Loss.mean: def of bendtorch-core@0.1.0.0
Import: import bendtorch-core@0.1.0.0/src/autograd/loss.bend as Loss
Lines 197-202 of bendtorch-core@0.1.0.0/src/autograd/loss.bend: https://jend.leeeet.dev/read.txt?path=bendtorch-core@0.1.0.0/src/autograd/loss.bend&start_line=197&end_line=202

import Base
import bendtorch-core@0.1.0.0/src/tensor/core.bend as Core

# PyTorch's mean of every element: the ordered sum divided by the element
# count, F32.div of the two. The sum adds left to right from +0.0, where
# PyTorch's CPU sum adds in a cascade, so for many words the last bits can
# differ.
def mean(input: Core.Dynamic) -> Result<&2, &1, Core.Error, Core.Dynamic>:
  mean_shaped(Core.shape(input))

Uses (5):
  https://jend.leeeet.dev/definition.txt?path=Base/base.bend&name=Result
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/autograd/loss.bend&name=mean_shaped
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/tensor/core.bend&name=Dynamic
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/tensor/core.bend&name=Error
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/tensor/core.bend&name=shape