test: add integration tests for LoRA module

[ooples]

Summary

• Add comprehensive integration tests for LoRA module covering:
  • LoRALayer initialization, forward/backward pass, parameter handling
  • StandardLoRAAdapter wrapping, freezing, training workflow
  • Multiple adapter variants (Standard, DoRA, VeRA, DVoRA, LoKr, LoHa, LoRAFA, PiSSA, MoRA)
  • Parameter efficiency calculations
• Remove stale CLBlast project reference from test project
• Fix multiple bugs discovered by integration tests:
  • DoRAAdapter: transpose MergeWeights result to match expected dimensions
  • LoRAAdapterBase: fix matrix indexing in MergeToDenseOrFullyConnected
  • LoRAXSAdapter: handle null _trainableR in ParameterCount property
  • StandardLoRAAdapter: fix matrix indexing in MergeToOriginalLayer
  • VeRAAdapter: handle null scaling vectors in ParameterCount and override UpdateParametersFromLayers

Test plan

• All 119 LoRA tests pass on both net10.0 and net471
• Build succeeds with no errors
• All adapter variants (Standard, DoRA, VeRA, DVoRA, LoKr, LoHa, LoRAFA, PiSSA, MoRA) tested

Closes #641

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Project	Deployment	Review	Updated (UTC)
aidotnet-playground-api	Ready	Preview, Comment	Jan 25, 2026 10:34pm

[coderabbitai]

Summary by CodeRabbit

• New Features

  • Added a comprehensive integration test suite for LoRA adapters covering many adapter variants, parameter-efficiency checks, edge cases, and end-to-end training scaffolds.

• Bug Fixes

  • Corrected LoRA weight-dimension and merge logic for stable fine-tuning behavior.
  • Fixed initialization-order handling so adapter parameters initialize and synchronize reliably.

• Chores

  • Removed an unused project dependency from the test project.

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Walkthrough

Removed a native project reference from the test project and added extensive LoRA integration tests; several LoRA adapters were corrected to align LoRA weight/index layouts and made initialization-safe.

Changes

Cohort / File(s)	Summary
Project reference change tests/AiDotNet.Tests/AiDotNetTests.csproj	Removed ProjectReference to ..\..\src\AiDotNet.Native.CLBlast\AiDotNet.Native.CLBlast.csproj.
LoRA integration tests tests/AiDotNet.Tests/IntegrationTests/LoRA/LoRAIntegrationTests.cs	Added comprehensive integration test suite (~618 lines) covering many LoRA adapters, forward/backward passes, parameter counts, edge cases, and a training scaffold.
DoRA adapter weight orientation src/LoRA/Adapters/DoRAAdapter.cs	Merge/forward now reads LoRA MergeWeights() as [inputSize, outputSize], transposes to [outputSize, inputSize] before applying to base weights.
LoRA adapter base merge indexing src/LoRA/Adapters/LoRAAdapterBase.cs	Fixed mapping from flat base parameter index to LoRA matrix indices to use inputIdx/outputIdx matching loraWeights layout [input, output].
Standard LoRA merge indexing src/LoRA/Adapters/StandardLoRAAdapter.cs	MergeToOriginalLayer now indexes loraWeights[inputIdx, outputIdx] when combining into base parameters.
LoRAXS parameter safety src/LoRA/Adapters/LoRAXSAdapter.cs	ParameterCount and UpdateParametersFromLayers now guard against _trainableR being null during base construction; returns safe defaults until initialized.
VeRA initialization & sync src/LoRA/Adapters/VeRAAdapter.cs	Added null-safe ParameterCount handling and a protected UpdateParametersFromLayers() override that no-ops if scaling vectors are null; otherwise packs scaling vectors into the parameter vector.

Sequence Diagram(s)

(omitted)

Estimated code review effort

🎯 4 (Complex) | ⏱️ ~45 minutes

Possibly related PRs

• test: add comprehensive integration tests for Prototypes module #761 — Removes the same AiDotNet.Native.CLBlast ProjectReference from tests/AiDotNet.Tests.csproj.
• test: add comprehensive TrainingMonitoring module integration tests #755 — Also removes the AiDotNet.Native.CLBlast ProjectReference from the test project.
• Fix/lora post merge fixes #260 — Overlapping changes to LoRA adapter internals (parameter/merge logic) relevant to adapter fixes in this PR.

Poem

🐰 I hopped through indices, flipped a bit,
I nudged a link and wrote a testy skit.
I transposed weights with careful cheer,
Now LoRA trains without a fear.
Tiny rabbit clap—code's in gear!

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 15.91% which is insufficient. The required threshold is 80.00%.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title accurately describes the main change: adding comprehensive integration tests for the LoRA module, which is the primary objective of this PR.
Description check	✅ Passed	The description clearly covers the main changes: integration tests for LoRA, removal of stale CLBlast reference, and bug fixes discovered during testing, all related to the changeset.
Linked Issues check	✅ Passed	The PR addresses issue #641's requirement for LoRA integration tests by providing comprehensive test coverage [#641], fixing bugs in adapters (DoRA, LoRAAdapterBase, LoRAXSAdapter, StandardLoRA, VeRA), and achieving broad variant coverage.
Out of Scope Changes check	✅ Passed	All changes are in scope: integration tests for LoRA module, bug fixes in LoRA adapters discovered by testing, and removal of stale project reference are all directly related to issue #641 objectives.

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✨ Finishing touches

• 📝 Generate docstrings

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Post copyable unit tests in a comment
• Commit unit tests in branch test/lora-integration-tests

---

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[coderabbitai]

Actionable comments posted: 1

🤖 Fix all issues with AI agents

In `@tests/AiDotNet.Tests/IntegrationTests/LoRA/LoRAIntegrationTests.cs`:
- Around line 443-482: The test LoRA_TrainingWorkflow_ReducesLoss currently
regenerates random input and target each epoch which prevents meaningful loss
reduction; fix it by creating a fixed training example or small fixed dataset
outside the epoch loop (call CreateTensor once or build an array of
inputs/targets before the for-loop) and reuse those same tensors each epoch for
adapter.Forward/Backward/UpdateParameters; optionally seed the RNG or create
deterministic tensors so the test is stable and then assert that finalLoss <
initialLoss (or at least decreased) in addition to the NaN/Infinity checks.

🧹 Nitpick comments (2)

tests/AiDotNet.Tests/IntegrationTests/LoRA/LoRAIntegrationTests.cs (2)

385-401: Consider adding forward pass tests for LoKr and LoHa adapters.

These adapters only have initialization tests, while QLoRA and AdaLoRA have both initialization and forward pass tests. For consistency and better coverage, consider adding forward pass tests similar to QLoRAAdapter_Forward_ProducesValidOutput.

---

548-573: Remove unused variable.

The input variable at line 552 is never used. The loop correctly creates testInput based on each adapter's actual input shape (line 567).

♻️ Suggested fix

     public void AllAdapters_ForwardPass_ProducesValidOutput()
     {
         var baseLayer = new DenseLayer<double>(InputSize, OutputSize);
-        var input = CreateTensor(1, InputSize);
 
         // Note: DoRA, VeRA, LoRAXS have bugs; MoRA requires square layers; DVoRA requires initialization

[coderabbitai]

Actionable comments posted: 2

🤖 Fix all issues with AI agents

In `@src/LoRA/Adapters/DoRAAdapter.cs`:
- Around line 374-378: Merge path still uses the untransposed delta: when
MergeWeights() returns loraWeightDeltaRaw ([inputSize, outputSize]) you
transpose it to loraWeightDelta ([outputSize, inputSize]) in Forward but
MergeToOriginalLayer() is still adding loraWeightDeltaRaw directly; update
MergeToOriginalLayer() (and the similar code around the 720-730 region) to use
the transposed matrix (or swap indices when indexing) so the delta is applied as
[outputSize, inputSize] to the base weight matrix, referencing MergeWeights(),
loraWeightDeltaRaw, loraWeightDelta, and MergeToOriginalLayer() to locate the
changes.

In `@src/LoRA/Adapters/LoRAXSAdapter.cs`:
- Around line 250-257: ParameterCount currently returns Rank * Rank when
_trainableR is null which allows the base constructor to call
UpdateParametersFromLayers() and pack _loraLayer parameters (size
_loraLayer.ParameterCount) into a too-small buffer; change behavior to prevent
packing until _trainableR is initialized by making ParameterCount return
_loraLayer.ParameterCount (or otherwise the larger safe size) when _trainableR
is null, or add a guard in UpdateParametersFromLayers() to early-return if
_trainableR is null; update references in ParameterCount, the class constructor,
and UpdateParametersFromLayers() so the base ctor cannot overrun the Parameters
buffer.

♻️ Duplicate comments (1)

tests/AiDotNet.Tests/IntegrationTests/LoRA/LoRAIntegrationTests.cs (1)

451-490: Loss-reduction test still lacks an assertion.

The test name implies a decrease, but only NaN/Infinity checks are performed. Consider asserting finalLoss <= initialLoss (with a small tolerance) or renaming the test to reflect intent.

♻️ Suggested assertion

         Assert.False(double.IsNaN(finalLoss), "Final loss should not be NaN");
         Assert.False(double.IsInfinity(finalLoss), "Final loss should not be Infinity");
+        Assert.True(finalLoss <= initialLoss + 1e-8,
+            $"Expected loss to decrease (initial {initialLoss}, final {finalLoss}).");

[sonarqubecloud]

Quality Gate failed

Failed conditions
0.0% Coverage on New Code (required ≥ 80%)

See analysis details on SonarQube Cloud