NNDIAL | open source toolkit for building end | Natural Language Processing library

by shawnwun Python Version: Current License: Non-SPDX

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

kandi X-RAY | NNDIAL Summary

NNDIAL is a Python library typically used in Artificial Intelligence, Natural Language Processing, Bert, Neural Network, Transformer applications. NNDIAL has no bugs, it has no vulnerabilities and it has low support. However NNDIAL build file is not available and it has a Non-SPDX License. You can download it from GitHub.

The model can be roughtly divided into encoder and decoder modules. This software encloses the work from three publications, Wen et al, 2016, 2017a, 2017b. The models/methods supported in this software are listed below,.

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Quality

Security

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Support

NNDIAL has a low active ecosystem.

It has 347 star(s) with 107 fork(s). There are 24 watchers for this library.

It had no major release in the last 6 months.

There are 7 open issues and 4 have been closed. On average issues are closed in 2 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of NNDIAL is current.

Quality

NNDIAL has 0 bugs and 0 code smells.

Security

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

NNDIAL code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

NNDIAL has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

NNDIAL releases are not available. You will need to build from source code and install.

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

Installation instructions, examples and code snippets are available.

NNDIAL saves you 2080 person hours of effort in developing the same functionality from scratch.

It has 4565 lines of code, 168 functions and 29 files.

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

Top functions reviewed by kandi - BETA

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

Generate a directed list of actions
Evaluate the score for a given rule
Compute the softmax
Sigmoid function
Forward pass through the model
Reads the convolution matrix
Compute the max pooling of data
Compute rmsprop
Create a shared shared array
Encodes the word embedding
Convolution layer
Calculate the new belief propagation
Reads cell activation layer
Track the belief distribution
Calculate source and source features
Track the source and source positions
Calculate the derivative of a set of parameters
Argument parser
Compute the momentum
Get user turn

Get all kandi verified functions for this library.

NNDIAL Key Features

No Key Features are available at this moment for NNDIAL.

NNDIAL Examples and Code Snippets

No Code Snippets are available at this moment for NNDIAL.

Community Discussions

Trending Discussions on NNDIAL

how do I deal: ERROR: (gcloud.compute.ssh)?

QUESTION

how do I deal: ERROR: (gcloud.compute.ssh)?

Asked 2019-May-25 at 18:51

I have built GPU instance on google cloud compute engine two weeks ago. When I reconnect today, it says:

ERROR: (gcloud.compute.ssh) Instance [nndial-1] in zone [asia-east1-b] has not been allocated an external IP address yet. Try rerunning this command later.

I tried several times, but still can't use.

I have allocated an external IP last time, why it does relate with the zone?

...

ANSWER

Answered 2018-Dec-02 at 15:03

'nndial-1' is another instance, I make mistake with the name. The problem is I wanted to connect one instance without external IP addresses and which is not running. But the prompt is not accurate.

Source https://stackoverflow.com/questions/53568473

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

Vulnerabilities

No vulnerabilities reported

Install NNDIAL

The training of the model is done in two steps. Firstly, train the belief tracker using a tracker config file,. Now train an NDM based on the pre-trained tracker,. Once you have the model trained, you can validate or test its performance,. Or interact with it directly to see how it does,. If you want an attention-based NDM model, just modified the config file,. Or you can train an LIDM using semi-supervised variational inference,. You can also choose to refine the LIDM policy network by corpus-based RL,. The commands listed here are just examples. Please refer to scp/example_run.sh for more detail. Note, each new config file could change the intended model architecture, therefore, prompt the model to re-initiate the model parameters. For example, when training trackers it doesn't matter the structure of decoder and encoder because we can change it in the next config file.

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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