Reformer (#3351)

* first copy & past commit from Bert and morgans LSH code

* add easy way to compare to trax original code

* translate most of function

* make trax lsh self attention deterministic with numpy seed + copy paste code

* add same config

* add same config

* make layer init work

* implemented hash_vectors function for lsh attention

* continue reformer translation

* hf LSHSelfAttentionLayer gives same output as trax layer

* refactor code

* refactor code

* refactor code

* refactor

* refactor + add reformer config

* delete bogus file

* split reformer attention layer into two layers

* save intermediate step

* save intermediate step

* make test work

* add complete reformer block layer

* finish reformer layer

* implement causal and self mask

* clean reformer test and refactor code

* fix merge conflicts

* fix merge conflicts

* update init

* fix device for GPU

* fix chunk length init for tests

* include morgans optimization

* improve memory a bit

* improve comment

* factorize num_buckets

* better testing parameters

* make whole model work

* make lm model work

* add t5 copy paste tokenizer

* add chunking feed forward

* clean config

* add improved assert statements

* make tokenizer work

* improve test

* correct typo

* extend config

* add complexer test

* add new axial position embeddings

* add local block attention layer

* clean tests

* refactor

* better testing

* save intermediate progress

* clean test file

* make shorter input length work for model

* allow variable input length

* refactor

* make forward pass for pretrained model work

* add generation possibility

* finish dropout and init

* make style

* refactor

* add first version of RevNet Layers

* make forward pass work and add convert file

* make uploaded model forward pass work

* make uploaded model forward pass work

* refactor code

* add namedtuples and cache buckets

* correct head masks

* refactor

* made reformer more flexible

* make style

* remove set max length

* add attention masks

* fix up tests

* fix lsh attention mask

* make random seed optional for the moment

* improve memory in reformer

* add tests

* make style

* make sure masks work correctly

* detach gradients

* save intermediate

* correct backprob through gather

* make style

* change back num hashes

* rename to labels

* fix rotation shape

* fix detach

* update

* fix trainer

* fix backward dropout

* make reformer more flexible

* fix conflict

* fix

* fix

* add tests for fixed seed in reformer layer

* fix trainer typo

* fix typo in activations

* add fp16 tests

* add fp16 training

* support fp16

* correct gradient bug in reformer

* add fast gelu

* re-add dropout for embedding dropout

* better naming

* better naming

* renaming

* finalize test branch

* finalize tests

* add more tests

* finish tests

* fix

* fix type trainer

* fix fp16 tests

* fix tests

* fix tests

* fix tests

* fix issue with dropout

* fix dropout seeds

* correct random seed on gpu

* finalize random seed for dropout

* finalize random seed for dropout

* remove duplicate line

* correct half precision bug

* make style

* refactor

* refactor

* docstring

* remove sinusoidal position encodings for reformer

* move chunking to modeling_utils

* make style

* clean config

* make style

* fix tests

* fix auto tests

* pretrained models

* fix docstring

* update conversion file

* Update pretrained_models.rst

* fix rst

* fix rst

* update copyright

* fix test path

* fix test path

* fix small issue in test

* include reformer in generation tests

* add docs for axial position encoding

* finish docs

* Update convert_reformer_trax_checkpoint_to_pytorch.py

* remove isort

* include sams comments

* remove wrong comment in utils

* correct typos

* fix typo

* Update reformer.rst

* applied morgans optimization

* make style

* make gpu compatible

* remove bogus file

* big test refactor

* add example for chunking

* fix typo

* add to README

src/transformers/__init__.py

@@ -47,6 +47,7 @@ from .configuration_gpt2 import GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP, GPT2Config
 from .configuration_marian import MarianConfig
 from .configuration_mmbt import MMBTConfig
 from .configuration_openai import OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenAIGPTConfig
+from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig
 from .configuration_roberta import ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, RobertaConfig
 from .configuration_t5 import T5_PRETRAINED_CONFIG_ARCHIVE_MAP, T5Config
 from .configuration_transfo_xl import TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP, TransfoXLConfig
@@ -138,6 +139,7 @@ from .tokenization_electra import ElectraTokenizer, ElectraTokenizerFast
 from .tokenization_flaubert import FlaubertTokenizer
 from .tokenization_gpt2 import GPT2Tokenizer, GPT2TokenizerFast
 from .tokenization_openai import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
+from .tokenization_reformer import ReformerTokenizer
 from .tokenization_roberta import RobertaTokenizer, RobertaTokenizerFast
 from .tokenization_t5 import T5Tokenizer
 from .tokenization_transfo_xl import TransfoXLCorpus, TransfoXLTokenizer, TransfoXLTokenizerFast
@@ -159,7 +161,7 @@ if is_sklearn_available():
 
 # Modeling
 if is_torch_available():
-    from .modeling_utils import PreTrainedModel, prune_layer, Conv1D, top_k_top_p_filtering
+    from .modeling_utils import PreTrainedModel, prune_layer, Conv1D, top_k_top_p_filtering, apply_chunking_to_forward
     from .modeling_auto import (
         AutoModel,
         AutoModelForPreTraining,
@@ -190,6 +192,7 @@ if is_torch_available():
         BertForQuestionAnswering,
         load_tf_weights_in_bert,
         BERT_PRETRAINED_MODEL_ARCHIVE_MAP,
+        BertLayer,
     )
     from .modeling_openai import (
         OpenAIGPTPreTrainedModel,
@@ -320,6 +323,14 @@ if is_torch_available():
         ELECTRA_PRETRAINED_MODEL_ARCHIVE_MAP,
     )
 
+    from .modeling_reformer import (
+        ReformerAttention,
+        ReformerLayer,
+        ReformerModel,
+        ReformerModelWithLMHead,
+        REFORMER_PRETRAINED_MODEL_ARCHIVE_MAP,
+    )
+
     # Optimization
     from .optimization import (
         AdamW,