diff --git a/sdks/python/apache_beam/examples/inference/pytorch_image_classification_with_side_inputs.py b/sdks/python/apache_beam/examples/inference/pytorch_image_classification_with_side_inputs.py
index 787341263fde..903bf38ab279 100644
--- a/sdks/python/apache_beam/examples/inference/pytorch_image_classification_with_side_inputs.py
+++ b/sdks/python/apache_beam/examples/inference/pytorch_image_classification_with_side_inputs.py
@@ -115,7 +115,7 @@ class PostProcessor(beam.DoFn):
   Return filename, prediction and the model id used to perform the
   prediction
   """
-  def process(self, element: tuple[str, PredictionResult]) -> Iterable[str]:
+  def process(self, element: tuple[str, PredictionResult]) -> Iterable[Any]:
     filename, prediction_result = element
     prediction = torch.argmax(prediction_result.inference, dim=0)
     yield filename, prediction, prediction_result.model_id
diff --git a/sdks/python/apache_beam/io/gcp/bigquery_change_history.py b/sdks/python/apache_beam/io/gcp/bigquery_change_history.py
index f0a23ddce02a..1e90c2974778 100644
--- a/sdks/python/apache_beam/io/gcp/bigquery_change_history.py
+++ b/sdks/python/apache_beam/io/gcp/bigquery_change_history.py
@@ -496,7 +496,8 @@ def _emit_query_ranges(
       self,
       start_ts: Timestamp,
       end_ts: Timestamp,
-      watermark_estimator: _PollWatermarkEstimator) -> Iterable[_QueryRange]:
+      watermark_estimator: _PollWatermarkEstimator
+  ) -> Iterable[TimestampedValue[_QueryRange]]:
     """Compute and yield _QueryRange elements, advancing estimator state."""
     ranges = compute_ranges(start_ts, end_ts, self._change_function)
     _LOGGER.info(
@@ -524,7 +525,7 @@ def process(
       restriction_tracker=beam.DoFn.RestrictionParam(),
       watermark_estimator=beam.DoFn.WatermarkEstimatorParam(
           _PollWatermarkEstimatorProvider())
-  ) -> Iterable[_QueryRange]:
+  ) -> Iterable[TimestampedValue[_QueryRange]]:
 
     now = time.time()
     start_ts = watermark_estimator.poll_cursor()
@@ -1031,7 +1032,10 @@ class _DecompressArrowBatchesFn(beam.DoFn):
   def __init__(self, change_timestamp_column: str = 'change_timestamp') -> None:
     self._change_timestamp_column = change_timestamp_column
 
-  def process(self, element: tuple[bytes, bytes]) -> Iterable[dict[str, Any]]:
+  def process(
+      self,
+      element: tuple[bytes,
+                     bytes]) -> Iterable[TimestampedValue[dict[str, Any]]]:
     schema_bytes, batch_bytes = element
     schema = pyarrow.ipc.read_schema(pyarrow.py_buffer(schema_bytes))
     batch = pyarrow.ipc.read_record_batch(
diff --git a/sdks/python/pyproject.toml b/sdks/python/pyproject.toml
index e769bf2d91e2..5901d817c9c7 100644
--- a/sdks/python/pyproject.toml
+++ b/sdks/python/pyproject.toml
@@ -212,5 +212,4 @@ invalid-argument = "ignore"
 invalid-inheritance = "ignore"
 not-iterable = "ignore"
 unexpected-keyword = "ignore"
-invalid-yield = "ignore"
 bad-typed-dict-key = "ignore"