1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853
/*! Macros to make using the `engine` module's interface more ergonomic. Demand-driven change propagation ================================= The example below demonstrates _demand-driven change propagation_, which is unique to Adapton's approach to incremental computation. The example constructs two mutable inputs, `nom` and `den`, an intermediate subcomputation `div` that divides the numerator in `nom` by the denominator in `den`, and a thunk `check` that first checks whether the denominator is zero (returning zero if so) and if non-zero, returns the value of the division. ``` # #[macro_use] extern crate adapton; # fn main() { use adapton::macros::*; use adapton::engine::*; manage::init_dcg(); // Two mutable inputs, for numerator and denominator of division //let num = cell!(42); //let den = cell!(2); let_cell!{num = 42; den = 2; { // In Rust, cloning is explicit: let den2 = den.clone(); // clone _global reference_ to cell. let den3 = den.clone(); // clone _global reference_ to cell, again. // Two subcomputations: The division, and a check thunk with a conditional expression let div = thunk![ get!(num) / get!(den) ]; let check = thunk![ if get!(den2) == 0 { None } else { Some(get!(div)) } ]; // Observe output of `check` while we change the input `den` // Step 1: (Explained in detail, below) assert_eq!(get!(check), Some(21)); // Step 2: (Explained in detail, below) set(&den3, 0); assert_eq!(get!(check), None); // Step 3: (Explained in detail, below) set(&den3, 2); assert_eq!(get!(check), Some(21)); // division is reused }} # } ``` The programmer's changes and observations in the last lines induce the following change propagation behavior: 1. When the `check` is demanded the first time, it executes the condition, and `den` holds `2`, which is non-zero. Hence, the `else` branch executes `get!(div)`, which demands the output of the division, `21`. 2. After this first observation of `check`, the programmer changes `den` to `0`, and re-demands the output of `check`. In response, change propagation first re-executes the condition (not the division), and the condition branches to the `then` branch, resulting in `None`; in particular, it does _not_ re-demand the `div` node, though this node still exists in the DCG. 3. Next, the programmer changes `den` back to its original value, `2`, and re-demands the output of `check`. In response, change propagation re-executes the condition, which re-demands the output of `div`. Change propagation attempts to "clean" the `div` node before re-executing it. To do so, it compares its _last observations_ of `num` and `den` to their current values, of `42` and `2`, respectively. In so doing, it finds that these earlier observations match the current values. Consequently, it _reuses_ the output of the division (`21`) _without_ having to re-execute the division. For a graphical illustration of this behavior, see [these slides](https://github.com/cuplv/adapton-talk/blob/master/adapton-example--div-by-zero/). In the academic literature on Adapton, we refer to this three-step pattern as _switching_: The demand of `div` switches from being present (in step 1) to absent (in step 2) to present (in step 3). Past work on self-adjusting computation does not support this switching pattern directly: Because of its change propagation semantics, it would "forget" the division in step 2, and rerun it _from-scratch_ in step 3. Furthermore, some other change propagation algorithms base their re-execution schedule on "node height" (of the graph's topological ordering). These algorithms may also have undesirable behavior. In particular, they may re-execute the division in step 2, though it is not presently in demand. For an example, see [this gist](https://gist.github.com/khooyp/98abc0e64dc296deaa48). Use `force_map` for finer-grained dependence tracking ====================================================== Below, we show that using `force_map` prunes the dirtying phase of change propagation; this test traces the engine, counts the number of dirtying steps, and ensures that this count is zero, as expected. ``` # #[macro_use] extern crate adapton; # fn main() { use adapton::macros::*; use adapton::engine::*; use adapton::reflect; manage::init_dcg(); // Trace the behavior of change propagation; ensure dirtying works as expected reflect::dcg_reflect_begin(); let pair = cell!((1234, 5678)); let pair1 = pair.clone(); let t = thunk![{ // Project the first component of pair: let fst = force_map(&pair, |_,x| x.0); fst + 100 }]; // The output is `1234 + 100` = `1334` assert_eq!(force(&t), 1334); // Update the second component of the pair; the first is still 1234 set(&pair1, (1234, 8765)); // The output is still `1234 + 100` = `1334` assert_eq!(force(&t), 1334); // Assert that nothing was dirtied (due to using `force_map`) let traces = reflect::dcg_reflect_end(); let counts = reflect::trace::trace_count(&traces, None); assert_eq!(counts.dirty.0, 0); assert_eq!(counts.dirty.1, 0); # } ``` Nominal memoization: Toy Examples =================================== Adapton offers nominal memoization, which uses first-class _names_ (each of type `Name`) to identify cached computations and data. Behind the scenes, these names control how and when the engine _overwrites_ cached data and computations. As such, they permit patterns of programmatic _cache eviction_. For a simple illustration, we memoize several function calls to `sum` with different names and arguments. In real applications, the memoized function typically performs more work than summing two machine words. :) ``` # #[macro_use] extern crate adapton; # fn main() { use adapton::macros::*; use adapton::engine::*; use adapton::reflect; // create an empty DCG (demanded computation graph) manage::init_dcg(); // a simple function (memoized below for illustration purposes; // probably actually not worth it!) fn sum(x:usize, y:usize) -> usize { x + y } // Optional: Traces what the engine does below (for diagnostics, testing, illustration) reflect::dcg_reflect_begin(); let nm_a_0 : Name = name_of_str("a"); // name "a" let nm_a_1 : Name = name_of_str("a"); // name "a" (another copy) let nm_b_0 : Name = name_of_str("b"); // name "b" let nm_b_1 : Name = name_of_str("b"); // name "b" (another copy) // create a memo entry, named "a", that remembers that `sum(42,43) = 85` let res1 : usize = memo!(nm_a_0 =>> sum, x:42, y:43); // same name "a", same arguments (42, 43) => reuses the memo entry above for `res1` let res2 : usize = memo!(nm_a_1 =>> sum, x:42, y:43); // different name "b", same arguments (42, 43) => will *not* match `res1`; creates a new entry let res3 : usize = memo!(nm_b_0 =>> sum, x:42, y:43); // same name "b", different arguments; will *overwrite* entry named "b" with new args & result let res4 : usize = memo!(nm_b_1 =>> sum, x:55, y:66); // Optional: Assert what happened above, in terms of analytical counts let traces = reflect::dcg_reflect_end(); let counts = reflect::trace::trace_count(&traces, None); // Editor allocated two thunks ("a" and "b") assert_eq!(counts.alloc_fresh.0, 2); // Editor allocated one thunk without changing it ("a", with same args) assert_eq!(counts.alloc_nochange.0, 1); // Editor allocated one thunk by changing it ("b", different args) assert_eq!(counts.alloc_change.0, 1); // Archivist allocated nothing assert_eq!(counts.alloc_fresh.1, 0); # drop((res1,res2,res3,res4)); # } ``` Some notes about the code above: - **Callsite argument names**: The macro `memo!` relies on programmer-supplied variable names in its macro expansion of these call sites, shown as `x` and `y` in the uses above. These can be chosen arbitrarily: So long as these symbols are distinct from one another, they can be _any_ symbols, and need not actually match the formal argument names. - **Type arguments**: If the function call expects type arguments, `memo!` accomodates these calls with alternative syntax. - **Spurious arguments**: If the function call expects some later arguments that do not implement `Eq`, but are _functionally determined_ by earlier ones that do (including the supplied `Name`), `memo!` accomodates these calls with alternative syntax. We call these arguments "spurious", since the Adapton engine does _not check_ their identity when performing change propagation. Common examples include function values (e.g., anonymous closures). Nominal Firewalls =================== This example demonstrates how nominal allocation mixes dirtying and cleaning behind the scenes: when the input changes, dirtying proceeds incrementally through the edges of the DCG, _during cleaning_. In some situations (Run 2, below), nominal allocation prevents dirtying from cascading, leading to finer-grained dependency tracking, and more incremental reuse. One might call this design pattern _"nominal firewalls"_ (thanks to @nikomatsakis for suggesting the term "firewall" in this context). First, consider this DCG: ``` // cell +---- Legend ------------------+ // a | [ 2 ] ref cell holding 2 | // [ 2 ] | (g) thunk named 'g' | // ^ | ----> force/observe edge | // | force | --->> allocation edge | // | 2 +------------------------------+ // | // | cell cell // | alloc 4 b force 4 alloc 4 c // (g)------------->>[ 4 ]<--------------(h)-------------->>[ 4 ] // ^ ^ // | force | force h, // | returns b | returns c // | | // (f)------------------------------------+ // ^ // | force f, // | returns cell c // | // (root of demand) ``` In this graph, the ref cell `b` acts as the "firewall". Below, we show a particular input change for cell `a` where a subcomputation `h` is never dirtied nor cleaned by change propagation (input change 2 to -2). We show another change to the same input where this subcomputation `h` *is* _eventually_ dirtied and cleaned by Adapton, though not immediately (input change -2 to 3). Here's the Rust code for generating this DCG, and these changes to its input cell, named `"a"`: ``` # #[macro_use] extern crate adapton; # fn main() { use adapton::macros::*; use adapton::engine::*; fn demand_graph(a: Art<i32>) -> Art<i32> { let_memo!{ c =(f)= { let a = a.clone(); let_memo!{ b =(g)={ let x = get!(a); let_cell!{b = x * x; b }}; c =(h)={ let x = get!(b); let_cell!{c = if x < 100 { x } else { 100 }; c }}; c }}; c } } manage::init_dcg(); // 1. Initialize input cell "a" to hold 2, and do the computation illustrated above: let _ = demand_graph(let_cell!{a = 2; a}); // 2. Change input cell "a" to hold -2, and do the computation illustrated above: let _ = demand_graph(let_cell!{a = -2; a}); // 3. Change input cell "a" to hold 3, and do the computation illustrated above: let _ = demand_graph(let_cell!{a = 3; a}); # } ``` In this example DCG, thunk `f` allocates and forces two sub-computations, thunks `g` and `h`. The first observes the input `a` and produces an intermediate result (ref cell `b`); the second observes this intermediate result and produces a final result (ref cell `c`), which both thunks `h` and `f` return as their final result. **Run 1.** In the first computation, the input cell `a` holds 2, and the final resulting cell `c` holds `4`. **Run 2.** When the input cell `a` changes, e.g., from 2 to -2, thunks `f` and `g` are dirtied. Thunk `g` is dirty because it observes the changed input. Thunk `f` is dirty because it demanded (observed) the output of thunk `g` in the extent of its own computation. _Importantly, thunk `h` is *not* immediately dirtied when cell `a` changes._ In a sense, cell `a` is an indirect ("transitive") input to thunk `h`. This fact may suggest that when cell `a` is changed from 2 to -2, we should dirty thunk `h` immediately. However, thunk `h` is related to this input only by reading a *different* ref cell (ref cell b) that depends, indirectly, on cell `a`, via the behavior of thunk `g`, on which thunk `h` does *not* directly depend: thunk `h` does not force thunk `g`. Rather, when thunk `f` is re-demanded, Adapton will necessarily perform a cleaning process (aka, "change propagation"), re-executing `g`, its immediate dependent, which is dirty. Since thunk `g` merely squares its input, and 2 and -2 both square to 4, the output of thunk `g` will not change in this case. Consequently, the observers of cell `b`, which holds this output, will not be dirtied or re-executed. In this case, thunk `h` is this observer. In situations like these, Adapton's dirtying + cleaning algorithms do not dirty nor clean thunk `h`. In sum, under this change, after `f` is re-demanded, the cleaning process will first re-execute `g`, the immediate observer of cell `a`. Thunk `g` will again allocate cell `b` to hold 4, the same value as before. It also yields this same cell pointer (to cell `b`). Consequently, thunk `f` is not re-executed, and is cleaned. Meanwhile, the outgoing (dependency) edges thunk of `h` are never dirtied. **Run 3.** For some other change, e.g., from 2 to 3, thunk `h` would _eventually_ be dirtied and cleaned. */ // Adapton uses memoization under the covers, which needs an efficient // mechanism to search for function pointers and compare them for // equality. // // Meanwhile, Rust does not provide Eq and Hash implementations for // trait Fn. So, to identify Rust functions as values that we can // hash and compare, we need to bundle additional static information // along with the function pointer as use this data as a proxy for the // function itself. The idea is that this information uniquely // identifies the function pointer (i.e., two distinct functions will // always have two distinct identities). // use std::cell::RefCell; use std::fmt::{Formatter,Result,Debug}; pub use std::rc::Rc; thread_local!(static NAME_COUNTER: RefCell<usize> = RefCell::new(0)); /// Program points: used by the Adapton engine to distinguish different memoized functions. #[derive(PartialEq,Eq,Clone,Hash)] pub struct ProgPt { // Symbolic identity, in Rust semantics: pub symbol:&'static str, // via stringify!(...) // module:Rc<String>, // via module!() // Location in local filesystem: //pub file:&'static str, // via file!() //pub line:u32, // via line!() //pub column:u32, // via column!() } impl Debug for ProgPt { fn fmt(&self, f: &mut Formatter) -> Result { self.symbol.fmt(f) } } /// Convenience function: A global counter for creating unique names, /// e.g., in unit tests. Avoid using this outside of unit tests. pub fn bump_name_counter() -> usize { NAME_COUNTER.with(|ctr|{let c = *ctr.borrow(); *ctr.borrow_mut() = c + 1; c}) } /// Generate a "program point", used as a unique ID for memoized functions. #[macro_export] macro_rules! prog_pt { ($symbol:expr) => {{ ProgPt{ symbol:$symbol, //file:file!(), //line:line!(), //column:column!(), } }} } /// Convenience wrapper for `engine::force` #[macro_export] macro_rules! get { ($art:expr) => {{ force(&($art)) }} } /// Convenience wrapper for `engine::cell` /// /// Warning: Uses a global counter to choose a unique name. This _may_ /// be appopriate for the Editor role, but is never appropriate for /// the Archivist role. #[macro_export] macro_rules! cell { ($value:expr) => {{ cell(name_of_usize(bump_name_counter()), $value) }} ; ($nm:ident =>>> $value:expr) => {{ cell(name_of_str(stringify($ident)), $value) }} } /// Convenience wrapper for `engine::thunk` /// /// Warning: When not given a name, this macro uses a global counter /// to choose a unique name. This _may_ be appopriate for the Editor /// role, but is never appropriate for the Archivist role. #[macro_export] macro_rules! thunk { [ $suspended_body:expr ] => {{ thunk (ArtIdChoice::Nominal(name_of_usize(bump_name_counter())), prog_pt!(stringify!("anonymous")), Rc::new(Box::new( move |(),()|{ $suspended_body })), (), () ) }} ; [ $nm:ident =>>> $suspended_body:expr ] => {{ thunk!(name_of_str(stringify!($nm)), $suspended_body) }} ; [ $nm:expr =>> $suspended_body:expr ] => {{ thunk (ArtIdChoice::Nominal($nm), prog_pt!(stringify!("anonymous")), Rc::new(Box::new( move |(),()|{ $suspended_body })), (), () ) }} ; ( $nm:expr =>> $f:ident :: < $( $ty:ty ),* > , $( $lab:ident : $arg:expr ),* ) => {{ thunk (ArtIdChoice::Nominal($nm), prog_pt!(stringify!($f)), Rc::new(Box::new( |args, _|{ let ($( $lab ),*, _) = args ; $f :: < $( $ty ),* >( $( $lab ),* ) })), ( $( $arg ),*, ()), () ) }} ; ( $nm:expr =>> $f:path , $( $lab:ident : $arg:expr ),* ) => {{ thunk (ArtIdChoice::Nominal($nm), prog_pt!(stringify!($f)), Rc::new(Box::new( |args, _|{ let ($( $lab ),*, _) = args ; $f ( $( $lab ),* ) })), ( $( $arg ),*, () ), () ) }} ; ( $f:ident :: < $( $ty:ty ),* > , $( $lab:ident : $arg:expr ),* ) => {{ thunk (ArtIdChoice::Structural, prog_pt!(stringify!($f)), Rc::new(Box::new( |args, _|{ let ($( $lab ),*, _) = args ; $f :: < $( $ty ),* >( $( $lab ),* ) })), ( $( $arg ),*, () ), () ) }} ; ( $f:path , $( $lab:ident : $arg:expr ),* ) => {{ thunk (ArtIdChoice::Structural, prog_pt!(stringify!($f)), Rc::new(Box::new( |args, _|{ let ($( $lab ),*, _) = args ; $f ( $( $lab ),* ) })), ( $( $arg ),*, () ), () ) }} ; ( $nm:expr =>> $f:ident =>> < $( $ty:ty ),* > , $( $lab1:ident : $arg1:expr ),* ;; $( $lab2:ident : $arg2:expr ),* ) => {{ let t = thunk (ArtIdChoice::Nominal($nm), prog_pt!(stringify!($f)), Rc::new(Box::new( |args1, args2|{ let ($( $lab1 ),*, _) = args1 ; let ($( $lab2 ),*, _) = args2 ; $f :: < $( $ty ),* > ( $( $lab1 ),* , $( $lab2 ),* ) })), ( $( $arg1 ),*, () ), ( $( $arg2 ),*, () ), ); t }} ; } /// Convenience wrapper for `engine::thunk` and `engine::force`: /// creates a thunk and immediately forces it. #[macro_export] macro_rules! memo { ( $nm:expr =>> $f:ident :: < $( $ty:ty ),* > , $( $lab:ident : $arg:expr ),* ) => {{ let t = thunk (ArtIdChoice::Nominal($nm), prog_pt!(stringify!($f)), Rc::new(Box::new( |args, _|{ let ($( $lab ),*) = args ; $f :: < $( $ty ),* >( $( $lab ),* ) })), ( $( $arg ),*, ), () ); force(&t) }} ; ( $nm:expr =>> $f:path , $( $lab:ident : $arg:expr ),* ) => {{ let t = thunk (ArtIdChoice::Nominal($nm), prog_pt!(stringify!($f)), Rc::new(Box::new( |args, _|{ let ($( $lab ),*) = args ; $f ( $( $lab ),* ) })), ( $( $arg ),* ), () ); force(&t) }} ; ( $f:ident :: < $( $ty:ty ),* > , $( $lab:ident : $arg:expr ),* ) => {{ let t = thunk (ArtIdChoice::Structural, prog_pt!(stringify!($f)), Rc::new(Box::new( |args, _|{ let ($( $lab ),*) = args ; $f :: < $( $ty ),* >( $( $lab ),* ) })), ( $( $arg ),* ), () ); force(&t) }} ; ( $f:path , $( $lab:ident : $arg:expr ),* ) => {{ let t = thunk (ArtIdChoice::Structural, prog_pt!(stringify!($f)), Rc::new(Box::new( |args, _|{ let ($( $lab ),*, _) = args ; $f ( $( $lab ),* ) })), ( $( $arg ),*, () ), () ); force(&t) }} ; ( $nm:expr =>> $f:path , $( $lab1:ident : $arg1:expr ),* ;; $( $lab2:ident : $arg2:expr ),* ) => {{ let t = thunk (ArtIdChoice::Nominal($nm), prog_pt!(stringify!($f)), Rc::new(Box::new( |args1, args2|{ let ($( $lab1 ),*, _) = args1 ; let ($( $lab2 ),*, _) = args2 ; $f ( $( $lab1 ),* , $( $lab2 ),* ) })), ( $( $arg1 ),*, () ), ( $( $arg2 ),*, () ), ); force(&t) }} ; ( $nm:expr =>> $f:ident =>> < $( $ty:ty ),* > , $( $lab1:ident : $arg1:expr ),* ;; $( $lab2:ident : $arg2:expr ),* ) => {{ let t = thunk (ArtIdChoice::Nominal($nm), prog_pt!(stringify!($f)), Rc::new(Box::new( |args1, args2|{ let ($( $lab1 ),*, _) = args1 ; let ($( $lab2 ),*, _) = args2 ; $f :: < $( $ty ),* > ( $( $lab1 ),* , $( $lab2 ),* ) })), ( $( $arg1 ),*, () ), ( $( $arg2 ),*, () ), ); force(&t) }} ; } /// Similar to `memo!`, except return both the thunk and its observed (`force`d) value. #[macro_export] macro_rules! eager { ( $nm:expr =>> $f:ident :: < $( $ty:ty ),* > , $( $lab:ident : $arg:expr ),* ) => {{ let t = thunk (ArtIdChoice::Nominal($nm), prog_pt!(stringify!($f)), Rc::new(Box::new( |args, _|{ let ($( $lab ),*) = args ; $f :: < $( $ty ),* >( $( $lab ),* ) })), ( $( $arg ),*, ), () ); let res = force(&t) ; (t, res) }} ; ( $nm:expr =>> $f:path , $( $lab:ident : $arg:expr ),* ) => {{ let t = thunk (ArtIdChoice::Nominal($nm), prog_pt!(stringify!($f)), Rc::new(Box::new( |args, _|{ let ($( $lab ),*) = args ; $f ( $( $lab ),* ) })), ( $( $arg ),* ), () ); let res = force(&t) ; (t, res) }} ; ( $f:ident :: < $( $ty:ty ),* > , $( $lab:ident : $arg:expr ),* ) => {{ let t = thunk (ArtIdChoice::Structural, prog_pt!(stringify!($f)), Rc::new(Box::new( |args, _|{ let ($( $lab ),*) = args ; $f :: < $( $ty ),* >( $( $lab ),* ) })), ( $( $arg ),* ), () ); let res = force(&t) ; (t, res) }} ; ( $f:path , $( $lab:ident : $arg:expr ),* ) => {{ let t = thunk (ArtIdChoice::Structural, prog_pt!(stringify!($f)), Rc::new(Box::new( |args, _|{ let ($( $lab ),*, _) = args ; $f ( $( $lab ),* ) })), ( $( $arg ),*, () ), () ); let res = force(&t) ; (t, res) }} ; ( $nm:expr =>> $f:ident =>> < $( $ty:ty ),* > , $( $lab1:ident : $arg1:expr ),* ;; $( $lab2:ident : $arg2:expr ),* ) => {{ let t = thunk (ArtIdChoice::Nominal($nm), prog_pt!(stringify!($f)), Rc::new(Box::new( |args1, args2|{ let ($( $lab1 ),*, _) = args1 ; let ($( $lab2 ),*, _) = args2 ; $f :: < $( $ty ),* > ( $( $lab1 ),* , $( $lab2 ),* ) })), ( $( $arg1 ),*, () ), ( $( $arg2 ),*, () ), ); let res = force(&t) ; (t, res) }} ; } /// Convenience wrapper: Call a function and place the result into an `engine::cell`. #[macro_export] macro_rules! cell_call { ( $nm:expr =>> $f:ident :: < $( $ty:ty ),* > , $( $lab:ident : $arg:expr ),* ) => {{ let res = { $f :: < $( $ty ),* >( $( $arg ),*, ) } ; let cell = cell($nm, res) ; cell }} ; ( $nm:expr =>> $f:ident , $( $lab:ident : $arg:expr ),* ) => {{ let res = { $f ( $( $arg ),*, ) } ; let cell = cell($nm, res) ; cell }} } /** Let-bind a nominal ref cell via `cell`, using the let-bound variable identifier as its name. Permits sequences of bindings. Example usage: [Adapton Example: Nominal firewalls](https://docs.rs/adapton/0/adapton/macros/index.html#nominal-firewalls). */ #[macro_export] macro_rules! let_cell { { $var:ident = $rhs:expr; $body:expr } => {{ { let name = name_of_str(stringify!($var)); let value = $rhs; let $var = cell(name, value); $body } }}; { $var1:ident = $rhs1:expr ; $( $var2:ident = $rhs2:expr ),+ ; $body:expr} => {{ let_cell!($var1 = $rhs1; let_cell!( $( $var2 = $rhs2 ),+ ; $body )) }}; } /** Let-bind a nominal thunk via `thunk!`, without forcing it. Permits sequences of bindings. */ #[macro_export] macro_rules! let_thunk { { $var:ident = $rhs:expr; $body:expr } => {{ let name = name_of_str(stringify!($var)); let $var = thunk![name =>> $rhs]; $body }}; { $var1:ident = $rhs1:expr ; $( $var2:ident = $rhs2:expr ),+ ; $body:expr} => {{ let_thunk!($var1 = $rhs1; let_thunk!( $( $var2 = $rhs2 ),+ ; $body )) }}; } /** Let-bind a nominal thunk, force it, and let-bind its result. Permits sequences of bindings. Example usage: [Adapton Example: Nominal firewalls](https://docs.rs/adapton/0/adapton/macros/index.html#nominal-firewalls). */ #[macro_export] macro_rules! let_memo { { $var:ident = ( $thkvar1:ident ) = $rhs:expr; $body:expr } => {{ let name = name_of_str(stringify!($thkvar1)); let $thkvar1 = thunk![name =>> $rhs]; let $var = get!($thkvar1); $body }}; { $var1:ident = ( $thkvar1:ident ) = $rhs1:expr ; $( $var2:ident = ( $thkvar2:ident ) = $rhs2:expr ),+ ; $body:expr} => {{ let_memo!($var1 = ( $thkvar1 ) = $rhs1; let_memo!( $( $var2 = ( $thkvar2 ) = $rhs2 ),+ ; $body )) }}; } #[test] fn test_let_macros() { use adapton::macros::*; use adapton::engine::*; fn demand_graph(a: Art<i32>) -> Art<i32> { let c : Art<i32> = get!(let_thunk!{f = { let a = a.clone(); let b : Art<i32> = get!(let_thunk!{g = {let x = get!(a); let_cell!{b = x * x; b}}; g}); let c : Art<i32> = get!(let_thunk!{h = {let x = get!(b); let_cell!{c = if x < 100 { x } else { 100 }; c}}; h}); c}; f}); return c }; manage::init_dcg(); // 1. Initialize input cell "a" to hold 2, and do the computation illustrated above: let _ = demand_graph(cell(name_of_str("a"), 2)); // 2. Change input cell "a" to hold -2, and do the computation illustrated above: let _ = demand_graph(cell(name_of_str("a"), -2)); // 3. Change input cell "a" to hold 3, and do the computation illustrated above: let _ = demand_graph(cell(name_of_str("a"), 3)); } #[test] fn test_memo_macros() { use adapton::macros::*; use adapton::engine::*; fn demand_graph(a: Art<i32>) -> Art<i32> { let_memo!{c =(f)= { let a = a.clone(); let_memo!{b =(g)= {let x = get!(a); let_cell!{b = x * x; b}}; c =(h)= {let x = get!(b); let_cell!{c = if x < 100 { x } else { 100 }; c}}; c}}; c} } manage::init_dcg(); // 1. Initialize input cell "a" to hold 2, and do the computation illustrated above: let _ = demand_graph(cell(name_of_str("a"), 2)); // 2. Change input cell "a" to hold -2, and do the computation illustrated above: let _ = demand_graph(cell(name_of_str("a"), -2)); // 3. Change input cell "a" to hold 3, and do the computation illustrated above: let _ = demand_graph(cell(name_of_str("a"), 3)); }