TensorBackward.linear: def of bendtorch-core@0.1.0.0
Import: import bendtorch-core@0.1.0.0/src/autograd/tensor_backward.bend as TensorBackward
Lines 1336-1345 of bendtorch-core@0.1.0.0/src/autograd/tensor_backward.bend: https://jend.leeeet.dev/read.txt?path=bendtorch-core@0.1.0.0/src/autograd/tensor_backward.bend&start_line=1336&end_line=1345

import Base

# Linear: records x @ W^T with W of [out, in], PyTorch's layout, then adds
# the bias b of [out] to every row. The id is the sum's; the product is the
# entry before it. The bias id is checked against the tape the call receives,
# before the product is recorded, so the product's own id never stands in
# for a missing bias. A refusal of any step (an unknown id, a product or a
# sum the tensor layer refuses) comes back with its error and the tape as it
# was.
def linear(tape: Tape, +x: Nat, +w: Nat, +bias: Nat) -> Tape & Result<&2, &2, Error, Nat>:
  Tape{entries} = tape
  linear_counted(x, w, bias, counted(entries))

Uses (7):
  https://jend.leeeet.dev/definition.txt?path=Base/base.bend&name=Nat
  https://jend.leeeet.dev/definition.txt?path=Base/base.bend&name=Pair
  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/tensor_backward.bend&name=Error
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/autograd/tensor_backward.bend&name=Tape
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/autograd/tensor_backward.bend&name=counted
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/autograd/tensor_backward.bend&name=linear_counted