code: def inplace_or_view_method_definition(
      fn: NativeFunctionWithDifferentiabilityInfo,
  ) -> Optional[str]:
      f = fn.func
      if get_view_info(f) is None and (
          # For functions that modify their inputs but don't return them,
          # we can't give them autograd support.
          # See https://github.com/pytorch/pytorch/issues/53796
          not modifies_arguments(f)
          or len(f.func.returns) == 0
      ):
          return None
      return METHOD_DEFINITION.substitute(
          return_type=cpp.returns_type(
              f.func.returns, symint=True
          ).cpp_type(),
          type_wrapper_name=type_wrapper_name(f),
          formals=gen_formals(f),
          type_definition_body=emit_inplace_or_view_body(fn),
      )
  
imports: from typing import Dict, List, Optional, Sequence, Tuple
  from torchgen.api import cpp
  from torchgen.api.autograd import dispatch_strategy, gen_differentiable_outputs, NativeFunctionWithDifferentiabilityInfo
  from torchgen.api.types import BaseCType, Binding, boolT, ConstRefCType, CType, DispatcherSignature, intArrayRefT, longT, OptionalCType, symIntArrayRefT, SymIntT, tensorT
  from torchgen.code_template import CodeTemplate
  from torchgen.context import with_native_function
  from torchgen.model import NativeFunction, SchemaKind, SelfArgument, TensorOptionsArguments, Type
  from torchgen.utils import FileManager
  from .context import with_native_function_with_differentiability_info
  from .gen_trace_type import get_return_value, MANUAL_AUTOGRAD, tie_return_values, type_wrapper_name
label_desc: Use image node_id 15 for calling a global function with example usage: inplace_or_view_method_definition(fn) and returns: METHOD_DEFINITION, None