v0.9.0

What's Changed

• Bump Cpp lib to 1.1.0
• Split Module creation to simple Module::new(path) and a new ModuleBuilder that support all customization and arguments, including new memory_allocator and temp_allocator args introduced in the new Cpp version.

  - let module = Module::from_file_path(path);
  + let module = Module::new(path);
  
  - let module = Module::new(
  -   pte_path,
  -   &[data1_path, data2_path],
  -   Some(LoadMode::File), 
  -   /* event_tracer */ None);
  + let module = ModuleBuilder::new(ptr_path)
  +   .data_files(&[data1_path, data2_path]),
  +   .load_mode(LoadMode::File)
  +   .build();

• Change list EValue constructors to accept pointer to ArrayRef/BoxedEvalueList rather than a slice/BoxedEvalueList-value.
  The new API comes from an optimization in the Cpp side (pytorch/executorch#13013), which added another indirection but reduced the size of EValue struct.
  Constructing an EValue from &str or &CStr directly is no longer possible, as ArrayRef must be allocated somewhere and borrowed to the EValue. Use ArrayRef::from_cstr or ArrayRef::from_chars and construct the value using the array ref instead.

    // lists of f64, bool and std::ffi::c_char are simply slices within EValue
    let list = [42.0, 17.0, 6.0];
  - let evalue = EValue::new(list.as_slice());
  + let list_ref = ArrayRef::from_slice(list.as_slice);
  + let evalue = EValue::new(&list);
  
  - let evalue = EValue::new(c"hello world!");
  + let chars = ArrayRef::from_cstr(c"hello world!");
  + let evalue = EValue::new(&chars);
  
    // lists of i64, Tensor and optional Tensor are stored in BoxedEvalueList within EValue
    let (evalue1, evalue2, evalue3) = (EValue::new(42), EValue::new(17), EValue::new(6));
    let wrapped_vals = EValuePtrList::new([&evalue1, &evalue2, &evalue3]);
    let mut unwrapped_vals = storage!(i64, (3));
    let list = BoxedEvalueList::new(&wrapped_vals, unwrapped_vals.as_mut()).unwrap();
  - let evalue = EValue::new(list);
  + let evalue = EValue::new(&list);

• Make DataLoader, MemoryAllocator and NamedDataMap traits instead of structs. In the Cpp side these are all base classes, and classes extending them used to implement AsRef<BaseClass> on the Rust side. Traits are more flexible, and allow for functions that consume self. This change is reverting the opposite change introduced in v0.8.0.
• Add TensorPtr::copy_of

Full Changelog: v0.8.1...v0.9.0