jjallaire

env/
__pycache__/
*-app.py
*_files/
*.html

jjallaire

library(keras)
library(reticulate)

layer_multiplicative_lstm <-function(
  object, units, activation = "tanh", recurrent_activation = "hard_sigmoid", use_bias = TRUE, 
  return_sequences = FALSE, return_state = FALSE, go_backwards = FALSE, stateful = FALSE, unroll = FALSE,
  kernel_initializer = "glorot_uniform", recurrent_initializer = "orthogonal", bias_initializer = "zeros", 
  unit_forget_bias = TRUE, kernel_regularizer = NULL, recurrent_regularizer = NULL, bias_regularizer = NULL, 

jjallaire

from keras.models import Model
from keras import layers
from keras import Input
text_vocabulary_size = 10000
question_vocabulary_size = 10000
answer_vocabulary_size = 500


text_input = Input(shape=(None,), dtype='int32', name='text')
embedded_text = layers.Embedding(

jjallaire

'''Train MNIST with tfrecords yielded from a TF Dataset

In order to run this example you should first run 'mnist_to_tfrecord.py'
which will download MNIST data and serialize it into 3 tfrecords files
(train.tfrecords, validation.tfrecords, and test.tfrecords).

This example demonstrates the use of TF Datasets wrapped by a generator
function. The example currently only works with a fork of keras that accepts
`workers=0` as an argument to fit_generator, etc. Passing `workers=0` results
in the generator function being run on the main thread (without this various

jjallaire

---
title: "Untitled"
output: 
  revealjs::revealjs_presentation:
    css: styles.css
---

## R Markdown

This is an R Markdown presentation. Markdown is a simple formatting syntax for authoring HTML, PDF,

jjallaire

---
title: "Untitled"
output: revealjs::revealjs_presentation
---

## R Markdown

This is an R Markdown presentation. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see <http://rmarkdown.rstudio.com>.

When you click the **Knit** button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document.

jjallaire

#include <Rcpp.h>
using namespace Rcpp;

// [[Rcpp::export]]
CharacterVector asUTF8(CharacterVector x) {
    const void *vmax = vmaxget();
    CharacterVector xUTF8(x.length());
    for (int i = 0; i<x.length(); i++) {
        const char* utf8 = Rf_translateCharUTF8(x[i]);
        xUTF8[i] = Rf_mkCharCE(utf8, CE_UTF8);

jjallaire

#include <Rcpp.h>
using namespace Rcpp;

void finalizeInt(int* ptr) {
    // do nothing
}

typedef XPtr<int,PreserveStorage,finalizeInt> XPtrInt;

// [[Rcpp::export]]

jjallaire

#include <Rcpp.h>
using namespace Rcpp;

// [[Rcpp::depends(BH)]]
#include <boost/bind.hpp>
#include <boost/function.hpp>

typedef boost::function<int(int,int)> Combiner;

int add(int x, int y) {

jjallaire

#include <Rcpp.h>
using namespace Rcpp;

using namespace Rcpp;
class Uniform {
public:
    Uniform(double min_, double max_) : min(min_), max(max_) {}
    NumericVector draw(int n) const {
        RNGScope scope;
        return runif( n, min, max );