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stable-baselines3

DLR-RM / stable-baselines3

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[Bug] Tensorboard logging not logging every log_interval timesteps

1
YannBerthelot
YannBerthelot commented Jan 18, 2022

🐛 Bug

The documentation of DQN agent (https://stable-baselines3.readthedocs.io/en/master/modules/dqn.html) specifies that log_interval parameter is "The number of timesteps before logging". However, when set to 1 (or any other value) the logging is not made at that pace but is instead made every log_interval episode (and not timesteps). In the example below this is made every 200 timesteps.

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bug documentation good first issue
stable-baselines

hill-a / stable-baselines

Star 3.5k
Open

Episode rewards not updated before being used by callback.on_step()

3
calerc
calerc commented Nov 23, 2020

The following applies to DDPG and TD3, and possibly other models. The following libraries were installed in a virtual environment:

numpy==1.16.4
stable-baselines==2.10.0
gym==0.14.0
tensorflow==1.14.0

Episode rewards do not seem to be updated in model.learn() before callback.on_step(). Depending on which callback.locals variable is used, this means that:

  • episode rewards may n
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good first issue question

MishaLaskin / curl

Star 457

CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning

deep-neural-networks reinforcement-learning deep-learning curl gpu deep-reinforcement-learning deep-learning-algorithms reinforcement-learning-algorithms deeplearning deep-q-network sac deep-q-learning reinforcement-agents deep-rl deeplearning-ai contrastive-loss off-policy contrastive-predictive-coding model-free-rl contrastive-learning
  • Updated Oct 28, 2020
  • Python

SforAiDl / genrl

Star 382
Open

More comprehensive unit testing

sampreet-arthi
sampreet-arthi commented Oct 10, 2020

There seem to be some vulnerabilities in our code that might fail easily. I suggest adding more unit tests for the following:

  • Custom agents (there's only VPG and PPO on CartPole-v0 as of now. We should preferably add more to cover discrete-offpolicy, continuous-offpolicy and continuous-onpolicy)
  • Evaluation for the Bandits and Classical agents
  • Testing of convergence of agents as proposed i
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enhancement good first issue CI/CD
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Madhu009 / Deep-math-machine-learning.ai

Star 190

A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.

machine-learning natural-language-processing deep-neural-networks tensorflow word2vec linear-regression q-learning neural-networks reinforcement-learning-algorithms sarsa logistic-regression gans support-vector-machines policy-iteration value-iteration gradient-descent-algorithm monte-carlo-methods temporal-differencing-learning general-adversarial-network
  • Updated Mar 15, 2019
  • Jupyter Notebook

sichkar-valentyn / Reinforcement_Learning_in_Python

Star 200

Implementing Reinforcement Learning, namely Q-learning and Sarsa algorithms, for global path planning of mobile robot in unknown environment with obstacles. Comparison analysis of Q-learning and Sarsa

reinforcement-learning q-learning path-planning rl-agents reinforcement-learning-algorithms sarsa maze-algorithms obstacle-avoidance maze-solver shortest-path rl-playground sarsa-learning sarsa-search rl-emulator rl-environment rl-algorithms rl-experiments rl-qlearning q-learning-vs-sarsa rl-sarsa
  • Updated Apr 25, 2022
  • Python

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