Kareem Abdelsalam karimamd

## basic html notes queue
<!DOCTYPE html>
<html>
<head>
	<title>Note Taking App</title>
</head>
<body>
	<h1>Note Taking App</h1>

	<div id="note">
		<h2 id="note-title">Note Title</h2>

## graph pb to tflite (Command line)
!toco \
  --graph_def_file=output_graph.pb \
  --output_file=xd_graph.tflite \
  --output_format=TFLITE \
  --input_shape=32,256,192,3 \
  --input_array= NAME OF INPUT MODEL OF YOUR MODEL \
  --output_array=  NAME OF OUTPUT LAYER OF YOUR MODEL \
  --inference_type=FLOAT \
  --inference_input_type=FLOAT \

## Download IMDB dataset into google colab and extract files
!rm -rf datalab
!wget http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz
!ls
!uncompress aclImdb_v1.tar.gz
!tar -xvf aclImdb_v1.tar
!rm aclImdb_v1.tar
!ls


## Cparser.c
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <assert.h>

char** str_split(char* a_str, const char a_delim)
{
    char** result    = 0;
    size_t count     = 0;
    char* tmp        = a_str;
	<!DOCTYPE html>
	<html>
	<head>
	<title>Note Taking App</title>
	</head>
	<body>
	<h1>Note Taking App</h1>

	<div id="note">
	<h2 id="note-title">Note Title</h2>
	!toco \
	--graph_def_file=output_graph.pb \
	--output_file=xd_graph.tflite \
	--output_format=TFLITE \
	--input_shape=32,256,192,3 \
	--input_array= NAME OF INPUT MODEL OF YOUR MODEL \
	--output_array= NAME OF OUTPUT LAYER OF YOUR MODEL \
	--inference_type=FLOAT \
	--inference_input_type=FLOAT \
	!rm -rf datalab
	!wget http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz
	!ls
	!uncompress aclImdb_v1.tar.gz
	!tar -xvf aclImdb_v1.tar
	!rm aclImdb_v1.tar
	!ls
	#include <stdio.h>
	#include <stdlib.h>
	#include <string.h>
	#include <assert.h>

	char** str_split(char* a_str, const char a_delim)
	{
	char** result = 0;
	size_t count = 0;
	char* tmp = a_str;