class_docstr: MTV model.
docstr: Creates tokens for each view.
  
  Args:
    x: A 5D float tensor of shape (batch, time, height, width, channels)
      representing the input video.
  
  Returns:
    Tokens for each view and each one has a shape of (batch, time,
    sequence_len, channels).
docstr_tok: ["Creates","tokens","for","each","view",".","Args",":","x",":","A","5D","float","tensor","of","shape","(","batch",",","time",",","height",",","width",",","channels",")","representing","the","input","video",".","Returns",":","Tokens","for","each","view","and","each","one","has","a","shape","of","(","batch",",","time",",","sequence_len",",","channels",")","."]
code: def _tokenize(self, x: jnp.ndarray) -> List[jnp.ndarray]:
      """Creates tokens for each view.
  
      Args:
        x: A 5D float tensor of shape (batch, time, height, width, channels)
          representing the input video.
  
      Returns:
        Tokens for each view and each one has a shape of (batch, time,
        sequence_len, channels).
      """
      tokens = []
      for idx, config in enumerate(self.view_configs):
          view_tokens, _ = vivit_model.temporal_encode(
              x,
              self.temporal_encoding_config,
              ml_collections.ConfigDict(config["patches"]),
              config["hidden_size"],
              return_1d=False,
              name=f"embedding_view{idx}",
          )
          bs, t, h, w, c = view_tokens.shape
          view_tokens = view_tokens.reshape(bs, t, h * w, c)
          tokens.append(view_tokens)
      return tokens
  
imports: import functools
  from typing import Any, List, Sequence, Tuple, Union
  import flax.linen
  import jax
  import jax.numpy
  import ml_collections
  from scenic.model_lib.layers import attention_layers
  from scenic.model_lib.layers import nn_layers
  from scenic.projects.baselines import vit
  from scenic.projects.mtv import model_utils
  from scenic.projects.vivit import model
  from scenic.train_lib import train_utils
label_desc: Use image node_id 5 for calling the MTV obj's underlying member method code with example usage: obj._tokenize(x) and returns: tokens