JonathanRaiman

// clang++ openmp.cpp -o openmp -fopenmp -O3 -std=c+11

#include <cassert>
#include <stdlib.h>
#include <cmath>
#include <omp.h>
#include <iostream>

template<typename T>
struct Vector {

JonathanRaiman

#ifndef RTC_ARRAY_H
#define RTC_ARRAY_H

#include <vector>
#include <string>
#include <memory>
#include <sstream>
#include <iostream>

#define XINLINE __device__ __host__

JonathanRaiman

/*
Comparing explicit BLAS parallelism using a thread pool
with vendor-implemented parallelism.

Program prints the runtime averaged over 100 runs of a matrix
multiply between two float matrices.

To run:

./gemm_parallel [<int> USE_EXPLICIT_PARALELLISM 0/1] [<int> LEADING_DIMENSION]

JonathanRaiman

def listify(x):
    if isinstance(x, tuple):
        return list(x)
    return x
    
def awesome_scan(fn, elems, initializer=None, parallel_iterations=10, back_prop=True,
         swap_memory=False, name=None):
  """scan on the list of tensors unpacked from `elems` on dimension 0.
  This scan operator repeatedly applies the callable `fn` to a sequence
  of elements from first to last. The elements are made of the tensors

JonathanRaiman

#include <vector>
#include <string>
#include <memory>
#include <sstream>
#include <iostream>

#define XINLINE __device__ __host__
#define MAX_DIM 10
#define INDENT_INCREMENT 2

JonathanRaiman

/*
Reduction over all dimensions in mshadow. Requires changing the structs in
mshadow expression to store their input expressions by value instead of
reference.

Installation:

nvcc some_file.cu -std=c++11 -O3 -w -o some_file -I /usr/local/include

Usage:

JonathanRaiman

#ifndef DALI_MATH_MSHADOW_EIGEN_DOT_H
#define DALI_MATH_MSHADOW_EIGEN_DOT_H
#if MSHADOW_USE_EIGEN_DOT
#include <Eigen/Eigen>
#include <mshadow/tensor.h>
#include <cblas.h>

// Eigen Backend for Dot-Product in Mshadow
// Causes Adagrad to be slower.

JonathanRaiman

#!/bin/bash

# stop script on error and print it
set -e
# inform me of undefined variables
set -u
# handle cascading failures well
set -o pipefail

# install homebrew

JonathanRaiman

import matplotlib.pyplot as plt
import theano, theano.tensor as T, numpy as np
import theano_lstm
import os
from collections import Counter

to_softmax = lambda x: T.nnet.softmax(x)[0] if x.ndim == 1 else T.nnet.softmax(x.T).T
class LatticeModel(object):
    def __init__(self,
                 word_size,

JonathanRaiman

import sqlite3
import pickle

protocol = 0
sqlite3.register_converter("pickle", pickle.loads)
sqlite3.register_adapter(list, pickle.dumps)
sqlite3.register_adapter(set, pickle.dumps)