def crf_mask(vocab, span_type, s_idx, e_idx, pad_idx=None):
"""Create a CRF mask.
Returns a Tensor with valid transitions as a 0 and invalid as a 1 for easy use with `masked_fill`
"""
np_mask = crf_m(vocab, span_type, s_idx, e_idx, pad_idx=pad_idx)
return (torch.from_numpy(np_mask) == 0)
def crf_mask(vocab, span_type, s_idx, e_idx, pad_idx=None):
"""Create a CRF Mask.
Returns a mask with invalid moves as 0 and valid moves as 1.
"""
return tf.constant(crf_m(vocab, span_type, s_idx, e_idx, pad_idx).T)