change: improve documentation of some functions (#864)

[pr-827][followups] Improve documentation of some functions.
Also some unit test fixes. See comments from marcio in
#827

Author: knaresh

src/sagemaker/session.py

@@ -581,9 +581,9 @@ def transform(
             input_config (dict): A dictionary describing the input data (and its location) for the job.
             output_config (dict): A dictionary describing the output location for the job.
             resource_config (dict): A dictionary describing the resources to complete the job.
-            tags (list[dict]): List of tags for labeling a transform job.
+            tags (list[dict]): List of tags for labeling a transform job. For more information,
+                see https://docs.aws.amazon.com/sagemaker/latest/dg/API_Tag.html.
             data_processing(dict): A dictionary describing config for combining the input data and transformed data.
-                                   For more, see https://docs.aws.amazon.com/sagemaker/latest/dg/API_Tag.html.
         """
         transform_request = {
             "TransformJobName": job_name,

src/sagemaker/transformer.py

@@ -142,10 +142,12 @@ def transform(
             input_filter (str): A JSONPath to select a portion of the input to
                 pass to the algorithm container for inference. If you omit the
                 field, it gets the value '$', representing the entire input.
-                Some examples: "$[1:]", "$.features"(default: None).
+                For more information, see https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateTransformJob.html.
+                Some examples: "$[1:]", "$.features" (default: None).
             output_filter (str): A JSONPath to select a portion of the
-                joined/original output to return as the output. Some examples:
-                "$[1:]", "$.prediction" (default: None).
+                joined/original output to return as the output.
+                For more information, see https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateTransformJob.html.
+                Some examples: "$[1:]", "$.prediction" (default: None).
             join_source (str): The source of data to be joined to the transform
                 output. It can be set to 'Input' meaning the entire input record
                 will be joined to the inference result. You can use OutputFilter

tests/integ/test_transformer.py

@@ -67,12 +67,13 @@ def test_transform_mxnet(sagemaker_session, mxnet_full_version):
 
     kms_key_arn = get_or_create_kms_key(sagemaker_session)
     output_filter = "$"
+    input_filter = "$"
 
     transformer = _create_transformer_and_transform_job(
         mx,
         transform_input,
         kms_key_arn,
-        input_filter=None,
+        input_filter=input_filter,
         output_filter=output_filter,
         join_source=None,
     )
@@ -86,6 +87,7 @@ def test_transform_mxnet(sagemaker_session, mxnet_full_version):
     )
     assert kms_key_arn == job_desc["TransformResources"]["VolumeKmsKeyId"]
     assert output_filter == job_desc["DataProcessing"]["OutputFilter"]
+    assert input_filter == job_desc["DataProcessing"]["InputFilter"]
 
 
 @pytest.mark.canary_quick

tests/unit/test_session.py

@@ -676,12 +676,15 @@ def test_transform_pack_to_request(sagemaker_session):
 
     resource_config = {"InstanceCount": INSTANCE_COUNT, "InstanceType": INSTANCE_TYPE}
 
+    data_processing = {"OutputFilter": "$", "InputFilter": "$", "JoinSource": "Input"}
+
     expected_args = {
         "TransformJobName": JOB_NAME,
         "ModelName": model_name,
         "TransformInput": in_config,
         "TransformOutput": out_config,
         "TransformResources": resource_config,
+        "DataProcessing": data_processing,
     }
 
     sagemaker_session.transform(
@@ -695,7 +698,7 @@ def test_transform_pack_to_request(sagemaker_session):
         output_config=out_config,
         resource_config=resource_config,
         tags=None,
-        data_processing=None,
+        data_processing=data_processing,
     )
 
     _, _, actual_args = sagemaker_session.sagemaker_client.method_calls[0]