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new 9abce4b4d docs(qdp): improve generated Markdown rendering (#1456)
9abce4b4d is described below
commit 9abce4b4d9d56efb68515de8ffc61324a32b4b5a
Author: Vic Wen <[email protected]>
AuthorDate: Sat Aug 8 14:05:03 2026 +0800
docs(qdp): improve generated Markdown rendering (#1456)
Signed-off-by: viiccwen <[email protected]>
---
qdp/qdp-python/qumat_qdp/_backend.py | 2 +-
qdp/qdp-python/qumat_qdp/api.py | 25 ++++++++++++++-----------
qdp/qdp-python/qumat_qdp/loader.py | 23 +++++++++++++----------
qdp/qdp-python/qumat_qdp/tensor.py | 2 +-
4 files changed, 29 insertions(+), 23 deletions(-)
diff --git a/qdp/qdp-python/qumat_qdp/_backend.py
b/qdp/qdp-python/qumat_qdp/_backend.py
index f44e19adc..583f84363 100644
--- a/qdp/qdp-python/qumat_qdp/_backend.py
+++ b/qdp/qdp-python/qumat_qdp/_backend.py
@@ -72,7 +72,7 @@ def get_backend() -> Backend:
"""Return the active backend.
Only the Rust backend is auto-detected. The PyTorch reference
- backend must be selected explicitly via :func:`force_backend`.
+ backend must be selected explicitly via ``force_backend()``.
"""
if _forced_backend is not None:
return _forced_backend
diff --git a/qdp/qdp-python/qumat_qdp/api.py b/qdp/qdp-python/qumat_qdp/api.py
index 98042b250..0cf66b8ce 100644
--- a/qdp/qdp-python/qumat_qdp/api.py
+++ b/qdp/qdp-python/qumat_qdp/api.py
@@ -18,15 +18,18 @@
Benchmark API: supports Rust-optimized pipeline and PyTorch reference backend.
Usage:
- from qumat_qdp import QdpBenchmark, ThroughputResult, LatencyResult
- # Rust backend (default):
- result = (QdpBenchmark(device_id=0).qubits(16).encoding("amplitude")
- .batches(100, size=64).warmup(2).run_throughput())
+```python
+from qumat_qdp import QdpBenchmark, ThroughputResult, LatencyResult
- # PyTorch reference (must be explicitly selected):
- result = (QdpBenchmark(device_id=0).backend("pytorch").qubits(16)
- .encoding("amplitude").batches(100, size=64).run_throughput())
+# Rust backend (default):
+result = (QdpBenchmark(device_id=0).qubits(16).encoding("amplitude")
+ .batches(100, size=64).warmup(2).run_throughput())
+
+# PyTorch reference (must be explicitly selected):
+result = (QdpBenchmark(device_id=0).backend("pytorch").qubits(16)
+ .encoding("amplitude").batches(100, size=64).run_throughput())
+```
"""
from __future__ import annotations
@@ -40,7 +43,7 @@ from typing import Any
class ThroughputResult:
"""Throughput benchmark measurement.
- Returned by :meth:`QdpBenchmark.run_throughput`. ``duration_sec`` is the
+ Returned by ``QdpBenchmark.run_throughput()``. ``duration_sec`` is the
measured timed section after any configured warmup batches.
``vectors_per_sec``
is computed over ``total_batches * batch_size`` encoded input vectors.
"""
@@ -53,7 +56,7 @@ class ThroughputResult:
class LatencyResult:
"""Latency benchmark measurement.
- Returned by :meth:`QdpBenchmark.run_latency`. ``duration_sec`` is the same
+ Returned by ``QdpBenchmark.run_latency()``. ``duration_sec`` is the same
timed interval used for throughput, and ``latency_ms_per_vector`` is the
average milliseconds per encoded input vector across the measured batches.
"""
@@ -206,7 +209,7 @@ class QdpBenchmark:
pipeline with any configured warmup batches; ``"pytorch"`` runs the
reference encoder loop and synchronizes CUDA timing when applicable.
- :returns: A :class:`ThroughputResult` containing elapsed seconds and
+ :returns: A ``ThroughputResult`` containing elapsed seconds and
encoded vectors per second.
:raises ValueError: If required benchmark parameters are missing.
:raises RuntimeError: If the Rust backend is selected but unavailable.
@@ -223,7 +226,7 @@ class QdpBenchmark:
method. The Rust backend reports latency from the native pipeline; the
PyTorch backend derives average latency from its throughput run.
- :returns: A :class:`LatencyResult` containing elapsed seconds and mean
+ :returns: A ``LatencyResult`` containing elapsed seconds and mean
milliseconds per encoded vector.
:raises ValueError: If required benchmark parameters are missing.
:raises RuntimeError: If the Rust backend is selected but unavailable.
diff --git a/qdp/qdp-python/qumat_qdp/loader.py
b/qdp/qdp-python/qumat_qdp/loader.py
index a70233650..bf225ad1e 100644
--- a/qdp/qdp-python/qumat_qdp/loader.py
+++ b/qdp/qdp-python/qumat_qdp/loader.py
@@ -18,13 +18,16 @@
Quantum Data Loader: Python builder for Rust-backed batch iterator.
Usage:
- from qumat_qdp import QuantumDataLoader
- loader = (QuantumDataLoader(device_id=0).qubits(16).encoding("amplitude")
- .batches(100, size=64).source_synthetic())
- for qt in loader:
- batch = torch.from_dlpack(qt)
- ...
+```python
+from qumat_qdp import QuantumDataLoader
+
+loader = (QuantumDataLoader(device_id=0).qubits(16).encoding("amplitude")
+ .batches(100, size=64).source_synthetic())
+for qt in loader:
+ batch = torch.from_dlpack(qt)
+ ...
+```
"""
from __future__ import annotations
@@ -333,7 +336,7 @@ class QuantumDataLoader:
``"iqp"``, ``"iqp-z"``, and ``"phase"``. Use these canonical
lowercase names because the selected backend receives the string
exactly
as supplied. The PyTorch reference backend supports the same methods
as
- :mod:`qumat_qdp.torch_ref`; use the native backend for methods that are
+ ``qumat_qdp.torch_ref``; use the native backend for methods that are
not available in the reference path.
:param method: Encoding method name.
@@ -415,7 +418,7 @@ class QuantumDataLoader:
Remote ``s3://`` and ``gs://`` paths are accepted when the native
remote
I/O feature is enabled; remote query strings and fragments are
rejected.
- Element precision is controlled by :meth:`dtype`. By default file
input is
+ Element precision is controlled by ``dtype()``. By default file input
is
loaded as ``float64`` (lossless). Selecting ``dtype("float32")``
narrows f64
file contents to f32 on load; values outside the f32 range become
``±Inf``.
``basis`` encoding is exempt: its values are integer state indices, so
it is
@@ -450,9 +453,9 @@ class QuantumDataLoader:
def dtype(self, name: str) -> QuantumDataLoader:
"""Set the element precision used when loading file sources.
- Applies to the native :meth:`source_file` path. ``"float64"`` (the
default)
+ Applies to the native ``source_file()`` path. ``"float64"`` (the
default)
loads file contents losslessly; ``"float32"`` narrows them to f32 on
load.
- See :meth:`source_file` for the cast caveats, including the ``basis``
+ See ``source_file()`` for the cast caveats, including the ``basis``
exemption.
:param name: ``"float32"``/``"f32"`` or ``"float64"``/``"f64"``
(case-insensitive).
diff --git a/qdp/qdp-python/qumat_qdp/tensor.py
b/qdp/qdp-python/qumat_qdp/tensor.py
index 986109fa0..aad9e7ca6 100644
--- a/qdp/qdp-python/qumat_qdp/tensor.py
+++ b/qdp/qdp-python/qumat_qdp/tensor.py
@@ -85,5 +85,5 @@ class QdpTensor:
return torch.from_dlpack(self)
-#: Backward-compatible alias for :class:`QdpTensor`.
+#: Backward-compatible alias for ``QdpTensor``.
QuantumTensor = QdpTensor
