5a8f346e64cb432a445002230246ee042dbc278b,keras/backend/theano_backend.py,,rnn,#Any#Any#Any#Any#Any#Any#Any#Any#,1446

Before Change

    if mask is not None:
        if mask.ndim == ndim - 1:
            mask = expand_dims(mask)
        assert mask.ndim == ndim
        mask = mask.dimshuffle(axes)

        if unroll:
            indices = list(range(input_length))

After Change

    uses_learning_phase = False

    if mask is not None:
        if mask.ndim != 2:
            raise ValueError(
                "mask should have `shape=(samples, time)`, "
                "got {}".format(mask.shape))
        mask = mask.dimshuffle([1, 0])

        def get_matching_mask(mask_t, ref_tensor_t):
            // tf.where needs its condition tensor

Instances