ryankert01 opened a new pull request, #1365:
URL: https://github.com/apache/mahout/pull/1365
## Problem
`QdpBenchmark.run_latency()` and `run_throughput()` raised `TypeError` on
any call because `api.py` was unconditionally passing `dtype="f32"` to
`run_throughput_pipeline_py()` — but `QdpBenchmark` had no `_dtype` field and
no `.dtype()` builder method. The Rust binding already accepted `dtype`
(defaulting to `"f64"`) but the Python layer never wired it up.
## Changes
- Add `_dtype: str = "f64"` to `QdpBenchmark.__init__`
- Add `.dtype("f32" | "f64")` builder method with validation
- `"f32"` activates the zero-copy float32 batch path where the encoding
supports it; encodings without an f32 kernel fall back to f64 inside the Rust
pipeline automatically
- `"f64"` is the default, matching the Rust binding default and the
PyTorch reference path
- Pass `dtype=self._dtype` to both Rust call sites (`_run_throughput_rust`,
`_run_latency_rust`)
## Test
```python
from qumat_qdp import QdpBenchmark
for dt in ("f64", "f32"):
r = QdpBenchmark(device_id=0).qubits(4).encoding("amplitude").batches(4,
size=8).warmup(1).dtype(dt).run_latency()
print(f"dtype={dt}: {r.latency_ms_per_vector:.3f} ms/vector")
# dtype=f64: 0.019 ms/vector
# dtype=f32: 0.013 ms/vector
```
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