AGENT SKILL

translation

Run and troubleshoot checkpoint translation with translate.py and transformer.Translator beam search.

License 许可
MIT
最近更新
2026-09-03
Stars
★ 351
Forks
27

01 前言 Front Matter

name
translation
license
MIT
metadata
{ "disco-role": "operating" }
description
Run and troubleshoot checkpoint translation with translate.py and transformer.Translator beam search.
disable-model-invocation
true

02 资源文件 5

03 SKILL.md 正文

Translation Sub-skill

Use this sub-skill when a future task needs to run, validate, or troubleshoot checkpoint-based translation for this repository. It covers the translate.py command-line flow, the load_model checkpoint contract, and programmatic beam search with transformer.Translator.

Route here for

  • Validating that a training checkpoint has the settings and model objects required by translation before launching a full decode job.
  • Checking that a preprocessing pickle contains the test split plus source and target vocab fields expected by translate.py.
  • Running the repository translation CLI on CPU or CUDA and interpreting its output file.
  • Calling Translator.translate_sentence(...) directly for one already-tokenized source sentence.
  • Debugging beam-size, max-length, token-index, batch-size-one, and device mismatches in translation.

Do not route here for

  • Creating preprocessing pickles or BPE files; use the data-preparation skill.
  • Producing checkpoints, choosing training flags, or optimizer settings; use the training skill.
  • Explaining encoder/decoder internals, attention masks, or parameter shapes in depth; use the model-architecture skill.

Start with these references

  1. Read references/cli-reference.md for the translate.py CLI, checkpoint/data-pickle schemas, device selection, and output semantics.
  2. Read references/api-reference.md for programmatic Transformer construction from a checkpoint and Translator.translate_sentence beam search usage.
  3. Read references/troubleshooting.md when a checkpoint, pickle, vocabulary, CUDA, OOV, or BPE issue appears.

Bundled helpers

  • scripts/inspect_checkpoint.py safely gates unpickling behind an explicit trust flag, then validates checkpoint and optional data-pickle schemas.
  • scripts/translation_smoke_check.py builds a tiny deterministic Transformer and exercises Translator beam search without requiring a trained checkpoint or dataset.

Typical preflight sequence:

python scripts/inspect_checkpoint.py \
  --checkpoint trained.chkpt --data-pkl m30k_deen_shr.pkl --trust-inputs
python scripts/translation_smoke_check.py \
  --repo-root /path/to/repo --device cpu

Operating reminders

  • translate.py loads the checkpoint with torch.load(..., map_location=device) and then reconstructs Transformer from checkpoint['settings']; incompatible settings are found only at load time unless you preflight them.
  • The CLI sets opt.cuda = not opt.no_cuda; on a CPU-only host include -no_cuda or model/device transfer will fail.
  • Translator.translate_sentence asserts batch size one. For multiple examples, iterate one sentence at a time or implement a separate batched decoder.
  • Output lines are target-vocabulary token strings with <s> and </s> removed by simple string replacement. BPE post-decoding is marked TODO/not ready in the repository flow.

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