refactor: refactor unnecessary else / elif when if block has a return statement

hsf/augmentation.py

@@ -62,5 +62,4 @@ def get_augmented_subject(subject: tio.Subject, augmentation_cfg: DictConfig,
         subjects.append(subject)
 
         return subjects
-    else:
-        return [subject]
+    return [subject]

hsf/engines.py

@@ -30,15 +30,14 @@ def deepsparse_support() -> str:
     if vnni:
         # Optimal for int8 quantized NN
         return "full"
-    elif avx512:
+    if avx512:
         # AVX512 vector instruction set for fast NN inference
         return "partial"
-    elif avx2:
+    if avx2:
         # AVX2 vector instruction set slower than AVX512
         return "minimal"
-    else:
-        # No AVX2/512 or VNNI -> Risk of slow inference time
-        return "not supported"
+    # No AVX2/512 or VNNI -> Risk of slow inference time
+    return "not supported"
 
 
 def print_deepsparse_support():
@@ -107,7 +106,7 @@ def __call__(self, x):
             assert len(feed_names) == 1, "Only one input is supported"
             return self.engine.run(None, {feed_names[0]: x})
 
-        elif self.engine_name == "deepsparse":
+        if self.engine_name == "deepsparse":
             return self.engine.run([x])
 
     def set_deepsparse_engine(self, model: PosixPath):
@@ -133,7 +132,7 @@ def set_ort_engine(self, model):
         def _correct_provider(provider):
             if isinstance(provider, str):
                 return provider
-            elif isinstance(provider, ListConfig):
+            if isinstance(provider, ListConfig):
                 provider = list(provider)
                 assert len(provider) == 2
                 provider[1] = dict(provider[1])

hsf/fetch_models.py

@@ -50,9 +50,8 @@ def fetch(directory: str, filename: str, url: str, xxh3_64: str) -> None:
         if get_hash(str(outfile)) == xxh3_64:
             log.info(f"{filename} already exists and is up to date")
             return
-        else:
-            log.info(f"{filename} already exists but is not up to date")
-            outfile.unlink()
+        log.info(f"{filename} already exists but is not up to date")
+        outfile.unlink()
 
     log.info(f"Fetching {url}")
     wget.download(url, out=str(outfile))

hsf/multispectrality.py

@@ -38,8 +38,7 @@ def get_second_contrast(mri: PosixPath, pattern: str) -> Optional[PosixPath]:
         ) == 1, f"Invalid file pattern: {pattern}. No or multiple files found."
 
         return second_contrast[0]
-    else:
-        return None
+    return None
 
 
 @handle_cache
@@ -61,33 +60,32 @@ def register(mri: PosixPath,
     """
     if cfg.multispectrality.same_space:
         return second_contrast
-    else:
-        registration_params = dict(cfg.multispectrality.registration)
-        if not registration_params.get("outprefix"):
-            registration_params["outprefix"] = outprefix
+    registration_params = dict(cfg.multispectrality.registration)
+    if not registration_params.get("outprefix"):
+        registration_params["outprefix"] = outprefix
 
-        fixed = ants.image_read(str(mri))
-        moving = ants.image_read(str(second_contrast))
+    fixed = ants.image_read(str(mri))
+    moving = ants.image_read(str(second_contrast))
 
-        log.info(f"Registering {str(second_contrast)} to {str(mri)}")
-        transformation = ants.registration(fixed=fixed,
-                                           moving=moving,
-                                           **registration_params)
+    log.info(f"Registering {str(second_contrast)} to {str(mri)}")
+    transformation = ants.registration(fixed=fixed,
+                                       moving=moving,
+                                       **registration_params)
 
-        registered = ants.apply_transforms(
-            fixed=fixed,
-            moving=moving,
-            transformlist=transformation["fwdtransforms"])
+    registered = ants.apply_transforms(
+        fixed=fixed,
+        moving=moving,
+        transformlist=transformation["fwdtransforms"])
 
-        extensions = "".join(second_contrast.suffixes)
-        fname = second_contrast.name.replace(extensions,
-                                             "") + "_registered.nii.gz"
-        output_dir = mri.parent / cfg.files.output_dir
-        output_dir.mkdir(parents=True, exist_ok=True)
+    extensions = "".join(second_contrast.suffixes)
+    fname = second_contrast.name.replace(extensions,
+                                         "") + "_registered.nii.gz"
+    output_dir = mri.parent / cfg.files.output_dir
+    output_dir.mkdir(parents=True, exist_ok=True)
 
-        ants.image_write(registered, str(output_dir / fname))
+    ants.image_write(registered, str(output_dir / fname))
 
-        return output_dir / fname
+    return output_dir / fname
 
 
 def get_additional_hippocampi(mri: PosixPath, second_contrast: PosixPath,

hsf/segment.py

@@ -53,17 +53,17 @@ def to_ca_mode(logits: torch.Tensor, ca_mode: str = "1/2/3") -> torch.Tensor:
         _in = torch.sum(logits[:, 1:, :, :, :], dim=1, keepdim=True)
 
         return torch.cat([_pre, _in], dim=1)
-    elif ca_mode == "1/2/3":
+    if ca_mode == "1/2/3":
         # identity
         return logits
-    elif ca_mode == "1/23":
+    if ca_mode == "1/23":
         # ca1; ca2+ca3
         _pre = logits[:, :3, :, :, :]
         _in = logits[:, 3:4, :, :, :] + logits[:, 4:5, :, :, :]
         _post = logits[:, 5:, :, :, :]
 
         return torch.cat([_pre, _in, _post], dim=1)
-    elif ca_mode == "123":
+    if ca_mode == "123":
         # ca1+ca2+ca3
         _pre = logits[:, :2, :, :, :]
         _in = logits[:,
@@ -73,10 +73,9 @@ def to_ca_mode(logits: torch.Tensor, ca_mode: str = "1/2/3") -> torch.Tensor:
         _post = logits[:, 5:, :, :, :]
 
         return torch.cat([_pre, _in, _post], dim=1)
-    else:
-        raise ValueError(
-            f"Unknown `ca_mode` ({ca_mode}). `ca_mode` must be 1/2/3, 1/23 or 123"
-        )
+    raise ValueError(
+        f"Unknown `ca_mode` ({ca_mode}). `ca_mode` must be 1/2/3, 1/23 or 123"
+    )
 
 
 def predict(mris: list,