code: def unsorted_segment_mean(
      data: np.ndarray,
      segment_ids: np.ndarray,
      num_segments: int,
  ) -> np.ndarray:
      ivy.utils.assertions.check_unsorted_segment_valid_params(
          data, segment_ids, num_segments
      )
  
      if len(segment_ids) == 0:
          # If segment_ids is empty, return an empty array of the correct shape
          return np.zeros(
              (num_segments,) + data.shape[1:], dtype=data.dtype
          )
  
      # Initialize an array to store the sum of elements for each segment
      res = np.zeros((num_segments,) + data.shape[1:], dtype=data.dtype)
  
      # Initialize an array to keep track of the number of elements in each segment
      counts = np.zeros(num_segments, dtype=np.int64)
  
      for i in range(len(segment_ids)):
          seg_id = segment_ids[i]
          if seg_id < num_segments:
              res[seg_id] += data[i]
              counts[seg_id] += 1
  
      return res / counts[:, np.newaxis]
  
file_path: ivy/ivy/functional/backends/numpy/experimental/creation.py
imports: from typing import Optional, Tuple, Sequence, Union
  import numpy
  import ivy
label_desc: Use image node_id 11 for calling a global function with example usage: unsorted_segment_mean(data, segment_ids, num_segments) and returns: unknown, np