fix markdown

Author: AntoineSimoulin

torchvision/transforms/v2/_type_conversion.py

@@ -96,7 +96,7 @@ def transform(self, inpt: Any, params: dict[str, Any]) -> torch.Tensor:
 
 
 class ToCVCUDATensor(Transform):
-    """Convert a `torch.Tensor` with NCHW layout to a `cvcuda.Tensor` with NHWC layout.
+    """Convert a ``torch.Tensor`` with NCHW layout to a ``cvcuda.Tensor`` with NHWC layout.
     If the input tensor is on CPU, it will automatically be transferred to GPU.
     Only 1-channel and 3-channel images are supported.
 
@@ -116,7 +116,7 @@ def transform(self, inpt: torch.Tensor, params: dict[str, Any]) -> "cvcuda.Tenso
 
 
 class CVCUDAToTensor(Transform):
-    """Convert a `cvcuda.Tensor` with NHWC layout to a `torch.Tensor` with NCHW layout.
+    """Convert a ``cvcuda.Tensor`` with NHWC layout to a ``torch.Tensor`` with NCHW layout.
 
     This function does not support torchscript.
 

torchvision/transforms/v2/functional/_type_conversion.py

@@ -35,12 +35,12 @@ def to_image(inpt: Union[torch.Tensor, PIL.Image.Image, np.ndarray]) -> tv_tenso
 
 @torch.jit.unused
 def to_cvcuda_tensor(inpt: torch.Tensor) -> "cvcuda.Tensor":
-    """See :class:`~torchvision.transforms.v2.ToCVCUDATensor` for details."""
+    """See :class:``~torchvision.transforms.v2.ToCVCUDATensor`` for details."""
     cvcuda = _import_cvcuda()
     if not torch.jit.is_scripting() and not torch.jit.is_tracing():
         _log_api_usage_once(to_cvcuda_tensor)
     if not isinstance(inpt, torch.Tensor):
-        raise TypeError(f"inpt should be `torch.Tensor`. Got {type(inpt)}.")
+        raise TypeError(f"inpt should be ``torch.Tensor``. Got {type(inpt)}.")
     if inpt.ndim != 4:
         raise ValueError(f"pic should be 4 dimensional. Got {inpt.ndim} dimensions.")
     # Convert to NHWC as CVCUDA transforms do not support NCHW
@@ -50,12 +50,12 @@ def to_cvcuda_tensor(inpt: torch.Tensor) -> "cvcuda.Tensor":
 
 @torch.jit.unused
 def cvcuda_to_tensor(cvcuda_img: "cvcuda.Tensor") -> torch.Tensor:
-    """See :class:`~torchvision.transforms.v2.CVCUDAToTensor` for details."""
+    """See :class:``~torchvision.transforms.v2.CVCUDAToTensor`` for details."""
     cvcuda = _import_cvcuda()
     if not torch.jit.is_scripting() and not torch.jit.is_tracing():
         _log_api_usage_once(cvcuda_to_tensor)
     if not isinstance(cvcuda_img, cvcuda.Tensor):
-        raise TypeError(f"cvcuda_img should be `cvcuda.Tensor`. Got {type(cvcuda_img)}.")
+        raise TypeError(f"cvcuda_img should be ``cvcuda.Tensor``. Got {type(cvcuda_img)}.")
     cuda_tensor = torch.as_tensor(cvcuda_img.cuda(), device="cuda")
     if cvcuda_img.ndim != 4:
         raise ValueError(f"Image should be 4 dimensional. Got {cuda_tensor.ndim} dimensions.")