simnet | semantic similarity model | Topic Modeling library

by yyht Python Version: Current License: No License

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

kandi X-RAY | simnet Summary

simnet is a Python library typically used in Artificial Intelligence, Topic Modeling, Deep Learning, Tensorflow, Keras applications. simnet has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

semantic similarity model

Support

Quality

Security

License

Reuse

Support

simnet has a low active ecosystem.

It has 7 star(s) with 4 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

simnet has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of simnet is current.

Quality

simnet has 0 bugs and 0 code smells.

Security

simnet has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

simnet code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

simnet does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

simnet 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.

It has 74570 lines of code, 5766 functions and 493 files.

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

Top functions reviewed by kandi - BETA

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

Perform beam search .
Implements SlSTM cell .
Basic hyperparameters .
Multi - head group attention .
Multi layer transformer .
Decorator to get standardized layers .
Creates masked local attention .
Transformer .
Local mixture of experts .
Define collect .

Get all kandi verified functions for this library.

simnet Key Features

No Key Features are available at this moment for simnet.

simnet Examples and Code Snippets

No Code Snippets are available at this moment for simnet.

Community Discussions

Trending Discussions on simnet

How to ensure notified bitcoin block is confirmed?

QUESTION

How to ensure notified bitcoin block is confirmed?

Asked 2020-Dec-09 at 16:44

How can i make sure the notified block is confirmed and related transactions of block is final?

I'm trying to monitor my wallet for any deposits, Someone told me to make sure block is verified i need to monitor older block of blockchain with difference of 3, which means i always need to get the height=newest_height - 3, Is this idea correct? How can i trust the notified block? My problem is when i try test with simnet chain params, i will be notified just after generation of any new block with the height of newest one. should i put any configuration for getting a block differ than newest block height?

I'm using Golang, and library i'm using is from btcsuite btcwallet.

I would be appreciated if you guide me with your helpful suggestions.

...

ANSWER

Answered 2020-Dec-09 at 16:44

PoW consensus does not provide for the concept of "finalizing" a block or transaction - for PoW this is a probabilistic concept. Since the PoW considers forks as normal, a block can theoretically be "canceled" at any depth. However, practice has established that the probability of replacing a block at a depth of more than 6 did not occur, therefore it is considered that if there are 6 or more other blocks "on top" of the block, then transactions in it are "conditionally finalized".

Source https://stackoverflow.com/questions/65212156

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

Vulnerabilities

No vulnerabilities reported

Install simnet

You can download it from GitHub.
You can use simnet 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

Bimpm, esim, diin, drcn, drmm, dsmm, multi-view, hard-attention(just like relation network that select parts of hidden vectors as output rather than soft attention).

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