don't view origin buffer when sharding (#5122)

* make buffer view optional with a flag

* do not view when sharding to save memory

test/test_multitensor.py

@@ -542,6 +542,12 @@ class TestMultiTensor(unittest.TestCase):
         assert ast.src[0].src[0].op is BufferOps.LOAD
         assert ast.src[0].src[1].op is BufferOps.CONST and ast.src[0].src[1].arg.val == 3
 
+  def test_shard_memory(self):
+    devices = (d0, d1, d2, d3)
+    t = Tensor.zeros(16, 16).contiguous()
+    t.shard_(devices, axis=0)
+    assert all([lb is lb.base and lb.buffer.base.size == 4 * 16 for lb in t.lazydata.lbs])
+
 @unittest.skipIf(CI and Device.DEFAULT in ("GPU", "CUDA", "METAL"), "no GPU CI")
 class TestHandleData(unittest.TestCase):
   def test_copied_to_device(self):

tinygrad/multi.py

@@ -73,7 +73,7 @@ class MultiLazyBuffer:
   def from_sharded(lb:LazyBuffer, devices:Tuple[str, ...], axis:Optional[int]=None):
     lbs = [lb.contiguous() if lb.base != lb and not lb.is_unrealized_unmasked_const() else lb] * len(devices)
     sharded_lbs = [lb.copy_to_device(d) for lb,d in zip(to_sharded(lbs, axis) if axis is not None else lbs, devices)]
-    return MultiLazyBuffer([lb if lb.is_unrealized_unmasked_const() else lb.contiguous() for lb in sharded_lbs], axis)
+    return MultiLazyBuffer([lb if lb.is_unrealized_unmasked_const() else lb.contiguous(allow_buffer_view=False) for lb in sharded_lbs], axis)
 
   def copy_to_device(self, device:str) -> LazyBuffer:
     if self.axis is None: