fix(sp21): T2.2 Phase 8.5 — wire factored-action branch sizes into closure-based eval (atomic)
v7 smoke (train-fv4s8, commit 23b89a90e) eval pod hit
CUDA_ERROR_ILLEGAL_ADDRESS at fold 0:
Error: DQN fold 0 GPU evaluation failed: GpuBacktestEvaluator::evaluate
failed for fold 0: Model error: eval_done_event synchronize:
DriverError(CUDA_ERROR_ILLEGAL_ADDRESS, "an illegal memory access was encountered")
The {:#} anyhow chain fix from Phase 8.3+9 made the failure mode visible.
Diagnosis from code (no second smoke needed): the closure-based
evaluate() path never sets b0_size..b3_size, leaving them at the
default 0. env_step kernel's decode_*_4b helpers do action/(b1*b2*b3)
→ divide-by-zero → garbage decoded indices → out-of-bounds memory
read → CUDA_ERROR_ILLEGAL_ADDRESS at next event-sync.
The production `evaluate_dqn_graphed` path sets b-sizes via
`ensure_action_select_ready` (which also lazy-allocates intent buffers
the closure path doesn't need). The closure-based `evaluate()` path
used by eval-baseline never calls it.
Fix:
1. Add pub fn `GpuBacktestEvaluator::set_branch_sizes(&mut self,
dqn_cfg: &DqnBacktestConfig)` — sets b0..b3_size only, no
buffer allocation.
2. Add defensive guard in `evaluate()` that bails with
`MLError::ConfigError` if any b-size is zero. Future regressions
produce a clear error instead of an opaque CUDA illegal-address.
3. Wire `set_branch_sizes(&dqn_cfg)` call in
`evaluate_dqn_fold_gpu` between `DqnBacktestConfig::from_network_dims`
and the closure-based `evaluator.evaluate(...)`.
Pearls honoured:
- feedback_no_hiding: zero-b-size now surfaces as ConfigError
rather than CUDA illegal-address downstream
- feedback_no_partial_refactor: closure-path was a partial wire-up
from pre-factored-action days; set_branch_sizes brings it into
parity with the CUBLAS production path for action decoding
- pearl_no_deferrals_for_complementary_fixes: v7's chain-exposing
fix surfaced this; lands immediately not after another smoke
Verification:
cargo check -p ml --example evaluate_baseline --features cuda # clean
Note on PPO/supervised paths:
Their evaluate() calls also lack set_branch_sizes and will now
trip the defensive guard. Those paths haven't actually run eval
since STATE_DIM grew past 54 — the silent failure mode had been
masking it. Future Phase will either wire their action conventions
(PPO: 5-exposure; supervised: signal thresholds) or delete the
dead paths per feedback_no_partial_refactor.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
@@ -832,6 +832,16 @@ fn evaluate_dqn_fold_gpu(
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let dqn_cfg = ml::cuda_pipeline::gpu_backtest_evaluator::DqnBacktestConfig::from_network_dims(network_dims);
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let dqn_cfg = ml::cuda_pipeline::gpu_backtest_evaluator::DqnBacktestConfig::from_network_dims(network_dims);
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// Phase 8.5 (2026-05-12) — wire factored-action branch sizes into the
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// evaluator's env_step kernel. Without this, env_step's
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// decode_direction_4b / decode_magnitude_4b / decode_order_4b /
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// decode_urgency_4b helpers divide by zero (b1*b2*b3 = 0), and the
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// GPU raises CUDA_ERROR_ILLEGAL_ADDRESS asynchronously at the next
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// event-sync. The production `evaluate_dqn_graphed` path sets these
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// via `ensure_action_select_ready`; this closure-path equivalent
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// calls the public `set_branch_sizes` setter.
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evaluator.set_branch_sizes(&dqn_cfg);
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{
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{
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// Standalone eval: closure-based forward pass.
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// Standalone eval: closure-based forward pass.
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// Training eval uses FusedTrainingCtx as QValueProvider for determinism.
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// Training eval uses FusedTrainingCtx as QValueProvider for determinism.
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@@ -1421,6 +1421,28 @@ impl GpuBacktestEvaluator {
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self.n_windows
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self.n_windows
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}
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}
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/// Set the four factored-action branch sizes from a `DqnBacktestConfig`.
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///
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/// The closure-based `evaluate()` path delegates the model forward pass
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/// to a user-supplied closure but still uses the internal `env_step`
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/// kernel to advance the simulator. `env_step` decodes flat action
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/// indices into `(dir, mag, order, urgency)` via `decode_*_4b()` helpers
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/// in `trade_physics.cuh`, which compute `action / (b1 * b2 * b3)`. If
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/// any `b*_size` is zero the helpers divide by zero, the kernel reads
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/// out-of-bounds, and CUDA raises `CUDA_ERROR_ILLEGAL_ADDRESS` at the
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/// next synchronise — exactly the v7 smoke failure mode (2026-05-12).
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///
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/// The production `evaluate_dqn_graphed` path sets these via
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/// `ensure_action_select_ready` (which also allocates intent buffers
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/// the closure path doesn't need). This setter is the closure-path
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/// equivalent — set b-sizes only, no buffer allocs.
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pub fn set_branch_sizes(&mut self, dqn_cfg: &DqnBacktestConfig) {
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self.b0_size = dqn_cfg.branch_0_size as i32;
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self.b1_size = dqn_cfg.branch_1_size as i32;
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self.b2_size = dqn_cfg.branch_2_size as i32;
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self.b3_size = dqn_cfg.branch_3_size as i32;
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}
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/// Maximum batch size that the val TLOB instance must support.
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/// Maximum batch size that the val TLOB instance must support.
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///
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///
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/// `submit_dqn_step_loop_cublas` runs TLOB once per chunk on
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/// `submit_dqn_step_loop_cublas` runs TLOB once per chunk on
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@@ -1571,6 +1593,24 @@ impl GpuBacktestEvaluator {
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{
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{
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let _nvtx = NvtxRange::new("backtest_evaluate");
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let _nvtx = NvtxRange::new("backtest_evaluate");
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// Phase 8.5 (2026-05-12) — defensive guard: `env_step` decodes flat
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// action indices into (dir, mag, order, urgency) via
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// `decode_*_4b()` helpers that divide by `b1 * b2 * b3`. If any
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// b-size is zero, the kernel divides by zero and raises
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// CUDA_ERROR_ILLEGAL_ADDRESS asynchronously at the next event-sync.
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// The production `evaluate_dqn_graphed` path sets these via
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// `ensure_action_select_ready`; closure-path callers must invoke
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// `set_branch_sizes` before `evaluate()`. Surface the requirement
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// up-front rather than crashing the CUDA context downstream.
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if self.b0_size == 0 || self.b1_size == 0 || self.b2_size == 0 || self.b3_size == 0 {
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return Err(MLError::ConfigError(format!(
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"evaluate: branch sizes unset (b0={}, b1={}, b2={}, b3={}); \
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call `set_branch_sizes(&DqnBacktestConfig)` before `evaluate()` \
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to wire factored-action decoding for env_step.",
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self.b0_size, self.b1_size, self.b2_size, self.b3_size
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)));
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}
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let state_dim = self.state_dim;
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let state_dim = self.state_dim;
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for step in 0..self.max_len {
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for step in 0..self.max_len {
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@@ -15741,3 +15741,105 @@ For volume bars with healthy policy and pnl_std ≈ 1e-5:
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If these signals fire, the Phase 7 (alpha boost via E6/E7/E8) wiring
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If these signals fire, the Phase 7 (alpha boost via E6/E7/E8) wiring
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is finally exercised end-to-end on volume bars.
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is finally exercised end-to-end on volume bars.
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## 2026-05-12 — SP21 T2.2 Phase 8.5: wire factored-action branch sizes into closure-based eval (atomic)
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### Scope (atomic single commit)
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v7 smoke (train-fv4s8, commit 23b89a90e) eval pod hit
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`CUDA_ERROR_ILLEGAL_ADDRESS` at fold 0:
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```
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Error: DQN fold 0 GPU evaluation failed: GpuBacktestEvaluator::evaluate
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failed for fold 0: Model error: eval_done_event synchronize:
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DriverError(CUDA_ERROR_ILLEGAL_ADDRESS, "an illegal memory access was encountered")
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```
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The `{:#}` anyhow-chain fix from Phase 8.3+9 made this loud (Phase 8.3+9
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was about exposing the chain — and exposing it surfaced the next bug
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in line). Diagnosis from code (no second smoke needed): the closure-
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based `evaluate()` path never sets `b0_size..b3_size` (factored-action
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branch sizes for env_step's `decode_*_4b()` helpers).
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### Root cause
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`backtest_env_step` kernel decodes flat action indices via helpers in
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`trade_physics.cuh`:
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```c
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int decode_direction_4b(int action, int b1, int b2, int b3) {
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return action / (b1 * b2 * b3); // ← divides by zero if any b_i=0
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}
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```
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The production `evaluate_dqn_graphed` path sets b-sizes via
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`ensure_action_select_ready` (which also allocates intent buffers etc).
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The closure-based `evaluate()` path used by eval-baseline DOES NOT
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call this — b-sizes default to zero (from `new()` initialiser at
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lines 1338-1341). v7's first env_step launch divides by zero, kernel
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reads garbage indices → out-of-bounds memory access → CUDA raises
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`CUDA_ERROR_ILLEGAL_ADDRESS` asynchronously at the next event-sync
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(in `launch_metrics_and_record_event`'s synchronise call).
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### Fix
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**1. New public method** `GpuBacktestEvaluator::set_branch_sizes(&mut self, dqn_cfg: &DqnBacktestConfig)`
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- Sets `b0..b3_size` from a `DqnBacktestConfig` without lazy-allocating
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intent buffers (those are needed only by the CUBLAS production path,
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not the closure path).
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- Mirror of the b-size assignment block inside the private
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`ensure_action_select_ready` but with closure-path-only scope.
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**2. Defensive guard in `evaluate()`**
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- Bails with `MLError::ConfigError` if any b-size is zero.
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- Surfaces the requirement up-front rather than crashing the CUDA
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context downstream. Future regressions to this wiring will produce
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a clear "branch sizes unset" error instead of a generic illegal-
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memory-access.
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**3. Wire `set_branch_sizes` from `evaluate_dqn_fold_gpu`**
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- Called after `DqnBacktestConfig::from_network_dims(...)` and before
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`evaluator.evaluate(...)`.
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- Only the branching closure path (the modern model's path). The
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non-branching else fallback is dead code for current models and
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will hit the new defensive guard if anyone tries to use it.
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### Files changed
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- `crates/ml/src/cuda_pipeline/gpu_backtest_evaluator.rs`:
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- `pub fn set_branch_sizes` added
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- `evaluate()` gains zero-branch-size guard
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- `crates/ml/examples/evaluate_baseline.rs`:
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- `evaluator.set_branch_sizes(&dqn_cfg)` call inserted before
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closure-based `evaluator.evaluate(...)` for DQN fold path
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- `docs/dqn-wire-up-audit.md`: this entry
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### Pearls + invariants honoured
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- **feedback_no_hiding**: defensive guard surfaces b-size zero as
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`ConfigError` rather than letting the next kernel divide by zero
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and produce an opaque `CUDA_ERROR_ILLEGAL_ADDRESS`
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- **feedback_no_partial_refactor**: the closure-based `evaluate()`
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path was a partial wire-up from the days before factored actions —
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`set_branch_sizes` makes it equivalent to the CUBLAS production
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path for action decoding
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- **pearl_no_deferrals_for_complementary_fixes**: the v7 smoke
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diagnostic (Phase 8.3+9's `{:#}` chain) exposed this; fix lands
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immediately rather than after another smoke cycle
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### Verification
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```
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cargo check -p ml --example evaluate_baseline --features cuda # clean
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```
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### Note on PPO / supervised eval paths
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These paths also call `evaluate()` without `set_branch_sizes` (lines
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~1106, ~1277). They would now fail with the new defensive guard —
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which is correct: those models have not actually run eval since
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STATE_DIM grew past the legacy 54, but the silent failure had been
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masking it. A future Phase will either wire PPO/supervised branch
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sizes correctly (PPO uses a 5-exposure action space, supervised uses
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signal thresholds — different conventions from DQN factored actions)
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or delete the dead paths per `feedback_no_partial_refactor`.
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