/* * Programming introduction with the SOD Embedded Recurrent Neural Networks (RNN) API. * Copyright (C) PixLab | Symisc Systems, https://sod.pixlab.io */ /* * Compile this file together with the SOD embedded source code to generate * the executable. For example: * * gcc sod.c rnn_text_gen.c -lm -Ofast -march=native -Wall -std=c99 -o sod_rnn * * Under Microsoft Visual Studio (>= 2015), just drop `sod.c` and its accompanying * header files on your source tree and you're done. If you have any trouble * integrating SOD in your project, please submit a support request at: * https://sod.pixlab.io/support.html */ /* * This simple program is a quick introduction on how to embed and start * experimenting with SOD without having to do a lot of tedious * reading and configuration. * * Make sure you have the latest release of SOD from: * https://pixlab.io/downloads * The SOD Embedded C/C++ documentation is available at: * https://sod.pixlab.io/api.html */ #include #include "sod.h" /* RNN text generation (i.e. Kant, Shakespeare, Tolstoy, Python code, 4 Chan, etc.) depending * on the pre-trained model. */ static void text_consumer_callback( const char *zText, /* Text ready to be consumed (always nil terminated) */ size_t text_len, /* zText[] length */ void *pUserdata /* Arbitrary user pointer passed verbatim by the RNN layer */ ) { /* * This is the callback that is called by the RNN * each time a generated text is ready * to be consumed. See below on how to install * this callback. */ puts(zText); /* Simply redirect the generated text to stdout */ } int main(int argc, char *argv[]) { /* * Path to the pre-trained RNN model where the generated text is based on. * You can download pre-trained RNN models on https://pixlab.io/downloads. */ const char *zRnnModel = argc > 1 ? argv[1] : "./tolstoy-rnn.sod"; /* * The RNN (although named sod_cnn) handle that should perform text generation for us */ sod_cnn *pNet; int rc; const char *zErr; /* Error log if any */ /* * Create our RNN handle using the built-in `rnn` * architecture and associate the desired pre-trained * model with it. */ rc = sod_cnn_create(&pNet, ":rnn", zRnnModel, &zErr); /* * ":rnn" is the magic word for the built-in RNN * architecture. The list of built-in Magic words (pre-ready to use * configurations and their associated models) are documented here: * https://sod.pixlab.io/c_api/sod_cnn_create.html. */ if (rc != SOD_OK) { /* Display the error message and exit */ puts(zErr); return 0; } /* Register the text consumer callback */ sod_cnn_config(pNet, SOD_RNN_CALLBACK, text_consumer_callback, 0 /* user data (NULL) */); /* Generate a text of length 500 characters */ sod_cnn_config(pNet, SOD_RNN_TEXT_LENGTH, 500); /* Seed for the text */ sod_cnn_config(pNet, SOD_RNN_SEED, "@>"); /* * Start the text generation process. The consumer callback * should redirect the generated text to STDOUT. */ sod_cnn_predict(pNet, 0, 0, 0); /* * At this stage, text_consumer_callback() should have been called * and the generated text already consumed. */ /* Clean-up */ sod_cnn_destroy(pNet); return 0; }