torch.compile
torch.compile(model=None, , fullgraph=False, dynamic=False, backend='inductor', mode=None, passes=None, *kwargs)
Optimizes given model/function using Dynamo and specified backend
Parameters:
      * model (Callable) -- Module/function to optimize
  * **fullgraph** (*bool*) -- Whether it is ok to break model into
    several subgraphs

  * **dynamic** (*bool*) -- Use dynamic shape tracing

  * **backend** (*str** or **Callable*) -- backend to be used

  * **mode** (*str*) -- Can be either "default", "reduce-overhead"
    or "max-autotune"

  * **passes** (*dict*) -- A dictionary of passes to the backend.
    Passes currently recognized by inductor backend: - static-
    memory - matmul-tune - matmul-padding - triton-autotune -
    triton-bmm - triton-mm - triton-convolution - rematerialize-
    threshold - rematerialize-acc-threshold

Return type:
      Callable
Example: