SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

[breaking|pipelines|tokenizers] Adding slow-fast tokenizers equivalence tests pipelines - Removing sentencepiece as a required dependency (#8073)

Browse Source 
* Fixing roberta for slow-fast tests

* WIP getting equivalence on pipelines

* slow-to-fast equivalence - working on question-answering pipeline

* optional FAISS tests

* Pipeline Q&A

* Move pipeline tests to their own test job again

* update tokenizer to add sequence id methods

* update to tokenizers 0.9.4

* set sentencepiecce as optional

* clean up squad

* clean up pipelines to use sequence_ids

* style/quality

* wording

* Switch to use_fast = True by default

* update tests for use_fast at True by default

* fix rag tokenizer test

* removing protobuf from required dependencies

* fix NER test for use_fast = True by default

* fixing example tests (Q&A examples use slow tokenizers for now)

* protobuf in main deps extras["sentencepiece"] and example deps

* fix protobug install test

* try to fix seq2seq by switching to slow tokenizers for now

* Update src/transformers/tokenization_utils_base.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/tokenization_utils_base.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
This commit is contained in:
Thomas Wolf
2020-11-15 22:50:59 +01:00
committed by GitHub
parent 24184e73c4
commit f4e04cd2c6
23 changed files with 689 additions and 262 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
tests/test_pipelines_zero_shot.py
View File

@@ -12,6 +12,18 @@ class ZeroShotClassificationPipelineTests(CustomInputPipelineCommonMixin, unitte
"sshleifer/tiny-distilbert-base-uncased-finetuned-sst-2-english"
] # Models tested without the @slow decorator
large_models = ["roberta-large-mnli"] # Models tested with the @slow decorator
valid_inputs = [
{"sequences": "Who are you voting for in 2020?", "candidate_labels": "politics"},
{"sequences": "Who are you voting for in 2020?", "candidate_labels": ["politics"]},
{"sequences": "Who are you voting for in 2020?", "candidate_labels": "politics, public health"},
{"sequences": "Who are you voting for in 2020?", "candidate_labels": ["politics", "public health"]},
{"sequences": ["Who are you voting for in 2020?"], "candidate_labels": "politics"},
{
"sequences": "Who are you voting for in 2020?",
"candidate_labels": "politics",
"hypothesis_template": "This text is about {}",
},
]
def _test_scores_sum_to_one(self, result):
sum = 0.0