Files
composable_kernel/test/reduce/reduce_with_index.cpp
Qianfeng 63eee2d999 Overhaul to Reducton and its dependants (#237)
* Tiny fix in dynamic_buffer.hpp to support vectorized AtomicAdd for double type

* Update to host layer and host reduction

* Merge and remove reduction kernels

* Merge and remove reduction device interfaces and update pooling device interface

* Merge and remove useless reduction device instances

* Update to reduction profiler and reduction ctests

* Update to reduction and pooling examples and add one reduction example

* Change to reduction examples to let them testable by ctest

* Add explicit pass checking for reduction and pooling examples

* Explicit assignment of tensor shapes in example reduce_blockwise_two_call

* Use atomic_add to repace atomicAdd and add atomic_add for double type

* Add reduce ctest support for double data type

* Replace to_int_vector() by using c++ std::vector::assign()

* Keep DeviceReduceThreadWise separated from DeviceReduceBlockWise

* Merge DeviceReduceBlockWise and DeviceReduceMultiBlockAtomicAdd into DeviceReduceMultiBlock

* Add GetAtomicOperationZeroValue() support for AtomicMax

* Tiny change to reduce example README.md

* Fix some tiny issues due to branch merging

* Revoke previous change in dynamic_buffer.hpp and add atomic_add for double2_t

* Add reduce multiblock_atomic_add instances for fp64 to verify vectorized atomic_add on fp64

* Renaming

* Clean the header includings in device_reduce instances header files
2022-05-24 12:19:12 -05:00

246 lines
9.9 KiB
C++

#include "getopt.h"
#include "host_common_util.hpp"
#include "profile_reduce_impl.hpp"
using namespace ck;
static struct option long_options[] = {{"inLengths", required_argument, nullptr, 'D'},
{"reduceDimensions", required_argument, nullptr, 'R'},
{"scales", required_argument, nullptr, 'S'},
{"help", no_argument, nullptr, '?'},
{nullptr, 0, nullptr, 0}};
class SimpleAppArgs
{
private:
int option_index = 0;
public:
std::vector<size_t> inLengths;
std::vector<int> reduceDims;
std::vector<float> scales;
int data_type;
int init_method = 1;
public:
void show_usage(const char* cmd)
{
std::cout << "Usage of " << cmd << std::endl;
std::cout << "--inLengths or -D, comma separated list of input tensor dimension lengths "
"(only 4-d tensor supported)"
<< std::endl;
std::cout << "--reduceDimensions or -R comma seperated list of dimension indexes to reduce "
"(only 1 or 3 or 4 dimensions supported)"
<< std::endl;
std::cout << "--scales or -S, comma separated two float values for alpha and beta"
<< std::endl;
std::cout << "Arg1 -- data type (1: fp32, 3: int8, 5: bp16, 6: fp64)" << std::endl;
std::cout << "Arg2 -- init method(0=no init, 1=single integer value, 2=scope integer "
"value, 3=decimal value)"
<< std::endl;
};
int processArgs(int argc, char* argv[])
{
using ck::host_common::getTypeValuesFromString;
int ch;
while(1)
{
ch = getopt_long(argc, argv, "D:R:S:", long_options, &option_index);
if(ch == -1)
break;
switch(ch)
{
case 'D':
if(!optarg)
throw std::runtime_error("Invalid option format!");
inLengths = getTypeValuesFromString<size_t>(optarg);
break;
case 'R':
if(!optarg)
throw std::runtime_error("Invalid option format!");
reduceDims = getTypeValuesFromString<int>(optarg);
break;
case 'S':
if(!optarg)
throw std::runtime_error("Invalid option format!");
scales = getTypeValuesFromString<float>(optarg);
break;
case '?':
if(std::string(long_options[option_index].name) == "help")
{
show_usage(argv[0]);
return (-1);
};
break;
default: show_usage(argv[0]); return (-1);
};
};
if(optind + 2 > argc)
throw std::runtime_error("Invalid cmd-line arguments, more argumetns are needed!");
data_type = std::atoi(argv[optind++]);
init_method = std::atoi(argv[optind]);
if(scales.empty())
{
scales.push_back(1.0f);
scales.push_back(0.0f);
};
if(inLengths.size() != 4 ||
(reduceDims.size() != 1 && reduceDims.size() != 3 && reduceDims.size() != 4))
return (-1);
if(data_type != 0 && data_type != 1 && data_type != 3 && data_type != 5 && data_type != 6)
return (-1);
return (0);
};
};
bool test_reduce_with_index(int data_type,
int init_method,
std::vector<int> reduceDims,
std::vector<size_t> inLengths,
ReduceTensorOp reduceOpId,
bool propagateNan,
float alpha,
float beta)
{
using ck::profiler::profile_reduce_impl;
bool result = true;
if(data_type == 0)
{
result = profile_reduce_impl<float, float, float>(true,
init_method,
false,
false,
inLengths,
reduceDims,
reduceOpId,
propagateNan,
true,
alpha,
beta);
}
else if(data_type == 1)
{
result = profile_reduce_impl<ck::half_t, ck::half_t, ck::half_t>(true,
init_method,
false,
false,
inLengths,
reduceDims,
reduceOpId,
propagateNan,
true,
alpha,
beta);
}
else if(data_type == 3)
{
result = profile_reduce_impl<int8_t, int8_t, int8_t>(true,
init_method,
false,
false,
inLengths,
reduceDims,
reduceOpId,
propagateNan,
true,
alpha,
beta);
}
else if(data_type == 5)
{
result = profile_reduce_impl<ck::bhalf_t, float, ck::bhalf_t>(true,
init_method,
false,
false,
inLengths,
reduceDims,
reduceOpId,
propagateNan,
true,
alpha,
beta);
}
else if(data_type == 6)
{
result = profile_reduce_impl<double, double, double>(true,
init_method,
false,
false,
inLengths,
reduceDims,
reduceOpId,
propagateNan,
true,
alpha,
beta);
}
return (result);
};
constexpr ReduceTensorOp reduceOpId = ReduceTensorOp::AMAX;
constexpr bool propagateNan = false;
int main(int argc, char* argv[])
{
SimpleAppArgs args;
bool result = true;
if(argc == 1)
{
int data_type = 1;
int init_method = 2;
std::vector<size_t> inLengths{64, 4, 280, 80};
std::vector<std::vector<int>> v_reduceDims{
{0, 1, 2, 3}, {0, 1, 2}, {1, 2, 3}, {0, 1, 3}, {0, 2, 3}, {0}, {1}, {2}, {3}};
for(auto& reduceDims : v_reduceDims)
result = result && test_reduce_with_index(data_type,
init_method,
reduceDims,
inLengths,
reduceOpId,
propagateNan,
1.0f,
0.0f);
}
else
{
if(args.processArgs(argc, argv) < 0)
{
throw std::runtime_error(
"Invalid input arguments, test_reduce_with_index could not be executed!");
};
result = test_reduce_with_index(args.data_type,
args.init_method,
args.reduceDims,
args.inLengths,
reduceOpId,
propagateNan,
args.scales[0],
args.scales[1]);
}
std::cout << "test_reduce_with_index ..... " << (result ? "SUCCESS" : "FAILURE") << std::endl;
return (result ? 0 : -1);
}