Update description for TransformInput()

Author: mwfongAWS

src/sagemaker/inputs.py

@@ -165,6 +165,54 @@ class TransformInput(object):
     """Create a class containing all the parameters.
 
     It can be used when calling ``sagemaker.transformer.Transformer.transform()``
+    
+    Args:
+        data (str): The S3 location of the input data that the model can consume.
+        data_type (str): elastic inference accelerator type.
+            (default: ``'S3Prefix'``)
+        content_type (str): The multipurpose internet mail extension (MIME) type of the data.
+            (default: None)
+        compression_type (str): If your transform data is compressed, specify the compression type.
+            Valid values: ``'Gzip'``, ``None``
+            (default: None)
+        split_type (str): The method to use to split the transform job's data files into smaller 
+            batches.
+        Valid values: ``'Line'``, ``RecordIO``, ``'TFRecord'``, None
+            (default: None)
+        input_filter (str): A JSONPath expression used to select a portion of the input data to pass 
+            to the algorithm. Use the InputFilter parameter to exclude fields, such as an ID column, 
+            from the input. If you want SageMaker to pass the entire input dataset to the algorithm, 
+            accept the default value ``$``. For more information on batch transform data processing, 
+            input, join, and output, see 
+            `Associate Prediction Results with Input Records 
+            <https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html?`.
+            Valid values: ``$``. See `JSONPath Operators 
+            <https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators>' 
+            for more options.
+            (default: ``$``)
+        output_filter (str): A JSONPath expression used to select a portion of the joined dataset to 
+            save in the output file for a batch transform job. If you want SageMaker to store the 
+            entire input dataset in the output file, leave the default value, $. If you specify 
+            indexes that aren't within the dimension size of the joined dataset, you get an error.
+            Valid values: ``$``. See `JSONPath Operators 
+            <https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators>' 
+            for more options.
+            (default: ``$``)
+            join_source (str): Specifies the source of the data to join with the transformed data. The 
+            default value is ``None``, which specifies not to join the input with the transformed data. 
+            If you want the batch transform job to join the original input data with the transformed data, 
+            set to ``Input``. For more information on 
+            Valid values: ``None``, ``Input``
+            (default: None)
+        model_client_config (dict): Configures the timeout and maximum number of retries for 
+            processing a transform job invocation.
+
+                * ``'InvocationsTimeoutInSeconds'`` (int) - The timeout value in seconds for an invocation request. The default value is 600.
+                * ``'InvocationsMaxRetries'`` (int) - The maximum number of retries when invocation requests are failing.
+        (default: ``{'InvocationsTimeoutInSeconds'=600,'InvocationsMaxRetries'=3}``)
+        batch_data_capture_config (dict): Specifies configuration related to batch transform job 
+            data capture for use with Amazon SageMaker Model Monitoring.
+            (default: None)
     """
 
     data: str = attr.ib()