thepulkitagarwal

# using Droid Sans Mono Nerd Font
# POWERLEVEL9K CONFIG

ZSH_THEME="powerlevel9k/powerlevel9k"
POWERLEVEL9K_MODE='awesome-fontconfig'

POWERLEVEL9K_PYTHON_ICON=''
POWERLEVEL9K_ANACONDA_BACKGROUND='cyan'

POWERLEVEL9K_DIR_HOME_BACKGROUND="blue"

thepulkitagarwal

import java.util.*;
import java.lang.reflect.*;

public class Class1 {
    public int x;
    
    public Class1() {
        // Default Constructor
    }
    

thepulkitagarwal

In this article, I will share some of my experience on installing NVIDIA driver and CUDA on Linux OS. Here I mainly use Ubuntu as example. Comments for CentOS/Fedora are also provided as much as I can.

Table of Contents

• Install NVIDIA Graphics Driver via apt-get
• Install NVIDIA Graphics Driver via runfile
  • Remove Previous Installations (Important)
  • Download the Driver
  • Install Dependencies
  • Creat Blacklist for Nouveau Driver

• Stop lightdm/gdm/kdm

thepulkitagarwal

def print_graph_nodes(filename):
    import tensorflow as tf
    g = tf.GraphDef()
    g.ParseFromString(open(filename, 'rb').read())
    print()
    print(filename)
    print("=======================INPUT=========================")
    print([n for n in g.node if n.name.find('input') != -1])
    print("=======================OUTPUT========================")
    print([n for n in g.node if n.name.find('output') != -1])

thepulkitagarwal

# This was created with @warptime's help. Thank you!

from tensorflow.python.framework import graph_util
from tensorflow.python.framework import graph_io
from keras.models import load_model
from keras import backend as K
import os.path as osp

model = load_model(path_to_model)
nb_classes = 1 # The number of output nodes in the model

thepulkitagarwal

import org.tensorflow.contrib.android.TensorFlowInferenceInterface;

/** One time initialization: */
TensorFlowInferenceInterface tensorflow = new TensorFlowInferenceInterface(getAssets(), "file:///android_asset/model.pb");

/** Continuous inference (floats used in example, can be any primitive): */

// loading new input
tensorflow.feed("input:0", input, INPUT_SHAPE); // INPUT_SHAPE is an long[] of expected shape, input is a float[] with the input data

thepulkitagarwal

sudo add-apt-repository ppa:git-core/ppa
sudo apt-get update
sudo apt-get install git
git --version

thepulkitagarwal

// AGGRCOW
// Aggressive cows

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

#define ll int64_t
#define MAX 1e5

void aggrcow() {

thepulkitagarwal

from fractions import gcd

def addToList(denominators, q):
	if(q in denominators):
		addToList(denominators, q+1)
		addToList(denominators, q*(q+1))
	else:
		denominators.append(q)

def breakIntoFractions(denominators, p, q):

thepulkitagarwal

maxFloorsDictionary = {}

def findMaxFloors(numberOfEggs, numberOfSteps):
	tupleEggsSteps = (numberOfEggs, numberOfSteps)
	if (numberOfEggs == 1 or numberOfSteps == 1):
		return numberOfSteps
	elif tupleEggsSteps in maxFloorsDictionary:
		return maxFloorsDictionary[tupleEggsSteps]
	else:
		maxFloorsDictionary[tupleEggsSteps] = findMaxFloors(numberOfEggs, numberOfSteps - 1) + findMaxFloors(numberOfEggs - 1, numberOfSteps - 1) + 1