python3Packages.vmas: init at 1.5.2 (#460080)
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@@ -0,0 +1,89 @@
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{
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lib,
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buildPythonPackage,
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fetchFromGitHub,
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gym,
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gym-notices,
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gymnasium,
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matplotlib,
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moviepy,
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numpy,
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opencv4,
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pyglet,
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pytestCheckHook,
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pythonOlder,
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pyyaml,
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setuptools,
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shimmy,
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six,
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torch,
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tqdm,
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}:
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buildPythonPackage rec {
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pname = "vmas";
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version = "1.5.2";
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pyproject = true;
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# dependency "gym" broken
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disabled = pythonOlder "3.12";
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src = fetchFromGitHub {
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owner = "proroklab";
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repo = "VectorizedMultiAgentSimulator";
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tag = version;
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hash = "sha256-i1dr65IPIOGAH/1jXS7+PnxJzl986+fGB7M4ydisIrs=";
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};
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build-system = [ setuptools ];
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dependencies = [
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gym
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gym-notices
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numpy
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pyglet
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six
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torch
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];
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optional-dependencies = {
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gymnasium = [
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gymnasium
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shimmy
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];
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render = [
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matplotlib
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moviepy
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opencv4
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];
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};
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pythonRelaxDeps = [
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"gym-notices"
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"pyglet"
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];
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disabledTests = [
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# pyglet.display.xlib.NoSuchDisplayException: Cannot connect to "None"
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"test_use_vmas_env"
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# Missing python3Packages.cvxpylayers
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"test_heuristic"
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];
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nativeCheckInputs = [
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pytestCheckHook
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pyyaml
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tqdm
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]
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++ optional-dependencies.gymnasium;
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pythonImportsCheck = [ "vmas" ];
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meta = {
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description = "A vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking";
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homepage = "https://github.com/proroklab/VectorizedMultiAgentSimulator";
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license = lib.licenses.gpl3Only;
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maintainers = with lib.maintainers; [ derdennisop ];
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};
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}
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@@ -19994,6 +19994,8 @@ self: super: with self; {
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vllm = callPackage ../development/python-modules/vllm { };
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vmas = callPackage ../development/python-modules/vmas { };
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vmprof = callPackage ../development/python-modules/vmprof { };
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vncdo = callPackage ../development/python-modules/vncdo { };
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