documentation: Minor updates to Clarify API documentation

src/sagemaker/clarify.py

@@ -48,12 +48,17 @@ def __init__(
             headers (list[str]): A list of column names in the input dataset.
             features (str): JSONPath for locating the feature columns for bias metrics if the
                 dataset format is JSONLines.
-            dataset_type (str): Format of the dataset. Valid values are "text/csv" for CSV
-                and "application/jsonlines" for JSONLines.
+            dataset_type (str): Format of the dataset. Valid values are "text/csv" for CSV,
+                "application/jsonlines" for JSONLines, and "application/x-parquet" for Parquet.
             s3_data_distribution_type (str): Valid options are "FullyReplicated" or
                 "ShardedByS3Key".
             s3_compression_type (str): Valid options are "None" or "Gzip".
         """
+        if dataset_type not in ["text/csv", "application/jsonlines", "application/x-parquet"]:
+            raise ValueError(
+                f"Invalid dataset_type '{dataset_type}'."
+                f" Please check the API documentation for the supported dataset types."
+            )
         self.s3_data_input_path = s3_data_input_path
         self.s3_output_path = s3_output_path
         self.s3_data_distribution_type = s3_data_distribution_type
@@ -508,7 +513,7 @@ def run_pre_training_bias(
         kms_key=None,
         experiment_config=None,
     ):
-        """Runs a ProcessingJob to compute the requested bias 'methods' of the input data.
+        """Runs a ProcessingJob to compute the pre-training bias methods of the input data.
 
         Computes the requested methods that compare 'methods' (e.g. fraction of examples) for the
         sensitive group vs the other examples.
@@ -517,14 +522,14 @@ def run_pre_training_bias(
             data_config (:class:`~sagemaker.clarify.DataConfig`): Config of the input/output data.
             data_bias_config (:class:`~sagemaker.clarify.BiasConfig`): Config of sensitive groups.
             methods (str or list[str]): Selector of a subset of potential metrics:
-                ["`CI <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-ci.html>`_",
-                "`DPL <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-dpl.html>`_",
-                "`KL <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-kl.html>`_",
-                "`JS <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-js.html>`_",
-                "`LP <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-lp.html>`_",
-                "`TVD <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-tvd.html>`_",
-                "`KS <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-ks.html>`_",
-                "`CDDL <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-cdd.html>`_"].
+                ["`CI <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-bias-metric-class-imbalance.html>`_",
+                "`DPL <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-data-bias-metric-true-label-imbalance.html>`_",
+                "`KL <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-data-bias-metric-kl-divergence.html>`_",
+                "`JS <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-data-bias-metric-jensen-shannon-divergence.html>`_",
+                "`LP <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-data-bias-metric-lp-norm.html>`_",
+                "`TVD <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-data-bias-metric-total-variation-distance.html>`_",
+                "`KS <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-data-bias-metric-kolmogorov-smirnov.html>`_",
+                "`CDDL <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-data-bias-metric-cddl.html>`_"].
                 Defaults to computing all.
             wait (bool): Whether the call should wait until the job completes (default: True).
             logs (bool): Whether to show the logs produced by the job.
@@ -538,7 +543,7 @@ def run_pre_training_bias(
             experiment_config (dict[str, str]): Experiment management configuration.
                 Dictionary contains three optional keys:
                 'ExperimentName', 'TrialName', and 'TrialComponentDisplayName'.
-        """
+        """  # noqa E501
         analysis_config = data_config.get_config()
         analysis_config.update(data_bias_config.get_config())
         analysis_config["methods"] = {"pre_training_bias": {"methods": methods}}
@@ -562,7 +567,7 @@ def run_post_training_bias(
         kms_key=None,
         experiment_config=None,
     ):
-        """Runs a ProcessingJob to compute the requested bias 'methods' of the model predictions.
+        """Runs a ProcessingJob to compute the post-training bias methods of the model predictions.
 
         Spins up a model endpoint, runs inference over the input example in the
         's3_data_input_path' to obtain predicted labels. Computes a the requested methods that
@@ -633,12 +638,11 @@ def run_bias(
         kms_key=None,
         experiment_config=None,
     ):
-        """Runs a ProcessingJob to compute the requested bias 'methods' of the model predictions.
+        """Runs a ProcessingJob to compute the requested bias methods.
 
-        Spins up a model endpoint, runs inference over the input example in the
-        's3_data_input_path' to obtain predicted labels. Computes a the requested methods that
-        compare 'methods' (e.g. accuracy, precision, recall) for the sensitive group vs the other
-        examples.
+        It computes the metrics of both the pre-training methods and the post-training methods.
+        To calculate post-training methods, it needs to spin up a model endpoint, runs inference
+        over the input example in the 's3_data_input_path' to obtain predicted labels.
 
         Args:
             data_config (:class:`~sagemaker.clarify.DataConfig`): Config of the input/output data.
@@ -648,14 +652,14 @@ def run_bias(
             model_predicted_label_config (:class:`~sagemaker.clarify.ModelPredictedLabelConfig`):
                 Config of how to extract the predicted label from the model output.
             pre_training_methods (str or list[str]): Selector of a subset of potential metrics:
-                ["`CI <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-ci.html>`_",
-                "`DPL <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-dpl.html>`_",
-                "`KL <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-kl.html>`_",
-                "`JS <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-js.html>`_",
-                "`LP <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-lp.html>`_",
-                "`TVD <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-tvd.html>`_",
-                "`KS <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-ks.html>`_",
-                "`CDDL <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-cdd.html>`_"].
+                ["`CI <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-bias-metric-class-imbalance.html>`_",
+                "`DPL <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-data-bias-metric-true-label-imbalance.html>`_",
+                "`KL <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-data-bias-metric-kl-divergence.html>`_",
+                "`JS <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-data-bias-metric-jensen-shannon-divergence.html>`_",
+                "`LP <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-data-bias-metric-lp-norm.html>`_",
+                "`TVD <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-data-bias-metric-total-variation-distance.html>`_",
+                "`KS <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-data-bias-metric-kolmogorov-smirnov.html>`_",
+                "`CDDL <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-data-bias-metric-cddl.html>`_"].
                 Defaults to computing all.
             post_training_methods (str or list[str]): Selector of a subset of potential metrics:
                 ["`DPPL <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-post-training-bias-metric-dppl.html>`_"
@@ -682,7 +686,7 @@ def run_bias(
             experiment_config (dict[str, str]): Experiment management configuration.
                 Dictionary contains three optional keys:
                 'ExperimentName', 'TrialName', and 'TrialComponentDisplayName'.
-        """
+        """  # noqa E501
         analysis_config = data_config.get_config()
         analysis_config.update(bias_config.get_config())
         analysis_config["predictor"] = model_config.get_predictor_config()

tests/unit/test_clarify.py

@@ -68,6 +68,15 @@ def test_data_config():
     assert "FullyReplicated" == data_config.s3_data_distribution_type
 
 
+def test_invalid_data_config():
+    with pytest.raises(ValueError, match=r"^Invalid dataset_type"):
+        DataConfig(
+            s3_data_input_path="s3://bucket/inputpath",
+            s3_output_path="s3://bucket/outputpath",
+            dataset_type="whatnot_type",
+        )
+
+
 def test_data_bias_config():
     label_values = [1]
     facet_name = "F1"