Fix failing distributed sampler test (#3453)

- Fix failing distributed sampler test
- Updated pytorch docker image in gpu GHA workflows

Author: vfdev-5

.github/workflows/gpu-hvd-tests.yml

@@ -24,7 +24,7 @@ jobs:
         pytorch-channel: [pytorch]
       fail-fast: false
     env:
-      DOCKER_IMAGE: "pytorch/conda-builder:cuda12.1"
+      DOCKER_IMAGE: "pytorch/almalinux-builder:cuda12.8"
       REPOSITORY: ${{ github.repository }}
       PR_NUMBER: ${{ github.event.pull_request.number }}
     runs-on: linux.8xlarge.nvidia.gpu
@@ -113,6 +113,10 @@ jobs:
           pip install -r requirements-dev.txt
           pip install -e .
 
+          # Upgrade pyOpenSSL to avoid issue:
+          # AttributeError: module 'lib' has no attribute 'X509_V_FLAG_NOTIFY_POLICY'. Did you mean: 'X509_V_FLAG_EXPLICIT_POLICY'?
+          pip install -U pyOpenSSL
+
           EOF
           )
 

.github/workflows/gpu-tests.yml

@@ -24,7 +24,7 @@ jobs:
         pytorch-channel: [pytorch, pytorch-nightly]
       fail-fast: false
     env:
-      DOCKER_IMAGE: "pytorch/almalinux-builder:cuda12.4"
+      DOCKER_IMAGE: "pytorch/almalinux-builder:cuda12.8"
       REPOSITORY: ${{ github.repository }}
       PR_NUMBER: ${{ github.event.pull_request.number }}
     runs-on: linux.g4dn.12xlarge.nvidia.gpu
@@ -113,6 +113,10 @@ jobs:
           pip install -r requirements-dev.txt
           pip install -e .
 
+          # Upgrade pyOpenSSL to avoid issue:
+          # AttributeError: module 'lib' has no attribute 'X509_V_FLAG_NOTIFY_POLICY'. Did you mean: 'X509_V_FLAG_EXPLICIT_POLICY'?
+          pip install -U pyOpenSSL
+
           EOF
           )
 

tests/ignite/distributed/test_auto.py

@@ -311,7 +311,7 @@ def test_dist_proxy_sampler():
         DistributedProxySampler(None)
 
     with pytest.raises(TypeError, match=r"Argument sampler should have length"):
-        DistributedProxySampler(Sampler([1]))
+        DistributedProxySampler(Sampler())
 
     with pytest.raises(TypeError, match=r"Argument sampler must not be a distributed sampler already"):
         DistributedProxySampler(DistributedSampler(sampler, num_replicas=num_replicas, rank=0))