code: def get_item(
      x: paddle.Tensor,
      /,
      query: Union[paddle.Tensor, Tuple],
      *,
      copy: Optional[bool] = None,
  ) -> paddle.Tensor:
      if copy:
          x = paddle.clone(x)
  
      if (
          isinstance(query, paddle.Tensor)
          and query.dtype == paddle.bool
          and query.ndim == 0
      ) or isinstance(query, bool):
          # special case to handle scalar boolean indices
          if query is True:
              return x[None]
          else:
              return paddle.zeros(shape=[0] + x.shape, dtype=x.dtype)
  
      if (
          isinstance(query, paddle.Tensor)
          and query.dtype == paddle.bool
      ):
          # # masked queries x[bool_1,bool_2,...,bool_i]
          return paddle.gather_nd(x, paddle.nonzero(query))
      if isinstance(query, paddle.Tensor):
          query = query.cast("int64")
  
      squeeze_indices = _squeeze_helper(query, x.ndim)
      # regular queries x[idx_1,idx_2,...,idx_i]
      # array queries idx = Tensor(idx_1,idx_2,...,idx_i), x[idx]
      ret = x.__getitem__(query)
      return ret.squeeze(squeeze_indices) if squeeze_indices else ret
  
imports: from numbers import Number
  from typing import Optional, Union, Sequence, Callable, List, Tuple
  import paddle
  import numpy
  import multiprocessing
  import ivy
  import ivy.functional.backends.paddle
  from ivy.func_wrapper import with_unsupported_device_and_dtypes
  from ivy.functional.ivy.general import _broadcast_to
  from ivy.utils.exceptions import _check_inplace_update_support
  from .None import backend_version
label_desc: Use image node_id 7 for calling a global function with example usage: get_item(query) and returns: unknown, paddle, x, paddle