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  1. 28 Apr, 2023 1 commit
  3. 27 Apr, 2023 2 commits
  5. 26 Apr, 2023 1 commit
    • Ritik Nandwal's avatar
      Add TensorFlow Wav2Vec2 for sequence classification (#22073) · 20ac86c6
      Ritik Nandwal authored 
      * Add initial changes for TF wav2vec2 for sequence classification

* Add suggested changes

* Add serving and serving output methods

* Add serving_output implementation and fix layer_weights

* Add fixes

* Fixed test cases

* Fixing test and adding suggested changes
      20ac86c6
  7. 25 Apr, 2023 1 commit
  9. 24 Apr, 2023 1 commit
  11. 23 Apr, 2023 1 commit
  13. 21 Apr, 2023 2 commits
  15. 20 Apr, 2023 3 commits
  17. 19 Apr, 2023 1 commit
    • Arthur's avatar
      Add Segment Anything Model (SAM) (#22654) · 474bf508
      Arthur authored 
      

* initial commit

* keys match

* update, fix conversion

* fixes, inference working

* fix

* more fixes

* more fixes

* clean up

* more clean up

* fix copies and add convext copied layer norm

* stash

* pretty big upfate

* cleaning

* more cleaning

* fixup stuffs

* fix copies

* fix iinit

* update test removing tokenizer

* nits

* add pretrained

* more nits

* remove tracking of pipeline

* few fixes

* update san and conversion script

* fix mask decoder and prompt encoder conversion

* fixes

* small update

* fix order

* fix

* fix image embeddings

* nites

* few fixes

* fix logits

* clean up

* fixes boxes inference

* v1 AMG

* clean up

* some clean up

* multi points support

* amg working

* fixup

* clean up

* readme

* update toctree

* fix type hint

* multiple fixes

* fixup

* fixes

* updates

* updates

* more tests

* few fixes

* change to `SamForMaskGeneration`

* doc

* fixup

* fix more tests

* multiple fixes

* fix CI tests

* refactor processor

* renamings

* draft the pipeline

* refactor

* fix tests

* fix test

* few cleanings

* fix test

* edit pipelien support chunking

* udate

* add slow tests

* fix nit

* fixup

* fix nit

* current chunk pipleine

* cast boxes in fp32

* nit

* current updates

* piepleine works

* fixup

* clean up config

* fix slow tests

* fix slow tests

* clean up

* update doc and pipeline

* adds more slow tests

* fix slow tests

* cleaning

* tests pass

* add docstring

* fix copies

* clean up

* support batch of images

* style

* dummy is needed, add tests

* fix slow tests

* fix CI

* update

* adds more tests

* fixes

* fixes

* fixup

* fixes

* few fixes

* filter

* few fixes

* some refactor

* touches finales

* fix

* style

* remove pipeline files

* fixes nits

* revert pipeline changes

* fix test

* fixup

* remove automodel for automatic mask generation

* fix failing torch tests

* update mdx

* revert removal of `MODEL_FOR_AUTOMATIC_MASK_GENERATION_MAPPING`

* update sam config based on review
Co-authored-by: default avataramyeroberts <aeroberts4444@gmail.com>
Co-authored-by: default avatarsgugger <sylvain.gugger@gmail.com>

* update low_resolution_masks -> pred_masks
inti ln with layer_norm_eps
add_decomposed_rel_pos doc
forward doc of SamForMaskGeneration

* update processor docstring

* remove image processor import empty

* update for testing

* output vision hidden states + clean recomm
also test all iou values

* fixup

* fixup

* remove unused

* Update src/transformers/models/sam/modeling_sam.py
Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/models/sam/image_processing_sam.py
Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>

* nits

* fix

* fix CI tests and slow tests

* replace with Amy's processor

* clearer docstring

* add `SamVisionNeck`

* refactor - all CI tests should pass

* fix broken import on Gcolab

* few fixes here and there

* fix another bug

* fix more bugs

* update and merge

* correct ckpt

* address comments

* add tips

* revert

* fix docstring

* replace with `SamModel`

* make fixup

* add support for bathed images and batch ed points

* make fixup this time, really

* make fixup again and again

* few fixes here and there, this should be the touche finale

* Update docs/source/en/model_doc/sam.mdx

* fixup

* correct checkpoints

* correct name

* rm unneeded file

* add notebook

---------
Co-authored-by: default avataryounesbelkada <younesbelkada@gmail.com>
Co-authored-by: default avataramyeroberts <aeroberts4444@gmail.com>
Co-authored-by: default avatarsgugger <sylvain.gugger@gmail.com>
Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: default avatarYounes Belkada <49240599+younesbelkada@users.noreply.github.com>
      474bf508
  19. 13 Apr, 2023 2 commits
  21. 12 Apr, 2023 2 commits
    • pioliverse's avatar
      add model resources for CPMAnt (new) (#20906) · 523ca4e0
      pioliverse authored 
      

* resolve conflicts

* rebase and make style

* test

* test

* test

* rebase and make style

* rebase and make style

* tests

* tests

* rewrite some functions

* rebase and make style

* fix load_tf_weights_in_cpmant

* reformat some unrelated files

* upgrade quality

* fix some bugs & docstring

* add models and tests

* solve conflicts

* resolve conflicts

* resolve conflicts

* resolve conflicts

* resolve conflicts

* tests

* resolve conflicts

* resolve conflicts

* fix load_tf_weights_in_cpmant

* reformat some unrelated files

* upgrade quality

* fix some bugs & docstring

* save resolution

* make style

* delete redefinition code

* reformat function

* reformat

* resolve conflicts

* resolve conflicts

* resolve conflicts

* resolve conflicts

* resolve conflicts

* tests

* resolve conflicts

* resolve conflicts

* fix load_tf_weights_in_cpmant

* reformat some unrelated files

* upgrade quality

* resolve conflicts

* resolve conflicts

* resolve conflicts

* resolve conflicts

* resolve conflicts

* fix load_tf_weights_in_cpmant

* reformat some unrelated files

* upgrade quality

* resolve conflicts

* make style

* fix bugs and refactor

* modify docstrings and make style

* unify import format in __init__.py

* fix import-altclp bug

* fix copies to update index.md

* fix unused config parameters

* fix unused config parameters

* fix unused config parameters

* update README_ja.md

* dummy commit for unit test

* fix attention mask

* add CPMAntTokenizer&-Fast to auto-mapping

* drop redundant changes in README_ko

* fix  defaults in docstring

* fix use_cache and some docstring

* add missing args in tokenizer

* modify tester inheritance

* add is_jieba_available

* fix some bugs

* make style and fix-copies

* add doctests

* skip integration tests

* add is_jieba_available

* fix bugs in common tests

* adjust docstrings and make style

* add argument docstring

* adjust code to some specifications

* make style and fix-copies

* add fast tokenization test

* dummy commit for unit test

* dummy commit for unit test

* dummy commit for unit test

* normalize some comments and names

* Bert->CPMAnt

* camel names and drop redundant codes

* make style and fix-coies

* add CpmTokenizerFast _import_structure

* drop cpmanttokenizerfast in model_doc

* fix some problems

* fix CPMAnt tokenization for common test

* make style and fixup

* fix copies and fixup

* fix bugs in tokenization test

* dummy commit for connection failure in unittest

* fix copies

* drop trailing comma

* fix decorator in tests

* dummy commit for connection failure in unittest

---------
Co-authored-by: default avatarGong Baitao <gongbaitao11@gmail.com>
      523ca4e0
    • Arthur's avatar
      remove wrong doc in readme (#22723) · b76e6ebd
      Arthur authored
      b76e6ebd
  23. 10 Apr, 2023 2 commits
    • Sugawara's avatar
      add GPTNeoXForSequenceClassification (#22671) · 6daa9cb5
      Sugawara authored 
      * add GPTNeoXForSequenceClassification

* move the labels to logits.device (ref: #22561)

* fix
      6daa9cb5
    • Joel Lamy-Poirier's avatar
      Add GPTBigCode model (Optimized GPT2 with MQA from Santacoder & BigCode) (#22575) · e0921c6b
      Joel Lamy-Poirier authored 
      

* Add model with cli tool

* Remove unwanted stuff

* Add new code

* Remove inference runner

* Style

* Fix checks

* Test updates

* make fixup

* fix docs

* fix doc

* fix test

* hopefully fix pipeline tests

* refactor

* fix CIs

* add comment

* rename to `GPTBigCodeForCausalLM`

* correct readme

* make fixup + docs

* make fixup

* fixes

* fixes

* Remove pruning

* Remove import

* Doc updates

* More pruning removal

* Combine copies

* Single MQA implementation, remove kv cache pre-allocation and padding

* Update doc

* Revert refactor to match gpt2 style

* Merge back key and value caches, fix some type hints

* Update doc

* Fix position ids pith padding (PR 21080)

* Add conversion script temporarily

* Update conversion script

* Remove checkpoint conversion

* New model

* Fix MQA test

* Fix copies

* try fix tests

* FIX TEST!!

* remove  `DoubleHeadsModel`

* add MQA tests

* add slow tests

* clean up

* add CPU checker

* final fixes

* fixes

- fix GPU issue
- fixed slow tests
- skip disk offload

* fix final issue

* Simplify and comment baddbmm fix

* Remove unnecessary code

* Transpose tweaks

* Use beta=1 on cpu, improve tests

---------
Co-authored-by: default avataryounesbelkada <younesbelkada@gmail.com>
      e0921c6b
  25. 06 Apr, 2023 1 commit
    • Nicolas Patry's avatar
      Adding Llama FastTokenizer support. (#22264) · 1670be4b
      Nicolas Patry authored 
      * Adding Llama FastTokenizer support.

- Requires https://github.com/huggingface/tokenizers/pull/1183 version
- Only support byte_fallback for llama, raise otherwise (safety net).
- Lots of questions are special tokens

How to test:

```python

from transformers.convert_slow_tokenizer import convert_slow_tokenizer
from transformers import AutoTokenizer
from tokenizers import Tokenizer

tokenizer = AutoTokenizer.from_pretrained("huggingface/llama-7b")

if False:
    new_tokenizer = Tokenizer.from_file("tok.json")
else:
    new_tokenizer = convert_slow_tokenizer(tokenizer)
    new_tokenizer.save("tok.json")

strings = [
    "This is a test",
    "生活的真谛是",
    "生活的真谛是[MASK]。",
    # XXX: This one is problematic because of special tokens
    # "<s> Something something",
]

for string in strings:
    encoded = tokenizer(string)["input_ids"]
    encoded2 = new_tokenizer.encode(string).ids

    assert encoded == encoded2, f"{encoded} != {encoded2}"

    decoded = tokenizer.decode(encoded)
    decoded2 = new_tokenizer.decode(encoded2)

    assert decoded.strip() == decoded2, f"{repr(decoded)} != {repr(decoded2)}"
```

The converter + some test script.

The test script.

Tmp save.

Adding Fast tokenizer + tests.

Adding the tokenization tests.

Correct combination.

Small fix.

Fixing tests.

Fixing with latest update.

Rebased.

fix copies + normalized added tokens  + copies.

Adding doc.

TMP.

Doc + split files.

Doc.

Versions + try import.

Fix Camembert + warnings -> Error.

Fix by ArthurZucker.

Not a decorator.

* Fixing comments.

* Adding more to docstring.

* Doc rewriting.
      1670be4b
  27. 05 Apr, 2023 1 commit
  29. 04 Apr, 2023 3 commits
  31. 03 Apr, 2023 2 commits
  33. 27 Mar, 2023 1 commit
    • Arthur's avatar
      [WIP]`NLLB-MoE` Adds the moe model (#22024) · 19ade242
      Arthur authored 
      * Initial commit

* update modeling code

* update doc

* add functions necessary

* fix impotrs

* revert changes

* fixup

* more styling to get going

* remove standalone encoder

* update code

* styling

* fix config and model

* update code and some refactoring

* make more tests pass

* Adding NLLB-200 - MoE - 54.5B for no language left behind
Fixes #21300

* fix mor common tests

* styke

* update testing file

* update

* update

* Router2 doc

* update check config with sparse layer

* add dummy router

* update current conversion script

* create on the fly conversion script

* Fixup

* style

* style 2

* fix empty return

* fix return

* Update default config sparse layers

* easier to create sparse layers

* update

* update conversion script

* update modeling

* add to toctree

* styling

* make ruff happy

* update docstring

* update conversion script

* update, will break tests but impelemting top2

* update

* ❗local groups are supported here

* ⚠️ Support for local groups is now removed ⚠️

This is because it has to work with model parallelism that we do not support

* finish simplificaiton

* Fix forward

* style

* fixup

* Update modelling and test, refactoring

* update tests

* remove final layer)norm as it is done in the FF

* routing works! Logits test added

* nit in test

* remove top1router

* style

* make sure sparse are tested. Had to change route_tokens a liottle bit

* add support for unslip models when converting

* fixup

* style

* update test s

* update test

* REFACTOR

* encoder outputs match!

* style

* update testing

* 🎉encoder and decoder logits match 🎉



* styleing

* update tests

* cleanup tests

* fix router test and CIs

* cleanup

* cleanup test styling

* fix tests

* Finally the generation tests match!

* cleanup

* update test

* style testing file

* remove script

* cleanup

* more cleanup

* nits

* update

* NLLB tokenizer is wrong and will be fixed soon

* use LongTensors

* update tests

* revert some small changes

* fix second expert sampling and batch prioritized routing

* update tests

* finish last tests

* make ruff happy

* update

* ruff again

* style

* Update docs/source/en/model_doc/nllb-moe.mdx
Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Updates based on review

* style and fix import issue

* nit

* more nits

* cleanup

* styling

* update test_seconde_expert_policy

* fix name

* last nit on the markdown examples

---------
Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>
      19ade242
  35. 24 Mar, 2023 2 commits
    • Shubhamai's avatar
      Resnet flax (#21472) · a0cbbba3
      Shubhamai authored 
      

* [WIP] flax resnet

* added pretrained flax models, results reproducible

* Added pretrained flax models, results reproducible

* working on tests

* no real code change, just some comments

* [flax] adding support for batch norm layers

* fixing bugs related to pt+flax integration

* removing loss from modeling flax output class

* fixing classifier tests

* fixing comments, model output

* cleaning comments

* review changes

* review changes

* Apply suggestions from code review
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* renaming Flax to PyTorch

---------
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      a0cbbba3
    • 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
  37. 22 Mar, 2023 1 commit
  39. 20 Mar, 2023 1 commit
  41. 17 Mar, 2023 7 commits
  43. 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