In Keras documentation, glorot_uniform says that the initializer is using Glorot Uniform from this paper. However, the Keras implementation is totally different from the equation on the paper. Also, there are some arguments such as mode ='fan_avg' is the default. It should be same as the referenced paper. 'fan_sum'. Golort uniform is shown

Hi, is there any plan to provide a tutorial of showing an example of employing the Transformer as an alternative of RNN for seq2seq task such as machine translation?

I was going though the existing enhancement issues again and though it'd be nice to collect ideas for spaCy plugins and related projects. There are always people in the community who are looking for new things to build, so here's some inspiration ✨ For existing plugins and projects, check out the spaCy universe.

If you have questions about the projects I suggested,

And what packages you have to install to use them

I did run following ones as the installation guide.

git clone https://github.com/lengstrom/fast-style-transfer.git
cd fast-style-transfer

pyenv local 2.7.9

pip2.7 install --upgrade pip
pip2.7 install virtualenv
python2.7 -m virtualenv dev
source dev/bin/activate

cat << 'EOT' > requirements.txt
tensorflow==0.11.0
Pillow==3.4.2
scipy==0.18.1
numpy==1.11.2
EOT

sudo apt

This is an awesome library, thanks @ddbourgin!!

Users might not know the best way to install this package and try it out. (I didn't, so I eventually just copied the source files.)
Neither the readme nor readthedocs have install instructions.

I couldn't find it on PyPi or Anaconda, and there doesn't appear to be a pyproject.toml, setup.cfg, setup.py, or conda recipe.

Moreover, the t

In the Ray Design Agents documentation the Ray Perception parameter Ray Layer Mask is not mentioned. I am a bit confused about what does it do and if it interacts with the Detectable Tags parameter.

![Screenshot from 2020-04-12 18-57-18](https://user-images.githubusercontent.com/3236037

it is really great code , only how to run it
MLAlgorithms/mla/fm.py
may you add example , as you did for other models?

Upon environment timeout python client will only receive the error message "Environment in wrong status for call to observations()". Might be good to provide more information why the environment is not running anymore (due to timeout etc.)

if (!is_running(self)) {
  PyErr_SetString(PyExc_RuntimeError,
  "Environment in wrong status for call to observations()");
  return NULL;
}

Sphinx (2.2.1 or master) produces the following two kinds of warnings in my environment.

duplicate object description

I think cross refs to such object is ambiguous.

autosummary: stub file not found

There are

• chainer.dataset.Converter base class and
• chainer.dataset.converter decorator.

Therefore the filesystem has to allow to store `chainer.dataset.Conver

Sample on front page:

const model = new KerasJS.Model({
  filepaths: {

filepaths in plural.
code for Model:

if (!filepath) {
      throw new Error('[Model] path to protobuf-serialized model definition file is missing.')
    }

I've noticed that there are a lot more tutorials/examples around VI
but less around sampling. I thought I might write up some of the sampling
examples as notebooks and add a sampling example for bayesian nets.

Is this something that would be helpful?

Python : 3.7.4
OS : Mac OSX 10.14.3
Bug : 'OSError' object has no attribute 'message' when using sample method
Solution : message is deprecated in latest Python version. One must use msg while catching such exceptions

When passing a two-dimensional input layer to LSTMLayer, it will break with an uninterpretable error message:

>>> lasagne.layers.LSTMLayer((10, 20), 30)
[...]
TypeError: 'numpy.float64' object cannot be interpreted as an index

The reason is that np.prod(()) returns 1.0 as a numpy.float64 instance when computing num_units: https://github.com/Lasagne/Lasagne/blob/master/lasagne

The OpenAI Gym installation instructions are missing reference to the "Build Tools for Visual Studio 2019" from the following site.

https://visualstudio.microsoft.com/downloads/

I also found this by reading the following article.
https://towardsdatascience.com/how-to-install-openai-gym-in-a-windows-environment-338969e24d30

Even though this is an issue in the OpenAI gym, a note in this RE

I'm using latest pyod version on pypi. How to generate simulated data where x-axis is time? Thank you.