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  1. 25 Feb, 2020 1 commit
  3. 24 Feb, 2020 4 commits
  5. 22 Feb, 2020 2 commits
  7. 21 Feb, 2020 1 commit
    • Patrick von Platen's avatar
      Improve special_token_id logic in run_generation.py and add tests (#2885) · fc38d4c8
      Patrick von Platen authored 
      

* improving generation

* finalized special token behaviour for no_beam_search generation

* solved modeling_utils merge conflict

* solve merge conflicts in modeling_utils.py

* add run_generation improvements from PR #2749

* adapted language generation to not use hardcoded -1 if no padding token is available

* remove the -1 removal as hard coded -1`s are not necessary anymore

* add lightweight language generation testing for randomely initialized models - just checking whether no errors are thrown

* add slow language generation tests for pretrained models using hardcoded output with pytorch seed

* delete ipdb

* check that all generated tokens are valid

* renaming

* renaming Generation -> Generate

* make style

* updated so that generate_beam_search has same token behavior than generate_no_beam_search

* consistent return format for run_generation.py

* deleted pretrain lm generate tests -> will be added in another PR

* cleaning of unused if statements and renaming

* run_generate will always return an iterable

* make style

* consistent renaming

* improve naming, make sure generate function always returns the same tensor, add docstring

* add slow tests for all lmhead models

* make style and improve example comments modeling_utils

* better naming and refactoring in modeling_utils

* improving generation

* finalized special token behaviour for no_beam_search generation

* solved modeling_utils merge conflict

* solve merge conflicts in modeling_utils.py

* add run_generation improvements from PR #2749

* adapted language generation to not use hardcoded -1 if no padding token is available

* remove the -1 removal as hard coded -1`s are not necessary anymore

* add lightweight language generation testing for randomely initialized models - just checking whether no errors are thrown

* add slow language generation tests for pretrained models using hardcoded output with pytorch seed

* delete ipdb

* check that all generated tokens are valid

* renaming

* renaming Generation -> Generate

* make style

* updated so that generate_beam_search has same token behavior than generate_no_beam_search

* consistent return format for run_generation.py

* deleted pretrain lm generate tests -> will be added in another PR

* cleaning of unused if statements and renaming

* run_generate will always return an iterable

* make style

* consistent renaming

* improve naming, make sure generate function always returns the same tensor, add docstring

* add slow tests for all lmhead models

* make style and improve example comments modeling_utils

* better naming and refactoring in modeling_utils

* changed fast random lm generation testing design to more general one

* delete in old testing design in gpt2

* correct old variable name

* temporary fix for encoder_decoder lm generation tests - has to be updated when t5 is fixed

* adapted all fast random generate tests to new design

* better warning description in modeling_utils

* better comment

* better comment and error message
Co-authored-by: default avatarThomas Wolf <thomwolf@users.noreply.github.com>
      fc38d4c8
  9. 20 Feb, 2020 2 commits
  11. 19 Feb, 2020 3 commits
  13. 18 Feb, 2020 1 commit
  15. 13 Feb, 2020 2 commits
    • Joe Davison's avatar
      Preserve spaces in GPT-2 tokenizers (#2778) · f1e8a51f
      Joe Davison authored 
      * Preserve spaces in GPT-2 tokenizers

Preserves spaces after special tokens in GPT-2 and inhereted (RoBERTa)
tokenizers, enabling correct BPE encoding. Automatically inserts a space
in front of first token in encode function when adding special tokens.

* Add tokenization preprocessing method

* Add framework argument to pipeline factory

Also fixes pipeline test issue. Each test input now treated as a
distinct sequence.
      f1e8a51f
    • Sam Shleifer's avatar
      get_activation('relu') provides a simple mapping from strings i… (#2807) · ef74b0f0
      Sam Shleifer authored 
      * activations.py contains a mapping from string to activation function
* resolves some `gelu` vs `gelu_new` ambiguity
      ef74b0f0
  17. 11 Feb, 2020 1 commit
    • Oleksiy Syvokon's avatar
      BERT decoder: Fix causal mask dtype. · ee5de0ba
      Oleksiy Syvokon authored 
      PyTorch < 1.3 requires multiplication operands to be of the same type.
This was violated when using default attention mask (i.e.,
attention_mask=None in arguments) given BERT in the decoder mode.

In particular, this was breaking Model2Model and made tutorial
from the quickstart failing.
      ee5de0ba
  19. 07 Feb, 2020 2 commits
  21. 04 Feb, 2020 8 commits
  23. 31 Jan, 2020 1 commit
  25. 30 Jan, 2020 2 commits
    • Julien Chaumond's avatar
      fill_mask helper (#2576) · 9fa836a7
      Julien Chaumond authored 
      * fill_mask helper

* [poc] FillMaskPipeline

* Revert "[poc] FillMaskPipeline"

This reverts commit 67eeea55b0f97b46c2b828de0f4ee97d87338335.

* Revert "fill_mask helper"

This reverts commit cacc17b884e14bb6b07989110ffe884ad9e36eaa.

* README: clarify that Pipelines can also do text-classification

cf. question at the AI&ML meetup last week, @mfuntowicz

* Fix test: test feature-extraction pipeline

* Test tweaks

* Slight refactor of existing pipeline (in preparation of new FillMaskPipeline)

* Extraneous doc

* More robust way of doing this

@mfuntowicz as we don't rely on the model name anymore (see AutoConfig)

* Also add RobertaConfig as a quickfix for wrong token_type_ids

* cs

* [BIG] FillMaskPipeline
      9fa836a7
    • Lysandre's avatar
      Rename test_examples to test_doc_samples · df27648b
      Lysandre authored
      df27648b
  27. 29 Jan, 2020 2 commits
  29. 28 Jan, 2020 1 commit
  31. 27 Jan, 2020 2 commits
  33. 23 Jan, 2020 5 commits