Pipeline: cleanup and improve docs (#443)

* add documentation

* remove parameter binary_output because it was not used

* remove parameter "shuffle" from dataloader_params because it would collide with fixed shuffle=False

src/pytorch_ie/pipeline.py

@@ -37,10 +37,15 @@ class Pipeline:
 
     Pipeline supports running on CPU or GPU through the device argument (see below).
 
-    Some pipeline, like for instance :class:`~transformers.FeatureExtractionPipeline` (:obj:`'feature-extraction'` )
-    output large tensor object as nested-lists. In order to avoid dumping such large structure as textual data we
-    provide the :obj:`binary_output` constructor argument. If set to :obj:`True`, the output will be stored in the
-    pickle format.
+    Args:
+        model (:class:`~pytorch_ie.PyTorchIEModel`):
+            The deep learning model to use for the pipeline.
+        taskmodule (:class:`~pytorch_ie.TaskModule`): The taskmodule to use for encoding
+            and decoding the documents.
+        device (:obj:`Union[int, str]`, `optional`, defaults to :obj:`"cpu"`):
+            The device to run the pipeline on. This can be a CPU device (:obj:`"cpu"`), a GPU
+            device (:obj:`"cuda"`) or a specific GPU device (:obj:`"cuda:X"`, where :obj:`X`
+            is the index of the GPU).
     """
 
     default_input_names = None
@@ -50,15 +55,13 @@ def __init__(
         model: PyTorchIEModel,
         taskmodule: TaskModule,
         device: Union[int, str] = "cpu",
-        binary_output: bool = False,
         **kwargs,
     ):
         self.taskmodule = taskmodule
         device_str = (
             ("cpu" if device < 0 else f"cuda:{device}") if isinstance(device, int) else device
         )
         self.device = torch.device(device_str)
-        self.binary_output = binary_output
 
         # Module.to() returns just self, but moved to the device. This is not correctly
         # reflected in typing of PyTorch.
@@ -192,7 +195,7 @@ def _sanitize_parameters(
                 forward_parameters[p_name] = pipeline_parameters[p_name]
 
         # set dataloader parameters
-        for p_name in ["batch_size", "num_workers", "shuffle"]:
+        for p_name in ["batch_size", "num_workers"]:
             if p_name in pipeline_parameters:
                 dataloader_params[p_name] = pipeline_parameters[p_name]
 
@@ -299,6 +302,38 @@ def __call__(
         *args,
         **kwargs,
     ) -> Union[Document, Sequence[Document]]:
+        """
+        The __call__ method is the entry point for the pipeline. It will run the pipeline workflow in the following
+        order:
+
+                1. Encode the documents
+                2. Run the model forward pass(es) on the encodings
+                3. Combine the model outputs with the inputs encodings and integrate them back into the documents
+
+        Args:
+            documents (:obj:`Union[Document, Sequence[Document]]`): The documents to process. If a single document is
+                passed, the output will be a single document. If a list of documents is passed, the output will be a
+                list of documents.
+            document_batch_size (:obj:`int`, `optional`): The batch size to use for encoding the documents with the
+                taskmodule. If not provided, the default batch size of the taskmodule will be used.
+            show_progress_bar (:obj:`bool`, `optional`, defaults to :obj:`False`): Whether or not to show a progress bar
+                during inference.
+            fast_dev_run (:obj:`bool`, `optional`, defaults to :obj:`False`): Whether or not to run a fast development
+                run. If set to :obj:`True`, only the first two model inputs will be processed.
+            batch_size (:obj:`int`, `optional`, defaults to :obj:`1`): The batch size to use for the dataloader. If not
+                provided, a batch size of 1 will be used.
+            num_workers (:obj:`int`, `optional`, defaults to :obj:`8`): The number of workers to use for the dataloader.
+                If not provided, 8 workers will be used.
+            inplace (:obj:`bool`, `optional`, defaults to :obj:`True`): Whether or not to modify the input documents
+                in place. Requires the input to be a mutable sequence of documents or a single document.
+
+        Note that all the arguments except `documents` can be set in the `__init__` method and/or overridden in the
+        `__call__` method.
+
+        Returns:
+            :obj:`Union[Document, Sequence[Document]]`: The processed documents. If a single document was passed, a
+            single document will be returned. If a list of documents was passed, a list of documents will be returned.
+        """
         if args:
             logger.warning(f"Ignoring args : {args}")
         (