class_docstr: Split the input tensor into 2 tensors along the time dimension.
class_docstr_tok: ["Split","the","input","tensor","into","2","tensors","along","the","time","dimension","."]
code: def compute_mask(self, inputs, mask=None):
      # Also split the mask into 2 if it presents.
      if mask is None:
          return None
      return ops.split(mask, 2, axis=1)
  
imports: import numpy
  import keras
  from keras import ops
  from keras import layers
label_desc: Use image node_id 2 for calling the TemporalSplit obj's underlying member method code with example usage: obj.compute_mask(inputs, mask) and returns: ops, None