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test(cake_gdn): with grad, stop depending on the former no-det names of the deterministic packages - #8916
The deterministic Cake GDN training packages are flashinfer.experimental.cake_gdn_det_train, flashinfer.experimental.cake_gdn_det_train_kcp and the facade flashinfer.cake_gdn_det_train_kcp. They still carry their former names, which lack "det": flashinfer.gdn_train, flashinfer.experimental.cake_gdn_train, chunk_gdn_kcp / KcpOptions and chunk_gated_delta_rule / ChunkGatedDeltaRuleFunction / gdn_chunk_forward / gdn_chunk_backward. The KDA compatibility package flashinfer.experimental.cake_kda_train has the same problem. The package owners will delete these names in follow-up PRs and won't keep compatibility aliases.
This PR stops the non-deterministic GDN tests, benchmark and READMEs from using these former GDN and KDA names. They pass both before and after the removals. The former conv1d names used in the same files are migrated separately by the conv1d package owner (#8912). Package behavior and kernels are unchanged. The only edits to package files are three provenance docstrings: they keep the historical KDA source path and add its current det path.
Removes the test that asserted the former names are the deterministic objects.
Keeps one absence test over a single list of former spellings. That list now also covers cake_backend, cake_build and cake_l2n.
Keeps a test, checked through the det names, that this package's entries and types are not the deterministic package's.
tests/experimental/test_cake_gdn_train.py: compares against the deterministic package's det names instead of its former aliases.
test_cake_gdn_train_kcp.py and test_cake_gdn_train_kcp_build.py: KDA references now use cake_kda_det_train_kcp.cake_kcp_plan (partition_det_kcp, build_context_det_kcp) and cake_kda_det_train.cake_build.
benchmarks/bench_cake_gdn_train_kcp.py: reads LAST_CALL and graph_cache_clear for both routes from each package's cake_kcp module, because the deterministic package will stop re-exporting them at package level.
The two non-deterministic READMEs refer to the deterministic packages only by their det names.
Testing
One commit on main 3757bab, head 1d5f7bb. The first revision 802dc8a differs from it only in docstrings and the commit message. Each run used a clean tree at the named head and a tree with the former names deleted (simulated removal):
CPU at 1d5f7bb (CUDA 13.4 devel image, Python 3.14.9, torch 2.14.1+cu130): test_cake_gdn_train_kcp_api.py, test_cake_gdn_train_kcp_build.py and test_cake_gdn_train_kcp.py gave 454 passed, 7 skipped, 0 failed on both trees. pre-commit (mypy, ruff check, ruff format, ...) passes.
CPU at 802dc8a: test_cake_gdn_train.py plus the 8 test_cake_gdn_train_kcp*.py files gave 577 passed, 352 skipped, 0 failed on both trees. As a control, the old tests fail 3 on the simulated-removal tree.
GPU at 802dc8a (B200, sm_100a): 0 failed on both trees.
test_plan_parity_with_kda_on_rows skips in every environment because it needs GDN_ROWS_DIR. That skip predates this PR and is unchanged.
Follow-ups
The deterministic package owners remove the former names.
The conv1d package owner migrates the former conv1d names in these files.
A later PR aligns the deterministic= behavior of the non-deterministic facade with the shared mode rules.
Summary by CodeRabbit
Documentation
Clarified which GDN training package names refer to deterministic and non-deterministic entry points, including the distinction between legacy names and the KCP package’s own entry point.
Updated package guidance to clarify its relationship to deterministic KDA counterparts.
Bug Fixes
Corrected benchmark handling of route graph-cache clearing and last-call metadata.
…er names exist
The non-deterministic GDN tests, bench and READMEs no longer depend on the
former no-det names of the deterministic GDN packages (cake_gdn_det_train,
cake_gdn_det_train_kcp) or on the former KDA package path
(flashinfer.experimental.cake_kda_train), so they stay green before and
after those names are removed:
- test_cake_gdn_train_kcp_api.py: drop the test that the former names
(flashinfer.gdn_train, flashinfer.experimental.cake_gdn_train and the
module-level aliases of cake_gdn_det_train_kcp) are the det objects. Keep
one absence test over a single list of the former spellings, now also on
cake_backend, cake_build and cake_l2n, and a test that this package's
entries and types are not the det package's (det names only). The KDA
hygiene test refuses any import containing "cake_kda".
- test_cake_gdn_train.py: compare this package's entries with the det
package's det names instead of asserting its former aliases.
- test_cake_gdn_train_kcp.py, test_cake_gdn_train_kcp_build.py: the KDA
references use cake_kda_det_train_kcp.cake_kcp_plan (partition_det_kcp,
build_context_det_kcp) and cake_kda_det_train.cake_build.
- bench_cake_gdn_train_kcp.py: read LAST_CALL and graph_cache_clear of both
routes through the package's cake_kcp module.
- READMEs: the deterministic packages are named by their det names only.
- cake_gdn_train_kcp provenance docstrings (cake_jit.py, cake_kcp.py,
cake_kcp_plan.py) keep the historical KDA path at the cited commit and
add the file's current det KDA path (text only).
The former conv1d names used in the same files (bench, dist test, facade
docstring) are migrated by the conv1d owner's own change.
The changes clarify deterministic and non-deterministic GDN package names, update KCP parity and import checks to use deterministic KDA references, and make the benchmark access KCP state through its imported module.
The README files distinguish deterministic and non-deterministic package names. Tests check entry-point identity and reject former legacy names in package bindings and exports.
Deterministic KDA references and checks flashinfer/experimental/cake_gdn_train_kcp/cake_*.py, tests/experimental/test_cake_gdn_train_kcp.py, tests/experimental/test_cake_gdn_train_kcp_api.py, tests/experimental/test_cake_gdn_train_kcp_build.py
KCP parity tests and provenance comments use deterministic KDA package paths and names. Import checks reject KDA package imports, and the build test loads its reference from the deterministic package.
Issue 7243: The KCP parity test now uses the deterministic KDA plan names identified in the issue.
Possibly related PRs
flashinfer-ai/flashinfer#8022: Introduces the deterministic GDN KCP package and renamed API that these changes distinguish from non-deterministic names.
flashinfer-ai/flashinfer#8054: Introduces the deterministic KDA paths and KCP names used by the updated parity tests and provenance references.
Suggested labels:op: linear attention
Merge Risk: Minimal · up to 1d5f7
The naming updates and benchmark module access show no identified merge-blocking issue. Merge after normal checks pass.
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yyihuang
changed the title
test(cake_gdn_train): stop depending on the former no-det names of the deterministic packages
test(cake_gdn): with grad, stop depending on the former no-det names of the deterministic packages
Nov 6, 2026
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This PR is fine on its own. Its follow-ups have no PR yet:
The deterministic GDN single-rank package still exports names without det.flashinfer.experimental.cake_gdn_det_train exports chunk_gated_delta_rule, ChunkGatedDeltaRuleFunction, gdn_chunk_forward and gdn_chunk_backward next to the det names.
flashinfer.gdn_train still binds the old KCP names. These include KcpContext, chunk_gdn_kcp, gdn_kcp_*_bytes and kcp_partition. KDA's equivalent flashinfer.kda_train is removed in #8908.
GDN single-rank has no top-level det facade. KDA has flashinfer.cake_kda_det_train; GDN has nothing equivalent.
The non-deterministic GDN facade's deterministic= behaviour (the last follow-up listed in the description).
Please open and link the removal PR so GDN ends up with the same naming as mHC, conv1d and KDA.
Follow-up for the second item (flashinfer.gdn_train and the old KCP names): #8921 removes flashinfer.gdn_train, flashinfer.experimental.cake_gdn_train and every no-det alias of the deterministic KCP package, without aliases. It merges after this PR, #8912 and #8918. The deterministic single-rank names and a top-level deterministic single-rank facade (first and third items) will come in a separate PR, linked here when it is open. The facade's deterministic= behaviour (fourth item) is #8920.
Follow-ups for the four items in the review above:
Non-deterministic GDN facade deterministic= behaviour:refactor(cake_gdn_kcp): the GDN KCP facade runs the non-deterministic package only #8920 (stacked on this PR). flashinfer.cake_gdn_train_kcp runs only the non-deterministic package. Any value other than deterministic=False, including the default, raises ValueError naming the deterministic entry in flashinfer.cake_gdn_det_train_kcp. There is no fallback or reroute under torch.use_deterministic_algorithms(True).
The four names without det in flashinfer.experimental.cake_gdn_det_train, and a top-level flashinfer.cake_gdn_det_train facade (det names only, like flashinfer.cake_kda_det_train): a separate removal PR from the deterministic owners, also to be linked here.
After this PR, the non-deterministic GDN tests, benchmark and READMEs no longer import any of those names, so the removals can merge right after it.
… package only (#8920)
## Summary
`flashinfer.cake_gdn_train_kcp` is the context-parallel GDN facade
without "det" in its name. It now runs only the non-deterministic
package, `flashinfer.experimental.cake_gdn_train_kcp`, and only with
`deterministic=False`. Any other value, including the default, raises
`ValueError` instead of running the deterministic package. A module
without "det" in its name no longer runs the deterministic package
silently, and a caller that relied on the old default gets an error
instead of being switched silently to the non-deterministic path. The
deterministic package keeps its explicit det names in
`flashinfer.cake_gdn_det_train_kcp`.
This PR is stacked on #8916 (base main 3757bab). The branch has two
commits: 1d5f7bb (= #8916) and b8a4781 (this change). Please review
b8a4781, which is the only commit left once #8916 merges.
## Behavior change
| Call to a facade entry | Before | After |
|---|---|---|
| `deterministic=True` (default) | Ran the deterministic package |
`ValueError` naming the deterministic entry in
`flashinfer.cake_gdn_det_train_kcp` and saying to pass
`deterministic=False` (same for any value other than `False`) |
| `deterministic=False` | Non-deterministic package | Non-deterministic
package |
| `deterministic=False` under `torch.use_deterministic_algorithms(True)`
| Rerouted to the deterministic package, warned once per process |
Non-deterministic package, in both strict and `warn_only`. No reroute,
no warning, and no PyTorch deterministic alert, because the package's
launches are fixed-order |
Nothing is routed to the deterministic package, and nothing falls back
to it. Each entry's one-time `ExperimentalWarning` is unrelated to the
mode.
## Migration
- If you relied on the default, call the deterministic entry in
`flashinfer.cake_gdn_det_train_kcp`:
- `partition_kcp` → `partition_det_kcp`
- `build_context_kcp` → `build_context_det_kcp`
- `chunk_gdn_fwd_kcp` → `chunk_gdn_det_fwd_kcp`
- `chunk_gdn_bwd_kcp` → `chunk_gdn_det_bwd_kcp`
- `chunk_gdn_kcp` → `chunk_gdn_det_kcp`
- `gdn_workspace_bytes_kcp` → `gdn_det_workspace_bytes_kcp`
- `gdn_saved_bytes_kcp` → `gdn_det_saved_bytes_kcp`
- `gdn_comm_bytes_kcp` → `gdn_det_comm_bytes_kcp`
- `is_gdn_train_kcp_supported` → `is_gdn_det_train_kcp_supported`
- If you want the non-deterministic package, pass `deterministic=False`
explicitly.
- `chunk_gdn_bwd_kcp` reads only this package's `SavedKcp` and raises
`ValueError` on a saved set from a deterministic forward. An options
instance from the deterministic package is still accepted as a mapping
of its fields.
```python
# Before: the default ran the deterministic package. Now it raises ValueError.
from flashinfer.cake_gdn_train_kcp import chunk_gdn_kcp
out = chunk_gdn_kcp(...)
# After: deterministic
from flashinfer.cake_gdn_det_train_kcp import chunk_gdn_det_kcp
out = chunk_gdn_det_kcp(...)
# After: non-deterministic
out = chunk_gdn_kcp(..., deterministic=False)
```
## Changes
- Facade: every entry keeps the keyword-only `deterministic: bool =
True` and accepts only `False`. Routing to the deterministic package,
the fallback, and the `torch.use_deterministic_algorithms` reroute and
warning are removed.
- The non-deterministic packages' own refusals now name the entry's
deterministic counterpart. These are `check_mode` in
`flashinfer.experimental.cake_gdn_train_kcp`, and
`flashinfer.experimental.cake.cake_gdn_train`.
- Docs:
- A "Mode and dispatch rules" section is added at the top of both
non-deterministic READMEs and the facade docstring.
- Every example passes `deterministic=False`.
- A byte-query note no longer says torch's deterministic algorithms must
be off.
- Tests: the facade tests now check:
- every refused value
- that no call reaches the deterministic facade
- that there is no reroute or fallback warning under torch's
deterministic algorithms (strict and `warn_only`), including
`is_gdn_train_kcp_supported` and the autograd node's output and
gradients against the package's own forward and backward
Cross-checks against the deterministic package call its det entries.
- Bench: the deterministic arm calls the det entries.
- 11 files, +487/-520 relative to #8916.
## Testing
- CPU at b8a4781 (CUDA 13.4 devel image, Python 3.14.9, torch
2.14.1+cu130), running `test_cake_gdn_train.py` plus the 8
`test_cake_gdn_train_kcp*.py` files: 579 passed, 352 skipped, 0 failed.
This holds both on the head and on a tree with the deterministic
packages' former names deleted (simulated removal).
- pre-commit (mypy, ruff check, ruff format, ...) passes.
- GPU at the previous revision 75232cc0 (4 x R200 (sm_107a), driver
620.43, torch 2.14.1+cu130, Python 3.14.8, nvcc 13.4), on both trees, 0
failed:
- `test_cake_gdn_train_kcp_api.py`: 164 passed
- `test_cake_gdn_train_kcp_l2n.py`: 41 passed, 2 skipped (by design)
- `test_cake_gdn_train_kcp_cp1.py`: 100 passed
- `test_cake_gdn_train.py -k "names or exports or deterministic"`: 27
passed, 2 skipped
- `test_cake_gdn_train_kcp_dist.py`, multi-GPU rows at world 4 and world
2: 2 passed
- b8a4781 differs from 75232cc0 only in docs, one facade docstring
sentence, and two added test checks, which run and pass on CPU.
- This change has not run on B200 / B300 GPUs beyond CI. It only changes
host-side dispatch; no kernels are touched.
## Notes
- The conv1d lines in the facade docstring are migrated in #8912, so the
two PRs don't overlap.
- No kernel, program, or numerical change.
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
<!-- coderabbit-ai-generated:v1 -->
## Summary by CodeRabbit
* **Behavior Changes**
* The GDN training and KCP interfaces now run only when
`deterministic=False`; other values raise an error directing you to the
corresponding deterministic entry point.
* Enabling PyTorch’s deterministic algorithms no longer switches these
interfaces to a different route. Use the separate deterministic package
when deterministic execution is needed.
* KCP options and queries follow the same explicit mode requirement.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Co-authored-by: Yingyi Huang <averyh@nvidia.com>
…8921)
Removes the pre-rename names of the deterministic context-parallel GDN
training route without aliases. Every public name of this route now
carries `det`. Follow-up to the review on #8916.
- Deleted: `flashinfer.gdn_train`, the
`flashinfer.experimental.cake_gdn_train` compatibility package, and the
no-det aliases in `flashinfer.experimental.cake_gdn_det_train_kcp`
(`chunk_gdn_kcp`, `chunk_gdn_fwd_kcp`, `chunk_gdn_bwd_kcp`,
`KcpContext`, `KcpOptions`, `kcp_partition`, `build_kcp_context`,
`gdn_kcp_*_bytes`, ...). Use `chunk_gdn_det_kcp`, `ContextDetKcp`,
`partition_det_kcp`, `build_context_det_kcp`, `gdn_det_*_bytes_kcp`, ...
- The package exports only names that carry `det`. `SCALE`, `LAST_CALL`,
the backend controls and the option helpers stay in their modules
(`cake_kcp`, `cake_options`).
- The legacy-alias test becomes absence tests. The removed modules do
not import, no deterministic module binds a removed name, and no
deterministic entry takes a `deterministic` keyword.
- The README and the `flashinfer.cake_gdn_det_train_kcp` docstring state
that the names were removed and add a "Mode and dispatch rules" section.
Merge order: this branch contains #8918, #8916 and #8912, and merges
after them. Kernels, numerics and performance do not change.
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
<!-- coderabbit-ai-generated:v1 -->
## Summary by CodeRabbit
- **Breaking Changes**
- Removed legacy GDN training import paths and compatibility aliases.
Update imports to use the current deterministic API.
- Deterministic entry points no longer accept a `deterministic` keyword.
Backward operations reject saved data or workspaces created in
non-deterministic mode.
- The deterministic API exposes only `det`-named entries;
non-deterministic training is available through a separate experimental
package and requires `deterministic=False`.
- **Documentation**
- Clarified the distinction between deterministic and non-deterministic
APIs and their usage requirements.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Co-authored-by: Yingyi Huang <averyh@nvidia.com>
Removes the remaining pre-`det` aliases from the deterministic
context-parallel KDA training package
`flashinfer/experimental/cake_kda_det_train_kcp` and its facade
`flashinfer/cake_kda_det_train_kcp.py`. This follows the project rule
that every deterministic kernel name carries `det`.
**This PR breaks the API.** It deletes the previous names and keeps no
compatibility alias. Importing a previous name raises `ImportError`.
Accessing one as a module attribute raises `AttributeError`. Callers
must switch to the `det` names in the table below.
Kernels and numerics are unchanged. The `det` entry points run the same
kernels, and their outputs are bitwise identical to the outputs before
this change.
### Changes
- Remove the 20 module-level aliases that bound the previous names: 12
in `cake_kcp.py` and 8 in `cake_kcp_plan.py`. No compatibility alias is
kept.
- In the KCP host module, use the single-rank `KdaDetWorkspace` instead
of the `KdaWorkspace` alias.
- Remove the list of previous names from the README and docstrings.
- Have the performance script call
`flashinfer.cake_kda_det_train.chunk_kda_det`.
- Make the API test check that the 18 previous names are gone from the
facade, the package and its modules.
### Migration
The modules below are under
`flashinfer.experimental.cake_kda_det_train_kcp`.
| Previous name | `det` name | Module |
|---|---|---|
| `ChunkKDAKcpFunction` | `ChunkKDADetFunctionKcp` | `cake_kcp` |
| `KcpCall` | `CallDetKcp` | `cake_kcp` |
| `KcpOptions` | `OptionsDetKcp` | `cake_kcp` |
| `KcpRecomputeHandle` | `RecomputeHandleDetKcp` | `cake_kcp` |
| `KcpSaved` | `SavedDetKcp` | `cake_kcp` |
| `KcpWorkspace` | `WorkspaceDetKcp` | `cake_kcp` |
| `chunk_kda_kcp` | `chunk_kda_det_kcp` | `cake_kcp` |
| `chunk_kda_kcp_fwd` | `chunk_kda_det_fwd_kcp` | `cake_kcp` |
| `chunk_kda_kcp_bwd` | `chunk_kda_det_bwd_kcp` | `cake_kcp` |
| `KcpContext` | `ContextDetKcp` | `cake_kcp_plan` |
| `KcpFragment` | `FragmentDetKcp` | `cake_kcp_plan` |
| `KcpPartition` | `PartitionDetKcp` | `cake_kcp_plan` |
| `build_kcp_context` | `build_context_det_kcp` | `cake_kcp_plan` |
| `kcp_partition` | `partition_det_kcp` | `cake_kcp_plan` |
| `kcp_comm_bytes` | `kda_det_comm_bytes_kcp` | `cake_kcp`,
`cake_kcp_plan` |
| `kcp_saved_bytes` | `kda_det_saved_bytes_kcp` | `cake_kcp`,
`cake_kcp_plan` |
| `kcp_workspace_bytes` | `kda_det_workspace_bytes_kcp` | `cake_kcp`,
`cake_kcp_plan` |
The KCP host module now refers to the single-rank workspace as
`cake_backend.KdaDetWorkspace` instead of `cake_backend.KdaWorkspace`.
Both are in the `flashinfer.experimental.cake_kda_det_train` package.
The public facade `flashinfer.cake_kda_det_train_kcp` exports these
`det` names:
- Functions: `partition_det_kcp`, `build_context_det_kcp`,
`chunk_kda_det_kcp`, `chunk_kda_det_fwd_kcp`, `chunk_kda_det_bwd_kcp`,
`kda_det_workspace_bytes_kcp`, `kda_det_saved_bytes_kcp`,
`kda_det_comm_bytes_kcp`, `reduce_gate_param_grads_det_kcp`
- Types: `ContextDetKcp`, `OptionsDetKcp`, `PartitionDetKcp`,
`RecomputeHandleDetKcp`, `SavedDetKcp`, `WorkspaceDetKcp`
### Related
#8908 merges after this PR. It deletes the module
`flashinfer.kda_train`, which bound the same previous KCP spellings:
`kcp_partition`, `build_kcp_context`, `chunk_kda_kcp[_fwd|_bwd]`,
`kcp_*_bytes`, `kcp_reduce_gate_param_grads` (now
`reduce_gate_param_grads_det_kcp`) and the `Kcp*` types. It also deletes
the compatibility package `flashinfer.experimental.cake_kda_train`,
including the import-path modules `cake_kcp`, `cake_kcp_jit` and
`cake_kcp_plan`. Their new paths are
`flashinfer.experimental.cake_kda_det_train_kcp.cake_kcp`,
`.cake_kcp_jit` and `.cake_kcp_plan`.
#8906, #8912, #8916 and #8918 have merged and moved every test call site
to the `det` names, including the non-deterministic causal conv1d KCP
dist test.
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
<!-- coderabbit-ai-generated:v1 -->
## Summary by CodeRabbit
* **API Changes**
* Removed legacy, pre-deterministic names from the experimental KCP API.
The canonical deterministic (`det`) names remain available; callers
using the removed names will need to update to the corresponding `det`
names.
* **Documentation**
* Updated KCP documentation to reflect the available deterministic API
names.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Co-authored-by: Yingyi Huang <averyh@nvidia.com>
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Summary
The deterministic Cake GDN training packages are
flashinfer.experimental.cake_gdn_det_train,flashinfer.experimental.cake_gdn_det_train_kcpand the facadeflashinfer.cake_gdn_det_train_kcp. They still carry their former names, which lack "det":flashinfer.gdn_train,flashinfer.experimental.cake_gdn_train,chunk_gdn_kcp/KcpOptionsandchunk_gated_delta_rule/ChunkGatedDeltaRuleFunction/gdn_chunk_forward/gdn_chunk_backward. The KDA compatibility packageflashinfer.experimental.cake_kda_trainhas the same problem. The package owners will delete these names in follow-up PRs and won't keep compatibility aliases.This PR stops the non-deterministic GDN tests, benchmark and READMEs from using these former GDN and KDA names. They pass both before and after the removals. The former conv1d names used in the same files are migrated separately by the conv1d package owner (#8912). Package behavior and kernels are unchanged. The only edits to package files are three provenance docstrings: they keep the historical KDA source path and add its current det path.
Changes
tests/experimental/test_cake_gdn_train_kcp_api.py:cake_backend,cake_buildandcake_l2n.tests/experimental/test_cake_gdn_train.py: compares against the deterministic package's det names instead of its former aliases.test_cake_gdn_train_kcp.pyandtest_cake_gdn_train_kcp_build.py: KDA references now usecake_kda_det_train_kcp.cake_kcp_plan(partition_det_kcp,build_context_det_kcp) andcake_kda_det_train.cake_build.benchmarks/bench_cake_gdn_train_kcp.py: readsLAST_CALLandgraph_cache_clearfor both routes from each package'scake_kcpmodule, because the deterministic package will stop re-exporting them at package level.Testing
One commit on main
3757bab, head1d5f7bb. The first revision802dc8adiffers from it only in docstrings and the commit message. Each run used a clean tree at the named head and a tree with the former names deleted (simulated removal):1d5f7bb(CUDA 13.4 devel image, Python 3.14.9, torch 2.14.1+cu130):test_cake_gdn_train_kcp_api.py,test_cake_gdn_train_kcp_build.pyandtest_cake_gdn_train_kcp.pygave 454 passed, 7 skipped, 0 failed on both trees.pre-commit(mypy, ruff check, ruff format, ...) passes.802dc8a:test_cake_gdn_train.pyplus the 8test_cake_gdn_train_kcp*.pyfiles gave 577 passed, 352 skipped, 0 failed on both trees. As a control, the old tests fail 3 on the simulated-removal tree.802dc8a(B200, sm_100a): 0 failed on both trees.test_plan_parity_with_kda_on_rowsskips in every environment because it needsGDN_ROWS_DIR. That skip predates this PR and is unchanged.Follow-ups
deterministic=behavior of the non-deterministic facade with the shared mode rules.Summary by CodeRabbit