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FQA

Visualization

Cannot Save Image

If you run the script via SSH control, sometime you may find the following error.

_tkinter.TclError: no display name and no $DISPLAY environment variable

If happen, add the following code into the top of visualize.py.

import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt

Install Master Version

To use all new features of TensorLayer, you need to install the master version from Github. Before that, you need to make sure you already installed git.

[stable version] pip install tensorlayer
[master version] pip install git+https://github.com/zsdonghao/tensorlayer.git

Editable Mode

    1. Download the TensorLayer folder from Github.
    1. Before editing the TensorLayer .py file.
  • If your script and TensorLayer folder are in the same folder, when you edit the .py inside TensorLayer folder, your script can access the new features.
  • If your script and TensorLayer folder are not in the same folder, you need to run the following command in the folder contains setup.py before you edit .py inside TensorLayer folder.
pip install -e .

Load Model

Note that, the tl.files.load_npz() can only able to load the npz model saved by tl.files.save_npz(). If you have a model want to load into your TensorLayer network, you can first assign your parameters into a list in order, then use tl.files.assign_params() to load the parameters into your TensorLayer model.

Recruitment

TensorLayer Contributors

TensorLayer contributors are from Imperial College, Tsinghua University, Carnegie Mellon University, Microsoft and etc.

There are many functions need to be contributed such as Maxout, Neural Turing Machine, Attention, TensorLayer Mobile and etc. Please push on GitHub, every bit helps and will be credited.

If you are interested in working with us, please contact us.

Data Science Institute, Imperial College London

Data science is therefore by nature at the core of all modern transdisciplinary scientific activities, as it involves the whole life cycle of data, from acquisition and exploration to analysis and communication of the results. Data science is not only concerned with the tools and methods to obtain, manage and analyse data: it is also about extracting value from data and translating it from asset to product.

Launched on 1st April 2014, the Data Science Institute at Imperial College London aims to enhance Imperial’s excellence in data-driven research across its faculties by fulfilling the following objectives.

The Data Science Institute is housed in purpose built facilities in the heart of the Imperial College campus in South Kensington. Such a central location provides excellent access to collabroators across the College and across London.

  • To act as a focal point for coordinating data science research at Imperial College by facilitating access to funding, engaging with global partners, and stimulating cross-disciplinary collaboration.
  • To develop data management and analysis technologies and services for supporting data driven research in the College.
  • To promote the training and education of the new generation of data scientist by developing and coordinating new degree courses, and conducting public outreach programmes on data science.
  • To advise College on data strategy and policy by providing world-class data science expertise.
  • To enable the translation of data science innovation by close collaboration with industry and supporting commercialization.

If you are interested in working with us, please check our vacancies and other ways to get involved , or feel free to contact us.