e2e gate: a device lane for adaptive_cartesian_gpu, and a host twin for the worst calibration row

.travis/test-integrate.sh

@@ -165,10 +165,11 @@ _ZLSTANDIN_OUT=$(python -m pytest -q -rs "$_ZLSTANDIN_TESTS" 2>&1 | tee >(cat >&
 # On a runner that PROMISES a device, any skip is bad.  The reason-matching below cannot tell
 # "there is no GPU here" from "the GPU probe itself broke": break the probe and every device
 # lane skips with a reason naming the GPU, which this would score as fine.  Measured -- an
-# unimportable module inside the e2e gate's _GPU_PROBE silently removed all 9 device lanes and
-# scored 0 bad.  RIFT_CI_REQUIRE_GPU=1 means the preflight at the top of this file already
-# proved cupy works and a device computes, so there is nothing left for a skip to legitimately
-# mean.  Measured on ldas-pcdev2 slot 0: 0 skips.
+# unimportable module inside the e2e gate's _GPU_PROBE silently removed EVERY device lane -- 9
+# of them when that was measured, and the count is not the point -- and scored 0 bad.
+# RIFT_CI_REQUIRE_GPU=1 means the preflight at the top of this file already proved cupy works
+# and a device computes, so there is nothing left for a skip to legitimately mean.  Measured on
+# ldas-pcdev2 CUDA slot 0 (A100): 0 skips.
 if [[ "${RIFT_CI_REQUIRE_GPU:-0}" == "1" ]]; then
     _ZLSTANDIN_BAD=$(echo "$_ZLSTANDIN_OUT" | grep -cE '^SKIPPED' || true)
 else
@@ -195,20 +196,20 @@ fi
 # lane here rather than a recorded defect.  Needs no network and no real event; about
 # 8-12 s per ILE arm plus ~15 s once for the distance-marginalization lookup table.
 # Its section 4 runs the same answers with a GPU VISIBLE and asserts the child reached one.
-# Those 9 lanes skip on a CPU-only runner and RUN under .gitlab-ci.yml's `gpu_integration` job
+# Those 11 lanes skip on a CPU-only runner and RUN under .gitlab-ci.yml's `gpu_integration` job
 # (RIFT_CI_REQUIRE_GPU=1, CUDA_VISIBLE_DEVICES=0, GPU container).  Skipped tests are still
 # collected, so the count below is the same on both; the SKIP GUARD after the run is what stops
 # a CPU-only pass from reading as device coverage.
 _E2E_TESTS=MonteCarloMarginalizeCode/Code/test/test_e2e_analytic_pipeline.py
-_E2E_EXPECTED=26
+_E2E_EXPECTED=29
 _E2E_FOUND=$(python -m pytest -q --collect-only "$_E2E_TESTS" 2>/dev/null | grep -c '::' || true)
 if [ "$_E2E_FOUND" -ne "$_E2E_EXPECTED" ]; then
     echo "e2e analytic gate: collected $_E2E_FOUND tests, expected $_E2E_EXPECTED" >&2
     exit 1
 fi
-# SKIP guard, as above.  This gate skips 9 of 26 on a CPU-only runner, and it has a non-GPU
+# SKIP guard, as above.  This gate skips 11 of 29 on a CPU-only runner, and it has a non-GPU
 # skip path that matters: build_event returns None when lal_path2cache is missing, which skips
-# the WHOLE module -- 26 silent skips under a green exit 0.  So a skip whose reason does not
+# the WHOLE module -- 29 silent skips under a green exit 0.  So a skip whose reason does not
 # name cupy/GPU/CUDA fails the gate.
 # Streamed, not `tee /dev/stderr` -- see the note on the stand-in gate above.  This is the gate
 # that made streaming worth having: 3-9 minutes, and silent when captured.
@@ -217,10 +218,11 @@ _E2E_OUT=$(python -m pytest -q -rs "$_E2E_TESTS" 2>&1 | tee >(cat >&2)) \
 # On a runner that PROMISES a device, any skip is bad.  The reason-matching below cannot tell
 # "there is no GPU here" from "the GPU probe itself broke": break the probe and every device
 # lane skips with a reason naming the GPU, which this would score as fine.  Measured -- an
-# unimportable module inside the e2e gate's _GPU_PROBE silently removed all 9 device lanes and
-# scored 0 bad.  RIFT_CI_REQUIRE_GPU=1 means the preflight at the top of this file already
-# proved cupy works and a device computes, so there is nothing left for a skip to legitimately
-# mean.  Measured on ldas-pcdev2 slot 0: 0 skips.
+# unimportable module inside the e2e gate's _GPU_PROBE silently removed EVERY device lane -- 9
+# of them when that was measured, and the count is not the point -- and scored 0 bad.
+# RIFT_CI_REQUIRE_GPU=1 means the preflight at the top of this file already proved cupy works
+# and a device computes, so there is nothing left for a skip to legitimately mean.  Measured on
+# ldas-pcdev2 CUDA slot 0 (A100): 0 skips.
 if [[ "${RIFT_CI_REQUIRE_GPU:-0}" == "1" ]]; then
     _E2E_BAD=$(echo "$_E2E_OUT" | grep -cE '^SKIPPED' || true)
 else

MonteCarloMarginalizeCode/Code/test/expensive_before_merging/integrators/make_e2e_calibration.py

@@ -30,12 +30,17 @@
 import test_e2e_analytic_pipeline as gate          # noqa: E402
 
 _AV, _PORTFOLIO, _GMM, _AC = gate._AV, gate._PORTFOLIO, gate._GMM, gate._AC
+_ACG = gate._ACG
 
 # (label, sampler argv, A, B, extra kwargs for _run_ile).  A is None for a prior-only lane.
 LANES = [
     ("prior-only,    AV",                        _AV,        None, 0.0, {}),
     ("prior-only,    portfolio",                 _PORTFOLIO, None, 0.0, {}),
     ("prior-only,    GMM",                       _GMM,       None, 0.0, {}),
+    # The host twin of the device prior-only adaptive_cartesian row, which sets the worst |z|
+    # in the committed table.  --n-max from the gate, not repeated here.
+    ("prior-only,    adaptive_cartesian",        _AC,        None, 0.0,
+     dict(n_max=gate._AC_N_MAX)),
     ("A=0.75 B=0,    AV",                        _AV,        0.75, 0.0, {}),
     ("A=0.75 B=0,    portfolio",                 _PORTFOLIO, 0.75, 0.0, {}),
     ("A=0.75 B=0,    GMM",                       _GMM,       0.75, 0.0, {}),
@@ -72,6 +77,15 @@
      dict(_needs_gpu=True, n_max=gate._AC_N_MAX)),
     ("GPU A=8    B=2, adaptive_cartesian", _AC, 8.0, 2.0,
      dict(_needs_gpu=True, n_max=gate._AC_N_MAX)),
+    # mcsamplerGPU STANDALONE, and the ILE driver's own default --sampler-method.  Device only:
+    # it reaches the compute_hist conversion through its own integrate/integrate_log adaptation
+    # blocks rather than through a portfolio member, and that route has no other lane.  It stops
+    # on the BUDGET at --n-max 20000 with the factor on, like adaptive_cartesian; measured, not
+    # assumed -- see _LANE_KW in the gate.
+    ("GPU prior-only, adaptive_cartesian_gpu", _ACG, None, 0.0,
+     dict(_needs_gpu=True, n_max=gate._AC_N_MAX)),
+    ("GPU A=8    B=2, adaptive_cartesian_gpu", _ACG, 8.0, 2.0,
+     dict(_needs_gpu=True, n_max=gate._AC_N_MAX)),
 ]