code: def stack(list_or_tensor, element_dtype=None, strict=True):
      """Stacks the input, if it admits the notion of stacking.
  
      For example, a list of tensors can be stacked into a larger tensor. This
      function is similar to tf.stack, but it accepts non-lists and lists of
      non-tensors as arguments. In the latter case, the function does nothing.
  
      Args:
        list_or_tensor: Any
        element_dtype: tf.DType, optional dtypedtype for the elements in the list.
            Required if the input is stackable, and the list is untyped.
        strict: bool, if True an error is raised if the input is not stackable.
            Otherwise the function is a no-op.
  
      Returns:
        Any, if the input is stackable, the result will be a tf.Tensor. Otherwise,
        if strict=False, the result will be list_or_tensor.
  
      Raises:
        ValueError: if strict=True and the input is not stackable.
      """
      if strict:
  
          def raise_error(x):
              raise ValueError(
                  "%s must be stackable when strict=True" % x
              )
  
          original_call = raise_error
      else:
          original_call = lambda x: x
      return data_structures.list_stack(
          list_or_tensor,
          data_structures.ListStackOpts(
              element_dtype=element_dtype, original_call=original_call
          ),
      )
  
imports: from tensorflow.python.autograph.operators import data_structures
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import tensor_util
label_desc: Use image node_id 4 for calling a global function with example usage: stack(list_or_tensor, element_dtype, strict) and returns: data_structures