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Unverified Commit 8784a72e authored by Po Yen Chen's avatar Po Yen Chen Committed by GitHub
Browse files

Modularize ckProfiler operations (#514)



* Re-structure ckProfiler source files

* Rename profiler.cpp to main.cpp

* Modularize ckProfiler operations

* Add description for profiler operations

* Use longer name to avoid name collision

* Use macro to delay expansion

* Use std::move() to avoid object copying

* Prohibit users from calling dtor

* Use macro to eliminate redundant code

* Make friend function hidden

* Add missing include directive <iostream>

* Fix wrong include directives

* Remove int8 from batchnorm-forward instances since it is not needed for forward training and could fail test
Co-authored-by: default avatarQianfeng Zhang <Qianfeng.Zhang@amd.com>
parent ad541ad6
......@@ -6,7 +6,8 @@
#include <initializer_list>
#include <cstdlib>
#include "profiler/include/profile_conv_fwd_bias_relu_impl.hpp"
#include "profiler/profile_conv_fwd_bias_relu_impl.hpp"
#include "profiler_operation_registry.hpp"
enum struct ConvDataType
{
......@@ -32,11 +33,14 @@ enum struct ConvOutputLayout
NHWK, // 1
};
#define OP_NAME "conv_fwd_bias_relu"
#define OP_DESC "Convolution Forward+Bias+ReLU"
int profile_conv_fwd_bias_relu(int argc, char* argv[])
{
if(argc != 25)
{
printf("arg1: tensor operation (conv_fwd_bias_relu: ForwardConvolution+Bias+ReLu)\n");
printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
printf("arg2: data type (0: fp32; 1: fp16)\n");
printf("arg3: input tensor layout (0: NCHW; 1: NHWC)\n");
printf("arg4: weight tensor layout (0: KCYX; 1: KYXC)\n");
......@@ -114,3 +118,5 @@ int profile_conv_fwd_bias_relu(int argc, char* argv[])
return 0;
}
REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_conv_fwd_bias_relu);
......@@ -6,7 +6,8 @@
#include <initializer_list>
#include <cstdlib>
#include "profiler/include/profile_conv_fwd_bias_relu_add_impl.hpp"
#include "profiler/profile_conv_fwd_bias_relu_add_impl.hpp"
#include "profiler_operation_registry.hpp"
enum struct ConvDataType
{
......@@ -32,12 +33,14 @@ enum struct ConvOutputLayout
NHWK, // 1
};
#define OP_NAME "conv_fwd_bias_relu_add"
#define OP_DESC "Convolution Forward+Bias+ReLU+Add"
int profile_conv_fwd_bias_relu_add(int argc, char* argv[])
{
if(argc != 25)
{
printf(
"arg1: tensor operation (conv_fwd_bias_relu_add: ForwardConvolution+Bias+ReLu+Add)\n");
printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
printf("arg2: data type (0: fp32; 1: fp16)\n");
printf("arg3: input tensor layout (0: NCHW; 1: NHWC)\n");
printf("arg4: weight tensor layout (0: KCYX; 1: KYXC)\n");
......@@ -115,3 +118,5 @@ int profile_conv_fwd_bias_relu_add(int argc, char* argv[])
return 0;
}
REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_conv_fwd_bias_relu_add);
......@@ -6,7 +6,8 @@
#include <initializer_list>
#include <cstdlib>
#include "profiler/include/profile_gemm_impl.hpp"
#include "profiler/profile_gemm_impl.hpp"
#include "profiler_operation_registry.hpp"
enum struct GemmMatrixLayout
{
......@@ -24,9 +25,12 @@ enum struct GemmDataType
INT8_INT8_INT8, // 3
};
#define OP_NAME "gemm"
#define OP_DESC "GEMM"
static void print_helper_msg()
{
std::cout << "arg1: tensor operation (gemm: GEMM)\n"
std::cout << "arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n"
<< "arg2: data type (0: fp32; 1: fp16; 2: bf16; 3: int8)\n"
<< "arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n"
<< " 1: A[m, k] * B[n, k] = C[m, n];\n"
......@@ -184,3 +188,5 @@ int profile_gemm(int argc, char* argv[])
return 1;
}
}
REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_gemm);
......@@ -6,7 +6,11 @@
#include <initializer_list>
#include <cstdlib>
#include "profiler/include/profile_gemm_add_add_fastgelu_impl.hpp"
#include "profiler/profile_gemm_add_add_fastgelu_impl.hpp"
#include "profiler_operation_registry.hpp"
#define OP_NAME "gemm_add_add_fastgelu"
#define OP_DESC "GEMM+Add+Add+FastGeLU"
int profile_gemm_add_add_fastgelu(int argc, char* argv[])
{
......@@ -29,7 +33,7 @@ int profile_gemm_add_add_fastgelu(int argc, char* argv[])
if(argc != 16)
{
// clang-format off
printf("arg1: tensor operation (gemm_add_add_fastgelu: GEMM+Add+Add+FastGeLU)\n");
printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
printf("arg2: data type (0: fp32; 1: fp16; 2: bf16; 3: int8)\n");
printf("arg3: matrix layout (0: E[m, n] = FastGeLU(A[m, k] * B[k, n] + D0[m, n] + D1[m, n]);\n");
printf(" 1: E[m, n] = FastGeLU(A[m, k] * B[n, k] + D0[m, n] + D1[m, n]);\n");
......@@ -150,3 +154,5 @@ int profile_gemm_add_add_fastgelu(int argc, char* argv[])
return 1;
}
}
REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_gemm_add_add_fastgelu);
......@@ -6,7 +6,11 @@
#include <initializer_list>
#include <cstdlib>
#include "profiler/include/profile_gemm_bias_add_reduce_impl.hpp"
#include "profiler/profile_gemm_bias_add_reduce_impl.hpp"
#include "profiler_operation_registry.hpp"
#define OP_NAME "gemm_bias_add_reduce"
#define OP_DESC "GEMM+Bias+Add+Reduce"
int profile_gemm_bias_add_reduce(int argc, char* argv[])
{
......@@ -26,7 +30,7 @@ int profile_gemm_bias_add_reduce(int argc, char* argv[])
if(!(argc == 14 || argc == 15))
{
printf("arg1: tensor operation (gemm: GEMM+bias+add+Reduce)\n");
printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
printf("arg2: data type (0: fp32; 1: fp16)\n");
printf("arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n");
printf(" 1: A[m, k] * B[n, k] = C[m, n];\n");
......@@ -159,3 +163,5 @@ int profile_gemm_bias_add_reduce(int argc, char* argv[])
return 0;
}
REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_gemm_bias_add_reduce);
......@@ -6,7 +6,11 @@
#include <initializer_list>
#include <cstdlib>
#include "profiler/include/profile_gemm_bilinear_impl.hpp"
#include "profiler/profile_gemm_bilinear_impl.hpp"
#include "profiler_operation_registry.hpp"
#define OP_NAME "gemm_bilinear"
#define OP_DESC "GEMM+Bilinear"
int profile_gemm_bilinear(int argc, char* argv[])
{
......@@ -29,7 +33,7 @@ int profile_gemm_bilinear(int argc, char* argv[])
if(argc != 17)
{
// clang-format off
printf("arg1: tensor operation (gemm_bilinear: GEMM+Bilinear)\n");
printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
printf("arg2: data type (0: fp32; 1: fp16; 2: bf16; 3: int8)\n");
printf("arg3: matrix layout (0: E[m, n] = alpha * A[m, k] * B[k, n] + beta * D[m, n];\n");
printf(" 1: E[m, n] = alpha * A[m, k] * B[n, k] + beta * D[m, n];\n");
......@@ -144,3 +148,5 @@ int profile_gemm_bilinear(int argc, char* argv[])
return 1;
}
}
REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_gemm_bilinear);
......@@ -6,7 +6,11 @@
#include <initializer_list>
#include <cstdlib>
#include "profiler/include/profile_gemm_reduce_impl.hpp"
#include "profiler/profile_gemm_reduce_impl.hpp"
#include "profiler_operation_registry.hpp"
#define OP_NAME "gemm_reduce"
#define OP_DESC "GEMM+Reduce"
int profile_gemm_reduce(int argc, char* argv[])
{
......@@ -26,7 +30,7 @@ int profile_gemm_reduce(int argc, char* argv[])
if(!(argc == 14 || argc == 15))
{
printf("arg1: tensor operation (gemm: GEMM+Reduce)\n");
printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
printf("arg2: data type (0: fp32; 1: fp16)\n");
printf("arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n");
printf(" 1: A[m, k] * B[n, k] = C[m, n];\n");
......@@ -146,3 +150,5 @@ int profile_gemm_reduce(int argc, char* argv[])
return 0;
}
REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_gemm_reduce);
......@@ -6,7 +6,8 @@
#include <initializer_list>
#include <cstdlib>
#include "profiler/include/profile_gemm_splitk_impl.hpp"
#include "profiler/profile_gemm_splitk_impl.hpp"
#include "profiler_operation_registry.hpp"
enum struct GemmMatrixLayout
{
......@@ -24,11 +25,14 @@ enum struct GemmDataType
INT8_INT8_INT8, // 3
};
#define OP_NAME "gemm_splitk"
#define OP_DESC "Split-K GEMM"
int profile_gemm_splitk(int argc, char* argv[])
{
if(argc != 15)
{
printf("arg1: tensor operation (gemm_splitk: Split-K GEMM)\n");
printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
printf("arg2: data type (0: fp32; 1: fp16; 2: bf16; 3: int8)\n");
printf("arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n");
printf(" 1: A[m, k] * B[n, k] = C[m, n];\n");
......@@ -146,3 +150,5 @@ int profile_gemm_splitk(int argc, char* argv[])
return 1;
}
}
REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_gemm_splitk);
......@@ -6,7 +6,8 @@
#include <iostream>
#include <numeric>
#include "profiler/include/profile_grouped_conv_bwd_weight_impl.hpp"
#include "profiler/profile_grouped_conv_bwd_weight_impl.hpp"
#include "profiler_operation_registry.hpp"
namespace {
......@@ -23,9 +24,12 @@ enum struct ConvDataType
BF16_F32_BF16, // 2
};
#define OP_NAME "grouped_conv_bwd_weight"
#define OP_DESC "Grouped Convolution Backward Weight"
static void print_helper_msg()
{
std::cout << "arg1: tensor operation (conv_bwd_weight: Convolution Backward Weight\n"
std::cout << "arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n"
<< "arg2: data type (0: Input fp32, Weight fp32, Output fp32\n"
<< " 1: Input fp16, Weight fp16, Output fp16\n"
<< " 2: Input bf16, Weight fp32, Output bf16)\n"
......@@ -174,3 +178,5 @@ int profile_grouped_conv_bwd_weight(int argc, char* argv[])
return 1;
}
REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_grouped_conv_bwd_weight);
......@@ -6,7 +6,8 @@
#include <initializer_list>
#include <cstdlib>
#include "profiler/include/profile_grouped_conv_fwd_impl.hpp"
#include "profiler/profile_grouped_conv_fwd_impl.hpp"
#include "profiler_operation_registry.hpp"
namespace {
......@@ -24,11 +25,14 @@ enum struct ConvDataType
INT8_INT8_INT8, // 3
};
#define OP_NAME "grouped_conv_fwd"
#define OP_DESC "Grouped Convolution Forward"
static void print_helper_msg()
{
std::cout
// clang-format off
<< "arg1: tensor operation (grouped_conv_fwd: Grouped Convolution Forward)\n"
<< "arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n"
<< "arg2: data type (0: Input fp32, Weight fp32, Output fp32\n"
<< " 1: Input fp16, Weight fp16, Output fp16\n"
<< " 2: Input bf16, Weight bf16, Output bf16\n"
......@@ -252,3 +256,5 @@ int profile_grouped_conv_fwd(int argc, char* argv[])
return 1;
}
REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_grouped_conv_fwd);
......@@ -6,7 +6,8 @@
#include <initializer_list>
#include <cstdlib>
#include "profiler/include/profile_grouped_gemm_impl.hpp"
#include "profiler/profile_grouped_gemm_impl.hpp"
#include "profiler_operation_registry.hpp"
enum struct GemmMatrixLayout
{
......@@ -44,11 +45,14 @@ std::vector<int> argToIntArray(char* input)
return out;
}
#define OP_NAME "grouped_gemm"
#define OP_DESC "Grouped GEMM"
int profile_grouped_gemm(int argc, char* argv[])
{
if(!(argc == 14))
{
printf("arg1: tensor operation (grouped_gemm: Grouped GEMM)\n");
printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
printf("arg2: data type (0: fp32; 1: fp16; 2: bf16; 3: int8)\n");
printf("arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n");
printf(" 1: A[m, k] * B[n, k] = C[m, n];\n");
......@@ -161,3 +165,5 @@ int profile_grouped_gemm(int argc, char* argv[])
return 0;
}
REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_grouped_gemm);
......@@ -5,8 +5,9 @@
#include <vector>
#include <unordered_map>
#include "profiler/include/data_type_enum.hpp"
#include "profiler/include/profile_groupnorm_impl.hpp"
#include "profiler/data_type_enum.hpp"
#include "profiler/profile_groupnorm_impl.hpp"
#include "profiler_operation_registry.hpp"
using ck::index_t;
......@@ -43,9 +44,12 @@ struct GroupnormArgParser
}
};
#define OP_NAME "groupnorm"
#define OP_DESC "Group Normalization"
void print_help_groupnorm()
{
std::cout << "arg1: tensor operation (groupnorm: Group normalization)\n"
std::cout << "arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n"
<< "arg2: data type (0: fp16; 1: fp32)\n"
<< "arg3: verification (0: no; 1: yes)\n"
<< "arg4: initialization (0: no init; 1: integer value; 2: decimal value)\n"
......@@ -104,3 +108,5 @@ int profile_groupnorm(int argc, char* argv[])
return 0;
}
REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_groupnorm);
......@@ -5,8 +5,9 @@
#include <vector>
#include <unordered_map>
#include "profiler/include/data_type_enum.hpp"
#include "profiler/include/profile_layernorm_impl.hpp"
#include "profiler/data_type_enum.hpp"
#include "profiler/profile_layernorm_impl.hpp"
#include "profiler_operation_registry.hpp"
using ck::index_t;
......@@ -96,3 +97,5 @@ int profile_layernorm(int argc, char* argv[])
return 0;
}
REGISTER_PROFILER_OPERATION("layernorm", "Layer Normalization", profile_layernorm);
......@@ -13,8 +13,9 @@
#include "ck/library/utility/host_common_util.hpp"
#include "profiler/include/profile_reduce_impl.hpp"
#include "profiler/include/data_type_enum.hpp"
#include "profiler/profile_reduce_impl.hpp"
#include "profiler/data_type_enum.hpp"
#include "profiler_operation_registry.hpp"
using namespace std;
......@@ -429,3 +430,5 @@ int profile_reduce(int argc, char* argv[])
return (0);
};
REGISTER_PROFILER_OPERATION("reduce", "Reduce", profile_reduce);
......@@ -5,7 +5,8 @@
#include <vector>
#include <unordered_map>
#include "profiler/include/profile_softmax_impl.hpp"
#include "profiler/profile_softmax_impl.hpp"
#include "profiler_operation_registry.hpp"
using ck::index_t;
using ck::profiler::SoftmaxDataType;
......@@ -164,3 +165,5 @@ int profile_softmax(int argc, char* argv[])
// profile_normalization(argc, argv);
// return 0;
// }
REGISTER_PROFILER_OPERATION("softmax", "Softmax", profile_softmax);
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstring>
#include <cstdlib>
#include <iostream>
int profile_gemm(int, char*[]);
int profile_gemm_splitk(int, char*[]);
int profile_gemm_bilinear(int, char*[]);
int profile_gemm_add_add_fastgelu(int, char*[]);
int profile_gemm_reduce(int, char*[]);
int profile_gemm_bias_add_reduce(int, char*[]);
int profile_batched_gemm(int, char*[]);
int profile_batched_gemm_gemm(int, char*[]);
int profile_batched_gemm_add_relu_gemm_add(int, char*[]);
int profile_batched_gemm_reduce(int, char*[]);
int profile_grouped_gemm(int, char*[]);
int profile_conv_fwd(int, char*[]);
int profile_conv_fwd_bias_relu(int, char*[]);
int profile_conv_fwd_bias_relu_add(int, char*[]);
int profile_conv_bwd_data(int, char*[]);
int profile_grouped_conv_fwd(int, char*[]);
int profile_grouped_conv_bwd_weight(int, char*[]);
int profile_softmax(int, char*[]);
int profile_layernorm(int, char*[]);
int profile_groupnorm(int, char*[]);
int profile_reduce(int, char*[]);
int profile_batchnorm_forward(int, char*[]);
int profile_batchnorm_backward(int, char*[]);
#include "profiler_operation_registry.hpp"
static void print_helper_message()
{
// clang-format off
printf("arg1: tensor operation (gemm: GEMM\n"
" gemm_splitk: Split-K GEMM\n"
" gemm_bilinear: GEMM+Bilinear\n"
" gemm_add_add_fastgelu: GEMM+Add+Add+FastGeLU\n"
" gemm_reduce: GEMM+Reduce\n"
" gemm_bias_add_reduce: GEMM+Bias+Add+Reduce\n"
" batched_gemm: Batched GEMM\n"
" batched_gemm_gemm: Batched+GEMM+GEMM\n"
" batched_gemm_add_relu_gemm_add: Batched+GEMM+bias+gelu+GEMM+bias\n"
" batched_gemm_reduce: Batched GEMM+Reduce\n"
" grouped_gemm: Grouped GEMM\n"
" conv_fwd: Convolution Forward\n"
" conv_fwd_bias_relu: ForwardConvolution+Bias+ReLU\n"
" conv_fwd_bias_relu_add: ForwardConvolution+Bias+ReLU+Add\n"
" conv_bwd_data: Convolution Backward Data\n"
" grouped_conv_fwd: Grouped Convolution Forward\n"
" grouped_conv_bwd_weight: Grouped Convolution Backward Weight\n"
" softmax: Softmax\n"
" reduce: Reduce\n"
" bnorm_fwd: Batchnorm forward\n");
// clang-format on
std::cout << "arg1: tensor operation " << ProfilerOperationRegistry::GetInstance() << std::endl;
}
int main(int argc, char* argv[])
......@@ -58,105 +16,15 @@ int main(int argc, char* argv[])
if(argc == 1)
{
print_helper_message();
return 0;
}
else if(strcmp(argv[1], "gemm") == 0)
{
return profile_gemm(argc, argv);
}
else if(strcmp(argv[1], "gemm_splitk") == 0)
{
return profile_gemm_splitk(argc, argv);
}
else if(strcmp(argv[1], "gemm_bilinear") == 0)
{
return profile_gemm_bilinear(argc, argv);
}
else if(strcmp(argv[1], "gemm_add_add_fastgelu") == 0)
{
return profile_gemm_add_add_fastgelu(argc, argv);
}
else if(strcmp(argv[1], "gemm_reduce") == 0)
{
return profile_gemm_reduce(argc, argv);
}
else if(strcmp(argv[1], "gemm_bias_add_reduce") == 0)
{
return profile_gemm_bias_add_reduce(argc, argv);
}
else if(strcmp(argv[1], "batched_gemm") == 0)
{
return profile_batched_gemm(argc, argv);
}
else if(strcmp(argv[1], "batched_gemm_gemm") == 0)
{
return profile_batched_gemm_gemm(argc, argv);
}
else if(strcmp(argv[1], "batched_gemm_add_relu_gemm_add") == 0)
{
return profile_batched_gemm_add_relu_gemm_add(argc, argv);
}
else if(strcmp(argv[1], "batched_gemm_reduce") == 0)
{
return profile_batched_gemm_reduce(argc, argv);
}
else if(strcmp(argv[1], "grouped_gemm") == 0)
else if(const auto operation = ProfilerOperationRegistry::GetInstance().Get(argv[1]);
operation.has_value())
{
return profile_grouped_gemm(argc, argv);
}
else if(strcmp(argv[1], "conv_fwd") == 0)
{
return profile_conv_fwd(argc, argv);
}
else if(strcmp(argv[1], "conv_fwd_bias_relu") == 0)
{
return profile_conv_fwd_bias_relu(argc, argv);
}
else if(strcmp(argv[1], "conv_fwd_bias_relu_add") == 0)
{
return profile_conv_fwd_bias_relu_add(argc, argv);
}
else if(strcmp(argv[1], "conv_bwd_data") == 0)
{
return profile_conv_bwd_data(argc, argv);
}
else if(strcmp(argv[1], "grouped_conv_fwd") == 0)
{
return profile_grouped_conv_fwd(argc, argv);
}
else if(strcmp(argv[1], "conv_bwd_weight") == 0)
{
return profile_grouped_conv_bwd_weight(argc, argv);
}
else if(strcmp(argv[1], "reduce") == 0)
{
return profile_reduce(argc, argv);
}
else if(strcmp(argv[1], "softmax") == 0)
{
return profile_softmax(argc, argv);
}
else if(strcmp(argv[1], "layernorm") == 0)
{
return profile_layernorm(argc, argv);
}
else if(strcmp(argv[1], "groupnorm") == 0)
{
return profile_groupnorm(argc, argv);
}
else if(strcmp(argv[1], "bnorm_fwd") == 0)
{
return profile_batchnorm_forward(argc, argv);
}
else if(strcmp(argv[1], "bnorm_bwd") == 0)
{
return profile_batchnorm_backward(argc, argv);
return (*operation)(argc, argv);
}
else
{
print_helper_message();
return 0;
std::cerr << "cannot find operation: " << argv[1] << std::endl;
return EXIT_FAILURE;
}
}
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <functional>
#include <iostream>
#include <iterator>
#include <map>
#include <optional>
#include <string_view>
#include <utility>
class ProfilerOperationRegistry final
{
ProfilerOperationRegistry() = default;
~ProfilerOperationRegistry() = default;
public:
using Operation = std::function<int(int, char*[])>;
private:
struct Entry final
{
explicit Entry(std::string_view description, Operation operation) noexcept
: description_(description), operation_(std::move(operation))
{
}
std::string_view description_;
Operation operation_;
};
std::map<std::string_view, Entry> entries_;
friend std::ostream& operator<<(std::ostream& stream, const ProfilerOperationRegistry& registry)
{
stream << "{\n";
for(auto& [name, entry] : registry.entries_)
{
stream << "\t" << name << ": " << entry.description_ << "\n";
}
stream << "}";
return stream;
}
public:
static ProfilerOperationRegistry& GetInstance()
{
static ProfilerOperationRegistry registry;
return registry;
}
std::optional<Operation> Get(std::string_view name) const
{
const auto found = entries_.find(name);
if(found == end(entries_))
{
return std::nullopt;
}
return (found->second).operation_;
}
bool Add(std::string_view name, std::string_view description, Operation operation)
{
return entries_
.emplace(std::piecewise_construct,
std::forward_as_tuple(name),
std::forward_as_tuple(description, std::move(operation)))
.second;
}
};
#define PP_CONCAT(x, y) PP_CONCAT_IMPL(x, y)
#define PP_CONCAT_IMPL(x, y) x##y
#define REGISTER_PROFILER_OPERATION(name, description, operation) \
static const bool PP_CONCAT(operation_registration_result_, __COUNTER__) = \
::ProfilerOperationRegistry::GetInstance().Add(name, description, operation)
include_directories(BEFORE
${PROJECT_SOURCE_DIR}/
${PROJECT_SOURCE_DIR}/profiler/include
)
include(googletest)
......
......@@ -3,7 +3,7 @@
#include <iostream>
#include "profiler/include/profile_batched_gemm_impl.hpp"
#include "profiler/profile_batched_gemm_impl.hpp"
namespace {
using ADataType = ck::bhalf_t;
......
......@@ -3,7 +3,7 @@
#include <iostream>
#include "profiler/include/profile_batched_gemm_impl.hpp"
#include "profiler/profile_batched_gemm_impl.hpp"
namespace {
using ADataType = ck::half_t;
......
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