Ordered-Memory | repository contains the code | Machine Learning library

by yikangshen Python Version: Current License: MIT

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kandi X-RAY | Ordered-Memory Summary

Ordered-Memory is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning applications. Ordered-Memory has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

This repository contains the code used for Ordered Memory.

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Ordered-Memory has a low active ecosystem.

It has 25 star(s) with 6 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

Ordered-Memory has no issues reported. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Ordered-Memory is current.

Quality

Ordered-Memory has no bugs reported.

Security

Ordered-Memory has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

Ordered-Memory is licensed under the MIT License. This license is Permissive.

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

Reuse

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

Build file is available. You can build the component from source.

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

Top functions reviewed by kandi - BETA

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

Generate parse tree
Generate a colour for a given value
Plot a numpy array
Build a tree
Load training data and embeddings from scratch
Preprocess a dataset
Creates an iterator for batches of examples
Generates an iterator that generates training examples
Compute softmax
Process softmax
Truncate the batch
Truncate data to max_length
Perform the omr step
Perform an omr step
Generate a random tree
Calculate validation accuracy
Evaluate the model
Save a model to file
Load a checkpoint from file
Return a string representation of the expression
Train the model
Convert t into a tuple

Get all kandi verified functions for this library.

Ordered-Memory Key Features

No Key Features are available at this moment for Ordered-Memory.

Ordered-Memory Examples and Code Snippets

No Code Snippets are available at this moment for Ordered-Memory.

Community Discussions

Trending Discussions on Ordered-Memory

How many memory barriers do we need to implement a Peterson lock?

QUESTION

How many memory barriers do we need to implement a Peterson lock?

Asked 2019-Jun-06 at 16:48

I'm trying to figure out how many memory fences do we need to implement a Peterson lock. Clearly, we need at least one.

https://bartoszmilewski.com/2008/11/05/who-ordered-memory-fences-on-an-x86/

In practice, it seems that one is sufficient, based on a number of tests executed in different architectures. However, in theory, do we need additional ones?

I have tried the code below

my peterson_lock failed in this situation

changing the order between Mark A by Mark B and it works! However, the memory fence does not capture the ordering between Mark A and Mark B. So, does it mean that the program is still incorrect?

...

ANSWER

Answered 2019-Jun-06 at 16:48

Nobody uses a Peterson lock on mainstream platforms because mutexes are available. But assuming you cannot use those and you are writing code for an old X86 platform without access to modern primitives (no memory model, no mutexes, no atomic RMW operations), this algorithm might be considered.

Your implementation of the Peterson lock is incorrect (also after swapping the lines 'Mark as A' & 'Mark as B').
If you translate the Wikipedia pseudo code to C++, the correct implementation becomes:

Source https://stackoverflow.com/questions/56470294

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

Vulnerabilities

No vulnerabilities reported

Install Ordered-Memory

You can download it from GitHub.
You can use Ordered-Memory 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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