mirror of
https://github.com/ROCm/composable_kernel.git
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[rocm-libraries] ROCm/rocm-libraries#4797 (commit 1a30400)
[CK_TILE] Add CK Tile bwd weight profiler MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit ## Motivation To compare old CK and CK Tile, we need to extend the current CK profiler to support running also CK Tile instance with the same API. In order to have the same instance coverage in CK Tile compared to the old CK, I've added code generation from old CK configurations to CK Tile instances using the CK Builder. ## Technical Details - The codegen python script for CK Tile fwd convs is extended to support also bwd weight and bwd data. - The generated instances are added to the CMake build (target `device_grouped_conv_bwd_weight_tile_instance`s). - A new profiler op (`grouped_conv_bwd_weight_tile`) has been added to the CK Profiler.
This commit is contained in:
Ville Pietilä
committed by
assistant-librarian[bot]
assistant-librarian[bot]
parent
fc1e1a5155
commit
ae4e632c7d
@@ -45,6 +45,7 @@ if(SUPPORTED_GPU_TARGETS MATCHES "gfx9")
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endif()
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if(CK_EXPERIMENTAL_BUILDER)
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list(APPEND PROFILER_OPS profile_grouped_conv_fwd_tile.cpp)
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list(APPEND PROFILER_OPS profile_grouped_conv_bwd_weight_tile.cpp)
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endif()
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endif()
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@@ -273,6 +274,7 @@ endif()
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if(SUPPORTED_GPU_TARGETS MATCHES "gfx9")
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if(CK_EXPERIMENTAL_BUILDER)
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list(APPEND DEVICE_INSTANCES device_grouped_conv_fwd_tile_instances)
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list(APPEND DEVICE_INSTANCES device_grouped_conv_bwd_weight_tile_instances)
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endif()
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endif()
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@@ -55,10 +55,263 @@ static void print_helper_msg()
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// clang-format on
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}
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void print_bwd_data_instances(ConvDataType data_type,
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ConvLayout layout,
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ck::index_t num_dim_spatial)
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{
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auto print_available_instances = [&](auto num_dim_spatial_tmp,
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auto in_layout,
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auto wei_layout,
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auto out_layout,
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auto in_type,
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auto wei_type,
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auto out_type,
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auto compute_type) {
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constexpr ck::index_t NDimSpatial = num_dim_spatial_tmp.value;
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using InLayout = decltype(in_layout);
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using WeiLayout = decltype(wei_layout);
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using OutLayout = decltype(out_layout);
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using InDataType = decltype(in_type);
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using WeiDataType = decltype(wei_type);
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using OutDataType = decltype(out_type);
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using ComputeType = decltype(compute_type);
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using PassThrough = ck::tensor_operation::element_wise::PassThrough;
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ck::profiler::bwd_data::print_instances<NDimSpatial,
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InLayout,
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WeiLayout,
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OutLayout,
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InDataType,
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WeiDataType,
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OutDataType,
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PassThrough,
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PassThrough,
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PassThrough,
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ComputeType>();
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};
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constexpr auto I2 = ck::Number<2>{};
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constexpr auto I3 = ck::Number<3>{};
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using F32 = float;
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using F16 = ck::half_t;
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using BF16 = ck::bhalf_t;
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using TF32 = ck::tf32_t;
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using namespace ck::tensor_layout::convolution;
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using namespace ck::profiler;
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if(num_dim_spatial == 2)
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{
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if(layout == ConvLayout::GNHWC_GKYXC_GNHWK)
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{
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if(data_type == ConvDataType::F32_F32_F32)
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{
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return print_available_instances(
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I2, GNHWC{}, GKYXC{}, GNHWK{}, F32{}, F32{}, F32{}, F32{});
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}
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else if(data_type == ConvDataType::F16_F16_F16)
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{
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return print_available_instances(
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I2, GNHWC{}, GKYXC{}, GNHWK{}, F16{}, F16{}, F16{}, F16{});
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}
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else if(data_type == ConvDataType::BF16_BF16_BF16)
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{
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return print_available_instances(
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I2, GNHWC{}, GKYXC{}, GNHWK{}, BF16{}, BF16{}, BF16{}, BF16{});
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}
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else if(data_type == ConvDataType::F32_F32_F32_TF32)
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{
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return print_available_instances(
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I2, GNHWC{}, GKYXC{}, GNHWK{}, F32{}, F32{}, F32{}, TF32{});
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}
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}
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else if(layout == ConvLayout::NHWGC_GKYXC_NHWGK)
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{
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if(data_type == ConvDataType::F32_F32_F32)
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{
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return print_available_instances(
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I2, NHWGC{}, GKYXC{}, NHWGK{}, F32{}, F32{}, F32{}, F32{});
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}
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else if(data_type == ConvDataType::F16_F16_F16)
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{
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return print_available_instances(
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I2, NHWGC{}, GKYXC{}, NHWGK{}, F16{}, F16{}, F16{}, F16{});
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}
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else if(data_type == ConvDataType::BF16_BF16_BF16)
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{
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return print_available_instances(
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I2, NHWGC{}, GKYXC{}, NHWGK{}, BF16{}, BF16{}, BF16{}, BF16{});
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}
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else if(data_type == ConvDataType::F32_F32_F32_TF32)
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{
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return print_available_instances(
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I2, NHWGC{}, GKYXC{}, NHWGK{}, F32{}, F32{}, F32{}, TF32{});
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}
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}
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else if(layout == ConvLayout::NGCHW_GKYXC_NGKHW)
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{
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if(data_type == ConvDataType::F32_F32_F32)
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{
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return print_available_instances(
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I2, NGCHW{}, GKYXC{}, NGKHW{}, F32{}, F32{}, F32{}, F32{});
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}
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else if(data_type == ConvDataType::F16_F16_F16)
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{
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return print_available_instances(
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I2, NGCHW{}, GKYXC{}, NGKHW{}, F16{}, F16{}, F16{}, F16{});
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}
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else if(data_type == ConvDataType::BF16_BF16_BF16)
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{
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return print_available_instances(
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I2, NGCHW{}, GKYXC{}, NGKHW{}, BF16{}, BF16{}, BF16{}, BF16{});
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}
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else if(data_type == ConvDataType::F32_F32_F32_TF32)
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{
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return print_available_instances(
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I2, NGCHW{}, GKYXC{}, NGKHW{}, F32{}, F32{}, F32{}, TF32{});
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}
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}
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else if(layout == ConvLayout::NGCHW_GKCYX_NGKHW)
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{
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if(data_type == ConvDataType::F32_F32_F32)
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{
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return print_available_instances(
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I2, NGCHW{}, GKCYX{}, NGKHW{}, F32{}, F32{}, F32{}, F32{});
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}
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else if(data_type == ConvDataType::F16_F16_F16)
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{
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return print_available_instances(
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I2, NGCHW{}, GKCYX{}, NGKHW{}, F16{}, F16{}, F16{}, F16{});
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}
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else if(data_type == ConvDataType::BF16_BF16_BF16)
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{
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return print_available_instances(
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I2, NGCHW{}, GKCYX{}, NGKHW{}, BF16{}, BF16{}, BF16{}, BF16{});
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}
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else if(data_type == ConvDataType::F32_F32_F32_TF32)
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{
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return print_available_instances(
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I2, NGCHW{}, GKCYX{}, NGKHW{}, F32{}, F32{}, F32{}, TF32{});
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}
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}
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}
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else if(num_dim_spatial == 3)
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{
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if(layout == ConvLayout::GNHWC_GKYXC_GNHWK)
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{
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if(data_type == ConvDataType::F32_F32_F32)
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{
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return print_available_instances(
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I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, F32{}, F32{}, F32{}, F32{});
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}
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else if(data_type == ConvDataType::F16_F16_F16)
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{
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return print_available_instances(
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I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, F16{}, F16{}, F16{}, F16{});
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}
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else if(data_type == ConvDataType::BF16_BF16_BF16)
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{
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return print_available_instances(
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I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, BF16{}, BF16{}, BF16{}, BF16{});
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}
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else if(data_type == ConvDataType::F32_F32_F32_TF32)
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{
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return print_available_instances(
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I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, F32{}, F32{}, F32{}, TF32{});
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}
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}
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else if(layout == ConvLayout::NHWGC_GKYXC_NHWGK)
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{
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if(data_type == ConvDataType::F32_F32_F32)
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{
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return print_available_instances(
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I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F32{}, F32{}, F32{}, F32{});
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}
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else if(data_type == ConvDataType::F16_F16_F16)
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{
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return print_available_instances(
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I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F16{}, F16{}, F16{}, F16{});
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}
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else if(data_type == ConvDataType::BF16_BF16_BF16)
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{
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return print_available_instances(
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I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, BF16{}, BF16{}, BF16{}, BF16{});
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}
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else if(data_type == ConvDataType::F32_F32_F32_TF32)
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{
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return print_available_instances(
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I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F32{}, F32{}, F32{}, TF32{});
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}
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}
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else if(layout == ConvLayout::NGCHW_GKYXC_NGKHW)
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{
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if(data_type == ConvDataType::F32_F32_F32)
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{
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return print_available_instances(
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I3, NGCDHW{}, GKZYXC{}, NGKDHW{}, F32{}, F32{}, F32{}, F32{});
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}
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else if(data_type == ConvDataType::F16_F16_F16)
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{
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return print_available_instances(
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I3, NGCDHW{}, GKZYXC{}, NGKDHW{}, F16{}, F16{}, F16{}, F16{});
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}
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else if(data_type == ConvDataType::BF16_BF16_BF16)
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{
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return print_available_instances(
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I3, NGCDHW{}, GKZYXC{}, NGKDHW{}, BF16{}, BF16{}, BF16{}, BF16{});
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}
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else if(data_type == ConvDataType::F32_F32_F32_TF32)
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{
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return print_available_instances(
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I3, NGCDHW{}, GKZYXC{}, NGKDHW{}, F32{}, F32{}, F32{}, TF32{});
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}
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}
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else if(layout == ConvLayout::NGCHW_GKYXC_NGKHW)
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{
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if(data_type == ConvDataType::F32_F32_F32)
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{
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return print_available_instances(
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I3, NGCDHW{}, GKCZYX{}, NGKDHW{}, F32{}, F32{}, F32{}, F32{});
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}
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else if(data_type == ConvDataType::F16_F16_F16)
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{
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return print_available_instances(
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I3, NGCDHW{}, GKCZYX{}, NGKDHW{}, F16{}, F16{}, F16{}, F16{});
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}
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else if(data_type == ConvDataType::BF16_BF16_BF16)
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{
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return print_available_instances(
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I3, NGCDHW{}, GKCZYX{}, NGKDHW{}, BF16{}, BF16{}, BF16{}, BF16{});
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}
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else if(data_type == ConvDataType::F32_F32_F32_TF32)
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{
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return print_available_instances(
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I3, NGCDHW{}, GKCZYX{}, NGKDHW{}, F32{}, F32{}, F32{}, TF32{});
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}
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}
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}
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std::cout << "[CK_PROFILER] This data_type & layout is not implemented" << std::endl;
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}
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} // namespace
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int profile_grouped_conv_bwd_data(int argc, char* argv[])
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{
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if(argc == 6 && std::string(argv[5]) == "--instances")
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{
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const auto data_type = static_cast<ConvDataType>(std::stoi(argv[2]));
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const auto layout = static_cast<ConvLayout>(std::stoi(argv[3]));
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const ck::index_t num_dim_spatial = static_cast<ck::index_t>(std::stoi(argv[4]));
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print_bwd_data_instances(data_type, layout, num_dim_spatial);
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return 0;
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}
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// Parse optional named arguments first
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ck::index_t instance_index = -1;
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bool list_instances = false;
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@@ -69,10 +69,297 @@ static void print_helper_msg()
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<< std::endl;
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}
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void print_bwd_weight_instances(ConvDataType data_type,
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ConvLayout layout,
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ck::index_t num_dim_spatial)
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{
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auto print_available_instances = [&](auto num_dim_spatial_tmp,
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auto in_layout,
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auto wei_layout,
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auto out_layout,
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auto in_type,
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auto wei_type,
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auto out_type,
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auto compute_type_a,
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auto compute_type_b) {
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constexpr ck::index_t NDimSpatial = num_dim_spatial_tmp.value;
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using InLayout = decltype(in_layout);
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using WeiLayout = decltype(wei_layout);
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using OutLayout = decltype(out_layout);
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using InDataType = decltype(in_type);
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using WeiDataType = decltype(wei_type);
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using OutDataType = decltype(out_type);
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using ComputeTypeA = decltype(compute_type_a);
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using ComputeTypeB = decltype(compute_type_b);
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using PassThrough = ck::tensor_operation::element_wise::PassThrough;
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ck::profiler::bwd_weight::print_instances<NDimSpatial,
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InLayout,
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WeiLayout,
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OutLayout,
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InDataType,
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WeiDataType,
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OutDataType,
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PassThrough,
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PassThrough,
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PassThrough,
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ComputeTypeA,
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ComputeTypeB>();
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};
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constexpr auto I1 = ck::Number<1>{};
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constexpr auto I2 = ck::Number<2>{};
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constexpr auto I3 = ck::Number<3>{};
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using F32 = float;
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using F16 = ck::half_t;
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using BF16 = ck::bhalf_t;
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using F8 = ck::f8_t;
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using BF8 = ck::bf8_t;
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using TF32 = ck::tf32_t;
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using namespace ck::tensor_layout::convolution;
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if(num_dim_spatial == 1 && layout == ConvLayout::GNHWC_GKYXC_GNHWK)
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{
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if(data_type == ConvDataType::F32_F32_F32)
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{
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return print_available_instances(
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I1, GNWC{}, GKXC{}, GNWK{}, F32{}, F32{}, F32{}, F32{}, F32{});
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}
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if(data_type == ConvDataType::F16_F16_F16)
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{
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return print_available_instances(
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I1, GNWC{}, GKXC{}, GNWK{}, F16{}, F16{}, F16{}, F16{}, F16{});
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}
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if(data_type == ConvDataType::BF16_F32_BF16)
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{
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// fp32 atomic add is used for weight tensor in bf16 kernel
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return print_available_instances(
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I1, GNWC{}, GKXC{}, GNWK{}, BF16{}, F32{}, BF16{}, BF16{}, BF16{});
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}
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else if(data_type == ConvDataType::F32_F32_F32_TF32)
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{
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return print_available_instances(
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I1, GNWC{}, GKXC{}, GNWK{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
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}
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}
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if(num_dim_spatial == 2 && layout == ConvLayout::GNHWC_GKYXC_GNHWK)
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{
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if(data_type == ConvDataType::F32_F32_F32)
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{
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return print_available_instances(
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I2, GNHWC{}, GKYXC{}, GNHWK{}, F32{}, F32{}, F32{}, F32{}, F32{});
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}
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if(data_type == ConvDataType::F16_F16_F16)
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{
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return print_available_instances(
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I2, GNHWC{}, GKYXC{}, GNHWK{}, F16{}, F16{}, F16{}, F16{}, F16{});
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}
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if(data_type == ConvDataType::BF16_F32_BF16)
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{
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// fp32 atomic add is used for weight tensor in bf16 kernel
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return print_available_instances(
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I2, GNHWC{}, GKYXC{}, GNHWK{}, BF16{}, F32{}, BF16{}, BF16{}, BF16{});
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}
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else if(data_type == ConvDataType::F32_F32_F32_TF32)
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{
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return print_available_instances(
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I2, GNHWC{}, GKYXC{}, GNHWK{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
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}
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}
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if(num_dim_spatial == 2 && layout == ConvLayout::NHWGC_GKYXC_NHWGK)
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{
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if(data_type == ConvDataType::F32_F32_F32)
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{
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return print_available_instances(
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I2, NHWGC{}, GKYXC{}, NHWGK{}, F32{}, F32{}, F32{}, F32{}, F32{});
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}
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if(data_type == ConvDataType::F16_F16_F16)
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{
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return print_available_instances(
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I2, NHWGC{}, GKYXC{}, NHWGK{}, F16{}, F16{}, F16{}, F16{}, F16{});
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}
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if(data_type == ConvDataType::BF16_F32_BF16)
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{
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// fp32 atomic add is used for weight tensor in bf16 kernel
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return print_available_instances(
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I2, NHWGC{}, GKYXC{}, NHWGK{}, BF16{}, F32{}, BF16{}, BF16{}, BF16{});
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}
|
||||
if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, NHWGC{}, GKYXC{}, NHWGK{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F32_F32_F32_TF32)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, NHWGC{}, GKYXC{}, NHWGK{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
|
||||
}
|
||||
}
|
||||
else if(num_dim_spatial == 2 && layout == ConvLayout::NGCHW_GKYXC_NGKHW)
|
||||
{
|
||||
if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, NGCHW{}, GKYXC{}, NGKHW{}, F16{}, F16{}, F16{}, F16{}, F16{});
|
||||
}
|
||||
if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
// fp32 atomic add is used for weight tensor in bf16 kernel
|
||||
return print_available_instances(
|
||||
I2, NGCHW{}, GKYXC{}, NGKHW{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
}
|
||||
else if(num_dim_spatial == 2 && layout == ConvLayout::NGCHW_GKCYX_NGKHW)
|
||||
{
|
||||
if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, NGCHW{}, GKCYX{}, NGKHW{}, F16{}, F16{}, F16{}, F16{}, F16{});
|
||||
}
|
||||
if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, NGCHW{}, GKCYX{}, NGKHW{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
if(data_type == ConvDataType::F32_F32_F32)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, NGCHW{}, GKCYX{}, NGKHW{}, F32{}, F32{}, F32{}, F32{}, F32{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F32_F32_F32_TF32)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, NGCHW{}, GKCYX{}, NGKHW{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
|
||||
}
|
||||
}
|
||||
if(num_dim_spatial == 3 && layout == ConvLayout::GNHWC_GKYXC_GNHWK)
|
||||
{
|
||||
if(data_type == ConvDataType::F32_F32_F32)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, F32{}, F32{}, F32{}, F32{}, F32{});
|
||||
}
|
||||
if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, F16{}, F16{}, F16{}, F16{}, F16{});
|
||||
}
|
||||
if(data_type == ConvDataType::BF16_F32_BF16)
|
||||
{
|
||||
// fp32 atomic add is used for weight tensor in bf16 kernel
|
||||
return print_available_instances(
|
||||
I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, BF16{}, F32{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::I8_I8_I8)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, int8_t{}, int8_t{}, int8_t{}, int8_t{}, int8_t{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F32_F32_F32_TF32)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
|
||||
}
|
||||
}
|
||||
if(num_dim_spatial == 3 && layout == ConvLayout::NHWGC_GKYXC_NHWGK)
|
||||
{
|
||||
if(data_type == ConvDataType::F32_F32_F32)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F32{}, F32{}, F32{}, F32{}, F32{});
|
||||
}
|
||||
if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F16{}, F16{}, F16{}, F16{}, F16{});
|
||||
}
|
||||
if(data_type == ConvDataType::BF16_F32_BF16)
|
||||
{
|
||||
// fp32 atomic add is used for weight tensor in bf16 kernel
|
||||
return print_available_instances(
|
||||
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, BF16{}, F32{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
if(data_type == ConvDataType::F16_F16_F16_BF8_F8)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F16{}, F16{}, F16{}, BF8{}, F8{});
|
||||
}
|
||||
else if(data_type == ConvDataType::I8_I8_I8)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, int8_t{}, int8_t{}, int8_t{}, int8_t{}, int8_t{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F32_F32_F32_TF32)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
|
||||
}
|
||||
}
|
||||
else if(num_dim_spatial == 3 && layout == ConvLayout::NGCHW_GKYXC_NGKHW)
|
||||
{
|
||||
if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NGCDHW{}, GKZYXC{}, NGKDHW{}, F16{}, F16{}, F16{}, F16{}, F16{});
|
||||
}
|
||||
if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NGCDHW{}, GKZYXC{}, NGKDHW{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
}
|
||||
else if(num_dim_spatial == 3 && layout == ConvLayout::NGCHW_GKCYX_NGKHW)
|
||||
{
|
||||
if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NGCDHW{}, GKCZYX{}, NGKDHW{}, F16{}, F16{}, F16{}, F16{}, F16{});
|
||||
}
|
||||
if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NGCDHW{}, GKCZYX{}, NGKDHW{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
if(data_type == ConvDataType::F32_F32_F32)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NGCDHW{}, GKCZYX{}, NGKDHW{}, F32{}, F32{}, F32{}, F32{}, F32{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F32_F32_F32_TF32)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NGCDHW{}, GKCZYX{}, NGKDHW{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
|
||||
}
|
||||
}
|
||||
|
||||
std::cout << "[CK_PROFILER] This data_type & layout is not implemented." << std::endl;
|
||||
}
|
||||
|
||||
} // namespace
|
||||
|
||||
int profile_grouped_conv_bwd_weight(int argc, char* argv[])
|
||||
{
|
||||
if(argc == 6 && std::string(argv[5]) == "--instances")
|
||||
{
|
||||
const auto data_type = static_cast<ConvDataType>(std::stoi(argv[2]));
|
||||
const auto layout = static_cast<ConvLayout>(std::stoi(argv[3]));
|
||||
const ck::index_t num_dim_spatial = static_cast<ck::index_t>(std::stoi(argv[4]));
|
||||
|
||||
print_bwd_weight_instances(data_type, layout, num_dim_spatial);
|
||||
return 0;
|
||||
}
|
||||
// Parse optional named arguments first
|
||||
ck::index_t instance_index = -1;
|
||||
bool list_instances = false;
|
||||
|
||||
233
profiler/src/profile_grouped_conv_bwd_weight_tile.cpp
Normal file
233
profiler/src/profile_grouped_conv_bwd_weight_tile.cpp
Normal file
@@ -0,0 +1,233 @@
|
||||
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
|
||||
// SPDX-License-Identifier: MIT
|
||||
|
||||
#include <iostream>
|
||||
#include <numeric>
|
||||
#include <initializer_list>
|
||||
#include <cstdlib>
|
||||
|
||||
#include "ck_tile/builder/testing/conv/ck_tile.hpp"
|
||||
#include "ck_tile/host/device_prop.hpp"
|
||||
#include "profiler/grouped_convolution_backward_weight_tile_algs.hpp"
|
||||
#include "profiler/tile_profiler_utils.hpp"
|
||||
|
||||
#include "profiler_operation_registry.hpp"
|
||||
|
||||
namespace {
|
||||
|
||||
enum struct ConvLayout
|
||||
{
|
||||
GNCHW_GKCYX_GNKHW, // 0
|
||||
GNHWC_GKYXC_GNHWK, // 1
|
||||
NHWGC_GKYXC_NHWGK, // 2
|
||||
NGCHW_GKYXC_NGKHW, // 3
|
||||
NGCHW_GKCYX_NGKHW, // 4
|
||||
};
|
||||
|
||||
std::ostream& operator<<(std::ostream& os, const ConvLayout& layout)
|
||||
{
|
||||
using ck::operator<<;
|
||||
switch(layout)
|
||||
{
|
||||
case ConvLayout::GNCHW_GKCYX_GNKHW:
|
||||
os << "Input[G, N, C, Hi, Wi], Weight[G, K, C, Y, X], Output[G, N, K, Ho, Wo]";
|
||||
break;
|
||||
case ConvLayout::GNHWC_GKYXC_GNHWK:
|
||||
os << "Input[G, N, Hi, Wi, C], Weight[G, K, Y, X, C], Output[G, N, Ho, Wo, K]";
|
||||
break;
|
||||
case ConvLayout::NHWGC_GKYXC_NHWGK:
|
||||
os << "Input[N, Hi, Wi, G, C], Weight[G, K, Y, X, C], Output[N, Ho, Wo, G, K]";
|
||||
break;
|
||||
case ConvLayout::NGCHW_GKYXC_NGKHW:
|
||||
os << "Input[N, G, C, Hi, Wi], Weight[G, K, Y, X, C], Output[N, G, K, Ho, Wo]";
|
||||
break;
|
||||
case ConvLayout::NGCHW_GKCYX_NGKHW:
|
||||
os << "Input[N, G, C, Hi, Wi], Weight[G, K, C, Y, X], Output[N, G, K, Ho, Wo]";
|
||||
break;
|
||||
default: os << "unknown layout";
|
||||
}
|
||||
|
||||
return os;
|
||||
}
|
||||
|
||||
enum struct ConvDataType
|
||||
{
|
||||
F32_F32_F32, // 0
|
||||
F16_F16_F16, // 1
|
||||
BF16_FP32_BF16, // 2
|
||||
F16_F16_F16_GEMM_BF8, // 3
|
||||
INT8_INT8_INT8, // 4
|
||||
BF16_BF16_BF16, // 5
|
||||
F32_F32_F32_COMP_TF32 // 6
|
||||
};
|
||||
|
||||
std::ostream& operator<<(std::ostream& os, const ConvDataType& data_type)
|
||||
{
|
||||
using ck::operator<<;
|
||||
switch(data_type)
|
||||
{
|
||||
case ConvDataType::F32_F32_F32: os << "Input fp32, Weight fp32, Output fp32"; break;
|
||||
case ConvDataType::F16_F16_F16: os << "Input fp16, Weight fp16, Output fp16"; break;
|
||||
case ConvDataType::BF16_FP32_BF16: os << "Input bf16, Weight fp32, Output bf16"; break;
|
||||
case ConvDataType::F16_F16_F16_GEMM_BF8:
|
||||
os << "Input fp16, Weight fp16, Output fp16, Gemm bf8@fp8";
|
||||
break;
|
||||
case ConvDataType::INT8_INT8_INT8: os << "Input int8, Weight int8, Output int8"; break;
|
||||
case ConvDataType::BF16_BF16_BF16: os << "Input bf16, Weight bf16, Output bf16"; break;
|
||||
case ConvDataType::F32_F32_F32_COMP_TF32:
|
||||
os << "Input fp32, Weight fp32, Output fp32, Compute tf32";
|
||||
break;
|
||||
default: os << "unknown data type";
|
||||
}
|
||||
|
||||
return os;
|
||||
}
|
||||
|
||||
#define OP_NAME "grouped_conv_bwd_weight_tile"
|
||||
#define OP_DESC "Grouped Convolution Backward Weight (CK Tile)"
|
||||
|
||||
static void print_helper_msg()
|
||||
{
|
||||
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"
|
||||
<< " 3: Input fp16, Weight fp16, Output fp16, Gemm bf8@fp8\n"
|
||||
<< " 4: Input int8, Weight int8, Output int8\n"
|
||||
<< " 5: Input bf16, Weight bf16, Output bf16\n"
|
||||
<< " 6: Input fp32, Weight fp32, Output fp32, Compute tf32)\n"
|
||||
<< "arg3: tensor layout (0: Input[G, N, C, Hi, Wi], Weight[G, K, C, Y, X], Output[G, "
|
||||
"N, K, Ho, Wo]\n"
|
||||
<< " 1: Input[G, N, Hi, Wi, C], Weight[G, K, Y, X, C], Output[G, "
|
||||
"N, Ho, Wo, K]\n"
|
||||
<< " 2: Input[N, Hi, Wi, G, C], Weight[G, K, Y, X, C], Output[N, "
|
||||
"Ho, Wo, G, K]\n"
|
||||
<< " 3: Input[N, G, C, Hi, Wi], Weight[G, K, Y, X, C], Output[N, "
|
||||
"G, K, Ho, Wo]\n"
|
||||
<< " 4: Input[N, G, C, Hi, Wi], Weight[G, K, C, Y, X], Output[N, "
|
||||
"G, K, Ho, Wo]\n"
|
||||
<< "arg4: verification (0: no, 1: yes)\n"
|
||||
<< "arg5: initialization (0: no init, 1: integer value, 2: decimal value)\n"
|
||||
<< "arg6: print tensor value (0: no; 1: yes)\n"
|
||||
<< "arg7: time kernel (0: no, 1: yes)\n"
|
||||
<< ck::utils::conv::get_conv_param_parser_helper_msg()
|
||||
<< " SplitK (-1 for internally computed split-K value, positive value to set k "
|
||||
"batches explicitly, or 'all' to test all internal split-K values)\n"
|
||||
<< std::endl;
|
||||
}
|
||||
|
||||
namespace ckb = ck_tile::builder;
|
||||
namespace ckt = ck_tile::builder::test;
|
||||
namespace ckp = ck_tile::builder::profiling;
|
||||
|
||||
template <auto SIGNATURE>
|
||||
int call_profiler(const ckt::Args<SIGNATURE>& args, const std::string& split_k, bool time_kernel)
|
||||
{
|
||||
auto inputs = ckt::alloc_inputs(args);
|
||||
auto outputs = ckt::alloc_outputs(args);
|
||||
ckt::init_inputs(args, inputs.get());
|
||||
|
||||
std::cout << args.make_input_descriptor() << std::endl;
|
||||
std::cout << args.make_weight_descriptor() << std::endl;
|
||||
std::cout << args.make_output_descriptor() << std::endl;
|
||||
auto&& [valid, avg_time, op_name, best_split_k] =
|
||||
ckp::run_grouped_conv_backward_weight_tile_algs(
|
||||
args,
|
||||
split_k,
|
||||
inputs.get(),
|
||||
outputs.get(),
|
||||
ck_tile::stream_config{nullptr, time_kernel});
|
||||
if(time_kernel)
|
||||
{
|
||||
std::cout << "\nBest configuration parameters:" << "\n\tname: " << op_name
|
||||
<< "\n\tavg_time: " << avg_time << ", SplitK " << best_split_k << std::endl;
|
||||
}
|
||||
return !valid;
|
||||
}
|
||||
|
||||
} // namespace
|
||||
|
||||
int profile_grouped_conv_bwd_weight_tile(int argc, char* argv[])
|
||||
{
|
||||
// 8 for control, 1 for num_dim_spatial
|
||||
if(argc < 9)
|
||||
{
|
||||
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 bool time_kernel = std::stoi(argv[7]);
|
||||
const int num_dim_spatial = std::stoi(argv[8]);
|
||||
|
||||
// 8 for control, 1 for num_dim_spatial, 4 for G/N/K/C, and 6 * num_dim_spatial, 1 for split-K
|
||||
if(argc != 8 + 1 + 4 + 6 * num_dim_spatial + 1)
|
||||
{
|
||||
print_helper_msg();
|
||||
return 1;
|
||||
}
|
||||
|
||||
constexpr ck_tile::index_t conv_params_start_idx = 9;
|
||||
|
||||
std::cout << "IMPORTANT: Generate instances using: python "
|
||||
"experimental/builder/src/generate_instances.py --mode=profiler and rerun cmake"
|
||||
<< std::endl;
|
||||
|
||||
std::cout << "Data type: " << data_type << std::endl;
|
||||
std::cout << "Layout: " << layout << std::endl;
|
||||
const auto params =
|
||||
ck::utils::conv::parse_conv_param(num_dim_spatial, conv_params_start_idx, argv);
|
||||
std::cout << params << std::endl;
|
||||
|
||||
const std::string& split_k = std::string(argv[8 + 1 + 4 + 6 * num_dim_spatial]);
|
||||
std::cout << "Split-K: " << split_k << std::endl;
|
||||
|
||||
if(layout == ConvLayout::NHWGC_GKYXC_NHWGK)
|
||||
{
|
||||
if(num_dim_spatial == 2)
|
||||
{
|
||||
if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
constexpr auto SIGNATURE = ckp::SIGNATURE_NHWGC_FP16_BWD_WEIGHT;
|
||||
return call_profiler<SIGNATURE>(
|
||||
ckp::parse_conv_args<SIGNATURE>(conv_params_start_idx, argv),
|
||||
split_k,
|
||||
time_kernel);
|
||||
}
|
||||
else if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
constexpr auto SIGNATURE = ckp::SIGNATURE_NHWGC_BF16_BWD_WEIGHT;
|
||||
return call_profiler<SIGNATURE>(
|
||||
ckp::parse_conv_args<SIGNATURE>(conv_params_start_idx, argv),
|
||||
split_k,
|
||||
time_kernel);
|
||||
}
|
||||
}
|
||||
else if(num_dim_spatial == 3)
|
||||
{
|
||||
if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
constexpr auto SIGNATURE = ckp::SIGNATURE_NDHWGC_FP16_BWD_WEIGHT;
|
||||
return call_profiler<SIGNATURE>(
|
||||
ckp::parse_conv_args<SIGNATURE>(conv_params_start_idx, argv),
|
||||
split_k,
|
||||
time_kernel);
|
||||
}
|
||||
else if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
constexpr auto SIGNATURE = ckp::SIGNATURE_NDHWGC_BF16_BWD_WEIGHT;
|
||||
return call_profiler<SIGNATURE>(
|
||||
ckp::parse_conv_args<SIGNATURE>(conv_params_start_idx, argv),
|
||||
split_k,
|
||||
time_kernel);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
std::cout << "this data_type & layout is not implemented" << std::endl;
|
||||
|
||||
return 1;
|
||||
}
|
||||
|
||||
REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_grouped_conv_bwd_weight_tile);
|
||||
@@ -73,10 +73,338 @@ static void print_helper_msg()
|
||||
// clang-format on
|
||||
}
|
||||
|
||||
void print_fwd_instances(ConvDataType data_type, ConvLayout layout, ck::index_t num_dim_spatial)
|
||||
{
|
||||
|
||||
auto print_available_instances = [&](auto num_dim_spatial_tmp,
|
||||
auto in_layout,
|
||||
auto wei_layout,
|
||||
auto out_layout,
|
||||
auto in_type,
|
||||
auto wei_type,
|
||||
auto out_type,
|
||||
auto compute_type_a,
|
||||
auto compute_type_b) {
|
||||
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 ComputeTypeA = decltype(compute_type_a);
|
||||
using ComputeTypeB = decltype(compute_type_b);
|
||||
|
||||
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
|
||||
|
||||
ck::profiler::fwd::print_instances<NDimSpatial,
|
||||
InLayout,
|
||||
WeiLayout,
|
||||
OutLayout,
|
||||
InDataType,
|
||||
WeiDataType,
|
||||
OutDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
ComputeTypeA,
|
||||
ComputeTypeB>();
|
||||
};
|
||||
|
||||
constexpr auto I1 = ck::Number<1>{};
|
||||
constexpr auto I2 = ck::Number<2>{};
|
||||
constexpr auto I3 = ck::Number<3>{};
|
||||
|
||||
using F32 = float;
|
||||
using F16 = ck::half_t;
|
||||
using BF16 = ck::bhalf_t;
|
||||
using F8 = ck::f8_t;
|
||||
using BF8 = ck::bf8_t;
|
||||
using TF32 = ck::tf32_t;
|
||||
using INT8 = int8_t;
|
||||
|
||||
using namespace ck::tensor_layout::convolution;
|
||||
|
||||
// GNHWC_GKYXC_GNHWK
|
||||
if(num_dim_spatial == 1 && layout == ConvLayout::GNHWC_GKYXC_GNHWK)
|
||||
{
|
||||
if(data_type == ConvDataType::F32_F32_F32)
|
||||
{
|
||||
return print_available_instances(
|
||||
I1, GNWC{}, GKXC{}, GNWK{}, F32{}, F32{}, F32{}, F32{}, F32{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I1, GNWC{}, GKXC{}, GNWK{}, F16{}, F16{}, F16{}, F16{}, F16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I1, GNWC{}, GKXC{}, GNWK{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::INT8_INT8_INT8)
|
||||
{
|
||||
return print_available_instances(
|
||||
I1, GNWC{}, GKXC{}, GNWK{}, INT8{}, INT8{}, INT8{}, INT8{}, INT8{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F32_F32_F32_TF32)
|
||||
{
|
||||
return print_available_instances(
|
||||
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 print_available_instances(
|
||||
I2, GNHWC{}, GKYXC{}, GNHWK{}, F32{}, F32{}, F32{}, F32{}, F32{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, GNHWC{}, GKYXC{}, GNHWK{}, F16{}, F16{}, F16{}, F16{}, F16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, GNHWC{}, GKYXC{}, GNHWK{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::INT8_INT8_INT8)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, GNHWC{}, GKYXC{}, GNHWK{}, INT8{}, INT8{}, INT8{}, INT8{}, INT8{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F32_F32_F32_TF32)
|
||||
{
|
||||
return print_available_instances(
|
||||
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 print_available_instances(
|
||||
I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, F32{}, F32{}, F32{}, F32{}, F32{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, F16{}, F16{}, F16{}, F16{}, F16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::INT8_INT8_INT8)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, GNDHWC{}, GKZYXC{}, GNDHWK{}, INT8{}, INT8{}, INT8{}, INT8{}, INT8{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F32_F32_F32_TF32)
|
||||
{
|
||||
return print_available_instances(
|
||||
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 print_available_instances(
|
||||
I1, NWGC{}, GKXC{}, NWGK{}, F32{}, F32{}, F32{}, F32{}, F32{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I1, NWGC{}, GKXC{}, NWGK{}, F16{}, F16{}, F16{}, F16{}, F16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I1, NWGC{}, GKXC{}, NWGK{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::INT8_INT8_INT8)
|
||||
{
|
||||
return print_available_instances(
|
||||
I1, NWGC{}, GKXC{}, NWGK{}, INT8{}, INT8{}, INT8{}, INT8{}, INT8{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F32_F32_F32_TF32)
|
||||
{
|
||||
return print_available_instances(
|
||||
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 print_available_instances(
|
||||
I2, NHWGC{}, GKYXC{}, NHWGK{}, F32{}, F32{}, F32{}, F32{}, F32{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, NHWGC{}, GKYXC{}, NHWGK{}, F16{}, F16{}, F16{}, F16{}, F16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, NHWGC{}, GKYXC{}, NHWGK{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::INT8_INT8_INT8)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, NHWGC{}, GKYXC{}, NHWGK{}, INT8{}, INT8{}, INT8{}, INT8{}, INT8{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F32_F32_F32_TF32)
|
||||
{
|
||||
return print_available_instances(
|
||||
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 print_available_instances(
|
||||
I2, NGCHW{}, GKYXC{}, NGKHW{}, F32{}, F32{}, F32{}, F32{}, F32{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, NGCHW{}, GKYXC{}, NGKHW{}, F16{}, F16{}, F16{}, F16{}, F16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, NGCHW{}, GKYXC{}, NGKHW{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F32_F32_F32_TF32)
|
||||
{
|
||||
return print_available_instances(
|
||||
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 print_available_instances(
|
||||
I2, NGCHW{}, GKCYX{}, NGKHW{}, F32{}, F32{}, F32{}, F32{}, F32{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, NGCHW{}, GKCYX{}, NGKHW{}, F16{}, F16{}, F16{}, F16{}, F16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I2, NGCHW{}, GKCYX{}, NGKHW{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F32_F32_F32_TF32)
|
||||
{
|
||||
return print_available_instances(
|
||||
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 print_available_instances(
|
||||
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F32{}, F32{}, F32{}, F32{}, F32{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F16{}, F16{}, F16{}, F16{}, F16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::INT8_INT8_INT8)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, INT8{}, INT8{}, INT8{}, INT8{}, INT8{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F8_F8_F8)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F8{}, F8{}, F8{}, F8{}, F8{});
|
||||
}
|
||||
else if(data_type == ConvDataType::BF8_BF8_F8)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, BF8{}, BF8{}, F8{}, BF8{}, BF8{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F8_BF8_F8)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F8{}, BF8{}, F8{}, F8{}, BF8{});
|
||||
}
|
||||
else if(data_type == ConvDataType::BF8_F8_F8)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, BF8{}, F8{}, F8{}, BF8{}, F8{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F32_F32_F32_TF32)
|
||||
{
|
||||
return print_available_instances(
|
||||
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 print_available_instances(
|
||||
I3, NGCDHW{}, GKCZYX{}, NGKDHW{}, F32{}, F32{}, F32{}, F32{}, F32{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F16_F16_F16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NGCDHW{}, GKCZYX{}, NGKDHW{}, F16{}, F16{}, F16{}, F16{}, F16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::BF16_BF16_BF16)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NGCDHW{}, GKCZYX{}, NGKDHW{}, BF16{}, BF16{}, BF16{}, BF16{}, BF16{});
|
||||
}
|
||||
else if(data_type == ConvDataType::F32_F32_F32_TF32)
|
||||
{
|
||||
return print_available_instances(
|
||||
I3, NGCDHW{}, GKCZYX{}, NGKDHW{}, F32{}, F32{}, F32{}, TF32{}, TF32{});
|
||||
}
|
||||
}
|
||||
|
||||
std::cout << "[CK_PROFILER] This data_type & layout is not implemented" << std::endl;
|
||||
}
|
||||
|
||||
} // namespace
|
||||
|
||||
int profile_grouped_conv_fwd(int argc, char* argv[])
|
||||
{
|
||||
if(argc == 6 && std::string(argv[5]) == "--instances")
|
||||
{
|
||||
const auto data_type = static_cast<ConvDataType>(std::stoi(argv[2]));
|
||||
const auto layout = static_cast<ConvLayout>(std::stoi(argv[3]));
|
||||
const ck::index_t num_dim_spatial = static_cast<ck::index_t>(std::stoi(argv[4]));
|
||||
|
||||
print_fwd_instances(data_type, layout, num_dim_spatial);
|
||||
return 0;
|
||||
}
|
||||
// Parse optional named arguments first
|
||||
ck::index_t instance_index = -1;
|
||||
bool list_instances = false;
|
||||
|
||||
@@ -9,6 +9,7 @@
|
||||
#include "ck_tile/builder/testing/conv/ck_tile.hpp"
|
||||
#include "ck_tile/host/device_prop.hpp"
|
||||
#include "profiler/grouped_convolution_forward_tile_algs.hpp"
|
||||
#include "profiler/tile_profiler_utils.hpp"
|
||||
|
||||
#include "profiler_operation_registry.hpp"
|
||||
|
||||
|
||||
Reference in New Issue
Block a user