minor doc update

docs/source/using_doctr/using_model_export.rst

@@ -57,7 +57,7 @@ Compiling your models (PyTorch only)
 
 **NOTE:**
 
-- This feature is only available for PyTorch models.
+- This feature is only available if you use PyTorch as backend.
 - The recognition architecture `master` is not supported for model compilation yet.
 - We provide only official support for the default (`inductor`) backend, but you can try other backends, configurations depending on your hardware and requirements as well.
 
@@ -125,7 +125,7 @@ It defines a common format for representing models, including the network struct
             dummy_input = torch.rand((batch_size, input_shape), dtype=torch.float32)
             model_path = export_model_to_onnx(
                 model,
-                model_name="vitstr.onnx,
+                model_name="vitstr.onnx",
                 dummy_input=dummy_input
             )
 

doctr/models/classification/zoo.py

@@ -50,6 +50,7 @@ def _orientation_predictor(
     else:
         allowed_archs = [classification.MobileNetV3]
         if is_torch_available():
+            # Adding the type for torch compiled models to the allowed architectures
             from doctr.models.utils import _CompiledModule
 
             allowed_archs.append(_CompiledModule)

doctr/models/detection/zoo.py

@@ -58,7 +58,7 @@ def _predictor(arch: Any, pretrained: bool, assume_straight_pages: bool = True,
     else:
         allowed_archs = [detection.DBNet, detection.LinkNet, detection.FAST]
         if is_torch_available():
-            # The following is required for torch compiled models
+            # Adding the type for torch compiled models to the allowed architectures
             from doctr.models.utils import _CompiledModule
 
             allowed_archs.append(_CompiledModule)

doctr/models/recognition/zoo.py

@@ -37,7 +37,7 @@ def _predictor(arch: Any, pretrained: bool, **kwargs: Any) -> RecognitionPredict
     else:
         allowed_archs = [recognition.CRNN, recognition.SAR, recognition.MASTER, recognition.ViTSTR, recognition.PARSeq]
         if is_torch_available():
-            # The following is required for torch compiled models
+            # Adding the type for torch compiled models to the allowed architectures
             from doctr.models.utils import _CompiledModule
 
             allowed_archs.append(_CompiledModule)