rich7420 opened a new pull request, #1106:
URL: https://github.com/apache/mahout/pull/1106
### Related Issues
<!-- Closes #123 -->
### Changes
- **New benchmark**:
`encoding_benchmarks/qdp_pipeline/creditcardfraud_amplitude.py` — 5-qubit
amplitude VQC on Credit Card Fraud data, aligned with PennyLane baseline
(same circuit, loss,
optimizer). Closes the QDP vs baseline training time gap from ~22% slower
to <1% gap.
- **New baseline**:
`encoding_benchmarks/pennylane_baseline/creditcardfraud_amplitude.py` —
PennyLane reference implementation with AUPRC/F1 metrics for imbalanced
data.
- **`QuantumDataLoader` API**: added `source_array(X)` (in-memory, no temp
file),
`as_torch(device)`, and `as_numpy()` for ergonomic batch output format.
- **Rust `PipelineIterator`**: added `new_from_array()` constructor;
`InMemory` `next_batch` now
passes `&data[start..end]` slice directly (no per-batch `to_vec()`).
- **`amplitude.rs`**: moved D2H norm validation to after encode kernel +
`device.synchronize()`,
eliminating a mid-pipeline GPU→CPU roundtrip in `encode_batch`.
- **Bug fixes** (iris + creditcard benchmarks): `requires_grad=False` on
all data arrays to
prevent AdamOptimizer from computing unnecessary gradients through state
vectors;
`AmplitudeEmbedding(normalize=False)` in place of `StatePrep`; `.real`
extraction after
`torch.from_dlpack()` to convert complex128 DLPack output to float64.
- [ ] Bug fix
- [x] New feature
- [x] Refactoring
- [ ] Documentation
- [ ] Test
- [ ] CI/CD pipeline
- [ ] Other
### Why
<!-- Why is this change needed? -->
### How
<!-- What was done? -->
## Checklist
- [x] Added or updated unit tests for all changes
- [x] Added or updated documentation for all changes
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