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tfp.experimental.substrates.numpy.math.reduce_logmeanexp( input_tensor, axis=None, keepdims=False, name=None )
input_tensor along the dimensions given in
keepdims is true, the rank of the tensor is reduced by 1 for each entry in
keepdims is true, the reduced dimensions are retained with length
axis has no entries, all dimensions are reduced, and a tensor with a
single element is returned.
This function is more numerically stable than
It avoids overflows caused by taking the exp of large inputs and underflows
caused by taking the log of small inputs.
input_tensor: The tensor to reduce. Should have numeric type.
axis: The dimensions to reduce. If
None(the default), reduces all dimensions. Must be in the range
keepdims: Boolean. Whether to keep the axis as singleton dimensions. Default value:
False(i.e., squeeze the reduced dimensions).
strname prefixed to Ops created by this function. Default value:
log_mean_exp: The reduced tensor.