{
    "info": {
        "author": "Thiago P. Bueno",
        "author_email": "thiago.pbueno@gmail.com",
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        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Environment :: Console",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
            "Natural Language :: English",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering :: Artificial Intelligence"
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        "description": "# rddl2tf [![Build Status](https://travis-ci.org/thiagopbueno/rddl2tf.svg?branch=master)](https://travis-ci.org/thiagopbueno/rddl2tf) [![Documentation Status](https://readthedocs.org/projects/rddl2tf/badge/?version=latest)](https://rddl2tf.readthedocs.io/en/latest/?badge=latest) [![License](https://img.shields.io/aur/license/yaourt.svg)](https://github.com/thiagopbueno/rddl2tf/blob/master/LICENSE)\n\nRDDL2TensorFlow compiler in Python3.\n\n# Quickstart\n\n**rddl2tf** is a Python 3.5+ package available in PyPI.\n\n```text\n$ pip3 install rddl2tf\n```\n\n\n# Usage\n\nrddl2tf can be used as a standalone script or programmatically.\n\n\n## Script mode\n\n```text\n$ rddl2tf --help\nusage: rddl2tf [-h] [-b BATCH_SIZE] [--logdir LOGDIR] rddl\n\nrddl2tf (v0.5.1): RDDL2TensorFlow compiler in Python3.\n\npositional arguments:\n  rddl                  path to RDDL file or rddlgym problem id\n\noptional arguments:\n  -h, --help            show this help message and exit\n  -b BATCH_SIZE, --batch-size BATCH_SIZE\n                        number of fluents in a batch (default=256)\n  --logdir LOGDIR       log directory for tensorboard graph visualization\n                        (default=/tmp/rddl2tf)\n```\n\n### Examples\n\n```text\n$ rddl2tf Reservoir-8 --batch-size=1024 --logdir=/tmp/rddl2tf\ntensorboard --logdir /tmp/rddl2tf/reservoir/inst_reservoir_res8\n```\n\n```text\n$ rddl2tf Mars_Rover --batch-size=1024 --logdir=/tmp/rddl2tf\ntensorboard --logdir /tmp/rddl2tf/simple_mars_rover/inst_simple_mars_rover_pics3\n```\n\n\n## Programmatic mode\n\n```python\nimport rddlgym\n\nfrom rddl2tf.compiler import Compiler\n\n# parse and compile RDDL\nmodel_id = 'Reservoir-8'\nmodel = rddlgym.make(model_id, mode=rddlgym.AST)\ncompiler = Compiler(model)\n\n# set batch mode\ncompiler.batch_mode_on()\nbatch_size = 256\n\n# compile initial state and default action fluents\nstate = compiler.compile_initial_state(batch_size)\naction = compiler.compile_default_action(batch_size)\n\n# compile state invariants and action preconditions\ninvariants = compiler.compile_state_invariants(state)\npreconditions = compiler.compile_action_preconditions(state, action)\n\n# compile action bounds\nbounds = compiler.compile_action_bound_constraints(state)\n\n# compile intermediate fluents and next state fluents\nscope = compiler.transition_scope(state, action)\ninterms, next_state = compiler.compile_cpfs(scope, batch_size)\n\n# compile reward function\nscope.update(next_state)\nreward = compiler.compile_reward(scope)\n```\n\n\n# Compiler\n\n## Core API methods\n\n- `rddl2tf.Compiler.compile_initial_state`\n- `rddl2tf.Compiler.compile_default_action`\n- `rddl2tf.Compiler.compile_cpfs`\n- `rddl2tf.Compiler.compile_intermediate_cpfs`\n- `rddl2tf.Compiler.compile_state_cpfs`\n- `rddl2tf.Compiler.compile_reward`\n- `rddl2tf.Compiler.compile_state_action_constraints`\n- `rddl2tf.Compiler.compile_action_preconditions`\n- `rddl2tf.Compiler.compile_state_invariants`\n- `rddl2tf.Compiler.compile_action_preconditions_checking`\n- `rddl2tf.Compiler.compile_action_bound_constraints`\n\n\n## Parameterized Variables (pvariables)\n\nEach RDDL fluent is compiled to a ``rddl2tf.TensorFluent`` after instantiation.\n\nA ``rddl2tf.TensorFluent`` object wraps a ``tf.Tensor`` object. The arity and the number of objects corresponding to the type of each parameter of a fluent are reflected in a ``rddl2tf.TensorFluentShape`` object (the rank of a ``rddl2tf.TensorFluent`` corresponds to the fluent arity and the size of its dimensions corresponds to the number of objects of each type). Also, a ``rddl2tf.TensorFluentShape`` manages batch sizes when evaluating operations in batch mode.\n\nAdditionally, a ``rddl2tf.TensorFluent``keeps information about the ordering of the fluent parameters in a ``rddl2tf.TensorScope`` object.\n\nThe ``rddl2tf.TensorFluent`` abstraction is necessary in the evaluation of RDDL expressions due the broadcasting rules of operations in TensorFlow.\n\n\n## Conditional Probability Functions (CPFs)\n\nEach CPF expression is compiled into an operation in a ``tf.Graph``, possibly composed of many other operations. Typical RDDL operations, functions, and probability distributions are mapped to equivalent TensorFlow ops. These operations are added to a ``tf.Graph`` by recursively compiling the expressions in a CPF into wrapped operations and functions implemented at the ``rddl2tf.TensorFluent`` level.\n\nNote that the RDDL2TensorFlow compiler currently only supports element-wise operations (e.g. ``a(?x, ?y) = b(?x) * c(?y)`` is not allowed). However, all compiled operations are vectorized, i.e., computations are done simultaneously for all object instantiations of a pvariable.\n\nOptionally, during simulation operations can be evaluated in batch mode. In this case, state-action trajectories are generated in parallel by the ``rddl2tf.Simulator``.\n\n\n# Documentation\n\nPlease refer to [https://rddl2tf.readthedocs.io/](https://rddl2tf.readthedocs.io/en/latest/) for the code documentation.\n\n\n# Support\n\nIf you are having issues with ``rddl2tf``, please let me know at: [thiago.pbueno@gmail.com](mailto://thiago.pbueno@gmail.com).\n\n\n# License\n\nCopyright (c) 2018-2019 Thiago Pereira Bueno All Rights Reserved.\n\nrddl2tf is free software: you can redistribute it and/or modify it\nunder the terms of the GNU Lesser General Public License as published by\nthe Free Software Foundation, either version 3 of the License, or (at\nyour option) any later version.\n\nrddl2tf is distributed in the hope that it will be useful, but\nWITHOUT ANY WARRANTY; without even the implied warranty of\nMERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser\nGeneral Public License for more details.\n\nYou should have received a copy of the GNU Lesser General Public License\nalong with rddl2tf. If not, see http://www.gnu.org/licenses/.",
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