CupyOps: Simplify asarray (explosion#661)

* `CupyOps`: Simplify `asarray`

* Remove `cast_array` flag and use `astype` unconditionally

* Revert unconditional call to `astype`

* Remove no-op

Author: shadeMe

thinc/backends/cupy_ops.py

@@ -72,29 +72,20 @@ def gemm(self, x, y, out=None, trans1=False, trans2=False):
             return out
 
     def asarray(self, data, dtype=None):
-        # This is sort of frustrating, but we can't easily otherwise pass
-        # forward "unset".
-        dtype = {"dtype": dtype} if dtype is not None else {}
-
         # We'll try to perform a zero-copy conversion if possible.
-        array = None
-        cast_array = False
-        if isinstance(data, cupy.ndarray):
-            array = self.xp.asarray(data, **dtype)
-        elif is_torch_array(data) and data.device.type == "cuda":
+        if is_cupy_array(data):
+            array = data
+        elif is_torch_gpu_array(data):
             array = torch2xp(data)
-            cast_array = True
-        elif is_tensorflow_array(data) and "GPU:" in data.device:
+        elif is_tensorflow_gpu_array(data):
             array = tensorflow2xp(data)
-            cast_array = True
-        elif is_mxnet_array(data) and data.context.device_type != "cpu":
+        elif is_mxnet_gpu_array(data):
             array = mxnet2xp(data)
-            cast_array = True
         else:
-            array = self.xp.array(data, **dtype)
+            array = self.xp.array(data)
 
-        if cast_array and dtype != {}:
-            array = array.astype(dtype["dtype"])
+        if dtype is not None:
+            array = array.astype(dtype=dtype, copy=False)
 
         return array