[REVIEW] New Dataset API Clarifying Ownership by HowardHuang1 · Pull Request #1846 · NVIDIA/cuvs

HowardHuang1 · 2026-02-24T23:21:21Z

Overview

Addressing #1574 and #1571.

Replaced strided_dataset with padded_dataset class. Added support all the way up to CAGRA code.

Old class structure (Classes + Inheritance):

New Class Structure (ContainerType Tags + Composition):

Inheritance is removed entirely and all dataset types are on the same level of the inheritance tree.

3 Levels:

Storage

Container tags

Public dataset/view aliases

Ownership

The index and cagra::build / cagra::index do not own raw vector storage, they only take views.

callers (or the C merged holder) must keep backing memory alive for as long as the index is used.

The old code had a type-erased std::unique_ptr<dataset_view<...>>, i.e. non-owning view handles. The new code uses templates on the index type which determines the type of dataset_view the index holds.

ACE v.s. non-ACE paths on Host

ACE path copies datasets that can't entirely fit in CPU memory in chunks onto GPU memory by calling make_padded_dataset. This is 1x memory on CPU and 1x memory on GPU.

Return types:

Used mainly to maintain lifetime of dataset.

cuvs_cagra_c_api_lifetime_holder

unique_ptr<vpq_dataset> vpq_owner
unique_ptr padded_dataset_owner
raft::device_matrix dataset
cagra::index idx
It is a single C++ struct in cagra.cpp that groups the real cagra::index with any extra heap-owned things the C API had to create so the index’s non-owning views stay valid.

Miscellaneous: Extend Serialize Deserialize

Will fill in later

Factories:

make_device_padded_dataset_view
make_host_padded_dataset_view
make_device_padded_dataset
make_host_padded_dataset
make_vpq_dataset
- in pq.hpp and pq.cu
make_merged_dataset
- in cagra.hpp

Places where make_padded_dataset/view are called internally (not by user):

Host non-ACE path

cpp/src/neighbors/cagra_build_inst.cu.in
cagra_from_host_padded in cpp/src/neighbors/iface/iface.hpp
c/src/neighbors/cagra.cpp

Tiered CAGRA

update_cagra_ann_dataset_for_stride
build_upstream_ann

Ownership in Downstream Functions:

build() takes dataset_view only.
Downstream functions search / serialize / deserialize / merge only take views.

Improvements:

build() function previously only supported device dataset inputs. It now supports host dataset inputs.

Breaking Changes for Dataset API:

The following functions are removed since index no longer owns the dataset, index only takes views:

Removed all owning dataset based builds. Build only takes views.
Removed all update_dataset() overloads that take owning dataset. Update_dataset() only takes views.
Removed old functions that took mdspan or derivatives of mdspan.

4 cases where index previously owned dataset [all deprecated paths]:

2 edge case build() paths when attach_dataset_on_build == true and a successful dense attach:

Non-ACE / typical padded attach: rows live under index_owning_dataset_storage_ (type-erased owning wrapper, commonly device_padded_dataset).
ACE in-memory device_matrix attach: rows live under index_owning_dataset_storage_ (optional raw device_matrix).

Compression Param:

implicit vpq dataset creation within build() when compression==True
this forces index to own new vpq dataset which violates our new contract that we want index to never own dataset.

Merge:

MERGE path: merge() internally creates merged_dataset on a deprecated internal merged dataset creation path. Here, index takes ownership of merged_dataset by storing it in index_owning_dataset_storage_ .

These paths have since been removed.

Attach Dataset

Previously, in the old code, ACE attach_dataset_on_build called make_device_padded_dataset on host dataset which did a H2D copy in order to attach dataset to final index.
cpp/src/neighbors/detail/cagra/cagra_build.cuh
This has since been removed. attach_dataset_on_build is disabled for host build paths. This avoids a H2D copy.

Compressed Dataset

Removed old code that did compressed dataset creation within build. This should only happen in the factory.

Merged Dataset

Removed implicit memory allocation within merge(), memory allocation now delegated to make_merged_dataset() factory. Removed index ownership within merge.

Deserialize

Removed index ownership of dataset during deserialization. Now users are expected to create/declare the dataset type to be deserialized and then pass it as a reference to the deserialize() function which will then populate this dataset and return it to the caller.

Helpers

cagra_required_row_width
matrix_actual_row_width
matrix_row_width_matches_cagra_required
convert_dataset_view_to_padded_for_graph_build
convert_host_to_device_index
attach_device_dataset_on_host_index

How to attach a compressed dataset onto an uncompressed index?

construct a new compressed index
copy over the graph and other params from the uncompressed index
delete the old uncompressed index
attach the vpq dataset onto the compressed index

How to attach a searchable device dataset onto an index built with host build?

Convert host index to device index with helper function convert_host_to_device_index
a. Utilizes map of host dataset type to device dataset type counterpart

TODOs:

Bring back Host functions [DONE]
Mark any old functions that are no longer used as [DONE]
Use templates wherever possible. Shift towards composition rather than inheritance [DONE]

Recent Updates:

build_ace() and build() functions merged on Public API surface
removed build_result(), ace_build_result(), and merge_result()
deprecated internal vpq dataset creation inside build() when index_params::compression == true --> moved to make_vpq_dataset() factory
deprecated internal merged dataset creation inside merge() --> moved to make_merged_dataset() factory. For backwards compatibility, have index take ownership of deprecated internal merged dataset creation path ONLY.
build() and build_ace() both had a attach_dataset_on_build which requires ownership of dataset. Ownership is given to index temporarily. This will later be deprecated. Users will be expected to pass padded dataset on device and call search() directly. Attach_dataset_on_build will no longer be supported for host builds.
added host versions of dataset API
templated build() and downstream functions to work on host datasets
added index template type conversion helpers

Future PRs:

PR#2: Add Support for Compressed Datasets

pq_dataset
bbq_dataset
rabitq_dataset
sq_dataset

PR#3: Migrate Rest of Algorithms to use Dataset API

HNSW
IVF
Vamana
Scann
Brute Force

copy-pr-bot · 2026-02-24T23:21:25Z

This pull request requires additional validation before any workflows can run on NVIDIA's runners.

Pull request vetters can view their responsibilities here.

Contributors can view more details about this message here.

aamijar · 2026-02-25T01:51:35Z

/ok to test 5447a4c

aamijar · 2026-02-25T02:12:45Z

/ok to test 17ab09d

achirkin · 2026-02-25T06:06:02Z

NB: I updated the label to breaking, since the description implies removal of a publicly visible class strided_dataset

cjnolet · 2026-02-25T22:22:05Z

Does the dataset(_view) type bring anything on top of mdarray/mdspan in that case?

@achirkin The problem w/ using mdspan/mdarray for this is that it's not carrying along the proper information to either the algorithms nor the user (which is why we created this specialized class for this in the first place!).

Two immediate reasons why this API is necessary:

The user should not have to know that they need to pad a dataset in order to use cagra without the additional copy. They should not need to know how any of these algorithms work internally. They should, however, need to know that CAGRA expects a padded dataset, and they should have an API to construct one so that they can own the dataset class and not have cagra creating one under the hood.
APIs, especially the graph-based APIs, should be able to accept as inputs data which has been quantized using a metod like PQ, which carries with additional information. In the case of PQ, the codebooks are needed to compute the distances. This again decouples the quantization from the algorithm (CAGRA-Q does not need to do its own quantization. It should just accept the quantized vectors). We're being asked for the same behavior with Vamana.

This new API solves both of these problems while leaving the control over the memory ownership entirely in the user's hands. We've discussed this for a long time. We've known this is needed for a long time. it's time to prioritize this and get it done. I agree that an anstract class might make more sense, but ultimately we should not be moving any owneship over to the algorithm (the user should maintain ownership over the class and underlying memory the entire time).

HowardHuang1 · 2026-03-04T23:24:04Z

The doc that outlines some of the API design choices can be found in slack. Let me know if there are any parts of the design that can be altered to better suit our users' needs.

The following files are test case files I've added and can be ignored for now. They will be removed before the final merge with upstream repo:

cagra_build_view_only.cu
cagra_padded_dataset.cu
cagra_vpq_build_result.cu
dataset_compression.cu
dataset_types.cu

cjnolet · 2026-03-25T14:54:12Z

/ok to test 70b6b58

achirkin

Sorry for being so late for the second round of reviews! I have a few suggestions for the dataset type hierarchy.

cjnolet · 2026-07-23T15:48:58Z

-  /** Compressed dataset.  */
-  raft::device_matrix<uint8_t, index_type, raft::row_major> data;
-
-  vpq_dataset(raft::device_matrix<math_type, uint32_t, raft::row_major>&& vq_code_book,


This is not cagra specific. Please move this to the respective preprocessing/pq.hpp file. Each different quantizer sohuld provide their respective dataset implementation so that when imported, the dataset comes w/ the quantizer.

cjnolet · 2026-07-23T15:52:14Z

+ * - IdxT: index type used for row counts (`n_rows()` return type).
+ */
+template <typename MatrixT, typename ViewT, typename DataT, typename IdxT>
+struct dense_row_major_dataset_owning_storage {


Agreed- for a single dense contiguous owning matrix type, we should be using mdarray... nothing else. If we need some type of composite, we should define that upon use... but i'm not seeing an immediate need for that in this PR.

cjnolet · 2026-07-23T16:09:22Z

+                                                              cuvsDatasetPaddedView_t padded_dataset,
+                                                              cuvsCagraIndex_t index);
+
+/**


What is a host cagra index? CAGRA is a GPU algorithn. This naming could be described with more clarity. Does "host cagra index" just imply the underlying dataset is on host? Because there is a potential configuration for CAGRA where the graph is always on host too.

Also, in C, we tend to put the verb last- "Make" "Create" "Destroy" "Attach" should all be last.

I would

Yes host cagra index just refers to an index where the attached dataset is on host but the index graph itself is on device. Such a dataset is not immediately searchable.

…ng 26.10 to 26.08 versions for release

… not correct. Use owning factory first and then create view from that.

Authors: - Zihao Wang (https://github.com/hhy3) - Anupam (https://github.com/aamijar) Approvers: - Tarang Jain (https://github.com/tarang-jain) URL: NVIDIA#2322

This PR removes the `libclang==20.1.8` pin from the `clang` dependency group in `dependencies.yaml`. ## Problem The explicit `libclang==20.1.8` pin causes the conda solver to hang when creating the combined RAPIDS devcontainer environment. Specifically, when cuvs is included alongside cudf (which depends on `matplotlib<3.11`), the solver cannot efficiently resolve the conflict between: - `libclang==20.1.8` → provides `libclang13 20.1.8` - `matplotlib<3.11` → pulls in `qt6-main` → requires `libclang13>=22.1.0` While the environment is technically solvable (older Qt builds accept `libclang13>=20.1.8`), the search space created by the 29 builds of `libclang 20.1.8` × multiple Qt versions × CUDA packages × rapidsai channel packages causes the solver to hang indefinitely. ## Why this is safe to remove 1. **`clang` and `clang-tools` do not depend on `libclang`.** The `clang` compiler depends on `libclang-cpp` (the C++ API), which is a separate package from `libclang` (the C API wrapper). 2. **The Rust bindgen workflow doesn't use the `clang` dependency group.** The `rust` file key does not include the `clang` group — bindgen finds `libclang.so` at runtime from whatever version is available in the environment (provided transitively via Qt/matplotlib's dependency on `libclang13`). 3. **Other RAPIDS repos don't pin `libclang`.** cudf, raft, and rmm only pin `clang` and `clang-tools` without `libclang` and do not experience this issue. 4. **Historical context:** `libclang` was originally added to the `rust` dependency group for bindgen support, then moved into the `clang` group during a version bump refactor. The `rust` file key no longer includes the `clang` group, making this entry vestigial. Authors: - Vyas Ramasubramani (https://github.com/vyasr) Approvers: - Gil Forsyth (https://github.com/gforsyth) URL: NVIDIA#2263

The sample code for cagra::build_knn_graph was using deprecated APIs. This PR updates it to use the current API. Authors: - tsuki (https://github.com/enp1s0) Approvers: - Corey J. Nolet (https://github.com/cjnolet) URL: NVIDIA#2339

Forward-merge release/26.08 into main

…taset() function. Attach_dataset() takes in any index type as input (host vs device, standard vs padded) and a device padded device and always returns a device padded index which is searchable. It internally dispatches on every combination of input index and input dataset type allowed and does internal host to device or standard to padded conversion if needed. We introduce 2 helper functions: convert_host_to_device_index() and convert_standard_to_padded_index(). These 2 helpers along with the original update_dataset(), which only takes device_padded_index and device_padded_dataset() as input, are internally called within attach_dataset() within each of the dispatch cases.

lowener · 2026-07-24T13:31:06Z

+extern "C" cuvsError_t cuvsDatasetMakeDevicePadded(cuvsResources_t res,
+                                                   DLManagedTensor* dataset_tensor,
+                                                   cuvsDatasetPadded_t* padded_dataset)


All those new cuvsDataset... functions should be in a separate compilation unit (src/core/dataset.cpp) (Not blocking this PR though, it can be a follow-up)

lowener · 2026-07-24T14:26:46Z

+  DLDataType dtype;
+  cuvsDatasetLayout_t layout;
+} cuvsDatasetStandard;
+typedef cuvsDatasetStandard* cuvsDatasetStandard_t;


The two structs are similar, can't there be just one struct definition and two typedefs? They already represent the same thing.

Same with the view struct just below

lowener · 2026-07-24T14:29:52Z

+  void (*destroy_addr)(void*);
+  cuvsDatasetViewKind_t kind;
+  DLDataType dtype;
+  cuvsDatasetLayout_t layout;


layout is redundant if kind is already present in the struct

cjnolet · 2026-07-24T15:42:27Z

-                           cuvsCagraIndexParams_t params,
-                           DLManagedTensor* dataset,
-                           cuvsCagraIndex_t index);
+CUVS_EXPORT cuvsError_t cuvsCagraGetDatasetViewKind(DLManagedTensor* dataset,


Any reason this needs to be exposed to the public?

cjnolet · 2026-07-24T15:44:39Z

+CUVS_EXPORT cuvsError_t cuvsCagraDeserializePadded(cuvsResources_t res,
+                                                    const char* filename,
+                                                    cuvsCagraIndex_t index,
+                                                    cuvsDatasetPadded_t* out_padded_dataset);


Question- why isn't the dataset type serialized with the cagra graph (in the even the user wants that serialized with the cagra graph)? This way we can just do "cuvsCagraDeserializeWithDataset" (which throws an error if the serialized file doesn't contain the dataset) and cuvsCagraDeserialize (which doesn't deserialize the dataset, even if it's in the file).

Pre-allocating the dataset buffer gives us 2 advantages: (1) no hidden memory allocations, (2) deterministic dataset type.

If we are pre-allocating the dataset buffer, I think we can just parse the type from that directly so there wouldn't be a need to modify the serialize algo itself to serialize the dataset type along with the graph.

If the proposal is to remove the passing in of the dataset buffer entirely in favor of serializing the dataset type with the cagra graph (which more closely mirrors the original serialize function), we would lose the beenfit of advantage (1).

cjnolet · 2026-07-24T17:49:31Z

+typedef enum {
+  CUVS_DATASET_VIEW_KIND_DEVICE_PADDED   = 0,
+  CUVS_DATASET_VIEW_KIND_HOST_PADDED     = 1,
+  CUVS_DATASET_VIEW_KIND_DEVICE_STANDARD = 2,


Instead of view kind containing both host and device for each dataset type (this is going to quickly become unmaintainable), please just define the accessor type (HOST and DEVICE) here and reuse the dataset layout enum above.

cjnolet · 2026-07-24T17:51:25Z

+  DLDataType dtype;
+  cuvsDatasetLayout_t layout;
+} cuvsDatasetPadded;
+typedef cuvsDatasetPadded* cuvsDatasetPadded_t;


We discussed this offline- we should probably just make a single dataset struct and use the enums to parameterize it so that we know what kind to cast it to in the C++ layer.

… NEIGHBORS_ANN_CAGRA_tests

…update_dataset() that only updated standard index with standard dataset or padded index with padded dataset() was renamed update_device_dataset_same_layout(). New centralized cuvsCagraUpdateDataset at C API layer was created which internally dispatches to cuvsCagraUpdateDeviceDatasetSameLayout if index type is device_padded_index. For all other index types, it dispatches internally to cuvsCagraAttachDataset. This resolves the mutability issue we were previously experiencing where cuvsCagraAttachDataset guarantees original input index is immutable and returns a new index of new type while cuvsCagraUpdateDeviceDatasetSameLayout requires mutating the input dataset and makes no such index copy. This is not implemented at the C++ API layer yet, it only exists in the C API layer since C API doesn't make immutability guarantees while C++ API does and tries to keep C++ logic immutable to prevent thread conflicts. Downstream langauge wrappers have been updated to call centralized cuvsCagraUpdateDataset as the single sole entry point for all cases of updating/attaching a dataset

…ut from exports in C API layer and remove from downstream wrappers. They are not meant to be exposed to users/callers. Users/callers should use cuvsCagraUpdateDataset as the only C API function they interface with when updating/attaching a dataset

Forward-merge release/26.08 into main

yan-zaretskiy · 2026-07-25T00:51:24Z

+      _deserialize_padded<float>(res, filename, index, out_padded_dataset);
+      index->dtype.code = kDLFloat;
+    } else if (dtype.kind == 'e' && dtype.itemsize == 2) {
+      _deserialize_padded<half>(res, filename, index, out_padded_dataset);
+      index->dtype.code = kDLFloat;
+    } else if (dtype.kind == 'i' && dtype.itemsize == 1) {
+      _deserialize_padded<int8_t>(res, filename, index, out_padded_dataset);
+      index->dtype.code = kDLInt;
+    } else if (dtype.kind == 'u' && dtype.itemsize == 1) {
+      _deserialize_padded<uint8_t>(res, filename, index, out_padded_dataset);
+      index->dtype.code = kDLUInt;


I think there's a bug here in the order of these ops. The _deserialize_padded copies the index's dtype into the handle it returns:

out->dtype = output_index->dtype;

So the dtype should already be set when it's called. Therefore, we should flip the two lines for each dtype kind branch:

index->dtype.code = ... _deserialize_padded...

Forward-merge release/26.08 into main

…or MG path. Factored out distribute_padded_dataset() shared GPU sharding logic and exposed both attach_dataset() and update_device_dataset_same_layout() C++ API functions for the MG path. Expose new MG centralized update dataset in python wrapper. Other downstream languages java, rust, and go for some reason don't have any CAGRA MG functions exposed. Will need to expose this in a future commit.

HowardHuang1 · 2026-07-26T02:29:00Z

/ok to test d377781

HowardHuang1 requested review from a team as code owners February 24, 2026 23:21

github-project-automation Bot added this to Unstructured Data Processing Feb 24, 2026

aamijar added non-breaking Introduces a non-breaking change feature request New feature or request labels Feb 25, 2026

aamijar assigned HowardHuang1 Feb 25, 2026

aamijar moved this to In Progress in Unstructured Data Processing Feb 25, 2026

achirkin added breaking Introduces a breaking change and removed non-breaking Introduces a non-breaking change labels Feb 25, 2026

achirkin reviewed Feb 25, 2026

View reviewed changes

Comment thread cpp/include/cuvs/neighbors/cagra.hpp

aamijar reviewed Feb 25, 2026

View reviewed changes

Comment thread cpp/CMakeLists.txt Outdated

seunghwak mentioned this pull request Feb 27, 2026

[WIP] Clarify dataset ownership and allocation semantics #1738

Closed

HowardHuang1 requested a review from a team as a code owner February 28, 2026 03:34

cjnolet mentioned this pull request Mar 10, 2026

[FEA] Implement binary dataset and accept in CAGRA #1906

Open

mohanprasand-nuvai mentioned this pull request Mar 23, 2026

Binary dataset support in CAGRA (upstream #1906) Nuvai/cuvs#5

Closed

5 tasks

HowardHuang1 changed the title ~~[WIP] New Dataset API Clarifying Ownership~~ [REVIEW] New Dataset API Clarifying Ownership Mar 25, 2026

HowardHuang1 changed the base branch from main to release/26.04 March 25, 2026 01:03

HowardHuang1 requested review from a team as code owners March 25, 2026 01:22

HowardHuang1 requested a review from bdice March 25, 2026 01:22

tfeher requested changes Apr 1, 2026

View reviewed changes

Comment thread cpp/include/cuvs/neighbors/cagra.hpp Outdated

Comment thread cpp/include/cuvs/neighbors/cagra.hpp Outdated

tfeher changed the base branch from release/26.04 to main April 1, 2026 23:31

achirkin requested changes Apr 8, 2026

View reviewed changes

cjnolet reviewed Jul 23, 2026

View reviewed changes

Comment thread c/include/cuvs/neighbors/cagra.h Outdated

cjnolet reviewed Jul 23, 2026

View reviewed changes

Comment thread c/include/cuvs/neighbors/cagra.h Outdated

HowardHuang1 and others added 11 commits July 23, 2026 11:44

Merge remote-tracking branch 'upstream' into HH-Dataset-API

72784d2

Change rmm 26.10 packages back to 26.08 for 26.08 release

ed281a9

Fix copyright on untouched files to minimize diff and restore remaini…

c18d29d

…ng 26.10 to 26.08 versions for release

Fix copyright on untouched files to minimize diff

d58d3e3

Fix failing python tests that were using view factory when stride was…

d6016de

… not correct. Use owning factory first and then create view from that.

Fix missing trailing barrier in ivf_rabitq blockReduceSum (NVIDIA#2322)

ac6a4c0

Authors: - Zihao Wang (https://github.com/hhy3) - Anupam (https://github.com/aamijar) Approvers: - Tarang Jain (https://github.com/tarang-jain) URL: NVIDIA#2322

Fix the build_knn_graph sample code (NVIDIA#2339)

8678c4b

The sample code for cagra::build_knn_graph was using deprecated APIs. This PR updates it to use the current API. Authors: - tsuki (https://github.com/enp1s0) Approvers: - Corey J. Nolet (https://github.com/cjnolet) URL: NVIDIA#2339

Merge pull request NVIDIA#2360 from NVIDIA/release/26.08

0bc1083

Forward-merge release/26.08 into main

Merge branch 'release/26.08' into HH-Dataset-API

f5aaa1c

lowener reviewed Jul 24, 2026

View reviewed changes

cjnolet reviewed Jul 24, 2026

View reviewed changes

HowardHuang1 and others added 4 commits July 24, 2026 11:13

Fix failing CAGRA_C_TEST, MG_C_TEST, NEIGHBORS_TIERED_INDEX_TEST, and…

c198066

… NEIGHBORS_ANN_CAGRA_tests

Merge pull request NVIDIA#2363 from NVIDIA/release/26.08

79fd3d4

Forward-merge release/26.08 into main

yan-zaretskiy reviewed Jul 25, 2026

View reviewed changes

GPUtester and others added 3 commits July 24, 2026 23:43

Merge pull request NVIDIA#2365 from NVIDIA/release/26.08

3aea5d8

Forward-merge release/26.08 into main

Merge remote-tracking branch 'upstream' into HH-Dataset-API

ef311ad

Uh oh!

Conversation

HowardHuang1 commented Feb 24, 2026 • edited Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

Overview

Old class structure (Classes + Inheritance):

New Class Structure (ContainerType Tags + Composition):

Ownership

ACE v.s. non-ACE paths on Host

Return types:

Miscellaneous: Extend Serialize Deserialize

Factories:

Places where make_padded_dataset/view are called internally (not by user):

Ownership in Downstream Functions:

Improvements:

Breaking Changes for Dataset API:

4 cases where index previously owned dataset [all deprecated paths]:

Attach Dataset

Compressed Dataset

Merged Dataset

Deserialize

Helpers

How to attach a compressed dataset onto an uncompressed index?

How to attach a searchable device dataset onto an index built with host build?

TODOs:

Recent Updates:

Future PRs:

Uh oh!

copy-pr-bot Bot commented Feb 24, 2026

Uh oh!

aamijar commented Feb 25, 2026

Uh oh!

aamijar commented Feb 25, 2026

Uh oh!

achirkin commented Feb 25, 2026

Uh oh!

Uh oh!

cjnolet commented Feb 25, 2026

Uh oh!

Uh oh!

HowardHuang1 commented Mar 4, 2026 • edited Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

Uh oh!

cjnolet commented Mar 25, 2026

Uh oh!

Uh oh!

Uh oh!

achirkin left a comment

Choose a reason for hiding this comment

Uh oh!

Uh oh!

Uh oh!

Uh oh!

Uh oh!

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

HowardHuang1 commented Feb 24, 2026 •

edited

Loading

HowardHuang1 commented Mar 4, 2026 •

edited

Loading