continue
		}

		st := state.symType(s)

		if st <= sym.STEXT || st >= sym.SXREF {
			continue
		}
		state.data[st] = append(state.data[st], s)

		// Similarly with checking the onlist attr.
		if ldr.AttrOnList(s) {
			log.Fatalf("symbol %s listed multiple times", ldr.SymName(s))
		}
		ldr.SetAttrOnList(s, true)
	}

	// Now that we have the data symbols, but before we start

    this op outputs a copy of the input tensor where values from the `depth`
    dimension are moved in spatial blocks to the `height` and `width`
    dimensions. The attr `block_size` indicates the input block size and how
    the data is moved.
   }];

  let arguments = (ins
    TFL_TensorOf<[F32, I8, I32, I64, TFL_Quint8, UI8, QI8, QUI8]>:$input,

            `Model.predict_step`.
        *   SavedModel uses its own `Model._saved_model_inputs_spec` attr now
            instead of relying on `Model.inputs` and `Model.input_names`, which
            are no longer set for subclass Models. This attr is set in eager,
            `tf.function`, and graph modes. This gets rid of the need for users