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CTranslate2 2.0.0
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@guillaumekln guillaumekln released this 03 Jun 08:56
· 892 commits to master since this release
v2.0.0
76de4d7

This major version introduces some breaking changes to simplify model conversion, improve the consistency of user options, and update the Python package to CUDA 11.x. It also comes with internal improvements to facilitate future changes.

Breaking changes

General

  • Disable return_scores by default as most applications do not use translation scores
  • Replace all Docker images by a single one: <version>-ubuntu20.04-cuda11.2
  • Replace CMake option LIB_ONLY by BUILD_CLI
  • Require CMake version >= 3.15 for GPU compilation

Python

  • For GPU execution, the Linux Python wheels published on PyPI now require CUDA 11.x to be installed on the system. The CUDA dependencies (e.g. cuBLAS) are no longer included in the package and are loaded dynamically.
  • Remove support for converting the TensorFlow SavedModel format (checkpoints should be converted instead)
  • Remove the model_spec option for converters that can automatically detect it from the checkpoints
  • Force translation options to be set with keyword arguments only (see the API reference)
  • Rename tokenization callables arguments in translate_file for clarity:
    • tokenize_fn to source_tokenize_fn
    • detokenize_fn to target_detokenize_fn

CLI

  • Rename length constraints options for consistency with other APIs:
    • max_sent_length to max_decoding_length
    • min_sent_length to min_decoding_length

C++

  • Move the max_batch_size and batch_type options from the TranslationOptions structure to the translation methods of TranslatorPool
  • Simplify the TranslationResult structure with public attributes instead of methods
  • Asynchronous translation API now returns one future per example instead of a single future for the batch

New features

  • Add translation option prefix_bias_beta to bias the decoding towards the target prefix (see Arivazhagan et al. 2020)
  • Automatically detect the model specification when converting OpenNMT-py models
  • Support conversion and execution of Post-Norm Transformers
  • Add an experimental asynchronous memory allocator for CUDA 11.2 and above (can be enabled with the environment variable CT2_CUDA_ALLOCATOR=cuda_malloc_async)
  • Expose the Python package version in ctranslate2.__version__

Fixes and improvements

  • Fix silent activation of replace_unknowns when enabling return_attention
  • Improve support for the NVIDIA Ampere architecture in prebuilt binaries
  • Reduce the size of the Python wheels published on PyPI
  • Define a custom CUDA kernel for the GEMM output dequantization instead of a Thrust-based implementation
  • Update Thrust to 1.12.0
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