<commit_before>---
layout: post-no-feature
title: Iterating over variable-length sequences
description: "RNNs using the TIMIT dataset"
categories: articles
comments: true
public: false
date: 2014-03-17
---

Lately I've been working on enabling Pylearn2 to iterate over variable-length
sequences. In this post, I'll discuss my progress so far.

### The problem

Some types of models (such as convolutional or recurrent neural nets) naturally
deal with variable-length inputs. Unfortunately, for the moment, this type of
input is not well supported in Pylearn2: ...

Even more fundamentally, there is no straightforward way to represent data
structures containing variable-length elements in Theano. This means even if we
solve the `Space` problem in Pylearn2, ...

### New spaces<commit_msg>Post not public for now<commit_after>---
layout: post-no-feature
title: Iterating over variable-length sequences
description: "RNNs using the TIMIT dataset"
categories: articles
comments: true
published: false
date: 2014-03-17
---

Lately I've been working on enabling Pylearn2 to iterate over variable-length
sequences. In this post, I'll discuss my progress so far.

### The problem

Some types of models (such as convolutional or recurrent neural nets) naturally
deal with variable-length inputs. Unfortunately, for the moment, this type of
input is not well supported in Pylearn2: ...

Even more fundamentally, there is no straightforward way to represent data
structures containing variable-length elements in Theano. This means even if we
solve the `Space` problem in Pylearn2, ...

### New spaces
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