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Develop #7

Merged
merged 3 commits into from
Nov 7, 2018
Merged

Develop #7

merged 3 commits into from
Nov 7, 2018

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thomwolf
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@thomwolf thomwolf commented Nov 7, 2018

Fixing run_squad.py pre-processing bug.

Various clean-ups:

  • the weight initialization was not optimal (tf. truncated_normal_initializer(stddev=0.02) was translated in weight.data.normal_(0.02) instead of weight.data.normal_(mean=0.0, std=0.02) which likely affected the performance of run_classifer.py also.
  • gradient accumulation loss was not averaged over the accumulation steps which would have required to change the hyper-parameters for using accumulation.
  • the evaluation was not done with torch.no_grad() and thus sub-optimal in terms of speed/memory.

@thomwolf thomwolf merged commit 5c0838d into master Nov 7, 2018
@thomwolf thomwolf deleted the develop branch November 7, 2018 22:51
qwang70 pushed a commit to DRL36/pytorch-pretrained-BERT that referenced this pull request Mar 2, 2019
@HongyanJiao HongyanJiao mentioned this pull request Sep 19, 2019
LysandreJik added a commit that referenced this pull request Apr 10, 2020
* Initial commit to get BERT + run_glue.py on TPU

* Add README section for TPU and address comments.

* Cleanup TPU bits from run_glue.py (#3)

TPU runner is currently implemented in:
https://github.com/pytorch-tpu/transformers/blob/tpu/examples/run_glue_tpu.py.

We plan to upstream this directly into `huggingface/transformers`
(either `master` or `tpu`) branch once it's been more thoroughly tested.

* Cleanup TPU bits from run_glue.py

TPU runner is currently implemented in:
https://github.com/pytorch-tpu/transformers/blob/tpu/examples/run_glue_tpu.py.

We plan to upstream this directly into `huggingface/transformers`
(either `master` or `tpu`) branch once it's been more thoroughly tested.

* No need to call `xm.mark_step()` explicitly (#4)

Since for gradient accumulation we're accumulating on batches from
`ParallelLoader` instance which on next() marks the step itself.

* Resolve R/W conflicts from multiprocessing (#5)

* Add XLNet in list of models for `run_glue_tpu.py` (#6)

* Add RoBERTa to list of models in TPU GLUE (#7)

* Add RoBERTa and DistilBert to list of models in TPU GLUE (#8)

* Use barriers to reduce duplicate work/resources (#9)

* Shard eval dataset and aggregate eval metrics (#10)

* Shard eval dataset and aggregate eval metrics

Also, instead of calling `eval_loss.item()` every time do summation with
tensors on device.

* Change defaultdict to float

* Reduce the pred, label tensors instead of metrics

As brought up during review some metrics like f1 cannot be aggregated
via averaging. GLUE task metrics depends largely on the dataset, so
instead we sync the prediction and label tensors so that the metrics can
be computed accurately on those instead.

* Only use tb_writer from master (#11)

* Apply huggingface black code formatting

* Style

* Remove `--do_lower_case` as example uses cased

* Add option to specify tensorboard logdir

This is needed for our testing framework which checks regressions
against key metrics writtern by the summary writer.

* Using configuration for `xla_device`

* Prefix TPU specific comments.

* num_cores clarification and namespace eval metrics

* Cache features file under `args.cache_dir`

Instead of under `args.data_dir`. This is needed as our test infra uses
data_dir with a read-only filesystem.

* Rename `run_glue_tpu` to `run_tpu_glue`

Co-authored-by: LysandreJik <[email protected]>
rraminen pushed a commit to rraminen/transformers that referenced this pull request Jun 3, 2022
jameshennessytempus pushed a commit to jameshennessytempus/transformers that referenced this pull request Jun 1, 2023
younesbelkada pushed a commit to younesbelkada/transformers that referenced this pull request Mar 14, 2024
LysandreJik pushed a commit that referenced this pull request Mar 15, 2024
* Cohere Model Release (#1)

Cohere Model Release

* Remove unnecessary files and code (#2)

Some cleanup

* Delete cohere-model directory (#3)

* Make Fix (#5)

* Pr fixes (#6)

* fixes for pr

* pr fixes for the format

* pr fixes for the format

* src/transformers/models/auto/tokenization_auto.py

* Tokenizer test (#8)

* tokenizer test

* format fix

* Adding Docs and other minor changes (#7)

* Add modeling tests (#9)

* Smol Fix (#11)

* tokenization tests are fixed

* format fixes

* fix pr doc tests

* fix pr doc tests

* fix pr doc tests

* fix pr style check

* small changes in cohere.md

* FIX: Address final comments for transformers integration (#13)

* fix modeling final nits and add proper test file

* for now leave empty tests

* add integration test

* push new test

* fix modeling cohere (#14)

* Update chat templates to use the new API (#15)

---------

Co-authored-by: ahmetustun <[email protected]>
Co-authored-by: Younes Belkada <[email protected]>
Co-authored-by: Matt <[email protected]>
SunMarc added a commit that referenced this pull request Jan 15, 2025
* gptqmodel

Signed-off-by: jiqing-feng <[email protected]>

* fix format

Signed-off-by: jiqing-feng <[email protected]>

* update readme

Signed-off-by: jiqing-feng <[email protected]>

* gptqmodel need use checkpoint_format (#1)

* gptqmodel need use checkpoint_format

* fix quantize

* Update quantization_config.py

* Update quantization_config.py

* Update quantization_config.py

---------

Co-authored-by: ZX-ModelCloud <[email protected]>
Co-authored-by: Qubitium-ModelCloud <[email protected]>

* Revert quantizer_gptq.py (#2)

* revert quantizer_gptq.py change

* pass **kwargs

* limit gptqmodel and optimum version

Signed-off-by: jiqing-feng <[email protected]>

* fix format

Signed-off-by: jiqing-feng <[email protected]>

* fix warning

Signed-off-by: jiqing-feng <[email protected]>

* fix version check

Signed-off-by: jiqing-feng <[email protected]>

* revert unrelated changes

Signed-off-by: jiqing-feng <[email protected]>

* enable gptqmodel tests

Signed-off-by: jiqing-feng <[email protected]>

* fix requires gptq

Signed-off-by: jiqing-feng <[email protected]>

* Fix Transformer compat (#3)

* revert quantizer_gptq.py change

* pass **kwargs

* add meta info

* cleanup

* cleanup

* Update quantization_config.py

* hf_select_quant_linear pass checkpoint_format and meta

* fix GPTQTestCUDA

* Update test_gptq.py

* gptqmodel.hf_select_quant_linear() now does not select ExllamaV2

* cleanup

* add backend

* cleanup

* cleanup

* no need check exllama version

* Update quantization_config.py

* lower checkpoint_format and backend

* check none

* cleanup

* Update quantization_config.py

* fix self.use_exllama == False

* spell

* fix unittest

* fix unittest

---------

Co-authored-by: LRL <[email protected]>
Co-authored-by: Qubitium-ModelCloud <[email protected]>

* fix format

Signed-off-by: jiqing-feng <[email protected]>

* fix format again

Signed-off-by: jiqing-feng <[email protected]>

* update gptqmodel version (#6)

* update gptqmodel version

* update gptqmodel version

* fix unit test (#5)

* update gptqmodel version

* update gptqmodel version

* "not self.use_exllama" is not equivalent to "self.use_exllama==False"

* fix unittest

* update gptqmodel version

* backend is loading_attibutes (#7)

* fix format and tests

Signed-off-by: jiqing-feng <[email protected]>

* fix memory check

Signed-off-by: jiqing-feng <[email protected]>

* fix device mismatch

Signed-off-by: jiqing-feng <[email protected]>

* fix result check

Signed-off-by: jiqing-feng <[email protected]>

* Update src/transformers/quantizers/quantizer_gptq.py

Co-authored-by: Marc Sun <[email protected]>

* Update src/transformers/quantizers/quantizer_gptq.py

Co-authored-by: Marc Sun <[email protected]>

* Update src/transformers/quantizers/quantizer_gptq.py

Co-authored-by: Marc Sun <[email protected]>

* update tests

Signed-off-by: jiqing-feng <[email protected]>

* review: update docs (#10)

* review: update docs (#12)

* review: update docs

* fix typo

* update tests for gptqmodel

Signed-off-by: jiqing-feng <[email protected]>

* update document (#9)

* update overview.md

* cleanup

* Update overview.md

* Update overview.md

* Update overview.md

* update gptq.md

* Update gptq.md

* Update gptq.md

* Update gptq.md

* Update gptq.md

* Update gptq.md

* Update gptq.md

---------

Co-authored-by: Qubitium-ModelCloud <[email protected]>

* typo

* doc note for asymmetric quant

* typo with apple silicon(e)

* typo for marlin

* column name revert: review

* doc rocm support

* Update docs/source/en/quantization/gptq.md

Co-authored-by: Steven Liu <[email protected]>

* Update docs/source/en/quantization/gptq.md

Co-authored-by: Steven Liu <[email protected]>

* Update docs/source/en/quantization/gptq.md

Co-authored-by: Steven Liu <[email protected]>

* Update docs/source/en/quantization/gptq.md

Co-authored-by: Steven Liu <[email protected]>

* Update docs/source/en/quantization/overview.md

Co-authored-by: Steven Liu <[email protected]>

* Update docs/source/en/quantization/overview.md

Co-authored-by: Steven Liu <[email protected]>

---------

Signed-off-by: jiqing-feng <[email protected]>
Co-authored-by: LRL-ModelCloud <[email protected]>
Co-authored-by: ZX-ModelCloud <[email protected]>
Co-authored-by: Qubitium-ModelCloud <[email protected]>
Co-authored-by: ZX-ModelCloud <[email protected]>
Co-authored-by: LRL <[email protected]>
Co-authored-by: Marc Sun <[email protected]>
Co-authored-by: Mohamed Mekkouri <[email protected]>
Co-authored-by: Steven Liu <[email protected]>
elvircrn pushed a commit to elvircrn/transformers that referenced this pull request Feb 7, 2025
* gptqmodel

Signed-off-by: jiqing-feng <[email protected]>

* fix format

Signed-off-by: jiqing-feng <[email protected]>

* update readme

Signed-off-by: jiqing-feng <[email protected]>

* gptqmodel need use checkpoint_format (huggingface#1)

* gptqmodel need use checkpoint_format

* fix quantize

* Update quantization_config.py

* Update quantization_config.py

* Update quantization_config.py

---------

Co-authored-by: ZX-ModelCloud <[email protected]>
Co-authored-by: Qubitium-ModelCloud <[email protected]>

* Revert quantizer_gptq.py (huggingface#2)

* revert quantizer_gptq.py change

* pass **kwargs

* limit gptqmodel and optimum version

Signed-off-by: jiqing-feng <[email protected]>

* fix format

Signed-off-by: jiqing-feng <[email protected]>

* fix warning

Signed-off-by: jiqing-feng <[email protected]>

* fix version check

Signed-off-by: jiqing-feng <[email protected]>

* revert unrelated changes

Signed-off-by: jiqing-feng <[email protected]>

* enable gptqmodel tests

Signed-off-by: jiqing-feng <[email protected]>

* fix requires gptq

Signed-off-by: jiqing-feng <[email protected]>

* Fix Transformer compat (huggingface#3)

* revert quantizer_gptq.py change

* pass **kwargs

* add meta info

* cleanup

* cleanup

* Update quantization_config.py

* hf_select_quant_linear pass checkpoint_format and meta

* fix GPTQTestCUDA

* Update test_gptq.py

* gptqmodel.hf_select_quant_linear() now does not select ExllamaV2

* cleanup

* add backend

* cleanup

* cleanup

* no need check exllama version

* Update quantization_config.py

* lower checkpoint_format and backend

* check none

* cleanup

* Update quantization_config.py

* fix self.use_exllama == False

* spell

* fix unittest

* fix unittest

---------

Co-authored-by: LRL <[email protected]>
Co-authored-by: Qubitium-ModelCloud <[email protected]>

* fix format

Signed-off-by: jiqing-feng <[email protected]>

* fix format again

Signed-off-by: jiqing-feng <[email protected]>

* update gptqmodel version (huggingface#6)

* update gptqmodel version

* update gptqmodel version

* fix unit test (huggingface#5)

* update gptqmodel version

* update gptqmodel version

* "not self.use_exllama" is not equivalent to "self.use_exllama==False"

* fix unittest

* update gptqmodel version

* backend is loading_attibutes (huggingface#7)

* fix format and tests

Signed-off-by: jiqing-feng <[email protected]>

* fix memory check

Signed-off-by: jiqing-feng <[email protected]>

* fix device mismatch

Signed-off-by: jiqing-feng <[email protected]>

* fix result check

Signed-off-by: jiqing-feng <[email protected]>

* Update src/transformers/quantizers/quantizer_gptq.py

Co-authored-by: Marc Sun <[email protected]>

* Update src/transformers/quantizers/quantizer_gptq.py

Co-authored-by: Marc Sun <[email protected]>

* Update src/transformers/quantizers/quantizer_gptq.py

Co-authored-by: Marc Sun <[email protected]>

* update tests

Signed-off-by: jiqing-feng <[email protected]>

* review: update docs (huggingface#10)

* review: update docs (huggingface#12)

* review: update docs

* fix typo

* update tests for gptqmodel

Signed-off-by: jiqing-feng <[email protected]>

* update document (huggingface#9)

* update overview.md

* cleanup

* Update overview.md

* Update overview.md

* Update overview.md

* update gptq.md

* Update gptq.md

* Update gptq.md

* Update gptq.md

* Update gptq.md

* Update gptq.md

* Update gptq.md

---------

Co-authored-by: Qubitium-ModelCloud <[email protected]>

* typo

* doc note for asymmetric quant

* typo with apple silicon(e)

* typo for marlin

* column name revert: review

* doc rocm support

* Update docs/source/en/quantization/gptq.md

Co-authored-by: Steven Liu <[email protected]>

* Update docs/source/en/quantization/gptq.md

Co-authored-by: Steven Liu <[email protected]>

* Update docs/source/en/quantization/gptq.md

Co-authored-by: Steven Liu <[email protected]>

* Update docs/source/en/quantization/gptq.md

Co-authored-by: Steven Liu <[email protected]>

* Update docs/source/en/quantization/overview.md

Co-authored-by: Steven Liu <[email protected]>

* Update docs/source/en/quantization/overview.md

Co-authored-by: Steven Liu <[email protected]>

---------

Signed-off-by: jiqing-feng <[email protected]>
Co-authored-by: LRL-ModelCloud <[email protected]>
Co-authored-by: ZX-ModelCloud <[email protected]>
Co-authored-by: Qubitium-ModelCloud <[email protected]>
Co-authored-by: ZX-ModelCloud <[email protected]>
Co-authored-by: LRL <[email protected]>
Co-authored-by: Marc Sun <[email protected]>
Co-authored-by: Mohamed Mekkouri <[email protected]>
Co-authored-by: Steven Liu <[email protected]>
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