* First version - OPT model

* Final changes

- putting use cache to False

* few changes

- remove commented block

* few changes

- remove unecessary files

* fix style issues

* few changes

- remove a test file
- added the logits test

* Update src/transformers/models/auto/tokenization_auto.py

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* add gen tests

* few changes

- rm mask filling example on docstring

* few changes

- remove useless args

* some changes

- more tests should pass now
- needs to clean more
- documentation still needs to be done

* fix code quality

* major changes

- change attention architecture to BART-like
- modify some tests
- style fix

* rm useless classes

- remove opt for:
- QA
- cond generation
- seq classif

* Removed autodoc calls to non-existant classes

TOkenizers are not implemented

* Update src/transformers/__init__.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/__init__.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/auto/modeling_tf_auto.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Replaced OPTTokeniser with GPT2 tokenizer

* added GPT2Tokenizer.from_pretrained("patrickvonplaten/opt_gpt2_tokenizer")

* Removed OPTTokenizer

* make style

* Make style replaces

``` ...).unsqueeze(```
by
``` >>>).unsqueeze(```

* make repo consistency

* Removed PretrainedOPTModel

* fix opt.mdx removed other heads

* fix init, removed 3 heads

* removed heads

* finished cleaning head

* removed seauence classif and question answering

* removed unused imports

* removed useless dummy object for QA, SC and CG

* removed tests for removed useless dummy object for QA, SC and CG

* Removed head_mask using encoder layers which don't exist

* fixed test

* fix line

* added OPT to toctree

* Updated model path with pushed weigths

* fix model path

* fixed code quality

* fixed embeddings and generation tests

* update paths

* clean comments

* removed OPTClassificationHead for sentence classification

* renamed hidden layer

* renamed num layers to standard num_hidden_layers

* num_attention_heads fix

* changes for 125m

* add first version for 125m

* add first version - flax

* add new version

* causal LM output

* replace output type with BaseModelOutputWithPastAndCrossAttentions

* revert working config from 150m to 350m

* clean

* removed decoder input ids

* fixed embed dim

* more embed_dim issues

* make style + removed enc_dec test

* update falx model

* removed troublesome copy

* added is_encoder_decoder=False to config

* added set_input emb fuinction to model class

* requires torch on embed test

* use head mask instead of decoder head mask input param solves a test

* 8 test remaining, update

* Updated create_and_check_decoder_model_past_large_inputs

* Make style

* update op tokenizer with condition

* make style

* See if I can push

* some clean up

* remove linear head hack

* save intermediate

* save correct attention

* add copied from from bart

* Update src/transformers/models/opt/modeling_opt.py

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* fix part of the reviewss
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* same changes in naming / conversion

* correct mask

* more fixes

* delete FlaxOPT and TfOPT

* clean traces of Flax and Tf

* fix mask

* fixed positionnal embedding length when past key value is provoded

* get 125m, 6.7b to work

* Added do_layer_norm

* solved mismatch in load dictionnary

* clean up preapre opt input dict

* fixed past key value as bool

* fix previus

* fixed return dict False tuple issue

* All tests are passing

* Make style

* Ignore OPTDecoder non tested

* make fix-copies

* make repo consistency

* small fix

* removed uselss @torch.no_grad decorator

* make styl;e

* fix previous opt test

* style

* make style

* added opt documentation

* update OPT_PRETRAINED_MODEL_ARCHIVE_LIST

* up

* more fixes

* model & config work

* Update src/transformers/models/opt/modeling_opt.py

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/models/opt/modeling_opt.py

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/models/opt/modeling_opt.py

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* added comment on padding hack (+2)

* cleaup

* review update

* docstring for missing arg

* Update docs/source/en/model_doc/opt.mdx

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update docs/source/en/model_doc/opt.mdx

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update docs/source/en/model_doc/opt.mdx

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/models/opt/__init__.py

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* update pretrained map

* update path and tests

* make style

* styling

* make consistency

* add gpt2 tok new

* more tok fixes

* Update src/transformers/models/auto/tokenization_auto.py

* Update docs/source/en/model_doc/opt.mdx

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update docs/source/en/model_doc/opt.mdx

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update docs/source/en/model_doc/opt.mdx

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/models/opt/modeling_opt.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update tests/models/opt/test_modeling_opt.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/models/opt/modeling_opt.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/models/opt/modeling_opt.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/models/opt/modeling_opt.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/models/opt/modeling_opt.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/models/opt/modeling_opt.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update based on reviews

* Apply suggestions from code review

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

* make style

* make tokenizer auto tests pass

* apply Lysandre suggestion

* finish tests

* add some good tokenizer tests

* improve docs slighly

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: ArthurZucker <arthur.zucker@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
This commit is contained in:
Younes Belkada
2022-05-12 12:24:35 +02:00
committed by GitHub
parent 8c7481f35c
commit b971c769e8
22 changed files with 1834 additions and 1 deletions

View File

@@ -175,6 +175,78 @@ class GPT2TokenizationTest(TokenizerTesterMixin, unittest.TestCase):
padding="max_length",
)
def test_padding_if_pad_token_set_slow(self):
tokenizer = GPT2Tokenizer.from_pretrained(self.tmpdirname, pad_token="<pad>")
# Simple input
s = "This is a simple input"
s2 = ["This is a simple input looooooooong", "This is a simple input"]
p = ("This is a simple input", "This is a pair")
p2 = [
("This is a simple input loooooong", "This is a simple input"),
("This is a simple pair loooooong", "This is a simple pair"),
]
pad_token_id = tokenizer.pad_token_id
out_s = tokenizer(s, padding="max_length", max_length=30, return_tensors="np")
out_s2 = tokenizer(s2, padding=True, truncate=True, return_tensors="np")
out_p = tokenizer(*p, padding="max_length", max_length=60, return_tensors="np")
out_p2 = tokenizer(p2, padding=True, truncate=True, return_tensors="np")
# s
# test single string max_length padding
self.assertEqual(out_s["input_ids"].shape[-1], 30)
self.assertTrue(pad_token_id in out_s["input_ids"])
self.assertTrue(0 in out_s["attention_mask"])
# s2
# test automatic padding
self.assertEqual(out_s2["input_ids"].shape[-1], 33)
# long slice doesn't have padding
self.assertFalse(pad_token_id in out_s2["input_ids"][0])
self.assertFalse(0 in out_s2["attention_mask"][0])
# short slice does have padding
self.assertTrue(pad_token_id in out_s2["input_ids"][1])
self.assertTrue(0 in out_s2["attention_mask"][1])
# p
# test single pair max_length padding
self.assertEqual(out_p["input_ids"].shape[-1], 60)
self.assertTrue(pad_token_id in out_p["input_ids"])
self.assertTrue(0 in out_p["attention_mask"])
# p2
# test automatic padding pair
self.assertEqual(out_p2["input_ids"].shape[-1], 52)
# long slice pair doesn't have padding
self.assertFalse(pad_token_id in out_p2["input_ids"][0])
self.assertFalse(0 in out_p2["attention_mask"][0])
# short slice pair does have padding
self.assertTrue(pad_token_id in out_p2["input_ids"][1])
self.assertTrue(0 in out_p2["attention_mask"][1])
def test_add_bos_token_slow(self):
bos_token = "$$$"
tokenizer = GPT2Tokenizer.from_pretrained(self.tmpdirname, bos_token=bos_token, add_bos_token=True)
s = "This is a simple input"
s2 = ["This is a simple input 1", "This is a simple input 2"]
bos_token_id = tokenizer.bos_token_id
out_s = tokenizer(s)
out_s2 = tokenizer(s2)
self.assertEqual(out_s.input_ids[0], bos_token_id)
self.assertTrue(all(o[0] == bos_token_id for o in out_s2.input_ids))
decode_s = tokenizer.decode(out_s.input_ids)
decode_s2 = tokenizer.batch_decode(out_s2.input_ids)
self.assertEqual(decode_s.split()[0], bos_token)
self.assertTrue(all(d.split()[0] == bos_token for d in decode_s2))
# tokenizer has no padding token
def test_padding_different_model_input_name(self):
pass