diff options
Diffstat (limited to 'tensorflow/contrib/quantize/python/fold_batch_norms.py')
| -rw-r--r-- | tensorflow/contrib/quantize/python/fold_batch_norms.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/tensorflow/contrib/quantize/python/fold_batch_norms.py b/tensorflow/contrib/quantize/python/fold_batch_norms.py index e8a0d41425..5750be6f4c 100644 --- a/tensorflow/contrib/quantize/python/fold_batch_norms.py +++ b/tensorflow/contrib/quantize/python/fold_batch_norms.py @@ -237,7 +237,7 @@ def _FindFusedBatchNorms(graph): # The batch variance used during forward and backward prop is biased, # i.e it is calculated as: V=sum(x(k)-mu)^2/N. For the moving average # calculation, the variance is corrected by the term N/N-1 (Bessel's - # correction). The variance tensor read from FuseBatchNorm has bessel's + # correction). The variance tensor read from FuseBatchNorm has Bessel's # correction applied, so we undo it here. scope, sep, _ = bn_op.name.rpartition('/') g = ops.get_default_graph() @@ -306,7 +306,7 @@ def _ComputeBatchNormCorrections(context, match, freeze_batch_norm_delay, Args: context: The scope under which we look for batch norm params - match: Object containg required batch norm tensors for correction + match: Object containing required batch norm tensors for correction computation. freeze_batch_norm_delay: Delay in steps at which computation switches from regular batch norm to frozen mean and variance. |