mirror of
https://github.com/ROCm/composable_kernel.git
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Add multiple d gridwise gemm on Navi21 for ResNet50 (#517)
* start add example * add multiple d fp16 example * device transfer elementwiseop to gridwise * gridwise add multiple d * change example for multiple d * fix spill registers * fix for passthrough element op * fix int8 overflow * change example file name * add instance for dl multiple d * example add DsDataType * remove grouped_convolution_forward_dl.hpp * add head file(was deleted before) * fix not support device issue * format * remove passthrough check Co-authored-by: letaoqin <letaoqin@amd.com>
This commit is contained in:
ltqin
@@ -8,3 +8,4 @@ add_example_executable_no_testing(example_convnd_fwd_xdl_fp64 convnd_fwd_xdl_fp6
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add_example_executable(example_convnd_fwd_dl_fp16 convnd_fwd_dl_fp16.cpp)
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add_example_executable(example_convnd_fwd_dl_fp32 convnd_fwd_dl_fp32.cpp)
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add_example_executable(example_convnd_fwd_dl_int8 convnd_fwd_dl_int8.cpp)
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@@ -30,6 +30,7 @@ void print_helper_msg()
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template <ck::index_t NDimSpatial,
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typename InDataType,
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typename WeiDataType,
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typename DsDataType,
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typename OutDataType,
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typename InElementOp,
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typename WeiElementOp,
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@@ -46,8 +47,10 @@ bool run_grouped_conv_fwd_dl(bool do_verification,
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const WeiElementOp& wei_element_op,
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const OutElementOp& out_element_op)
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{
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using DDataType = ck::remove_cvref_t<ck::tuple_element_t<0, DsDataType>>;
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Tensor<InDataType> in(in_g_n_c_wis_desc);
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Tensor<WeiDataType> wei(wei_g_k_c_xs_desc);
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Tensor<DDataType> bias(out_g_n_k_wos_desc);
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Tensor<OutDataType> out_host(out_g_n_k_wos_desc);
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Tensor<OutDataType> out_device(out_g_n_k_wos_desc);
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@@ -59,31 +62,38 @@ bool run_grouped_conv_fwd_dl(bool do_verification,
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{
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case 0: break;
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case 1:
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in.GenerateTensorValue(GeneratorTensor_2<InDataType>{-5, 5});
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wei.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-5, 5});
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in.GenerateTensorValue(GeneratorTensor_2<InDataType>{-2, 3});
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wei.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-2, 3});
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bias.GenerateTensorValue(GeneratorTensor_2<DDataType>{-2, 3});
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break;
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case 2:
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in.GenerateTensorValue(GeneratorTensor_3<InDataType>{0.0, 1.0});
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wei.GenerateTensorValue(GeneratorTensor_3<WeiDataType>{-0.5, 0.5});
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bias.GenerateTensorValue(GeneratorTensor_3<DDataType>{-0.5, 0.5});
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break;
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default:
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in.GenerateTensorValue(GeneratorTensor_1<InDataType>{1});
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wei.GenerateTensorValue(GeneratorTensor_1<WeiDataType>{1});
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wei.GenerateTensorValue(GeneratorTensor_1<WeiDataType>{-1});
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bias.GenerateTensorValue(GeneratorTensor_1<DDataType>{1});
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}
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DeviceMem in_device_buf(sizeof(InDataType) * in.mDesc.GetElementSpaceSize());
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DeviceMem wei_device_buf(sizeof(WeiDataType) * wei.mDesc.GetElementSpaceSize());
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DeviceMem bias_device_buf(sizeof(DDataType) * bias.mDesc.GetElementSpaceSize());
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DeviceMem out_device_buf(sizeof(OutDataType) * out_device.mDesc.GetElementSpaceSize());
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in_device_buf.ToDevice(in.mData.data());
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wei_device_buf.ToDevice(wei.mData.data());
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bias_device_buf.ToDevice(bias.mData.data());
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std::array<ck::index_t, NDimSpatial + 3> a_g_n_c_wis_lengths{};
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std::array<ck::index_t, NDimSpatial + 3> a_g_n_c_wis_strides{};
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std::array<ck::index_t, NDimSpatial + 3> b_g_k_c_xs_lengths{};
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std::array<ck::index_t, NDimSpatial + 3> b_g_k_c_xs_strides{};
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std::array<ck::index_t, NDimSpatial + 3> c_g_n_k_wos_lengths{};
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std::array<ck::index_t, NDimSpatial + 3> c_g_n_k_wos_strides{};
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std::array<ck::index_t, NDimSpatial + 3> d_g_n_k_wos_lengths{};
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std::array<ck::index_t, NDimSpatial + 3> d_g_n_k_wos_strides{};
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std::array<ck::index_t, NDimSpatial + 3> e_g_n_k_wos_lengths{};
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std::array<ck::index_t, NDimSpatial + 3> e_g_n_k_wos_strides{};
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std::array<ck::index_t, NDimSpatial> conv_filter_strides{};
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std::array<ck::index_t, NDimSpatial> conv_filter_dilations{};
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std::array<ck::index_t, NDimSpatial> input_left_pads{};
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@@ -95,8 +105,10 @@ bool run_grouped_conv_fwd_dl(bool do_verification,
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copy(in_g_n_c_wis_desc.GetStrides(), a_g_n_c_wis_strides);
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copy(wei_g_k_c_xs_desc.GetLengths(), b_g_k_c_xs_lengths);
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copy(wei_g_k_c_xs_desc.GetStrides(), b_g_k_c_xs_strides);
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copy(out_g_n_k_wos_desc.GetLengths(), c_g_n_k_wos_lengths);
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copy(out_g_n_k_wos_desc.GetStrides(), c_g_n_k_wos_strides);
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copy(out_g_n_k_wos_desc.GetLengths(), d_g_n_k_wos_lengths);
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copy(out_g_n_k_wos_desc.GetStrides(), d_g_n_k_wos_strides);
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copy(out_g_n_k_wos_desc.GetLengths(), e_g_n_k_wos_lengths);
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copy(out_g_n_k_wos_desc.GetStrides(), e_g_n_k_wos_strides);
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copy(conv_param.conv_filter_strides_, conv_filter_strides);
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copy(conv_param.conv_filter_dilations_, conv_filter_dilations);
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copy(conv_param.input_left_pads_, input_left_pads);
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@@ -105,25 +117,32 @@ bool run_grouped_conv_fwd_dl(bool do_verification,
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// do Conv
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auto conv = DeviceConvNDFwdInstance{};
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auto invoker = conv.MakeInvoker();
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auto argument = conv.MakeArgument(in_device_buf.GetDeviceBuffer(),
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wei_device_buf.GetDeviceBuffer(),
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out_device_buf.GetDeviceBuffer(),
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a_g_n_c_wis_lengths,
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a_g_n_c_wis_strides,
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b_g_k_c_xs_lengths,
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b_g_k_c_xs_strides,
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c_g_n_k_wos_lengths,
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c_g_n_k_wos_strides,
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conv_filter_strides,
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conv_filter_dilations,
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input_left_pads,
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input_right_pads,
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in_element_op,
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wei_element_op,
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out_element_op);
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auto argument = conv.MakeArgument(
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in_device_buf.GetDeviceBuffer(),
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wei_device_buf.GetDeviceBuffer(),
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std::array<const void*, 1>{bias_device_buf.GetDeviceBuffer()},
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out_device_buf.GetDeviceBuffer(),
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a_g_n_c_wis_lengths,
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a_g_n_c_wis_strides,
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b_g_k_c_xs_lengths,
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b_g_k_c_xs_strides,
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std::array<std::array<ck::index_t, NDimSpatial + 3>, 1>{{d_g_n_k_wos_lengths}},
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std::array<std::array<ck::index_t, NDimSpatial + 3>, 1>{{d_g_n_k_wos_strides}},
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e_g_n_k_wos_lengths,
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e_g_n_k_wos_strides,
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conv_filter_strides,
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conv_filter_dilations,
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input_left_pads,
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input_right_pads,
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in_element_op,
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wei_element_op,
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out_element_op);
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if(!conv.IsSupportedArgument(argument))
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{
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std::cout << "wrong! device_conv with the specified compilation parameters does not "
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"support this Conv problem"
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<< std::endl;
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return true;
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}
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@@ -139,28 +158,34 @@ bool run_grouped_conv_fwd_dl(bool do_verification,
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if(do_verification)
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{
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auto ref_conv = ck::tensor_operation::host::ReferenceConvFwd<NDimSpatial,
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InDataType,
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WeiDataType,
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OutDataType,
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InElementOp,
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WeiElementOp,
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OutElementOp>();
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auto ref_conv = ck::tensor_operation::host::ReferenceConvFwd<
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NDimSpatial,
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InDataType,
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WeiDataType,
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OutDataType,
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InElementOp,
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WeiElementOp,
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ck::tensor_operation::element_wise::PassThrough>();
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auto ref_invoker = ref_conv.MakeInvoker();
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auto ref_argument = ref_conv.MakeArgument(in,
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wei,
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out_host,
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conv_param.conv_filter_strides_,
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conv_param.conv_filter_dilations_,
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conv_param.input_left_pads_,
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conv_param.input_right_pads_,
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in_element_op,
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wei_element_op,
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out_element_op);
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auto ref_invoker = ref_conv.MakeInvoker();
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auto ref_argument =
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ref_conv.MakeArgument(in,
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wei,
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out_host,
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conv_param.conv_filter_strides_,
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conv_param.conv_filter_dilations_,
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conv_param.input_left_pads_,
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conv_param.input_right_pads_,
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in_element_op,
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wei_element_op,
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ck::tensor_operation::element_wise::PassThrough{});
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ref_invoker.Run(ref_argument);
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// cde_elementwise
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out_host.ForEach(
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[&](auto&, auto idx) { out_element_op(out_host(idx), out_host(idx), bias(idx)); });
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out_device_buf.FromDevice(out_device.mData.data());
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return ck::utils::check_err(
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@@ -3,13 +3,14 @@
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#include "convnd_fwd_dl_common.hpp"
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#include "ck/tensor_operation/gpu/device/device_grouped_conv_fwd_dl_nhwc_kyxc_nhwk.hpp"
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#include "ck/tensor_operation/gpu/device/device_grouped_conv_fwd_dl_multiple_d_nhwc_kyxc_nhwk.hpp"
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#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
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using InDataType = ck::half_t;
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using WeiDataType = ck::half_t;
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using AccDataType = float;
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using DsDataType = ck::Tuple<ck::half_t>;
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using OutDataType = ck::half_t;
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template <ck::index_t... Is>
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@@ -17,7 +18,7 @@ using S = ck::Sequence<Is...>;
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using InElementOp = ck::tensor_operation::element_wise::PassThrough;
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using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
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using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
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using OutElementOp = ck::tensor_operation::element_wise::AddRelu;
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static constexpr auto ConvSpec =
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ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
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@@ -26,12 +27,12 @@ static constexpr auto GemmPadingSpec = ck::tensor_operation::device::GemmSpecial
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template <ck::index_t NDimSpatial, typename InLayout, typename WeiLayout, typename OutLayout>
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// clang-format off
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using DeviceGroupedConvNDFwdInstance = ck::tensor_operation::device::DeviceGroupedConvFwdDl_NHWC_KYXC_NHWK
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// ######| NDim| InData| WeiData| OutData| AccData| InLayout| WeiLayout| OutLayout| In| Wei| Out| Convolution| GEMM| Block| MPer| NPer| K0Per| K1| M1Per| N1Per| KPer| M11N11Thread| M11N11Thread| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| CThreadTransfer| CThreadTransfer| CThreadTransfer|
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// ######| Spatial| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise| Forward| Spacialization| Size| Block| Block| Block| | ThreadM111| ThreadN111| Thread| ClusterM110Xs| ClusterN110Xs| ThreadSliceLengths| ThreadClusterLengths| ThreadCluster| SrcAccess| SrcVectorTensor| SrcVectorTensor| DstVectorTensor| ThreadSliceLengths| ThreadClusterLengths| ThreadCluster| SrcAccess| SrcVectorTensor| SrcVectorTensor| DstVectorTensor| SrcDstAccess| SrcDstVectorDim| DstScalarPerVector|
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// ######| | | | | | | | | Operation| Operation| Operation| Specialization| | | | | | | | | | | | K0_M0_M1_K1| K0_M0_M1_K1| ArrangeOrder| Order| Lengths_K0_M0_M1_K1| ContiguousDimOrder| Lengths_K0_M0_M1_K1| K0_N0_N1_K1| K0_N0_N1_K1| ArrangeOrder| Order| Lengths_K0_N0_N1_K1| ContiguousDimOrder| Lengths_K0_N0_N1_K1| Order| | |
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// ######| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
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< NDimSpatial, InDataType, WeiDataType, OutDataType, AccDataType, InLayout, WeiLayout, OutLayout, InElementOp, WeiElementOp, OutElementOp, ConvSpec, GemmPadingSpec, 256, 128, 128, 16, 2, 4, 4, 1, S<8, 2>, S<8, 2>, S<8, 1, 1, 2>, S<2, 1, 128, 1>, S<1, 2, 0, 3>, S<1, 2, 0, 3>, S<4, 1, 1, 2>, S<1, 2, 0, 3>, S<1, 1, 1, 2>, S<8, 1, 1, 2>, S<2, 1, 128, 1>, S<1, 2, 0, 3>, S<1, 2, 0, 3>, S<4, 1, 1, 2>, S<1, 2, 0, 3>, S<1, 1, 1, 2>, S<0, 1, 2, 3, 4, 5>, 5, 4>;
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using DeviceGroupedConvNDFwdInstance = ck::tensor_operation::device::DeviceGroupedConvFwdDlMultipleD_NHWC_KYXC_NHWK
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// ######| NDim| InData| WeiData| MultpleD| OutData| AccData| InLayout| WeiLayout| MultipleD| OutLayout| In| Wei| Out| Convolution| GEMM| Block| MPer| NPer| K0Per| K1| M1Per| N1Per| KPer| M11N11Thread| M11N11Thread| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| CThreadTransfer| CThreadTransfer| CThreadTransfer|
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// ######| Spatial| Type| Type| Type| Type| Type| | | Layout| | Elementwise| Elementwise| Elementwise| Forward| Spacialization| Size| Block| Block| Block| | ThreadM111| ThreadN111| Thread| ClusterM110Xs| ClusterN110Xs| ThreadSliceLengths| ThreadClusterLengths| ThreadCluster| SrcAccess| SrcVectorTensor| SrcVectorTensor| DstVectorTensor| ThreadSliceLengths| ThreadClusterLengths| ThreadCluster| SrcAccess| SrcVectorTensor| SrcVectorTensor| DstVectorTensor| SrcDstAccess| SrcDstVectorDim| DstScalarPerVector|
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// ######| | | | | | | | | | | Operation| Operation| Operation| Specialization| | | | | | | | | | | | K0_M0_M1_K1| K0_M0_M1_K1| ArrangeOrder| Order| Lengths_K0_M0_M1_K1| ContiguousDimOrder| Lengths_K0_M0_M1_K1| K0_N0_N1_K1| K0_N0_N1_K1| ArrangeOrder| Order| Lengths_K0_N0_N1_K1| ContiguousDimOrder| Lengths_K0_N0_N1_K1| Order| | |
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// ######| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
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< NDimSpatial, InDataType, WeiDataType, DsDataType, OutDataType, AccDataType, InLayout, WeiLayout, ck::Tuple<OutLayout>, OutLayout, InElementOp, WeiElementOp, OutElementOp, ConvSpec, GemmPadingSpec, 256, 128, 128, 16, 2, 4, 4, 1, S<8, 2>, S<8, 2>, S<8, 1, 1, 2>, S<2, 1, 128, 1>, S<1, 2, 0, 3>, S<1, 2, 0, 3>, S<4, 1, 1, 2>, S<1, 2, 0, 3>, S<1, 1, 1, 2>, S<8, 1, 1, 2>, S<2, 1, 128, 1>, S<1, 2, 0, 3>, S<1, 2, 0, 3>, S<4, 1, 1, 2>, S<1, 2, 0, 3>, S<1, 1, 1, 2>, S<0, 1, 2, 3, 4, 5>, 5, 4>;
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// clang-format on
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#include "run_convnd_fwd_dl_example.inc"
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@@ -3,13 +3,14 @@
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#include "convnd_fwd_dl_common.hpp"
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#include "ck/tensor_operation/gpu/device/device_grouped_conv_fwd_dl_nhwc_kyxc_nhwk.hpp"
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#include "ck/tensor_operation/gpu/device/device_grouped_conv_fwd_dl_multiple_d_nhwc_kyxc_nhwk.hpp"
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#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
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using InDataType = float;
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using WeiDataType = float;
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using AccDataType = float;
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using DsDataType = ck::Tuple<float>;
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using OutDataType = float;
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template <ck::index_t... Is>
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@@ -17,7 +18,7 @@ using S = ck::Sequence<Is...>;
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using InElementOp = ck::tensor_operation::element_wise::PassThrough;
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using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
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using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
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using OutElementOp = ck::tensor_operation::element_wise::AddRelu;
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static constexpr auto ConvSpec =
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ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
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@@ -26,12 +27,12 @@ static constexpr auto GemmPadingSpec = ck::tensor_operation::device::GemmSpecial
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template <ck::index_t NDimSpatial, typename InLayout, typename WeiLayout, typename OutLayout>
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// clang-format off
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using DeviceGroupedConvNDFwdInstance = ck::tensor_operation::device::DeviceGroupedConvFwdDl_NHWC_KYXC_NHWK
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// ######| NDim| InData| WeiData| OutData| AccData| InLayout| WeiLayout| OutLayout| In| Wei| Out| Convolution| GEMM| Block| MPer| NPer| K0Per| K1| M1Per| N1Per| KPer| M11N11Thread| M11N11Thread| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| CThreadTransfer| CThreadTransfer| CThreadTransfer|
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// ######| Spatial| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise| Forward| Spacialization| Size| Block| Block| Block| | ThreadM111| ThreadN111| Thread| ClusterM110Xs| ClusterN110Xs| ThreadSliceLengths| ThreadClusterLengths| ThreadCluster| SrcAccess| SrcVectorTensor| SrcVectorTensor| DstVectorTensor| ThreadSliceLengths| ThreadClusterLengths| ThreadCluster| SrcAccess| SrcVectorTensor| SrcVectorTensor| DstVectorTensor| SrcDstAccess| SrcDstVectorDim| DstScalarPerVector|
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// ######| | | | | | | | | Operation| Operation| Operation| Specialization| | | | | | | | | | | | K0_M0_M1_K1| K0_M0_M1_K1| ArrangeOrder| Order| Lengths_K0_M0_M1_K1| ContiguousDimOrder| Lengths_K0_M0_M1_K1| K0_N0_N1_K1| K0_N0_N1_K1| ArrangeOrder| Order| Lengths_K0_N0_N1_K1| ContiguousDimOrder| Lengths_K0_N0_N1_K1| Order| | |
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// ######| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
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< NDimSpatial, InDataType, WeiDataType, OutDataType, AccDataType, InLayout, WeiLayout, OutLayout, InElementOp, WeiElementOp, OutElementOp, ConvSpec, GemmPadingSpec, 256, 128, 128, 16, 1, 4, 4, 1, S<8, 2>, S<8, 2>, S<8, 1, 1, 1>, S<2, 1, 128, 1>, S<1, 2, 0, 3>, S<1, 2, 0, 3>, S<4, 1, 1, 1>, S<1, 2, 0, 3>, S<1, 1, 1, 1>, S<8, 1, 1, 1>, S<2, 1, 128, 1>, S<1, 2, 0, 3>, S<1, 2, 0, 3>, S<4, 1, 1, 1>, S<1, 2, 0, 3>, S<1, 1, 1, 1>, S<0, 1, 2, 3, 4, 5>, 5, 4>;
|
||||
using DeviceGroupedConvNDFwdInstance = ck::tensor_operation::device::DeviceGroupedConvFwdDlMultipleD_NHWC_KYXC_NHWK
|
||||
// ######| NDim| InData| WeiData| MultpleD| OutData| AccData| InLayout| WeiLayout| MultipleD| OutLayout| In| Wei| Out| Convolution| GEMM| Block| MPer| NPer| K0Per| K1| M1Per| N1Per| KPer| M11N11Thread| M11N11Thread| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| CThreadTransfer| CThreadTransfer| CThreadTransfer|
|
||||
// ######| Spatial| Type| Type| Type| Type| Type| | | Layout| | Elementwise| Elementwise| Elementwise| Forward| Spacialization| Size| Block| Block| Block| | ThreadM111| ThreadN111| Thread| ClusterM110Xs| ClusterN110Xs| ThreadSliceLengths| ThreadClusterLengths| ThreadCluster| SrcAccess| SrcVectorTensor| SrcVectorTensor| DstVectorTensor| ThreadSliceLengths| ThreadClusterLengths| ThreadCluster| SrcAccess| SrcVectorTensor| SrcVectorTensor| DstVectorTensor| SrcDstAccess| SrcDstVectorDim| DstScalarPerVector|
|
||||
// ######| | | | | | | | | | | Operation| Operation| Operation| Specialization| | | | | | | | | | | | K0_M0_M1_K1| K0_M0_M1_K1| ArrangeOrder| Order| Lengths_K0_M0_M1_K1| ContiguousDimOrder| Lengths_K0_M0_M1_K1| K0_N0_N1_K1| K0_N0_N1_K1| ArrangeOrder| Order| Lengths_K0_N0_N1_K1| ContiguousDimOrder| Lengths_K0_N0_N1_K1| Order| | |
|
||||
// ######| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
< NDimSpatial, InDataType, WeiDataType, DsDataType, OutDataType, AccDataType, InLayout, WeiLayout, ck::Tuple<OutLayout>, OutLayout, InElementOp, WeiElementOp, OutElementOp, ConvSpec, GemmPadingSpec, 256, 128, 128, 16, 1, 4, 4, 1, S<8, 2>, S<8, 2>, S<8, 1, 1, 1>, S<2, 1, 128, 1>, S<1, 2, 0, 3>, S<1, 2, 0, 3>, S<4, 1, 1, 1>, S<1, 2, 0, 3>, S<1, 1, 1, 1>, S<8, 1, 1, 1>, S<2, 1, 128, 1>, S<1, 2, 0, 3>, S<1, 2, 0, 3>, S<4, 1, 1, 1>, S<1, 2, 0, 3>, S<1, 1, 1, 1>, S<0, 1, 2, 3, 4, 5>, 5, 4>;
|
||||
// clang-format on
|
||||
|
||||
#include "run_convnd_fwd_dl_example.inc"
|
||||
|
||||
@@ -3,13 +3,14 @@
|
||||
|
||||
#include "convnd_fwd_dl_common.hpp"
|
||||
|
||||
#include "ck/tensor_operation/gpu/device/device_grouped_conv_fwd_dl_nhwc_kyxc_nhwk.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/device_grouped_conv_fwd_dl_multiple_d_nhwc_kyxc_nhwk.hpp"
|
||||
|
||||
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
|
||||
|
||||
using InDataType = int8_t;
|
||||
using WeiDataType = int8_t;
|
||||
using AccDataType = int32_t;
|
||||
using DsDataType = ck::Tuple<int8_t>;
|
||||
using OutDataType = int8_t;
|
||||
|
||||
template <ck::index_t... Is>
|
||||
@@ -17,7 +18,7 @@ using S = ck::Sequence<Is...>;
|
||||
|
||||
using InElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
using OutElementOp = ck::tensor_operation::element_wise::AddRelu;
|
||||
|
||||
static constexpr auto ConvSpec =
|
||||
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
|
||||
@@ -26,12 +27,12 @@ static constexpr auto GemmPadingSpec = ck::tensor_operation::device::GemmSpecial
|
||||
|
||||
template <ck::index_t NDimSpatial, typename InLayout, typename WeiLayout, typename OutLayout>
|
||||
// clang-format off
|
||||
using DeviceGroupedConvNDFwdInstance = ck::tensor_operation::device::DeviceGroupedConvFwdDl_NHWC_KYXC_NHWK
|
||||
// ######| NDim| InData| WeiData| OutData| AccData| InLayout| WeiLayout| OutLayout| In| Wei| Out| Convolution| GEMM| Block| MPer| NPer| K0Per| K1| M1Per| N1Per| KPer| M11N11Thread| M11N11Thread| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| CThreadTransfer| CThreadTransfer| CThreadTransfer|
|
||||
// ######| Spatial| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise| Forward| Spacialization| Size| Block| Block| Block| | ThreadM111| ThreadN111| Thread| ClusterM110Xs| ClusterN110Xs| ThreadSliceLengths| ThreadClusterLengths| ThreadCluster| SrcAccess| SrcVectorTensor| SrcVectorTensor| DstVectorTensor| ThreadSliceLengths| ThreadClusterLengths| ThreadCluster| SrcAccess| SrcVectorTensor| SrcVectorTensor| DstVectorTensor| SrcDstAccess| SrcDstVectorDim| DstScalarPerVector|
|
||||
// ######| | | | | | | | | Operation| Operation| Operation| Specialization| | | | | | | | | | | | K0_M0_M1_K1| K0_M0_M1_K1| ArrangeOrder| Order| Lengths_K0_M0_M1_K1| ContiguousDimOrder| Lengths_K0_M0_M1_K1| K0_N0_N1_K1| K0_N0_N1_K1| ArrangeOrder| Order| Lengths_K0_N0_N1_K1| ContiguousDimOrder| Lengths_K0_N0_N1_K1| Order| | |
|
||||
// ######| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
< NDimSpatial, InDataType, WeiDataType, OutDataType, AccDataType, InLayout, WeiLayout, OutLayout, InElementOp, WeiElementOp, OutElementOp, ConvSpec, GemmPadingSpec, 256, 128, 128, 16, 4, 4, 4, 1, S<8, 2>, S<8, 2>, S<8, 1, 1, 4>, S<2, 1, 128, 1>, S<1, 2, 0, 3>, S<1, 2, 0, 3>, S<4, 1, 1, 4>, S<1, 2, 0, 3>, S<1, 1, 1, 4>, S<8, 1, 1, 4>, S<2, 1, 128, 1>, S<1, 2, 0, 3>, S<1, 2, 0, 3>, S<4, 1, 1, 4>, S<1, 2, 0, 3>, S<1, 1, 1, 4>, S<0, 1, 2, 3, 4, 5>, 5, 4>;
|
||||
using DeviceGroupedConvNDFwdInstance = ck::tensor_operation::device::DeviceGroupedConvFwdDlMultipleD_NHWC_KYXC_NHWK
|
||||
// ######| NDim| InData| WeiData| MultpleD| OutData| AccData| InLayout| WeiLayout| MultipleD| OutLayout| In| Wei| Out| Convolution| GEMM| Block| MPer| NPer| K0Per| K1| M1Per| N1Per| KPer| M11N11Thread| M11N11Thread| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| CThreadTransfer| CThreadTransfer| CThreadTransfer|
|
||||
// ######| Spatial| Type| Type| Type| Type| Type| | | Layout| | Elementwise| Elementwise| Elementwise| Forward| Spacialization| Size| Block| Block| Block| | ThreadM111| ThreadN111| Thread| ClusterM110Xs| ClusterN110Xs| ThreadSliceLengths| ThreadClusterLengths| ThreadCluster| SrcAccess| SrcVectorTensor| SrcVectorTensor| DstVectorTensor| ThreadSliceLengths| ThreadClusterLengths| ThreadCluster| SrcAccess| SrcVectorTensor| SrcVectorTensor| DstVectorTensor| SrcDstAccess| SrcDstVectorDim| DstScalarPerVector|
|
||||
// ######| | | | | | | | | | | Operation| Operation| Operation| Specialization| | | | | | | | | | | | K0_M0_M1_K1| K0_M0_M1_K1| ArrangeOrder| Order| Lengths_K0_M0_M1_K1| ContiguousDimOrder| Lengths_K0_M0_M1_K1| K0_N0_N1_K1| K0_N0_N1_K1| ArrangeOrder| Order| Lengths_K0_N0_N1_K1| ContiguousDimOrder| Lengths_K0_N0_N1_K1| Order| | |
|
||||
// ######| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
< NDimSpatial, InDataType, WeiDataType, DsDataType, OutDataType, AccDataType, InLayout, WeiLayout, ck::Tuple<OutLayout>, OutLayout, InElementOp, WeiElementOp, OutElementOp, ConvSpec, GemmPadingSpec, 256, 128, 128, 16, 4, 4, 4, 1, S<8, 2>, S<8, 2>, S<8, 1, 1, 4>, S<2, 1, 128, 1>, S<1, 2, 0, 3>, S<1, 2, 0, 3>, S<4, 1, 1, 4>, S<1, 2, 0, 3>, S<1, 1, 1, 4>, S<8, 1, 1, 4>, S<2, 1, 128, 1>, S<1, 2, 0, 3>, S<1, 2, 0, 3>, S<4, 1, 1, 4>, S<1, 2, 0, 3>, S<1, 1, 1, 4>, S<0, 1, 2, 3, 4, 5>, 5, 4>;
|
||||
// clang-format on
|
||||
|
||||
#include "run_convnd_fwd_dl_example.inc"
|
||||
|
||||
@@ -61,6 +61,7 @@ bool run_convnd_fwd_dl_example(int argc, char* argv[])
|
||||
ndim_spatial_value,
|
||||
InDataType,
|
||||
WeiDataType,
|
||||
DsDataType,
|
||||
OutDataType,
|
||||
InElementOp,
|
||||
WeiElementOp,
|
||||
|
||||
Reference in New Issue
Block a user