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@leddoo
leddoo / reg_vm.rs
Created December 29, 2022 11:03
a very simple register vm
// a very minimal instruction set.
// it has just enough operations to implement a recursive
// fibonacci function - what a coincidence :D
// NOTE: in my VM, i don't use an `enum`.
// this is just for simplicity.
#[derive(Clone, Copy, Debug)]
enum Instruction {
LoadInt { dst: u8, value: i16 },
Copy { dst: u8, src: u8 },
Add { dst: u8, src1: u8, src2: u8 },
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@bogdan-kulynych
bogdan-kulynych / install-cuda-10-bionic.sh
Last active December 5, 2023 10:26
Install CUDA 10 on Ubuntu 18.04
# WARNING: These steps seem to not work anymore!
#!/bin/bash
# Purge existign CUDA first
sudo apt --purge remove "cublas*" "cuda*"
sudo apt --purge remove "nvidia*"
# Install CUDA Toolkit 10
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.0.130-1_amd64.deb
@goldsborough
goldsborough / conv.cu
Last active November 27, 2023 05:59
Convolution with cuDNN
#include <cudnn.h>
#include <cassert>
#include <cstdlib>
#include <iostream>
#include <opencv2/opencv.hpp>
#define checkCUDNN(expression) \
{ \
cudnnStatus_t status = (expression); \
if (status != CUDNN_STATUS_SUCCESS) { \
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@jaanli
jaanli / black_box_vi_bayesian_linear_regression.py
Created February 11, 2017 17:32
Black box variational inference for Bayesian linear regression. Numpy and scipy only.
"""Use black-box variational inference (https://arxiv.org/abs/1401.0118) to
fit Bayesian linear regression (https://en.wikipedia.org/wiki/Bayesian_linear_regression)
and ensure it gets the analytic posterior mean from wikipedia.
"""
import numpy as np
import scipy.stats
def generate_data(cfg):
"""synthetic data:
@siemanko
siemanko / tf_lstm.py
Last active July 26, 2023 06:57
Simple implementation of LSTM in Tensorflow in 50 lines (+ 130 lines of data generation and comments)
"""Short and sweet LSTM implementation in Tensorflow.
Motivation:
When Tensorflow was released, adding RNNs was a bit of a hack - it required
building separate graphs for every number of timesteps and was a bit obscure
to use. Since then TF devs added things like `dynamic_rnn`, `scan` and `map_fn`.
Currently the APIs are decent, but all the tutorials that I am aware of are not
making the best use of the new APIs.
Advantages of this implementation:
@twiecki
twiecki / bayesian_neural_network.ipynb
Last active February 22, 2022 01:28
Bayesian Neural Network in PyMC3
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@parmentf
parmentf / GitCommitEmoji.md
Last active April 26, 2024 09:53
Git Commit message Emoji
@danoneata
danoneata / visitor.py
Created November 19, 2015 23:41
Visitor pattern in Python
class Expr(object):
def accept(self, visitor):
method_name = 'visit_{}'.format(self.__class__.__name__.lower())
visit = getattr(visitor, method_name)
return visit(self)
class Int(Expr):
def __init__(self, value):
self.value = value