[Deepspeed] support zero.Init in from_config (#11805)

* support zero.Init in from_config

* no need for eval test
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Stas Bekman 2021-05-21 09:07:46 -07:00 committed by GitHub
parent 82335185fe
commit a26f4d6208
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2 changed files with 48 additions and 2 deletions

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@ -18,9 +18,14 @@ import types
from ...configuration_utils import PretrainedConfig
from ...file_utils import copy_func
from ...integrations import deepspeed_config, is_deepspeed_zero3_enabled
from ...utils import logging
from .configuration_auto import AutoConfig, replace_list_option_in_docstrings
logger = logging.get_logger(__name__)
CLASS_DOCSTRING = """
This is a generic model class that will be instantiated as one of the model classes of the library when created
with the :meth:`~transformers.BaseAutoModelClass.from_pretrained` class method or the
@ -362,7 +367,16 @@ class _BaseAutoModelClass:
def from_config(cls, config, **kwargs):
if type(config) in cls._model_mapping.keys():
model_class = _get_model_class(config, cls._model_mapping)
return model_class(config, **kwargs)
if is_deepspeed_zero3_enabled():
import deepspeed
logger.info("Detected DeepSpeed ZeRO-3: activating zero.init() for this model")
# this immediately partitions the model across all gpus, to avoid the overhead in time
# and memory copying it on CPU or each GPU first
with deepspeed.zero.Init(config=deepspeed_config()):
return model_class(config, **kwargs)
else:
return model_class(config, **kwargs)
raise ValueError(
f"Unrecognized configuration class {config.__class__} for this kind of AutoModel: {cls.__name__}.\n"
f"Model type should be one of {', '.join(c.__name__ for c in cls._model_mapping.keys())}."

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@ -25,6 +25,7 @@ from transformers.file_utils import WEIGHTS_NAME
from transformers.integrations import is_deepspeed_available
from transformers.testing_utils import (
CaptureLogger,
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
@ -741,7 +742,38 @@ class TestDeepSpeedWithLauncher(TestCasePlus):
# print(" ".join([f"\nPYTHONPATH={self.src_dir_str}"] +cmd)); die
execute_subprocess_async(cmd, env=self.get_env())
return output_dir
def test_clm_from_config_zero3(self):
# this test exercises AutoModel.from_config(config) - to ensure zero.Init is called
data_dir = self.tests_dir / "fixtures"
output_dir = self.get_auto_remove_tmp_dir()
args = f"""
--model_type gpt2
--tokenizer_name sshleifer/tiny-gpt2
--train_file {data_dir}/sample_text.txt
--validation_file {data_dir}/sample_text.txt
--output_dir {output_dir}
--overwrite_output_dir
--do_train
--max_train_samples 4
--per_device_train_batch_size 2
--num_train_epochs 1
--warmup_steps 8
--block_size 8
--fp16
--report_to none
""".split()
ds_args = f"--deepspeed {self.test_file_dir_str}/ds_config_zero3.json".split()
script = [f"{self.examples_dir_str}/pytorch/language-modeling/run_clm.py"]
launcher = self.get_launcher(distributed=True)
cmd = launcher + script + args + ds_args
# keep for quick debug
# print(" ".join([f"\nPYTHONPATH={self.src_dir_str}"] +cmd)); die
with CaptureStderr() as cs:
execute_subprocess_async(cmd, env=self.get_env())
assert "Detected DeepSpeed ZeRO-3" in cs.err
def get_launcher(self, distributed=False):
# 1. explicitly set --num_nodes=1 just in case these tests end up run on a multi-node setup