Merge remote-tracking branch 'aws/master' into fix-tf2-sm-benchmark

* aws/master:
  Skip temporarily to revert it (aws#1087)
  Add back efa configs to SM tests (aws#1086)

Author: jeet4320

test/dlc_tests/sanity/test_pre_release.py

@@ -272,7 +272,7 @@ def _run_dependency_check_test(image, ec2_connection, processor):
 @pytest.mark.model("N/A")
 @pytest.mark.canary("Run dependency tests regularly on production images")
 @pytest.mark.parametrize("ec2_instance_type", ["c5.4xlarge"], indirect=True)
-@pytest.mark.skipif(not (is_nightly_context() or is_mainline_context() or (is_canary_context() and is_time_for_canary_safety_scan())),
+@pytest.mark.skipif(not (is_nightly_context() or (is_canary_context() and is_time_for_canary_safety_scan())),
                     reason="Do not run dependency check on PR tests. "
                            "Executing test in canaries pipeline during only a limited period of time."
                     )
@@ -283,7 +283,7 @@ def test_dependency_check_cpu(cpu, ec2_connection):
 @pytest.mark.model("N/A")
 @pytest.mark.canary("Run dependency tests regularly on production images")
 @pytest.mark.parametrize("ec2_instance_type", ["p3.2xlarge"], indirect=True)
-@pytest.mark.skipif(not (is_nightly_context() or is_mainline_context() or (is_canary_context() and is_time_for_canary_safety_scan())),
+@pytest.mark.skipif(not (is_nightly_context() or (is_canary_context() and is_time_for_canary_safety_scan())),
                     reason="Do not run dependency check on PR tests. "
                            "Executing test in canaries pipeline during only a limited period of time."
                     )

test/sagemaker_tests/pytorch/training/conftest.py

@@ -105,6 +105,20 @@ def pytest_addoption(parser):
     parser.addoption('--tag', default=None)
     parser.addoption('--generate-coverage-doc', default=False, action='store_true',
                      help='use this option to generate test coverage doc')
+    parser.addoption(
+        "--efa", action="store_true", default=False, help="Run only efa tests",
+    )
+
+
+def pytest_configure(config):
+    config.addinivalue_line("markers", "efa(): explicitly mark to run efa tests")
+
+
+def pytest_runtest_setup(item):
+    if item.config.getoption("--efa"):
+        efa_tests = [mark for mark in item.iter_markers(name="efa")]
+        if not efa_tests:
+            pytest.skip("Skipping non-efa tests")
 
 
 def pytest_collection_modifyitems(session, config, items):

test/sagemaker_tests/tensorflow/tensorflow2_training/integration/conftest.py

@@ -42,6 +42,16 @@ def pytest_addoption(parser):
     parser.addoption('--instance-type', default=None)
     parser.addoption('--generate-coverage-doc', default=False, action='store_true',
                      help='use this option to generate test coverage doc')
+    parser.addoption(
+        "--efa", action="store_true", default=False, help="Run only efa tests",
+    )
+
+
+def pytest_runtest_setup(item):
+    if item.config.getoption("--efa"):
+        efa_tests = [mark for mark in item.iter_markers("efa")]
+        if not efa_tests:
+            pytest.skip("Skipping non-efa tests")
 
 
 def pytest_collection_modifyitems(session, config, items):
@@ -54,6 +64,7 @@ def pytest_collection_modifyitems(session, config, items):
 def pytest_configure(config):
     os.environ['TEST_PY_VERSIONS'] = config.getoption('--py-version')
     os.environ['TEST_PROCESSORS'] = config.getoption('--processor')
+    config.addinivalue_line("markers", "efa(): explicitly mark to run efa tests")
 
 
 @pytest.fixture(scope='session')

test/test_utils/sagemaker.py

@@ -140,9 +140,10 @@ def generate_sagemaker_pytest_cmd(image, sagemaker_test_type):
     is_py3 = " python3 -m "
 
     efa_flag = ""
-    if job_type == "training" and (framework == "tensorflow" or framework == "pytorch"):
-        efa_dedicated = os.getenv("EFA_DEDICATED", "False").lower() == "true"
-        efa_flag = '--efa' if efa_dedicated else '-m not efa'
+    if job_type == "training":
+        if (framework == "tensorflow" and framework_major_version >= "2") or framework == "pytorch":
+            efa_dedicated = os.getenv("EFA_DEDICATED", "False").lower() == "true"
+            efa_flag = '--efa' if efa_dedicated else '-m \"not efa\"'
 
     remote_pytest_cmd = (
         f"pytest -rA {integration_path} --region {region} --processor {processor} {docker_base_arg} "