Revert "export model file name v2"

This reverts commit 37c8306.

Author: alexriedel1

src/anomalib/engine/engine.py

@@ -728,7 +728,6 @@ def export(
         model: AnomalibModule,
         export_type: ExportType | str,
         export_root: str | Path | None = None,
-        model_file_name: str = "model",
         input_size: tuple[int, int] | None = None,
         compression_type: CompressionType | None = None,
         datamodule: AnomalibDataModule | None = None,
@@ -743,8 +742,6 @@ def export(
             export_type (ExportType): Export type.
             export_root (str | Path | None, optional): Path to the output directory. If it is not set, the model is
                 exported to trainer.default_root_dir. Defaults to None.
-            model_file_name (str = "model"): Name of the exported model file. If it is not set, the model is
-                is called "model". Defaults to "model".
             input_size (tuple[int, int] | None, optional): A statis input shape for the model, which is exported to ONNX
                 and OpenVINO format. Defaults to None.
             compression_type (CompressionType | None, optional): Compression type for OpenVINO exporting only.
@@ -801,18 +798,15 @@ def export(
         if export_type == ExportType.TORCH:
             exported_model_path = model.to_torch(
                 export_root=export_root,
-                model_file_name=model_file_name,
             )
         elif export_type == ExportType.ONNX:
             exported_model_path = model.to_onnx(
                 export_root=export_root,
-                model_file_name=model_file_name,
                 input_size=input_size,
             )
         elif export_type == ExportType.OPENVINO:
             exported_model_path = model.to_openvino(
                 export_root=export_root,
-                model_file_name=model_file_name,
                 input_size=input_size,
                 compression_type=compression_type,
                 datamodule=datamodule,

src/anomalib/models/components/base/export_mixin.py

@@ -80,13 +80,11 @@ class ExportMixin:
     def to_torch(
         self,
         export_root: Path | str,
-        model_file_name: str,
     ) -> Path:
         """Export model to PyTorch format.
 
         Args:
             export_root (Path | str): Path to the output folder
-            model_file_name (str): Name of the exported model
 
         Returns:
             Path: Path to the exported PyTorch model (.pt file)
@@ -101,7 +99,7 @@ def to_torch(
             PosixPath('./exports/weights/torch/model.pt')
         """
         export_root = _create_export_root(export_root, ExportType.TORCH)
-        pt_model_path = export_root / (model_file_name + ".pt")
+        pt_model_path = export_root / "model.pt"
         torch.save(
             obj={"model": self},
             f=pt_model_path,
@@ -111,14 +109,12 @@ def to_torch(
     def to_onnx(
         self,
         export_root: Path | str,
-        model_file_name: str,
         input_size: tuple[int, int] | None = None,
     ) -> Path:
         """Export model to ONNX format.
 
         Args:
             export_root (Path | str): Path to the output folder
-            model_file_name (str): Name of the exported model.
             input_size (tuple[int, int] | None): Input image dimensions (height, width).
                 If ``None``, uses dynamic input shape. Defaults to ``None``
 
@@ -147,7 +143,7 @@ def to_onnx(
             if input_size
             else {"input": {0: "batch_size", 2: "height", 3: "weight"}, "output": {0: "batch_size"}}
         )
-        onnx_path = export_root / (model_file_name + ".onnx")
+        onnx_path = export_root / "model.onnx"
         # apply pass through the model to get the output names
         assert isinstance(self, LightningModule)  # mypy
         output_names = [name for name, value in self.eval()(input_shape)._asdict().items() if value is not None]
@@ -166,7 +162,6 @@ def to_onnx(
     def to_openvino(
         self,
         export_root: Path | str,
-        model_file_name: str,
         input_size: tuple[int, int] | None = None,
         compression_type: CompressionType | None = None,
         datamodule: AnomalibDataModule | None = None,
@@ -178,7 +173,6 @@ def to_openvino(
 
         Args:
             export_root (Path | str): Path to the output folder
-            model_file_name (str): Name of the exported model
             input_size (tuple[int, int] | None): Input image dimensions (height, width).
                 If ``None``, uses dynamic input shape. Defaults to ``None``
             compression_type (CompressionType | None): Type of compression to apply.
@@ -224,9 +218,9 @@ def to_openvino(
         import openvino as ov
 
         with TemporaryDirectory() as onnx_directory:
-            model_path = self.to_onnx(onnx_directory, model_file_name, input_size)
+            model_path = self.to_onnx(onnx_directory, input_size)
             export_root = _create_export_root(export_root, ExportType.OPENVINO)
-            ov_model_path = export_root / (model_file_name + ".xml")
+            ov_model_path = export_root / "model.xml"
             ov_args = {} if ov_args is None else ov_args
 
             model = ov.convert_model(model_path, **ov_args)