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  1. 24 Mar, 2023 2 commits
    • Mitch Naylor's avatar
      Add Mega: Moving Average Equipped Gated Attention (#21766) · 57f25f4b
      Mitch Naylor authored 
      

* add mega file structure and plain pytorch version of mega source code

* added config class with old naming conventions

* filled in mega documentation

* added config class and embeddings with optional token types

* updated notes

* starting the conversion process, deleted intermediate and added use_cache back to config

* renamed config attributes in modeling_mega.py

* checkpointing before refactoring incremental decoding functions

* removed stateful incremental key/values for EMA and self-attention

* refactored MovingAverageGatedAttention to remove stateful k/v history and use unified attention mask

* MovingAverageGatedAttention works with incremental decoding + past values, added sequence length enforcement

* more comments in MovingAverageGatedAttention + checkpointing before GatedCrossAttention

* bug fix in attention mask handling in MovingAverageGatedAttention

* removed incremental state from GatedCrossAttention and removed IncrementalState class

* finished gated cross attention and got MegaLayer working

* fixed causal masking in mega decoder

* fixed how padding and causal masks are passed through MegaLayer with and without k/v caching

* finished MegaModel; tested with encoder, decoder-only, and cross-attention type inputs; started work on downstream classes; removed mentions of position_ids

* added optional dense hidden layer for masked and causal LM classes

* docstring updates in MultiHeadEMA and GatedCrossAttention, removed unnecessary inputs in cross-attention

* removed before_attn_fn in Mega class and updated docstrings and comments up to there

* bug fix in MovingAverageGatedAttention masking

* working conversion of MLM checkpoint in scratchpad script -- perfect matches

* moved arg for hidden dense layer in LM head to config; discovered issue where from_pretrained is renaming gamma and beta parameters

* renamed gamma and beta parameters to avoid HF renaming when loading from checkpoint

* finished checkpoint conversion script

* cleanup old class in mega config script

* removed 'copied from' statements and passing integration tests

* added num_attention_heads=1 to config for integration compatibility, decoder tests working, generation tests failing

* fixed tuple output of megamodel

* all common tests passing after fixing issues in decoder, gradient retention, and initialization

* added mega-specific tests, ready for more documentation and style checks

* updated docstrings; checkpoint before style fixes

* style and quality checks, fixed initialization problem in float_tensor, ready for PR

* added mega to toctree

* removed unnecessary arg in megaconfig

* removed unused arg and fixed code samples with leftover roberta models

* Apply suggestions from code review

Applied all suggestions except the one renaming a class, as I'll need to update that througout
Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>

* fixed issue where .view breaks batch dimension, conversion script fixed with absolute imports, updated readme with Mega->MEGA

* removed asserts in Mega code, renamed sequencenorm, gatedcrossattention, and NFFN, replaced get_activation_fn with ACTFN, and added sequencenorm to layer norms

* reformatted .forward() docstrings to match style and removed unused mask input in cross-attention

* removed all reset_parameters() methods and rolled into MegaPreTrainedModel._init_weights()

* renamed all single-letter variables and improved readability in tensor size comments, Mega->MEGA in 2 documentation files

* variable names in NFFN

* manual Mega->MEGA changes in docs

* Mega->MEGA in config auto

* style and quality fixes

* Apply suggestions from code review
Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>

* renamed parameters and variables with confusing names, added copied from statements, moved fft conv to its own method, other cleanup from PR comments

* commit before dealing with merge conflicts

* made new attention activation functions available in ACT2FN and added generation test from OPT

* style and quality in activations and tests

* documentation fixes, renaming variables in dropout and rotary positions, used built-in causal masking, encoders->layers in MegaModel, moved comments into docstrings

* style and quality fixes after latest updates, before rotary position ids

* causal mask in MegaBlock docstring + added missing device passing

* Apply suggestions from code review
Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>

* Update README.md
Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>

* added Mega prefixes where missing, reverted MegaSequenceNorm to if-else, other module renaming requested in PR

* style and quality fixes + readme updates pointing to main

---------
Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>
      57f25f4b
    • Ashwin Mathur's avatar
      Fix typo in Greedy Search Description (#22345) · b7960765
      Ashwin Mathur authored 
      Fix typo in greedy search docs
      b7960765
  3. 22 Mar, 2023 3 commits
  5. 20 Mar, 2023 3 commits
  7. 17 Mar, 2023 7 commits
  9. 16 Mar, 2023 2 commits
    • Jason Phang's avatar
      LLaMA Implementation (#21955) · 0041be5b
      Jason Phang authored 
      

* LLaMA

* sharding and docs

* tweak

* black

* inits

* ruff

* LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP

* init

* no checkpoint

* docs

* ruff

* type_vocab_size

* tokenizer fixes

* tokenizer fixes

* Update tokenization_llama.py

* Update tokenization_llama.py

* Update configuration_llama.py

* Update modeling_llama.py

* tokenizer add_bos by default

* licenses

* remove decoder

* norms and mlp

* rope overhaul

* tweaks

* black

* mention OPT implementation

* off-by-one naming

* typo

* fix

* tokenization fix and slicing bug

* padding config

* cleanup

* black

* update tests

* undo typo

* fix vocab caching logic

* ruff

* docbuilder

* attn fix from BlackSamorez

* initial feedback

* typo

* docs

* llama case

* llama case

* load checkpoint docs

* comment about tokenizer

* tokenizer defaults

* clear past_key_values if use_cache=False

* last tweaks

* last tweaks

* last tweaks

* last tweaks

---------
Co-authored-by: default avatarStella Biderman <stellabiderman@gmail.com>
      0041be5b
    • Alara Dirik's avatar
      Fix typo in Align docs (#22199) · 1485bd9c
      Alara Dirik authored 
      Fix align docs typo
      1485bd9c
  11. 14 Mar, 2023 2 commits
  13. 13 Mar, 2023 5 commits
  15. 10 Mar, 2023 2 commits
  17. 09 Mar, 2023 3 commits
  19. 08 Mar, 2023 2 commits
  21. 07 Mar, 2023 2 commits
    • Eli Simhayev's avatar
      [Time-Series] informer model (#21099) · 8abe4930
      Eli Simhayev authored 
      * added informer to gitignore

* added informer to gitignore

* WIP informer2020

* added checking that instantiate works

* added config using gluonTS by kashif

* WIP config

* adding informeConfig. need to remove FeatureEmbedder

* done InformerConfig, but need to change the names

* Done informer model init. working on enc-dec

* added things to address, after reading again enc-dec in the paper

* done modeling - checking initialization work

* added informer to gitignore

* WIP informer2020

* added checking that instantiate works

* added config using gluonTS by kashif

* WIP config

* adding informeConfig. need to remove FeatureEmbedder

* done InformerConfig, but need to change the names

* Done informer model init. working on enc-dec

* added things to address, after reading again enc-dec in the paper

* done modeling - checking initialization work

* moved enc-dec init to InformerEncoder/Decoder init

* added 'init_std' to config, now model init works!

* WIP conversion script, and added code sources

* WIP conversion script: loading original informer pth works

* WIP conversion script: change defaults in the config

* WIP conversion script: supporting Informer input embedding

* WIP conversion script: added parameters for the informer embed

* WIP conversion script: change dim_feedforward=2048

* WIP conversion script: remove unused args for loading checkpoint

* just cleaning up

* DataEmbedding removed, after thinking with Kashif

* working on forward pass

* WIP forward pass: trying to establish working batch for forward pass

* cleaning and finalizing

* adding HF names and docs

* init after cleaning works

* WIP in tests

* added docs for the informer specific args

* fix style

* undo change

* cleaning informer, now need to work only enc-dec

* initial enc-dec classes

* added encoder and decoder

* added todo

* add todos for conv_layers

* added decoder docs from vanilla

* added encoder docs from vanilla

* remove encoder decoder from the original informer

* removed AttentionLayer from the original paper

* removed TriangularCausalMask, same as decoder_attention_mask

* initial sparse attention

* use conv_layers

* fixed test_config test

* fix parenthesis when itearting zip(layers, conv_layers)

* error found in prob attention, added sizes as comments

* fix sizes

* added proposal for q_reduce indexing, and remove unused

* WIP ProbMask, and changed factor=2 for testing

* remove unused libs for this PR for creating the env

* fix checking the attn_weights.size() after bmm

* Q_reduce: changed from torch.gather to simple slicing

* WIP calculate final attn_output

* finish adding v_aggregated, attn_output ready

* changed tgt_len to u in attention_mask, need to fix the size error

* comment attention_mask for encoder, and fix if cond for v_agg

* added ProbMask support (wip), removed old original code

* finished ProbMask 馃槂



* Revert "remove unused libs for this PR for creating the env"

This reverts commit 11a081e09e92771e51a5d2758d53a9afb59547f0.

* fixes

* make style

* fix initial tests

* fix more tests

* dry

* make style

* remove unused files

* style

* added integration tests

* fix num_static_real_features

* fix header

* remove unused function

* fix example

* fix docs

* Update src/transformers/models/informer/configuration_informer.py
Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/informer/modeling_informer.py
Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/informer/configuration_informer.py
Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/informer/configuration_informer.py
Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/informer/configuration_informer.py
Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/informer/configuration_informer.py
Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>

* fixes for reviewer

* use prediction_length from model

* fix style

* fixed informer.mdx

* added to index

* updated readme

* undo

* make fix-copies

* typo

* fix copy

* added Informer to toctree

* in order

* fixed comments

* remove unneeded new lines in docs

* make static real and cat optional

* fix use of distil conv layers

* fixed integration test

* added checkpoint for convlayer

* make fix-copies

* updated from time series model

* make fix-copies

* copy decoder

* fix unit tests

* updated scaling config

* fix integration tests

* IGNORE_NON_TESTED

* IGNORE_NON_AUTO_CONFIGURED

* IGNORE_NON_AUTO_CONFIGURED

* updated check configs

* fix formatting

* undo change from time series

* prediction_length should not be None

* aliign with the blog: prettify ProbSparse and change attention_factor  to sampling_factor

* make style

* make fix-copies

* niels CR: update contributed by

* niels CR: update configuration_informer.py
Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>

* niels CR: update kashif -> huggingface
Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>

* niels CR: `sampling_factor` only relevant when `attention_type`=prob

* make style

* fixed U_part: added multiplication by `L_Q`

* fixed bug: remove `is not None` from `if config.distil`

* fixed test: `decoder_seq_length` to `encoder_seq_length` in cross_attentions check

* fix integration tests

* updated model hub

* do not shift as in training

* undo

* fix make-copies

* make fix-copies

* added `if prediction_length is None`

* changed `ProbSparseAttention` to `InformerProbSparseAttention`

* changed `V_sum` -> `v_mean_dim_time`

* changed `ConvLayer` to `InformerConvLayer` and fixed `super()`

* TimeSeriesTansformer->Informer in decoder's Copied from

* more descriptive in ProbSparse

* make style

* fix coped from

* Revert "added `if prediction_length is None`"

This reverts commit b4cbddfa05e3bd739b79569cd3c3b89e316f2451.

* fixed indent

* use InformerSinusoidalPositionalEmbedding

* make fix-style

* fix from #21860

* fix name

* make fix-copies

* use time series utils

* fix dec num_heads

* docstring

* added time series util doc

* _import_structure

* formatting

* changes from review

* make style

* fix docs

* fix doc

* removed NegativeLogLikelihood

---------
Co-authored-by: default avatarKashif Rasul <kashif.rasul@gmail.com>
Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>
      8abe4930
    • Sanchit Gandhi's avatar
      [Whisper] Add model for audio classification (#21754) · 7c393181
      Sanchit Gandhi authored 
      * [Whisper] Add model for audio classification

* make fix-copies

* add to docs

* add docstring

* empty returns

* add code example

* switch to fleurs

* stick everything on one line
      7c393181
  23. 06 Mar, 2023 1 commit
  25. 03 Mar, 2023 1 commit
  27. 01 Mar, 2023 5 commits