{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/blocks-and-fuel-frameworks-for-deep-learning","title":"Blocks and Fuel: Frameworks for deep learning","arxiv_id":"1506.00619","date":"2015-06-01","proceeding":null,"authors":["Bart van Merriënboer","Dzmitry Bahdanau","Vincent Dumoulin","Dmitriy Serdyuk","David Warde-Farley","Jan Chorowski","Yoshua Bengio"],"abstract":"We introduce two Python frameworks to train neural networks on large\ndatasets: Blocks and Fuel. Blocks is based on Theano, a linear algebra compiler\nwith CUDA-support. It facilitates the training of complex neural network models\nby providing parametrized Theano operations, attaching metadata to Theano's\nsymbolic computational graph, and providing an extensive set of utilities to\nassist training the networks, e.g. training algorithms, logging, monitoring,\nvisualization, and serialization. Fuel provides a standard format for machine\nlearning datasets. It allows the user to easily iterate over large datasets,\nperforming many types of pre-processing on the fly.","url_abs":"http://arxiv.org/abs/1506.00619v1","url_pdf":"http://arxiv.org/pdf/1506.00619v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"blocks-and-fuel-frameworks-for-deep-learning","repo_url":"https://github.com/mdsufz/PredicTF","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"blocks-and-fuel-frameworks-for-deep-learning","repo_url":"https://github.com/mila-iqia/blocks","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"blocks-and-fuel-frameworks-for-deep-learning","repo_url":"https://github.com/mila-iqia/fuel","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"blocks-and-fuel-frameworks-for-deep-learning","repo_url":"https://github.com/mila-udem/blocks","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"blocks-and-fuel-frameworks-for-deep-learning","repo_url":"https://github.com/mila-udem/fuel","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"},{"task_slug":"deep-learning","task_name":"Deep Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}