thepurpleowl

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thepurpleowl

# Written by Doug Dahms
#
# Prints the tree structure for the path specified on the command line

from os import listdir, sep
from os.path import abspath, basename, isdir
from sys import argv

def tree(dir, padding, print_files=False):
    print (padding[:-1] + '+-' + basename(abspath(dir)) + '/')

thepurpleowl

#include <iostream>
#include <map>
#include <utility>
using namespace std;

/*
Internally map and set are almost always stored as red-black trees. We do not need to worry about the internal structure, 
the thing to remember is that the elements of map and set are always sorted in ascending order 
while traversing these containers. And that’s why it’s strongly not recommended to change the key value while traversing map or set: If you make the modification that breaks the order, it will lead to improper functionality of container’s algorithms, at least.
*/

thepurpleowl

val a = 4
var b = 3

// if-else
val greater_4: Boolean = a>b
if(!greater_4)
  val asquared = a*a
  asquared*2
else
  val bsquared = b*b

thepurpleowl

#include <iostream>
using namespace std;

struct node{
	int val;
	struct node *right, *left;
};

struct node *createNode(int item){
	struct node *temp = (struct node *)malloc(sizeof(struct node));

thepurpleowl

// #include <iostream>
#include <bits/stdc++.h>
using namespace std;

bool cmp(pair<int,int> a, pair<int,int> b){
	return a.second> b.second;
}

void find_w(map<int,int> m){
	vector<pair<int,int>> arr;

thepurpleowl

# Written by thepurpleowl
#
# Filter out files while retaining the directory structure

import os
import json
from shutil import copyfile
import pathlib

# dev__manifest contains path information of unfiltered files

thepurpleowl

import tensorflow as tf
from tensorflow.python.tools.inspect_checkpoint import print_tensors_in_checkpoint_file
import re

latest_ckp = tf.train.latest_checkpoint('./training_checkpoints')
print_tensors_in_checkpoint_file(latest_ckp, all_tensors=True, tensor_name='')

# to check specific variable in checkpoint
# [print(var.variables) for var in tf.train.list_variables(latest_ckp) if re.match(r'.*decoder/embedding/embeddings/.ATTRIBUTES/.*',var[0])]

thepurpleowl

import numpy as np
import tensorboard as tb
from torch.utils.tensorboard import SummaryWriter
import tensorflow as tf
tf.io.gfile = tb.compat.tensorflow_stub.io.gfile

writer = SummaryWriter()
writer.add_embedding(<embeddings>, <labels>)  # (doc_vector, Y_true[:TRAIN_SIZE_EVALS[-3]])
writer.close()
%load_ext tensorboard