run all tests and skip data service for tf2.18

Author: Yadan Wei

dlc_developer_config.toml

@@ -64,13 +64,13 @@ ecs_tests = true
 eks_tests = true
 ec2_tests = true
 # Set it to true if you are preparing a Benchmark related PR
-ec2_benchmark_tests = false
+ec2_benchmark_tests = true
 
 ### Set ec2_tests_on_heavy_instances = true to be able to run any EC2 tests that use large/expensive instance types by
 ### default. If false, these types of tests will be skipped while other tests will run as usual.
 ### These tests are run in EC2 test jobs, so ec2_tests must be true if ec2_tests_on_heavy_instances is true.
 ### Off by default (set to false)
-ec2_tests_on_heavy_instances = false
+ec2_tests_on_heavy_instances = true
 
 ### SM specific tests
 ### On by default

test/dlc_tests/ec2/tensorflow/training/test_tensorflow_training.py

@@ -370,12 +370,13 @@ def test_tensorflow_dataservice_cpu(
 
 # Testing Data Service on only one GPU instance
 # Skip test for TF 2.3 and below
+# skip temporily with this issue https://github.com/aws/deep-learning-containers/pull/4485
 @pytest.mark.integration("tensorflow-dataservice-test")
 @pytest.mark.model("N/A")
 @pytest.mark.team("frameworks")
 @pytest.mark.parametrize("ec2_instance_type", TF_EC2_GPU_INSTANCE_TYPE, indirect=True)
 def test_tensorflow_dataservice_gpu(
-    tensorflow_training, ec2_connection, tf24_and_above_only, gpu_only, ec2_instance_type
+    tensorflow_training, ec2_connection, tf24_and_above_only, gpu_only, ec2_instance_type, skip_tf218
 ):
     if test_utils.is_image_incompatible_with_instance_type(tensorflow_training, ec2_instance_type):
         pytest.skip(
@@ -398,12 +399,13 @@ def test_tensorflow_distribute_dataservice_cpu(
 
 # Testing Data Service Distributed mode on only one GPU instance
 # Skip test for TF 2.3 and below
+# skip temporily with this issue https://github.com/aws/deep-learning-containers/pull/4485
 @pytest.mark.integration("tensorflow-dataservice-distribute-test")
 @pytest.mark.model("N/A")
 @pytest.mark.team("frameworks")
 @pytest.mark.parametrize("ec2_instance_type", TF_EC2_GPU_INSTANCE_TYPE, indirect=True)
 def test_tensorflow_distribute_dataservice_gpu(
-    tensorflow_training, ec2_connection, tf24_and_above_only, gpu_only, ec2_instance_type
+    tensorflow_training, ec2_connection, tf24_and_above_only, gpu_only, ec2_instance_type, skip_tf218
 ):
     if test_utils.is_image_incompatible_with_instance_type(tensorflow_training, ec2_instance_type):
         pytest.skip(