Files
nvbench/python/cuda/bench/__init__.pyi
Oleksandr Pavlyk 4a22923721 Add BenchmarkResult JSON results namespace and summary CLI
Move NVBench JSON result parsing into cuda.bench.results with explicit
BenchmarkResult, BenchmarkResultDevice, BenchmarkResultSummary,
SubBenchmarkResult, and SubBenchmarkState types. Remove the result reader
from the top-level cuda.bench namespace and require construction through
BenchmarkResult.from_json() or BenchmarkResult.empty().

Preserve bulk sample/frequency parsing and estimator helpers while making
summaries rich objects that retain tag/name/hint/hide/description metadata.

Add nvbench-json-summary to render NVBench JSON output as an NVBench-style
markdown summary table, including axis formatting, device sections, hidden
summary filtering, and summary hint formatting.

Update packaging, type stubs, and tests for the new namespace, renamed
classes, Python 3.10-compatible annotations, and summary-table generation.
2026-05-12 09:58:30 -05:00

128 lines
5.2 KiB
Python

# Copyright 2025-2026 NVIDIA Corporation
#
# Licensed under the Apache License, Version 2.0 with the LLVM exception
# (the "License"); you may not use this file except in compliance with
# the License.
#
# You may obtain a copy of the License at
#
# http://llvm.org/foundation/relicensing/LICENSE.txt
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================
# PLEASE KEEP IN SYNC WITH py_nvbench.cpp FILE
# ============================================
# Please be sure to keep these type hints and docstring in sync
# with the pybind11 bindings in ``../../src/py_nvbench.cpp``
# Use mypy's stubgen to auto-generate stubs using
# ``stubgen -m cuda.nvbench._nvbench`` and compare
# stubs in generated out/cuda/nvbench/_nvbench.pyi
# with definitions given here.
from collections.abc import (
Callable,
Sequence,
)
from typing import (
Optional,
Self,
SupportsFloat,
SupportsInt,
Union,
)
class CudaStream:
def __cuda_stream__(self) -> tuple[int, int]: ...
def addressof(self) -> int: ...
class Benchmark:
def get_name(self) -> str: ...
def add_int64_axis(self, name: str, values: Sequence[SupportsInt]) -> Self: ...
def add_int64_power_of_two_axis(
self, name: str, values: Sequence[SupportsInt]
) -> Self: ...
def add_float64_axis(self, name: str, values: Sequence[SupportsFloat]) -> Self: ...
def add_string_axis(self, name: str, values: Sequence[str]) -> Self: ...
def set_name(self, name: str) -> Self: ...
def set_run_once(self, v: bool) -> Self: ...
def set_skip_time(self, duration_seconds: SupportsFloat) -> Self: ...
def set_throttle_recovery_delay(self, delay_seconds: SupportsFloat) -> Self: ...
def set_throttle_threshold(self, threshold: SupportsFloat) -> Self: ...
def set_timeout(self, duration_seconds: SupportsFloat) -> Self: ...
def set_stopping_criterion(self, criterion: str) -> Self: ...
def set_criterion_param_float64(self, name: str, value: SupportsFloat) -> Self: ...
def set_criterion_param_int64(self, name: str, value: SupportsInt) -> Self: ...
def set_criterion_param_string(self, name: str, value: str) -> Self: ...
def set_min_samples(self, count: SupportsInt) -> Self: ...
def set_is_cpu_only(self, is_cpu_only: bool) -> Self: ...
class Launch:
def get_stream(self) -> CudaStream: ...
class State:
def has_device(self) -> bool: ...
def has_printers(self) -> bool: ...
def get_device(self) -> Union[int, None]: ...
def get_stream(self) -> CudaStream: ...
def get_int64(self, name: str) -> int: ...
def get_int64_or_default(self, name: str, default_value: SupportsInt) -> int: ...
def get_float64(self, name: str) -> float: ...
def get_float64_or_default(
self, name: str, default_value: SupportsFloat
) -> float: ...
def get_string(self, name: str) -> str: ...
def get_string_or_default(self, name: str, default_value: str) -> str: ...
def add_element_count(
self, count: SupportsInt, column_name: Optional[str] = None
) -> None: ...
def set_element_count(self, count: SupportsInt) -> None: ...
def get_element_count(self) -> int: ...
def skip(self, reason: str) -> None: ...
def is_skipped(self) -> bool: ...
def get_skip_reason(self) -> str: ...
def add_global_memory_reads(
self, nbytes: SupportsInt, /, column_name: str = ""
) -> None: ...
def add_global_memory_writes(
self, nbytes: SupportsInt, /, column_name: str = ""
) -> None: ...
def get_benchmark(self) -> Benchmark: ...
def get_throttle_threshold(self) -> float: ...
def set_throttle_threshold(self, threshold_fraction: SupportsFloat) -> None: ...
def get_min_samples(self) -> int: ...
def set_min_samples(self, min_samples_count: SupportsInt) -> None: ...
def get_disable_blocking_kernel(self) -> bool: ...
def set_disable_blocking_kernel(self, flag: bool) -> None: ...
def get_run_once(self) -> bool: ...
def set_run_once(self, run_once_flag: bool) -> None: ...
def get_timeout(self) -> float: ...
def set_timeout(self, duration: SupportsFloat) -> None: ...
def get_blocking_kernel_timeout(self) -> float: ...
def set_blocking_kernel_timeout(self, duration: SupportsFloat) -> None: ...
def exec(
self,
fn: Callable[[Launch], None],
/,
*,
batched: Optional[bool] = True,
sync: Optional[bool] = False,
): ...
def get_short_description(self) -> str: ...
def add_summary(
self, column_name: str, value: Union[SupportsInt, SupportsFloat, str]
) -> None: ...
def get_axis_values(self) -> dict[str, int | float | str]: ...
def get_axis_values_as_string(self, color: bool = ...) -> str: ...
def get_stopping_criterion(self) -> str: ...
def register(fn: Callable[[State], None]) -> Benchmark: ...
def run_all_benchmarks(argv: Sequence[str]) -> None: ...
class NVBenchRuntimeError(RuntimeError): ...