Transfer-Learning-Library | Transfer Learning Library for Domain Adaptation | Machine Learning library

by thuml Python Version: v0.4 License: MIT

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

kandi X-RAY | Transfer-Learning-Library Summary

Transfer-Learning-Library is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Generative adversarial networks applications. Transfer-Learning-Library has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can download it from GitHub.

TLlib is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms, or readily apply existing algorithms.

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Quality

Security

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Transfer-Learning-Library has a medium active ecosystem.

It has 2601 star(s) with 478 fork(s). There are 46 watchers for this library.

It had no major release in the last 12 months.

There are 11 open issues and 151 have been closed. On average issues are closed in 29 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Transfer-Learning-Library is v0.4

Quality

Transfer-Learning-Library has 0 bugs and 0 code smells.

Security

Transfer-Learning-Library has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Transfer-Learning-Library code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Transfer-Learning-Library is licensed under the MIT License. This license is Permissive.

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

Reuse

Transfer-Learning-Library releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Fit the model on the source domain
Validate the model
Returns a pretty formatted table of the class
Compute the gradient matrix
Train the model
Validate a dataset
Plot the predicted class labels
Update self mat
Flattens a list of proposals
Fit the model
Calculate channel attention
Preprocess a part
Validate the training
Visualize ranking results
Prepare a vocabulary to train data files
Performs a forward projection
Returns a train transform
Calculate the similarity between source and target features
Run dbscan clustering algorithm
Loads the samples of the given task
Return argument parser
Get argument parser
Compute the maximum evidence of the features
Evaluate the prediction
Perform empirical risk minimization
Perform training
Load a dataset

Get all kandi verified functions for this library.

Transfer-Learning-Library Key Features

No Key Features are available at this moment for Transfer-Learning-Library.

Transfer-Learning-Library Examples and Code Snippets

Xlearn Transfer Learning Library,Usage,Quick Start

Python

Lines of Code : 8

License : No License

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# Prepare the data
sh data/office/download.sh
# Download and process the pretrained mean
python download_mean_from_caffe.py
# Download and process the pretrained model
python download_model_from_caffe.py
# Train
python main.py

Community Discussions

Trending Discussions on Transfer-Learning-Library

Getting this while using pytorch transforms--->TypeError: integer argument expected, got float

QUESTION

Getting this while using pytorch transforms--->TypeError: integer argument expected, got float

Asked 2021-Jul-09 at 05:00

I cloned transfer-learning-library repo and working on maximum classifier discrepancy. I am trying to change the augmentation but getting the following error

...

ANSWER

Answered 2021-Jul-08 at 18:51

The fill argument needs to be an integer.

This transform does not support the fill parameter for Tensor types; therefore, if you wish to use the fill parameter, then you must use this transform before the ToTensor transform. At this point, the data is integral.

Source https://stackoverflow.com/questions/68305315

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

Vulnerabilities

No vulnerabilities reported

Install Transfer-Learning-Library

To use dalib, talib, dglib, and common in other places, you need to install Transfer-Learn,. Note that we do not support pip install currently. For flexible use and modification of Transfer-Learn, please git clone the library.

Support

You can find the tutorial and API documentation on the website: Documentation. You can also build the doc by yourself following the instructions in http://tl.thuml.ai/get_started/faq.html. Also, we have examples in the directory examples. A typical usage is. In the directory examples, you can find all the necessary running scripts to reproduce the benchmarks with specified hyper-parameters.

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