tf.sequence_mask     View source on GitHub    Returns a mask tensor representing the first N positions of each cell.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.sequence_mask  
tf.sequence_mask(
    lengths, maxlen=None, dtype=tf.dtypes.bool, name=None
)
 If lengths has shape [d_1, d_2, ..., d_n] the resulting tensor mask has dtype dtype and shape [d_1, d_2, ..., d_n, maxlen], with mask[i_1, i_2, ..., i_n, j] = (j < lengths[i_1, i_2, ..., i_n])
 Examples: tf.sequence_mask([1, 3, 2], 5)  # [[True, False, False, False, False],
                                #  [True, True, True, False, False],
                                #  [True, True, False, False, False]]

tf.sequence_mask([[1, 3],[2,0]])  # [[[True, False, False],
                                  #   [True, True, True]],
                                  #  [[True, True, False],
                                  #   [False, False, False]]]

 


 Args
  lengths   integer tensor, all its values <= maxlen.  
  maxlen   scalar integer tensor, size of last dimension of returned tensor. Default is the maximum value in lengths.  
  dtype   output type of the resulting tensor.  
  name   name of the op.   
 


 Returns   A mask tensor of shape lengths.shape + (maxlen,), cast to specified dtype.  

 


 Raises
  ValueError   if maxlen is not a scalar.     

    
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