treeano | more composable than other neural network libraries

by diogo149 Python Version: Current License: Apache-2.0

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

kandi X-RAY | treeano Summary

treeano is a Python library. treeano 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.

more composable than other neural network libraries

Support

Quality

Security

License

Reuse

Support

treeano has a low active ecosystem.

It has 42 star(s) with 9 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

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

It has a neutral sentiment in the developer community.

The latest version of treeano is current.

Quality

treeano has 0 bugs and 0 code smells.

Security

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

treeano code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

treeano is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

treeano 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.

Top functions reviewed by kandi - BETA

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

Compute the network
Build a relative network
Build the tree
Return the list of nodes
Generates a generalized residual block convolution layer
Generates a generalized residual convolution layer
Return a generalized residual node
Calculate the SWiveL cost
Point - wise mutual information
Perform the computation
Compute update deltas
Local Response Normalization
Make a thunk module
Pretty print the given network
Compute the deep metric loss of the deep metric loss
Flatten a nested list
Load localization network
Local response normalization
Add a parent to the network
Evaluate a function until it is reached
Calculate the sgns cost
Transform kwargs to inputs
Access the tensor
Performs the evaluation on the given node
Finds the axes of the given parameters
Adds the given input to the graph

Get all kandi verified functions for this library.

treeano Key Features

No Key Features are available at this moment for treeano.

treeano Examples and Code Snippets

No Code Snippets are available at this moment for treeano.

Community Discussions

No Community Discussions are available at this moment for treeano.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install treeano

You can download it from GitHub.
You can use treeano 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 .

Find more information at: