BatchNorm backward instance/external API/profiler/tests (#519)

* Refine the device batchnorm-backward base API templates and data type assignments

* Remove duplicated kernel file

* Add batchnorm backward instances and external API

* Add batchnorm-backward profiler and tests

* Add client example which uses batchnorm backward external API

* Merge test/batchnorm_fwd and test/batchnorm_bwd into one directory

* Loose the threshold for batchnorm-backward check_err()
This commit is contained in:
Qianfeng
2022-12-01 03:32:20 +08:00
committed by GitHub
parent 236bd148b9
commit 63af525c06
25 changed files with 2240 additions and 832 deletions

View File

@@ -0,0 +1,92 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include <iostream>
#include <initializer_list>
#include <vector>
#include <tuple>
#include <gtest/gtest.h>
#include "profiler/include/profile_batchnorm_backward_impl.hpp"
using F16 = ck::half_t;
using F32 = float;
using BF16 = ck::bhalf_t;
using F64 = double;
template <typename Tuple>
class TestBatchNormBwdRank4 : public ::testing::Test
{
private:
const double epsilon = std::numeric_limits<float>::epsilon();
protected:
using XDataType = std::tuple_element_t<0, Tuple>;
using DxDataType = std::tuple_element_t<1, Tuple>;
using DyDataType = std::tuple_element_t<2, Tuple>;
using AccDataType = std::tuple_element_t<3, Tuple>;
using ScaleDataType = std::tuple_element_t<4, Tuple>;
using BiasDataType = std::tuple_element_t<5, Tuple>;
using MeanVarDataType = std::tuple_element_t<6, Tuple>;
std::vector<std::vector<size_t>> list_of_lengths = {
{128, 16, 3, 1024}, {128, 16, 6, 512}, {1, 1, 1, 1}, {4, 4, 4, 4}, {32, 32, 32, 32}};
std::vector<int> reduceDims;
template <int NumReduceDim>
void Run()
{
for(auto& inOutLengths : list_of_lengths)
{
bool pass = true;
EXPECT_FALSE(reduceDims.size() != NumReduceDim);
pass = pass && ck::profiler::profile_batchnorm_backward_impl<XDataType,
DxDataType,
DyDataType,
AccDataType,
ScaleDataType,
BiasDataType,
MeanVarDataType,
4,
NumReduceDim>(
true, 3, false, false, inOutLengths, reduceDims, true, epsilon);
pass = pass && ck::profiler::profile_batchnorm_backward_impl<XDataType,
DxDataType,
DyDataType,
AccDataType,
ScaleDataType,
BiasDataType,
MeanVarDataType,
4,
NumReduceDim>(
true, 3, false, false, inOutLengths, reduceDims, false, epsilon);
EXPECT_TRUE(pass);
}
}
};
using KernelTypes = ::testing::Types<std::tuple<F16, F32, F32, F32, F16, F32, F32>,
std::tuple<F32, F32, F32, F32, F32, F32, F32>,
std::tuple<BF16, F32, F32, F32, BF16, F32, F32>,
std::tuple<F64, F64, F64, F64, F64, F64, F64>>;
TYPED_TEST_SUITE(TestBatchNormBwdRank4, KernelTypes);
// nhwc
TYPED_TEST(TestBatchNormBwdRank4, nhwc)
{
this->reduceDims = {0, 1, 2};
this->template Run<3>();
}
// nchw
TYPED_TEST(TestBatchNormBwdRank4, nchw)
{
this->reduceDims = {0, 2, 3};
this->template Run<3>();
}