GATNE | Source code and dataset for KDD 2019 paper

 by   THUDM Python Version: v1.0 License: MIT

kandi X-RAY | GATNE Summary

kandi X-RAY | GATNE Summary

GATNE is a Python library typically used in Simulation applications. GATNE has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Representation Learning for Attributed Multiplex Heterogeneous Network. Yukuo Cen, Xu Zou, Jianwei Zhang, Hongxia Yang, Jingren Zhou, Jie Tang.
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              GATNE has a low active ecosystem.
              It has 478 star(s) with 139 fork(s). There are 16 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 34 open issues and 90 have been closed. On average issues are closed in 21 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of GATNE is v1.0

            kandi-Quality Quality

              GATNE has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              GATNE is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              GATNE 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.
              GATNE saves you 170 person hours of effort in developing the same functionality from scratch.
              It has 421 lines of code, 15 functions and 3 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed GATNE and discovered the below as its top functions. This is intended to give you an instant insight into GATNE implemented functionality, and help decide if they suit your requirements.
            • Train the model
            • Loads a walk file
            • Generate node list
            • Save all the walkks to a file
            • Get G from edges
            • Computes the distance between two nodes
            • Loads node type from file
            • Evaluate the model
            • Generate the vocabulary
            • Generate training pairs
            • Yield batches from the given pairs
            • Simulate a random walk
            • Generate neighbors for a layer
            • Generate random walk for each layer
            • Generate vocabulary
            • Parse arguments
            • Load test data from a file
            • Load training data from file
            • Load feature data from file
            Get all kandi verified functions for this library.

            GATNE Key Features

            No Key Features are available at this moment for GATNE.

            GATNE Examples and Code Snippets

            No Code Snippets are available at this moment for GATNE.

            Community Discussions

            QUESTION

            Tensorflow distributed training hangs with RecvTensor cancelled warning
            Asked 2021-Apr-08 at 07:39

            I'm training a model using tensorflow 2.1.0's estimator api under parameter server distributed mode. The code to launch the training is like this:

            ...

            ANSWER

            Answered 2021-Apr-08 at 07:39

            I ran my task a few times and found that one training worker will finish at the first place, then all the other training workers starts to hang. So I guess the finished training worker has some impact to the other workers. How about let the first finished training worker not "finished"? So I added a 10-minutes sleep after the training code for each training worker in order to let the worker not "finished". And this worked. While the first finished worker is sleeping, other training workers keeps training properly and all finished training within 10-minutes. This is my solution so far. Still open to other solutions.

            Source https://stackoverflow.com/questions/66899783

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

            Vulnerabilities

            No vulnerabilities reported

            Install GATNE

            Please first install TensorFlow or PyTorch, and then install other dependencies by.

            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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            https://github.com/THUDM/GATNE.git

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            gh repo clone THUDM/GATNE

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            git@github.com:THUDM/GATNE.git

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