deep_complex_networks-master_复数域神经网络_

Deep Complex Networks ===================== This repository contains code which reproduces experiments presented in the paper [Deep Complex Networks](https://arxiv.org/abs/1705.09792). Requirements ------------ Install requirements for computer vision experiments with pip: ``` pip install numpy Theano keras kerosene ``` And for music experiments: ``` pip install scipy sklearn intervaltree resampy pip install git+git://github.com/bartvm/mimir.git ``` Depending on your Python installation you might want to use anaconda or other tools. Installation ------------ ``` pip install . ``` Experiments ----------- ### Computer vision 1. Get help: ``` python scripts/run.py train --help ``` 2. Run models: ``` python scripts/run.py train -w WORKDIR --model {real,complex} --sf STARTFILTER --nb NUMBEROFBLOCKSPERSTAGE ``` Other arguments may be added as well; Refer to run.py train --help for - Optimizer settings - Dropout rate - Clipping - ... ### MusicNet 0. Download the dataset from [the official page](https://homes.cs.washington.edu/~thickstn/musicnet.html) ``` mkdir data/ wget https://homes.cs.washington.edu/~thickstn/media/musicnet.npz -P data/ ``` 1. Resample the dataset with ``` resample.py data/musicnet.npz data/musicnet_11khz.npz 44100 11000 ``` 2. Run shallow models ``` train.py shallow_model --in-memory --model=shallow_convnet --local-data data/musicnet_11khz.npz train.py shallow_complex_model --in-memory --model=complex_shallow_convnet --complex --local-data data/musicnet_11khz.npz ``` 3. Run deep models ``` train.py deep_model --in-memory --model=deep_convnet --fourier --local-data data/musicnet_11khz.npz train.py deep_complex_model --in-memory --model=complex_deep_convnet --fourier --complex --local-data data/musicnet_11khz.npz ``` 4. Visualize with jupyter notebook Run the notebook `notebooks/visualize_musicnet.ipynb`.   Citation -------- Please cite our work as ``` @ARTICLE {, author = "Chiheb Trabelsi, Olexa Bilaniuk, Ying Zhang, Dmitriy Serdyuk, Sandeep Subramanian, João Felipe Santos, Soroush Mehri, Negar Rostamzadeh, Yoshua Bengio, Christopher J Pal", title = "Deep Complex Networks", journal = "arXiv preprint arXiv:1705.09792", year = "2017" } ```