Const pad support to pad2d and slice (#1392)

* slice to pad2d migrate

* Gain line

* Mypy happy

* Mypy happy

* Revert

* whitespace

tinygrad/tensor.py

@@ -251,10 +251,10 @@ class Tensor:
   # ***** movement hlops *****
 
   # NOTE: using slice is discouraged and things should migrate to pad and shrink
-  def slice(self, arg:Sequence[Optional[Tuple[int, int]]]) -> Tensor:
+  def slice(self, arg:Sequence[Optional[Tuple[int, int]]], value:float=0) -> Tensor:
     arg_ = tuple([a if a is not None else (0,s) for s,a in zip(self.shape, arg)])
     padding = tuple([(max(0, -p[0]), max(0, p[1]-self.shape[i])) for i,p in enumerate(arg_)])
-    return self.pad(padding).shrink(tuple([(p[0] + padding[i][0], p[1] + padding[i][0]) for i,p in enumerate(arg_)]))
+    return self.pad(padding, value=value).shrink(tuple([(p[0] + padding[i][0], p[1] + padding[i][0]) for i,p in enumerate(arg_)]))
 
   # - Negative indices are taken relative to the end of the sequence, so X[-2] returns the 2nd-to-last element
   # - A slice i:j returns the elements with indices in [i, j)
@@ -377,9 +377,9 @@ class Tensor:
     return self.reshape(self.shape[:dim] + (1,) + self.shape[dim:])
 
   # (padding_left, padding_right, padding_top, padding_bottom)
-  def pad2d(self, padding:Union[List[int], Tuple[int, ...]]):
+  def pad2d(self, padding:Union[List[int], Tuple[int, ...]], value:float=0):
     slc = [(-p0, s+p1) for p0,p1,s in zip(padding[::2], padding[1::2], self.shape[::-1])][::-1]
-    return self.slice([(0,s) for s in self.shape[:-(len(padding)//2)]] + slc)
+    return self.slice([(0,s) for s in self.shape[:-(len(padding)//2)]] + slc, value=value)
 
   @property
   def T(self) -> Tensor: return self.transpose()