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Unverified Commit 22443f7a authored by Bartłomiej Kocot's avatar Bartłomiej Kocot Committed by GitHub
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Add wei_strides to grouped conv3d wei to keep consistency (#817) 



* Add wei_strides to grouped conv3d wei to keep consistency

* Fix strides in client examples

* Unify backward weight api with forward

* Fix for example

* Fixes for examples

---------
Co-authored-by: default avatarzjing14 <zhangjing14@gmail.com>
parent 2474dddb
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Showing with 357 additions and 433 deletions
client_example/11_grouped_conv_bwd_weight/common.hpp
View file @ 22443f7a
......@@ -32,63 +32,49 @@ struct SimpleDeviceMem
};
template <ck::index_t NumDimSpatial>
std::size_t GetFlops(ck::index_t G,
ck::index_t N,
ck::index_t K,
ck::index_t C,
const std::array<ck::index_t, NumDimSpatial>& output_spatial_lengths,
const std::array<ck::index_t, NumDimSpatial>& filter_spatial_lengths)
std::size_t GetFlops(const std::array<ck::index_t, NumDimSpatial>& output_lengths,
const std::array<ck::index_t, NumDimSpatial>& filter_lengths)
{
constexpr ck::index_t spatial_offset = 3;
const auto C = filter_lengths[2];
// 2 * G * N * K * C * <output spatial lengths product> * <filter spatial lengths product>
return static_cast<std::size_t>(2) * G * N * K * C *
std::accumulate(std::begin(output_spatial_lengths),
std::end(output_spatial_lengths),
return static_cast<std::size_t>(2) * C *
std::accumulate(std::begin(output_lengths),
std::end(output_lengths),
static_cast<std::size_t>(1),
std::multiplies<>()) *
std::accumulate(std::begin(filter_spatial_lengths),
std::end(filter_spatial_lengths),
std::accumulate(std::begin(filter_lengths) + spatial_offset,
std::end(filter_lengths),
static_cast<std::size_t>(1),
std::multiplies<>());
}
template <typename InDataType, ck::index_t NumDimSpatial>
std::size_t GetInputByte(ck::index_t G,
ck::index_t N,
ck::index_t C,
const std::array<ck::index_t, NumDimSpatial>& input_spatial_lengths)
std::size_t GetInputByte(const std::array<ck::index_t, NumDimSpatial>& input_lengths)
{
// sizeof(InDataType) * (G * N * C * <input spatial lengths product>) +
return sizeof(InDataType) * (G * N * C *
std::accumulate(std::begin(input_spatial_lengths),
std::end(input_spatial_lengths),
return sizeof(InDataType) * (std::accumulate(std::begin(input_lengths),
std::end(input_lengths),
static_cast<std::size_t>(1),
std::multiplies<>()));
}
template <typename WeiDataType, ck::index_t NumDimSpatial>
std::size_t GetWeightByte(ck::index_t G,
ck::index_t K,
ck::index_t C,
const std::array<ck::index_t, NumDimSpatial>& filter_spatial_lengths)
std::size_t GetWeightByte(const std::array<ck::index_t, NumDimSpatial>& filter_lengths)
{
// sizeof(WeiDataType) * (G * K * C * <filter spatial lengths product>) +
return sizeof(WeiDataType) * (G * K * C *
std::accumulate(std::begin(filter_spatial_lengths),
std::end(filter_spatial_lengths),
return sizeof(WeiDataType) * (std::accumulate(std::begin(filter_lengths),
std::end(filter_lengths),
static_cast<std::size_t>(1),
std::multiplies<>()));
}
template <typename OutDataType, ck::index_t NumDimSpatial>
std::size_t GetOutputByte(ck::index_t G,
ck::index_t N,
ck::index_t K,
const std::array<ck::index_t, NumDimSpatial>& output_spatial_lengths)
std::size_t GetOutputByte(const std::array<ck::index_t, NumDimSpatial>& output_lengths)
{
// sizeof(OutDataType) * (G * N * K * <output spatial lengths product>);
return sizeof(OutDataType) * (G * N * K *
std::accumulate(std::begin(output_spatial_lengths),
std::end(output_spatial_lengths),
return sizeof(OutDataType) * (std::accumulate(std::begin(output_lengths),
std::end(output_lengths),
static_cast<std::size_t>(1),
std::multiplies<std::size_t>()));
}
......@@ -101,14 +87,11 @@ template <ck::index_t NumDimSpatial,
typename WeiLayout,
typename OutLayout>
bool run_grouped_conv_bwd_weight(
const ck::index_t G,
const ck::index_t N,
const ck::index_t K,
const ck::index_t C,
const std::array<ck::index_t, NumDimSpatial>& input_spatial_lengths,
const std::array<ck::index_t, NumDimSpatial>& filter_spatial_lengths,
const std::array<ck::index_t, NumDimSpatial>& output_spatial_lengths,
const std::array<ck::index_t, NumDimSpatial + 3>& input_lengths,
const std::array<ck::index_t, NumDimSpatial + 3>& input_strides,
const std::array<ck::index_t, NumDimSpatial + 3>& filter_lengths,
const std::array<ck::index_t, NumDimSpatial + 3>& weights_strides,
const std::array<ck::index_t, NumDimSpatial + 3>& output_lengths,
const std::array<ck::index_t, NumDimSpatial + 3>& output_strides,
const std::array<ck::index_t, NumDimSpatial>& conv_filter_strides,
const std::array<ck::index_t, NumDimSpatial>& conv_filter_dilations,
......@@ -117,9 +100,9 @@ bool run_grouped_conv_bwd_weight(
{
ck::index_t split_k = 2;
SimpleDeviceMem in(GetInputByte<InDataType, NumDimSpatial>(G, N, C, input_spatial_lengths));
SimpleDeviceMem wei(GetWeightByte<WeiDataType, NumDimSpatial>(G, K, C, filter_spatial_lengths));
SimpleDeviceMem out(GetOutputByte<OutDataType, NumDimSpatial>(G, N, K, output_spatial_lengths));
SimpleDeviceMem in(GetInputByte<InDataType, NumDimSpatial + 3>(input_lengths));
SimpleDeviceMem wei(GetWeightByte<WeiDataType, NumDimSpatial + 3>(filter_lengths));
SimpleDeviceMem out(GetOutputByte<OutDataType, NumDimSpatial + 3>(output_lengths));
using DeviceOp = ck::tensor_operation::device::DeviceGroupedConvBwdWeight<NumDimSpatial,
InLayout,
......@@ -143,6 +126,10 @@ bool run_grouped_conv_bwd_weight(
float best_gb_per_sec = 0;
float best_tflops = 0;
std::array<ck::index_t, NumDimSpatial + 3> a_g_n_c_wis_lengths{};
std::array<ck::index_t, NumDimSpatial + 3> a_g_n_c_wis_strides{};
std::array<ck::index_t, NumDimSpatial + 3> b_g_k_c_xs_lengths{};
// profile device operation instances
std::cout << "Run all instances and do timing" << std::endl;
......@@ -152,14 +139,11 @@ bool run_grouped_conv_bwd_weight(
auto argument_ptr = op_ptr->MakeArgumentPointer(in.GetDeviceBuffer(),
wei.GetDeviceBuffer(),
out.GetDeviceBuffer(),
G,
N,
K,
C,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
input_lengths,
input_strides,
filter_lengths,
weights_strides,
output_lengths,
output_strides,
conv_filter_strides,
conv_filter_dilations,
......@@ -176,12 +160,10 @@ bool run_grouped_conv_bwd_weight(
{
float avg_time = invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, true});
std::size_t flop =
GetFlops<NumDimSpatial>(G, N, K, C, output_spatial_lengths, filter_spatial_lengths);
std::size_t num_bytes =
GetInputByte<InDataType, NumDimSpatial>(G, N, C, input_spatial_lengths) +
GetWeightByte<WeiDataType, NumDimSpatial>(G, K, C, filter_spatial_lengths) +
GetOutputByte<OutDataType, NumDimSpatial>(G, N, K, output_spatial_lengths);
std::size_t flop = GetFlops<NumDimSpatial + 3>(output_lengths, filter_lengths);
std::size_t num_bytes = GetInputByte<InDataType, NumDimSpatial + 3>(input_lengths) +
GetWeightByte<WeiDataType, NumDimSpatial + 3>(filter_lengths) +
GetOutputByte<OutDataType, NumDimSpatial + 3>(output_lengths);
float tflops = static_cast<float>(flop) / 1.E9 / avg_time;
float gb_per_sec = num_bytes / 1.E6 / avg_time;
......@@ -221,14 +203,11 @@ bool run_grouped_conv_bwd_weight(
auto argument_ptr = op_ptr->MakeArgumentPointer(in.GetDeviceBuffer(),
wei.GetDeviceBuffer(),
out.GetDeviceBuffer(),
G,
N,
K,
C,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
input_lengths,
input_strides,
filter_lengths,
weights_strides,
output_lengths,
output_strides,
conv_filter_strides,
conv_filter_dilations,
......
client_example/11_grouped_conv_bwd_weight/grouped_conv1d_bwd_weight_fp16.cpp
View file @ 22443f7a
......@@ -22,11 +22,12 @@ static constexpr ck::index_t C = 192;
static constexpr ck::index_t X = 3;
static constexpr ck::index_t Wi = 28;
static constexpr ck::index_t Wo = 28;
static constexpr std::array<ck::index_t, NumDimSpatial> input_spatial_lengths{Wi};
static constexpr std::array<ck::index_t, NumDimSpatial> filter_spatial_lengths{X};
static constexpr std::array<ck::index_t, NumDimSpatial> output_spatial_lengths{Wo};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> input_strides{N * Wi * C, Wi* C, C, 1};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> output_strides{N * Wo * K, Wo* K, K, 1};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> input_lengths{G, N, C, Wi};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> filter_lengths{G, K, C, X};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> output_lengths{G, N, K, Wo};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> input_strides{N * Wi * C, Wi* C, 1, C};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> weights_strides{K * X * C, X* C, 1, C};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> output_strides{N * Wo * K, Wo* K, 1, K};
static constexpr std::array<ck::index_t, NumDimSpatial> conv_filter_strides{1};
static constexpr std::array<ck::index_t, NumDimSpatial> conv_filter_dilations{1};
static constexpr std::array<ck::index_t, NumDimSpatial> input_left_pads{1};
......@@ -40,14 +41,11 @@ int main()
OutDataType,
InLayout,
WeiLayout,
OutLayout>(G,
N,
K,
C,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
OutLayout>(input_lengths,
input_strides,
filter_lengths,
weights_strides,
output_lengths,
output_strides,
conv_filter_strides,
conv_filter_dilations,
......
client_example/11_grouped_conv_bwd_weight/grouped_conv2d_bwd_weight_fp16.cpp
View file @ 22443f7a
......@@ -25,13 +25,15 @@ static constexpr ck::index_t Hi = 28;
static constexpr ck::index_t Wi = 28;
static constexpr ck::index_t Ho = 28;
static constexpr ck::index_t Wo = 28;
static constexpr std::array<ck::index_t, NumDimSpatial> input_spatial_lengths{Hi, Wi};
static constexpr std::array<ck::index_t, NumDimSpatial> filter_spatial_lengths{Y, X};
static constexpr std::array<ck::index_t, NumDimSpatial> output_spatial_lengths{Ho, Wo};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> input_lengths{G, N, C, Hi, Wi};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> filter_lengths{G, K, C, Y, X};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> output_lengths{G, N, K, Ho, Wo};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> input_strides{
N * Hi * Wi * C, Hi* Wi* C, Wi* C, C, 1};
N * Hi * Wi * C, Hi* Wi* C, 1, Wi* C, C};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> weights_strides{
K * Y * X * C, Y* X* C, 1, X* C, C};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> output_strides{
N * Ho * Wo * K, Ho* Wo* K, Wo* K, K, 1};
N * Ho * Wo * K, Ho* Wo* K, 1, Wo* K, K};
static constexpr std::array<ck::index_t, NumDimSpatial> conv_filter_strides{1, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> conv_filter_dilations{1, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> input_left_pads{1, 1};
......@@ -45,14 +47,11 @@ int main()
OutDataType,
InLayout,
WeiLayout,
OutLayout>(G,
N,
K,
C,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
OutLayout>(input_lengths,
input_strides,
filter_lengths,
weights_strides,
output_lengths,
output_strides,
conv_filter_strides,
conv_filter_dilations,
......
client_example/11_grouped_conv_bwd_weight/grouped_conv3d_bwd_weight_fp16.cpp
View file @ 22443f7a
......@@ -28,13 +28,15 @@ static constexpr ck::index_t Wi = 3;
static constexpr ck::index_t Do = 28;
static constexpr ck::index_t Ho = 28;
static constexpr ck::index_t Wo = 3;
static constexpr std::array<ck::index_t, NumDimSpatial> input_spatial_lengths{Di, Hi, Wi};
static constexpr std::array<ck::index_t, NumDimSpatial> filter_spatial_lengths{Z, Y, X};
static constexpr std::array<ck::index_t, NumDimSpatial> output_spatial_lengths{Do, Ho, Wo};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> input_lengths{G, N, C, Di, Hi, Wi};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> filter_lengths{G, K, C, Z, Y, X};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> output_lengths{G, N, K, Do, Ho, Wo};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> input_strides{
N * Di * Hi * Wi * C, Di* Hi* Wi* C, Hi* Wi* C, Wi* C, C, 1};
N * Di * Hi * Wi * C, Di* Hi* Wi* C, 1, Hi* Wi* C, Wi* C, C};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> weights_strides{
K * Z * Y * X * C, Z* Y* X* C, 1, Y* X* C, X* C, C};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> output_strides{
N * Do * Ho * Wo * K, Do* Ho* Wo* K, Ho* Wo* K, Wo* K, K, 1};
N * Do * Ho * Wo * K, Do* Ho* Wo* K, 1, Ho* Wo* K, Wo* K, K};
static constexpr std::array<ck::index_t, NumDimSpatial> conv_filter_strides{1, 1, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> conv_filter_dilations{1, 1, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> input_left_pads{1, 1, 1};
......@@ -48,14 +50,11 @@ int main()
OutDataType,
InLayout,
WeiLayout,
OutLayout>(G,
N,
K,
C,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
OutLayout>(input_lengths,
input_strides,
filter_lengths,
weights_strides,
output_lengths,
output_strides,
conv_filter_strides,
conv_filter_dilations,
......
client_example/11_grouped_conv_bwd_weight/grouped_conv3d_bwd_weight_fp32.cpp
View file @ 22443f7a
......@@ -28,13 +28,15 @@ static constexpr ck::index_t Wi = 3;
static constexpr ck::index_t Do = 28;
static constexpr ck::index_t Ho = 28;
static constexpr ck::index_t Wo = 3;
static constexpr std::array<ck::index_t, NumDimSpatial> input_spatial_lengths{Di, Hi, Wi};
static constexpr std::array<ck::index_t, NumDimSpatial> filter_spatial_lengths{Z, Y, X};
static constexpr std::array<ck::index_t, NumDimSpatial> output_spatial_lengths{Do, Ho, Wo};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> input_lengths{G, N, C, Di, Hi, Wi};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> filter_lengths{G, K, C, Z, Y, X};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> output_lengths{G, N, K, Do, Ho, Wo};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> input_strides{
N * Di * Hi * Wi * C, Di* Hi* Wi* C, Hi* Wi* C, Wi* C, C, 1};
N * Di * Hi * Wi * C, Di* Hi* Wi* C, 1, Hi* Wi* C, Wi* C, C};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> weights_strides{
K * Z * Y * X * C, Z* Y* X* C, 1, Y* X* C, X* C, C};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> output_strides{
N * Do * Ho * Wo * K, Do* Ho* Wo* K, Ho* Wo* K, Wo* K, K, 1};
N * Do * Ho * Wo * K, Do* Ho* Wo* K, 1, Ho* Wo* K, Wo* K, K};
static constexpr std::array<ck::index_t, NumDimSpatial> conv_filter_strides{1, 1, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> conv_filter_dilations{1, 1, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> input_left_pads{1, 1, 1};
......@@ -48,20 +50,16 @@ int main()
OutDataType,
InLayout,
WeiLayout,
OutLayout>(
G,
N,
K,
C,
{Di, Hi, Wi},
{Z, Y, X},
{Do, Ho, Wo},
{N * Di * Hi * Wi * C, Di * Hi * Wi * C, Hi * Wi * C, Wi * C, C, 1},
{N * Do * Ho * Wo * K, Do * Ho * Wo * K, Ho * Wo * K, Wo * K, K, 1},
{1, 1, 1},
{1, 1, 1},
{1, 1, 1},
{1, 1, 1})
OutLayout>(input_lengths,
input_strides,
filter_lengths,
weights_strides,
output_lengths,
output_strides,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
input_right_pads)
? EXIT_SUCCESS
: EXIT_FAILURE;
}
example/20_grouped_conv_bwd_weight/run_grouped_conv_bwd_weight_example.inc
View file @ 22443f7a
......@@ -72,10 +72,11 @@ bool run_grouped_conv_bwd_weight(const ExecutionConfig& config,
// init to 0
wei_device_buf.SetZero();
std::array<ck::index_t, NDimSpatial> input_spatial_lengths{};
std::array<ck::index_t, NDimSpatial> filter_spatial_lengths{};
std::array<ck::index_t, NDimSpatial> output_spatial_lengths{};
std::array<ck::index_t, NDimSpatial + 3> input_lengths{};
std::array<ck::index_t, NDimSpatial + 3> input_strides{};
std::array<ck::index_t, NDimSpatial + 3> filter_lengths{};
std::array<ck::index_t, NDimSpatial + 3> weights_strides{};
std::array<ck::index_t, NDimSpatial + 3> output_lengths{};
std::array<ck::index_t, NDimSpatial + 3> output_strides{};
std::array<ck::index_t, NDimSpatial> conv_filter_strides{};
std::array<ck::index_t, NDimSpatial> conv_filter_dilations{};
......@@ -84,10 +85,11 @@ bool run_grouped_conv_bwd_weight(const ExecutionConfig& config,
auto range_copy = [](const auto& from, auto to) { std::copy(begin(from), end(from), to); };
range_copy(conv_param.input_spatial_lengths_, begin(input_spatial_lengths));
range_copy(conv_param.filter_spatial_lengths_, begin(filter_spatial_lengths));
range_copy(conv_param.output_spatial_lengths_, begin(output_spatial_lengths));
range_copy(in_g_n_c_wis_desc.GetLengths(), begin(input_lengths));
range_copy(in_g_n_c_wis_desc.GetStrides(), begin(input_strides));
range_copy(wei_g_k_c_xs_desc.GetLengths(), begin(filter_lengths));
range_copy(wei_g_k_c_xs_desc.GetStrides(), begin(weights_strides));
range_copy(out_g_n_k_wos_desc.GetLengths(), begin(output_lengths));
range_copy(out_g_n_k_wos_desc.GetStrides(), begin(output_strides));
range_copy(conv_param.conv_filter_strides_, begin(conv_filter_strides));
range_copy(conv_param.conv_filter_dilations_, begin(conv_filter_dilations));
......@@ -100,14 +102,11 @@ bool run_grouped_conv_bwd_weight(const ExecutionConfig& config,
auto argument = conv.MakeArgument(static_cast<InDataType*>(in_device_buf.GetDeviceBuffer()),
static_cast<WeiDataType*>(wei_device_buf.GetDeviceBuffer()),
static_cast<OutDataType*>(out_device_buf.GetDeviceBuffer()),
conv_param.G_,
conv_param.N_,
conv_param.K_,
conv_param.C_,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
input_lengths,
input_strides,
filter_lengths,
weights_strides,
output_lengths,
output_strides,
conv_filter_strides,
conv_filter_dilations,
......
include/ck/tensor_operation/gpu/device/device_grouped_conv_bwd_weight.hpp
View file @ 22443f7a
......@@ -27,15 +27,12 @@ struct DeviceGroupedConvBwdWeight : public BaseOperator
MakeArgumentPointer(const void* p_in,
void* p_wei,
const void* p_out,
const ck::index_t G,
const ck::index_t N,
const ck::index_t K,
const ck::index_t C,
const std::array<ck::index_t, NDimSpatial>& input_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& filter_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& output_spatial_lengths,
const std::array<ck::index_t, NDimSpatial + 3>& input_strides,
const std::array<ck::index_t, NDimSpatial + 3>& output_strides,
const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_lengths, // input
const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_strides,
const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_lengths, // weight
const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_strides,
const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_lengths, // output
const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_dilations,
const std::array<ck::index_t, NDimSpatial>& input_left_pads,
......
include/ck/tensor_operation/gpu/device/impl/device_grouped_conv_bwd_weight_gnwc_gkxc_gnwk_dl.hpp
View file @ 22443f7a
......@@ -784,15 +784,12 @@ struct DeviceGroupedConvBwdWeightGnwcGkxcGnwk_Dl
Argument(const InDataType* p_in_grid,
WeiDataType* p_wei_grid,
const OutDataType* p_out_grid,
const ck::index_t G,
const ck::index_t N,
const ck::index_t K,
const ck::index_t C,
const std::array<ck::index_t, NDimSpatial>& input_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& filter_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& output_spatial_lengths,
const std::array<ck::index_t, NDimSpatial + 3>& /*input_strides*/,
const std::array<ck::index_t, NDimSpatial + 3>& /*output_strides*/,
const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_lengths, // input
const std::array<index_t, NDimSpatial + 3>& /*a_g_n_c_wis_strides*/,
const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_lengths, // weight
const std::array<index_t, NDimSpatial + 3>& /*b_g_k_c_xs_strides*/,
const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_lengths, // output
const std::array<index_t, NDimSpatial + 3>& /*e_g_n_k_wos_strides*/,
const std::array<ck::index_t, NDimSpatial>& conv_filter_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_dilations,
const std::array<ck::index_t, NDimSpatial>& input_left_pads,
......@@ -812,27 +809,38 @@ struct DeviceGroupedConvBwdWeightGnwcGkxcGnwk_Dl
a_element_op_{out_element_op},
b_element_op_{wei_element_op},
c_element_op_{in_element_op},
Conv_G_{G},
Conv_N_{N},
Conv_K_{K},
Conv_C_{C},
input_spatial_lengths_{input_spatial_lengths},
filter_spatial_lengths_{filter_spatial_lengths},
output_spatial_lengths_{output_spatial_lengths},
Conv_G_{a_g_n_c_wis_lengths[0]},
Conv_N_{a_g_n_c_wis_lengths[1]},
Conv_K_{b_g_k_c_xs_lengths[1]},
Conv_C_{a_g_n_c_wis_lengths[2]},
input_spatial_lengths_{},
filter_spatial_lengths_{},
output_spatial_lengths_{},
conv_filter_strides_{conv_filter_strides},
conv_filter_dilations_{conv_filter_dilations},
input_left_pads_{input_left_pads},
input_right_pads_{input_right_pads},
k_batch_{split_k}
{
constexpr index_t spatial_offset = 3;
std::copy(begin(a_g_n_c_wis_lengths) + spatial_offset,
end(a_g_n_c_wis_lengths),
begin(input_spatial_lengths_));
std::copy(begin(b_g_k_c_xs_lengths) + spatial_offset,
end(b_g_k_c_xs_lengths),
begin(filter_spatial_lengths_));
std::copy(begin(e_g_n_k_wos_lengths) + spatial_offset,
end(e_g_n_k_wos_lengths),
begin(output_spatial_lengths_));
const auto descs =
DeviceOp::MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N<NDimSpatial>(
N,
K,
C,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
Conv_N_,
Conv_K_,
Conv_C_,
input_spatial_lengths_,
filter_spatial_lengths_,
output_spatial_lengths_,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
......@@ -856,21 +864,21 @@ struct DeviceGroupedConvBwdWeightGnwcGkxcGnwk_Dl
// A/B/C Batch Stride
compute_ptr_offset_of_batch_.BatchStrideA_ =
N * K *
std::accumulate(begin(output_spatial_lengths),
end(output_spatial_lengths),
Conv_N_ * Conv_K_ *
std::accumulate(begin(output_spatial_lengths_),
end(output_spatial_lengths_),
index_t{1},
std::multiplies<>{});
compute_ptr_offset_of_batch_.BatchStrideB_ =
N * C *
std::accumulate(begin(input_spatial_lengths),
end(input_spatial_lengths),
Conv_N_ * Conv_C_ *
std::accumulate(begin(input_spatial_lengths_),
end(input_spatial_lengths_),
index_t{1},
std::multiplies<>{});
compute_ptr_offset_of_batch_.BatchStrideC_ =
K * C *
std::accumulate(begin(filter_spatial_lengths),
end(filter_spatial_lengths),
Conv_K_ * Conv_C_ *
std::accumulate(begin(filter_spatial_lengths_),
end(filter_spatial_lengths_),
index_t{1},
std::multiplies<>{});
}
......@@ -904,9 +912,9 @@ struct DeviceGroupedConvBwdWeightGnwcGkxcGnwk_Dl
const index_t Conv_K_;
const index_t Conv_C_;
const std::array<ck::index_t, NDimSpatial>& input_spatial_lengths_;
const std::array<ck::index_t, NDimSpatial>& filter_spatial_lengths_;
const std::array<ck::index_t, NDimSpatial>& output_spatial_lengths_;
std::array<ck::index_t, NDimSpatial> input_spatial_lengths_;
std::array<ck::index_t, NDimSpatial> filter_spatial_lengths_;
std::array<ck::index_t, NDimSpatial> output_spatial_lengths_;
const std::array<ck::index_t, NDimSpatial>& conv_filter_strides_;
const std::array<ck::index_t, NDimSpatial>& conv_filter_dilations_;
const std::array<ck::index_t, NDimSpatial>& input_left_pads_;
......@@ -1110,18 +1118,16 @@ struct DeviceGroupedConvBwdWeightGnwcGkxcGnwk_Dl
return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
}
static auto MakeArgument(const InDataType* p_in_grid,
static auto
MakeArgument(const InDataType* p_in_grid,
WeiDataType* p_wei_grid,
const OutDataType* p_out_grid,
const ck::index_t G,
const ck::index_t N,
const ck::index_t K,
const ck::index_t C,
const std::array<ck::index_t, NDimSpatial>& input_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& filter_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& output_spatial_lengths,
const std::array<ck::index_t, NDimSpatial + 3>& input_strides,
const std::array<ck::index_t, NDimSpatial + 3>& output_strides,
const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_lengths, // input
const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_strides,
const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_lengths, // weight
const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_strides,
const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_lengths, // output
const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_dilations,
const std::array<ck::index_t, NDimSpatial>& input_left_pads,
......@@ -1134,15 +1140,12 @@ struct DeviceGroupedConvBwdWeightGnwcGkxcGnwk_Dl
return Argument{p_in_grid,
p_wei_grid,
p_out_grid,
G,
N,
K,
C,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
input_strides,
output_strides,
a_g_n_c_wis_lengths, // input
a_g_n_c_wis_strides,
b_g_k_c_xs_lengths, // weight
b_g_k_c_xs_strides,
e_g_n_k_wos_lengths, // output
e_g_n_k_wos_strides,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
......@@ -1159,15 +1162,12 @@ struct DeviceGroupedConvBwdWeightGnwcGkxcGnwk_Dl
MakeArgumentPointer(const void* p_in_grid,
void* p_wei_grid,
const void* p_out_grid,
const ck::index_t G,
const ck::index_t N,
const ck::index_t K,
const ck::index_t C,
const std::array<ck::index_t, NDimSpatial>& input_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& filter_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& output_spatial_lengths,
const std::array<ck::index_t, NDimSpatial + 3>& input_strides,
const std::array<ck::index_t, NDimSpatial + 3>& output_strides,
const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_lengths, // input
const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_strides,
const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_lengths, // weight
const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_strides,
const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_lengths, // output
const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_dilations,
const std::array<ck::index_t, NDimSpatial>& input_left_pads,
......@@ -1180,15 +1180,12 @@ struct DeviceGroupedConvBwdWeightGnwcGkxcGnwk_Dl
return std::make_unique<Argument>(static_cast<const InDataType*>(p_in_grid),
static_cast<WeiDataType*>(p_wei_grid),
static_cast<const OutDataType*>(p_out_grid),
G,
N,
K,
C,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
input_strides,
output_strides,
a_g_n_c_wis_lengths, // input
a_g_n_c_wis_strides,
b_g_k_c_xs_lengths, // weight
b_g_k_c_xs_strides,
e_g_n_k_wos_lengths, // output
e_g_n_k_wos_strides,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
......
include/ck/tensor_operation/gpu/device/impl/device_grouped_conv_bwd_weight_xdl_cshuffle.hpp
View file @ 22443f7a
......@@ -244,23 +244,12 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
const ck::index_t Wo,
const ck::index_t K,
const std::array<ck::index_t, NDimSpatial + 3>& output_strides)
{
if constexpr(is_GNHWK_GKYXC_GNHWC)
{
return make_naive_tensor_descriptor_packed(make_tuple(N * Ho * Wo, K));
}
else if constexpr(is_NHWGK_GKYXC_NHWGC)
{
const index_t WoStride = output_strides[4];
const auto KStride = Number<1>{};
return make_naive_tensor_descriptor(make_tuple(N * Ho * Wo, K),
make_tuple(WoStride, KStride));
}
else
{
throw std::runtime_error("wrong! unsupported layout: " + OutLayout::name());
}
}
template <ck::index_t NDim, typename ck::enable_if<NDim == 2, bool>::type = false>
constexpr static auto
......@@ -269,20 +258,6 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
const ck::index_t Wi,
const ck::index_t C,
const std::array<ck::index_t, NDimSpatial + 3>& input_strides)
{
if constexpr(is_GNHWK_GKYXC_GNHWC)
{
if constexpr(ConvBackwardWeightSpecialization ==
ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0)
{
return make_naive_tensor_descriptor_packed(make_tuple(N * Hi * Wi, C));
}
else
{
return make_naive_tensor_descriptor_packed(make_tuple(N, Hi, Wi, C));
}
}
else if constexpr(is_NHWGK_GKYXC_NHWGC)
{
const index_t NStride = input_strides[1];
const index_t HiStride = input_strides[3];
......@@ -296,14 +271,22 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
}
else
{
return make_naive_tensor_descriptor(
make_tuple(N, Hi, Wi, C), make_tuple(NStride, HiStride, WiStride, CStride));
return make_naive_tensor_descriptor(make_tuple(N, Hi, Wi, C),
make_tuple(NStride, HiStride, WiStride, CStride));
}
}
else
template <ck::index_t NDim, typename ck::enable_if<NDim == 2, bool>::type = false>
constexpr static auto
make_wei_grid_desc(const ck::index_t K,
const ck::index_t Y,
const ck::index_t X,
const ck::index_t C,
const std::array<ck::index_t, NDimSpatial + 3>& weights_strides)
{
throw std::runtime_error("wrong! unsupported layout: " + InLayout::name());
}
const auto CStride = Number<1>{};
const auto KStride = weights_strides[1];
return make_naive_tensor_descriptor(make_tuple(K, Y * X * C), make_tuple(KStride, CStride));
}
template <ck::index_t NDim, typename ck::enable_if<NDim == 3, bool>::type = false>
......@@ -314,23 +297,12 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
const ck::index_t Wo,
const ck::index_t K,
const std::array<ck::index_t, NDimSpatial + 3>& output_strides)
{
if constexpr(is_GNDHWK_GKZYXC_GNDHWC)
{
return make_naive_tensor_descriptor_packed(make_tuple(N * Do * Ho * Wo, K));
}
else if constexpr(is_NDHWGK_GKZYXC_NDHWGC)
{
const index_t WoStride = output_strides[5];
const auto KStride = Number<1>{};
return make_naive_tensor_descriptor(make_tuple(N * Do * Ho * Wo, K),
make_tuple(WoStride, KStride));
}
else
{
throw std::runtime_error("wrong! unsupported layout: " + OutLayout::name());
}
}
template <ck::index_t NDim, typename ck::enable_if<NDim == 3, bool>::type = false>
constexpr static auto
......@@ -340,20 +312,6 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
const ck::index_t Wi,
const ck::index_t C,
const std::array<ck::index_t, NDimSpatial + 3>& input_strides)
{
if constexpr(is_GNDHWK_GKZYXC_GNDHWC)
{
if constexpr(ConvBackwardWeightSpecialization ==
ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0)
{
return make_naive_tensor_descriptor_packed(make_tuple(N * Di * Hi * Wi, C));
}
else
{
return make_naive_tensor_descriptor_packed(make_tuple(N, Di, Hi, Wi, C));
}
}
else if constexpr(is_NDHWGK_GKZYXC_NDHWGC)
{
const index_t NStride = input_strides[1];
const index_t DiStride = input_strides[3];
......@@ -373,10 +331,20 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
make_tuple(NStride, DiStride, HiStride, WiStride, CStride));
}
}
else
template <ck::index_t NDim, typename ck::enable_if<NDim == 3, bool>::type = false>
constexpr static auto
make_wei_grid_desc(const ck::index_t K,
const ck::index_t Z,
const ck::index_t Y,
const ck::index_t X,
const ck::index_t C,
const std::array<ck::index_t, NDimSpatial + 3>& weights_strides)
{
throw std::runtime_error("wrong! unsupported layout: " + InLayout::name());
}
const auto CStride = Number<1>{};
const auto KStride = weights_strides[1];
return make_naive_tensor_descriptor(make_tuple(K, Z * Y * X * C),
make_tuple(KStride, CStride));
}
template <ck::index_t NDim, typename ck::enable_if<NDim == 1, bool>::type = false>
......@@ -388,6 +356,7 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
const std::array<ck::index_t, NDimSpatial>& filter_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& output_spatial_lengths,
const std::array<ck::index_t, NDimSpatial + 3>& /* input_strides */,
const std::array<ck::index_t, NDimSpatial + 3>& /* weights_strides */,
const std::array<ck::index_t, NDimSpatial + 3>& /* output_strides */,
const std::array<ck::index_t, NDimSpatial>& conv_filter_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_dilations,
......@@ -542,6 +511,7 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
const std::array<ck::index_t, NDimSpatial>& filter_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& output_spatial_lengths,
const std::array<ck::index_t, NDimSpatial + 3>& input_strides,
const std::array<ck::index_t, NDimSpatial + 3>& weights_strides,
const std::array<ck::index_t, NDimSpatial + 3>& output_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_dilations,
......@@ -584,6 +554,7 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
const auto out_grid_desc = make_out_grid_desc<NDim>(N, Ho, Wo, K, output_strides);
const auto in_grid_desc = make_in_grid_desc<NDim>(N, Hi, Wi, C, input_strides);
const auto wei_grid_desc = make_wei_grid_desc<NDim>(K, Y, X, C, weights_strides);
if constexpr(ConvBackwardWeightSpecialization ==
ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0)
......@@ -618,13 +589,9 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
make_tuple(Sequence<0>{}, Sequence<1>{}),
make_tuple(Sequence<0, 1, 3>{}, Sequence<2>{}));
// C: weight tensor
const auto wei_gemmm_gemmn_grid_desc =
make_naive_tensor_descriptor_packed(make_tuple(K, Y * X * C));
return make_tuple(out_gemmkbatch_gemmk0_gemmm_gemmk1_grid_desc,
in_gemmkbatch_gemmk0_gemmn_gemmk1_grid_desc,
wei_gemmm_gemmn_grid_desc);
wei_grid_desc);
}
else
{
......@@ -684,13 +651,9 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
make_tuple(Sequence<0>{}, Sequence<1>{}),
make_tuple(Sequence<0, 1, 3>{}, Sequence<2>{}));
// C: weight tensor
const auto wei_gemmm_gemmn_grid_desc =
make_naive_tensor_descriptor_packed(make_tuple(K, Y * X * C));
return make_tuple(out_gemmkbatch_gemmk0_gemmm_gemmk1_grid_desc,
in_gemmkbatch_gemmk0_gemmn_gemmk1_grid_desc,
wei_gemmm_gemmn_grid_desc);
wei_grid_desc);
}
}
......@@ -703,6 +666,7 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
const std::array<ck::index_t, NDimSpatial>& filter_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& output_spatial_lengths,
const std::array<ck::index_t, NDimSpatial + 3>& input_strides,
const std::array<ck::index_t, NDimSpatial + 3>& weights_strides,
const std::array<ck::index_t, NDimSpatial + 3>& output_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_dilations,
......@@ -752,6 +716,7 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
const auto out_grid_desc = make_out_grid_desc<NDim>(N, Do, Ho, Wo, K, output_strides);
const auto in_grid_desc = make_in_grid_desc<NDim>(N, Di, Hi, Wi, C, input_strides);
const auto wei_grid_desc = make_wei_grid_desc<NDim>(K, Z, Y, X, C, weights_strides);
if constexpr(ConvBackwardWeightSpecialization ==
ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0)
......@@ -786,13 +751,9 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
make_tuple(Sequence<0>{}, Sequence<1>{}),
make_tuple(Sequence<0, 1, 3>{}, Sequence<2>{}));
// C: weight tensor
const auto wei_gemmm_gemmn_grid_desc =
make_naive_tensor_descriptor_packed(make_tuple(K, Z * Y * X * C));
return make_tuple(out_gemmkbatch_gemmk0_gemmm_gemmk1_grid_desc,
in_gemmkbatch_gemmk0_gemmn_gemmk1_grid_desc,
wei_gemmm_gemmn_grid_desc);
wei_grid_desc);
}
else
{
......@@ -861,13 +822,9 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
make_tuple(Sequence<0>{}, Sequence<1>{}),
make_tuple(Sequence<0, 1, 3>{}, Sequence<2>{}));
// C: weight tensor
const auto wei_gemmm_gemmn_grid_desc =
make_naive_tensor_descriptor_packed(make_tuple(K, Z * Y * X * C));
return make_tuple(out_gemmkbatch_gemmk0_gemmm_gemmk1_grid_desc,
in_gemmkbatch_gemmk0_gemmn_gemmk1_grid_desc,
wei_gemmm_gemmn_grid_desc);
wei_grid_desc);
}
} // function end
......@@ -887,6 +844,7 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
lengths,
strides,
strides,
strides,
params,
params,
params,
......@@ -910,6 +868,7 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
lengths,
strides,
strides,
strides,
params,
params,
params,
......@@ -933,6 +892,7 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
lengths,
strides,
strides,
strides,
params,
params,
params,
......@@ -1051,15 +1011,12 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
Argument(const InDataType* p_in_grid,
WeiDataType* p_wei_grid,
const OutDataType* p_out_grid,
const ck::index_t G,
const ck::index_t N,
const ck::index_t K,
const ck::index_t C,
const std::array<ck::index_t, NDimSpatial>& input_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& filter_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& output_spatial_lengths,
const std::array<ck::index_t, NDimSpatial + 3>& input_strides,
const std::array<ck::index_t, NDimSpatial + 3>& output_strides,
const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_lengths, // input
const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_strides,
const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_lengths, // weight
const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_strides,
const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_lengths, // output
const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_dilations,
const std::array<ck::index_t, NDimSpatial>& input_left_pads,
......@@ -1084,27 +1041,40 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
a_element_op_{out_element_op},
b_element_op_{in_element_op},
c_element_op_{wei_element_op},
Conv_G_{G},
Conv_N_{N},
Conv_K_{K},
Conv_C_{C},
output_spatial_lengths_{output_spatial_lengths},
filter_spatial_lengths_{filter_spatial_lengths},
Conv_G_{a_g_n_c_wis_lengths[0]},
Conv_N_{a_g_n_c_wis_lengths[1]},
Conv_K_{b_g_k_c_xs_lengths[1]},
Conv_C_{a_g_n_c_wis_lengths[2]},
input_spatial_lengths_{},
filter_spatial_lengths_{},
output_spatial_lengths_{},
conv_filter_strides_{conv_filter_strides},
input_left_pads_{input_left_pads},
input_right_pads_{input_right_pads},
k_batch_{split_k}
{
constexpr index_t spatial_offset = 3;
std::copy(begin(a_g_n_c_wis_lengths) + spatial_offset,
end(a_g_n_c_wis_lengths),
begin(input_spatial_lengths_));
std::copy(begin(b_g_k_c_xs_lengths) + spatial_offset,
end(b_g_k_c_xs_lengths),
begin(filter_spatial_lengths_));
std::copy(begin(e_g_n_k_wos_lengths) + spatial_offset,
end(e_g_n_k_wos_lengths),
begin(output_spatial_lengths_));
const auto descs =
DeviceOp::MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N<NDimSpatial>(
N,
K,
C,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
input_strides,
output_strides,
Conv_N_,
Conv_K_,
Conv_C_,
input_spatial_lengths_,
filter_spatial_lengths_,
output_spatial_lengths_,
a_g_n_c_wis_strides,
b_g_k_c_xs_strides,
e_g_n_k_wos_strides,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
......@@ -1119,12 +1089,12 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
GridwiseGemm::MakeCBlockClusterAdaptor(c_grid_desc_m_n_, M01, N01, k_batch_);
// A/B/C Batch Stride
compute_ptr_offset_of_batch_.BatchStrideA_ = output_strides[0];
compute_ptr_offset_of_batch_.BatchStrideB_ = input_strides[0];
compute_ptr_offset_of_batch_.BatchStrideA_ = e_g_n_k_wos_strides[0];
compute_ptr_offset_of_batch_.BatchStrideB_ = a_g_n_c_wis_strides[0];
compute_ptr_offset_of_batch_.BatchStrideC_ =
K * C *
std::accumulate(begin(filter_spatial_lengths),
end(filter_spatial_lengths),
Conv_K_ * Conv_C_ *
std::accumulate(begin(filter_spatial_lengths_),
end(filter_spatial_lengths_),
index_t{1},
std::multiplies<>{});
......@@ -1163,8 +1133,9 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
const index_t Conv_N_;
const index_t Conv_K_;
const index_t Conv_C_;
const std::array<ck::index_t, NDimSpatial>& output_spatial_lengths_;
const std::array<ck::index_t, NDimSpatial>& filter_spatial_lengths_;
std::array<ck::index_t, NDimSpatial> input_spatial_lengths_;
std::array<ck::index_t, NDimSpatial> filter_spatial_lengths_;
std::array<ck::index_t, NDimSpatial> output_spatial_lengths_;
const std::array<ck::index_t, NDimSpatial>& conv_filter_strides_;
const std::array<ck::index_t, NDimSpatial>& input_left_pads_;
const std::array<ck::index_t, NDimSpatial>& input_right_pads_;
......@@ -1339,18 +1310,16 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
}
static auto MakeArgument(const InDataType* p_in_grid,
static auto
MakeArgument(const InDataType* p_in_grid,
WeiDataType* p_wei_grid,
const OutDataType* p_out_grid,
const ck::index_t G,
const ck::index_t N,
const ck::index_t K,
const ck::index_t C,
const std::array<ck::index_t, NDimSpatial>& input_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& filter_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& output_spatial_lengths,
const std::array<ck::index_t, NDimSpatial + 3>& input_strides,
const std::array<ck::index_t, NDimSpatial + 3>& output_strides,
const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_lengths, // input
const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_strides,
const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_lengths, // weight
const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_strides,
const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_lengths, // output
const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_dilations,
const std::array<ck::index_t, NDimSpatial>& input_left_pads,
......@@ -1363,15 +1332,12 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
return Argument{p_in_grid,
p_wei_grid,
p_out_grid,
G,
N,
K,
C,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
input_strides,
output_strides,
a_g_n_c_wis_lengths, // input
a_g_n_c_wis_strides,
b_g_k_c_xs_lengths, // weight
b_g_k_c_xs_strides,
e_g_n_k_wos_lengths, // output
e_g_n_k_wos_strides,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
......@@ -1390,15 +1356,12 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
MakeArgumentPointer(const void* p_in_grid,
void* p_wei_grid,
const void* p_out_grid,
const ck::index_t G,
const ck::index_t N,
const ck::index_t K,
const ck::index_t C,
const std::array<ck::index_t, NDimSpatial>& input_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& filter_spatial_lengths,
const std::array<ck::index_t, NDimSpatial>& output_spatial_lengths,
const std::array<ck::index_t, NDimSpatial + 3>& input_strides,
const std::array<ck::index_t, NDimSpatial + 3>& output_strides,
const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_lengths, // input
const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_strides,
const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_lengths, // weight
const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_strides,
const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_lengths, // output
const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_strides,
const std::array<ck::index_t, NDimSpatial>& conv_filter_dilations,
const std::array<ck::index_t, NDimSpatial>& input_left_pads,
......@@ -1411,15 +1374,12 @@ struct DeviceGroupedConvBwdWeight_Xdl_CShuffle
return std::make_unique<Argument>(static_cast<const InDataType*>(p_in_grid),
static_cast<WeiDataType*>(p_wei_grid),
static_cast<const OutDataType*>(p_out_grid),
G,
N,
K,
C,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
input_strides,
output_strides,
a_g_n_c_wis_lengths, // input
a_g_n_c_wis_strides,
b_g_k_c_xs_lengths, // weight
b_g_k_c_xs_strides,
e_g_n_k_wos_lengths, // output
e_g_n_k_wos_strides,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
......
profiler/include/profiler/profile_grouped_conv_bwd_weight_impl.hpp
View file @ 22443f7a
......@@ -136,10 +136,11 @@ bool profile_grouped_conv_bwd_weight_impl(int do_verification,
// profile device Conv instances
bool all_pass = true;
std::array<ck::index_t, NDimSpatial> input_spatial_lengths{};
std::array<ck::index_t, NDimSpatial> filter_spatial_lengths{};
std::array<ck::index_t, NDimSpatial> output_spatial_lengths{};
std::array<ck::index_t, NDimSpatial + 3> input_lengths{};
std::array<ck::index_t, NDimSpatial + 3> filter_lengths{};
std::array<ck::index_t, NDimSpatial + 3> output_lengths{};
std::array<ck::index_t, NDimSpatial + 3> input_strides{};
std::array<ck::index_t, NDimSpatial + 3> weights_strides{};
std::array<ck::index_t, NDimSpatial + 3> output_strides{};
std::array<ck::index_t, NDimSpatial> conv_filter_strides{};
std::array<ck::index_t, NDimSpatial> conv_filter_dilations{};
......@@ -148,10 +149,11 @@ bool profile_grouped_conv_bwd_weight_impl(int do_verification,
auto range_copy = [](const auto& from, auto to) { std::copy(begin(from), end(from), to); };
range_copy(conv_param.input_spatial_lengths_, begin(input_spatial_lengths));
range_copy(conv_param.filter_spatial_lengths_, begin(filter_spatial_lengths));
range_copy(conv_param.output_spatial_lengths_, begin(output_spatial_lengths));
range_copy(in_g_n_c_wis_desc.GetLengths(), begin(input_lengths));
range_copy(in_g_n_c_wis_desc.GetStrides(), begin(input_strides));
range_copy(wei_g_k_c_xs_desc.GetLengths(), begin(filter_lengths));
range_copy(wei_g_k_c_xs_desc.GetStrides(), begin(weights_strides));
range_copy(out_g_n_k_wos_desc.GetLengths(), begin(output_lengths));
range_copy(out_g_n_k_wos_desc.GetStrides(), begin(output_strides));
range_copy(conv_param.conv_filter_strides_, begin(conv_filter_strides));
range_copy(conv_param.conv_filter_dilations_, begin(conv_filter_dilations));
......@@ -164,14 +166,11 @@ bool profile_grouped_conv_bwd_weight_impl(int do_verification,
op_ptr->MakeArgumentPointer(static_cast<InDataType*>(in_device_buf.GetDeviceBuffer()),
static_cast<WeiDataType*>(wei_device_buf.GetDeviceBuffer()),
static_cast<OutDataType*>(out_device_buf.GetDeviceBuffer()),
conv_param.G_,
conv_param.N_,
conv_param.K_,
conv_param.C_,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
input_lengths,
input_strides,
filter_lengths,
weights_strides,
output_lengths,
output_strides,
conv_filter_strides,
conv_filter_dilations,
......
test/grouped_convnd_bwd_weight/test_grouped_convnd_bwd_weight_interface.cpp
View file @ 22443f7a
......@@ -70,10 +70,11 @@ class TestGroupedConvndBwdWeight : public ::testing::Test
ck::utils::conv::make_output_host_tensor_descriptor_g_n_k_wos_packed<OutLayout>(
conv_param);
std::array<ck::index_t, NDimSpatial> input_spatial_lengths{};
std::array<ck::index_t, NDimSpatial> filter_spatial_lengths{};
std::array<ck::index_t, NDimSpatial> output_spatial_lengths{};
std::array<ck::index_t, NDimSpatial + 3> input_lengths{};
std::array<ck::index_t, NDimSpatial + 3> filter_lengths{};
std::array<ck::index_t, NDimSpatial + 3> output_lengths{};
std::array<ck::index_t, NDimSpatial + 3> input_strides{};
std::array<ck::index_t, NDimSpatial + 3> weights_strides{};
std::array<ck::index_t, NDimSpatial + 3> output_strides{};
std::array<ck::index_t, NDimSpatial> conv_filter_strides{};
std::array<ck::index_t, NDimSpatial> conv_filter_dilations{};
......@@ -82,10 +83,11 @@ class TestGroupedConvndBwdWeight : public ::testing::Test
auto range_copy = [](const auto& from, auto to) { std::copy(begin(from), end(from), to); };
range_copy(conv_param.input_spatial_lengths_, begin(input_spatial_lengths));
range_copy(conv_param.filter_spatial_lengths_, begin(filter_spatial_lengths));
range_copy(conv_param.output_spatial_lengths_, begin(output_spatial_lengths));
range_copy(in_g_n_c_wis_desc.GetLengths(), begin(input_lengths));
range_copy(in_g_n_c_wis_desc.GetStrides(), begin(input_strides));
range_copy(wei_g_k_c_xs_desc.GetLengths(), begin(filter_lengths));
range_copy(wei_g_k_c_xs_desc.GetStrides(), begin(weights_strides));
range_copy(out_g_n_k_wos_desc.GetLengths(), begin(output_lengths));
range_copy(out_g_n_k_wos_desc.GetStrides(), begin(output_strides));
range_copy(conv_param.conv_filter_strides_, begin(conv_filter_strides));
range_copy(conv_param.conv_filter_dilations_, begin(conv_filter_dilations));
......@@ -97,14 +99,11 @@ class TestGroupedConvndBwdWeight : public ::testing::Test
auto argument = conv.MakeArgument(nullptr,
nullptr,
nullptr,
conv_param.G_,
conv_param.N_,
conv_param.K_,
conv_param.C_,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
input_lengths,
input_strides,
filter_lengths,
weights_strides,
output_lengths,
output_strides,
conv_filter_strides,
conv_filter_dilations,
......
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