%global _empty_manifest_terminate_build 0 Name: python-minerl Version: 0.4.4 Release: 1 Summary: MineRL environment and data loader for reinforcement learning from human demonstration in Minecraft License: MIT URL: http://github.com/minerllabs/minerl Source0: https://mirrors.nju.edu.cn/pypi/web/packages/08/c1/651340d34dc6a165821c8aba61903db7c5ac874827efb185e78e35086835/minerl-0.4.4.tar.gz BuildArch: noarch %description # The [MineRL](http://minerl.io) Python Package [![Documentation Status](https://readthedocs.org/projects/minerl/badge/?version=latest)](https://minerl.readthedocs.io/en/latest/?badge=latest) [![Dev Build status](https://badge.buildkite.com/0717cd35b9a708f0b4ac0b2858eec9ca7d08f6768868d3ac08.svg?branch=dev)](https://buildkite.com/openai-mono/minerl-public-dev) [![Downloads](https://pepy.tech/badge/minerl)](https://pepy.tech/project/minerl) [![PyPI version](https://badge.fury.io/py/minerl.svg)](https://badge.fury.io/py/minerl) [!["Open Issues"](https://img.shields.io/github/issues-raw/minerllabs/minerl.svg)](https://github.com/minerllabs/minerl/issues) [![GitHub issues by-label](https://img.shields.io/github/issues/minerllabs/minerl/bug.svg?color=red)](https://github.com/minerllabs/minerl/issues?utf8=%E2%9C%93&q=is%3Aissue+is%3Aopen+label%3Abug) [![Discord](https://img.shields.io/discord/565639094860775436.svg?label=&logo=discord&logoColor=ffffff&color=7389D8&labelColor=6A7EC2)](https://discord.gg/BT9uegr) Python package providing easy to use gym environments and a simple data api for the MineRLv0 dataset. **To [get started please read the docs here](http://minerl.io/docs/)!** ![](http://www.minerl.io/docs/_images/demo.gif) ## Installation With JDK-8 installed run this command ``` pip3 install --upgrade minerl ``` ## Basic Usage Running an environment: ```python import minerl import gym env = gym.make('MineRLNavigateDense-v0') obs = env.reset() done = False while not done: action = env.action_space.sample() # One can also take a no_op action with # action =env.action_space.noop() obs, reward, done, info = env.step( action) ``` Sampling the dataset: ```python import minerl # YOU ONLY NEED TO DO THIS ONCE! minerl.data.download('/your/local/path') data = minerl.data.make( 'MineRLObtainDiamond-v0', data_dir='/your/local/path') # Iterate through a single epoch gathering sequences of at most 32 steps for current_state, action, reward, next_state, done \ in data.batch_iter( num_epochs=1, seq_len=32): # Print the POV @ the first step of the sequence print(current_state['pov'][0]) # Print the final reward pf the sequence! print(reward[-1]) # Check if final (next_state) is terminal. print(done[-1]) # ... do something with the data. print("At the end of trajectories the length" "can be < max_sequence_len", len(reward)) ``` Visualizing the dataset: ![viewer|540x272](http://www.minerl.io/docs/_images/cropped_viewer.gif) ```bash # Make sure your MINERL_DATA_ROOT is set! export MINERL_DATA_ROOT='/your/local/path' # Visualizes a random trajectory of MineRLObtainDiamondDense-v0 python3 -m minerl.viewer MineRLObtainDiamondDense-v0 ``` ## MineRL Competition If you're here for the MineRL competition. Please check [the main competition website here](https://www.aicrowd.com/challenges/neurips-2021-minerl-competition). %package -n python3-minerl Summary: MineRL environment and data loader for reinforcement learning from human demonstration in Minecraft Provides: python-minerl BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-minerl # The [MineRL](http://minerl.io) Python Package [![Documentation Status](https://readthedocs.org/projects/minerl/badge/?version=latest)](https://minerl.readthedocs.io/en/latest/?badge=latest) [![Dev Build status](https://badge.buildkite.com/0717cd35b9a708f0b4ac0b2858eec9ca7d08f6768868d3ac08.svg?branch=dev)](https://buildkite.com/openai-mono/minerl-public-dev) [![Downloads](https://pepy.tech/badge/minerl)](https://pepy.tech/project/minerl) [![PyPI version](https://badge.fury.io/py/minerl.svg)](https://badge.fury.io/py/minerl) [!["Open Issues"](https://img.shields.io/github/issues-raw/minerllabs/minerl.svg)](https://github.com/minerllabs/minerl/issues) [![GitHub issues by-label](https://img.shields.io/github/issues/minerllabs/minerl/bug.svg?color=red)](https://github.com/minerllabs/minerl/issues?utf8=%E2%9C%93&q=is%3Aissue+is%3Aopen+label%3Abug) [![Discord](https://img.shields.io/discord/565639094860775436.svg?label=&logo=discord&logoColor=ffffff&color=7389D8&labelColor=6A7EC2)](https://discord.gg/BT9uegr) Python package providing easy to use gym environments and a simple data api for the MineRLv0 dataset. **To [get started please read the docs here](http://minerl.io/docs/)!** ![](http://www.minerl.io/docs/_images/demo.gif) ## Installation With JDK-8 installed run this command ``` pip3 install --upgrade minerl ``` ## Basic Usage Running an environment: ```python import minerl import gym env = gym.make('MineRLNavigateDense-v0') obs = env.reset() done = False while not done: action = env.action_space.sample() # One can also take a no_op action with # action =env.action_space.noop() obs, reward, done, info = env.step( action) ``` Sampling the dataset: ```python import minerl # YOU ONLY NEED TO DO THIS ONCE! minerl.data.download('/your/local/path') data = minerl.data.make( 'MineRLObtainDiamond-v0', data_dir='/your/local/path') # Iterate through a single epoch gathering sequences of at most 32 steps for current_state, action, reward, next_state, done \ in data.batch_iter( num_epochs=1, seq_len=32): # Print the POV @ the first step of the sequence print(current_state['pov'][0]) # Print the final reward pf the sequence! print(reward[-1]) # Check if final (next_state) is terminal. print(done[-1]) # ... do something with the data. print("At the end of trajectories the length" "can be < max_sequence_len", len(reward)) ``` Visualizing the dataset: ![viewer|540x272](http://www.minerl.io/docs/_images/cropped_viewer.gif) ```bash # Make sure your MINERL_DATA_ROOT is set! export MINERL_DATA_ROOT='/your/local/path' # Visualizes a random trajectory of MineRLObtainDiamondDense-v0 python3 -m minerl.viewer MineRLObtainDiamondDense-v0 ``` ## MineRL Competition If you're here for the MineRL competition. Please check [the main competition website here](https://www.aicrowd.com/challenges/neurips-2021-minerl-competition). %package help Summary: Development documents and examples for minerl Provides: python3-minerl-doc %description help # The [MineRL](http://minerl.io) Python Package [![Documentation Status](https://readthedocs.org/projects/minerl/badge/?version=latest)](https://minerl.readthedocs.io/en/latest/?badge=latest) [![Dev Build status](https://badge.buildkite.com/0717cd35b9a708f0b4ac0b2858eec9ca7d08f6768868d3ac08.svg?branch=dev)](https://buildkite.com/openai-mono/minerl-public-dev) [![Downloads](https://pepy.tech/badge/minerl)](https://pepy.tech/project/minerl) [![PyPI version](https://badge.fury.io/py/minerl.svg)](https://badge.fury.io/py/minerl) [!["Open Issues"](https://img.shields.io/github/issues-raw/minerllabs/minerl.svg)](https://github.com/minerllabs/minerl/issues) [![GitHub issues by-label](https://img.shields.io/github/issues/minerllabs/minerl/bug.svg?color=red)](https://github.com/minerllabs/minerl/issues?utf8=%E2%9C%93&q=is%3Aissue+is%3Aopen+label%3Abug) [![Discord](https://img.shields.io/discord/565639094860775436.svg?label=&logo=discord&logoColor=ffffff&color=7389D8&labelColor=6A7EC2)](https://discord.gg/BT9uegr) Python package providing easy to use gym environments and a simple data api for the MineRLv0 dataset. **To [get started please read the docs here](http://minerl.io/docs/)!** ![](http://www.minerl.io/docs/_images/demo.gif) ## Installation With JDK-8 installed run this command ``` pip3 install --upgrade minerl ``` ## Basic Usage Running an environment: ```python import minerl import gym env = gym.make('MineRLNavigateDense-v0') obs = env.reset() done = False while not done: action = env.action_space.sample() # One can also take a no_op action with # action =env.action_space.noop() obs, reward, done, info = env.step( action) ``` Sampling the dataset: ```python import minerl # YOU ONLY NEED TO DO THIS ONCE! minerl.data.download('/your/local/path') data = minerl.data.make( 'MineRLObtainDiamond-v0', data_dir='/your/local/path') # Iterate through a single epoch gathering sequences of at most 32 steps for current_state, action, reward, next_state, done \ in data.batch_iter( num_epochs=1, seq_len=32): # Print the POV @ the first step of the sequence print(current_state['pov'][0]) # Print the final reward pf the sequence! print(reward[-1]) # Check if final (next_state) is terminal. print(done[-1]) # ... do something with the data. print("At the end of trajectories the length" "can be < max_sequence_len", len(reward)) ``` Visualizing the dataset: ![viewer|540x272](http://www.minerl.io/docs/_images/cropped_viewer.gif) ```bash # Make sure your MINERL_DATA_ROOT is set! export MINERL_DATA_ROOT='/your/local/path' # Visualizes a random trajectory of MineRLObtainDiamondDense-v0 python3 -m minerl.viewer MineRLObtainDiamondDense-v0 ``` ## MineRL Competition If you're here for the MineRL competition. Please check [the main competition website here](https://www.aicrowd.com/challenges/neurips-2021-minerl-competition). %prep %autosetup -n minerl-0.4.4 %build %py3_build %install %py3_install install -d -m755 %{buildroot}/%{_pkgdocdir} if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi pushd %{buildroot} if [ -d usr/lib ]; then find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst fi popd mv %{buildroot}/filelist.lst . mv %{buildroot}/doclist.lst . %files -n python3-minerl -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Wed May 31 2023 Python_Bot - 0.4.4-1 - Package Spec generated