message: chore: Update partitioning readme
diff: @@ -34,11 +34,9 @@ To enable automatic fallback feature, you can set following attributes in Python
  ts_model = torch.jit.script(model)
  trt_model = torchtrt.ts.compile(model, **{
  ...
  - "torch_fallback" : {
  - "enabled" : True,
  "min_block_size" : 3,
  - "forced_fallback_ops": ["aten::add"],
  - }
  + "torch_executed_ops": ["aten::add"],
  + "torch_executed_modules": [],
  })
  ```
  - `enabled`: By default automatic fallback will be off. It is enabled by setting it to True.
  @@ -59,9 +57,8 @@ auto in = torch::randn({1, 3, 224, 224}, {torch::kCUDA});
  auto mod = torch::jit::load("trt_ts_module.ts");
  auto input_sizes = std::vector<torchtrt::InputRange>{{in.sizes()}};
  torchtrt::ts::CompileSpec cfg(input_sizes);
  -cfg.torch_fallback = torchtrt::CompileSpec::TorchFallback(true);
  -cfg.torch_fallback.min_block_size = 2;
  -cfg.torch_fallback.forced_fallback_ops.push_back("aten::relu");
  +cfg.min_block_size = 2;
  +cfg.torch_executed_ops.push_back("aten::relu");
  auto trt_mod = torchtrt::ts::compile(mod, cfg);
  auto out = trt_mod.forward({in});
  ```
  