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

 by   automl Python Version: v0.2.1 License: Apache-2.0

kandi X-RAY | Auto-PyTorch Summary

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

            kandi-support Support

              Auto-PyTorch has a medium active ecosystem.
              It has 2057 star(s) with 255 fork(s). There are 44 watchers for this library.
              It had no major release in the last 12 months.
              There are 42 open issues and 201 have been closed. On average issues are closed in 213 days. There are 20 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of Auto-PyTorch is v0.2.1

            kandi-Quality Quality

              Auto-PyTorch has 0 bugs and 0 code smells.

            kandi-Security Security

              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.

            kandi-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.

            kandi-Reuse Reuse

              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.

            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 the forward computation
            • Rescale outputs
            • Repeat intermediate values
            • Set the network to the given device
            • Get hyperparameter search space
            • Returns a hyperparameter object corresponding to the given hyperparameter_type
            • Adds a hyperparameter to the configuration space
            • Fit the pipeline
            • Clean up the logger
            • Returns a Dataset
            • Evaluate the model
            • Evaluate a train function
            • Returns a ConfigurationSpace instance for the given dataset properties
            • Estimate the model
            • Forward computation
            • Predict for each time series
            • Builds a decoder
            • Get a hyperparameter search space
            • Get a single dataset
            • Estimate the fitness estimator
            • Build a forecasting evaluator
            • Performs a search on the model
            • Refit the dataset
            • Get hyperparameter space
            • Performs an optimization search
            • Perform forward computation
            • Performs a search
            Get all kandi verified functions for this library.

            Auto-PyTorch Key Features

            No Key Features are available at this moment for Auto-PyTorch.

            Auto-PyTorch Examples and Code Snippets

            Rdot img1Lines of Code : 11dot img1License : Weak Copyleft (LGPL-3.0)
            copy iconCopy
              # Instantiate Learner
              lrn = LearnerClassifKerasFF$new()
              # Set Learner Hyperparams
              lrn$param_set$values$epochs = 50
              lrn$param_set$values$layer_units = 12
              # Train and Predict

            Community Discussions


            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:, in a Windows 10 system. The installation steps are as follow:



            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):


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


            No vulnerabilities reported

            Install Auto-PyTorch

            We recommend using Anaconda for developing as follows:.


            If you want to contribute to Auto-PyTorch, clone the repository and checkout our current development branch.
            Find more information at:

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