code: def is_tensor_type(t: Type) -> bool:
      # TODO: Should handle optional here?
      return t.is_tensor_like() and t.is_list_like() is None
  
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 1 for calling a global function with example usage: is_tensor_type(t) and returns: unknown