class_docstr: Converts a video from dtype float32 to dtype uint8.
class_docstr_tok: ["Converts","a","video","from","dtype","float32","to","dtype","uint8","."]
docstr: Args:
      x (torch.Tensor): video tensor with shape (C, T, H, W).
docstr_tok: ["Args",":","x","(","torch.Tensor",")",":","video","tensor","with","shape","(","C",",","T",",","H",",","W",")","."]
code: def forward(self, x: torch.Tensor) -> torch.Tensor:
      """
      Args:
          x (torch.Tensor): video tensor with shape (C, T, H, W).
      """
      assert (
          x.dtype == torch.float or x.dtype == torch.half
      ), "image must have dtype torch.uint8"
      return self.convert_func(x)
  
imports: from typing import Callable, Dict, List, Optional, Tuple
  import pytorchvideo.transforms.functional
  import torch
  import torchvision.transforms
label_desc: Use image node_id 2 for calling the ConvertFloatToUint8 obj's underlying member method code with example usage: obj.forward(x) and returns: self