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Auto-PyTorch | Automatic architecture search and hyperparameter optimization | Machine Learning library

 by   automl Python Version: v0.1.1 License: Apache-2.0

 by   automl Python Version: v0.1.1 License: Apache-2.0

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kandi X-RAY | Auto-PyTorch Summary

Auto-PyTorch is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. Auto-PyTorch has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install Auto-PyTorch' or download it from GitHub, PyPI.
Automatic architecture search and hyperparameter optimization for PyTorch
Support
Support
Quality
Quality
Security
Security
License
License
Reuse
Reuse

kandi-support Support

  • Auto-PyTorch has a medium active ecosystem.
  • It has 1607 star(s) with 202 fork(s). There are 42 watchers for this library.
  • There were 1 major release(s) in the last 12 months.
  • There are 46 open issues and 168 have been closed. On average issues are closed in 137 days. There are 33 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of Auto-PyTorch is v0.1.1
Auto-PyTorch Support
Best in #Machine Learning
Average in #Machine Learning
Auto-PyTorch Support
Best in #Machine Learning
Average in #Machine Learning

quality kandi Quality

  • Auto-PyTorch has 0 bugs and 0 code smells.
Auto-PyTorch Quality
Best in #Machine Learning
Average in #Machine Learning
Auto-PyTorch Quality
Best in #Machine Learning
Average in #Machine Learning

securitySecurity

  • Auto-PyTorch has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • Auto-PyTorch code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
Auto-PyTorch Security
Best in #Machine Learning
Average in #Machine Learning
Auto-PyTorch Security
Best in #Machine Learning
Average in #Machine Learning

license License

  • Auto-PyTorch 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.
Auto-PyTorch License
Best in #Machine Learning
Average in #Machine Learning
Auto-PyTorch License
Best in #Machine Learning
Average in #Machine Learning

buildReuse

  • Auto-PyTorch releases are available to install and integrate.
  • Deployable package is available in PyPI.
  • Build file is available. You can build the component from source.
  • Installation instructions, examples and code snippets are available.
  • Auto-PyTorch saves you 6431 person hours of effort in developing the same functionality from scratch.
  • It has 22384 lines of code, 1276 functions and 241 files.
  • It has medium code complexity. Code complexity directly impacts maintainability of the code.
Auto-PyTorch Reuse
Best in #Machine Learning
Average in #Machine Learning
Auto-PyTorch Reuse
Best in #Machine Learning
Average in #Machine Learning
Top functions reviewed by kandi - BETA

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

  • Performs a search on the given dataset .
  • Initialize the builder .
  • Perform a search on the model .
  • Performs training and loss .
  • Calculates the number of neurons in_feat .
  • Adds forbidden nodes .
  • Start a run of SMBO .
  • Compute file output .
  • Constructs an EnsembleBuilder and returns it .
  • Evaluate a function .

Auto-PyTorch Key Features

Automatic architecture search and hyperparameter optimization for PyTorch

PyPI Installation

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pip install autoPyTorch

Manual Installation

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# Following commands assume the user is in a cloned directory of Auto-Pytorch

# We also need to initialize the automl_common repository as follows
# You can find more information about this here:
# https://github.com/automl/automl_common/
git submodule update --init --recursive

# Create the environment
conda create -n auto-pytorch python=3.8
conda activate auto-pytorch
conda install swig
python setup.py install

Examples

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from autoPyTorch.api.tabular_classification import TabularClassificationTask

# data and metric imports
import sklearn.model_selection
import sklearn.datasets
import sklearn.metrics
X, y = sklearn.datasets.load_digits(return_X_y=True)
X_train, X_test, y_train, y_test = \
        sklearn.model_selection.train_test_split(X, y, random_state=1)

# initialise Auto-PyTorch api
api = TabularClassificationTask()

# Search for an ensemble of machine learning algorithms
api.search(
    X_train=X_train,
    y_train=y_train,
    X_test=X_test,
    y_test=y_test,
    optimize_metric='accuracy',
    total_walltime_limit=300,
    func_eval_time_limit_secs=50
)

# Calculate test accuracy
y_pred = api.predict(X_test)
score = api.score(y_pred, y_test)
print("Accuracy score", score)

Contributing

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$ git checkout development

Reference

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  @article{zimmer-tpami21a,
  author = {Lucas Zimmer and Marius Lindauer and Frank Hutter},
  title = {Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2021},
  note = {also available under https://arxiv.org/abs/2006.13799},
  pages = {3079 - 3090}
}

How can I install Auto-PyTorch on Windows 10 from requirements.txt?

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Set-Location install/path
git clone https://github.com/automl/Auto-PyTorch.git
Set-Location Auto-PyTorch
Get-Content requirements.txt | % { pip install $_ }
python setup.py install

Community Discussions

Trending Discussions on Auto-PyTorch
  • How can I install Auto-PyTorch on Windows 10 from requirements.txt?
Trending Discussions on Auto-PyTorch

QUESTION

How can I install Auto-PyTorch on Windows 10 from requirements.txt?

Asked 2020-Jul-09 at 02:49

I have been trying to install Auto-PyTorch, an automatic Neural Network tuning system (more info about installation here: https://github.com/automl/Auto-PyTorch), in a Windows 10 system. The installation steps are as follow:

$ cd install/path
$ git clone https://github.com/automl/Auto-PyTorch.git
$ cd Auto-PyTorch
$ cat requirements.txt | xargs -n 1 -L 1 pip install
$ python setup.py install

However, I can't get around the following line of code:

cat requirements.txt | xargs -n 1 -L 1 pip install

Once I get there, the following Windows PowerShell error is raised:

xargs : The term 'xargs' is not recognized as the name of a cmdlet, function, script file, or 

operable program.
Check the spelling of the name, or if a path was included, verify that the path is correct and try again.
At line:1 char:86
+ ... read.CurrentUICulture = 'en-US'; cat requirements.txt | xargs -n 1 -L ...
+                                                             ~~~~~
    + CategoryInfo          : ObjectNotFound: (xargs:String) [], CommandNotFoundException
    + FullyQualifiedErrorId : CommandNotFoundException

Note that I passed the following line of code so that the error is thrown in English (I am Spanish):

[Threading.Thread]::CurrentThread.CurrentUICulture = 'en-US'; cat requirements.txt | xargs -n 1 -L 1 pip install

I'm not an expert on PowerShell, so I would greatly appreciate your help.

Best regards!

ANSWER

Answered 2020-Jul-09 at 02:49

Since you're running on Windows PowerShell, only command-line utilities natively available on Windows can be assumed to be available - and xargs, a Unix utility, is not among them.
(While git also isn't natively available, it looks like you've already installed it).

Here's a translation of your code into native PowerShell code (note that cd is a built-in alias for Set-Location, and, on Windows only, cat is a built-in alias for Get-Content; % is a built-in alias for the ForEach-Object cmdlet):

Set-Location install/path
git clone https://github.com/automl/Auto-PyTorch.git
Set-Location Auto-PyTorch
Get-Content requirements.txt | % { pip install $_ }
python setup.py install

Source https://stackoverflow.com/questions/62804230

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

Vulnerabilities

No vulnerabilities reported

Install Auto-PyTorch

We recommend using Anaconda for developing as follows:.

Support

If you want to contribute to Auto-PyTorch, clone the repository and checkout our current development branch.

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