byol | PyTorch implementation of BYOL | Machine Learning library

 by   fkodom Python Version: Current License: MIT

kandi X-RAY | byol Summary

kandi X-RAY | byol Summary

byol is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. byol 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.

PyTorch implementation of BYOL: a fantastically simple method for self-supervised image representation learning with SOTA performance. Strongly influenced and inspired by this Github repo, but with a few notable differences:.
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            kandi-support Support

              byol has a low active ecosystem.
              It has 7 star(s) with 1 fork(s). There are 2 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              byol has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of byol is current.

            kandi-Quality Quality

              byol has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              byol 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

              byol releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              It has 482 lines of code, 43 functions and 8 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed byol and discovered the below as its top functions. This is intended to give you an instant insight into byol implemented functionality, and help decide if they suit your requirements.
            • Performs the training step
            • Project x onto x
            • Create a Module for MLP
            • Returns the projector
            • Return the normalized MSE between x and y
            • Calculate the normalized mean loss
            • Forward a tensor
            • Return the predicted tensor
            • Update the target
            • Update the targets
            • Update target parameters
            • Perform a training step
            • Return the forward function
            • Train a model
            • Get data loader
            • Implementation of the hook
            • Evaluate the validation step
            • Performs training step
            Get all kandi verified functions for this library.

            byol Key Features

            No Key Features are available at this moment for byol.

            byol Examples and Code Snippets

            No Code Snippets are available at this moment for byol.

            Community Discussions

            QUESTION

            How to know the trained model is correct?
            Asked 2022-Mar-21 at 16:05

            I use PyTorch Lightning for model training, during which I use ModelCheckpoint to save loading points. Finally, I would like to know whether the model is loaded correctly. Let me know if you require further information?

            ...

            ANSWER

            Answered 2022-Mar-21 at 16:05

            load_from_checkpoint() will return a model with trained weights, so you need to assign it to a new variable.

            Source https://stackoverflow.com/questions/71558917

            QUESTION

            Parse json with jq in aws cli
            Asked 2021-Dec-14 at 16:30

            i need an output similar to this

            ...

            ANSWER

            Answered 2021-Dec-14 at 16:30

            QUESTION

            AWS: Dedicated Host VS Dedicated Instance, why the first is more expensive than the later?
            Asked 2020-Oct-12 at 06:36

            I'm studying for my Associate Architect exam at AWS, and I can't find an explanation for this question. Why Dedicated Host are more expensive than Dedicated Instances? I understand the main differences between the two, it is just that in my brain it doesn't make sense.

            This is my perspective: if you ask for a dedicated host, you control the entire hardware. CPUs, RAM, Sockets, etc. You can use your own license (BYOL). But if you ask for a Dedicated Instance, the hardware it is still just for you. Your AWS account is still the only one using that hardware. You have less control over it, but even though you are locking down a single piece of hardware just for your purposes.

            So, why dedicated hosts are more expensive than dedicated instances, if after all, in either case, you "own" the hardware? Again, in either case, AWS won't be able to use that hardware for something else.

            ...

            ANSWER

            Answered 2020-Oct-12 at 06:36

            you are locking down a single piece of hardware just for your purposes.

            Dedicated Instance does not work like this. Your instance runs on some dedicated hardware. Its not lockdown to you. If you stop/start instance, you can get some other hardware somewhere else. Basically, the hardware is "yours" (you are not sharing it with others) for the time your instance is running. You stop/start it, you may get different physical machine later on (maybe older, maybe newer, maybe its specs will be a bit different), and so on. So your instance is moved around on different physical servers - whichever is not occupied by others at the time.

            With Dedicated Host the physical server is basically yours. It does not change, it's always the same physical machine for as long as you are paying.

            Source https://stackoverflow.com/questions/64309679

            QUESTION

            AWS EC2 import-image: ClientError: Disk validation failed [We do not have access to the given resource. Reason 403 Forbidden
            Asked 2020-Sep-22 at 14:24

            I have an S3 bucket which contains my ova file. The file name does not contain space, etc. The S3 bucket is in my default region. I have created the role and trusting policy as described in https://docs.aws.amazon.com/vm-import/latest/userguide/vmimport-image-import.html#import-image-prereqs

            Command used:

            I call the following command to start the import:

            ...

            ANSWER

            Answered 2020-Sep-22 at 14:24

            Make sure the vmimport policy attached to vmimport role allows access to the S3 bucket containing your .ova files.

            If you copied the policy from the documentation verbatim, you will need to edit it to explicitly grant access to your S3 buckets.

            This section:

            Source https://stackoverflow.com/questions/63933702

            QUESTION

            Compare two nested objects by its keys and get the matched object/array
            Asked 2020-Mar-10 at 10:23

            I have 2 objects a and diff I need the matching array or object from nested object "a".

            The INPUT as below :

            ...

            ANSWER

            Answered 2020-Mar-10 at 10:23

            Loop through diff properties and add each property of diff to output as field and its value from the a object :

            Source https://stackoverflow.com/questions/60613793

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

            Vulnerabilities

            No vulnerabilities reported

            Install byol

            You can download it from GitHub.
            You can use byol 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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          • HTTPS

            https://github.com/fkodom/byol.git

          • CLI

            gh repo clone fkodom/byol

          • sshUrl

            git@github.com:fkodom/byol.git

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