code: def testSequentialRollingRangeResolverFn_E2E_SkipRaised(self):
      # The artifacts will only have consecutive spans from [1, 5] but
      # num_spans=10 so no artifacts will be returnd by the resolver_fn and
      # a Skip will be raised during input resolution.
      xs = canned_resolver_functions.sequential_rolling_range(
          channel_utils.artifact_query(
              artifact_type=test_utils.DummyArtifact
          ),
          start_span_number=1,
          num_spans=10,
          skip_num_recent_spans=0,
          keep_all_versions=False,
      )
      with for_each.ForEach(xs) as each_x:
          inputs = {"x": each_x}
      pipeline_node = test_utils.compile_inputs(inputs)
  
      spans = [1, 2, 3, 3, 4, 5]
      versions = [0, 0, 1, 0, 0, 0]
      _ = self._insert_artifacts_into_mlmd(spans, versions)
  
      resolved = inputs_utils.resolve_input_artifacts(
          pipeline_node=pipeline_node, metadata_handle=self.mlmd_handle
      )
      self.assertEmpty(resolved)
  
imports: from typing import Sequence
  import tensorflow
  from tfx import types
  from tfx.dsl.control_flow import for_each
  from tfx.dsl.input_resolution import canned_resolver_functions
  from tfx.dsl.input_resolution import resolver_op
  from tfx.dsl.input_resolution.ops import test_utils
  from tfx.orchestration import pipeline
  from tfx.orchestration.portable import inputs_utils
  from tfx.orchestration.portable.input_resolution import exceptions
  from tfx.types import channel_utils
  from tfx.types import resolved_channel
  from ml_metadata.proto import metadata_store_pb2
label_desc: Use image node_id 17 for calling the CannedResolverFunctionsTest obj's underlying member method code with example usage: obj.testSequentialRollingRangeResolverFn_E2E_SkipRaised() without return types