ignite | level library to help with training | Machine Learning library

 by   pytorch Python Version: v0.4.12 License: BSD-3-Clause

kandi X-RAY | ignite Summary

kandi X-RAY | ignite Summary

ignite is a Python library typically used in Institutions, Learning, Education, Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. ignite has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has high support. You can install using 'pip install ignite' or download it from GitHub, PyPI.

PyTorch-Ignite is a NumFOCUS Affiliated Project, operated and maintained by volunteers in the PyTorch community in their capacities as individuals (and not as representatives of their employers). See the "About us" page for a list of core contributors. For usage questions and issues, please see the various channels here. For all other questions and inquiries, please send an email to contact@pytorch-ignite.ai.

            kandi-support Support

              ignite has a highly active ecosystem.
              It has 4277 star(s) with 596 fork(s). There are 59 watchers for this library.
              It had no major release in the last 12 months.
              There are 109 open issues and 1098 have been closed. On average issues are closed in 4 days. There are 43 open pull requests and 0 closed requests.
              It has a positive sentiment in the developer community.
              The latest version of ignite is v0.4.12

            kandi-Quality Quality

              ignite has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              ignite is licensed under the BSD-3-Clause License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              ignite 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.
              ignite saves you 14511 person hours of effort in developing the same functionality from scratch.
              It has 40301 lines of code, 3680 functions and 274 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed ignite and discovered the below as its top functions. This is intended to give you an instant insight into ignite implemented functionality, and help decide if they suit your requirements.
            • Runs the model
            • Create a supervised evaluation function
            • Check if the argument is valid
            • Returns a function that evaluates a model
            • Spawn a function asynchronously
            • Return available backend names
            • Assert that backend is a valid backend
            • Perform training
            • Create an evaluation function
            • Evaluate the model
            • Decorate a function with only one rank
            • Get train and test loaders
            • Create a layer
            • Simulate num_events
            • Initialize training
            • Run a training
            • Record the results of the computation
            • Attach a timer to an engine
            • Setup TensorBoard logging
            • Runs the evaluation
            • Broadcast a tensor
            • Plot learning rate
            • Run the optimizer
            • Get train and validation loaders
            • Create an engine that evaluates a model
            • Broadcast tensor to source
            Get all kandi verified functions for this library.

            ignite Key Features

            No Key Features are available at this moment for ignite.

            ignite Examples and Code Snippets

            pytorch_geometric - gin-pytorch ignite
            Pythondot img1Lines of Code : 134dot img1License : Permissive (MIT License)
            copy iconCopy
            import os.path as osp
            import ignite
            import ignite.contrib.handlers.tensorboard_logger
            import ignite.contrib.handlers.tqdm_logger
            import torch
            import torch.nn.functional as F
            import torch_geometric.transforms as T
            from torch_geometric import seed_ev  
            Initiates an Ignite instance .
            javadot img2Lines of Code : 10dot img2License : Permissive (MIT License)
            copy iconCopy
                public Ignite igniteInstance() {
                    IgniteConfiguration config = new IgniteConfiguration();
                    CacheConfiguration cache = new CacheConfiguration("baeldungCache");
                    cache.setIndexedTypes(Integer.class, Empl  

            Community Discussions


            Apache Ignite "Update of composite key column is not supported"
            Asked 2022-Mar-28 at 11:06

            I have a cache with an AffinityKey as Key and want to insert an entry. If i try to insert the entry using a SQL-Insert statement i get an exception stating "Update of composite key column is not supported" which i guess is because the AffinityKey is a composite key. On https://ignite.apache.org/docs/latest/SQL/indexes#indexing-nested-objects i have read that if you are using indexed nested objects you will no longer be able to use insert or update statements but it is not mentioned on https://ignite.apache.org/docs/latest/data-modeling/affinity-collocation for composite keys.

            Does using composite keys also cause insert and update statements to no longer be usable or am i missing something?




            Answered 2022-Mar-25 at 23:59

            You are mixing the concepts.

            In Apache Ignite you can access or insert your data multiple ways. One would be to use Cache API, like cache#get, cache#put, another option would be - using SQL, like INSERT, SELECT, etc.

            Since eventually everything is just a key-value pair undeneath, Ignite provide a special SQL _key and _val properties to access the corresponded values.

            The thing is - if you don't need to use Cache API and SQL interchangeably and are OK using only, say, SQL, you don't set _key at all.

            On the other hand, if you need to use both APIs, say, defined with QueryEntity just like in your example, you need to specify _key field properly.

            Consider this example:

            Source https://stackoverflow.com/questions/71619576


            Apache ignite startup failure
            Asked 2022-Feb-24 at 18:28

            Apache ignite .net core server node fails to start with the below error, any idea what could be the reason?



            Answered 2022-Feb-24 at 18:19

            Apache Ignite requires Java 8 or Java 11. Java 17 is not yet supported.


            (update: Java 17 support is coming soon: IGNITE-16622)

            Source https://stackoverflow.com/questions/71159713


            Ignite Server Node with CacheJdbcPojoStore / Delay Client Node
            Asked 2022-Feb-24 at 10:37

            I'm using Spring and Ignite Spring to run a pretty simple cluster consisting of one server node and multiple client nodes with varying domain logic.

            Ignite configuration:

            • All nodes connect via TcpCommuncationSpi, TcpDiscoverySpi and TcpDiscoveryVmIpFinder. TcpDiscoveryVmIpFinder.setAddresses only contain the server node.
            • The server node has serveral CacheJdbcPojoStore configured, the database data is loaded after calling Ignition.start(cfg) using ignite.cache("mycachename").loadCache(null).

            After a client node is connected to the server node, it does some domain specific checks to verify data integrity. This works very well if I first start the server node, wait for all data to be loaded and then start the client nodes.

            My problem: if I first start the client nodes, they can't connect to the server node as it is not yet started. They patiently wait for the server node to come up. If I now start the server node, the client nodes connect directly after Ignition.start(cfg) is done on the server node, but BEFORE the CacheJdbcPojoStores are done loading their data. Thus the domain specific integrity checks do fail as there is no data present in the caches yet.

            My goal: I need a way to ensure the client nodes are only able to connect to the server node AFTER all data is loaded in the server node. This would simply the deployment process as well as local development a lot, as there would be no strict ordering of starting the nodes.

            What I tried so far: Fiddling around with ignite.cluster().state(ClusterState.INACTIVE) as well as setting up a manually controlled BaselineTopology. Sadly, both methods simple declare the cluster as not being ready yet and thus I can't even create the caches, let alone load data.

            My question: Is there any way to achieve either:

            1. hook up into the the startup process of the server node so I can load the data in BEFORE it joins the cluster
            2. Declare the server node "not yet ready" until the data is loaded.


            Answered 2022-Feb-24 at 10:37

            Use one of the available data structures like AtomicLong or Semaphore to simulate readiness state. There is no need for internal hooks.

            Added an example below:


            Source https://stackoverflow.com/questions/71169863


            Can't change AllowOverwrite data streamer option for .NET apache ignite thin client
            Asked 2022-Feb-07 at 17:32

            I try to remove some data using the thin client data streamer (.NET apache ignite) but i end up with an exception:

            DataStreamer can't remove data when AllowOverwrite is false.

            My problem is when i try to change AllowOverwrite to true it is not respected.



            Answered 2022-Feb-02 at 12:16

            You are modifying a data streamer after it was created, which is not supported. After the instance is created, you can obtain only a copy of its configuration. Provide the complete configuration on initialization instead:

            Source https://stackoverflow.com/questions/70954848


            Isolated Ignite clusters on same set of machines
            Asked 2022-Feb-04 at 07:27

            I'm using Apache.Ignite NET 2.12.0.

            I tried several approaches to allow two Ignite clusters to be run separately on the machine:

            1. Approach described here. I specified DiscoverySPI and CommunicationSPI port for each instance of server(I use client-server model) to isolate them, but the server failed to run with this warning:

            [05:03:01,968][WARNING][main][TcpDiscoverySpi] Failed to connect to any address from IP finder (make sure IP finder addresses are correct and firewalls are disabled on all host machines): [/, /]

            In that case, the execution enters Ignition.Start and don't leave it.

            1. I tried to provide IgniteConfiguration.SslContextFactory with different certificates to avoid the different clusters seeing each other, but in that case - they see each other, but the clusters fail to join each other, which prevents them from working.

            Is there some easy way to do this?



            Answered 2022-Feb-04 at 06:08

            The approach from the docs works, here is the corresponding C# code, tested with Ignite.NET 2.12:

            Source https://stackoverflow.com/questions/70980731


            What is a "closure" in Julia?
            Asked 2022-Feb-03 at 18:34

            I am learning how to write a Maximum Likelihood implementation in Julia and currently, I am following this material (highly recommended btw!). So the thing is I do not fully understand what a closure is in Julia nor when should I actually use it. Even after reading the official documentation the concept still remain a bit obscure to me.

            For instance, in the tutorial, I mentioned the author defines the log-likelihood function as:



            Answered 2022-Feb-03 at 18:34

            In the context you ask about you can think that closure is a function that references to some variables that are defined in its outer scope (for other cases see the answer by @phipsgabler). Here is a minimal example:

            Source https://stackoverflow.com/questions/70969919


            Why does Apache Ignite use more memory than configured
            Asked 2022-Feb-01 at 00:50

            When using Ignite 2.8.1-1 version and default configuration(1GB heap, 20% default region for off-heap storage and persistence enabled) on a Linux host with 16GB memory, I notice the ignite process could use up to 11GB of memory(verified by checking the resident size of memory used by the process in top, see attachment). When I check the metrics in the log, the consumed memory(heap+off-heap) doesn't add up to close to 7GB. One possibility is the extra memory could be used by the checkpoint buffer but that shall be by default 1/4 of the default region, that is, only about a quarter of 0.25 * 0.2 * 16GB.

            Any hints on what the rest of the memory is used for?




            Answered 2022-Feb-01 at 00:50

            Yes, the checkpoint buffer size is also taken into account here, if you haven't overridden the defaults, it should be 3GB/4 as you correctly highlighted. I wonder if it might be changed automatically since you have a lot more data ^-- Ignite persistence [used=57084MB] stored than the region capacity is - only 3GB. Also, this might be related to Direct Memory usage which I suppose is not being counted for the Java heap usage.

            Anyway, I think it's better to check for Ignite memory metrics explicitly like data region and onheap usage and inspect them in detail.

            Source https://stackoverflow.com/questions/70888632


            Apache Ignite 'Failed to prepare update plan' when executing SQL query on cache
            Asked 2022-Jan-31 at 10:44

            I am playing around with different approaches on how to configure caches and tables in Ignite and then insert an entry via the SQL API using the .NET SDK.

            I create two caches with each having a table. The first is created via CacheClientConfiguration and QueryEntities and the second using the 'CREATE TABLE...' DDL command. I then try to insert the same object (same values) into both tables using 'INSERT INTO...'. For the table created using the 'CREATE Table...' command it works, but the for the table created using QueryEntities i get an IgniteClientException stating: 'Failed to prepare update plan'. Both Insert commands look exactly the same (besides the table name).

            What is the exception trying to tell me, why does the insert work for the second approach but not for the first?

            See example code below.

            Creating caches and tables:



            Answered 2022-Jan-29 at 14:49

            I believe this is because you didn't provide the _KEY to the first query explicitly and would like to keep it on your POJO model.

            Specify the key configuration explicitly using the following configuration and give it a try.

            Source https://stackoverflow.com/questions/70896295


            Apache Ignite unexpectedly deletes IgniteSet
            Asked 2022-Jan-28 at 13:35

            I am facing the problem where my Ignite repository instance unexpectedly closes the opened Ignite set after attempt to save it in map or pass as return value from function.

            So I have Java Spring application where Ignite is used under the hood of Spring Data (master) and Spark application where the same Ignite is used as DB (client). In this case the set is created and filled in Spark application, and in Java app I just want to access it and check set.contains(element).

            On the first part everything looks good - set is created, I can see in logs that its size is correct:



            Answered 2022-Jan-28 at 13:35

            So finally after hours of debug I found the reason and solution.

            First of all, I debugged size of the set each time I open it. And weirdly after first call its size becomes 0, so set is erased after the first call to ignite.set(). After this I switched to plain cache (instead of set) and just check cache.containsKey(user). Its size was persistent among the getOrCreateCache() calls but the NPO problem was still raised.

            Then I found this tiny little answer on Ignite mailing list where it's said that Ignite caches implement AutoCloseable interface. Which means that after try-except block cache.close() is automatically called. And it means not just close the "connection" to cache but stopping the cache itself.

            After this I changed my code to this:

            Source https://stackoverflow.com/questions/70877973


            Apache ignite docker 'image' not compatible on Apple M1 Max
            Asked 2022-Jan-26 at 08:42

            docker run -p 10800:10800 apacheignite/ignite:2.11.1

            WARNING: The requested image's platform (linux/amd64) does not match the detected host platform (linux/arm64/v8) and no specific platform was requested

            How to resolve the above issue ?



            Answered 2022-Jan-13 at 11:02

            Until an ARM image is available, you'll probably have to run it using Rosetta:

            Source https://stackoverflow.com/questions/70685637

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


            No vulnerabilities reported

            Install ignite

            Few pointers to get you started:.
            Quick Start Guide: Essentials of getting a project up and running
            Concepts of the library: Engine, Events & Handlers, State, Metrics
            Full-featured template examples (coming soon)


            Stable API documentation and an overview of the library: https://pytorch.org/ignite/Development version API documentation: https://pytorch.org/ignite/master/FAQ, "Questions on Github" and "Questions on Discuss.PyTorch".Project's Roadmap
            Find more information at:

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