FluxML/Flux.jl

Optional batch dimension for convolutions

Closed

#593 opened on Feb 4, 2019

View on GitHubContributor guide
 (3 comments) (0 reactions) (0 assignees)Julia (619 forks)batch import
help wanted

Repository metrics

Stars
 (4,725 stars)
PR merge metrics
 (Avg merge 3d 6h) (6 merged PRs in 30d)

Description

Currently Conv is the only place a batch dimension is required. It would be nice to check dimensions and reshape as necessary so that it isn't require, for convenience.

#583

Contributor guide

Research direction
Examine the Conv implementation in Flux.jl, understand the current batch dimension requirement, and modify the dimension checking and reshaping to support optional batch dimension. Refer to issue #583 for additional context.
Tech stack
julia
Domain
machine learning
Issue type
Feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
2
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-3 hours
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
JuliaFlux
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
75