Initial commit to get BERT + run_glue.py on TPU by jysohn23 · Pull Request #1 · pytorch-tpu/transformers

jysohn23 · 2019-11-09T01:19:48Z

Verified performance numbers look at least comparable on a chip-to-chip basis (TPUv3 vs V100) for MRPC dataset (pretty much the same accuracy & f1 test metrics too). Runner script works for both GPU and TPU.

taylanbil · 2019-11-11T18:17:48Z

+    parser.add_argument('--use_tpu', action='store_true', help='Whether to use TPUs.')
+    parser.add_argument('--num_cores', default=8, type=int, help='Number of TPU cores to use.')
+    parser.add_argument('--metrics_debug', action='store_true', help='Whether to print debug metrics.')


are these the only tpu specific args?

taylanbil · 2019-11-11T18:18:20Z

+    parser.add_argument('--seed', type=int, default=42,
+                        help="random seed for initialization")
+
+    parser.add_argument('--fp16', action='store_true',


Does enabling this break tpu? It did for fairseq.

taylanbil · 2019-11-11T18:20:10Z

        preds = None
        out_label_ids = None
-        for batch in tqdm(eval_dataloader, desc="Evaluating"):
+        for batch in tqdm(eval_dataloader, desc="Evaluating", disable=args.use_tpu):


why disable this?

taylanbil · 2019-11-11T18:21:20Z


    # Saving best-practices: if you use defaults names for the model, you can reload it using from_pretrained()
-    if args.do_train and (args.local_rank == -1 or torch.distributed.get_rank() == 0) and not args.tpu:
+    if args.do_train and (args.local_rank == -1 or torch.distributed.get_rank() == 0):


where do these get set correctly for our MP purposes?

taylanbil · 2019-11-11T18:22:50Z

+
+def main_cli():
+    args = get_args()
+    if args.use_tpu:


having to pass --use_tpu every time feels annoying, but no big deal.

Yep, it indeed is so will create separate runner as discussed offline.

taylanbil · 2019-11-11T18:23:47Z

        tb_writer.close()

-    return global_step, tr_loss / global_step
+    return global_step, loss.item()


is this equivalent?

Sort of, just that it's not a real average.

taylanbil · 2019-11-11T18:24:25Z


-                optimizer.step()
+                if args.use_tpu:
+                    xm.optimizer_step(optimizer, barrier=True)


why do we need barrier here? Isn't it in parallelloader already?

Good point! We don't need barrier here. Artifact I forgot to cleanup from testing on single core.

jysohn23 · 2019-11-13T02:14:01Z

Thanks for the review @taylanbil!

Based on offline conversation with Google and HuggingFace teams, will close the PR in favor of preparing a separate run_glue_tpu.py runner.

…gface#26681) * Draft version of new KV Caching This should allow Attention Sinks (https://github.com/tomaarsen/attention_sinks) / StreamingLLM (https://arxiv.org/abs/2309.17453) to be easily implemented in a third-party or in transformers directly * Address numerous PR suggestions 1. Move layer_idx from cache to ...Attention. Removes confusing set_layer_idx magic. 2. Always convert past_key_values to Cache instance at the start of ...Attention, removes all other isinstance calls. 3. Remove __bool__ and __getitem__ magic as they're confusing. 4. past_key_values.update(key, value, idx) now returns key, value. 5. Add use_legacy_cache flag, defaults to None, i.e. Falsey. This breaks generate for now, until 1) the cache is used is generate() or 2) use_legacy_cache is defaulted to True in generate() until we change it in another PR. 6. Separate key_cache and value_cache. Some work is still needed to see if the SinkCache can conveniently be implemented with just one update method. * Implement the SinkCache through backward+forward rotations * Integrate (Sink)Cache with Llama FA2 * Set use_legacy_cache=True as default, allows for test passes * Move from/to_legacy_cache to ...Model class * Undo unnecessary newline change * Remove copy utility from deprecated OpenLlama * Match import style * manual rebase with main * Cache class working with generate (#1) * Draft version of new KV Caching This should allow Attention Sinks (https://github.com/tomaarsen/attention_sinks) / StreamingLLM (https://arxiv.org/abs/2309.17453) to be easily implemented in a third-party or in transformers directly * Address numerous PR suggestions 1. Move layer_idx from cache to ...Attention. Removes confusing set_layer_idx magic. 2. Always convert past_key_values to Cache instance at the start of ...Attention, removes all other isinstance calls. 3. Remove __bool__ and __getitem__ magic as they're confusing. 4. past_key_values.update(key, value, idx) now returns key, value. 5. Add use_legacy_cache flag, defaults to None, i.e. Falsey. This breaks generate for now, until 1) the cache is used is generate() or 2) use_legacy_cache is defaulted to True in generate() until we change it in another PR. 6. Separate key_cache and value_cache. Some work is still needed to see if the SinkCache can conveniently be implemented with just one update method. * Integrate (Sink)Cache with Llama FA2 * Move from/to_legacy_cache to ...Model class * Undo unnecessary newline change * Match import style * working generate * Add tests; Simplify code; Apply changes to Mistral and Persimmon * fix rebase mess * a few more manual fixes * last manual fix * propagate changes to phi * upgrade test * add use_legacy_cache docstring; beef up tests * reintroduce unwanted deletes --------- Co-authored-by: Tom Aarsen <Cubiegamedev@gmail.com> * move import * add default to model_kwargs.get('use_legacy_cache') * correct failing test * Apply suggestions from code review Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * apply PR suggestions * fix failing test * Apply suggestions from code review Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by: Tom Aarsen <37621491+tomaarsen@users.noreply.github.com> * PR comments * tmp commit * add docstrings * more tests, more docstrings, add to docs * derp * tmp commit * tmp dbg * more dbg * fix beam search bug * cache can be a list of tuples in some models * fix group beam search * all but sinkcache integration tests * fix sink cache and add hard integration test * now also compatible with input_embeds input * PR comments * add Cache support to Phi+FA2 * make fixup --------- Co-authored-by: Joao Gante <joao@huggingface.co> Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com> Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* 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>

Initial commit to get BERT + run_glue.py on TPU

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jysohn23 requested a review from taylanbil November 9, 2019 01:19

taylanbil reviewed Nov 11, 2019

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jysohn23 closed this Nov 13, 2019

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Initial commit to get BERT + run_glue.py on TPU - #1

Initial commit to get BERT + run_glue.py on TPU#1
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