docstr: Makes a gap of max_frame_gap frame numbers in the middle of each sequence
docstr_tok: ["Makes","a","gap","of","max_frame_gap","frame","numbers","in","the","middle","of","each","sequence"]
code: def __init__(self, num_seq, max_frame_gap=1):
      """
      Makes a gap of max_frame_gap frame numbers in the middle of each sequence
      """
      self.seq_annots = {f"seq_{i}": None for i in range(num_seq)}
      self._seq_to_idx = {
          f"seq_{i}": list(range(i * 10, i * 10 + 10))
          for i in range(num_seq)
      }
  
      # frame numbers within sequence: [0, ..., 4, n, ..., n+4]
      # where n - 4 == max_frame_gap
      frame_nos = list(range(5)) + list(
          range(4 + max_frame_gap, 9 + max_frame_gap)
      )
      self.frame_annots = [
          {"frame_annotation": MockFrameAnnotation(no)}
          for no in frame_nos * num_seq
      ]
      for seq_name, idx in self._seq_to_idx.items():
          for i in idx:
              self.frame_annots[i][
                  "frame_annotation"
              ].sequence_name = seq_name
  
imports: import unittest
  from collections import defaultdict
  from dataclasses import dataclass
  from itertools import product
  import numpy
  import torch
  from pytorch3d.implicitron.dataset.data_loader_map_provider import DoublePoolBatchSampler
  from pytorch3d.implicitron.dataset.dataset_base import DatasetBase
  from pytorch3d.implicitron.dataset.frame_data import FrameData
  from pytorch3d.implicitron.dataset.scene_batch_sampler import SceneBatchSampler
label_desc: Use image node_id 1 to create a new MockDataset object from inherited base classes: DatasetBase with example: obj = MockDataset(num_seq, max_frame_gap)