22
33from . import scatter_add , scatter_max
44
5- EPSILON = 1e-16
65
7- def _scatter_logsumexp (src , index , dim = - 1 , out = None , dim_size = None , fill_value = None ):
6+ def _scatter_logsumexp (src , index , dim = - 1 , out = None , dim_size = None , fill_value = None , epsilon = 1e-16 ):
87 if not torch .is_floating_point (src ):
98 raise ValueError ('logsumexp can be computed over tensors floating point data types.' )
109
@@ -25,9 +24,10 @@ def _scatter_logsumexp(src, index, dim=-1, out=None, dim_size=None, fill_value=N
2524 dim_size = dim_size ,
2625 fill_value = fill_value ,
2726 )
28- return torch .log (sum_per_index + EPSILON ) + max_value_per_index , recentered_scores
27+ return torch .log (sum_per_index + epsilon ) + max_value_per_index , recentered_scores
2928
30- def scatter_logsumexp (src , index , dim = - 1 , out = None , dim_size = None , fill_value = None ):
29+
30+ def scatter_logsumexp (src , index , dim = - 1 , out = None , dim_size = None , fill_value = None , epsilon = 1e-16 ):
3131 r"""
3232 Numerically safe logsumexp of all values from the :attr:`src` tensor into :attr:`out` at the
3333 indices specified in the :attr:`index` tensor along a given axis
@@ -63,4 +63,4 @@ def scatter_logsumexp(src, index, dim=-1, out=None, dim_size=None, fill_value=No
6363
6464 :rtype: :class:`Tensor`
6565 """
66- return _scatter_logsumexp (src ,index , dim , out , dim_size , fill_value )[0 ]
66+ return _scatter_logsumexp (src ,index , dim , out , dim_size , fill_value , epsilon = epsilon )[0 ]
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