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Modifies Installation Instructions for black - #201

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prabhatnagarajan:black_install
Dec 14, 2025
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Modifies Installation Instructions for black#201
muupan merged 3 commits into
pfnet:masterfrom
prabhatnagarajan:black_install

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@prabhatnagarajan

@prabhatnagarajan prabhatnagarajan commented Nov 28, 2025 •
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I rewrite the installation instructions for installing the linter.

@prabhatnagarajan

prabhatnagarajan commented Dec 11, 2025

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@keisuke-nakata following up for a review when you have time.

keisuke-nakata
keisuke-nakata reviewed Dec 11, 2025
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Update CONTRIBUTING.md
ec2c54d 
Co-authored-by: NAKATA Keisuke <keisuke.nakata.919@gmail.com>
keisuke-nakata
keisuke-nakata approved these changes Dec 11, 2025
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LGTM!

@prabhatnagarajan

prabhatnagarajan commented Dec 11, 2025

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@keisuke-nakata I think I need you to run tests.

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keisuke-nakata commented Dec 11, 2025

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/test

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Successfully created a job for commit ec2c54d:

@keisuke-nakata

keisuke-nakata commented Dec 11, 2025

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The failing tests seem to be unrelated to this PR, but the merge policy requires all tests to pass before merging.
@prabhatnagarajan Can you see the CI (pfrl.lint) log?
If not, please refer the log I copied from CI:

00:00:07.537305 STDOUT 1192]	--- /tmp/flexci/run-00417839/work/src/examples/atari/train_drqn_ale.py	2025-12-11 06:50:13.036945+00:00	
00:00:07.537318 STDOUT 1192]	+++ /tmp/flexci/run-00417839/work/src/examples/atari/train_drqn_ale.py	2025-12-11 06:50:18.769362+00:00	
00:00:07.537326 STDOUT 1192]	@@ -7,10 +7,11 @@	
00:00:07.537561 STDOUT 1192]	     python train_drqn_ale.py --recurrent	
00:00:07.537563 STDOUT 1192]		
00:00:07.537566 STDOUT 1192]	 To train DQRN using a recurrent model on flickering 1-frame Breakout, run:	
00:00:07.537592 STDOUT 1192]	     python train_drqn_ale.py --recurrent --flicker --no-frame-stack	
00:00:07.537593 STDOUT 1192]	 """	
00:00:07.537596 STDOUT 1192]	+	
00:00:07.537622 STDOUT 1192]	 import argparse	
00:00:07.537623 STDOUT 1192]		
00:00:07.537626 STDOUT 1192]	 import gym	
00:00:07.537651 STDOUT 1192]	 import gym.wrappers	
00:00:07.537653 STDOUT 1192]	 import numpy as np	
00:00:07.538090 STDERR 1192]	would reformat /tmp/flexci/run-00417839/work/src/examples/atari/train_drqn_ale.py	
00:00:07.626010 STDOUT 1192]	--- /tmp/flexci/run-00417839/work/src/examples/atari/train_ppo_ale.py	2025-12-11 06:50:13.036945+00:00	
00:00:07.626023 STDOUT 1192]	+++ /tmp/flexci/run-00417839/work/src/examples/atari/train_ppo_ale.py	2025-12-11 06:50:18.860875+00:00	
00:00:07.626031 STDOUT 1192]	@@ -6,10 +6,11 @@	
00:00:07.626093 STDOUT 1192]	     python train_ppo_ale.py	
00:00:07.626095 STDOUT 1192]		
00:00:07.626098 STDOUT 1192]	 To train PPO using a recurrent model on a flickering Atari env, run:	
00:00:07.626121 STDOUT 1192]	     python train_ppo_ale.py --recurrent --flicker --no-frame-stack	
00:00:07.626128 STDOUT 1192]	 """	
00:00:07.626132 STDOUT 1192]	+	
00:00:07.626154 STDOUT 1192]	 import argparse	
00:00:07.626156 STDOUT 1192]	 import functools	
00:00:07.626159 STDOUT 1192]		
00:00:07.626181 STDOUT 1192]	 import numpy as np	
00:00:07.626182 STDOUT 1192]	 import torch	
00:00:07.626618 STDERR 1192]	would reformat /tmp/flexci/run-00417839/work/src/examples/atari/train_ppo_ale.py	
00:00:07.863694 STDOUT 1192]	--- /tmp/flexci/run-00417839/work/src/examples/atlas/train_soft_actor_critic_atlas.py	2025-12-11 06:50:13.040946+00:00	
00:00:07.863709 STDOUT 1192]	+++ /tmp/flexci/run-00417839/work/src/examples/atlas/train_soft_actor_critic_atlas.py	2025-12-11 06:50:19.103276+00:00	
00:00:07.863717 STDOUT 1192]	@@ -1,6 +1,7 @@	
00:00:07.863939 STDOUT 1192]	 """A training script of Soft Actor-Critic on RoboschoolAtlasForwardWalk-v1."""	
00:00:07.863941 STDOUT 1192]	+	
00:00:07.863945 STDOUT 1192]	 import argparse	
00:00:07.863973 STDOUT 1192]	 import functools	
00:00:07.863975 STDOUT 1192]	 import logging	
00:00:07.863979 STDOUT 1192]	 import sys	
00:00:07.864002 STDOUT 1192]		
00:00:07.865260 STDERR 1192]	would reformat /tmp/flexci/run-00417839/work/src/examples/atlas/train_soft_actor_critic_atlas.py	
00:00:08.071995 STDOUT 1192]	--- /tmp/flexci/run-00417839/work/src/examples/gym/train_reinforce_gym.py	2025-12-11 06:50:13.985035+00:00	
00:00:08.072009 STDOUT 1192]	+++ /tmp/flexci/run-00417839/work/src/examples/gym/train_reinforce_gym.py	2025-12-11 06:50:19.312047+00:00	
00:00:08.072018 STDOUT 1192]	@@ -7,10 +7,11 @@	
00:00:08.072177 STDOUT 1192]	     python train_reinforce_gym.py	
00:00:08.072179 STDOUT 1192]		
00:00:08.072183 STDOUT 1192]	 To solve InvertedPendulum-v1, run:	
00:00:08.072210 STDOUT 1192]	     python train_reinforce_gym.py --env InvertedPendulum-v1	
00:00:08.072212 STDOUT 1192]	 """	
00:00:08.072215 STDOUT 1192]	+	
00:00:08.072242 STDOUT 1192]	 import argparse	
00:00:08.072244 STDOUT 1192]		
00:00:08.072246 STDOUT 1192]	 import gym	
00:00:08.072271 STDOUT 1192]	 import gym.spaces	
00:00:08.072272 STDOUT 1192]	 import torch	
00:00:08.073251 STDERR 1192]	would reformat /tmp/flexci/run-00417839/work/src/examples/gym/train_reinforce_gym.py	
00:00:08.275587 STDOUT 1192]	--- /tmp/flexci/run-00417839/work/src/examples/mujoco/reproduction/ppo/train_ppo.py	2025-12-11 06:50:13.036945+00:00	
00:00:08.275600 STDOUT 1192]	+++ /tmp/flexci/run-00417839/work/src/examples/mujoco/reproduction/ppo/train_ppo.py	2025-12-11 06:50:19.515315+00:00	
00:00:08.275634 STDOUT 1192]	@@ -1,10 +1,11 @@	
00:00:08.275798 STDOUT 1192]	 """A training script of PPO on OpenAI Gym Mujoco environments.	
00:00:08.275800 STDOUT 1192]		
00:00:08.275803 STDOUT 1192]	 This script follows the settings of https://arxiv.org/abs/1709.06560 as much	
00:00:08.275844 STDOUT 1192]	 as possible.	
00:00:08.275846 STDOUT 1192]	 """	
00:00:08.275850 STDOUT 1192]	+	
00:00:08.275873 STDOUT 1192]	 import argparse	
00:00:08.275875 STDOUT 1192]	 import functools	
00:00:08.275881 STDOUT 1192]		
00:00:08.275908 STDOUT 1192]	 import gym	
00:00:08.275910 STDOUT 1192]	 import gym.spaces	
00:00:08.276660 STDERR 1192]	would reformat /tmp/flexci/run-00417839/work/src/examples/mujoco/reproduction/ppo/train_ppo.py	
00:00:08.384960 STDOUT 1192]	--- /tmp/flexci/run-00417839/work/src/examples/mujoco/reproduction/soft_actor_critic/train_soft_actor_critic.py	2025-12-11 06:50:13.036945+00:00	
00:00:08.384982 STDOUT 1192]	+++ /tmp/flexci/run-00417839/work/src/examples/mujoco/reproduction/soft_actor_critic/train_soft_actor_critic.py	2025-12-11 06:50:19.624452+00:00	
00:00:08.385050 STDOUT 1192]	@@ -1,10 +1,11 @@	
00:00:08.385053 STDOUT 1192]	 """A training script of Soft Actor-Critic on OpenAI Gym Mujoco environments.	
00:00:08.385081 STDOUT 1192]		
00:00:08.385083 STDOUT 1192]	 This script follows the settings of https://arxiv.org/abs/1812.05905 as much	
00:00:08.385086 STDOUT 1192]	 as possible.	
00:00:08.385110 STDOUT 1192]	 """	
00:00:08.385112 STDOUT 1192]	+	
00:00:08.385114 STDOUT 1192]	 import argparse	
00:00:08.385137 STDOUT 1192]	 import functools	
00:00:08.385138 STDOUT 1192]	 import logging	
00:00:08.385141 STDOUT 1192]	 import sys	
00:00:08.385164 STDOUT 1192]	 from distutils.version import LooseVersion	
00:00:08.385710 STDERR 1192]	would reformat /tmp/flexci/run-00417839/work/src/examples/mujoco/reproduction/soft_actor_critic/train_soft_actor_critic.py	
00:00:08.581822 STDOUT 1192]	--- /tmp/flexci/run-00417839/work/src/examples/mujoco/reproduction/trpo/train_trpo.py	2025-12-11 06:50:13.036945+00:00	
00:00:08.581835 STDOUT 1192]	+++ /tmp/flexci/run-00417839/work/src/examples/mujoco/reproduction/trpo/train_trpo.py	2025-12-11 06:50:19.821719+00:00	
00:00:08.581844 STDOUT 1192]	@@ -1,10 +1,11 @@	
00:00:08.582003 STDOUT 1192]	 """A training script of TRPO on OpenAI Gym Mujoco environments.	
00:00:08.582005 STDOUT 1192]		
00:00:08.582009 STDOUT 1192]	 This script follows the settings of https://arxiv.org/abs/1709.06560 as much	
00:00:08.582034 STDOUT 1192]	 as possible.	
00:00:08.582040 STDOUT 1192]	 """	
00:00:08.582044 STDOUT 1192]	+	
00:00:08.582068 STDOUT 1192]	 import argparse	
00:00:08.582069 STDOUT 1192]	 import logging	
00:00:08.582072 STDOUT 1192]		
00:00:08.582095 STDOUT 1192]	 import gym	
00:00:08.582096 STDOUT 1192]	 import gym.spaces	
00:00:08.582523 STDERR 1192]	would reformat /tmp/flexci/run-00417839/work/src/examples/mujoco/reproduction/trpo/train_trpo.py	
00:00:09.529217 STDOUT 1192]	--- /tmp/flexci/run-00417839/work/src/pfrl/agents/iqn.py	2025-12-11 06:50:13.985035+00:00	
00:00:09.529230 STDOUT 1192]	+++ /tmp/flexci/run-00417839/work/src/pfrl/agents/iqn.py	2025-12-11 06:50:20.767705+00:00	
00:00:09.529244 STDOUT 1192]	@@ -28,11 +28,10 @@	
00:00:09.529402 STDOUT 1192]	     assert embedding.shape == x.shape + (n_basis_functions,)	
00:00:09.529405 STDOUT 1192]	     return embedding	
00:00:09.529408 STDOUT 1192]		
00:00:09.529436 STDOUT 1192]		
00:00:09.529438 STDOUT 1192]	 class CosineBasisLinear(nn.Module):	
00:00:09.529441 STDOUT 1192]	-	
00:00:09.529469 STDOUT 1192]	     """Linear layer following cosine basis functions.	
00:00:09.529470 STDOUT 1192]		
00:00:09.529474 STDOUT 1192]	     Args:	
00:00:09.529503 STDOUT 1192]	         n_basis_functions (int): Number of cosine basis functions.	
00:00:09.529504 STDOUT 1192]	         out_size (int): Output size.	
00:00:09.529508 STDOUT 1192]	@@ -79,11 +78,10 @@	
00:00:09.529535 STDOUT 1192]	     h = h.reshape(batch_size, n_taus, n_actions)	
00:00:09.529537 STDOUT 1192]	     return QuantileDiscreteActionValue(h)	
00:00:09.529540 STDOUT 1192]		
00:00:09.529567 STDOUT 1192]		
00:00:09.529568 STDOUT 1192]	 class ImplicitQuantileQFunction(nn.Module):	
00:00:09.529571 STDOUT 1192]	-	
00:00:09.529601 STDOUT 1192]	     """Implicit quantile network-based Q-function.	
00:00:09.529602 STDOUT 1192]		
00:00:09.529606 STDOUT 1192]	     Args:	
00:00:09.529634 STDOUT 1192]	         psi (torch.nn.Module): Callable module	
00:00:09.529635 STDOUT 1192]	             (batch_size, obs_size) -> (batch_size, hidden_size).	
00:00:09.529639 STDOUT 1192]	@@ -123,11 +121,10 @@	
00:00:09.529663 STDOUT 1192]		
00:00:09.529665 STDOUT 1192]	         return evaluate_with_quantile_thresholds	
00:00:09.529668 STDOUT 1192]		
00:00:09.529693 STDOUT 1192]		
00:00:09.529695 STDOUT 1192]	 class RecurrentImplicitQuantileQFunction(Recurrent, nn.Module):	
00:00:09.529698 STDOUT 1192]	-	
00:00:09.529725 STDOUT 1192]	     """Recurrent implicit quantile network-based Q-function.	
00:00:09.529726 STDOUT 1192]		
00:00:09.529729 STDOUT 1192]	     Args:	
00:00:09.529756 STDOUT 1192]	         psi (torch.nn.Module): Module that implements	
00:00:09.529762 STDOUT 1192]	             `pfrl.nn.Recurrent`.	
00:00:09.529765 STDOUT 1192]	@@ -254,11 +251,10 @@	
00:00:09.529791 STDOUT 1192]	         loss = loss_sum	
00:00:09.529792 STDOUT 1192]	     return loss	
00:00:09.529796 STDOUT 1192]		
00:00:09.529818 STDOUT 1192]		
00:00:09.529820 STDOUT 1192]	 class IQN(dqn.DQN):	
00:00:09.529823 STDOUT 1192]	-	
00:00:09.529856 STDOUT 1192]	     """Implicit Quantile Networks.	
00:00:09.529858 STDOUT 1192]		
00:00:09.529861 STDOUT 1192]	     See https://arxiv.org/abs/1806.06923.	
00:00:09.529885 STDOUT 1192]		
00:00:09.529886 STDOUT 1192]	     Args:	
00:00:09.531158 STDERR 1192]	would reformat /tmp/flexci/run-00417839/work/src/pfrl/agents/iqn.py	1.0s
00:00:10.573780 STDOUT 1192]	--- /tmp/flexci/run-00417839/work/src/pfrl/initializers/chainer_default.py	2025-12-11 06:50:13.985035+00:00	
00:00:10.573794 STDOUT 1192]	+++ /tmp/flexci/run-00417839/work/src/pfrl/initializers/chainer_default.py	2025-12-11 06:50:21.814753+00:00	
00:00:10.573802 STDOUT 1192]	@@ -1,7 +1,7 @@	
00:00:10.574024 STDOUT 1192]	-"""Initializes the weights and biases of a layer to chainer default.	
00:00:10.574026 STDOUT 1192]	-"""	
00:00:10.574030 STDOUT 1192]	+"""Initializes the weights and biases of a layer to chainer default."""	
00:00:10.574068 STDOUT 1192]	+	
00:00:10.574070 STDOUT 1192]	 import torch	
00:00:10.574074 STDOUT 1192]	 import torch.nn as nn	
00:00:10.574103 STDOUT 1192]		
00:00:10.574105 STDOUT 1192]	 from pfrl.initializers.lecun_normal import init_lecun_normal	
00:00:10.574108 STDOUT 1192]		
00:00:10.574919 STDERR 1192]	would reformat /tmp/flexci/run-00417839/work/src/pfrl/initializers/chainer_default.py	2.8s
00:00:13.384328 STDOUT 1192]	--- /tmp/flexci/run-00417839/work/src/tests/wrappers_tests/test_atari_wrappers.py	2025-12-11 06:50:13.985035+00:00	
00:00:13.384363 STDOUT 1192]	+++ /tmp/flexci/run-00417839/work/src/tests/wrappers_tests/test_atari_wrappers.py	2025-12-11 06:50:24.624953+00:00	
00:00:13.384371 STDOUT 1192]	@@ -1,8 +1,7 @@	
00:00:13.384526 STDOUT 1192]	 """Currently this script tests `pfrl.wrappers.atari_wrappers.FrameStack`	
00:00:13.384529 STDOUT 1192]	 only."""	
00:00:13.384534 STDOUT 1192]	-	
00:00:13.384577 STDOUT 1192]		
00:00:13.384579 STDOUT 1192]	 from unittest import mock	
00:00:13.384583 STDOUT 1192]		
00:00:13.384602 STDOUT 1192]	 import gym	
00:00:13.384603 STDOUT 1192]	 import gym.spaces	
00:00:13.385064 STDERR 1192]	would reformat /tmp/flexci/run-00417839/work/src/tests/wrappers_tests/test_atari_wrappers.py	
00:00:13.392222 STDERR 1192]		
00:00:13.392235 STDERR 1192]	Oh no! 💥 💔 💥	
00:00:13.392287 STDERR 1192]	10 files would be reformatted, 203 files would be left unchanged.

@prabhatnagarajan

prabhatnagarajan commented Dec 11, 2025

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@keisuke-nakata Can you run the tests for this PR: #202? I applied the linters to the repository.

@prabhatnagarajan prabhatnagarajan mentioned this pull request Dec 11, 2025
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@prabhatnagarajan

prabhatnagarajan commented Dec 13, 2025

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@keisuke-nakata Sorry (tests need running again). I just merged with the changes to master.

@muupan

muupan commented Dec 14, 2025

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/test

@pfn-ci-bot

pfn-ci-bot commented Dec 14, 2025

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Successfully created a job for commit d5396d9:

@muupan
muupan merged commit 89ce16b into pfnet:master Dec 14, 2025
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@prabhatnagarajan
prabhatnagarajan deleted the black_install branch April 12, 2026 08:31
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@prabhatnagarajan @keisuke-nakata @pfn-ci-bot @muupan