slac | Stochastic Latent Actor-Critic : Deep Reinforcement Learning | Reinforcement Learning library

 by   alexlee-gk Python Version: Current License: MIT

kandi X-RAY | slac Summary

kandi X-RAY | slac Summary

slac is a Python library typically used in Artificial Intelligence, Reinforcement Learning, Deep Learning, Pytorch applications. slac 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.

Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model
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              slac has a low active ecosystem.
              It has 120 star(s) with 26 fork(s). There are 17 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 3 open issues and 0 have been closed. On average issues are closed in 308 days. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of slac is current.

            kandi-Quality Quality

              slac has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              slac 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

              slac 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.
              Installation instructions, examples and code snippets are available.
              slac saves you 1278 person hours of effort in developing the same functionality from scratch.
              It has 2872 lines of code, 112 functions and 19 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed slac and discovered the below as its top functions. This is intended to give you an instant insight into slac implemented functionality, and help decide if they suit your requirements.
            • Train the CrossCheetah model
            • Compute the summaries of the given metrics
            • Returns the path to train eval eval_dir
            • Pad and concatenate multiple videos
            • Gets the control timestep
            • Summarize images
            • Loads environments for a given universe
            • Create a summary writer
            • Returns a single step
            • Encodes images using ffmpeg
            • Create a TensorFlow summary
            • Returns a tensorflow distribution
            • Convenience wrapper for images
            • Filter steps before first step
            • Apply actor network
            • Step the given action
            • Modify an observation
            • Forward an action
            • Modify observation
            • Reset the environment
            Get all kandi verified functions for this library.

            slac Key Features

            No Key Features are available at this moment for slac.

            slac Examples and Code Snippets

            No Code Snippets are available at this moment for slac.

            Community Discussions

            QUESTION

            Renault Zoe doesn't send SDP Request After SLAC Matching Process
            Asked 2022-Feb-25 at 12:01

            We are trying to communicate with Renault Zoe according to DIN SPEC 70121.

            We are successfully communciating with the Hyundai Kona and BMW i3 but fail to receive the SPD Request with Renault Zoe. We are passing the SLAC process with Renault Zoe but we don't recieve any UDP messages afterwards. We are sending the CM_SLAC_MATCH_CNF message as an ethernet unicast message according to DIN SPEC 70121:2014-12, 8.3.3.3.2, Table 2 (noted in Design Guide Combined Charging System V5 - Failures during SLAC - Interruption at SLAC match sequence).

            Why can it be that we receive the SDP Request with Kona and i3 but fail to do so with Zoe? Has anyone experienced this behaviour before?

            Sniffed SLAC messages with scapy:

            (= '' means the field is filled with zeroes)

            Received from Zoe:

            ...

            ANSWER

            Answered 2022-Feb-25 at 12:01

            The solution was to send the 2 byte field MatchVariableFieldLen in the CM_SLAC_MATCH_CNF message in little-endian byte order.

            From the message that was send by the Renault Zoe, we can see that Zoe sends the CM_SLAC_MATCH_REQ with the MatchVariableFieldLen as 0x3e 0x00 (15872 == 0x3e00). Since this field should be 0x3e according to DIN SPEC 2014-12, we can see the byte order of this field is little-endian. So a reasonable guess was that it expects this field in little-endian in the response message.

            Result: We received the SDP request and the messages after that.

            The HomePlug GP Specification does not specify the endianness of this field in clause 11.5.58. But looking at the example in Table 11-316, one would say its big-endian.

            It's clear that Zoe interpret this field as little-endian and doesn't accept 0x00 0x56 but accepts 0x56 0x00.

            Kona and i3 either don't complain about this field and accept the message or Zoe's intepreting is false. Either way the cause of the problem has been identified.

            Source https://stackoverflow.com/questions/71237398

            QUESTION

            Analog fuction to xaxis in Numpy array
            Asked 2021-Jul-05 at 19:10

            I´m looking for any similar function to axis. using numpy array I´m trying to generate subplots and I set different parameters to generate three plots. Here the package that I´m using:

            ...

            ANSWER

            Answered 2021-Jul-05 at 19:10

            Add this line to the script:

            Source https://stackoverflow.com/questions/68258237

            QUESTION

            Low latency video player on android
            Asked 2021-May-20 at 11:24

            I'd like to be able to stream the video from my webcam to an Android app with a latency below 500ms, on my local network.

            To capture and send the video over the network, I use ffmpeg.

            ...

            ANSWER

            Answered 2021-May-20 at 11:24

            I do not know a native low latency player in Android.
            However you can use a WebView in Android Studio and use a player in the web.
            With this solution I streamed the webcam of my pc to my phone (in the local network) with livecam.
            They use websockets to transmit the video frame by frame, which is not ideal. With this method I had 370 ms of latency.

            Source https://stackoverflow.com/questions/67572522

            QUESTION

            LOG: connection failed during start up processing: user= database= FATAL: GSSAPI authentication failed for user "postgres"
            Asked 2020-Sep-23 at 18:47

            I am trying to configure Kerberos for GSSAPI Currently I have two nodes One the KDC server (windows server 2016) and the the other is Postgres-server(Ubuntu). I have created Active directory on in kdc-server and create user with the name of postgres and selected the option "password will never expire".

            Then I have installed a kerbrose client of MIT. here is krb5.ini on kdc server.

            ...

            ANSWER

            Answered 2020-Aug-18 at 19:24

            This is a common issue experienced in earlier releases of Postgres and EDB Postgres v. 12, since GSSAPI encryption has been added, but a bug existed. The bug has been fixed in commit 79e594cf04754d55196d2ce54fc869ccad5fa9c3, released in v. 12.3. If you can upgrade to v. 12.3, you may be able to work around this issue.

            If you require use of an older client for some reason, please be sure to set gssencmode=disable in your connection string or set PGGSSAPIENCMODE=disable in your environment.

            Source https://stackoverflow.com/questions/63469679

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

            Vulnerabilities

            No vulnerabilities reported

            Install slac

            Clone this repo:
            To use the DeepMind Control Suite, follow the instructions in the dm_control package.
            To use OpenAI Gym , follow the instructions in the gym and mujoco_py packages.
            Modify the requirements.txt file if necessary: Replace tf-nightly-gpu with tf-nightly if using CPU. Omit gym, mujoco-py, or dm_control accordingly if only using one of the suites.
            Install python packages:
            Install the tf_agents package:
            Install ffmpeg (optional, used to generate GIFs for visualization in TensorBoard).
            For some python installations, the root directory should be added to the PYTHONPATH:

            Support

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            https://github.com/alexlee-gk/slac.git

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            gh repo clone alexlee-gk/slac

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            git@github.com:alexlee-gk/slac.git

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