remove device set

Signed-off-by: Yiheng Wang <[email protected]>

Author: yiheng-wang-nv

monai/data/meta_tensor.py

@@ -537,7 +537,6 @@ def ensure_torch_and_prune_meta(
         simple_keys: bool = False,
         pattern: str | None = None,
         sep: str = ".",
-        device: None | str | torch.device = None,
     ):
         """
         Convert the image to MetaTensor (when meta is not None). If `affine` is in the `meta` dictionary,
@@ -552,15 +551,12 @@ def ensure_torch_and_prune_meta(
             sep: combined with `pattern`, used to match and delete keys in the metadata (nested dictionary).
                 default is ".", see also :py:class:`monai.transforms.DeleteItemsd`.
                 e.g. ``pattern=".*_code$", sep=" "`` removes any meta keys that ends with ``"_code"``.
-            device: target device to put the Tensor data.
 
         Returns:
             By default, a `MetaTensor` is returned.
             However, if `get_track_meta()` is `False` or meta=None, a `torch.Tensor` is returned.
         """
-        img = convert_to_tensor(
-            im, track_meta=get_track_meta() and meta is not None, device=device
-        )  # potentially ascontiguousarray
+        img = convert_to_tensor(im, track_meta=get_track_meta() and meta is not None)  # potentially ascontiguousarray
         # if not tracking metadata, return `torch.Tensor`
         if not isinstance(img, MetaTensor):
             return img
@@ -572,7 +568,7 @@ def ensure_torch_and_prune_meta(
         if simple_keys:
             # ensure affine is of type `torch.Tensor`
             if MetaKeys.AFFINE in meta:
-                meta[MetaKeys.AFFINE] = convert_to_tensor(meta[MetaKeys.AFFINE], device=device)  # bc-breaking
+                meta[MetaKeys.AFFINE] = convert_to_tensor(meta[MetaKeys.AFFINE])  # bc-breaking
             remove_extra_metadata(meta)  # bc-breaking
 
         if pattern is not None:

monai/transforms/io/array.py

@@ -164,7 +164,6 @@ def __init__(
                 e.g. ``prune_meta_pattern=".*_code$", prune_meta_sep=" "`` removes meta keys that ends with ``"_code"``.
             expanduser: if True cast filename to Path and call .expanduser on it, otherwise keep filename as is.
             args: additional parameters for reader if providing a reader name.
-            device: target device to put the loaded image.
             kwargs: additional parameters for reader if providing a reader name.
 
         Note:
@@ -186,7 +185,6 @@ def __init__(
         self.pattern = prune_meta_pattern
         self.sep = prune_meta_sep
         self.expanduser = expanduser
-        self.device = device
 
         self.readers: list[ImageReader] = []
         for r in SUPPORTED_READERS:  # set predefined readers as default
@@ -291,15 +289,15 @@ def __call__(self, filename: Sequence[PathLike] | PathLike, reader: ImageReader
             )
         img_array: NdarrayOrTensor
         img_array, meta_data = reader.get_data(img)
-        img_array = convert_to_dst_type(img_array, dst=img_array, dtype=self.dtype, device=self.device)[0]
+        img_array = convert_to_dst_type(img_array, dst=img_array, dtype=self.dtype)[0]
         if not isinstance(meta_data, dict):
             raise ValueError(f"`meta_data` must be a dict, got type {type(meta_data)}.")
         # make sure all elements in metadata are little endian
         meta_data = switch_endianness(meta_data, "<")
 
         meta_data[Key.FILENAME_OR_OBJ] = f"{ensure_tuple(filename)[0]}"  # Path obj should be strings for data loader
         img = MetaTensor.ensure_torch_and_prune_meta(
-            img_array, meta_data, self.simple_keys, pattern=self.pattern, sep=self.sep, device=self.device
+            img_array, meta_data, self.simple_keys, pattern=self.pattern, sep=self.sep
         )
         if self.ensure_channel_first:
             img = EnsureChannelFirst()(img)