Use barriers to reduce duplicate work/resources #9
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
taylanbil
approved these changes
Apr 1, 2020
| if xm.is_master_ordinal(): | ||
| model_to_save.config.save_pretrained(save_directory) | ||
| # xm.save takes care of saving only from master | ||
| xm.save(model_to_save.state_dict(), output_model_file) |
There was a problem hiding this comment.
idea for the future; you could use the checkpoint tagger later, if they mark which chpt is the best etc.
There was a problem hiding this comment.
As far as I know, they don't have such tagger but let me see if they do. Good idea we could even upstream if they don't. Thanks.
| @@ -341,6 +355,9 @@ def main(args): | |||
| label_list = processor.get_labels() | |||
| num_labels = len(label_list) | |||
|
|
|||
| if not xm.is_master_ordinal(): | |||
| xm.rendezvous('download_only_once') # Make sure only the first process in distributed training will download model & vocab | |||
There was a problem hiding this comment.
I'm assuming no tensor work is done in the methods b/w download_only_once rendezvous's
jysohn23
added a commit
to jysohn23/transformers
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 (pytorch-tpu#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 (pytorch-tpu#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 (pytorch-tpu#5) * Add XLNet in list of models for `run_glue_tpu.py` (pytorch-tpu#6) * Add RoBERTa to list of models in TPU GLUE (pytorch-tpu#7) * Add RoBERTa and DistilBert to list of models in TPU GLUE (pytorch-tpu#8) * Use barriers to reduce duplicate work/resources (pytorch-tpu#9) * Shard eval dataset and aggregate eval metrics (pytorch-tpu#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 (pytorch-tpu#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 <lysandre.debut@reseau.eseo.fr>
alanwaketan
pushed a commit
that referenced
this pull request
Apr 17, 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 <ahmetustun89@gmail.com> Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
No description provided.