ReduceLAWS.reduce_mapping: law of bendtorch-core@0.1.0.0 Import: import bendtorch-core@0.1.0.0/src/autograd/reduce_LAWS.bend as ReduceLAWS Lines 120-126 of bendtorch-core@0.1.0.0/src/autograd/reduce_LAWS.bend: https://jend.leeeet.dev/read.txt?path=bendtorch-core@0.1.0.0/src/autograd/reduce_LAWS.bend&start_line=120&end_line=126 import Base import bendtorch-core@0.1.0.0/src/shape/core.bend as Shape import bendtorch-core@0.1.0.0/src/tensor/core.bend as Core import bendtorch-core@0.1.0.0/src/autograd/reduce.bend as Reduce # On success the output has the target's dimensions, and for every list of # words that lists the contribution, each in-bounds target position holds the # ordered fiber sum of those words. law reduce_mapping: for input: Core.Dynamic for +target: Shape.Shape MappingModel Uses (11): https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/autograd/reduce.bend&name=planned https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/autograd/reduce.bend&name=reduce_to https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/autograd/reduce_LAWS.bend&name=Mapping https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/autograd/reduce_LAWS.bend&name=MappingModel https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/autograd/reduce_LAWS.bend&name=MappingWith https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/autograd/reduce_PROOF.bend&name=Holds https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/autograd/reduce_PROOF.bend&name=planned_mapping https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/shape/core.bend&name=Shape https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/shape/core.bend&name=broadcast_checked https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/shape/plan_proofs.bend&name=broadcast_checked_plan https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/tensor/core.bend&name=Dynamic