Bump version to 0.3.11 and update changelog

CHANGELOG.md

@@ -6,9 +6,19 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
 
 ## [Unreleased]
 
+## [0.3.11] - 2026-08-14
+
 ### Added
 
 - `RemoteModelWrapper` (`textattack.models.wrappers.RemoteModelWrapper`): query a model served behind a remote HTTP API instead of running it locally. Request/response handling is adaptable to different endpoint schemas via `request_fn`/`response_fn`.
+- New attack recipe `bad-characters` (`BadCharacters2021`, see
+  `textattack/attack_recipes/bad_characters_2021.py`) implementing
+  [Bad Characters: Imperceptible NLP Attacks](https://arxiv.org/abs/2106.09898):
+  perturbations invisible on some rendering systems (invisible characters,
+  homoglyphs, reorderings, deletions of zero-width characters), combining a
+  new `differential-evolution` search method (`WordSwapDifferentialEvolution`
+  transformation family) with new `LogitSum`/`NamedEntityRecognition`/
+  `TargetedStrict`/`TargetedBonus` goal functions ([#817](https://github.com/QData/TextAttack/issues/817)).
 - New attack recipe `leap` (`LEAP2023`, see `textattack/attack_recipes/leap_2023.py`)
   implementing LEAP: Efficient and Automated Test Method for NLP Software
   ([arXiv:2308.11284](https://arxiv.org/abs/2308.11284)). LEAP is a
@@ -28,9 +38,28 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
   LEAP using ~6% fewer queries and running ~2.25x faster; under a 2000-query
   budget (n=100), success collapses to ~23-24% for both, with LEAP still
   modestly ahead on every metric but by a much smaller margin.
+- `train` command: `--dataset-from-file` support, matching what `attack`/`eval`
+  already had. Point it at a Python module exposing `train_dataset`/
+  `eval_dataset` (each a `textattack.datasets.Dataset`), optionally
+  `path.py^prefix` for `prefix_train_dataset`/`prefix_eval_dataset` ([#625](https://github.com/QData/TextAttack/issues/625)).
+- `HuggingFaceModelWrapper`: an optional `max_length` constructor argument,
+  forwarded to `.generate()` for raw `transformers` encoder-decoder
+  generation models. Left unset by default so a checkpoint's own
+  `generation_config` isn't overridden.
+- Docs: the single-example `Attack.attack(text, label)` API (already existed,
+  wasn't documented) ([#673](https://github.com/QData/TextAttack/issues/673)); a working example attacking a raw
+  `transformers.BartForConditionalGeneration`/`T5ForConditionalGeneration`
+  via `Seq2SickCheng2018BlackBox` ([#772](https://github.com/QData/TextAttack/issues/772)); a "Multi-lingual attacks" section
+  listing the French/Spanish/Chinese recipes ([#423](https://github.com/QData/TextAttack/issues/423)).
 
 ### Changed
 
+- Modernized CI: bumped GitHub Actions (`actions/checkout` v2->v4,
+  `actions/setup-python` v2->v5, `github/codeql-action/*` v1->v3), fixed
+  the pre-existing lint errors this surfaced, and re-enabled `pytest`
+  execution in CI (it had been disabled) ([#822](https://github.com/QData/TextAttack/issues/822)).
+- `ChineseWordSwapHowNet`: cache HowNet replacement-word lookups to speed
+  up repeated candidate generation, without changing results ([#786](https://github.com/QData/TextAttack/issues/786)).
 - Refactored `ParticleSwarmOptimization.perform_search` (shared base class)
   to expose its per-iteration deltas as overridable hook methods
   (`_initialize_velocities`, `_pre_iteration_setup`, `_compute_omega`,
@@ -54,6 +83,29 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
 
 ### Fixed
 
+- `EDA` augmentation recipe (`textattack augment` CLI with `--recipe eda`):
+  didn't accept the default arguments defined on the `Augmentation`
+  superclass, since it didn't forward `**kwargs` to its component
+  `Augmenter` objects.
+- `HuggingFaceDataset`: `shuffle()` (and `shuffle=True` at construction)
+  had no effect, since `datasets.Dataset.shuffle()` returns a new
+  `Dataset` rather than shuffling in place, and the return value wasn't
+  being assigned back ([#791](https://github.com/QData/TextAttack/issues/791)).
+- `WordSwapChangeNumber._alter_number`: raised `ValueError: high is out
+  of bounds for int64` on negative numbers, since `int(num *
+  self.max_change) + 1` can compute a negative `change` that flips the
+  `randrange`/`randint` bounds ([#741](https://github.com/QData/TextAttack/issues/741)).
+- `sentence_encoder.py`'s `get_angular_sim`: clamp `cos_sim` to `[-1, 1]`
+  before `torch.acos`, since floating-point error can push an equal pair
+  of embeddings' cosine similarity slightly above `1` (e.g. `1.00004`),
+  making `acos` return `NaN` instead of `1`.
+- `CompositeTransformation`: iterated its sub-transformations' results
+  through a `set`, making output order (and therefore downstream
+  behavior relying on it) non-deterministic across runs; switched to a
+  list-based dedup that preserves order.
+- Typo fix in `composite_transformation.py`'s docstring ("optoins" ->
+  "options").
+
 Several correctness issues found while porting LEAP against its authors'
 reference implementation, some of which also affect the pre-existing `pso`
 recipe since `ParticleSwarmOptimizationLEAP` shares code with
@@ -88,3 +140,80 @@ recipe since `ParticleSwarmOptimizationLEAP` shares code with
   unbounded `while True` loop with no fallback.
 - Fixed `docs/api/search_methods.rst`'s `ParticleSwarmOptimizationLEAP`
   section heading underline, which was shorter than the title.
+
+A round of fixes for long-standing issues found during an issue-triage pass:
+
+- `BERTAttackLi2020`: default `max_candidates` `48` -> `8`, since `48`
+  makes the masked-LM candidate search explode combinatorially on
+  multi-subword tokens, causing multi-hour runtimes ([#586](https://github.com/QData/TextAttack/issues/586)).
+- `AttackedText.generate_new_attacked_text`: fixed corruption of the
+  `<SPLIT>` join token when a replaced word (e.g. "I") is itself a
+  character substring of `"<SPLIT>"` and directly follows it in the
+  joined text ([#631](https://github.com/QData/TextAttack/issues/631)).
+- `WordSwapInflections`: restored matching against flair's current
+  `"upos-fast"` tags (`NOUN`/`VERB`/`ADJ`/`PROPN`/`AUX`), which
+  `AttackedText.pos_of_word_index` had switched to emitting directly a
+  while back, leaving the transformation silently returning zero
+  candidates for ordinary words ([#713](https://github.com/QData/TextAttack/issues/713), [#727](https://github.com/QData/TextAttack/issues/727)).
+- `textattack.shared.utils.flair_tag`: cached one tagger per `tag_type`
+  instead of a single global slot, which silently reused whichever
+  tagger (POS or NER) loaded first for every later call regardless of
+  the requested `tag_type` -- corrupting POS/NER results for whichever
+  came second in the same process.
+- `GreedyWordSwapWIR`: actually implemented `truncate_words_to` (a2t's
+  recipe had been passing it since an earlier PR, but the constructor
+  never accepted it, crashing on init) ([#754](https://github.com/QData/TextAttack/issues/754)); for `wir_method="gradient"`,
+  the truncation now also bounds the expensive `get_grad` call itself
+  (not just the cheap post-hoc index-scoring loop), and sorts
+  `indices_to_order` first since it can arrive in non-ascending order
+  from a `set`-derived source.
+- `textattack/shared/validators.py`: the model-compatibility regex for
+  classification models only matched the pre-4.x
+  `transformers.modeling_<model>` layout; now also matches
+  `transformers.models.<model>.modeling_<model>` ([#722](https://github.com/QData/TextAttack/issues/722)). Also added a
+  matching entry for raw `transformers` encoder-decoder generation
+  classes (`T5ForConditionalGeneration`, `BartForConditionalGeneration`,
+  ...), not just TextAttack's own `T5ForTextToText` helper, which used
+  to print a spurious compatibility warning for every attack against one
+  ([#771](https://github.com/QData/TextAttack/issues/771)).
+- `AttackArgs`: warn (rather than silently drop) when `num_examples` is
+  explicitly set alongside `num_successful_examples`, since the latter
+  overrides the former and users combining both had no way to tell why
+  `num_examples` came back `None` ([#728](https://github.com/QData/TextAttack/issues/728)).
+- `AttackedText.words_diff_ratio`: comparing two Python lists with `!=`
+  yields a single bool, not an elementwise mask, so this always returned
+  `0` or `1` regardless of how many words actually differed; fixed by
+  comparing as numpy arrays ([#787](https://github.com/QData/TextAttack/issues/787)).
+- `Augmenter.augment`: bound-retry the outer sampling loop so a
+  transformation with limited output diversity for a given input (e.g.
+  `BackTranslationAugmenter`'s random language chaining colliding on
+  short sentences) doesn't silently return fewer than
+  `transformations_per_example` unique augmentations ([#800](https://github.com/QData/TextAttack/issues/800)); a later
+  version of that same fix made `high_yield=True` mode plateau at roughly
+  half its previous output instead of scaling with
+  `transformations_per_example` (a single outer pass can add several
+  results at once in that mode), and its final downsampling step called
+  `random.sample()` on a `set`, which Python 3.11+ no longer accepts.
+- `words_from_text`: strip allowed marks (quotes/hyphens/etc.) from both
+  ends of a word, not just the leading end, so a quoted word like
+  `"'CCC'"` doesn't keep its trailing quote ([#723](https://github.com/QData/TextAttack/issues/723)).
+- `HuggingFaceModelWrapper`: route encoder-decoder generation models
+  (e.g. a raw `BartForConditionalGeneration` loaded directly from
+  `transformers`) through `.generate()` + decode instead of a plain
+  forward pass, which only returns logits and breaks text-to-text goal
+  functions expecting strings ([#771](https://github.com/QData/TextAttack/issues/771)). Routing prefers `model.can_generate()`
+  over `hasattr(model, "generate")`, since on `transformers` versions
+  predating `can_generate()`, every `PreTrainedModel` exposed `.generate`
+  regardless of whether it had a generation-capable head, risking
+  misrouting a seq2seq-backbone classification model.
+- `Attack.cuda_`/`cpu_`: skip re-placing a `transformers.PreTrainedModel`
+  that already has an `hf_device_map` (i.e. was loaded with
+  `device_map=...` across multiple GPUs via `accelerate`), since forcing
+  it onto a single device breaks that placement ([#798](https://github.com/QData/TextAttack/issues/798)); `cpu_` was missing
+  this guard entirely, and the guard is now scoped to
+  `transformers.PreTrainedModel` specifically rather than any
+  `torch.nn.Module`, since this visitor also traverses non-HuggingFace
+  models reachable from a `Constraint`/`GoalFunction`/`Transformation`.
+- `Trainer.training_step`/`evaluate_step`: pad to the longest sequence in
+  the batch (`padding=True`) instead of the tokenizer's static max
+  length, avoiding wasted compute on shorter batches ([#737](https://github.com/QData/TextAttack/issues/737)).

docs/conf.py

@@ -21,7 +21,7 @@
 author = "UVA QData Lab"
 
 # The full version, including alpha/beta/rc tags
-release = "0.3.10"
+release = "0.3.11"
 
 # Set master doc to `index.rst`.
 master_doc = "index"