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Lamb optimizer update #16715

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merged 3 commits into from
Nov 24, 2019
Merged

Lamb optimizer update #16715

merged 3 commits into from
Nov 24, 2019

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access2rohit
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@access2rohit access2rohit commented Nov 4, 2019

Description

adding to new operators:

Checklist

Essentials

Please feel free to remove inapplicable items for your PR.

  • Changes are complete (i.e. I finished coding on this PR)
  • All changes have test coverage:
  • Unit tests are added for small changes to verify correctness (e.g. adding a new operator)
  • Code is well-documented:
  • To the my best knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change

Changes

  • lamb_update, tests, (and when applicable, API doc)

Testing

[DEBUG] 1000 of 1000: Setting test np/mx/python random seeds, use MXNET_TEST_SEED=2052238159 to reproduce.
ok

----------------------------------------------------------------------
Ran 1 test in 5085.147s

OK

@access2rohit access2rohit changed the title Lamb optimizer update [WIP]Lamb optimizer update Nov 4, 2019
@access2rohit access2rohit force-pushed the lamb branch 3 times, most recently from 63488d6 to c0508d3 Compare November 8, 2019 19:38
@access2rohit access2rohit force-pushed the lamb branch 3 times, most recently from e1a3ad9 to 8d62300 Compare November 13, 2019 20:02
@access2rohit access2rohit changed the title [WIP]Lamb optimizer update Lamb optimizer update Nov 13, 2019
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access2rohit commented Nov 13, 2019

@mxnet-label-bot add [pr-awaiting-review]

@lanking520 lanking520 added the pr-awaiting-review PR is waiting for code review label Nov 13, 2019
@access2rohit access2rohit force-pushed the lamb branch 5 times, most recently from dfdfdab to e656220 Compare November 13, 2019 22:02

@register
class LAMB(Optimizer):
"""LAMB Optimizer.
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pls add doc

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working on it now

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The name is clashing with the GLuon one, can we give it a different name?

python/mxnet/optimizer/optimizer.py Outdated Show resolved Hide resolved
src/operator/optimizer_op.cc Show resolved Hide resolved
src/operator/optimizer_op-inl.h Outdated Show resolved Hide resolved
tests/python/unittest/test_optimizer.py Show resolved Hide resolved
tests/python/unittest/test_optimizer.py Show resolved Hide resolved
@access2rohit access2rohit force-pushed the lamb branch 2 times, most recently from 32f26cc to e6ac0dc Compare November 14, 2019 01:36
@access2rohit access2rohit force-pushed the lamb branch 2 times, most recently from f720d46 to 9beed69 Compare November 14, 2019 02:07
src/operator/optimizer_op.cc Outdated Show resolved Hide resolved
tests/python/unittest/test_optimizer.py Outdated Show resolved Hide resolved
tests/python/unittest/test_optimizer.py Show resolved Hide resolved
src/operator/optimizer_op-inl.h Show resolved Hide resolved
@access2rohit access2rohit force-pushed the lamb branch 3 times, most recently from 1eb581a to b6851c9 Compare November 14, 2019 20:24
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larroy commented Nov 14, 2019

Please add description and reference to paper in the PR.

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larroy commented Nov 14, 2019

I see a crash in the way gluon trainer is calling the optimizer...

+ python3 run_pretraining.py '--data=/home/piotr/mxnet-data/bert-pretraining/datasets/book-corpus/book-corpus-large-split/*.train,/home/piotr/mxnet-data/bert-pretraining/datasets/enwiki/enwiki-feb-doc-split/*.train' '--data_eval=/home/piotr/mxnet-data/bert-pretraining/datasets/book-corpus/book-corpus-large-split/*.test,/home/piotr/mxnet-data/bert-pretraining/datasets/enwiki/enwiki-feb-doc-split/*.test' --optimizer lamb3 --warmup_ratio 0.2 --num_steps 200 --ckpt_interval 300000000 --dtype float16 --ckpt_dir ./test-ckpt --lr 0.0001 --total_batch_size 32 --total_batch_size_eval 32 --accumulate 1 --model bert_24_1024_16 --max_seq_length 128 --max_predictions_per_seq 20 --num_data_workers 1 --eval_interval 100000000 --verbose --no_compute_acc --raw --comm_backend horovod --log_interval 10 --verbose --synthetic_data --raw --eval_use_npz
[22:42:38] ../src/storage/storage.cc:110: Using GPUPooledRoundedStorageManager.
Traceback (most recent call last):
  File "run_pretraining.py", line 574, in <module>
    train(data_train, data_eval, model)
  File "run_pretraining.py", line 457, in train
    num_ctxs=len(ctxs) * num_workers)
  File "/home/piotr/gluon-nlp/scripts/bert/fp16_utils.py", line 433, in step
    self.fp32_trainer.update(step_size)
  File "/home/piotr/mxnet_lamb/python/mxnet/gluon/trainer.py", line 397, in update
    self._update(ignore_stale_grad)
  File "/home/piotr/mxnet_lamb/python/mxnet/gluon/trainer.py", line 434, in _update
    updater(i, w, g)
  File "/home/piotr/mxnet_lamb/python/mxnet/optimizer/optimizer.py", line 1777, in __call__
    self.optimizer.update_multi_precision(i, w, g, self.states[i])
  File "/home/piotr/mxnet_lamb/python/mxnet/optimizer/optimizer.py", line 291, in update_multi_precision
    self.update(index, weight_master_copy, grad32, original_state)
  File "/home/piotr/mxnet_lamb/python/mxnet/optimizer/optimizer.py", line 1012, in update
    g = lamb_update(weight, grad, mean, var, wd=wd, **kwargs)
  File "<string>", line 88, in lamb_update
  File "/home/piotr/mxnet_lamb/python/mxnet/_ctypes/ndarray.py", line 107, in _imperative_invoke
    ctypes.byref(out_stypes)))
  File "/home/piotr/mxnet_lamb/python/mxnet/base.py", line 254, in check_call
    raise MXNetError(py_str(_LIB.MXGetLastError()))
mxnet.base.MXNetError: Some trailing characters could not be parsed: '[0.0015625]
<NDArray 1 @gpu(0)>', in operator lamb_update(name="", rescale_grad="
[0.0015625]
<NDArray 1 @gpu(0)>", wd="0.01", bias_correction="True", t="1", epsilon="1e-06", beta2="0.999", beta1="0.9")

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Please add description and reference to paper in the PR.

Done

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larroy commented Nov 20, 2019

@access2rohit could you answer Sam's comments?

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@access2rohit could you answer Sam's comments?

Done

@eric-haibin-lin eric-haibin-lin merged commit 85d3ef3 into apache:master Nov 24, 2019
float beta1;
float beta2;
float epsilon;
float t;
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@eric-haibin-lin @access2rohit I find this issue when reading the code. Here, the t should be the number of updates and should not be stored as float, which will lose the precision. I think we need to store it as index_t.

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we are using float here for integer data type. @sxjscience can you explain how we will loses precision for the operation beta^t ?


if (bias_correction) {
DType mean_hat = mean_data[i] / (1. - power::Map(beta1, t));
DType var_hat = var_data[i] / (1 - power::Map(beta2, t));
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Actually, in apex, it uses a float32 to calculate the power and then switch to float16:
https://github.com/NVIDIA/apex/blob/325f5a0bec542701edba1628ad34f3b2ea47c556/csrc/multi_tensor_lamb.cu#L231-L249

@leezu leezu removed the pr-awaiting-review PR is waiting for code review label Nov 27, 2019
ptrendx pushed a commit to ptrendx/mxnet that referenced this pull request Dec 10, 2019
* initial commit lamb optimizer

* fixing base lamb optimizer

* adding API doc for Lamb Phase 1 and 2
eric-haibin-lin pushed a commit that referenced this pull request Dec 10, 2019
* initial commit lamb optimizer

* fixing base lamb optimizer

* adding API doc for Lamb Phase 1 and 2
eric-haibin-lin pushed a commit to eric-haibin-lin/mxnet that referenced this pull request Dec 14, 2019
* initial commit lamb optimizer

* fixing base lamb optimizer

* adding API doc for Lamb Phase 1 and 2
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8 participants