docstr: Provide different tensors as test cases.
  
  Yield:
      (torch.tensor): tensor as test case input.
docstr_tok: ["Provide","different","tensors","as","test","cases",".","Yield",":","(","torch.tensor",")",":","tensor","as","test","case","input","."]
code: def _get_inputs(
      channel: int = 3,
      clip_length: int = 8,
      crop_size: int = 224,
      frame_ratios: Tuple[int] = (4, 1),
  ) -> torch.tensor:
      """
      Provide different tensors as test cases.
  
      Yield:
          (torch.tensor): tensor as test case input.
      """
      # Prepare random inputs as test cases.
      shapes = ((1, channel, clip_length, crop_size, crop_size),)
      for shape in shapes:
          yield uniform_temporal_subsample_repeated(
              torch.rand(shape),
              frame_ratios=frame_ratios,
              temporal_dim=2,
          )
  
file_path: pytorchvideo/tests/test_models_slowfast.py
imports: import itertools
  import os
  import unittest
  from typing import Tuple
  import torch
  from pytorchvideo.models.slowfast import create_slowfast, create_slowfast_with_roi_head
  from pytorchvideo.transforms.functional import uniform_temporal_subsample_repeated
  from torch import nn
label_desc: Use image node_id 6 for calling the TestSlowFast obj's underlying member method code with example usage: obj._get_inputs(channel, clip_length, crop_size, frame_ratios) without return types