Replace hf_hub_download with wrapper

Author: qued

unstructured_inference/models/chipper.py

@@ -9,7 +9,6 @@
 import torch
 import transformers
 from cv2.typing import MatLike
-from huggingface_hub import hf_hub_download
 from PIL.Image import Image
 from transformers import DonutProcessor, VisionEncoderDecoderModel
 from transformers.generation.logits_process import LogitsProcessor
@@ -22,7 +21,7 @@
 from unstructured_inference.models.unstructuredmodel import (
     UnstructuredElementExtractionModel,
 )
-from unstructured_inference.utils import LazyDict, strip_tags
+from unstructured_inference.utils import LazyDict, strip_tags, download_if_needed_and_get_local_path
 
 MODEL_TYPES: Dict[str, Union[LazyDict, dict]] = {
     "chipperv1": {
@@ -115,7 +114,7 @@ def initialize(
             token=auth_token,
         )
         if swap_head:
-            lm_head_file = hf_hub_download(
+            lm_head_file = download_if_needed_and_get_local_path(
                 repo_id=pre_trained_model_repo,
                 filename="lm_head.pth",
                 token=auth_token,

unstructured_inference/models/detectron2.py

@@ -3,7 +3,6 @@
 from pathlib import Path
 from typing import Any, Dict, Final, List, Optional, Union
 
-from huggingface_hub import hf_hub_download
 from layoutparser.models.detectron2.layoutmodel import (
     Detectron2LayoutModel,
     is_detectron2_available,
@@ -17,7 +16,11 @@
 from unstructured_inference.models.unstructuredmodel import (
     UnstructuredObjectDetectionModel,
 )
-from unstructured_inference.utils import LazyDict, LazyEvaluateInfo
+from unstructured_inference.utils import (
+    LazyDict,
+    LazyEvaluateInfo,
+    download_if_needed_and_get_local_path,
+)
 
 DETECTRON_CONFIG: Final = "lp://PubLayNet/faster_rcnn_R_50_FPN_3x/config"
 DEFAULT_LABEL_MAP: Final[Dict[int, str]] = {
@@ -35,12 +38,12 @@
 MODEL_TYPES = {
     "detectron2_lp": LazyDict(
         model_path=LazyEvaluateInfo(
-            hf_hub_download,
+            download_if_needed_and_get_local_path,
             "layoutparser/detectron2",
             "PubLayNet/faster_rcnn_R_50_FPN_3x/model_final.pth",
         ),
         config_path=LazyEvaluateInfo(
-            hf_hub_download,
+            download_if_needed_and_get_local_path,
             "layoutparser/detectron2",
             "PubLayNet/faster_rcnn_R_50_FPN_3x/config.yml",
         ),
@@ -49,12 +52,12 @@
     ),
     "checkbox": LazyDict(
         model_path=LazyEvaluateInfo(
-            hf_hub_download,
+            download_if_needed_and_get_local_path,
             "unstructuredio/oer-checkbox",
             "detectron2_finetuned_oer_checkbox.pth",
         ),
         config_path=LazyEvaluateInfo(
-            hf_hub_download,
+            download_if_needed_and_get_local_path,
             "unstructuredio/oer-checkbox",
             "detectron2_oer_checkbox.json",
         ),

unstructured_inference/models/detectron2onnx.py

@@ -4,7 +4,6 @@
 import cv2
 import numpy as np
 import onnxruntime
-from huggingface_hub import hf_hub_download
 from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE
 from onnxruntime.capi import _pybind_state as C
 from onnxruntime.quantization import QuantType, quantize_dynamic
@@ -16,7 +15,11 @@
 from unstructured_inference.models.unstructuredmodel import (
     UnstructuredObjectDetectionModel,
 )
-from unstructured_inference.utils import LazyDict, LazyEvaluateInfo
+from unstructured_inference.utils import (
+    LazyDict,
+    LazyEvaluateInfo,
+    download_if_needed_and_get_local_path,
+)
 
 onnxruntime.set_default_logger_severity(logger_onnx.getEffectiveLevel())
 
@@ -34,7 +37,7 @@
 MODEL_TYPES: Dict[str, Union[LazyDict, dict]] = {
     "detectron2_onnx": LazyDict(
         model_path=LazyEvaluateInfo(
-            hf_hub_download,
+            download_if_needed_and_get_local_path,
             "unstructuredio/detectron2_faster_rcnn_R_50_FPN_3x",
             "model.onnx",
         ),
@@ -52,7 +55,7 @@
     },
     "detectron2_mask_rcnn": LazyDict(
         model_path=LazyEvaluateInfo(
-            hf_hub_download,
+            download_if_needed_and_get_local_path,
             "unstructuredio/detectron2_mask_rcnn_X_101_32x8d_FPN_3x",
             "model.onnx",
         ),

unstructured_inference/models/yolox.py

@@ -8,14 +8,17 @@
 import cv2
 import numpy as np
 import onnxruntime
-from huggingface_hub import hf_hub_download
 from onnxruntime.capi import _pybind_state as C
 from PIL import Image as PILImage
 
 from unstructured_inference.constants import ElementType, Source
 from unstructured_inference.inference.layoutelement import LayoutElement
 from unstructured_inference.models.unstructuredmodel import UnstructuredObjectDetectionModel
-from unstructured_inference.utils import LazyDict, LazyEvaluateInfo
+from unstructured_inference.utils import (
+    LazyDict,
+    LazyEvaluateInfo,
+    download_if_needed_and_get_local_path,
+)
 
 YOLOX_LABEL_MAP = {
     0: ElementType.CAPTION,
@@ -34,23 +37,23 @@
 MODEL_TYPES = {
     "yolox": LazyDict(
         model_path=LazyEvaluateInfo(
-            hf_hub_download,
+            download_if_needed_and_get_local_path,
             "unstructuredio/yolo_x_layout",
             "yolox_l0.05.onnx",
         ),
         label_map=YOLOX_LABEL_MAP,
     ),
     "yolox_tiny": LazyDict(
         model_path=LazyEvaluateInfo(
-            hf_hub_download,
+            download_if_needed_and_get_local_path,
             "unstructuredio/yolo_x_layout",
             "yolox_tiny.onnx",
         ),
         label_map=YOLOX_LABEL_MAP,
     ),
     "yolox_quantized": LazyDict(
         model_path=LazyEvaluateInfo(
-            hf_hub_download,
+            download_if_needed_and_get_local_path,
             "unstructuredio/yolo_x_layout",
             "yolox_l0.05_quantized.onnx",
         ),