code: def view_default(func, *args, **kwargs):
      _, new_kwargs = normalize_function(
          func,
          args=args,
          kwargs=kwargs,
          normalize_to_only_use_kwargs=True,
      )
  
      inp = new_kwargs.pop("input")
      size = new_kwargs.pop("size")
  
      # Ensure specified size still includes batch and ragged dims
      if len(size) < 3 or not raggedness_matches(inp, size):
          raise RuntimeError(
              f"view(): cannot view shape {inp._size} as {size}"
          )
  
      jagged_size = [inp._values.shape[0]] + size[2:]
      return NestedTensor(
          func(inp._values, jagged_size), **extract_kwargs(inp)
      )
  
imports: import functools
  import math
  import operator
  import torch
  from torch.nested._internal.sdpa import jagged_scaled_dot_product_attention
  from .nested_tensor import NestedTensor
  from typing import *
  from torch.fx.operator_schemas import normalize_function
label_desc: Use image node_id 40 for calling a global function with example usage: view_default(func) and returns: NestedTensor