed25519-dalek.
// Copyright (c) 2017 Isis Lovecruft
// See LICENSE for licensing information.
//
// Authors:
// - Isis Agora Lovecruft <isis@patternsinthevoid.net>
//! A Rust implementation of ed25519 EdDSA key generation, signing, and
//! verification.
use core::fmt:... | TestSignVerify
let mut cspring: OsRng;
let keypair: Keypair;
let good_sig: Signature;
let bad_sig: Signature;
let good: &[u8] = "test message".as_bytes();
let bad: &[u8] = "wrong message".as_bytes();
cspring = OsRng::new().unwrap();
keypair = Keypai... | ify() { // | identifier_name |
ed25519.rs | // -*- mode: rust; -*-
//
// This file is part of ed25519-dalek.
// Copyright (c) 2017 Isis Lovecruft
// See LICENSE for licensing information.
//
// Authors:
// - Isis Agora Lovecruft <isis@patternsinthevoid.net>
//! A Rust implementation of ed25519 EdDSA key generation, signing, and
//! verification.
use core::fmt:... | if ao.is_some() {
a = ao.unwrap();
} else {
return false;
}
a = -(&a);
let top_half: &[u8; 32] = array_ref!(&signature.0, 32, 32);
let bottom_half: &[u8; 32] = array_ref!(&signature.0, 0, 32);
h.input(&bottom_half[..]);
h.inpu... | return false;
}
ao = self.decompress();
| random_line_split |
ed25519.rs | // -*- mode: rust; -*-
//
// This file is part of ed25519-dalek.
// Copyright (c) 2017 Isis Lovecruft
// See LICENSE for licensing information.
//
// Authors:
// - Isis Agora Lovecruft <isis@patternsinthevoid.net>
//! A Rust implementation of ed25519 EdDSA key generation, signing, and
//! verification.
use core::fmt:... | /// View this public key as a byte array.
#[inline]
pub fn as_bytes<'a>(&'a self) -> &'a [u8; PUBLIC_KEY_LENGTH] {
&(self.0).0
}
/// Construct a `PublicKey` from a slice of bytes.
///
/// # Warning
///
/// The caller is responsible for ensuring that the bytes passed into this
... | self.0.to_bytes()
}
| identifier_body |
ed25519.rs | // -*- mode: rust; -*-
//
// This file is part of ed25519-dalek.
// Copyright (c) 2017 Isis Lovecruft
// See LICENSE for licensing information.
//
// Authors:
// - Isis Agora Lovecruft <isis@patternsinthevoid.net>
//! A Rust implementation of ed25519 EdDSA key generation, signing, and
//! verification.
use core::fmt:... | lse {
return false;
}
}
}
impl Signature {
/// View this `Signature` as a byte array.
#[inline]
pub fn to_bytes(&self) -> [u8; SIGNATURE_LENGTH] {
self.0
}
/// View this `Signature` as a byte array.
#[inline]
pub fn as_bytes<'a>(&'a self) -> &'a [u8; SIGNATU... | return true;
} e | conditional_block |
asset.go | // Generated by goasset(1.0 20200404) or "go generate" . DO NOT EDIT.
// https://github.com/hidu/goasset/
package res
import (
"bytes"
"compress/gzip"
"encoding/base64"
"flag"
"fmt"
"io/ioutil"
"log"
"mime"
"net/http"
"os"
"path"
"path/filepath"
"regexp"
"runtime"
"strings"
"time"
)
// AssetFile one ... | (name string) []byte {
s, err := afs.GetAssetFile(name)
if err != nil {
return []byte("")
}
return s.Content()
}
// GetFileNames get all file names
func (afs *assetFiles) GetFileNames(dir string) []string {
if dir == "" {
dir = "/"
}
names := make([]string, 0, len(afs.Files))
dirRaw := dir
dir = path.Clea... | GetContent | identifier_name |
asset.go | // Generated by goasset(1.0 20200404) or "go generate" . DO NOT EDIT.
// https://github.com/hidu/goasset/
package res
import (
"bytes"
"compress/gzip"
"encoding/base64"
"flag"
"fmt"
"io/ioutil"
"log"
"mime"
"net/http"
"os"
"path"
"path/filepath"
"regexp"
"runtime"
"strings"
"time"
)
// AssetFile one ... |
helper := newAssetHelper()
contentNew, errHelper := helper.Execute(assetFilePath, content, "")
if errHelper != nil {
return nil, errHelper
}
return &assetFile{
content: contentNew,
name: name,
mtime: info.ModTime(),
}, nil
}
return nil, fmt.Errorf("not file")
}
if sf, has ... | {
return nil, err
} | conditional_block |
asset.go | // Generated by goasset(1.0 20200404) or "go generate" . DO NOT EDIT.
// https://github.com/hidu/goasset/
package res
import (
"bytes"
"compress/gzip"
"encoding/base64"
"flag"
"fmt"
"io/ioutil"
"log"
"mime"
"net/http"
"os"
"path"
"path/filepath"
"regexp"
"runtime"
"strings"
"time"
)
// AssetFile one ... | r _ = flag.String
var _ = runtime.Version()
// ---------------------------helper.go--------begin--------------------------//
func newAssetHelper() *assetHelper {
helper := &assetHelper{}
helper.Regs = make(map[string]*regexp.Regexp)
helper.Regs["remove_above"] = regexp.MustCompile(`[\S\s]*?//\s*asset_remove_above... | oin(f.pdir, r.URL.Path))
f.sf.FileHandlerFunc(name).ServeHTTP(w, r)
}
var _ AssetFiles = &assetFiles{}
va | identifier_body |
asset.go | // Generated by goasset(1.0 20200404) or "go generate" . DO NOT EDIT.
// https://github.com/hidu/goasset/
package res
import (
"bytes"
"compress/gzip"
"encoding/base64"
"flag"
"fmt"
"io/ioutil"
"log"
"mime"
"net/http"
"os"
"path"
"path/filepath"
"regexp"
"runtime"
"strings"
"time"
)
// AssetFile one ... |
// assetFiles asset files
type assetFiles struct {
Files map[string]*assetFile
}
var _assetDirect bool
var _assetCwd, _ = os.Getwd()
// GetAssetFile get file by name
func (afs *assetFiles) GetAssetFile(name string) (AssetFile, error) {
name = filepath.ToSlash(name)
if name != "" && name[0] != '/' {
name = "/" ... | random_line_split | |
Measurements.py | #!/usr/bin/env python
# encoding: utf-8
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version... | (related):
"""For related words found for a measurement (usually nouns), add any connected adjectives, compounds, or modifiers.
Args:
related (list): objects containing related words and their metadata
Returns:
list: original list of related objects augmented with additional descriptor wor... | _add_descriptors | identifier_name |
Measurements.py | #!/usr/bin/env python
# encoding: utf-8
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version... |
def _get_cousin(sibling_idx, dep_type_list, visited_nodes={}):
"""Find a second degree relation within the dependency graph.
Used to find subject in a sentence when the measurement unit is a direct object, for example.
Args:
sibling_idx (str): Token index of the sibling node through which to fin... | """If an edge connects to a node (word), return the index of the node
Args:
edge (tuple): Contains token indices of two connect words and the dependency type between them - e.g. ('11', '14', {'dep': 'nmod:at'})
idx (int): Token index of word
Returns:
str or None: str if connected word ... | identifier_body |
Measurements.py | #!/usr/bin/env python
# encoding: utf-8
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version... | "Not finding token index for Grobid Quantity value in CoreNLP output. Sentence: %s" % sentence)
return {}
if "rawUnit" in q[key]:
q[key]["rawUnit"]["after"] = a.lookup[q[key]["tokenIndex"]]["after"]
q[key]["rawUnit"]["t... | random_line_split | |
Measurements.py | #!/usr/bin/env python
# encoding: utf-8
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version... |
return simplified
def _reconstruct_sent(parsed_sentence):
"""Reconstruct sentence from CoreNLP tokens - raw sentence text isn't retained by CoreNLP after sentence splitting and processing
Args:
parsed_sentence (dict): Object containing CoreNLP output
Returns:
str: original sentence... | r["descriptors"].sort(key=lambda x: int(x["tokenIndex"]), reverse=False)
for z in r["descriptors"]:
simplified["related"][r["rawName"]].append(z["rawName"]) | conditional_block |
nsis.rs | // Copyright 2019-2023 Tauri Programme within The Commons Conservancy
// SPDX-License-Identifier: Apache-2.0
// SPDX-License-Identifier: MIT
#[cfg(target_os = "windows")]
use crate::bundle::windows::util::try_sign;
use crate::{
bundle::{
common::CommandExt,
windows::util::{
download, download_and_verif... | (settings: &Settings, updater: bool) -> crate::Result<Vec<PathBuf>> {
let tauri_tools_path = dirs_next::cache_dir().unwrap().join("tauri");
let nsis_toolset_path = tauri_tools_path.join("NSIS");
if !nsis_toolset_path.exists() {
get_and_extract_nsis(&nsis_toolset_path, &tauri_tools_path)?;
} else if NSIS_RE... | bundle_project | identifier_name |
nsis.rs | // Copyright 2019-2023 Tauri Programme within The Commons Conservancy
// SPDX-License-Identifier: Apache-2.0
// SPDX-License-Identifier: MIT
#[cfg(target_os = "windows")]
use crate::bundle::windows::util::try_sign;
use crate::{
bundle::{
common::CommandExt,
windows::util::{
download, download_and_verif... | rename(_tauri_tools_path.join("nsis-3.08"), nsis_toolset_path)?;
}
let nsis_plugins = nsis_toolset_path.join("Plugins");
let data = download(NSIS_APPLICATIONID_URL)?;
info!("extracting NSIS ApplicationID plugin");
extract_zip(&data, &nsis_plugins)?;
create_dir_all(nsis_plugins.join("x86-unicode"))?;
... | info!("extracting NSIS");
extract_zip(&data, _tauri_tools_path)?; | random_line_split |
nsis.rs | // Copyright 2019-2023 Tauri Programme within The Commons Conservancy
// SPDX-License-Identifier: Apache-2.0
// SPDX-License-Identifier: MIT
#[cfg(target_os = "windows")]
use crate::bundle::windows::util::try_sign;
use crate::{
bundle::{
common::CommandExt,
windows::util::{
download, download_and_verif... |
fn write_ut16_le_with_bom<P: AsRef<Path>>(path: P, content: &str) -> crate::Result<()> {
use std::fs::File;
use std::io::{BufWriter, Write};
let file = File::create(path)?;
let mut output = BufWriter::new(file);
output.write_all(&[0xFF, 0xFE])?; // the BOM part
for utf16 in content.encode_utf16() {
o... | {
if let Some(path) = custom_lang_files.and_then(|h| h.get(lang)) {
return Ok(Some((dunce::canonicalize(path)?, None)));
}
let lang_path = PathBuf::from(format!("{lang}.nsh"));
let lang_content = match lang.to_lowercase().as_str() {
"arabic" => Some(include_str!("./templates/nsis-languages/Arabic.nsh")... | identifier_body |
scheduler.go | /*
Copyright 2019 The Vitess Authors.
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 law or agreed to in writing, soft... |
delete(s.activeClusterOperations, clusterOp.Id)
s.finishedClusterOperations[clusterOp.Id] = clusterOp
}
func (s *Scheduler) runTask(taskProto *automationpb.Task, clusterOpID string) ([]*automationpb.TaskContainer, string, error) {
if taskProto.State == automationpb.TaskState_DONE {
// Task is already done (e.g. ... | {
panic("Pending ClusterOperation was not recorded as active, but should have.")
} | conditional_block |
scheduler.go | /*
Copyright 2019 The Vitess Authors.
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 law or agreed to in writing, soft... |
func (s *Scheduler) createTaskInstance(taskName string) (Task, error) {
s.taskCreatorMu.Lock()
taskCreator := s.taskCreator
s.taskCreatorMu.Unlock()
task := taskCreator(taskName)
if task == nil {
return nil, fmt.Errorf("no implementation found for: %v", taskName)
}
return task, nil
}
// validateParameters ... | {
taskInstanceForParametersCheck, err := s.createTaskInstance(taskName)
if err != nil {
return err
}
errParameters := validateParameters(taskInstanceForParametersCheck, parameters)
if errParameters != nil {
return errParameters
}
return nil
} | identifier_body |
scheduler.go | /*
Copyright 2019 The Vitess Authors.
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 law or agreed to in writing, soft... | // The scheduler may update the copy with the latest status.
activeClusterOperations map[string]ClusterOperationInstance
// Guarded by "muOpList".
// The key of the map is ClusterOperationInstance.ID.
finishedClusterOperations map[string]ClusterOperationInstance
}
// NewScheduler creates a new instance.
func NewS... | // The key of the map is ClusterOperationInstance.ID.
// This map contains a copy of the ClusterOperationInstance which is currently processed. | random_line_split |
scheduler.go | /*
Copyright 2019 The Vitess Authors.
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 law or agreed to in writing, soft... | () {
s.mu.Lock()
if s.state != stateShuttingDown {
s.state = stateShuttingDown
close(s.toBeScheduledClusterOperations)
}
s.mu.Unlock()
log.Infof("Scheduler was shut down. Waiting for pending ClusterOperations to finish.")
s.pendingOpsWg.Wait()
s.mu.Lock()
s.state = stateShutdown
s.mu.Unlock()
log.Infof(... | ShutdownAndWait | identifier_name |
index.js | import { defineHidden, FluidType, is, each, isFluidValue, createInterpolator, toArray, isEqual, Globals, needsInterpolation, useForceUpdate, useIsomorphicLayoutEffect } from '@react-spring/shared';
import _extends from '@babel/runtime/helpers/esm/extends';
import { deprecateInterpolate } from '@react-spring/shared/de... |
super.setValue(props.style && createAnimatedStyle ? _extends({}, props, {
style: createAnimatedStyle(props.style)
}) : props);
Animated.context = null;
}
/** @internal */
onParentChange() {
if (!this.dirty) {
this.dirty = true;
frameLoop.onFrame(() => {
th... | if (context) {
Animated.context = context;
}
| random_line_split |
index.js | import { defineHidden, FluidType, is, each, isFluidValue, createInterpolator, toArray, isEqual, Globals, needsInterpolation, useForceUpdate, useIsomorphicLayoutEffect } from '@react-spring/shared';
import _extends from '@babel/runtime/helpers/esm/extends';
import { deprecateInterpolate } from '@react-spring/shared/de... | () {
let value = this._string;
return value == null ? this._string = this._toString(this._value) : value;
}
setValue(value) {
if (!is$1.num(value)) {
this._string = value;
this._value = 1;
} else if (super.setValue(value)) {
this._string = null;
} else {
retu... | getValue | identifier_name |
index.js | import { defineHidden, FluidType, is, each, isFluidValue, createInterpolator, toArray, isEqual, Globals, needsInterpolation, useForceUpdate, useIsomorphicLayoutEffect } from '@react-spring/shared';
import _extends from '@babel/runtime/helpers/esm/extends';
import { deprecateInterpolate } from '@react-spring/shared/de... |
});
}
/** Reset our node and the nodes of every descendant */
_reset(goal) {
this.node.reset(!this.idle, goal);
each(this._children, observer => {
if (isAnimationValue(observer)) {
observer._reset(goal);
}
});
}
}
/** An object containing `Animated` node... | {
observer.onParentPriorityChange(priority, this);
} | conditional_block |
train.py | import argparse
import torch
import torch.nn as nn
import re
import numpy as np
import os
import pickle
from data_loader import get_loader
from data_loader import get_images
from build_vocab import Vocabulary
from model import EncoderCNN, DecoderRNN
from torch.autograd import Variable
from torch.nn.utils.rnn import ... |
def main(args):
# Create model directory
if not os.path.exists(args.model_path):
os.makedirs(args.model_path)
# Image preprocessing
# For normalization, see https://github.com/pytorch/vision#models
transform = transforms.Compose([
transforms.RandomCrop(args.crop_size),
... | if torch.cuda.is_available():
x = x.cuda()
return Variable(x, volatile=volatile) | identifier_body |
train.py | import argparse
import torch
import torch.nn as nn
import re
import numpy as np
import os
import pickle
from data_loader import get_loader
from data_loader import get_images
from build_vocab import Vocabulary
from model import EncoderCNN, DecoderRNN
from torch.autograd import Variable
from torch.nn.utils.rnn import ... |
for index,word in enumerate(words):
words[index] = vocab.word2idx[word]
rationalizations.append(words)
# max_length = max(rationalizations,key=len
rationalizations=[np.array(xi) for xi in rationalizations]
# for index,r in enumerate(rationalizations):
# # pr... | max_length = length | conditional_block |
train.py | import argparse
import torch
import torch.nn as nn
import re
import numpy as np
import os
import pickle
from data_loader import get_loader
from data_loader import get_images
from build_vocab import Vocabulary
from model import EncoderCNN, DecoderRNN
from torch.autograd import Variable
from torch.nn.utils.rnn import ... | new_lengths.reverse()
captions = captions
# print(captions)
# print(new_lengths)
targets = pack_padded_sequence(captions, new_lengths, batch_first=True)[0]
decoder.zero_grad()
encoder.zero_grad()
# print(images)
... | random_line_split | |
train.py | import argparse
import torch
import torch.nn as nn
import re
import numpy as np
import os
import pickle
from data_loader import get_loader
from data_loader import get_images
from build_vocab import Vocabulary
from model import EncoderCNN, DecoderRNN
from torch.autograd import Variable
from torch.nn.utils.rnn import ... | (x, volatile=False):
if torch.cuda.is_available():
x = x.cuda()
return Variable(x, volatile=volatile)
def main(args):
# Create model directory
if not os.path.exists(args.model_path):
os.makedirs(args.model_path)
# Image preprocessing
# For normalization, see https://git... | to_var | identifier_name |
tasks.py | """Define celery tasks for hs_core app."""
from __future__ import absolute_import
import os
import sys
import traceback
import zipfile
import logging
import json
from datetime import datetime, timedelta, date
from xml.etree import ElementTree
import requests
from celery import shared_task
from celer... |
@periodic_task(ignore_result=True, run_every=crontab(minute=0, hour=0))
def manage_task_nightly():
# The nightly running task do DOI activation check
# Check DOI activation on failed and pending resources and send email.
msg_lst = []
# retrieve all published resources with failed metadata d... | logger.info("added " + str(add_count) + " out of " + str(
active_subscribed.count()) + " for list id " + list_id) | conditional_block |
tasks.py | """Define celery tasks for hs_core app."""
from __future__ import absolute_import
import os
import sys
import traceback
import zipfile
import logging
import json
from datetime import datetime, timedelta, date
from xml.etree import ElementTree
import requests
from celery import shared_task
from celer... |
@shared_task
def add_zip_file_contents_to_resource(pk, zip_file_path):
"""Add zip file to existing resource and remove tmp zip file."""
zfile = None
resource = None
try:
resource = utils.get_resource_by_shortkey(pk, or_404=False)
zfile = zipfile.ZipFile(zip_file_path)
... | hs_internal_zone = "hydroshare"
if not QuotaMessage.objects.exists():
QuotaMessage.objects.create()
qmsg = QuotaMessage.objects.first()
users = User.objects.filter(is_active=True).filter(is_superuser=False).all()
for u in users:
uq = UserQuota.objects.filter(user__username=u.userna... | identifier_body |
tasks.py | """Define celery tasks for hs_core app."""
from __future__ import absolute_import
import os
import sys
import traceback
import zipfile
import logging
import json
from datetime import datetime, timedelta, date
from xml.etree import ElementTree
import requests
from celery import shared_task
from celer... | (pk, zip_file_path):
"""Add zip file to existing resource and remove tmp zip file."""
zfile = None
resource = None
try:
resource = utils.get_resource_by_shortkey(pk, or_404=False)
zfile = zipfile.ZipFile(zip_file_path)
num_files = len(zfile.infolist())
zcontents =... | add_zip_file_contents_to_resource | identifier_name |
tasks.py | """Define celery tasks for hs_core app."""
from __future__ import absolute_import
import os
import sys
import traceback
import zipfile
import logging
import json
from datetime import datetime, timedelta, date
from xml.etree import ElementTree
import requests
from celery import shared_task
from celer... | DOI_BATCH_ID=res.short_id,
TYPE='result'))
root = ElementTree.fromstring(response.content)
rec_cnt_elem = root.find('.//record_count')
failure_cnt_elem = root.find('.//failure_co... | USERNAME=settings.CROSSREF_LOGIN_ID,
PASSWORD=settings.CROSSREF_LOGIN_PWD,
| random_line_split |
controllers.js | angular.module('starter.controllers', [])
.controller('HomeCtrl', function($scope) {})
.controller('ChatsCtrl', function($scope, Chats) {
$scope.chats = Chats.all();
$scope.remove = function(chat) {
Chats.remove(chat);
};
})
.controller('PieChartCtrl', function($scope,$stateParams,$timeout,$rootScope,$ionic... | $scope.add={};
alert($scope.add.fname);
var id1=$scope.p[$scope.p.length-1].id+1;
var savep={
id: id1,
face: 'img/mike.png',
name: $scope.add.fname,
PatientID: '12556'+id1,
Age : $scope.add.fname,
message : 'Hi doctor',
date:'26/3/2017 3.20PM',
gender:'Male'
};
// Patients.s... |
$scope.done=function(){
$scope.p=Patients.all(); | random_line_split |
controllers.js | angular.module('starter.controllers', [])
.controller('HomeCtrl', function($scope) {})
.controller('ChatsCtrl', function($scope, Chats) {
$scope.chats = Chats.all();
$scope.remove = function(chat) {
Chats.remove(chat);
};
})
.controller('PieChartCtrl', function($scope,$stateParams,$timeout,$rootScope,$ionic... |
}
}
//iterate through contacts list and delete
//contact if found
this.delete = function (id) {
for (i in contacts) {
if (contacts[i].id == id) {
contacts.splice(i, 1);
}
}
}
//simply returns the contacts list
this.list... | {
return contacts[i];
} | conditional_block |
mamikon.js | (function () {
var body = document.querySelector('body');
//прелоадер >>>>>>>>>>>>>>>>>>>>>>*/
var preloader = document.querySelector('.loader');
//body.classList.add('overflow');
window.onload = function () {
window.setTimeout(function () {
preloader.classList.add('disable');
//document.body.classList.r... | estsElementClass(target, 'popup');
closePopup(popup);
bodyOverflow();
}
});
//Закрытие попапа при клике на escape (Esc)
body.addEventListener('keydown', function (e) {
if (e.keyCode !== 27)
return;
else {
var popup = document.querySelector('.popup.is-active');
closePopup(popup);
bodyOverflo... | up = clos | identifier_name |
mamikon.js | (function () {
var body = document.querySelector('body');
//прелоадер >>>>>>>>>>>>>>>>>>>>>>*/
var preloader = document.querySelector('.loader');
//body.classList.add('overflow');
window.onload = function () {
window.setTimeout(function () {
preloader.classList.add('disable');
//document.body.classList.r... | //Поиск названия data-popup, который задан у кнопки бургера
//var popupClass = target.getAttribute('data-popup');
var popupClass = closestsElementAttr(target, 'data-popup');
//если элемент, на котором кликнули, не имеет аттрибут data-popup, то выходим
if (popupClass === null) {
return;
}
e.preventDefa... | var target = e.target; | random_line_split |
mamikon.js | (function () {
var body = document.querySelector('body');
//прелоадер >>>>>>>>>>>>>>>>>>>>>>*/
var preloader = document.querySelector('.loader');
//body.classList.add('overflow');
window.onload = function () {
window.setTimeout(function () {
preloader.classList.add('disable');
//document.body.classList.r... | eturn;
}
e.preventDefault();
var popup = document.querySelector('.' + popupClass);
if (popup) {
showPopup(popup);
bodyOverflow();
}
})
//Закрытие попапа при клике X или на область вне попапа
body.addEventListener('click', function (e) {
var target = e.target;
//Если клик был на кнопку Х или фон ... | data-popup');
//если элемент, на котором кликнули, не имеет аттрибут data-popup, то выходим
if (popupClass === null) {
r | conditional_block |
mamikon.js | (function () {
var body = document.querySelector('body');
//прелоадер >>>>>>>>>>>>>>>>>>>>>>*/
var preloader = document.querySelector('.loader');
//body.classList.add('overflow');
window.onload = function () {
window.setTimeout(function () {
preloader.classList.add('disable');
//document.body.classList.r... | on changeSlideLeft() {
//activeSlide.classList.remove('active');
for (var i = slides.length - 1; i >= 0; i--) {
if (slides[i].classList.contains('active')) {
slides[i].classList.remove('active');
if (i > 0)
slides[--i].classList.add('active');
else
slides[slides.length - 1].classList.add('a... | iveSlide.classList.remove('active');
for (var i = 0; i < slides.length; i++) {
if (slides[i].classList.contains('active')) {
slides[i].classList.remove('active');
if (i < slides.length - 1)
slides[++i].classList.add('active');
else
slides[0].classList.add('active');
return;
}
}
}
... | identifier_body |
GameScene.ts | module wqq
{
import Vector2D = snake.Vector2;
export enum InGameEvent
{
kInGamePlayerRespawn = 30000,
kInGamePlayerPlayerDead = 30001,
kInGameEndlessRankPlayer = 30002
};
export class AnimationCurve
{
private m_keys:Array<number> = [];
private m_Values:Array<number> = [];
public constructor(){
}... | }
public GetTimeLeft():number
{
return 0;
}
public GetNameInfo(id:number):NameInfo
{
return this.allNames[id];
}
public Enter()
{
//SceneManager.GetInstance().ShowApp(AppModuleType.kAppInGameMainUI, false, false, false);
//SoundManager.GetInstance().PlayBackgroundMusic("sound/music/GameS... | date(deltaTime);
this.LateUpdate(deltaTime);
| conditional_block |
GameScene.ts | module wqq
{
import Vector2D = snake.Vector2;
export enum InGameEvent
{
kInGamePlayerRespawn = 30000,
kInGamePlayerPlayerDead = 30001,
kInGameEndlessRankPlayer = 30002
};
export class AnimationCurve
{
private m_keys:Array<number> = [];
private m_Values:Array<number> = [];
public constructor(){
}... | public AddNameInfo(name:NameInfo)
{
this.allNames[name.id] = name;
}
public SendSlitherCmd(targetDirection:Vector2D, accelarating:boolean)
{
}
public SetSlitherNameInfo(slither:Slither, id:number)
{
let info = this.allNames[id];
if (!info) {
return;
}
slither.SetName(info.name);... | let attr = (typeof name == "number")?"GetID":"GetName";
let size = this.m_AllSlithers.length;
for (let i = 0; i < size; ++i) {
let slither = this.m_AllSlithers[i];
if (slither[attr]() == name) {
return slither;
}
}
return null;
}
| identifier_body |
GameScene.ts | module wqq
{
import Vector2D = snake.Vector2;
export enum InGameEvent
{
kInGamePlayerRespawn = 30000,
kInGamePlayerPlayerDead = 30001,
kInGameEndlessRankPlayer = 30002
};
export class AnimationCurve
{
private m_keys:Array<number> = [];
private m_Values:Array<number> = [];
public constructor(){
}... | sg:RpcSlitherBirthDeathSync)
{
let foundPlayer = false;
let count = msg.slithers.length;
for (let i = 0; i < count; i++)
{
let info = msg.slithers[i];
let slither = this.FindSlither(info.id);
let isPlayer = info.id == this.m_PlayerID;
if (isPlayer) {
foundPlayer = true;
}
if ... | SlitherBirthDeathSync(m | identifier_name |
GameScene.ts | module wqq
{
import Vector2D = snake.Vector2;
export enum InGameEvent
{
kInGamePlayerRespawn = 30000,
kInGamePlayerPlayerDead = 30001,
kInGameEndlessRankPlayer = 30002
};
export class AnimationCurve
{
private m_keys:Array<number> = [];
private m_Values:Array<number> = [];
public constructor(){
}... |
this.DestroyAllSlithers();
let gameLayer = this;
gameLayer.removeChild(this.m_TileBackground);
gameLayer.removeChild(this.m_BeanView);
gameLayer.removeChild(this.m_FlyBeanContainer);
gameLayer.removeChild(this.m_SlitherContainer);
this.allNames = {};
this.m_TileBackground = null;
this.m_Be... | random_line_split | |
mod.rs | //! Abstraction over multiple versions of the file format allowed
//!
//! Because we want to continue to properly handle old config file formats - even when they'll no
//! longer be generated by default. In the future, we might provide some kind of feature-gating for
//! older versions, so that the dependencies associa... | /// An immutable handle on an entry in the file
pub trait EntryRef {
/// Returns the title of the entry
fn name(&self) -> &str;
/// Returns all the tags associated with the entry
fn tags(&self) -> Vec<&str>;
/// Returns the date + time at which the
fn first_added(&self) -> SystemTime;
///... | fn remove_entry(&mut self, idx: usize);
}
| random_line_split |
mod.rs | //! Abstraction over multiple versions of the file format allowed
//!
//! Because we want to continue to properly handle old config file formats - even when they'll no
//! longer be generated by default. In the future, we might provide some kind of feature-gating for
//! older versions, so that the dependencies associa... |
}
| {
PlaintextContent {
last_update: SystemTime::now(),
entries: Vec::new(),
}
} | identifier_body |
mod.rs | //! Abstraction over multiple versions of the file format allowed
//!
//! Because we want to continue to properly handle old config file formats - even when they'll no
//! longer be generated by default. In the future, we might provide some kind of feature-gating for
//! older versions, so that the dependencies associa... |
};
macro_rules! prefix_match {
($val:expr => { $($str:literal => $arm:expr,)* _ => $else_arm:expr, }) => {{
let v = $val;
$(if v.starts_with($str) {
$arm
} else)* {
$else_arm
}
}};
}
prefix_match!(content.... | {
eprintln!("failed to read file {:?}: {}", file.to_string_lossy(), e);
exit(1);
} | conditional_block |
mod.rs | //! Abstraction over multiple versions of the file format allowed
//!
//! Because we want to continue to properly handle old config file formats - even when they'll no
//! longer be generated by default. In the future, we might provide some kind of feature-gating for
//! older versions, so that the dependencies associa... | {
Basic,
Protected,
Totp,
}
impl Display for ValueKind {
fn fmt(&self, f: &mut Formatter) -> fmt::Result {
match self {
ValueKind::Basic => f.write_str("Basic"),
ValueKind::Protected => f.write_str("Protected"),
ValueKind::Totp => f.write_str("TOTP"),
... | ValueKind | identifier_name |
draw.js | var pickColor = (category) => {
if(category == "pup" || category == "weanling" || category == "yearling") {
return "#220C08"; //chocolate black
}
else if (category == "adult_female") {
return "#9B8576"; //tan
}
else if (category == "adult_male") {
return "#BC8D7D"; /... | .style("text-anchor", "middle")
.attr("transform", "translate(" + width/3 + ", " + height/2 + ")")
.text("Mid Bight Beach");
//bottom right text
svg.append("text")
.style("text-anchor", "middle")
.attr("transform", "translate(" + width*2/3 + ", " + height/2 + ")")... | .attr("transform", "translate(" + width*2/3 + ", " + height/12 + ")")
.text("Bight Beach North");
//bottom left text
svg.append("text")
| random_line_split |
draw.js | var pickColor = (category) => {
if(category == "pup" || category == "weanling" || category == "yearling") {
return "#220C08"; //chocolate black
}
else if (category == "adult_female") {
return "#9B8576"; //tan
}
else if (category == "adult_male") {
return "#BC8D7D"; /... | (old, location) {
let newData;
console.log("Fixing this data: ");
console.log(old);
//create new array where each element is an object with the seal type and where it is
newData = old.map( seal => {
return {type: seal, location: location};
});
return newData;
} | fixData | identifier_name |
draw.js | var pickColor = (category) => {
if(category == "pup" || category == "weanling" || category == "yearling") {
return "#220C08"; //chocolate black
}
else if (category == "adult_female") {
return "#9B8576"; //tan
}
else if (category == "adult_male") {
return "#BC8D7D"; /... |
}
// bubble cluster physics
// help from https://youtu.be/NTS7uXOxQeM
var forceX = d3.forceX( d => {
if(d.location == "North Point") { //North Point
return width*1/3;
}
else if(d.location == "Bight Beach North") { //Bight Beach North
return width*2/3;
... | {
circles
.attr("cx", d => d.x)
.attr("cy", d => d.y)
} | identifier_body |
draw.js | var pickColor = (category) => {
if(category == "pup" || category == "weanling" || category == "yearling") {
return "#220C08"; //chocolate black
}
else if (category == "adult_female") {
return "#9B8576"; //tan
}
else if (category == "adult_male") {
return "#BC8D7D"; /... |
else {//d.data[0].long > medianLong
return height*3/4;
}
})
.strength(0.1);
var simulation = d3.forceSimulation()
.force("x", forceX)
.force("y", forceY)
.force("collide", d3.forceCollide( d => pickSize(d.type) ));
//this function specifically exists to ... | {
return height/4;
} | conditional_block |
main.rs | extern crate petgraph;
extern crate rand;
extern crate time;
extern crate clap;
use std::cmp::{max, min};
use std::collections::HashSet;
use rand::Rng;
use time::PreciseTime;
enum Method {
Any,
All,
}
fn main() {
let matches = clap::App::new("square-sum")
.about("Calculates solutions to the squa... | (
g: &mut petgraph::Graph<(), (), petgraph::Undirected, usize>,
square_numbers: &[usize],
) {
let i = g.node_count() + 1;
g.add_node(());
for sq in square_numbers
.iter()
.skip_while(|&sq| sq <= &i)
.take_while(|&sq| sq <= &((i * 2) - 1))
{
let i_index = petgraph:... | add_square_sum_node | identifier_name |
main.rs | extern crate petgraph;
extern crate rand;
extern crate time;
extern crate clap;
use std::cmp::{max, min};
use std::collections::HashSet;
use rand::Rng;
use time::PreciseTime;
enum Method {
Any,
All,
}
fn main() {
let matches = clap::App::new("square-sum")
.about("Calculates solutions to the squa... |
fn push(&mut self, node_index: usize) {
self.path.push(node_index);
self.member[node_index] = true;
}
fn len(&self) -> usize {
self.path.len()
}
fn contains(&self, node_index: usize) -> bool {
self.member[node_index]
}
fn backtrack(&mut self, amount: usiz... | {
// TODO check that size >= seed.len()
let mut path = Vec::with_capacity(size);
let mut member = vec![false; size];
for i in seed.iter() {
path.push(i - 1);
member[*i - 1] = true;
}
Path { path, member }
} | identifier_body |
main.rs | extern crate petgraph;
extern crate rand;
extern crate time;
extern crate clap;
use std::cmp::{max, min};
use std::collections::HashSet;
use rand::Rng;
use time::PreciseTime;
enum Method {
Any,
All,
}
fn main() {
let matches = clap::App::new("square-sum")
.about("Calculates solutions to the squa... | fn reverse(&mut self) {
self.path.reverse();
}
fn iter(&self) -> std::slice::Iter<usize> {
self.path.iter()
}
}
fn setup_path<N, E, Ty>(g: &petgraph::Graph<N, E, Ty, usize>) -> Result<Path, &'static str>
where
Ty: petgraph::EdgeType,
{
let mut rng = rand::thread_rng();
let... | self.path.truncate(new_size);
}
| random_line_split |
_bev_qfz.py | import os
import smilPython as sm
import numpy as np
from pyntcloud import PyntCloud
from smutsia.point_cloud.projection import Projection, project_img, back_projection_ground
from smutsia.utils.image import np_2_smil, smil_2_np, label_with_measure | self.delta_ground = delta_ground
self.delta_h_circle = delta_h_circle
self.nl = nl
def find_min_z(zL, step):
# TODO: Ask Bea the reason why this function. Apparently minPercent is not used
# histogram of zL, step = 0.2. minZ is set to the value over 0
# with at maximum 5% of points... |
class LambdaGDParameters:
def __init__(self, my_lambda=2, delta_ground=0.2, delta_h_circle=0.5, nl=sm.HexSE()):
self.my_lambda = my_lambda | random_line_split |
_bev_qfz.py | import os
import smilPython as sm
import numpy as np
from pyntcloud import PyntCloud
from smutsia.point_cloud.projection import Projection, project_img, back_projection_ground
from smutsia.utils.image import np_2_smil, smil_2_np, label_with_measure
class LambdaGDParameters:
def __init__(self, my_lambda=2, delta_g... |
# for each distance to scanner, get the layer index
inverse_radius_index = {}
index = 0
# get the maximum index falling into the image
imsize = max(im.getHeight(), im.getWidth())
while imsize <= radius_index[index]:
index = index + 1
# for this index, get the corresponding radius... | radius_index[i] = radius | conditional_block |
_bev_qfz.py | import os
import smilPython as sm
import numpy as np
from pyntcloud import PyntCloud
from smutsia.point_cloud.projection import Projection, project_img, back_projection_ground
from smutsia.utils.image import np_2_smil, smil_2_np, label_with_measure
class LambdaGDParameters:
def __init__(self, my_lambda=2, delta_g... |
def get_scanner_xy(points, proj):
""" get x0,y0 coordinates of the scanner location """
# Find the pixel corresponding to (x=0,y=0)
res_x = proj.projector.res_x # 5 pixels / m, 1 px = 20 cm
res_y = proj.projector.res_y # 5 pixels / m , 1 px = 20 cm
min_x, min_y, min_z = points.min(0)
# t... | """im: as an input image just the size is important. As an output
image it contains the dart board
x0,y0,hScanner: scanner position
alpha0: first angle
res_x,res_y : spatial resolution of input image
nb_layers
The output draws a chess board according to the size of the each
"""
... | identifier_body |
_bev_qfz.py | import os
import smilPython as sm
import numpy as np
from pyntcloud import PyntCloud
from smutsia.point_cloud.projection import Projection, project_img, back_projection_ground
from smutsia.utils.image import np_2_smil, smil_2_np, label_with_measure
class LambdaGDParameters:
def __init__(self, my_lambda=2, delta_g... | (zL, step):
# TODO: Ask Bea the reason why this function. Apparently minPercent is not used
# histogram of zL, step = 0.2. minZ is set to the value over 0
# with at maximum 5% of points under it.
mybins = np.arange(np.amin(zL), np.amax(zL), step)
myhisto = np.histogram(zL, mybins)
mycount = myh... | find_min_z | identifier_name |
particle.py | '''
Water Wheel of Fortune
By Nathaniel Yearwood
Cody Macedo
'''
import pygame, sys
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import ode
import random as rand
import math
import threading
win_width = 800 # 500 cm = 5 m
win_height = 600
# set up the colors
BLACK = (0, 0, 0)
GREY... | event = pygame.event.poll()
if event.type == pygame.QUIT:
sys.exit(0)
elif event.type == pygame.KEYDOWN and event.key == pygame.K_q:
pygame.quit()
sys.exit(0)
elif event.type == pygame.KEYDOWN and event.key == pygame.K_p:
pause = not pause
... | while True:
# 30 fps
if not pause:
clock.tick(30)
| random_line_split |
particle.py | '''
Water Wheel of Fortune
By Nathaniel Yearwood
Cody Macedo
'''
import pygame, sys
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import ode
import random as rand
import math
import threading
win_width = 800 # 500 cm = 5 m
win_height = 600
# set up the colors
BLACK = (0, 0, 0)
GREY... |
if __name__ == '__main__':
main() | if not pause:
clock.tick(30)
event = pygame.event.poll()
if event.type == pygame.QUIT:
sys.exit(0)
elif event.type == pygame.KEYDOWN and event.key == pygame.K_q:
pygame.quit()
sys.exit(0)
elif event.type == pygame.KEYDOWN and event... | conditional_block |
particle.py | '''
Water Wheel of Fortune
By Nathaniel Yearwood
Cody Macedo
'''
import pygame, sys
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import ode
import random as rand
import math
import threading
win_width = 800 # 500 cm = 5 m
win_height = 600
# set up the colors
BLACK = (0, 0, 0)
GREY... |
def outside_screen(self, particle):
if (particle.state[0] < -particle.radius):
return False
elif (particle.state[0] > win_width + particle.radius):
return False
elif (particle.state[1] < -particle.radius):
return False
else:
return T... | self.particles = [x for x in self.particles if self.outside_screen(x)] | identifier_body |
particle.py | '''
Water Wheel of Fortune
By Nathaniel Yearwood
Cody Macedo
'''
import pygame, sys
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import ode
import random as rand
import math
import threading
win_width = 800 # 500 cm = 5 m
win_height = 600
# set up the colors
BLACK = (0, 0, 0)
GREY... | (self, imgfile, radius, mass=1.0):
particle = Particle(imgfile, radius, mass)
self.particles.append(particle)
return particle
def addWheel(self, centre, radius):
wheel = Wheel(centre, radius)
self.wheels.append(wheel)
return wheel
def pprint(self):
pri... | add | identifier_name |
peticiones_bitacora.js | $(document).ready(function () {
var vendedores = $("#vendedores");
//window.moment = require('moment');
var rangoFecha = $("#rangoFecha");
var MmensajeOrdenFecha = $('#MmensajeOrdenFecha');
var map;
//Para enviar la fecha Actual
var fechaActual = new Date();
var MesActual = fechaActual... | SeleccionarVendedor();
//GOOGLE MAPS
}); | //DESCRICION : Funcion que me obtiene la lista de rutas asignadas segun el vendedor seleccionado.
vendedores.change(function () {
var optionSelected = $(this).find("option:selected");
var valueSelected = optionSelected.val();
ListarBitacoras(valueSelected,... | identifier_body |
peticiones_bitacora.js | $(document).ready(function () {
var vendedores = $("#vendedores");
//window.moment = require('moment');
var rangoFecha = $("#rangoFecha");
var MmensajeOrdenFecha = $('#MmensajeOrdenFecha');
var map;
//Para enviar la fecha Actual
var fechaActual = new Date();
var MesActual = fechaActual... | ndedor, Mes, flagFiltro,fechaIncio,fechaFin) {
//DESCRICION : Funcion que me obtiene la lista de bitacoras
var json = JSON.stringify({
codVendedor: idVendedor,
fechaActual: Mes,
flagFiltro: flagFiltro,
fechaIncio: fechaIncio,
fe... | rBitacoras(idVe | identifier_name |
peticiones_bitacora.js | $(document).ready(function () {
var vendedores = $("#vendedores");
//window.moment = require('moment');
var rangoFecha = $("#rangoFecha");
var MmensajeOrdenFecha = $('#MmensajeOrdenFecha');
var map;
//Para enviar la fecha Actual
var fechaActual = new Date();
var MesActual = fechaActual... |
$.fn.dataTableExt.afnFiltering.push(
function(settings, data, dataIndex) {
var min = $('#min-date').val();
var minr = min.split('/').join('-');
var max = $('#max-date').val()
var maxr = max.split('/')... | replaceCli = data[i].cliente;
clientRuc = replaceCli.replace(/ /g, "");
if (clientRuc == "") {
clientRazonS = data[i].razonsocial;
}
else {
clientRazonS = data[i].cliente;
}
i... | conditional_block |
peticiones_bitacora.js | $(document).ready(function () {
var vendedores = $("#vendedores");
//window.moment = require('moment');
var rangoFecha = $("#rangoFecha");
var MmensajeOrdenFecha = $('#MmensajeOrdenFecha');
var map;
//Para enviar la fecha Actual
var fechaActual = new Date();
var MesActual = fechaActual... |
},
{
"width": "10%",
targets: [3],
},
{
"width": "2%",
targets: [5],
render: function (data) {
return moment(data).format('DD/MM/YYYY');
}
}],
... | "width": "5%",
targets: [3], | random_line_split |
lib.rs | mod utils;
use std::cell::RefCell;
use std::rc::Rc;
use wasm_bindgen::prelude::*;
use wasm_bindgen::JsCast;
use web_sys::{ImageData, WebGlProgram, WebGlRenderingContext, WebGlShader};
const WIDTH: i32 = 128;
const HEIGHT: i32 = 128;
const CHANNELS: i32 = 4;
const BUFFER_SIZE: usize = ((WIDTH * HEIGHT) * CHANNELS) as ... | else {
Err(context
.get_shader_info_log(&shader)
.unwrap_or_else(|| String::from("Unknown error creating shader")))
}
}
pub fn link_program(
context: &WebGlRenderingContext,
vert_shader: &WebGlShader,
frag_shader: &WebGlShader,
) -> Result<WebGlProgram, String> {
le... | {
Ok(shader)
} | conditional_block |
lib.rs | mod utils;
use std::cell::RefCell;
use std::rc::Rc;
use wasm_bindgen::prelude::*;
use wasm_bindgen::JsCast;
use web_sys::{ImageData, WebGlProgram, WebGlRenderingContext, WebGlShader};
const WIDTH: i32 = 128;
const HEIGHT: i32 = 128;
const CHANNELS: i32 = 4;
const BUFFER_SIZE: usize = ((WIDTH * HEIGHT) * CHANNELS) as ... | pub fn start() {
utils::set_panic_hook();
log!("Hello there! Compositor canvas starting/loading");
}
#[wasm_bindgen]
pub fn initialise(element_id: String) -> Result<(), JsValue> {
log!(
"Compositor canvas (element_id: String = `{}`) initialisation",
&element_id
);
let document = we... | .expect("should register `requestAnimationFrame` OK");
}
#[wasm_bindgen(start)] | random_line_split |
lib.rs | mod utils;
use std::cell::RefCell;
use std::rc::Rc;
use wasm_bindgen::prelude::*;
use wasm_bindgen::JsCast;
use web_sys::{ImageData, WebGlProgram, WebGlRenderingContext, WebGlShader};
const WIDTH: i32 = 128;
const HEIGHT: i32 = 128;
const CHANNELS: i32 = 4;
const BUFFER_SIZE: usize = ((WIDTH * HEIGHT) * CHANNELS) as ... | (
context: &WebGlRenderingContext,
shader_type: u32,
source: &str,
) -> Result<WebGlShader, String> {
let shader = context
.create_shader(shader_type)
.ok_or_else(|| String::from("Unable to create shader object"))?;
context.shader_source(&shader, source);
context.compile_shader(&... | compile_shader | identifier_name |
lib.rs | mod utils;
use std::cell::RefCell;
use std::rc::Rc;
use wasm_bindgen::prelude::*;
use wasm_bindgen::JsCast;
use web_sys::{ImageData, WebGlProgram, WebGlRenderingContext, WebGlShader};
const WIDTH: i32 = 128;
const HEIGHT: i32 = 128;
const CHANNELS: i32 = 4;
const BUFFER_SIZE: usize = ((WIDTH * HEIGHT) * CHANNELS) as ... |
#[wasm_bindgen(start)]
pub fn start() {
utils::set_panic_hook();
log!("Hello there! Compositor canvas starting/loading");
}
#[wasm_bindgen]
pub fn initialise(element_id: String) -> Result<(), JsValue> {
log!(
"Compositor canvas (element_id: String = `{}`) initialisation",
&element_id
... | {
window()
.request_animation_frame(f.as_ref().unchecked_ref())
.expect("should register `requestAnimationFrame` OK");
} | identifier_body |
async_stream_cdc.rs | //
// Copyright (c) 2023 Nathan Fiedler
//
use super::*;
#[cfg(all(feature = "futures", not(feature = "tokio")))]
use futures::{
io::{AsyncRead, AsyncReadExt},
stream::Stream,
};
#[cfg(all(feature = "tokio", not(feature = "futures")))]
use tokio_stream::Stream;
#[cfg(all(feature = "tokio", not(feature = "fu... | () {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 64, 255, 1024);
}
#[test]
#[should_panic]
fn test_average_too_high() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 64, 268_435_457, 1024);
}
#[test]
#[should_panic]
fn... | test_average_too_low | identifier_name |
async_stream_cdc.rs | //
// Copyright (c) 2023 Nathan Fiedler
//
use super::*;
#[cfg(all(feature = "futures", not(feature = "tokio")))]
use futures::{
io::{AsyncRead, AsyncReadExt},
stream::Stream,
};
#[cfg(all(feature = "tokio", not(feature = "futures")))]
use tokio_stream::Stream;
#[cfg(all(feature = "tokio", not(feature = "fu... |
}
Ok(all_bytes_read)
}
}
/// Drains a specified number of bytes from the buffer, then resizes the
/// buffer back to `capacity` size in preparation for further reads.
fn drain_bytes(&mut self, count: usize) -> Result<Vec<u8>, Error> {
// this code originally cop... | {
self.length += bytes_read;
all_bytes_read += bytes_read;
} | conditional_block |
async_stream_cdc.rs | //
// Copyright (c) 2023 Nathan Fiedler
//
use super::*;
#[cfg(all(feature = "futures", not(feature = "tokio")))]
use futures::{
io::{AsyncRead, AsyncReadExt},
stream::Stream,
};
#[cfg(all(feature = "tokio", not(feature = "futures")))]
use tokio_stream::Stream;
#[cfg(all(feature = "tokio", not(feature = "fu... | max_size: usize,
mask_s: u64,
mask_l: u64,
mask_s_ls: u64,
mask_l_ls: u64,
}
impl<R: AsyncRead + Unpin> AsyncStreamCDC<R> {
///
/// Construct a `StreamCDC` that will process bytes from the given source.
///
/// Uses chunk size normalization level 1 by default.
///
pub fn new... | /// True when the source produces no more data.
eof: bool,
min_size: usize,
avg_size: usize, | random_line_split |
run_mlm_my.py | import logging
import os
from dataclasses import dataclass, field
from typing import Optional
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
AutoTokenizer,
HfArgumentParser,
Trainer,
TrainingArguments,
set_seed,
)
from transformers... | :
"""
Arguments pertaining to which model/config/tokenizer we are going to fine-tune, or train from scratch.
"""
model_name_or_path: Optional[str] = field(
default=None,
metadata={
"help": "The model checkpoint for weights initialization."
"Don't set if you want ... | ModelArguments | identifier_name |
run_mlm_my.py | import logging
import os
from dataclasses import dataclass, field
from typing import Optional
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
AutoTokenizer,
HfArgumentParser,
Trainer,
TrainingArguments,
set_seed,
)
from transformers... | revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
)
else:
logger.info("Training new model from scratch")
model = PairWiseBertForPreTraining.from_config(config)
model.resize_token_embeddings(len(tokenizer))
# Get ... | model_args.model_name_or_path,
from_tf=bool(".ckpt" in model_args.model_name_or_path),
config=config,
cache_dir=model_args.cache_dir, | random_line_split |
run_mlm_my.py | import logging
import os
from dataclasses import dataclass, field
from typing import Optional
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
AutoTokenizer,
HfArgumentParser,
Trainer,
TrainingArguments,
set_seed,
)
from transformers... |
if model_args.model_name_or_path:
model = PairWiseBertForPreTraining.from_pretrained(
model_args.model_name_or_path,
from_tf=bool(".ckpt" in model_args.model_name_or_path),
config=config,
cache_dir=model_args.cache_dir,
revision=model_args.model_r... | raise ValueError(
"You are instantiating a new tokenizer from scratch. This is not supported by this script."
"You can do it from another script, save it, and load it from here, using --tokenizer_name."
) | conditional_block |
run_mlm_my.py | import logging
import os
from dataclasses import dataclass, field
from typing import Optional
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
AutoTokenizer,
HfArgumentParser,
Trainer,
TrainingArguments,
set_seed,
)
from transformers... |
@dataclass
class DataTrainingArguments:
"""
Arguments pertaining to what data we are going to input our model for training and eval.
"""
dataset_name: Optional[str] = field(
default=None, metadata={"help": "The name of the dataset to use (via the datasets library)."}
)
dataset_config... | """
Arguments pertaining to which model/config/tokenizer we are going to fine-tune, or train from scratch.
"""
model_name_or_path: Optional[str] = field(
default=None,
metadata={
"help": "The model checkpoint for weights initialization."
"Don't set if you want to tra... | identifier_body |
titanic_keras_exp.py | """Evaluate Keras Classifiers and learn from the Titanic data set."""
from sklearn.model_selection import StratifiedKFold
from sklearn.pipeline import Pipeline
from sklearn.dummy import DummyClassifier
from pandas import read_csv
# from pandas.plotting import scatter_matrix
import matplotlib.pyplot as plt
import nump... |
print()
print()
input("Press key to continue...")
preprocessing = (encoding, scaler_tuple, featselector)
if labels is not None:
print("You have labels:", labels)
all_models_and_parameters['labels'] = labels
print("Defined dictionary with models... | print("'%s' is quicker than DummyClf." % best_model_name) | conditional_block |
titanic_keras_exp.py | """Evaluate Keras Classifiers and learn from the Titanic data set."""
from sklearn.model_selection import StratifiedKFold
from sklearn.pipeline import Pipeline
from sklearn.dummy import DummyClassifier
from pandas import read_csv
# from pandas.plotting import scatter_matrix
import matplotlib.pyplot as plt
import nump... | # Feature-Feature Relationships
# scatter_matrix(df)
print()
# too many missing values in 'Cabin' columns: about 3/4
print("Dropping 'Cabin' column -- too many missing values")
# df.Cabin.replace(to_replace=np.nan, value='Unknown', inplace=True)
df.drop(['Cabin'], axis=1, inplace=True)
... | plt.style.use('ggplot')
# input("Enter key to continue... \n")
| random_line_split |
titanic_keras_exp.py | """Evaluate Keras Classifiers and learn from the Titanic data set."""
from sklearn.model_selection import StratifiedKFold
from sklearn.pipeline import Pipeline
from sklearn.dummy import DummyClassifier
from pandas import read_csv
# from pandas.plotting import scatter_matrix
import matplotlib.pyplot as plt
import nump... | ():
is_valid = 0
choice = 0
while not is_valid:
try:
choice = int(input("Select cv method: [1] Classical CV, [2] Nested-CV?\n"))
if choice in (1, 2):
is_valid = 1
else:
print("Invalid number. Try again...")
except ValueErr... | select_cv_method | identifier_name |
titanic_keras_exp.py | """Evaluate Keras Classifiers and learn from the Titanic data set."""
from sklearn.model_selection import StratifiedKFold
from sklearn.pipeline import Pipeline
from sklearn.dummy import DummyClassifier
from pandas import read_csv
# from pandas.plotting import scatter_matrix
import matplotlib.pyplot as plt
import nump... |
# starting program
if __name__ == '__main__':
print("### Probability Calibration Experiment -- CalibratedClassifierCV "
"with cv=cv (no prefit) ###")
print()
d_name = ga.get_name()
if d_name is None:
d_name = "titanic"
# fix random seed for reproducibility
seed = 7
n... | is_valid = 0
choice = 0
while not is_valid:
try:
choice = int(input("Select cv method: [1] Classical CV, [2] Nested-CV?\n"))
if choice in (1, 2):
is_valid = 1
else:
print("Invalid number. Try again...")
except ValueError as e:
... | identifier_body |
AUTO_ASSAM_PART3.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#A program to parse user.LP
import itertools, sys, os, subprocess, shutil, glob, numpy as np, re, collections, operator, datetime, optparse, csv
#import Bio
trans = {'ALA':'A','CYS':'C','CYH':'C','CSS':'C','ASP':'D','GLU':'E','PHE':'F','GLY':'G','HIS':'H','ILE':'I','LYS':'K... | ():
pdbs_to_edit = [i for i in glob.glob("BINDING_SITES_CLUSTERS/*.pdb")]
pdbs_to_edit2 = [[i]+[i.split("/")[-1].split("_")[0].lower()] for i in pdbs_to_edit]
d_dct = collections.defaultdict(list)
for n in pdbs_to_edit2: d_dct[n[1]].append(n[0])
keys = sorted([key for key in d_dct.keys()])
for key in keys:
for ... | rename_pdb_dbs | identifier_name |
AUTO_ASSAM_PART3.py | #A program to parse user.LP
import itertools, sys, os, subprocess, shutil, glob, numpy as np, re, collections, operator, datetime, optparse, csv
#import Bio
trans = {'ALA':'A','CYS':'C','CYH':'C','CSS':'C','ASP':'D','GLU':'E','PHE':'F','GLY':'G','HIS':'H','ILE':'I','LYS':'K','LEU':'L','MET':'M','ASN':'N','PRO':'P','GLN... | #!/usr/bin/env python
# -*- coding: utf-8 -*- | random_line_split | |
AUTO_ASSAM_PART3.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#A program to parse user.LP
import itertools, sys, os, subprocess, shutil, glob, numpy as np, re, collections, operator, datetime, optparse, csv
#import Bio
trans = {'ALA':'A','CYS':'C','CYH':'C','CSS':'C','ASP':'D','GLU':'E','PHE':'F','GLY':'G','HIS':'H','ILE':'I','LYS':'K... |
else: het_res = ";".join(het_resx)
else: het_res = "None"
else: het_res = "None"
return het_res
#BINDING_INTERFACES_ASSAM
def save_output_binding_interfaces_assam():
pdb_dict=collections.defaultdict(list)
pdb_new_dict=collections.defaultdict(list)
pdbs_all=[["_".join(i.split("/")[-1].split("_")[:3]).upper()... | het_res = "None" | conditional_block |
AUTO_ASSAM_PART3.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#A program to parse user.LP
import itertools, sys, os, subprocess, shutil, glob, numpy as np, re, collections, operator, datetime, optparse, csv
#import Bio
trans = {'ALA':'A','CYS':'C','CYH':'C','CSS':'C','ASP':'D','GLU':'E','PHE':'F','GLY':'G','HIS':'H','ILE':'I','LYS':'K... |
#BINDING_INTERFACES_EXACT
def binding_interfaces_exact():
csv_readerx=csv.reader(open("BINDING_INTERFACES_CLUSTERS.csv","r"),delimiter=",")
rowsx=[[row[0]]+[row[8]] for row in csv_readerx]
dreposer_id_dict=collections.defaultdict(list)
for r in rowsx: dreposer_id_dict[r[0]].append(len(r[1].split(";")))
csv_re... | pdb_dict=collections.defaultdict(list)
pdb_new_dict=collections.defaultdict(list)
pdbs_all=[["_".join(i.split("/")[-1].split("_")[:3]).upper()]+[i.split("/")[-1].replace(".pdb","")] for i in glob.glob("renew_bs_finalized/*.pdb")]
for pdb in pdbs_all: pdb_dict[pdb[0]].append(pdb[1])
for k in pdb_dict.keys():
for i... | identifier_body |
town.py | ###########################################
""" Town manager """
# Imports
import os
import time
import items
import storyline
import classes
# Functions
def shop_inventory():
pass
def ultimate(player):
texts = [
"Oh my...can it possibly be?...the legendary ore...Unobtainium?\n",
"I can\'t... |
time.sleep(1)
os.system('cls' if os.name == 'nt' else 'clear')
def town(player, wmap):
os.system('cls' if os.name == 'nt' else 'clear')
locations = [blacksmith, armory, alchemist, jeweler, church, tavern]
town_options = [('Blacksmith', 0), ('Armory', 1), ('Alchemist', 2), ('Jeweler', 3), ... | print("Please enter a valid option.") | conditional_block |
town.py | ###########################################
""" Town manager """
# Imports
import os
import time
import items
import storyline
import classes
# Functions
def shop_inventory():
pass
def ultimate(player):
texts = [
"Oh my...can it possibly be?...the legendary ore...Unobtainium?\n",
"I can\'t... | else:
locations[town_index](player)
os.system('cls' if os.name == 'nt' else 'clear') | player.status()
elif town_options[town_index][0] == 'Church':
locations[town_index](player, wmap) | random_line_split |
town.py | ###########################################
""" Town manager """
# Imports
import os
import time
import items
import storyline
import classes
# Functions
def shop_inventory():
pass
def ultimate(player):
texts = [
"Oh my...can it possibly be?...the legendary ore...Unobtainium?\n",
"I can\'t... |
def jeweler(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "Come glimpse the finest jewelry in the land."
buy_list = [('Accessory', 0)]
shop(player, buy_list, shop_text)
def tavern(player):
"""
Quests
"""
print("Sorry but we are closed for construction. Come b... | os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "Welcome to Ye Olde Item Shoppe."
buy_list = [('Potion', 0), ('Misc', 1)]
shop(player, buy_list, shop_text) | identifier_body |
town.py | ###########################################
""" Town manager """
# Imports
import os
import time
import items
import storyline
import classes
# Functions
def shop_inventory():
pass
def ultimate(player):
texts = [
"Oh my...can it possibly be?...the legendary ore...Unobtainium?\n",
"I can\'t... | (player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "I have the finest armors for sale. Come in and look around."
buy_list = [('Armor', 0)]
shop(player, buy_list, shop_text)
def alchemist(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "Welcome to Ye Ol... | armory | identifier_name |
impl_encryption.rs | // Copyright 2019 TiKV Project Authors. Licensed under Apache-2.0.
use openssl::hash::{self, MessageDigest};
use tidb_query_codegen::rpn_fn;
use tidb_query_datatype::expr::{Error, EvalContext};
use tidb_query_common::Result;
use tidb_query_datatype::codec::data_type::*;
use tidb_query_shared_expr::rand::{gen_random_... | KV", "*cca644408381f962dba8dfb9889db1371ee74208"),
("Pingcap", "*f33bc75eac70ac317621fbbfa560d6251c43cf8a"),
("rust", "*090c2b08e0c1776910e777b917c2185be6554c2e"),
("database", "*02e86b4af5219d0ba6c974908aea62d42eb7da24"),
("raft", "*b23a77787ed44e62ef2570f03ce8982d119fb6... | identifier_body | |
impl_encryption.rs | // Copyright 2019 TiKV Project Authors. Licensed under Apache-2.0.
use openssl::hash::{self, MessageDigest};
use tidb_query_codegen::rpn_fn;
use tidb_query_datatype::expr::{Error, EvalContext};
use tidb_query_common::Result;
use tidb_query_datatype::codec::data_type::*;
use tidb_query_shared_expr::rand::{gen_random_... | (b"abc".to_vec(), "900150983cd24fb0d6963f7d28e17f72"),
(b"123".to_vec(), "202cb962ac59075b964b07152d234b70"),
(
"你好".as_bytes().to_vec(),
"7eca689f0d3389d9dea66ae112e5cfd7",
),
(
"分布式データベース".as_bytes().to_vec(),
... | (vec![], "d41d8cd98f00b204e9800998ecf8427e"),
(b"a".to_vec(), "0cc175b9c0f1b6a831c399e269772661"),
(b"ab".to_vec(), "187ef4436122d1cc2f40dc2b92f0eba0"), | random_line_split |
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