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* Add cross attentions to TFGPT2Model * Add TFEncoderDecoderModel * Add TFBaseModelOutputWithPoolingAndCrossAttentions * Add cross attentions to TFBertModel * Fix past or past_key_values argument issue * Fix generation * Fix save and load * Add some checks and comments * Clean the code that deals with past keys/values * Add kwargs to processing_inputs * Add serving_output to TFEncoderDecoderModel * Some cleaning + fix use_cache value issue * Fix tests + add bert2bert/bert2gpt2 tests * Fix more tests * Ignore crossattention.bias when loading GPT2 weights into TFGPT2 * Fix return_dict_in_generate in tf generation * Fix is_token_logit_eos_token bug in tf generation * Finalize the tests after fixing some bugs * Fix another is_token_logit_eos_token bug in tf generation * Add/Update docs * Add TFBertEncoderDecoderModelTest * Clean test script * Add TFEncoderDecoderModel to the library * Add cross attentions to TFRobertaModel * Add TFRobertaEncoderDecoderModelTest * make style * Change the way of position_ids computation * bug fix * Fix copies in tf_albert * Remove some copied from and apply some fix-copies * Remove some copied * Add cross attentions to some other TF models * Remove encoder_hidden_states from TFLayoutLMModel.call for now * Make style * Fix TFRemBertForCausalLM * Revert the change to longformer + Remove copies * Revert the change to albert and convbert + Remove copies * make quality * make style * Add TFRembertEncoderDecoderModelTest * make quality and fix-copies * test TFRobertaForCausalLM * Fixes for failed tests * Fixes for failed tests * fix more tests * Fixes for failed tests * Fix Auto mapping order * Fix TFRemBertEncoder return value * fix tf_rembert * Check copies are OK * Fix missing TFBaseModelOutputWithPastAndCrossAttentions is not defined * Add TFEncoderDecoderModelSaveLoadTests * fix tf weight loading * check the change of use_cache * Revert the change * Add missing test_for_causal_lm for TFRobertaModelTest * Try cleaning past * fix _reorder_cache * Revert some files to original versions * Keep as many copies as possible * Apply suggested changes - Use raise ValueError instead of assert * Move import to top * Fix wrong require_torch * Replace more assert by raise ValueError * Add test_pt_tf_model_equivalence (the test won't pass for now) * add test for loading/saving * finish * finish * Remove test_pt_tf_model_equivalence * Update tf modeling template * Remove pooling, added in the prev. commit, from MainLayer * Update tf modeling test template * Move inputs["use_cache"] = False to modeling_tf_utils.py * Fix torch.Tensor in the comment * fix use_cache * Fix missing use_cache in ElectraConfig * Add a note to from_pretrained * Fix style * Change test_encoder_decoder_save_load_from_encoder_decoder_from_pt * Fix TFMLP (in TFGPT2) activation issue * Fix None past_key_values value in serving_output * Don't call get_encoderdecoder_model in TFEncoderDecoderModelTest.test_configuration_tie until we have a TF checkpoint on Hub * Apply review suggestions - style for cross_attns in serving_output * Apply review suggestions - change assert + docstrings * break the error message to respect the char limit * deprecate the argument past * fix docstring style * Update the encoder-decoder rst file * fix Unknown interpreted text role "method" * fix typo Co-authored-by: ydshieh <ydshieh@users.noreply.github.com> Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
76 lines
3.6 KiB
ReStructuredText
76 lines
3.6 KiB
ReStructuredText
..
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Copyright 2020 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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Encoder Decoder Models
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-----------------------------------------------------------------------------------------------------------------------
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The :class:`~transformers.EncoderDecoderModel` can be used to initialize a sequence-to-sequence model with any
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pretrained autoencoding model as the encoder and any pretrained autoregressive model as the decoder.
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The effectiveness of initializing sequence-to-sequence models with pretrained checkpoints for sequence generation tasks
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was shown in `Leveraging Pre-trained Checkpoints for Sequence Generation Tasks <https://arxiv.org/abs/1907.12461>`__ by
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Sascha Rothe, Shashi Narayan, Aliaksei Severyn.
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After such an :class:`~transformers.EncoderDecoderModel` has been trained/fine-tuned, it can be saved/loaded just like
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any other models (see the examples for more information).
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An application of this architecture could be to leverage two pretrained :class:`~transformers.BertModel` as the encoder
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and decoder for a summarization model as was shown in: `Text Summarization with Pretrained Encoders
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<https://arxiv.org/abs/1908.08345>`__ by Yang Liu and Mirella Lapata.
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The :meth:`~transformers.TFEncoderDecoderModel.from_pretrained` currently doesn't support initializing the model from a
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pytorch checkpoint. Passing ``from_pt=True`` to this method will throw an exception. If there are only pytorch
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checkpoints for a particular encoder-decoder model, a workaround is:
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.. code-block::
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>>> # a workaround to load from pytorch checkpoint
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>>> _model = EncoderDecoderModel.from_pretrained("patrickvonplaten/bert2bert-cnn_dailymail-fp16")
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>>> _model.encoder.save_pretrained("./encoder")
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>>> _model.decoder.save_pretrained("./decoder")
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>>> model = TFEncoderDecoderModel.from_encoder_decoder_pretrained(
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... "./encoder", "./decoder", encoder_from_pt=True, decoder_from_pt=True
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... )
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>>> # This is only for copying some specific attributes of this particular model.
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>>> model.config = _model.config
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This model was contributed by `thomwolf <https://github.com/thomwolf>`__. This model's TensorFlow and Flax versions
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were contributed by `ydshieh <https://github.com/ydshieh>`__.
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EncoderDecoderConfig
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.EncoderDecoderConfig
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:members:
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EncoderDecoderModel
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.EncoderDecoderModel
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:members: forward, from_encoder_decoder_pretrained
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TFEncoderDecoderModel
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.TFEncoderDecoderModel
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:members: call, from_encoder_decoder_pretrained
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FlaxEncoderDecoderModel
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.FlaxEncoderDecoderModel
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:members: __call__, from_encoder_decoder_pretrained
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