parameters: (op)
return_statement: return (sparse_index_shapes + sparse_value_shapes + sparse_shape_shapes +
            dense_shapes)
docstring: Shape function for the ParseExample op.
docstring_summary: Shape function for the ParseExample op.
docstring_tokens: Shape function for the ParseExample op .
function: def _ParseExampleShape(op):  # pylint: disable=invalid-name
    """Shape function for the ParseExample op."""
    input_shape = op.inputs[0].get_shape().with_rank(1)
    op.inputs[1].get_shape().with_rank(1)  # names
    num_sparse = op.get_attr("Nsparse")
    num_dense = op.get_attr("Ndense")
    dense_shapes = op.get_attr("dense_shapes")
    sparse_index_shapes = [
        tensor_shape.matrix(None, 2) for _ in range(num_sparse)]
    sparse_value_shapes = [tensor_shape.vector(None) for _ in range(num_sparse)]
    sparse_shape_shapes = [tensor_shape.vector(2) for _ in range(num_sparse)]
    assert num_dense == len(dense_shapes)
    dense_shapes = [
        input_shape.concatenate(dense_shape)
        for dense_shape in dense_shapes]
    return (sparse_index_shapes + sparse_value_shapes + sparse_shape_shapes +
            dense_shapes)
function_tokens: def _ParseExampleShape ( op ) : # pylint: disable=invalid-name input_shape = op . inputs [ 0 ] . get_shape ( ) . with_rank ( 1 ) op . inputs [ 1 ] . get_shape ( ) . with_rank ( 1 ) # names num_sparse = op . get_attr ( "Nsparse" ) num_dense = op . get_attr ( "Ndense" ) dense_shapes = op . get_attr ( "dense_shapes" ) sparse_index_shapes = [ tensor_shape . matrix ( None , 2 ) for _ in range ( num_sparse ) ] sparse_value_shapes = [ tensor_shape . vector ( None ) for _ in range ( num_sparse ) ] sparse_shape_shapes = [ tensor_shape . vector ( 2 ) for _ in range ( num_sparse ) ] assert num_dense == len ( dense_shapes ) dense_shapes = [ input_shape . concatenate ( dense_shape ) for dense_shape in dense_shapes ] return ( sparse_index_shapes + sparse_value_shapes + sparse_shape_shapes + dense_shapes )