greed2411

"""
Python script to find the memory allocations 
    i. over a module/function that is running
    ii. between the loops

It is a script so that it can be torn apart for your own use-cases.

Based on this nice article on trying to find memory leaks in python:
https://www.fugue.co/blog/diagnosing-and-fixing-memory-leaks-in-python.html
But the code is non-existent and isn't reproducible as of 2023.

greed2411

//===================================================================
// File: circular_buffer.cpp
//
// Desc: A Circular Buffer implementation in C++.
//
// Copyright © 2019 Edwin Cloud. All rights reserved.
//
//===================================================================

//-------------------------------------------------------------------

greed2411

//===================================================================
// File: circular_buffer.cpp
//
// Desc: A Circular Buffer implementation in C++.
//
// Copyright © 2019 Edwin Cloud. All rights reserved.
//
//===================================================================

//-------------------------------------------------------------------

greed2411

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greed2411

"""
Want to generate sorted random numbers optimally? Here you go.

Traditionally if you wanted a list of sorted random numbers,
you generate `n` random numbers and then sort them. which at worst
case has:

    Time Complexity : O(n log n) # for generating & sorting.
    Space Complexity: O(n)       # for storing all of them in array/set.

greed2411

"""
This gist comes out of frustration that I couldn't have a 
random-int-without-replacement-generator-given-a-range.

random.sample, and np.random.choice(replace=False) both fail on really large numbers. 
Python crashes saying OOM & segfaults.

Problem was for smaller `n` (<5 million) they optimized for linear/sub-linear
times and linear storage (set, pool-tracking list). 

greed2411

"""
Trying to find a way to handle channels-like situations (producer->consumer) in Python
using asyncio.Queue.

borrowed code actually from:
https://web.archive.org/web/20210507031446/https://asyncio.readthedocs.io/en/latest/producer_consumer.html
"""

import asyncio
import random

greed2411

greed2411

from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.utils.np_utils import to_categorical

from keras.models import Sequential
from keras.layers.embeddings import Embedding
from keras.layers.core import Dense, Dropout
from keras.layers import LSTM
from keras.regularizers import l2
from keras.optimizers import Adam

greed2411

Updated 4/11/2018

Here's my experience of installing the NVIDIA CUDA kit 9.0 on a fresh install of Ubuntu Desktop 16.04.4 LTS.

Table of Contents

• Install NVIDIA Graphics Driver via apt-get
• Install CUDA
• Install cuDNN

Table of contents generated with markdown-toc