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Horovod tests do not make sense for 1 gpu (#12710) 

Co-authored-by: Akihiro Nitta <nitta@akihironitta.com>
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otaj 2022-04-21 10:49:40 +02:00 committed by GitHub
parent 1233554e73
commit f300b60f47
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1 changed files with 4 additions and 4 deletions
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8
tests/models/test_horovod.py
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@ -168,7 +168,7 @@ def test_horovod_multi_gpu_accumulate_grad_batches(tmpdir):
_run_horovod(trainer_options) _run_horovod(trainer_options)
@RunIf(horovod=True, skip_windows=True) @RunIf(horovod=True, skip_windows=True, min_gpus=2)
def test_horovod_raises_unsupported_accumulate_grad_batches(tmpdir): def test_horovod_raises_unsupported_accumulate_grad_batches(tmpdir):
"""Ensure MisConfigurationException for different `accumulate_grad_batches` at different epochs for Horovod """Ensure MisConfigurationException for different `accumulate_grad_batches` at different epochs for Horovod
Strategy on multi-gpus.""" Strategy on multi-gpus."""
@ -178,7 +178,7 @@ def test_horovod_raises_unsupported_accumulate_grad_batches(tmpdir):
enable_progress_bar=False, enable_progress_bar=False,
accumulate_grad_batches={0: 4, 2: 2}, accumulate_grad_batches={0: 4, 2: 2},
accelerator="auto", accelerator="auto",
devices=1, devices=2,
strategy="horovod", strategy="horovod",
) )
with pytest.raises(MisconfigurationException, match="Horovod.*does not support.*accumulate_grad_batches"): with pytest.raises(MisconfigurationException, match="Horovod.*does not support.*accumulate_grad_batches"):
@ -262,7 +262,7 @@ def test_horovod_gather(tmpdir):
_run_horovod(trainer_options) _run_horovod(trainer_options)
@RunIf(min_gpus=1, skip_windows=True, horovod=True, horovod_nccl=True) @RunIf(min_gpus=2, skip_windows=True, horovod=True, horovod_nccl=True)
def test_horovod_transfer_batch_to_gpu(tmpdir): def test_horovod_transfer_batch_to_gpu(tmpdir):
class TestTrainingStepModel(BoringModel): class TestTrainingStepModel(BoringModel):
def training_step(self, batch, *args, **kwargs): def training_step(self, batch, *args, **kwargs):
@ -282,7 +282,7 @@ def test_horovod_transfer_batch_to_gpu(tmpdir):
limit_train_batches=0.4, limit_train_batches=0.4,
limit_val_batches=0.2, limit_val_batches=0.2,
accelerator="gpu", accelerator="gpu",
devices=1, devices=2,
strategy="horovod", strategy="horovod",
) )
tpipes.run_model_test_without_loggers(trainer_options, model) tpipes.run_model_test_without_loggers(trainer_options, model)