dist-keras | Distributed Deep Learning , with a focus

 by   cerndb Python Version: 0.2.1 License: GPL-3.0

kandi X-RAY | dist-keras Summary

kandi X-RAY | dist-keras Summary

dist-keras is a Python library typically used in Big Data, Deep Learning, Pytorch, Tensorflow, Spark, Hadoop applications. dist-keras has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

Distributed Keras is a distributed deep learning framework built op top of Apache Spark and Keras, with a focus on "state-of-the-art" distributed optimization algorithms. We designed the framework in such a way that a new distributed optimizer could be implemented with ease, thus enabling a person to focus on research. Several distributed methods are supported, such as, but not restricted to, the training of ensembles and models using data parallel methods. Most of the distributed optimizers we provide, are based on data parallel methods. A data parallel method, as described in [1], is a learning paradigm where multiple replicas of a single model are used to optimize a single objective. Using this approach, we are able to dignificantly reduce the training time of a model. Depending on the parametrization, we also observed that it is possible to achieve better statistical model performance compared to a more traditional approach (e.g., like the SingleTrainer implementation), and yet, spending less wallclock time on the training of the model. However, this is subject to further research. Attention: A rather complete introduction to the problem of Distributed Deep Learning is presented in my Master Thesis Furthermore, the thesis describes includes several novel insights, such as a redefinition of parameter staleness, and several new distributed optimizers such as AGN and ADAG.

            kandi-support Support

              dist-keras has a low active ecosystem.
              It has 615 star(s) with 170 fork(s). There are 48 watchers for this library.
              It had no major release in the last 12 months.
              There are 31 open issues and 42 have been closed. On average issues are closed in 12 days. There are 4 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of dist-keras is 0.2.1

            kandi-Quality Quality

              dist-keras has 0 bugs and 0 code smells.

            kandi-Security Security

              dist-keras has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              dist-keras code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              dist-keras is licensed under the GPL-3.0 License. This license is Strong Copyleft.
              Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

            kandi-Reuse Reuse

              dist-keras 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.
              dist-keras saves you 918 person hours of effort in developing the same functionality from scratch.
              It has 2095 lines of code, 249 functions and 19 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed dist-keras and discovered the below as its top functions. This is intended to give you an instant insight into dist-keras implemented functionality, and help decide if they suit your requirements.
            • Train a dataframe
            • Allocates a parameter server
            • Start the parameter service
            • Allocate a worker
            • Train the model
            • Train a Keras model
            • Average a list of models
            • Deserialize a keras model
            • Allocates a SequentialWorker
            • Train a keras model
            • Runs the optimizer
            • Optimizes the training set
            • Handle a pull event
            • Transform a dataframe
            • Handle a connection
            • Normalize a row
            • Run the optimizer
            • Handle a commit command
            • Transform a row into a Spark DataFrame
            • Predict predictions for the given iterator
            • Reads the data file
            • Stops the connection
            • Transform row into one - hot encoded row
            • Transform a row into a dataframe
            • Parse command line arguments
            • Run the model
            Get all kandi verified functions for this library.

            dist-keras Key Features

            No Key Features are available at this moment for dist-keras.

            dist-keras Examples and Code Snippets

            No Code Snippets are available at this moment for dist-keras.

            Community Discussions


            pyspark addPyFile to add zip of .py files, but module still not found
            Asked 2020-Mar-27 at 15:41

            Using addPyFiles() seems to not be adding desiered files to spark job nodes (new to spark so may be missing some basic usage knowledge here).

            Attempting to run a script using pyspark and was seeing errors that certain modules are not found for import. Never used spark before, but other posts (from package in question https://github.com/cerndb/dist-keras/issues/36#issuecomment-378918484 and https://stackoverflow.com/a/39779271/8236733) recommended zipping the module and adding to the spark job via sparkContext.addPyFiles(mymodulefiles.zip), yet still getting error. The relevant code snippets being...



            Answered 2018-Nov-27 at 17:20

            Fixed problem. Admittedly, solution is not totally spark-related, but leaving question posted for the sake of others who may have similar problem, since the given error message did not make my mistake totally clear from the start.

            TLDR: Make sure the package contents (so they should include an __init.py__ in each dir.) of the zip file being loaded in are structured and named the way your code expects.

            The package I was trying to load into the spark context via zip was of the form

            Source https://stackoverflow.com/questions/51450462

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


            No vulnerabilities reported

            Install dist-keras

            We will guide you how to install Distributed Keras. However, we will assume that an Apache Spark installation is available. In the following subsections, we describe two approaches to achieve this.


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