Refa: PARALLEL_DEVICES is a static parameter. (#6168)

### What problem does this PR solve?


### Type of change

- [x] Refactoring

deepdoc/parser/pdf_parser.py

@@ -37,13 +37,15 @@ from rag.nlp import rag_tokenizer
 from copy import deepcopy
 from huggingface_hub import snapshot_download
 
+from rag.settings import PARALLEL_DEVICES
+
 LOCK_KEY_pdfplumber = "global_shared_lock_pdfplumber"
 if LOCK_KEY_pdfplumber not in sys.modules:
     sys.modules[LOCK_KEY_pdfplumber] = threading.Lock()
 
 
 class RAGFlowPdfParser:
-    def __init__(self, parallel_devices: int | None = None):
+    def __init__(self):
         """
         If you have trouble downloading HuggingFace models, -_^ this might help!!
 
@@ -56,11 +58,10 @@ class RAGFlowPdfParser:
 
         """
         
-        self.ocr = OCR(parallel_devices = parallel_devices)
-        self.parallel_devices = parallel_devices
+        self.ocr = OCR()
         self.parallel_limiter = None
-        if parallel_devices is not None and parallel_devices > 1:
-            self.parallel_limiter = [trio.CapacityLimiter(1) for _ in range(parallel_devices)]
+        if PARALLEL_DEVICES is not None and PARALLEL_DEVICES > 1:
+            self.parallel_limiter = [trio.CapacityLimiter(1) for _ in range(PARALLEL_DEVICES)]
         
         if hasattr(self, "model_speciess"):
             self.layouter = LayoutRecognizer("layout." + self.model_speciess)
@@ -1018,7 +1019,6 @@ class RAGFlowPdfParser:
             self.pdf.close()
         if not self.outlines:
             logging.warning("Miss outlines")
-        
 
         logging.debug("Images converted.")
         self.is_english = [re.search(r"[a-zA-Z0-9,/¸;:'\[\]\(\)!@#$%^&*\"?<>._-]{30,}", "".join(
@@ -1066,8 +1066,8 @@ class RAGFlowPdfParser:
                     for i, img in enumerate(self.page_images):
                         chars = __ocr_preprocess()
 
-                        nursery.start_soon(__img_ocr, i, i % self.parallel_devices, img, chars,
-                                        self.parallel_limiter[i % self.parallel_devices])
+                        nursery.start_soon(__img_ocr, i, i % PARALLEL_DEVICES, img, chars,
+                                        self.parallel_limiter[i % PARALLEL_DEVICES])
                         await trio.sleep(0.1)
             else:
                 for i, img in enumerate(self.page_images):

deepdoc/vision/ocr.py

@@ -22,6 +22,7 @@ import os
 from huggingface_hub import snapshot_download
 
 from api.utils.file_utils import get_project_base_directory
+from rag.settings import PARALLEL_DEVICES
 from .operators import *  # noqa: F403
 from . import operators
 import math
@@ -509,7 +510,7 @@ class TextDetector:
 
 
 class OCR:
-    def __init__(self, model_dir=None, parallel_devices: int | None = None):
+    def __init__(self, model_dir=None):
         """
         If you have trouble downloading HuggingFace models, -_^ this might help!!
 
@@ -528,10 +529,10 @@ class OCR:
                         "rag/res/deepdoc")
                 
                 # Append muti-gpus task to the list
-                if parallel_devices is not None and parallel_devices > 0:
+                if PARALLEL_DEVICES is not None and PARALLEL_DEVICES > 0:
                     self.text_detector = []
                     self.text_recognizer = []
-                    for device_id in range(parallel_devices):
+                    for device_id in range(PARALLEL_DEVICES):
                         self.text_detector.append(TextDetector(model_dir, device_id))
                         self.text_recognizer.append(TextRecognizer(model_dir, device_id))
                 else:
@@ -543,11 +544,11 @@ class OCR:
                                               local_dir=os.path.join(get_project_base_directory(), "rag/res/deepdoc"),
                                               local_dir_use_symlinks=False)
                 
-                if parallel_devices is not None:
-                    assert parallel_devices > 0 , "Number of devices must be >= 1"
+                if PARALLEL_DEVICES is not None:
+                    assert PARALLEL_DEVICES > 0, "Number of devices must be >= 1"
                     self.text_detector = []
                     self.text_recognizer = []
-                    for device_id in range(parallel_devices):
+                    for device_id in range(PARALLEL_DEVICES):
                         self.text_detector.append(TextDetector(model_dir, device_id))
                         self.text_recognizer.append(TextRecognizer(model_dir, device_id))
                 else:

deepdoc/vision/t_ocr.py

@@ -34,15 +34,15 @@ import trio
 os.environ['CUDA_VISIBLE_DEVICES'] = '0' #1 gpu
 # os.environ['CUDA_VISIBLE_DEVICES'] = '' #cpu
 
+
 def main(args):
     import torch.cuda
 
     cuda_devices = torch.cuda.device_count()
     limiter = [trio.CapacityLimiter(1) for _ in range(cuda_devices)] if cuda_devices > 1 else None
-    ocr = OCR(parallel_devices = cuda_devices)
+    ocr = OCR()
     images, outputs = init_in_out(args)
 
-
     def __ocr(i, id, img):
         print("Task {} start".format(i))
         bxs = ocr(np.array(img), id)