mac-graph | An attempt to get MACnets | Machine Learning library

by Octavian-ai Python Version: Current License: Unlicense

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | mac-graph Summary

mac-graph is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. mac-graph has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However mac-graph build file is not available. You can download it from GitHub.

The MacGraph network. An attempt to get MACnets running on graph knowledge

Support

Quality

Security

License

Reuse

Support

mac-graph has a low active ecosystem.

It has 114 star(s) with 19 fork(s). There are 11 watchers for this library.

It had no major release in the last 6 months.

mac-graph has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of mac-graph is current.

Quality

mac-graph has 0 bugs and 0 code smells.

Security

mac-graph has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

mac-graph code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

mac-graph is licensed under the Unlicense License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

mac-graph releases are not available. You will need to build from source code and install.

mac-graph has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

mac-graph saves you 2279 person hours of effort in developing the same functionality from scratch.

It has 4980 lines of code, 471 functions and 79 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed mac-graph and discovered the below as its top functions. This is intended to give you an instant insight into mac-graph implemented functionality, and help decide if they suit your requirements.

Predict on the input records
Prints tap_dict
Apply fn to each component
Print all the features
Reshape examples
Construct a model function
Execute the reason
Define the decoder
Define dynamic decoder
Write a single cell to memory
Construct the taps
Add positional encoding
Get all the messages from the queue
Apply mi_activation
Start drone
Start supervisor
Perform nodegru
Reshape an example
Gets TensorFlow configuration
Layer normalize tensor
Parse a single example
Mutate the model with a new one
Get argument parser
Train the model
Build data
Forward computation
Create a LarsMinimizer

Get all kandi verified functions for this library.

mac-graph Key Features

No Key Features are available at this moment for mac-graph.

mac-graph Examples and Code Snippets

No Code Snippets are available at this moment for mac-graph.

Community Discussions

Trending Discussions on mac-graph

Scaling an image OSX Swift

QUESTION

Scaling an image OSX Swift

Asked 2017-Jun-13 at 00:55

Im currently trying to scale an image using swift. This shouldnt be a difficult task, since i've implemented a scaling solution in C# in 30 mins - however, i've been stuck for 2 days now.

I've tried googling/crawling through stack posts but to no avail. The two main solutions i have seen people use are:

A function written in Swift to resize an NSImage proportionately

and

resizeNSImage.swift

An Obj C Implementation of the above link

So i would prefer to use the most efficient/least cpu intensive solution, which according to my research is option 2. Due to option 2 using NSImage.lockfocus() and NSImage.unlockFocus, the image will scale fine on non-retina Macs, but double the scaling size on retina macs. I know this is due to the pixel density of Retina macs, and is to be expected, but i need a scaling solution that ignores HiDPI specifications and just performs a normal scale operation.

This led me to do more research into option 1. It seems like a sound function, however it literally doesnt scale the input image, and then doubles the filesize as i save the returned image (presumably due to pixel density). I found another stack post with someone else having the exact same problem as i am, using the exact same implementation (found here). Of the two suggested answers, the first one doesnt work, and the second is the other implementation i've been trying to use.

If people could post Swift-ified answers, as opposed to Obj C, i'd appreciate it very much!

EDIT: Here's a copy of my implementation of the first solution - I've divided it into 2 functions:

...

ANSWER

Answered 2017-Jun-13 at 00:55

To anyone else experiencing this problem - I ended up spending countless hours trying to find a way to do this, and ended up just getting the scaling factor of the screen (1 for normal macs, 2 for retina)... The code looks like this:

Source https://stackoverflow.com/questions/43383331

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install mac-graph

You can download it from GitHub.
You can use mac-graph like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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