blas | Wrappers for BLAS | Wrapper library

I'm trying to study the neural-network-and-deep-learning (http://neuralnetworksanddeeplearning.com/chap1.html). Using the updated version for Python 3 by MichalDanielDobrzanski (https://github.com/MichalDanielDobrzanski/DeepLearningPython). Tried to run it in my command console and it gives an error below. I've tried uninstalling and reinstalling setuptools, theano, and numpy but none have worked thus far. Any help is very appreciated!!

Here's the full error log:

It is my understanding that NumPy dropped support for using the Accelerate BLAS and LAPACK at version 1.20.0. According to the release notes for NumPy 1.21.1, these bugs have been resolved and building NumPy from source using the Accelerate framework on MacOS >= 11.3 is now possible again: https://numpy.org/doc/stable/release/1.21.0-notes.html, but I cannot find any documentation on how to do so. This seems like it would be an interesting thing to try and do because the Accelerate framework is supposed to be highly-optimized for M-series processors. I imagine the process is something like this:

1. Download numpy source code folder and navigate to this folder.
2. Make a site.cfg file that looks something like:

my computer has only 1 GPU.

Below is what I get the result by entering someone's code

For the last 5 days, I am trying to make Keras/Tensorflow packages work in R. I am using RStudio for installation and have used conda, miniconda, virtualenv but it crashes each time in the end. Installing a library should not be a nightmare especially when we are talking about R (one of the best statistical languages) and TensorFlow (one of the best deep learning libraries). Can someone share a reliable way to install Keras/Tensorflow on CentOS 7?

Following are the steps I am using to install tensorflow in RStudio.

Since RStudio simply crashes each time I run tensorflow::tf_config() I have no way to check what is going wrong.

I have a local python project called jive that I would like to use in an another project. My current method of using jive in other projects is to activate the conda env for the project, then move to my jive directory and use python setup.py install. This works fine, and when I use conda list, I see everything installed in the env including jive, with a note that jive was installed using pip.

But what I really want is to do this with full conda. When I want to use jive in another project, I want to just put jive in that projects environment.yml.

So I did the following:

1. write a simple meta.yaml so I could use conda-build to build jive locally
2. build jive with conda build .
3. I looked at the tarball that was produced and it does indeed contain the jive source as expected
4. In my other project, add jive to the dependencies in environment.yml, and add 'local' to the list of channels.
5. create a conda env using that environment.yml.

When I activate the environment and use conda list, it lists all the dependencies including jive, as desired. But when I open python interpreter, I cannot import jive, it says there is no such package. (If use python setup.py install, I can import it.) How can I fix the build/install so that this works?

Here is the meta.yaml, which lives in the jive project top level directory:

I've built this new ggplot2 geom layer I'm calling geom_triangles (see https://github.com/ctesta01/ggtriangles/) that plots isosceles triangles given aesthetics including x, y, z where z is the height of the triangle and the base of the isosceles triangle has midpoint (x,y) on the graph.

What I want is for the geom_triangles() layer to automatically provide legend components for the height and width of the triangles, but I am not sure how to do that.

I understand based on this reference that I may need to adjust the draw_key argument in the ggproto StatTriangles object, but I'm not sure how I would do that and can't seem to find examples online of how to do it. I've been looking at the source code in ggplot2 for the draw_key functions, but I'm not sure how I would introduce multiple legend components (one for each of height and width) in a single draw_key argument in the StatTriangles ggproto.

I am deploying multiple R versions on multiple virtual desktops. I've built 3.6.3 and 4.1.2 R from source on Ubuntu 18.04.3 LTS. None of them finds the system-wide Rprofile.site file in /etc/R or the system certificates in /usr/share/ca-certificates. However R (3.4.4) installed with APT has no such problems. I used Ansible, but for the sake of this question I reproduced the deployment for one host with a shell script.

I would like to calculate a quadratic form: x' Q y in Julia.
What would be the most efficient way to calculate this for the cases:

1. No assumption.
2. Q is symmetric.
3. x and y are the same (x = y).
4. Both Q is symmetric and x = y.

I know Julia has dot(). But I wonder if it is faster than BLAS call.

I have the following Fortran code (modified on top of many answers from stack overflow..)