Adrian Hill
Adrian Hill
I can recreate this in 1.7.1: ```julia-repl julia> VERSION v"1.7.1" (@v1.7) pkg> activate --temp Activating new project at `/var/folders/74/wcz8c9qs5dzc8wgkk7839k5c0000gn/T/jl_gugiKX` (jl_gugiKX) pkg> add ChainRules Updating registry at `~/.julia/registries/General.toml` Resolving package versions......
Also happens to me on 1.7.2 on macOS. `up` doesn't help. ```julia-repl julia> VERSION v"1.7.2" (@v1.7) pkg> activate --temp Activating new project at `/var/folders/74/wcz8c9qs5dzc8wgkk7839k5c0000gn/T/jl_Z0xCP0` (jl_Z0xCP0) pkg> add ChainRules Updating registry...
Maybe this is due to my startup.jl? ``` ➜ ~ cat ~/.julia/config/startup.jl using Revise using OhMyREPL using JuliaFormatter using BenchmarkTools using TestEnv ```
Ok, this issue can stay closed. Somehow Compat `3.42` doesn't export `allequal` on my machine. I'll open an issue there. Thanks for the help! :) Edit: This wasn't an issue...
@ChrisRackauckas It should be an array of shape `nstates` x `ntimesteps`. Basically the format you'd get from calling `Array(solve(...))`. @VoSiLk the DomainError in your multiple shooting code occurred because ```julia...
I hope this is the right place for this discussion, but it looks like using PyTorch weights might not be too complicated. I've had success opening Torch's `.pth` files using...
So fixing this would require Measurements.jl to implement a `similar` method? I'm guessing the issue would be the unique identifier `tag` and dictionary of derivatives `der` that are part of...
Thanks a lot, loading smaller images with JpegTurbo is indeed much faster! I've also added a lookup-table `wnid_to_label` to the metadata. Once you know the label, you can access class...
JpegTurbo's `preferred_size` keyword already returns images pretty close to the desired `224x224` size. At the cost of losing a couple of pixels, we could skip the second resizing in `resize_smallest_dimension`,...
I've done some local benchmarks: Current commit [cac14d2](https://github.com/JuliaML/MLDatasets.jl/pull/146/commits/cac14d25d1d102dd70020d6add47a0017dcbf535) with JpegTurbo loading smaller images: ```julia julia> using MLDatasets julia> dataset = ImageNet(Float32, :val); julia> @benchmark dataset[1:16] BenchmarkTools.Trial: 44 samples with 1...