kandi X-RAY | twoLayerNet Summary
kandi X-RAY | twoLayerNet Summary
twoLayerNet is a Python library. twoLayerNet has no bugs, it has no vulnerabilities and it has low support. However twoLayerNet build file is not available. You can download it from GitHub.
twoLayerNet
twoLayerNet
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Quality
Security
License
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Support
twoLayerNet has a low active ecosystem.
It has 1 star(s) with 0 fork(s). There are no watchers for this library.
It had no major release in the last 6 months.
twoLayerNet has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of twoLayerNet is current.
Quality
twoLayerNet has 0 bugs and 0 code smells.
Security
twoLayerNet has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
twoLayerNet code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
twoLayerNet 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
twoLayerNet releases are not available. You will need to build from source code and install.
twoLayerNet has no build file. You will be need to create the build yourself to build the component from source.
It has 124 lines of code, 6 functions and 5 files.
It has low code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed twoLayerNet and discovered the below as its top functions. This is intended to give you an instant insight into twoLayerNet implemented functionality, and help decide if they suit your requirements.
- Train the model .
- Compute the loss .
- Get training data .
- Initialize matrices .
- Predict the features in X .
Get all kandi verified functions for this library.
twoLayerNet Key Features
No Key Features are available at this moment for twoLayerNet.
twoLayerNet Examples and Code Snippets
No Code Snippets are available at this moment for twoLayerNet.
Community Discussions
Trending Discussions on twoLayerNet
QUESTION
Size mismatch error in converting TensorFlow model to Pytorch
Asked 2020-Jun-15 at 20:52
I´m trying to convert a TensorFlow model to Pytorch but got stuck in this error. Can anyone help me?
...ANSWER
Answered 2020-Jun-15 at 20:52You need to transpose the weights and biases:
QUESTION
Pytorch tensor, how to switch channel position - Runtime error
Asked 2020-Jan-08 at 17:19
I have my training dataset as below, where X_train is 3D with 3 channels
Shape of X_Train: (708, 256, 3) Shape of Y_Train: (708, 4)
Then I convert them into a tensor and input into the dataloader:
...ANSWER
Answered 2020-Jan-08 at 14:56Use permute.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install twoLayerNet
You can download it from GitHub.
You can use twoLayerNet 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.
You can use twoLayerNet 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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