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# torch.jit.annotate

torch.jit.annotate(the_type, the_value)

  This method is a pass-through function that returns the_value, used to hint TorchScript compiler the type of the_value. It is a no-op when running outside of TorchScript.

  Though TorchScript can infer correct type for most Python expressions, there are some cases where type inference can be wrong, including:

  - Empty containers like [] and {}, which TorchScript assumes to be container of Tensor

  - Optional types like Optional[T] but assigned a valid value of type T, TorchScript would assume it is type T rather than Optional[T]

  Note that annotate() does not help in __init__ method of torch.nn.Module subclasses because it is executed in eager mode. To annotate types of torch.nn.Module attributes, use `Annotate()` instead.

  Example:

      import torch
      from typing import Dict

      @torch.jit.script
      def fn():
          # Telling TorchScript that this empty dictionary is a (str -> int) dictionary
          # instead of default dictionary type of (str -> Tensor).
          d = torch.jit.annotate(Dict[str, int], {})

          # Without `torch.jit.annotate` above, following statement would fail because of
          # type mismatch.
          d["name"] = 20

  Parameters:

    - the_type – Python type that should be passed to TorchScript compiler as type hint for the_value

    - the_value – Value or expression to hint type for.

  Returns:

    the_value is passed back as return value.

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