use Tensor.replace [pr] (#8455)

test/helpers.py

@@ -15,7 +15,7 @@ from tinygrad.runtime.ops_python import PythonProgram, PythonRenderer, PythonCom
 
 def derandomize_model(model):
   for p in get_parameters(model):
-    p.lazydata = Tensor.empty(p.shape, device=p.device, dtype=p.dtype).lazydata
+    p.replace(Tensor.empty(p.shape, device=p.device, dtype=p.dtype))
     p.realize()
 
 def assert_jit_cache_len(fxn, expected_len):

test/imported/test_indexing.py

@@ -1,6 +1,6 @@
 # test cases are modified from pytorch test_indexing.py https://github.com/pytorch/pytorch/blob/597d3fb86a2f3b8d6d8ee067e769624dcca31cdb/test/test_indexing.py
 
-import unittest, random, copy, warnings
+import unittest, random, warnings
 import numpy as np
 
 from tinygrad import Tensor, dtypes, Device, TinyJit
@@ -27,8 +27,8 @@ def set_(reference: Tensor, shape, strides, offset):
   assert strided.lazydata.st.real_strides() == strides, "real_strides should equal strides for strided"
   return strided
 
-def clone(original:Tensor): return copy.copy(original)
-def copy_(src:Tensor, other:Tensor) -> Tensor: return copy.copy(src)
+def clone(original:Tensor): return original.clone()
+def copy_(src:Tensor, other:Tensor) -> Tensor: return src.clone()
 # this is fine for tested usecases since as geohotstan understands,
 # data_ptr is used to compare if operations needed between tensors is the same
 def data_ptr(tensor:Tensor): return tensor.lazydata

tinygrad/tensor.py

@@ -353,8 +353,7 @@ class Tensor(SimpleMathTrait):
     Moves the tensor to the given device in place.
     """
     real = self.to(device)
-    # TODO: is this assign?
-    if self.grad is not None and real.grad is not None: self.grad.lazydata = real.grad.lazydata
+    if self.grad is not None and real.grad is not None: self.grad.replace(real.grad)
     return self.replace(real)
 
   def shard(self, devices:tuple[str, ...], axis:Optional[int]=None, splits:Optional[tuple[int, ...]]=None) -> Tensor: