523e24e8acf8ecc6d6b31e78cdc6e4c3967bbbdb,keras/backend/theano_backend.py,,rnn,#Any#Any#Any#Any#Any#,407

Before Change

    axes = [1, 0] + list(range(2, ndim))
    inputs = inputs.dimshuffle(axes)
    if mask is None:
        mask = expand_dims(ones_like(T.sum(inputs, axis=-1)))
    else:
        mask = mask.dimshuffle(axes)

    def _step(input, mask, output_tm1, *states):

After Change

            output, new_states = step_function(input, states)
            return [output] + new_states

        results, _ = theano.scan(
            _step,
            sequences=inputs,
            outputs_info=[None] + initial_states,

Instances