Edward

Troubleshooting

Edward depends on

Installing edward by default also installs numpy and six if they are unavailable (or out-of-date).

Installing edward does not automatically install or update TensorFlow. We recommend installing it via

pip install tensorflow

To use Edward with GPUs, install tensorflow-gpu instead of tensorflow as

pip install tensorflow-gpu

See TensorFlow’s installation instructions for details, including how to set up NVIDIA software for TensorFlow with GPUs.

Edward has optional features that depend on external packages.

Any examples using real data sets typically require Observations (>=0.1.2)
```
pip install observations
```
Observations lets you load an extensive collection of data sets with minimal effort under a one-line interface. Observations was originally developed for Edward and it has since become a standalone library for general machine learning.
Neural networks are supported through any library operating on TensorFlow. For example: tf.layers, Keras (>=1.0)
```
pip install keras==2.0.4
```
and TensorFlow Slim (native in TensorFlow).

Note that for Keras 2.0.5 and beyond, all neural net layer transformations cannot be directly applied on random variables anymore. For example, if x is a ed.RandomVariable object, one must call tf.convert_to_tensor before applying it to a layer transformation, Dense(256)(tf.convert_to_tensor(x)). See here for more details.
Notebooks require Jupyter (>=1.0.0)
```
pip install jupyter
```
Visualization requires Matplotlib (>=1.3), Pillow (>=3.4.2), and Seaborn (>=0.3.1)
```
pip install matplotlib
pip install pillow
pip install seaborn
```