Posts

cpprb v10.1.0 can save & load transitions

From cpprb version 10.1.0, ReplayBuffer and its sub-classes can save and load transitions. from cpprb import ReplayBuffer rb1 = ReplayBuffer(256, {"obs": {"shape": 3}, "act": {}, "rew": {}, "done": {}}, next_of="obs")

GitLab CI/CD: Single job for multiple conditions

At a previous post, I used following configuration to achive manual or scheduled job at GitLab CI/CD. .docker_build_base: &docker_build image: docker:latest stage: build_image services: - docker:dind script: - docker login

ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject

When import cpprb, I got ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject. Recently, NumPy has changed its ABI at version

Hugo: Markdown rendering inside nested shortcodes

Hugo is a static site generator from markdown, which I use for this blog and project site. Hugo has a template mechanism, Shortcodes, which allows users to use complicated HTML.

Embed reveal.js slide into Hugo site

By utilizing custom shortcodes, we can embed pages including reveal.js slides into Hugo-powered site. First, create custom shortcodes at layouts/shortcodes/SlideInclusion.html <iframe src="{{.Get 0}}" width="1000" height="600" frameborder="0" allowfullscreen="allowfullscreen" allow="geolocation *; microphone

Enable GitHub Discussions for cpprb

We enabled GitHub Discussions for cpprb as end user forum. Issues at GitLab.com will be used for developer issue trakcer. We hope this separation will help both end users and

Speed up Ape-X implementation on single machine

Alghough neural network is optimized for GPU, environments for reinforcement learning (e.g. simulator) are not always GPU friendly. One of the method to speed up reinforcement learning is to run

Solved: Failed to install Emacs packages from MELPA

On 25th December 2020, CI jobs at cpprb started to fail. ( 1, 2, etc.) Installing ox-hugo from MELPA was failed with a strange error of Wrong type argument: stringp,

Snippet: Binary Classification with LightGBM

Following snippet executes binary classification with LightGBM. The binary_gbm_cv function runs cross validation on training data and returns prediction function composing boosters used at the cross validation. The function also

Count the number of |1> states with Qiskit

Qiskit is a OSS SDK for developing quantum computing. The following snippet has small functions counting the number of |1> states in qbits. def add_bit(qc,ans,new,aux,sub=False): """ Add a single bit