spark-deep-learning | Deep Learning Pipelines for Apache Spark

by databricks Python Version: v1.6.0 License: Apache-2.0

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | spark-deep-learning Summary

spark-deep-learning is a Python library typically used in Institutions, Learning, Education, Big Data, Deep Learning, Tensorflow, Spark applications. spark-deep-learning 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.

Deep Learning Pipelines for Apache Spark.

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spark-deep-learning has a medium active ecosystem.

It has 1968 star(s) with 502 fork(s). There are 158 watchers for this library.

It had no major release in the last 12 months.

There are 78 open issues and 27 have been closed. On average issues are closed in 46 days. There are 8 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of spark-deep-learning is v1.6.0

Quality

spark-deep-learning has 0 bugs and 0 code smells.

Security

spark-deep-learning has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

spark-deep-learning code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

spark-deep-learning 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.

Reuse

spark-deep-learning releases are available to install and integrate.

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

Installation instructions are not available. Examples and code snippets are available.

spark-deep-learning saves you 5654 person hours of effort in developing the same functionality from scratch.

It has 11830 lines of code, 523 functions and 107 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

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spark-deep-learning Key Features

No Key Features are available at this moment for spark-deep-learning.

spark-deep-learning Examples and Code Snippets

A Scalable Implementation of Deep Learning on Spark,Example of use,Stacked Autoencoder

Scala

Lines of Code : 15

License : Permissive (Apache-2.0)

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import org.apache.spark.ml.scaladl.{MultilayerPerceptronClassifier, StackedAutoencoder}
val train = spark.read.format("libsvm").option("numFeatures", 784).load(mnistTrain).persist()
train.count()
val stackedAutoencoder = new StackedAutoencoder().setL

A Scalable Implementation of Deep Learning on Spark,Example of use,Multilayer perceptron

Scala

Lines of Code : 8

License : Permissive (Apache-2.0)

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import org.apache.spark.ml.scaladl.MultilayerPerceptronClassifier
val train = spark.read.format("libsvm").option("numFeatures", 784).load("mnist.scale").persist()
val test = spark.read.format("libsvm").option("numFeatures", 784).load("mnist.scale.t")

Windows:

Scala

Lines of Code : 6

License : Permissive (Apache-2.0)

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libquadmath-0.dll // MINGW
libgcc_s_seh-1.dll // MINGW
libgfortran-3.dll // MINGW
libopeblas.dll // OpenBLAS binary
liblapack3.dll // copy of libopeblas.dll
libblas3.dll // copy of libopenblas.dll

Community Discussions

Trending Discussions on spark-deep-learning

ModuleNotFoundError: No module named 'PIL' when I want to import sparkdl in databricks

QUESTION

ModuleNotFoundError: No module named 'PIL' when I want to import sparkdl in databricks

Asked 2020-Apr-16 at 00:39

I am trying to implement a deep learning pipeline, I need to import sparkdl package in databricks (community edition). My other installed libraries include: spark-deep-learning:1.4.0-spark2.4-s_2.11, h5py, keras==2.2.4, tensorflow==1.15.0, wrapt.

When I run from sparkdl import DeepImageFeaturizer, I keep getting the error of ModuleNotFoundError: No module named 'PIL'.

Update: Installing Pillow solves the problem.

...

ANSWER

Answered 2020-Apr-08 at 11:40

Make sure you have installed all the libraries as the prerequisites:

Create a spark-deep-learning library with the Source option Maven and Coordinate 1.4.0-spark2.4-s_2.11.
Create libraries with the Source option PyPI and Package tensorflow==1.12.0,keras==2.2.4, h5py==2.7.0, wrapt.

Reference: https://docs.azuredatabricks.net/_static/notebooks/deep-learning/deep-learning-pipelines-1.4.0.html

Source https://stackoverflow.com/questions/60715995

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

Vulnerabilities

No vulnerabilities reported

Install spark-deep-learning

You can download it from GitHub.
You can use spark-deep-learning 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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