requirements.
    Besides the AWS configuration, it is very similar to the other PDF
    loaders, while also supporting JPEG, PNG and TIFF and non-native
    PDF formats.
    ```python
    from langchain_community.document_loaders import AmazonTextractPDFLoader
    loader=AmazonTextractPDFLoader("example_data/alejandro_rosalez_sample-small.jpeg")
    documents = loader.load()
    ```
    One feature is the linearization of the output.
    When using the features LAYOUT, FORMS or TABLES together with Textract
    ```python
    from langchain_community.document_loaders import AmazonTextractPDFLoader
    # you can mix and match each of the features
    loader=AmazonTextractPDFLoader(
        "example_data/alejandro_rosalez_sample-small.jpeg",
        textract_features=["TABLES", "LAYOUT"])
    documents = loader.load()
    ```
    it will generate output that formats the text in reading order and
    try to output the information in a tabular structure or
    output the key/value pairs with a colon (key: value).
    This helps most LLMs to achieve better accuracy when
    processing these texts.
    """
[docs]    def __init__(
        self,
        textract_features: Optional[Sequence[int]] = None,
        client: Optional[Any] = None,
    ) -> None:
        """Initializes the parser.
        Args:
            textract_features: Features to be used for extraction, each feature
                               should be passed as an int that conforms to the enum
                               `Textract_Features`, see `amazon-textract-caller` pkg
            client: boto3 textract client
        """
        try:
            import textractcaller as tc
            import textractor.entities.document as textractor