cae.py | Contractive Auto-Encoders in Numpy | Data Manipulation library

by ynd Python Version: Current License: No License

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kandi X-RAY | cae.py Summary

cae.py is a Python library typically used in Utilities, Data Manipulation, Numpy applications. cae.py has no bugs, it has no vulnerabilities and it has low support. However cae.py build file is not available. You can download it from GitHub.

Contractive Auto-Encoders in Numpy

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cae.py has a low active ecosystem.

It has 28 star(s) with 19 fork(s). There are 5 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 2 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of cae.py is current.

Quality

cae.py has 0 bugs and 0 code smells.

Security

cae.py has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

cae.py code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

cae.py 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

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

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

cae.py saves you 36 person hours of effort in developing the same functionality from scratch.

It has 98 lines of code, 15 functions and 2 files.

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

Top functions reviewed by kandi - BETA

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

Fit the minimization cost function .
Initialize the model .
Computes the loss of the model .
Estimate the model weights .
Sample from data .
Compute Jacobian
Decodes the covariance matrix .
Reconstruct the decoded data .
Encode the tensor .
Sigmoid function .

Get all kandi verified functions for this library.

cae.py Key Features

No Key Features are available at this moment for cae.py.

cae.py Examples and Code Snippets

No Code Snippets are available at this moment for cae.py.

Community Discussions

Trending Discussions on cae.py

How to assign a tf.keras.layers.layer to a class without initializing it?

QUESTION

How to assign a tf.keras.layers.layer to a class without initializing it?

Asked 2019-May-03 at 17:15

I work on a class to create all sorts of symmetric AE's. I now port this class to TF 2.0 and it is more complicated than I thought. However, I use subclassing of layers and models to achieve this. Therefore I want to group several keras layers to one keras layer. But if I want to write something like this:

...

ANSWER

Answered 2019-May-03 at 17:15

The problem is with setting not instantiated class as an attribute in a subclass of tf.keras.layers.Layer. If you remove following line

self.keras_layer = keras_layer

the code would work:

Source https://stackoverflow.com/questions/55965135

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

Vulnerabilities

No vulnerabilities reported

Install cae.py

You can download it from GitHub.
You can use cae.py 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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