Merge pull request #2 from gugarosa/gugarosa/rework

gugarosa/rework

.travis.yml

@@ -1,11 +1,14 @@
+dist: xenial
 language: python
 python:
   - "3.6"
+  - "3.7"
+  - "3.8-dev"
   # PyPy versions
   - "pypy3.5"
 # command to install dependencies
 install:
   - pip install -r requirements.txt
   - pip install .
 # command to run tests
-script: pytest
+script: pytest

README.md

@@ -40,32 +40,40 @@ NALP is based on the following structure, and you should pay attention to its tr
 ```
 - nalp
     - core
+        - corpus
         - dataset
         - encoder
-        - neural
+    - corpus
+        - audio
+        - document
+        - text
     - datasets
-        - one_hot
-        - vanilla
+        - next
     - encoders
         - count
+        - integer
         - tfidf
         - word2vec
-    - neurals
+    - models
+        - gru
+        - lstm
         - rnn
-    - stream
-        - loader
-        - preprocess
+    - neurals
+        - complex
+        - simple
     - utils
-        - decorators
+        - loader
         - logging
-        - math
-        - splitters
-    - visualization
+        - preprocess
 ```
 
 ### Core
 
-Core is the core. Essentially, it is the parent of everything. You should find parent classes defining the basis of our structure. They should provide variables and methods that will help to construct other modules. It is composed of the following classes:
+The core is the core. Essentially, it is the parent of everything. You should find parent classes defining the basis of our structure. They should provide variables and methods that will help to construct other modules.
+
+### Corpus
+
+Every pipeline has its first step, right? The corpus package serves as a basic class to load raw text, documents (list of sentences), and audio.
 
 ### Datasets
 
@@ -75,22 +83,18 @@ Because we need data, right? Datasets are composed of classes and methods that a
 
 Text or Numbers? Encodings are used to make embeddings. Embeddings are used to feed into neural networks. Remember that networks cannot read raw data; therefore, you might want to pre-encode your data using well-known encoders.
 
-### Neurals
+### Models
 
-A neural networks package. In this package, you can find all neural-related implementations. From naïve RNNs to BiLSTMs, you can use whatever suits your needs. All implementations were done using raw Tensorflow, mainly to understand better and control the whole training and inference process.
+Each neural network architecture is defined in this package. From naïve RNNs to BiLSTMs, you can use whatever suits your needs.
 
-### Stream
+### Neurals
 
-A stream package is used to manipulate data. From loading to processing, here you can find all classes and methods defined in order to help you achieve these tasks.
+The neurals package provides simple or complex implementations using Tensorflow. You can choose straightforward examples using the Simple class or more advanced customization methods using the Complex class.
 
 ### Utils
 
 This is a utility package. Common things shared across the application should be implemented here. It is better to implement once and use as you wish than re-implementing the same thing over and over again.
 
-### Visualization
-
-A visualization package illustrates what is happening with your data. Use classes and methods to help you decide if your data is well enough to fulfill your desires.
-
 ---
 
 ## Installation

data/document/chapter1_harry.txt

@@ -0,0 +1,18 @@
+Mr. and Mrs. Dursley, of number four, Privet Drive, were proud to say that they were perfectly normal, thank you very much.
+They were the last people you'd expect to be involved in anything strange or mysterious, because they just didn't hold with such nonsense.
+Mr. Dursley was the director of a firm called Grunnings, which made drills.
+He was a big, beefy man with hardly any neck, although he did have a very large mustache.
+Mrs. Dursley was thin and blonde and had nearly twice the usual amount of neck, which came in very useful as she spent so much of her time craning over garden fences, spying on the neighbors.
+The Dursleys had a small son called Dudley and in their opinion there was no finer boy anywhere.
+The Dursleys had everything they wanted, but they also had a secret, and their greatest fear was that somebody would discover it.
+They didn't think they could bear it if anyone found out about the Potters.
+Mrs. Potter was Mrs. Dursley's sister, but they hadn't met for several years; in fact, Mrs. Dursley pretended she didn't have a sister, because her sister and her good-for-nothing husband were as unDursleyish as it was possible to be.
+The Dursleys shuddered to think what the neighbors would say if the Potters arrived in the street.
+The Dursleys knew that the Potters had a small son, too, but they had never even seen him.
+This boy was another good reason for keeping the Potters away; they didn't want Dudley mixing with a child like that.
+When Mr. and Mrs. Dursley woke up on the dull, gray Tuesday our story starts, there was nothing about the cloudy sky outside to suggest that strange and mysterious things would soon be happening all over the country.
+Mr. Dursley hummed as he picked out his most boring tie for work, and Mrs. Dursley gossiped away happily as she wrestled a screaming Dudley into his high chair.
+None of them noticed a large, tawny owl flutter past the window.
+At half past eight, Mr. Dursley picked up his briefcase, pecked Mrs. Dursley on the cheek, and tried to kiss Dudley good-bye but missed, because Dudley was now having a tantrum and throwing his cereal at the walls.
+"Little tyke," chortled Mr. Dursley as he left the house.
+He got into his car and backed out of number four's drive.