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[examples tests on multigpu] resolving require_torch_non_multi_gpu_but_fix_me (#10561)

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* batch 1

* this is tpu

* deebert attempt

* the rest
This commit is contained in:
Stas Bekman
2021-03-08 11:11:40 -08:00
committed by GitHub
parent dfd16af832
commit f284089ec4
9 changed files with 35 additions and 62 deletions
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43
examples/research_projects/deebert/test_glue_deebert.py
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@@ -1,11 +1,10 @@
import argparse
import logging
import sys
import unittest
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import require_torch_non_multi_gpu_but_fix_me, slow
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
@@ -20,17 +19,34 @@ def get_setup_file():
return args.f
class DeeBertTests(unittest.TestCase):
class DeeBertTests(TestCasePlus):
def setup(self) -> None:
stream_handler = logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
def run_and_check(self, args):
n_gpu = get_gpu_count()
if n_gpu > 1:
pass
# XXX: doesn't quite work with n_gpu > 1 https://github.com/huggingface/transformers/issues/10560
# script = f"{self.examples_dir_str}/research_projects/deebert/run_glue_deebert.py"
# distributed_args = f"-m torch.distributed.launch --nproc_per_node={n_gpu} {script}".split()
# cmd = [sys.executable] + distributed_args + args
# execute_subprocess_async(cmd, env=self.get_env())
# XXX: test the results - need to save them first into .json file
else:
args.insert(0, "run_glue_deebert.py")
with patch.object(sys, "argv", args):
result = run_glue_deebert.main()
for value in result.values():
self.assertGreaterEqual(value, 0.666)
@slow
@require_torch_non_multi_gpu_but_fix_me
@require_torch_non_multi_gpu
def test_glue_deebert_train(self):
train_args = """
run_glue_deebert.py
--model_type roberta
--model_name_or_path roberta-base
--task_name MRPC
@@ -51,13 +67,9 @@ class DeeBertTests(unittest.TestCase):
--overwrite_cache
--eval_after_first_stage
""".split()
with patch.object(sys, "argv", train_args):
result = run_glue_deebert.main()
for value in result.values():
self.assertGreaterEqual(value, 0.666)
self.run_and_check(train_args)
eval_args = """
run_glue_deebert.py
--model_type roberta
--model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
--task_name MRPC
@@ -72,13 +84,9 @@ class DeeBertTests(unittest.TestCase):
--overwrite_cache
--per_gpu_eval_batch_size=1
""".split()
with patch.object(sys, "argv", eval_args):
result = run_glue_deebert.main()
for value in result.values():
self.assertGreaterEqual(value, 0.666)
self.run_and_check(eval_args)
entropy_eval_args = """
run_glue_deebert.py
--model_type roberta
--model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
--task_name MRPC
@@ -93,7 +101,4 @@ class DeeBertTests(unittest.TestCase):
--overwrite_cache
--per_gpu_eval_batch_size=1
""".split()
with patch.object(sys, "argv", entropy_eval_args):
result = run_glue_deebert.main()
for value in result.values():
self.assertGreaterEqual(value, 0.666)
self.run_and_check(entropy_eval_args)