Real-GPU lane on dgx-spark, image graphistry/test-rapids-official:26.02-gfql-polars (cudf 26.02.01, cupy 13.6.0, polars 1.35.2), TEST_CUDF=1, suites test_chain.py / test_hop.py / test_chain_alias_column_collision.py / tests/compute/gfql/**. At master 86de0f5: 13227 passed / 93 failed / 47 xfailed / 4 xpassed. The same 93 fail at the #2056 and #2060 heads (set difference vs master empty), so this is an image/runtime capability gap, not a branch effect:
tests/compute/gfql/cypher/test_grouped_aggregate_fused_polars.py (matches_eager_twin_and_pandas ×71, serves_total_order_shapes ×8, serves_the_graph_benchmark_shapes ×2, places_nulls_the_opencypher_way ×2): on engine='polars-gpu' the fused lane raises NotImplementedError: GFQL engine='polars-gpu': this query plan is not fully GPU-executable on the installed cudf-polars (NO-CHEATING: we raise rather than silently run it on CPU …) where the tests expect the lane to serve.
tests/compute/gfql/test_strictness_levels.py polars-gpu cases (absent_return_property_is_null ×2, warns_once, strict_absent_names_raise, quiet_emits_no_warning): same decline.
These pins never run in CI (#1890: polars-gpu executes in no CI lane), so the dgx receipt is the only place they show. Either the fused lane declines to the CPU polars plan on this cudf-polars (typed decline, tests adjusted to expect it on that runtime) or the plan is made GPU-executable; until then every real-GPU receipt carries these 93 as the known baseline.
Real-GPU lane on dgx-spark, image
graphistry/test-rapids-official:26.02-gfql-polars(cudf 26.02.01, cupy 13.6.0, polars 1.35.2),TEST_CUDF=1, suites test_chain.py / test_hop.py / test_chain_alias_column_collision.py / tests/compute/gfql/**. At master 86de0f5: 13227 passed / 93 failed / 47 xfailed / 4 xpassed. The same 93 fail at the #2056 and #2060 heads (set difference vs master empty), so this is an image/runtime capability gap, not a branch effect:tests/compute/gfql/cypher/test_grouped_aggregate_fused_polars.py(matches_eager_twin_and_pandas ×71, serves_total_order_shapes ×8, serves_the_graph_benchmark_shapes ×2, places_nulls_the_opencypher_way ×2): onengine='polars-gpu'the fused lane raisesNotImplementedError: GFQL engine='polars-gpu': this query plan is not fully GPU-executable on the installed cudf-polars (NO-CHEATING: we raise rather than silently run it on CPU …)where the tests expect the lane to serve.tests/compute/gfql/test_strictness_levels.pypolars-gpu cases (absent_return_property_is_null ×2, warns_once, strict_absent_names_raise, quiet_emits_no_warning): same decline.These pins never run in CI (#1890: polars-gpu executes in no CI lane), so the dgx receipt is the only place they show. Either the fused lane declines to the CPU polars plan on this cudf-polars (typed decline, tests adjusted to expect it on that runtime) or the plan is made GPU-executable; until then every real-GPU receipt carries these 93 as the known baseline.