code: def _slice_length(value_length, slice_key):
      """Computes the number of elements in a slice of a value with a given length.
  
      Returns the equivalent of: `len(range(value_length)[slice_key])`
  
      Args:
        value_length: Scalar int `Tensor`: the length of the value being sliced.
        slice_key: A `slice` object used to slice elements from the value.
  
      Returns:
        The number of elements in the sliced value.
      """
      # Note: we could compute the slice length without creating a zeros tensor
      # with some variant of (stop-start)//step, but doing so would require more
      # ops (for checking bounds, handling negative indices, negative step sizes,
      # etc); and we expect this to be an uncommon operation, so we use this
      # simpler implementation.
      zeros = array_ops.zeros(value_length, dtype=dtypes.bool)
      return array_ops.size(
          zeros[slice_key], out_type=value_length.dtype
      )
  
imports: from tensorflow.python.eager import context
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.ragged import ragged_gather_ops
  from tensorflow.python.ops.ragged import ragged_math_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.util import dispatch
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 5 for calling a global function with example usage: _slice_length(value_length, slice_key) and returns: array_ops