Failure to run and build in nightly 2.4

[artyom-beilis]

Several issues

1. issues with changed const and missing copy_data from Allocator class
2. torch.register_privateuse1_backend -> +torch.utils.rename_privateuse1_backend

However even with all that I still get failure during runtime:

Traceback (most recent call last):
  File "/tmp/pytorch_open_registration_example/open_registration_example.py", line 102, in <module>
    x = torch.ones(4, 4, device='foo:2')
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ModuleNotFoundError: No module named 'torch.foo'

My modifications:

diff --git a/cpp_extensions/open_registration_extension.cpp b/cpp_extensions/open_registration_extension.cpp
index b666253..89d4486 100644
--- a/cpp_extensions/open_registration_extension.cpp
+++ b/cpp_extensions/open_registration_extension.cpp
@@ -43,7 +43,7 @@ at::Tensor custom_add_Tensor(const at::Tensor & self, const at::Tensor & other,
 // A dummy allocator for our custom device, that secretly uses the CPU
 struct DummyCustomAllocator final : at::Allocator {
   DummyCustomAllocator() = default;
-  at::DataPtr allocate(size_t nbytes) const override {
+  at::DataPtr allocate(size_t nbytes) override {
     std::cout << "Custom allocator's allocate() called!" << std::endl;
     void* data = c10::alloc_cpu(nbytes);
     return {data, data, &ReportAndDelete, at::Device(at::DeviceType::PrivateUse1, 0)};
@@ -57,6 +57,11 @@ struct DummyCustomAllocator final : at::Allocator {
     c10::free_cpu(ptr);
   }
 
+  void copy_data(void* dest, const void* src, std::size_t count) const override
+  {
+        default_copy_data(dest,src,count);
+  }
+
   at::DeleterFnPtr raw_deleter() const override {
     return &ReportAndDelete;
   }
diff --git a/open_registration_example.py b/open_registration_example.py
index 9b31d69..1c1e048 100644
--- a/open_registration_example.py
+++ b/open_registration_example.py
@@ -88,7 +88,7 @@ def test(x, y):
 # Option 1: Use torch.register_privateuse1_backend("foo"), which will allow
 # "foo" as a device string to work seamlessly with pytorch's API's.
 # You may need a more recent nightly of PyTorch for this.
-torch.register_privateuse1_backend('foo')
+torch.utils.rename_privateuse1_backend('foo')
 
 # Show that in general, passing in a custom device string will fail.
 try:
``