Bump burn-cuda from 0.20.1 to 0.21.0

[dependabot]

Bumps burn-cuda from 0.20.1 to 0.21.0.

Release notes

Sourced from burn-cuda's releases.

v0.21.0

Summary

Burn 0.21.0 brings 4 months of improvements that make the framework significantly faster and more reliable across the board. The gains span distributed workflows for training large models all the way down to small-model inference, where the reduced framework overhead becomes especially noticeable.

We rethought our distributed computing stack around differentiable collective operations. Kernel selection is now more reliable thanks to better autotuning and a new validation layer, and a project-level burn.toml file lets you tweak those internals (and many others) without recompiling. A reworked device handle reduces framework overhead, and a new burn-dispatch crate simplifies backend selection while paving the way for faster compile times. The release also ships burn-flex, a lightweight eager CPU backend for WebAssembly and embedded targets that replaces burn-ndarray. Finally, we added early off-policy reinforcement learning support and a fresh round of kernel work on GEMV, top-k, and FFT.

For more details, check out the release post on our website.

Changelog

Breaking

We've introduced a couple of breaking changes with this release. The affected areas are detailed in the sections below.

burn-dataset cache directory

To respect platform conventions, we switched from using a hardcoded ~/.cache directory root for downloaded artifacts.

Platform	Path
Linux	$XDG_CACHE_HOME or ~/.cache
macOS	~/Library/Caches
Windows	{FOLDERPATH_LOCAL_APPDATA}

For Linux users without $XDG_CACHE_HOME configured, this change has no effect. The cache directory is still ~/.cache.

Interface Changes

TensorData::shape now stores a Shape instead of a Vec<usize>. Existing binary records using BinFileRecorder or BinBytesRecorder are no not forward-compatible and must be converted before upgrading.

static STATE_ENCODED: &[u8] = include_bytes!("model.bin");
let model: Model<B> = Model::new(&Default::default());
// Old format can still be loaded before upgrade, but must be re-saved in a forward-compatible format.
let record = BinBytesRecorder::<FullPrecisionSettings, &'static [u8]>::default()
.load(STATE_ENCODED, &Default::default())
.expect("Failed to decode state");
let model = model.load_record(record);
model.save_file("model.mpk", &NamedMpkFileRecorder::<FullPrecisionSettings>::new()).unwrap();

The module derive macro has been improved, and the Ignored<T> wrapper is now deprecated. For fields that should not considered modules, use #[module(skip)] instead.

pub struct Conv1d<B: Backend> {
</tr></table> 

... (truncated)

Commits

• 546cacb Change pwff activation to #[module(skip)] for backward compat (stateless) (...
• fdf774b Update version to 0.21.0 (#4927)
• 2a34823 fix: conv_transpose x-backward output size (#4845) (#4916)
• 7640aa7 add autodiff for scatter_nd min/max/mul (#4909)
• da317a8 Fix some test tolerances (#4926)
• b6546c9 Remove optim::optim (#4924)
• bcbde9a Fix fusion read_quantized native type (#4923)
• bf2e8b7 rnnt.rs: Optimize extract_log_probs and init_alpha (#4922)
• 7728590 Update version to 0.21.0-pre.5 (#4921)
• fdacf17 Re-enable fusion f16 conv + bn regression tests (#4920)
• Additional commits viewable in compare view

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