feat: Introduce support for GPU Accelerators (#593)

* Upgraded Layout Postprocessing, sending old code back to ERZ

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Implement hierachical cluster layout processing

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Pass nested cluster processing through full pipeline

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Pass nested clusters through GLM as payload

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Move to_docling_document from ds-glm to this repo

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Clean up imports again

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* feat(Accelerator): Introduce options to control the num_threads and device from API, envvars, CLI.
- Introduce the AcceleratorOptions, AcceleratorDevice and use them to set the device where the models run.
- Introduce the accelerator_utils with function to decide the device and resolve the AUTO setting.
- Refactor the way how the docling-ibm-models are called to match the new init signature of models.
- Translate the accelerator options to the specific inputs for third-party models.
- Extend the docling CLI with parameters to set the num_threads and device.
- Add new unit tests.
- Write new example how to use the accelerator options.

* fix: Improve the pydantic objects in the pipeline_options and imports.

Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>

* fix: TableStructureModel: Refactor the artifacts path to use the new structure for fast/accurate model

Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>

* Updated test ground-truth

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Updated test ground-truth (again), bugfix for empty layout

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* fix: Do proper check to set the device in EasyOCR, RapidOCR.

Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>

* Rollback changes from main

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Update test gt

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Remove unused debug settings

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Review fixes

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Nail the accelerator defaults for MPS

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

---------

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>
Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>
Co-authored-by: Christoph Auer <cau@zurich.ibm.com>
Co-authored-by: Christoph Auer <60343111+cau-git@users.noreply.github.com>

docling/utils/accelerator_utils.py

@@ -0,0 +1,42 @@
+import logging
+
+import torch
+
+from docling.datamodel.pipeline_options import AcceleratorDevice
+
+_log = logging.getLogger(__name__)
+
+
+def decide_device(accelerator_device: AcceleratorDevice) -> str:
+    r"""
+    Resolve the device based on the acceleration options and the available devices in the system
+    Rules:
+    1. AUTO: Check for the best available device on the system.
+    2. User-defined: Check if the device actually exists, otherwise fall-back to CPU
+    """
+    cuda_index = 0
+    device = "cpu"
+
+    has_cuda = torch.backends.cuda.is_built() and torch.cuda.is_available()
+    has_mps = torch.backends.mps.is_built() and torch.backends.mps.is_available()
+
+    if accelerator_device == AcceleratorDevice.AUTO:
+        if has_cuda:
+            device = f"cuda:{cuda_index}"
+        elif has_mps:
+            device = "mps"
+
+    else:
+        if accelerator_device == AcceleratorDevice.CUDA:
+            if has_cuda:
+                device = f"cuda:{cuda_index}"
+            else:
+                _log.warning("CUDA is not available in the system. Fall back to 'CPU'")
+        elif accelerator_device == AcceleratorDevice.MPS:
+            if has_mps:
+                device = "mps"
+            else:
+                _log.warning("MPS is not available in the system. Fall back to 'CPU'")
+
+    _log.info("Accelerator device: '%s'", device)
+    return device