deps(deps-dev): update braintools requirement from >=0.1.9 to >=0.3.0 in the development-dependencies group

[dependabot]

Updates the requirements on braintools to permit the latest version.
Updates braintools to 0.3.0

Release notes

Sourced from braintools's releases.

v0.3.0

This release completes the library-wide correctness audit campaign begun in 0.2.0. The two remaining major modules — cogtask and metric — received their first dedicated static audits, while optim, trainer, visualize, surrogate, and init underwent deeper second-pass re-audits whose findings were each verified against reference implementations (optax 0.2.6, torch.optim, PyTorch's NAdam) and numeric reproductions. Every fix is locked in behind a regression test suite. The changes are corrections to existing behavior — no intentional API breaks — but the breadth and the genuine numerical/algorithmic bugs corrected (double-applied SM3 momentum, a centered RMSprop that was a silent no-op, dropped Parallel branches in cogtask, distributed broadcast that failed on more than one device, and more) warrant the minor-version bump.

Highlights

• Audit campaign completed: cogtask and metric are now audited, and the five previously-audited modules were re-audited against their reference implementations, replacing plausible-but-unverified behavior with reference-checked correctness.
• Real algorithmic fixes: SM3 no longer applies momentum twice; RMSprop(centered=True) actually centers; Nadam honors momentum_decay; cogtask.Parallel no longer silently drops compound (>> / Repeat) branches; distributed broadcast() works on more than one device.
• Restored public API: cogtask.create_task and metric.L1Loss are now importable from their packages (both were documented but absent from __all__).
• Regression coverage: each audited module ships a dedicated regression test suite (visualize exercised source at 99%, surrogate at 100%).

Added

• braintools.cogtask.create_task is now exported from the package (#122).
• braintools.metric.L1Loss is now exported (documented but previously missing from __all__) (#121).

Fixed

braintools.optim (#120) — re-audit verified against optax 0.2.6 / torch.optim

• SM3 no longer applies first-moment momentum twice; momentum=0 now truly disables it (matches optax.sm3).
• RMSprop(centered=True) uses scale_by_stddev instead of silently falling back to scale_by_rms.
• Nadam implements PyTorch-style scheduled momentum so momentum_decay takes effect (verified against torch.optim.NAdam).
• LBFGS reads the live LR schedule each step instead of freezing the LR at construction; CosineAnnealingWarmRestarts.step(epoch=...) recomputes T_cur/T_i from the absolute epoch.
• Fail-fast validation of optimizer hyperparameters and scheduler enums;

... (truncated)

Changelog

Sourced from braintools's changelog.

Version 0.3.0 (2026-06-19)

This release completes the library-wide correctness audit campaign begun in 0.2.0. The two remaining major modules — cogtask and metric — received their first dedicated static audits, while optim, trainer, visualize, surrogate, and init underwent deeper second-pass re-audits whose findings were each verified against reference implementations (optax 0.2.6, torch.optim, PyTorch's NAdam) and numeric reproductions. Every fix is locked in behind a regression test suite. The changes are corrections to existing behavior — no intentional API breaks — but the breadth and the genuine numerical/algorithmic bugs corrected (double-applied SM3 momentum, a centered RMSprop that was a silent no-op, dropped Parallel branches in cogtask, distributed broadcast that failed on more than one device, and more) warrant the minor-version bump.

Highlights

• Audit campaign completed: cogtask and metric are now audited, and the five previously-audited modules were re-audited against their reference implementations, replacing plausible-but-unverified behavior with reference-checked correctness.
• Real algorithmic fixes: SM3 no longer applies momentum twice; RMSprop(centered=True) actually centers; Nadam honors momentum_decay; cogtask.Parallel no longer silently drops compound (>> / Repeat) branches; distributed broadcast() works on more than one device.
• Restored public API: cogtask.create_task and metric.L1Loss are now importable from their packages (both were documented but absent from __all__).
• Regression coverage: each audited module ships a dedicated regression test suite (visualize exercised source at 99%, surrogate at 100%).

Added

• braintools.cogtask.create_task is now exported from the package (#122).
• braintools.metric.L1Loss is now exported (documented but previously missing from __all__) (#121).

Fixed

braintools.optim (#120) — re-audit verified against optax 0.2.6 / torch.optim

• SM3 no longer applies first-moment momentum twice; momentum=0 now truly disables it (matches optax.sm3).
• RMSprop(centered=True) uses scale_by_stddev instead of silently falling back to scale_by_rms.
• Nadam implements PyTorch-style scheduled momentum so momentum_decay takes effect (verified against torch.optim.NAdam).
• LBFGS reads the live LR schedule each step instead of freezing the LR at construction; CosineAnnealingWarmRestarts.step(epoch=...) recomputes T_cur/T_i from the absolute epoch.

... (truncated)

Commits

• f37f3c0 release: 0.3.0 (#123)
• bc6da89 delete issues doc
• d6e86bf fix(cogtask): repair Parallel compound children, make_encoder scalar, and bro...
• 072c6cd fix(metric): correctness, brainunit, and edge-case fixes across braintools.me...
• 6a29629 fix(optim): re-audit fixes — SM3 double momentum, RMSprop centered, NAdam sch...
• e9d4ae8 fix(trainer): correct LR-monitor logging, save_top_k pruning, resume, and dis...
• 336bebc fix(visualize): resolve audit issues, add regression tests (>90% cov) (#118)
• 252d4ff fix(surrogate): make LogTailedRelu.surrogate_fun continuous, fix docs (#117)
• 1189c9d delete issues doc
• d92bc18 fix(init): correct TruncatedNormal array std, param() State handling & docs (...
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