Previously, PullbackEmitter assumed that original values' value category
matches their `TangentVector` types' value category. This was problematic
for loadable types with address-only `TangentVector` types.
Now, PullbackEmitter starts to support differentiation of loadable types with
address-only `TangentVector` types. This patch focuses on supporting and testing
class types, more support can be added incrementally.
Resolves TF-1149.
`DifferentiableFunctionInst` now stores result indices.
`SILAutoDiffIndices` now stores result indices instead of a source index.
`@differentiable` SIL function types may now have multiple differentiability
result indices and `@noDerivative` resutls.
`@differentiable` AST function types do not have `@noDerivative` results (yet),
so this functionality is not exposed to users.
Resolves TF-689 and TF-1256.
Infrastructural support for TF-983: supporting differentiation of `apply`
instructions with multiple active semantic results.
Support differentiation of `is` and `as?` operators.
These operators lower to branching cast SIL instructions, requiring control
flow differentiation support.
Resolves SR-12898.
For accessors: make `AbstractFunctionDecl::getDerivativeFunctionConfigurations`
resolve configurations from parent storage declaration `@differentiable`
attributes.
Fixes "no `@differentiable` attribute" non-differentiability error for accessors
whose parent storage declaration `@differentiable` attributes have not been
type-checked (e.g. because the storage declarations are in another file).
Add protocol requirement and class member storage declaration tests.
Resolves TF-1234.
Move differentiation-related SILOptimizer files to
{include/swift,lib}/SILOptimizer/Differentiation/.
This reduces directory nesting and gathers files together.
JVP functions are forward-mode derivative functions. They take original
arguments and return original results and a differential function. Differential
functions take derivatives wrt arguments and return derivatives wrt results.
`JVPEmitter` is a cloner that emits JVP and differential functions at the same
time. In JVP functions, function applications are replaced with JVP function
applications. In differential functions, function applications are replaced
with differential function applications.
In JVP functions, each basic block takes a differential struct containing callee
differentials. These structs are consumed by differential functions.
`VJPEmitter` is a cloner that emits VJP functions. It implements reverse-mode
automatic differentiation, along with `PullbackEmitter`.
`VJPEmitter` clones an original function, replacing function applications with
VJP function applications. In VJP functions, each basic block takes a pullback
struct (containing callee pullbacks) and produces a predecessor enum: these data
structures are consumed by pullback functions.
Canonicalizes `differentiable_function` instructions by filling in missing
derivative function operands.
Derivative function emission rules, based on the original function value:
- `function_ref`: look up differentiability witness with the exact or a minimal
superset derivative configuration. Emit a `differentiability_witness_function`
for the derivative function.
- `witness_method`: emit a `witness_method` with the minimal superset derivative
configuration for the derivative function.
- `class_method`: emit a `class_method` with the minimal superset derivative
configuration for the derivative function.
If an *actual* emitted derivative function has a superset derivative
configuration versus the *desired* derivative configuration, create a "subset
parameters thunk" to thunk the actual derivative to the desired type.
For `differentiable_function` instructions formed from curry thunk applications:
clone the curry thunk (with type `(Self) -> (T, ...) -> U`) and create a new
version with type `(Self) -> @differentiable (T, ...) -> U`.
Progress towards TF-1211.
The differentiation transform does the following:
- Canonicalizes differentiability witnesses by filling in missing derivative
function entries.
- Canonicalizes `differentiable_function` instructions by filling in missing
derivative function operands.
- If necessary, performs automatic differentiation: generating derivative
functions for original functions.
- When encountering non-differentiability code, produces a diagnostic and
errors out.
Partially resolves TF-1211: add the main canonicalization loop.
To incrementally stage changes, derivative functions are currently created
with empty bodies that fatal error with a nice message.
Derivative emitters will be upstreamed separately.
