API: remove ndarray.base

Base is tracked via `self._tensor._base`. Use `a.get()._base is b.get()` instead
of numpy's `a.base is b`.

Author: ev-br

torch_np/_dtypes.py

@@ -51,7 +51,6 @@ def __new__(self, value):
         #
         return _ndarray.ndarray(tensor)
 
-
 ##### these are abstract types
 
 

torch_np/_helpers.py

@@ -86,7 +86,6 @@ def result_or_out(result_tensor, out_array=None, promote_scalar=False):
 
 def array_from(tensor, base=None):
     from ._ndarray import ndarray
-
     return ndarray(tensor)
 
 

torch_np/_ndarray.py

@@ -93,6 +93,7 @@ def strides(self):
     def itemsize(self):
         return self.tensor.element_size()
 
+
     @property
     def flags(self):
         # Note contiguous in torch is assumed C-style
@@ -423,6 +424,7 @@ def array(obj, dtype=None, *, copy=True, order="K", subok=False, ndmin=0, like=N
     if isinstance(obj, ndarray):
         obj = obj.tensor
 
+
     # is a specific dtype requrested?
     torch_dtype = None
     if dtype is not None:
@@ -432,6 +434,7 @@ def array(obj, dtype=None, *, copy=True, order="K", subok=False, ndmin=0, like=N
     return ndarray(tensor)
 
 
+
 def asarray(a, dtype=None, order=None, *, like=None):
     if order is None:
         order = "K"