Skip to content

[CI] Disabled APEX tests on CUDA #2308

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Nov 1, 2021
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
5 changes: 3 additions & 2 deletions tests/ignite/engine/test_create_supervised.py
Original file line number Diff line number Diff line change
Expand Up @@ -478,8 +478,9 @@ def test_create_supervised_trainer_on_cuda_amp_scaler():
)


@pytest.mark.skipif(not torch.cuda.is_available(), reason="Skip if no GPU")
@pytest.mark.skipif(not find_spec("apex"), reason="Skip if no APEX")
# @pytest.mark.skipif(not torch.cuda.is_available(), reason="Skip if no GPU")
# @pytest.mark.skipif(not find_spec("apex"), reason="Skip if no APEX")
@pytest.mark.skip(reason="Temporarily disabled, as it fails because of an issue from apex side")
def test_create_supervised_trainer_on_cuda_apex():
model_device = trainer_device = "cuda"
_test_create_supervised_trainer_wrong_accumulation(
Expand Down
7 changes: 4 additions & 3 deletions tests/ignite/metrics/test_accumulation.py
Original file line number Diff line number Diff line change
@@ -1,5 +1,4 @@
import os
from importlib.util import find_spec

import numpy as np
import pytest
Expand Down Expand Up @@ -500,8 +499,10 @@ def test_distrib_xla_nprocs(xmp_executor):
xmp_executor(_test_distrib_xla_nprocs, args=(), nprocs=n)


@pytest.mark.skipif(not torch.cuda.is_available(), reason="Skip if no GPU")
@pytest.mark.skipif(not find_spec("apex"), reason="Skip if no APEX")
# Enable this test when apex issue is fixed
# @pytest.mark.skipif(not torch.cuda.is_available(), reason="Skip if no GPU")
# @pytest.mark.skipif(not find_spec("apex"), reason="Skip if no APEX")
@pytest.mark.skip(reason="Temporarily disabled, as it fails because of an issue from apex side")
def test_apex_average_on_cuda():
device = "cuda"
_test_apex_average(device, amp_mode="apex", opt_level="O0")
Expand Down