Speech2TextTransformer (#10175)

* s2t

* fix config

* conversion script

* fix import

* add tokenizer

* fix tok init

* fix tokenizer

* first version working

* fix embeds

* fix lm head

* remove extra heads

* fix convert script

* handle encoder attn mask

* style

* better enc attn mask

* override _prepare_attention_mask_for_generation

* handle attn_maks in encoder and decoder

* input_ids => input_features

* enable use_cache

* remove old code

* expand embeddings if needed

* remove logits bias

* masked_lm_loss => loss

* hack tokenizer to support feature processing

* fix model_input_names

* style

* fix error message

* doc

* remove inputs_embeds

* remove input_embeds

* remove unnecessary docstring

* quality

* SpeechToText => Speech2Text

* style

* remove shared_embeds

* subsample => conv

* remove Speech2TextTransformerDecoderWrapper

* update output_lengths formula

* fix table

* remove max_position_embeddings

* update conversion scripts

* add possibility to do upper case for now

* add FeatureExtractor and Processor

* add tests for extractor

* require_torch_audio => require_torchaudio

* add processor test

* update import

* remove classification head

* attention mask is now 1D

* update docstrings

* attention mask should be of type long

* handle attention mask from generate

* alwyas return attention_mask

* fix test

* style

* doc

* Speech2TextTransformer => Speech2Text

* Speech2TextTransformerConfig => Speech2TextConfig

* remove dummy_inputs

* nit

* style

* multilinguial tok

* fix tokenizer

* add tgt_lang setter

* save lang_codes

* fix tokenizer

* add forced_bos_token_id to tokenizer

* apply review suggestions

* add torchaudio to extra deps

* add speech deps to CI

* fix dep

* add libsndfile to ci

* libsndfile1

* add speech to extras all

* libsndfile1 -> libsndfile1

* libsndfile

* libsndfile1-dev

* apt update

* add sudo to install

* update deps table

* install libsndfile1-dev on CI

* tuple to list

* init conv layer

* add model tests

* quality

* add integration tests

* skip_special_tokens

* add speech_to_text_transformer in toctree

* fix tokenizer

* fix fp16 tests

* add tokenizer tests

* fix copyright

* input_values => input_features

* doc

* add model in readme

* doc

* change checkpoint names

* fix copyright

* fix code example

* add max_model_input_sizes in tokenizer

* fix integration tests

* add do_lower_case to tokenizer

* remove clamp trick

* fix "Add modeling imports here"

* fix copyrights

* fix tests

* SpeechToTextTransformer => SpeechToText

* fix naming

* fix table formatting

* fix typo

* style

* fix typos

* remove speech dep from extras[testing]

* fix copies

* rename doc file,

* put imports under is_torch_available

* run feat extract tests when torch is available

* dummy objects for processor and extractor

* fix imports in tests

* fix import in modeling test

* fxi imports

* fix torch import

* fix imports again

* fix positional embeddings

* fix typo in import

* adapt new extractor refactor

* style

* fix torchscript test

* doc

* doc

* Apply suggestions from code review

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* fix docs, copied from, style

* fix docstring

* handle imports

* remove speech from all extra deps

* remove s2t from seq2seq lm mapping

* better names

* skip training tests

* add install instructions

* List => Tuple

* doc

* fix conversion script

* fix urls

* add instruction for libsndfile

* fix fp16 test

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

tests/test_generation_utils.py

@@ -53,12 +53,13 @@ if is_torch_available():
 class GenerationTesterMixin:
     model_tester = None
     all_generative_model_classes = ()
+    input_name = "input_ids"
 
     def _get_input_ids_and_config(self):
         config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
 
-        input_ids = inputs_dict["input_ids"]
-        attention_mask = torch.ones_like(input_ids)
+        input_ids = inputs_dict[self.input_name]
+        attention_mask = torch.ones_like(input_ids, dtype=torch.long)
 
         # cut to half length & take max batch_size 3
         max_batch_size = 2