gavincangan

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

gavincangan

from tensorflow.python.client import device_lib

def get_available_gpus():
    local_device_protos = device_lib.list_local_devices()
    return [x.name for x in local_device_protos if x.device_type == 'GPU']

get_available_gpus()

gavincangan

# 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,

gavincangan

import tensorflow as tf

def beam_decoder(decoder_inputs, initial_state, cell, loop_function, scope=None,
                 beam_size=7, done_token=0
                ):
    """
    Beam search decoder
    
    Args:
      decoder_inputs: A list of 2D Tensors [batch_size x input_size].

gavincangan

import time
import math

def find_fact(num, cur_quot=[]):
    ix = 3
    if(num < 2):
        return cur_quot
    while(ix < math.sqrt(num)):
        if(num % ix == 0):
            cur_quot.append(ix)

gavincangan

#!/bin/bash

cpp_file_to_build=$1
output_file=$(pwd)/${cpp_file_to_build/\.cpp/\.o}

rename_output_file=$(pwd)/zz_${cpp_file_to_build/\.cpp/\.o}ld

mv $output_file $rename_output_file

g++ -std=gnu++11 -Wall $cpp_file_to_build -o $output_file;

gavincangan

# Check for open ports in a range
for i in $(seq 20 99); do netcat -v -n -z -w 1 192.168.5.$i 22; done

# Windows - show WiFi password
netsh wlan show profile name=”<Profile-Name>” key=clear

# Windows - show all devices in network
arp -a

# Convert images or other files to pdf using ImageMagick

gavincangan

Keybase proof

I hereby claim:

• I am gavincangan on github.
• I am bgavin (https://keybase.io/bgavin) on keybase.
• I have a public key ASAzVotPWrTux92cdLLsndyYfpkLiCaj9vofPyQzC1yAFQo

To claim this, I am signing this object:

gavincangan

/*
 * Source: https://stackoverflow.com/questions/8401777/simple-glob-in-c-on-unix-system
 */

#include <glob.h> // glob(), globfree()
#include <string.h> // memset()
#include <vector>
#include <stdexcept>
#include <string>
#include <sstream>

gavincangan

% https://stats.stackexchange.com/a/394487/204863

clear; close all;

num_points  = 100;
xrange = [-100, 100];
x = xrange(1) + 2 * xrange(2) * rand(num_points, 1);

yrange = [0, 20];
y = yrange(1) + 2 * yrange(2) * rand(num_points, 1);