NumpyOps: Better type-casting in asarray (#656)

* `NumpyOps`: Better type-casting in `asarray` * Simplify `dtype` check * Update thinc/backends/numpy_ops.pyx Co-authored-by: Adriane Boyd <[email protected]> * Simplify casting further, avoid copies if possible * Remove no-op Co-authored-by: Adriane Boyd <[email protected]>
explosion · May 17, 2022 · d2d7917 · d2d7917
1 parent abbe0ff
commit d2d7917
Showing 1 changed file with 10 additions and 9 deletions.
diff --git a/thinc/backends/numpy_ops.pyx b/thinc/backends/numpy_ops.pyx
@@ -66,19 +66,20 @@ class NumpyOps(Ops):
 
  def asarray(self, data, dtype=None):
  if isinstance(data, self.xp.ndarray):
- if dtype is not None:
- return self.xp.asarray(data, dtype=dtype)
- else:
- return self.xp.asarray(data)
+ array = data
  elif hasattr(data, 'numpy'):
  # Handles PyTorch Tensor
- return data.numpy()
+ array = data.numpy()
  elif hasattr(data, "get"):
- return data.get()
- elif dtype is not None:
- return self.xp.array(data, dtype=dtype)
+ array = data.get()
  else:
- return self.xp.array(data)
+ array = self.xp.array(data)
+
+ if dtype is not None:
+ array = array.astype(dtype=dtype, copy=False)
+
+ return array
+
 
  def alloc(self, shape: Shape, *, dtype: Optional[DTypes] = "float32", zeros: bool = True) -> ArrayXd:
  if zeros: