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Commit 33f7a5b
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Cong Zhang
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[cl] Support nested conditionals and break_loop in task-scheduling domain loops
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@@ -30,7 +30,82 @@ The manager also computes a warp-group-rounded initial register budget and threa
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Automatic value routing hides storage positions from callback authors. Each callback receives its routed inputs after the `StageInfo` argument and returns the values declared by its captured work method. The frozen `DeviceStep` performs the corresponding value-stack operations, while `DeviceTask.make_context(tasks_inputs)` creates the immutable execution context. The tuple representation remains an internal compiler detail; no placeholder or named routing slot is exposed to resource authors.
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`outputs=N` creates `N` independent lexical `ScheduleValue` instances. A work call returns one value directly or a tuple that can be unpacked normally, and its device callback returns the same number of runtime values. A value produced inside a conditional or domain loop cannot escape that scope accidentally. A domain loop(don't support while senmantic and contional early break) that needs state across iterations uses `domain_loop(start, end, step, body, *initial_values)`, with one callback parameter per initial value. The schedule builder invokes `body(*iter_values)` once while capturing the loop body, so every resource call remains a schedule step. The callback must return one work-call output per input; those outputs become both the next-iteration values and the post-loop results. The device adapter preserves zero-trip pass-through and materializes the backedge without exposing routing positions to callbacks. Work methods read the current device offset from `stage_info.loop_offset`; it is not a callback parameter or a routed value. Loop bodies may use `first_iter()`, `last_iter()`, and `every(period, start=...)` to capture iteration-guarded regions.
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`outputs=N` creates `N` independent lexical `ScheduleValue` instances. A work call returns one value directly or a tuple that can be unpacked normally, and its device callback returns the same number of runtime values. A value produced inside a conditional or domain loop cannot escape that scope accidentally. A domain loop that needs state across iterations uses `domain_loop(start, end, step, body, *initial_values)`, with one callback parameter per initial value. The schedule builder invokes `body(*iter_values)` once while capturing the loop body, so every resource call remains a schedule step. The callback must return one work-call output per input; those outputs become both the next-iteration values and the post-loop results. The device adapter preserves zero-trip pass-through and materializes the backedge without exposing routing positions to callbacks. Work methods read the current device offset from `stage_info.loop_offset`; it is not a callback parameter or a routed value. Loop bodies may use `first_iter()`, `last_iter()`, and `every(period, start=...)` to capture iteration-guarded regions.
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`when_true()` and `when_false()` regions may nest, including inside iteration
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guards. An inner region executes only when every enclosing guard is active.
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Predicates and other work outputs produced inside a branch may be used by its
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nested regions, but cannot escape to a parent or sibling scope. Reusing the same
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routed predicate preserves true/false correlation in host analysis.
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The runnable `tutorial/01_copy_basics/04_copy_tma_nested_conditional.py` example
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extends the conditional TMA copy with all four two-level true/false combinations
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and a third-level condition. It checks the copied tensor and exact per-row branch
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markers, including the absence of writes from inactive branches:
`break_loop()` exits the enclosing domain loop immediately, including from a
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nested conditional. It skips the rest of that iteration and resumes after the
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loop. The context-manager handle provides the same operation:
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```python
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with ts.domain_loop(num_tiles) as loop:
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done = resource.is_done()
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with ts.when_true(done):
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loop.break_loop()
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resource.process()
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```
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Use `ts.break_loop()` in a functional loop body. A bare break skips the normal
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backedge: returned loop-carried results retain their values from the last
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completed iteration (or the initial values if the first iteration breaks).
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Pass explicit results to return values computed during the interrupted iteration:
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```python
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initial = resource.init_state()
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defbody(state):
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updated = resource.advance_state(state)
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done = resource.is_done(updated)
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with ts.when_true(done):
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ts.break_loop(updated)
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return updated
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result = ts.domain_loop(0, num_tiles, 1, body, initial)
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resource.consume_state(result)
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```
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For multiple carried inputs, use `ts.break_loop(next_count, next_total)` in the
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same order as the functional loop's inputs. Supply all carried results or none.
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Each explicit argument must be a visible routed `ScheduleValue` with the same
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pipeline-stage provenance and a compatible CUDA type as its carried input;
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ordinary constants must first be returned by a work method. Values created
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inside a nested branch may be returned directly by a break in that branch.
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The exit values are captured before branch-local routes are discarded. Wrong
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arity, foreign-schedule values, and values escaping a sibling/child scope are
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rejected during capture; CUDA types are checked during device compilation.
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An untaken break uses the normal body return values, and a zero-trip loop still
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returns its initial values.
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Side effects and pipeline-state updates performed before the break are retained.
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A break exits only the domain loop, so an enclosing `work_tile_loop()` continues.
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`last_iter()` still means the last iteration of the declared range; it is not an
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exit hook. Breaks outside a domain loop and expired loop handles are rejected.
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Unbounded while loops remain unsupported.
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The nested-copy tutorial also accepts `--stop-row 5`. Both producer and consumer
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break before acquiring/waiting for row 5, and the example verifies that the
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uncopied output and trace remain zero. A pipeline schedule must ensure that its
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producer and consumer exit consistently and finish any acquired work before
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exiting; `break_loop()` does not implicitly release or drain an interrupted step.
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Host expansion honors breaks for its selected opaque-condition assignment and
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representative loop bounds, including zero-trip loops. Opaque assignments remain
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fixed during each explored execution; these checks do not prove safety for all
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possible iteration-varying runtime predicate sequences.
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`StageInfo` contains the current `stage_idx`, `phase`, selected full `barrier`, zero-based iteration count, loop offset/bounds, work label, and owning `ExecutionContext`; loop offset/bounds are `None` for peeled work outside a domain loop. This lets pipeline payload work use `stage_info.barrier` without knowing how barrier arrays are stored by the device manager.
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