Fixes in MultiFab setitem (#440)

Previously, `setitem` was only checking for numpy arrays, which was
causing errors on a GPU when a cupy array was passed in. This fix makes
it more flexible, so now lists can also be used for example.

Also, when using GPU, the input value must be converted to a cupy array
before the copy can be done.

A minor cleanup of `_get_field` is also done, simplifying the code.

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: dpgrote

src/amrex/extensions/MultiFab.py

@@ -395,13 +395,7 @@ def _get_field(self, mfi):
     # The transpose is taken since the Python array interface to Array4 in
     # self.array(mfi) is in C ordering.
     # Note: transposing creates a view and not a copy.
-    import inspect
-
-    amr = inspect.getmodule(self)
-    if amr.Config.have_gpu:
-        device_arr = self.array(mfi).to_cupy(copy=False, order="F")
-    else:
-        device_arr = self.array(mfi).to_numpy(copy=False, order="F")
+    device_arr = self.array(mfi).to_xp(copy=False, order="F")
     return device_arr
 
 
@@ -603,15 +597,26 @@ def __setitem__(self, index, value):
     value : scalar or array
         Input value to assign to the specified slice of the MultiFab
     """
+    # When filling an array that is a cupy array, the RHS must also be a cupy array.
+    # This checks if amr was built with GPU, and if so, it must convert the input
+    # value to a cupy array. Otherwise, it will use a numpy array.
+    import inspect
+
+    amr = inspect.getmodule(self)
+    if amr.Config.have_gpu:
+        import cupy as xp
+    else:
+        xp = np
+
     index = _process_index(self, index)
 
-    if isinstance(value, np.ndarray):
+    if not np.isscalar(value):
         # Expand the shape of the input array to match the shape of the global array
         # (it needs to be 4-D).
         # This converts value to an array if needed, and the [...] grabs a view so
         # that the shape change below doesn't affect value.
-        value3d = np.array(value)[...]
-        global_shape = list(value3d.shape)
+        value4d = xp.array(value)[...]
+        global_shape = list(value4d.shape)
         # The shape of 1 is added for the extra dimensions and when index is an integer
         # (in which case the dimension was not in the input array).
         if (index[0].stop - index[0].start) == 1:
@@ -622,15 +627,15 @@ def __setitem__(self, index, value):
             global_shape[2:2] = [1]
         if (index[3].stop - index[3].start) == 1 or len(global_shape) < 4:
             global_shape[3:3] = [1]
-        value3d.shape = global_shape
+        value4d.shape = global_shape
 
     for mfi in self:
         block_slices, global_slices = _get_intersect_slice(self, mfi, index, True)
         if global_slices is not None:
             mf_arr = _get_field(self, mfi)
-            if isinstance(value, np.ndarray):
+            if not np.isscalar(value):
                 # The data is copied from host to device automatically if needed
-                mf_arr[block_slices] = value3d[global_slices]
+                mf_arr[block_slices] = value4d[global_slices]
             else:
                 mf_arr[block_slices] = value