class_docstr: MTV model.
docstr: Reshapes tokens from each view so they have the same temporal dim.
docstr_tok: ["Reshapes","tokens","from","each","view","so","they","have","the","same","temporal","dim","."]
code: def _align_temporal_dimension_across_views(
      self, tokens: Sequence[jnp.ndarray]
  ) -> List[jnp.ndarray]:
      """Reshapes tokens from each view so they have the same temporal dim."""
      min_temporal_dim = min(self.input_token_temporal_dims)
      outputs = []
      for t in tokens:
          bs, time, n, c = t.shape
          outputs.append(
              t.reshape(
                  bs,
                  min_temporal_dim,
                  (n * time) // min_temporal_dim,
                  c,
              )
          )
      return outputs
  
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 6 for calling the MTV obj's underlying member method code with example usage: obj._align_temporal_dimension_across_views(tokens) and returns: outputs