SgdLAWS.DescendWith: def of bendtorch-core@0.1.0.0
Import: import bendtorch-core@0.1.0.0/src/autograd/sgd_LAWS.bend as SgdLAWS
Lines 34-59 of bendtorch-core@0.1.0.0/src/autograd/sgd_LAWS.bend: https://jend.leeeet.dev/read.txt?path=bendtorch-core@0.1.0.0/src/autograd/sgd_LAWS.bend&start_line=34&end_line=59

import Base
import bendtorch-core@0.1.0.0/src/shape/core.bend as Shape
import bendtorch-core@0.1.0.0/src/storage/LAWS.bend as StorageLaws
import bendtorch-core@0.1.0.0/src/tensor/core.bend as Core
import bendtorch-core@0.1.0.0/src/tensor/elementwise.bend as Elementwise
import bendtorch-core@0.1.0.0/src/tensor/lifecycle.bend as Lifecycle
import bendtorch-core@0.1.0.0/src/tensor/contracts/replayed.bend as Replayed
import bendtorch-core@0.1.0.0/src/tensor/contracts/LAWS.bend as Contracts
import bendtorch-core@0.1.0.0/src/tensor/contracts/binary_LAWS.bend as Binary
import bendtorch-core@0.1.0.0/src/autograd/gradient.bend as Gradient
import bendtorch-core@0.1.0.0/src/autograd/tensor_backward.bend as Backward
import bendtorch-core@0.1.0.0/src/autograd/sgd.bend as Sgd

# What the transport form of sgd_step_values asks of P: P holds for the entry
# with its node, shape and saved values, whose value is replayed over +0.0
# with any history whose words are the cells of Descend{lr} over the old
# value p and the gradient g, and whose slot still holds g with its words,
# next to Done.
def DescendWith(+lr: F32, node: Backward.Node, +shape: Shape.Shape, saved: Backward.Saved, +plan: Shape.BroadcastPlan,
  +fill: F32, +ops: List<&2, StorageLaws.Op>,
  +g_shape: Shape.Shape, +g_fill: F32, +g_ops: List<&2, StorageLaws.Op>,
  -P: Backward.Entry & Result<&2, &2, Sgd.Error, Unit> -> Type) -> Type:
  @+kept: List<&2, StorageLaws.Op> ->
  @kept_words: {Contracts.words(shape, fill, kept, Shape.logical_numel(Shape.dimensions(shape))) ==
    Contracts.words(shape, fill, ops, Shape.logical_numel(Shape.dimensions(shape))) : List<&2, F32>} ->
  @-kept_fits: {Lifecycle.logical_length(Replayed.storage(shape, fill, kept)) == Shape.logical_numel(Shape.dimensions(shape)) : Nat} ->
  @+g_kept: List<&2, StorageLaws.Op> ->
  @g_words: {Contracts.words(g_shape, g_fill, g_kept, Shape.logical_numel(Shape.dimensions(g_shape))) ==
    Contracts.words(g_shape, g_fill, g_ops, Shape.logical_numel(Shape.dimensions(g_shape))) : List<&2, F32>} ->
  @-g_fits: {Lifecycle.logical_length(Replayed.storage(g_shape, g_fill, g_kept)) == Shape.logical_numel(Shape.dimensions(g_shape)) : Nat} ->
  @+output_ops: List<&2, StorageLaws.Op> ->
  @values: {Contracts.words(Shape.output_shape(plan), 0.0, output_ops, Shape.logical_numel(Shape.dimensions(Shape.output_shape(plan)))) ==
    Binary.cells(Elementwise.Descend{lr}, plan, shape, fill, ops, g_shape, g_fill, g_ops,
      Shape.logical_numel(Shape.dimensions(Shape.output_shape(plan)))) : List<&2, F32>} ->
  @-output_fits: {Lifecycle.logical_length(Replayed.storage(Shape.output_shape(plan), 0.0, output_ops)) ==
    Shape.logical_numel(Shape.dimensions(Shape.output_shape(plan))) : Nat} ->
    P((Backward.Entry{node, shape,
      Core.Packed{Shape.output_shape(plan), Core.TTensor{Replayed.storage(Shape.output_shape(plan), 0.0, output_ops), output_fits}},
      saved, Gradient.Held{Core.Packed{g_shape, Core.TTensor{Replayed.storage(g_shape, g_fill, g_kept), g_fits}}}}, Done{Unit{}}))

Uses (25):
  https://jend.leeeet.dev/definition.txt?path=Base/base.bend&name=F32
  https://jend.leeeet.dev/definition.txt?path=Base/base.bend&name=List
  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=Base/base.bend&name=Sigma
  https://jend.leeeet.dev/definition.txt?path=Base/base.bend&name=Unit
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/autograd/gradient.bend&name=Slot
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/autograd/sgd.bend&name=Error
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/autograd/tensor_backward.bend&name=Entry
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/autograd/tensor_backward.bend&name=Node
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/autograd/tensor_backward.bend&name=Saved
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/shape/core.bend&name=BroadcastPlan
  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=dimensions
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/shape/core.bend&name=logical_numel
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/shape/core.bend&name=output_shape
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/storage/LAWS.bend&name=Op
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/tensor/contracts/LAWS.bend&name=words
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/tensor/contracts/binary_LAWS.bend&name=cells
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/tensor/contracts/replayed.bend&name=storage
  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=Tensor
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/tensor/elementwise.bend&name=Operation
  https://jend.leeeet.dev/definition.txt?path=bendtorch-core@0.1.0.0/src/tensor/lifecycle.bend&name=logical_length