rlax | library built on top of JAX that exposes useful building | Reinforcement Learning library

 by   deepmind Python Version: 0.1.6 License: Apache-2.0

kandi X-RAY | rlax Summary

kandi X-RAY | rlax Summary

rlax is a Python library typically used in Artificial Intelligence, Reinforcement Learning applications. rlax has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install rlax' or download it from GitHub, PyPI.

RLax (pronounced "relax") is a library built on top of JAX that exposes useful building blocks for implementing reinforcement learning agents. Full documentation can be found at rlax.readthedocs.io.

            kandi-support Support

              rlax has a medium active ecosystem.
              It has 1025 star(s) with 73 fork(s). There are 32 watchers for this library.
              There were 1 major release(s) in the last 6 months.
              There are 6 open issues and 18 have been closed. On average issues are closed in 38 days. There are 5 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of rlax is 0.1.6

            kandi-Quality Quality

              rlax has 0 bugs and 3 code smells.

            kandi-Security Security

              rlax has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              rlax code analysis shows 0 unresolved vulnerabilities.
              There are 1 security hotspots that need review.

            kandi-License License

              rlax 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.

            kandi-Reuse Reuse

              rlax 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 are available. Examples and code snippets are not available.
              rlax saves you 2539 person hours of effort in developing the same functionality from scratch.
              It has 5520 lines of code, 472 functions and 44 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed rlax and discovered the below as its top functions. This is intended to give you an instant insight into rlax implemented functionality, and help decide if they suit your requirements.
            • Computes the mean objective loss
            • Compute weights and temperature loss
            • Computes the KL loss for a given penalty
            • Computes the KL loss and dual loss for the given constraints
            • Calculate MPOO loss
            • Creates a leaky vtrace output
            • Performs leaky_vtrace
            • Gets the generalized off - policy returns from the given values
            • Calculate general off - policy returns from q and v
            • Generate a PopArt
            • Perform a PopArt operation
            • Cross replicas
            • Compute the KL loss for a given axis
            • Create an EmaState
            • Calculate the dpg loss between two arrays
            • Deprecated
            • Compute a TxPair between two bins
            • Compose a two - hot pair
            • Unnormalize the input array
            • Replaces masked values with replacement
            • Decorator for transform_targets
            • Deprecated_update
            • Check for documentation
            • Get the module version
            • Parse requirements file
            • Recursively add all python files
            Get all kandi verified functions for this library.

            rlax Key Features

            No Key Features are available at this moment for rlax.

            rlax Examples and Code Snippets

            No Code Snippets are available at this moment for rlax.

            Community Discussions

            Trending Discussions on rlax


            when is sign extension done?
            Asked 2020-Oct-15 at 16:11

            I am compiling C for the MSP430. I'm wondering what the specific rules are for when sign extension is done for chars (or (u)int8_t) to the register size (16 bit) I found that sign extension will be done when the MSB of the destination operand will affect the correct result of the instruction and all succeeding instructions. However, this does not really explain it I think. For example when looking at this code:



            Answered 2020-Oct-15 at 14:06

            Let f(a, b,…) be a function of signed objects a, b,… Let a', b',… be the values of those objects reinterpreted as unsigned. If, for all values of a, b,… (in their signed types), the reinterpretation of f(a, b,…) as unsigned equals f(a', b',…), then no sign extension of a, b,… is needed when evaluating f.

            This is evident because, if the condition is satisfied, then f(a', b',…) produces the bits required to represent f(a, b,…). However, it may be incomplete. We might have some f(a, b) that requires a sign extension of a but not of b, and that is not directly addressed by the above. However, it could be considered included in that f(a, b) may be expressed as a function ga(b), and then the above tells us no sign extension of b is needed when evaluating ga. If this is true for all ga, then evaluating f(a, b) does not require sign extension of b.

            Also, the fact that a sign extension is not needed does not imply a compiler will necessarily detect this and generate code without sign extension. A compiler might generate sign extension even if it is not necessary. I think this may be seen in sint8fun; I would expect (int8_t) (a+b)*2 to be evaluable as an addition and a shift without sign extension. However, the compiler may be failing to account for the fact that the expression is converted to int8_t by the return. By itself, (a+b)*2 does require sign extension, as it could produce a negative int result that it would not if the signs were not extended. It is only after the conversion to int8_t that the result is then independent of sign extension.

            Source https://stackoverflow.com/questions/64370346

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


            No vulnerabilities reported

            Install rlax

            RLax can be installed with pip directly from github, with the following command:. All RLax code may then be just in time compiled for different hardware (e.g. CPU, GPU, TPU) using jax.jit. In order to run the examples/ you will also need to clone the repo and install the additional requirements: optax, haiku, and bsuite.


            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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          • PyPI

            pip install rlax

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          • CLI

            gh repo clone deepmind/rlax

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