Pass argument in recursive call of convert_to_tensor

Signed-off-by: Eric Kerfoot <[email protected]>

Author: ericspod

monai/utils/type_conversion.py

@@ -158,6 +158,10 @@ def _convert_tensor(tensor: Any, **kwargs: Any) -> Any:
     if safe:
         data = safe_dtype_range(data, dtype)
     dtype = get_equivalent_dtype(dtype, torch.Tensor)
+
+    # common keyword arguments for recursive calls
+    conv_kwargs = dict(dtype=dtype, device=device, track_meta=track_meta, convert_numeric=convert_numeric)
+
     if isinstance(data, torch.Tensor):
         return _convert_tensor(data).to(dtype=dtype, device=device, memory_format=torch.contiguous_format)
     if isinstance(data, np.ndarray):
@@ -172,13 +176,13 @@ def _convert_tensor(tensor: Any, **kwargs: Any) -> Any:
     elif (has_cp and isinstance(data, cp_ndarray)) or (convert_numeric and isinstance(data, (float, int, bool))):
         return _convert_tensor(data, dtype=dtype, device=device)
     elif isinstance(data, list):
-        list_ret = [convert_to_tensor(i, dtype=dtype, device=device, track_meta=track_meta) for i in data]
+        list_ret = [convert_to_tensor(i, **conv_kwargs) for i in data]
         return _convert_tensor(list_ret, dtype=dtype, device=device) if wrap_sequence else list_ret
     elif isinstance(data, tuple):
-        tuple_ret = tuple(convert_to_tensor(i, dtype=dtype, device=device, track_meta=track_meta) for i in data)
+        tuple_ret = tuple(convert_to_tensor(i, **conv_kwargs) for i in data)
         return _convert_tensor(tuple_ret, dtype=dtype, device=device) if wrap_sequence else tuple_ret
     elif isinstance(data, dict):
-        return {k: convert_to_tensor(v, dtype=dtype, device=device, track_meta=track_meta) for k, v in data.items()}
+        return {k: convert_to_tensor(v, **conv_kwargs) for k, v in data.items()}
 
     return data