Files
cutlass/python/cutlass/cpp/include/conv/convolution.h
ANIKET SHIVAM d572cc1aab CUTLASS 3.1 (#915)
Co-authored-by: Aniket Shivam <ashivam@nvidia.com>
2023-04-14 23:19:34 -04:00

92 lines
4.7 KiB
C++

/***************************************************************************************************
* Copyright (c) 2017 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* 1. Redistributions of source code must retain the above copyright notice, this
* list of conditions and the following disclaimer.
*
* 2. Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
*
* 3. Neither the name of the copyright holder nor the names of its
* contributors may be used to endorse or promote products derived from
* this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*
**************************************************************************************************/
/* \file
\brief Bind convolution related enum types to python
*/
#pragma once
#include <pybind11/pybind11.h>
#include <pybind11/stl_bind.h>
#include "conv_problem_size.h"
#include "host.h"
#include "cutlass/conv/convolution.h"
namespace py = pybind11;
void bind_convolution(py::module &m) {
//
// Enumerate types
// cutlass/include/cutlass/conv/convolution.h
//
/// Convolutional operator
py::enum_<cutlass::conv::Operator>(m, "Operator", R"pbdoc(Convolutional operator)pbdoc")
.value("fprop", cutlass::conv::Operator::kFprop, "Forward propagation")
.value("dgrad", cutlass::conv::Operator::kDgrad, "Activation grad")
.value("wgrad", cutlass::conv::Operator::kWgrad, "Weight grad");
/// Distinguishes convolution from cross correlation
py::enum_<cutlass::conv::Mode>(m, "Mode")
.value("cross_correlation", cutlass::conv::Mode::kCrossCorrelation)
.value("convolution", cutlass::conv::Mode::kConvolution);
/// Selects among several implementation variants trading off performance with simplicity
py::enum_<cutlass::conv::IteratorAlgorithm>(m, "IteratorAlgorithm",
R"pbdoc(Selects among several implementation variants trading off performance with simplicity)pbdoc")
.value("analytic", cutlass::conv::IteratorAlgorithm::kAnalytic, R"pbdoc(functionally correct in all cases but lower performance)pbdoc")
.value("optimized", cutlass::conv::IteratorAlgorithm::kOptimized, R"pbdoc(optimized for R <= 32, S <= 32 and unity-stride dgrad)pbdoc")
.value("fixed_channels", cutlass::conv::IteratorAlgorithm::kFixedChannels, R"pbdoc(Analytic algorithm optimized for fixed channel count (C == AccessSize))pbdoc")
.value("few_channels", cutlass::conv::IteratorAlgorithm::kFewChannels, R"pbdoc(Analytic algorithm optimized for few channels (C divisible by AccessSize))pbdoc");
/// Distinguishes among partial specializations that accelerate certain problems where convolution
/// stride is unit.
py::enum_<cutlass::conv::StrideSupport>(m, "StrideSupport",
R"pbdoc(Distinguishes among partial specializations that accelerate certain problems where convolution
stride is unit.)pbdoc")
.value("strided", cutlass::conv::StrideSupport::kStrided, R"pbdoc(arbitrary convolution stride)pbdoc")
.value("unity", cutlass::conv::StrideSupport::kUnity, R"pbdoc(unit convolution stride)pbdoc");
/// Identifies split-K mode
py::enum_<cutlass::conv::SplitKMode>(m, "SplitKMode")
.value("None", cutlass::conv::SplitKMode::kNone)
.value("Serial", cutlass::conv::SplitKMode::kSerial)
.value("Parallel", cutlass::conv::SplitKMode::kParallel);
// Conv problem sizes
bind_conv_problem_size(m);
//
// host helper functions
//
py::module_ host_submodule = m.def_submodule("host");
bind_conv_host_helper(host_submodule);
}