time series forecasting model (#17965)
* initial files * initial model via cli * typos * make a start on the model config * ready with configuation * remove tokenizer ref. * init the transformer * added initial model forward to return dec_output * require gluonts * update dep. ver table and add as extra * fixed typo * add type for prediction_length * use num_time_features * use config * more config * typos * opps another typo * freq can be none * default via transformation is 1 * initial transformations * fix imports * added transform_start_field * add helper to create pytorch dataloader * added inital val and test data loader * added initial distr head and loss * training working * remove TimeSeriesTransformerTokenizer Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/__init__.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/time_series_transformer/__init__.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * fixed copyright * removed docs * remove time series tokenizer * fixed docs * fix text * fix second * fix default * fix order * use config directly * undo change * fix comment * fix year * fix import * add additional arguments for training vs. test * initial greedy inference loop * fix inference * comment out token inputs to enc dec * Use HF encoder/decoder * fix inference * Use Seq2SeqTSModelOutput output * return Seq2SeqTSPredictionOutput * added default arguments * fix return_dict true * scale is a tensor * output static_features for inference * clean up some unused bits * fixed typo * set return_dict if none * call model once for both train/predict * use cache if future_target is none * initial generate func * generate arguments * future_time_feat is required * return SampleTSPredictionOutput * removed unneeded classes * fix when params is none * fix return dict * fix num_attention_heads * fix arguments * remove unused shift_tokens_right * add different dropout configs * implement FeatureEmbedder, Scaler and weighted_average * remove gluonts dependency * fix class names * avoid _variable names * remove gluonts dependency * fix imports * remove gluonts from configuration * fix docs * fixed typo * move utils to examples * add example requirements * config has no freq * initial run_ts_no_trainer * remove from ignore * fix output_attentions and removed unsued getters/setters * removed unsed tests * add dec seq len * add test_attention_outputs * set has_text_modality=False * add config attribute_map * make style * make fix-copies * add encoder_outputs to TimeSeriesTransformerForPrediction forward * Improve docs, add model to README * added test_forward_signature * More improvements * Add more copied from * Fix README * Fix remaining quality issues * updated encoder and decoder * fix generate * output_hidden_states and use_cache are optional * past key_values returned too * initialize weights of distribution_output module * fixed more tests * update test_forward_signature * fix return_dict outputs * Update src/transformers/models/time_series_transformer/configuration_time_series_transformer.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/models/time_series_transformer/configuration_time_series_transformer.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/models/time_series_transformer/configuration_time_series_transformer.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/models/time_series_transformer/configuration_time_series_transformer.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/models/time_series_transformer/modeling_time_series_transformer.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/models/time_series_transformer/modeling_time_series_transformer.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/models/time_series_transformer/modeling_time_series_transformer.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * removed commented out tests * added neg. bin and normal output * Update src/transformers/models/time_series_transformer/configuration_time_series_transformer.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * move to one line * Add docstrings * Update src/transformers/models/time_series_transformer/configuration_time_series_transformer.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * add try except for assert and raise * try and raise exception * fix the documentation formatting * fix assert call * fix docstring formatting * removed input_ids from DOCSTRING * Update input docstring * Improve variable names * Update order of inputs * Improve configuration * Improve variable names * Improve docs * Remove key_length from tests * Add extra docs * initial unittests * added test_inference_no_head test * added test_inference_head * add test_seq_to_seq_generation * make style * one line * assert mean prediction * removed comments * Update src/transformers/models/time_series_transformer/modeling_time_series_transformer.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/time_series_transformer/modeling_time_series_transformer.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * fix order of args * make past_observed_mask optional as well * added Amazon license header * updated utils with new fieldnames * make style * cleanup * undo position of past_observed_mask * fix import * typo * more typo * rename example files * remove example for now * Update docs/source/en/_toctree.yml Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/models/time_series_transformer/configuration_time_series_transformer.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/models/time_series_transformer/modeling_time_series_transformer.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/models/time_series_transformer/modeling_time_series_transformer.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update modeling_time_series_transformer.py fix style * fixed typo * fix typo and grammer * fix style Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: NielsRogge <niels.rogge1@gmail.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
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@@ -375,6 +375,7 @@ Current number of checkpoints: ** (from Google AI) released in the repository [google-research/text-to-text-transfer-transformer](https://github.com/google-research/text-to-text-transfer-transformer/blob/main/released_checkpoints.md#t511) by Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu.
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1. **[TAPAS](https://huggingface.co/docs/transformers/model_doc/tapas)** (from Google AI) released with the paper [TAPAS: Weakly Supervised Table Parsing via Pre-training](https://arxiv.org/abs/2004.02349) by Jonathan Herzig, Paweł Krzysztof Nowak, Thomas Müller, Francesco Piccinno and Julian Martin Eisenschlos.
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1. **[TAPEX](https://huggingface.co/docs/transformers/model_doc/tapex)** (from Microsoft Research) released with the paper [TAPEX: Table Pre-training via Learning a Neural SQL Executor](https://arxiv.org/abs/2107.07653) by Qian Liu, Bei Chen, Jiaqi Guo, Morteza Ziyadi, Zeqi Lin, Weizhu Chen, Jian-Guang Lou.
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1. **[Time Series Transformer](https://huggingface.co/docs/transformers/main/model_doc/time_series_transformer)** (from HuggingFace).
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1. **[Trajectory Transformer](https://huggingface.co/docs/transformers/model_doc/trajectory_transformers)** (from the University of California at Berkeley) released with the paper [Offline Reinforcement Learning as One Big Sequence Modeling Problem](https://arxiv.org/abs/2106.02039) by Michael Janner, Qiyang Li, Sergey Levine
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1. **[Transformer-XL](https://huggingface.co/docs/transformers/model_doc/transfo-xl)** (from Google/CMU) released with the paper [Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context](https://arxiv.org/abs/1901.02860) by Zihang Dai*, Zhilin Yang*, Yiming Yang, Jaime Carbonell, Quoc V. Le, Ruslan Salakhutdinov.
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1. **[TrOCR](https://huggingface.co/docs/transformers/model_doc/trocr)** (from Microsoft), released together with the paper [TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models](https://arxiv.org/abs/2109.10282) by Minghao Li, Tengchao Lv, Lei Cui, Yijuan Lu, Dinei Florencio, Cha Zhang, Zhoujun Li, Furu Wei.
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