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d9c0d08f9a
* add flax bert * bert -> bigbird * original_full ported * add debugger * init block sparse * fix copies ; gelu_fast -> gelu_new * block sparse port * fix block sparse * block sparse working * all ckpts working * fix-copies * make quality * init tests * temporary fix for FlaxBigBirdForMultipleChoice * skip test_attention_outputs * fix * gelu_fast -> gelu_new ; fix multiple choice model * remove nsp * fix sequence classifier * fix * make quality * make fix-copies * finish * Delete debugger.ipynb * Update src/transformers/models/big_bird/modeling_flax_big_bird.py * make style * finish * bye bye jit flax tests Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
186 lines
7.9 KiB
ReStructuredText
186 lines
7.9 KiB
ReStructuredText
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Copyright 2021 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
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specific language governing permissions and limitations under the License.
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BigBird
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-----------------------------------------------------------------------------------------------------------------------
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Overview
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The BigBird model was proposed in `Big Bird: Transformers for Longer Sequences <https://arxiv.org/abs/2007.14062>`__ by
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Zaheer, Manzil and Guruganesh, Guru and Dubey, Kumar Avinava and Ainslie, Joshua and Alberti, Chris and Ontanon,
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Santiago and Pham, Philip and Ravula, Anirudh and Wang, Qifan and Yang, Li and others. BigBird, is a sparse-attention
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based transformer which extends Transformer based models, such as BERT to much longer sequences. In addition to sparse
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attention, BigBird also applies global attention as well as random attention to the input sequence. Theoretically, it
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has been shown that applying sparse, global, and random attention approximates full attention, while being
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computationally much more efficient for longer sequences. As a consequence of the capability to handle longer context,
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BigBird has shown improved performance on various long document NLP tasks, such as question answering and
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summarization, compared to BERT or RoBERTa.
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The abstract from the paper is the following:
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*Transformers-based models, such as BERT, have been one of the most successful deep learning models for NLP.
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Unfortunately, one of their core limitations is the quadratic dependency (mainly in terms of memory) on the sequence
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length due to their full attention mechanism. To remedy this, we propose, BigBird, a sparse attention mechanism that
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reduces this quadratic dependency to linear. We show that BigBird is a universal approximator of sequence functions and
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is Turing complete, thereby preserving these properties of the quadratic, full attention model. Along the way, our
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theoretical analysis reveals some of the benefits of having O(1) global tokens (such as CLS), that attend to the entire
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sequence as part of the sparse attention mechanism. The proposed sparse attention can handle sequences of length up to
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8x of what was previously possible using similar hardware. As a consequence of the capability to handle longer context,
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BigBird drastically improves performance on various NLP tasks such as question answering and summarization. We also
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propose novel applications to genomics data.*
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Tips:
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- For an in-detail explanation on how BigBird's attention works, see `this blog post
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<https://huggingface.co/blog/big-bird>`__.
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- BigBird comes with 2 implementations: **original_full** & **block_sparse**. For the sequence length < 1024, using
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**original_full** is advised as there is no benefit in using **block_sparse** attention.
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- The code currently uses window size of 3 blocks and 2 global blocks.
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- Sequence length must be divisible by block size.
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- Current implementation supports only **ITC**.
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- Current implementation doesn't support **num_random_blocks = 0**
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This model was contributed by `vasudevgupta <https://huggingface.co/vasudevgupta>`__. The original code can be found
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`here <https://github.com/google-research/bigbird>`__.
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BigBirdConfig
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.BigBirdConfig
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:members:
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BigBirdTokenizer
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.BigBirdTokenizer
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:members: build_inputs_with_special_tokens, get_special_tokens_mask,
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create_token_type_ids_from_sequences, save_vocabulary
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BigBirdTokenizerFast
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.BigBirdTokenizerFast
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:members:
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BigBird specific outputs
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.models.big_bird.modeling_big_bird.BigBirdForPreTrainingOutput
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:members:
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BigBirdModel
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.BigBirdModel
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:members: forward
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BigBirdForPreTraining
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.BigBirdForPreTraining
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:members: forward
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BigBirdForCausalLM
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.BigBirdForCausalLM
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:members: forward
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BigBirdForMaskedLM
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.BigBirdForMaskedLM
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:members: forward
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BigBirdForSequenceClassification
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.BigBirdForSequenceClassification
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:members: forward
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BigBirdForMultipleChoice
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.BigBirdForMultipleChoice
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:members: forward
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BigBirdForTokenClassification
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.BigBirdForTokenClassification
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:members: forward
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BigBirdForQuestionAnswering
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.BigBirdForQuestionAnswering
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:members: forward
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FlaxBigBirdModel
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.FlaxBigBirdModel
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:members: __call__
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FlaxBigBirdForPreTraining
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.FlaxBigBirdForPreTraining
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:members: __call__
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FlaxBigBirdForMaskedLM
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.FlaxBigBirdForMaskedLM
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:members: __call__
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FlaxBigBirdForSequenceClassification
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.FlaxBigBirdForSequenceClassification
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:members: __call__
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FlaxBigBirdForMultipleChoice
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.FlaxBigBirdForMultipleChoice
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:members: __call__
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FlaxBigBirdForTokenClassification
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.FlaxBigBirdForTokenClassification
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:members: __call__
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FlaxBigBirdForQuestionAnswering
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.FlaxBigBirdForQuestionAnswering
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:members: __call__
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