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composable_kernel/profiler/src/profile_grouped_conv_fwd.cpp
Ville Pietilä 2cfc4209bb Profile optionally only a given instance.
2026-02-04 06:31:36 -05:00

439 lines
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// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#include <iostream>
#include <numeric>
#include <initializer_list>
#include <cstdlib>
#include "profiler/profile_grouped_conv_fwd_impl.hpp"
#include "profiler_operation_registry.hpp"
namespace {
enum struct ConvLayout
{
GNHWC_GKYXC_GNHWK, // 0
NHWGC_GKYXC_NHWGK, // 1
NGCHW_GKYXC_NGKHW, // 2
NGCHW_GKCYX_NGKHW, // 3
};
enum struct ConvDataType
{
F32_F32_F32, // 0
F16_F16_F16, // 1
BF16_BF16_BF16, // 2
INT8_INT8_INT8, // 3
F8_F8_F8, // 4
BF8_BF8_F8, // 5
F8_BF8_F8, // 6
BF8_F8_F8, // 7
F32_F32_F32_TF32, // 8
};
enum struct IndexType
{
INDEX_T, // 0
LONG_INDEX_T, // 1
};
#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 (" 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"
<< " 3: Input int8, Weight int8, Output int8\n"
<< " 4: Input fp8, Weight fp8, Output fp8\n"
<< " 5: Input bf8, Weight bf8, Output fp8\n"
<< " 6: Input fp8, Weight bf8, Output fp8\n"
<< " 7: Input bf8, Weight fp8, Output fp8\n"
<< " 8: Input fp32, Weight fp32, Output fp32, Compute tf32)\n"
<< "arg3: tensor layout (0: Input[G, N, Hi, Wi, C], Weight[G, K, Y, X, C], Output[G, N, Ho, Wo, K]\n"
<< " 1: Input[N, Hi, Wi, G, C], Weight[G, K, Y, X, C], Output[N, Ho, Wo, G, K]\n"
<< " 2: Input[N, G, C, Hi, Wi], Weight[G, K, Y, X, C], Output[N, "
"G, K, Ho, Wo]\n"
<< " 3: Input[N, G, C, Hi, Wi], Weight[G, K, C, Y, X], Output[N, "
"G, K, Ho, Wo])\n"
<< "arg4: indexing data type (0: 32-bit, 1: 64-bit)\n"
<< "arg5: verification (0: no, 1: yes)\n"
<< "arg6: initialization (0: no init, 1: integer value, 2: decimal value)\n"
<< "arg7: print tensor value (0: no; 1: yes)\n"
<< "arg8: time kernel (0: no, 1: yes)\n"
<< ck::utils::conv::get_conv_param_parser_helper_msg()
<< "last arg: run only given instance (string), optional\n"
<< std::endl;
// clang-format on
}
} // namespace
int profile_grouped_conv_fwd(int argc, char* argv[])
{
// 8 for control, 1 for num_dim_spatial
if(argc < 10)
{
print_helper_msg();
return 1;
}
const auto data_type = static_cast<ConvDataType>(std::stoi(argv[2]));
const auto layout = static_cast<ConvLayout>(std::stoi(argv[3]));
const auto index_type = static_cast<IndexType>(std::stoi(argv[4]));
const bool do_verification = std::stoi(argv[5]);
const int init_method = std::stoi(argv[6]);
const bool do_log = std::stoi(argv[7]);
const bool time_kernel = std::stoi(argv[8]);
const int num_dim_spatial = std::stoi(argv[9]);
// 9 for control, 1 for num_dim_spatial, 4 for G/N/K/C, 6 * num_dim_spatial, and optionally 1 for instance name
const int base_number_of_args = 9 + 1 + 4 + 6 * num_dim_spatial;
if(argc != base_number_of_args && argc != base_number_of_args + 1)
{
print_helper_msg();
return 1;
}
const auto params = ck::utils::conv::parse_conv_param(num_dim_spatial, 10, argv);
const std::string run_instance =
(argc == base_number_of_args + 1) ? std::string(argv[base_number_of_args]) : "";
using F32 = float;
using F16 = ck::half_t;
using BF16 = ck::bhalf_t;
using INT8 = int8_t;
using F8 = ck::f8_t;
using BF8 = ck::bf8_t;
using TF32 = ck::tf32_t;
//
using GNWC = ck::tensor_layout::convolution::GNWC;
using GNHWC = ck::tensor_layout::convolution::GNHWC;
using GNDHWC = ck::tensor_layout::convolution::GNDHWC;
using GKXC = ck::tensor_layout::convolution::GKXC;
using GKYXC = ck::tensor_layout::convolution::GKYXC;
using GKZYXC = ck::tensor_layout::convolution::GKZYXC;
// using GKCX = ck::tensor_layout::convolution::GKXC;
using GKCYX = ck::tensor_layout::convolution::GKCYX;
using GKCZYX = ck::tensor_layout::convolution::GKCZYX;
using GNWK = ck::tensor_layout::convolution::GNWK;
using GNHWK = ck::tensor_layout::convolution::GNHWK;
using GNDHWK = ck::tensor_layout::convolution::GNDHWK;
//
using NGCHW = ck::tensor_layout::convolution::NGCHW;
using NGCDHW = ck::tensor_layout::convolution::NGCDHW;
using NGKHW = ck::tensor_layout::convolution::NGKHW;
using NGKDHW = ck::tensor_layout::convolution::NGKDHW;
//
using NWGC = ck::tensor_layout::convolution::NWGC;
using NHWGC = ck::tensor_layout::convolution::NHWGC;
using NDHWGC = ck::tensor_layout::convolution::NDHWGC;
using NWGK = ck::tensor_layout::convolution::NWGK;
using NHWGK = ck::tensor_layout::convolution::NHWGK;
using NDHWGK = ck::tensor_layout::convolution::NDHWGK;
constexpr auto I1 = ck::Number<1>{};
constexpr auto I2 = ck::Number<2>{};
constexpr auto I3 = ck::Number<3>{};
auto profile = [&](auto num_dim_spatial_tmp,
auto in_layout,
auto wei_layout,
auto out_layout,
auto in_type,
auto wei_type,
auto out_type,
auto a_compute_type,
auto b_compute_type) {
constexpr ck::index_t NDimSpatial = num_dim_spatial_tmp.value;
using InLayout = decltype(in_layout);
using WeiLayout = decltype(wei_layout);
using OutLayout = decltype(out_layout);
using InDataType = decltype(in_type);
using WeiDataType = decltype(wei_type);
using OutDataType = decltype(out_type);
using AComputeType = decltype(a_compute_type);
using BComputeType = decltype(b_compute_type);
if(index_type == IndexType::INDEX_T)
{
bool pass = ck::profiler::profile_grouped_conv_fwd_impl<NDimSpatial,
InLayout,
WeiLayout,
OutLayout,
InDataType,
WeiDataType,
OutDataType,
AComputeType,
BComputeType,
ck::index_t>(
do_verification, init_method, do_log, time_kernel, params, run_instance);
return pass ? 0 : 1;
}
else if(index_type == IndexType::LONG_INDEX_T)
{
bool pass = ck::profiler::profile_grouped_conv_fwd_impl<NDimSpatial,
InLayout,
WeiLayout,
OutLayout,
InDataType,
WeiDataType,
OutDataType,
AComputeType,
BComputeType,
ck::long_index_t>(
do_verification, init_method, do_log, time_kernel, params, run_instance);
return pass ? 0 : 1;
}
else
{
std::cout << "this indexing data type is not implemented" << std::endl;
return 1;
}
};
// GNHWC_GKYXC_GNHWK
if(num_dim_spatial == 1 && layout == ConvLayout::GNHWC_GKYXC_GNHWK)
{
if(data_type == ConvDataType::F32_F32_F32)
{
return profile(I1, GNWC{}, GKXC{}, GNWK{}, F32{}, F32{}, F32{}, F32{}, F32{});
}
else if(data_type == ConvDataType::F16_F16_F16)
{
return profile(I1, GNWC{}, GKXC{}, GNWK{}, F16{}, F16{}, F16{}, F16{}, F16{});
}
else if(data_type == ConvDataType::BF16_BF16_BF16)
{
return profile(I1, GNWC{}, GKXC{}, GNWK{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
}
else if(data_type == ConvDataType::INT8_INT8_INT8)
{
return profile(I1, GNWC{}, GKXC{}, GNWK{}, INT8{}, INT8{}, INT8{}, INT8{}, INT8{});
}
else if(data_type == ConvDataType::F32_F32_F32_TF32)
{
return profile(I1, GNWC{}, GKXC{}, GNWK{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
}
}
else if(num_dim_spatial == 2 && layout == ConvLayout::GNHWC_GKYXC_GNHWK)
{
if(data_type == ConvDataType::F32_F32_F32)
{
return profile(I2, GNHWC{}, GKYXC{}, GNHWK{}, F32{}, F32{}, F32{}, F32{}, F32{});
}
else if(data_type == ConvDataType::F16_F16_F16)
{
return profile(I2, GNHWC{}, GKYXC{}, GNHWK{}, F16{}, F16{}, F16{}, F16{}, F16{});
}
else if(data_type == ConvDataType::BF16_BF16_BF16)
{
return profile(I2, GNHWC{}, GKYXC{}, GNHWK{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
}
else if(data_type == ConvDataType::INT8_INT8_INT8)
{
return profile(I2, GNHWC{}, GKYXC{}, GNHWK{}, INT8{}, INT8{}, INT8{}, INT8{}, INT8{});
}
else if(data_type == ConvDataType::F32_F32_F32_TF32)
{
return profile(I2, GNHWC{}, GKYXC{}, GNHWK{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
}
}
else if(num_dim_spatial == 3 && layout == ConvLayout::GNHWC_GKYXC_GNHWK)
{
if(data_type == ConvDataType::F32_F32_F32)
{
return profile(I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, F32{}, F32{}, F32{}, F32{}, F32{});
}
else if(data_type == ConvDataType::F16_F16_F16)
{
return profile(I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, F16{}, F16{}, F16{}, F16{}, F16{});
}
else if(data_type == ConvDataType::BF16_BF16_BF16)
{
return profile(
I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
}
else if(data_type == ConvDataType::INT8_INT8_INT8)
{
return profile(
I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, INT8{}, INT8{}, INT8{}, INT8{}, INT8{});
}
else if(data_type == ConvDataType::F32_F32_F32_TF32)
{
return profile(I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
}
}
// NHWGC_GKYXC_NHWGK
else if(num_dim_spatial == 1 && layout == ConvLayout::NHWGC_GKYXC_NHWGK)
{
if(data_type == ConvDataType::F32_F32_F32)
{
return profile(I1, NWGC{}, GKXC{}, NWGK{}, F32{}, F32{}, F32{}, F32{}, F32{});
}
else if(data_type == ConvDataType::F16_F16_F16)
{
return profile(I1, NWGC{}, GKXC{}, NWGK{}, F16{}, F16{}, F16{}, F16{}, F16{});
}
else if(data_type == ConvDataType::BF16_BF16_BF16)
{
return profile(I1, NWGC{}, GKXC{}, NWGK{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
}
else if(data_type == ConvDataType::INT8_INT8_INT8)
{
return profile(I1, NWGC{}, GKXC{}, NWGK{}, INT8{}, INT8{}, INT8{}, INT8{}, INT8{});
}
else if(data_type == ConvDataType::F32_F32_F32_TF32)
{
return profile(I1, NWGC{}, GKXC{}, NWGK{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
}
}
else if(num_dim_spatial == 2 && layout == ConvLayout::NHWGC_GKYXC_NHWGK)
{
if(data_type == ConvDataType::F32_F32_F32)
{
return profile(I2, NHWGC{}, GKYXC{}, NHWGK{}, F32{}, F32{}, F32{}, F32{}, F32{});
}
else if(data_type == ConvDataType::F16_F16_F16)
{
return profile(I2, NHWGC{}, GKYXC{}, NHWGK{}, F16{}, F16{}, F16{}, F16{}, F16{});
}
else if(data_type == ConvDataType::BF16_BF16_BF16)
{
return profile(I2, NHWGC{}, GKYXC{}, NHWGK{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
}
else if(data_type == ConvDataType::INT8_INT8_INT8)
{
return profile(I2, NHWGC{}, GKYXC{}, NHWGK{}, INT8{}, INT8{}, INT8{}, INT8{}, INT8{});
}
else if(data_type == ConvDataType::F32_F32_F32_TF32)
{
return profile(I2, NHWGC{}, GKYXC{}, NHWGK{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
}
}
else if(num_dim_spatial == 2 && layout == ConvLayout::NGCHW_GKYXC_NGKHW)
{
if(data_type == ConvDataType::F32_F32_F32)
{
return profile(I2, NGCHW{}, GKYXC{}, NGKHW{}, F32{}, F32{}, F32{}, F32{}, F32{});
}
else if(data_type == ConvDataType::F16_F16_F16)
{
return profile(I2, NGCHW{}, GKYXC{}, NGKHW{}, F16{}, F16{}, F16{}, F16{}, F16{});
}
else if(data_type == ConvDataType::BF16_BF16_BF16)
{
return profile(I2, NGCHW{}, GKYXC{}, NGKHW{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
}
else if(data_type == ConvDataType::F32_F32_F32_TF32)
{
return profile(I2, NGCHW{}, GKYXC{}, NGKHW{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
}
}
else if(num_dim_spatial == 2 && layout == ConvLayout::NGCHW_GKCYX_NGKHW)
{
if(data_type == ConvDataType::F32_F32_F32)
{
return profile(I2, NGCHW{}, GKCYX{}, NGKHW{}, F32{}, F32{}, F32{}, F32{}, F32{});
}
else if(data_type == ConvDataType::F16_F16_F16)
{
return profile(I2, NGCHW{}, GKCYX{}, NGKHW{}, F16{}, F16{}, F16{}, F16{}, F16{});
}
else if(data_type == ConvDataType::BF16_BF16_BF16)
{
return profile(I2, NGCHW{}, GKCYX{}, NGKHW{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
}
else if(data_type == ConvDataType::F32_F32_F32_TF32)
{
return profile(I2, NGCHW{}, GKCYX{}, NGKHW{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
}
}
else if(num_dim_spatial == 3 && layout == ConvLayout::NHWGC_GKYXC_NHWGK)
{
if(data_type == ConvDataType::F32_F32_F32)
{
return profile(I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F32{}, F32{}, F32{}, F32{}, F32{});
}
else if(data_type == ConvDataType::F16_F16_F16)
{
return profile(I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F16{}, F16{}, F16{}, F16{}, F16{});
}
else if(data_type == ConvDataType::BF16_BF16_BF16)
{
return profile(
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
}
else if(data_type == ConvDataType::INT8_INT8_INT8)
{
return profile(
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, INT8{}, INT8{}, INT8{}, INT8{}, INT8{});
}
else if(data_type == ConvDataType::F8_F8_F8)
{
return profile(I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F8{}, F8{}, F8{}, F8{}, F8{});
}
else if(data_type == ConvDataType::BF8_BF8_F8)
{
return profile(I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, BF8{}, BF8{}, F8{}, BF8{}, BF8{});
}
else if(data_type == ConvDataType::F8_BF8_F8)
{
return profile(I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F8{}, BF8{}, F8{}, F8{}, BF8{});
}
else if(data_type == ConvDataType::BF8_F8_F8)
{
return profile(I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, BF8{}, F8{}, F8{}, BF8{}, F8{});
}
else if(data_type == ConvDataType::F32_F32_F32_TF32)
{
return profile(I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
}
}
// NGCDHW_GKCZYX_NGKDHW
else if(num_dim_spatial == 3 && layout == ConvLayout::NGCHW_GKCYX_NGKHW)
{
if(data_type == ConvDataType::F32_F32_F32)
{
return profile(I3, NGCDHW{}, GKCZYX{}, NGKDHW{}, F32{}, F32{}, F32{}, F32{}, F32{});
}
else if(data_type == ConvDataType::F16_F16_F16)
{
return profile(I3, NGCDHW{}, GKCZYX{}, NGKDHW{}, F16{}, F16{}, F16{}, F16{}, F16{});
}
else if(data_type == ConvDataType::BF16_BF16_BF16)
{
return profile(
I3, NGCDHW{}, GKCZYX{}, NGKDHW{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
}
else if(data_type == ConvDataType::F32_F32_F32_TF32)
{
return profile(I3, NGCDHW{}, GKCZYX{}, NGKDHW{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
}
}
std::cout << "this data_type & layout is not implemented" << std::endl;
return 1;
}
REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_grouped_conv_fwd);
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