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4b6a5a7caa
* ran `transformers-cli add-new-model-like`
* added `AutoformerLayernorm` and `AutoformerSeriesDecomposition`
* added `decomposition_layer` in `init` and `moving_avg` to config
* added `AutoformerAutoCorrelation` to encoder & decoder
* removed caninical self attention `AutoformerAttention`
* added arguments in config and model tester. Init works! 😁
* WIP autoformer attention with autocorrlation
* fixed `attn_weights` size
* wip time_delay_agg_training
* fixing sizes and debug time_delay_agg_training
* aggregation in training works! 😁
* `top_k_delays` -> `top_k_delays_index` and added `contiguous()`
* wip time_delay_agg_inference
* finish time_delay_agg_inference 😎
* added resize to autocorrelation
* bug fix: added the length of the output signal to `irfft`
* `attention_mask = None` in the decoder
* fixed test: changed attention expected size, `test_attention_outputs` works!
* removed unnecessary code
* apply AutoformerLayernorm in final norm in enc & dec
* added series decomposition to the encoder
* added series decomp to decoder, with inputs
* added trend todos
* added autoformer to README
* added to index
* added autoformer.mdx
* remove scaling and init attention_mask in the decoder
* make style
* fix copies
* make fix-copies
* inital fix-copies
* fix from https://github.com/huggingface/transformers/pull/22076
* make style
* fix class names
* added trend
* added d_model and projection layers
* added `trend_projection` source, and decomp layer init
* added trend & seasonal init for decoder input
* AutoformerModel cannot be copied as it has the decomp layer too
* encoder can be copied from time series transformer
* fixed generation and made distrb. out more robust
* use context window to calculate decomposition
* use the context_window for decomposition
* use output_params helper
* clean up AutoformerAttention
* subsequences_length off by 1
* make fix copies
* fix test
* added init for nn.Conv1d
* fix IGNORE_NON_TESTED
* added model_doc
* fix ruff
* ignore tests
* remove dup
* fix SPECIAL_CASES_TO_ALLOW
* do not copy due to conv1d weight init
* remove unused imports
* added short summary
* added label_length and made the model non-autoregressive
* added params docs
* better doc for `factor`
* fix tests
* renamed `moving_avg` to `moving_average`
* renamed `factor` to `autocorrelation_factor`
* make style
* Update src/transformers/models/autoformer/configuration_autoformer.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Update src/transformers/models/autoformer/configuration_autoformer.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* fix configurations
* fix integration tests
* Update src/transformers/models/autoformer/configuration_autoformer.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* fixing `lags_sequence` doc
* Revert "fixing `lags_sequence` doc"
This reverts commit
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| .. | ||
| benchmark | ||
| bettertransformer | ||
| bitsandbytes | ||
| deepspeed | ||
| extended | ||
| fixtures | ||
| generation | ||
| models | ||
| onnx | ||
| optimization | ||
| pipelines | ||
| repo_utils | ||
| sagemaker | ||
| tokenization | ||
| tools | ||
| trainer | ||
| utils | ||
| __init__.py | ||
| test_backbone_common.py | ||
| test_configuration_common.py | ||
| test_feature_extraction_common.py | ||
| test_image_processing_common.py | ||
| test_image_transforms.py | ||
| test_modeling_common.py | ||
| test_modeling_flax_common.py | ||
| test_modeling_tf_common.py | ||
| test_pipeline_mixin.py | ||
| test_sequence_feature_extraction_common.py | ||
| test_tokenization_common.py | ||