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Commit ff46bd90 authored by rocking's avatar rocking
Browse files

Add conv dl instances and client example

parent dc7b6568
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Showing with 717 additions and 171 deletions
client_example/09_quantization/conv2d_fwd_bias_relu_perchannel_quantization.cpp
View file @ ff46bd90
...@@ -28,16 +28,15 @@ using OutElementOp = ck::tensor_operation::element_wise::Add_Activation_Mul2_Cla ...@@ -28,16 +28,15 @@ using OutElementOp = ck::tensor_operation::element_wise::Add_Activation_Mul2_Cla
static constexpr ck::index_t NumDimSpatial = 2; static constexpr ck::index_t NumDimSpatial = 2;
static constexpr ck::index_t G = 1; static constexpr ck::index_t G = 1;
static constexpr ck::index_t N = 4; static constexpr ck::index_t N = 4; // batch size
static constexpr ck::index_t K = 64; static constexpr ck::index_t K = 64; // output channel
static constexpr ck::index_t C = 32; static constexpr ck::index_t C = 192; // input channel
static constexpr ck::index_t Y = 3; static constexpr ck::index_t Y = 3; // filter H
static constexpr ck::index_t X = 3; static constexpr ck::index_t X = 3; // filter W
static constexpr ck::index_t Hi = 71; static constexpr ck::index_t Hi = 71; // input H
static constexpr ck::index_t Wi = 71; static constexpr ck::index_t Wi = 71; // input W
static constexpr ck::index_t Ho = 36; static constexpr ck::index_t Ho = 36; // output H
static constexpr ck::index_t Wo = 36; static constexpr ck::index_t Wo = 36; // output W
struct SimpleDeviceMem struct SimpleDeviceMem
{ {
SimpleDeviceMem() = delete; SimpleDeviceMem() = delete;
...@@ -64,8 +63,8 @@ int main(int argc, char* argv[]) ...@@ -64,8 +63,8 @@ int main(int argc, char* argv[])
std::array<ck::index_t, 5> bias_strides{K, 0, 1, 0, 0}; std::array<ck::index_t, 5> bias_strides{K, 0, 1, 0, 0};
std::array<ck::index_t, 5> requant_scale_lengths{G, N, K, Ho, Wo}; std::array<ck::index_t, 5> requant_scale_lengths{G, N, K, Ho, Wo};
std::array<ck::index_t, 5> requant_scale_strides{K, 0, 1, 0, 0}; std::array<ck::index_t, 5> requant_scale_strides{K, 0, 1, 0, 0};
std::array<ck::index_t, 5> out_lengths{G, N, C, Ho, Wo}; std::array<ck::index_t, 5> out_lengths{G, N, K, Ho, Wo};
std::array<ck::index_t, 5> out_strides{N * Ho * Wo * C, Ho * Wo * C, 1, Wo * C, C}; std::array<ck::index_t, 5> out_strides{N * Ho * Wo * K, Ho * Wo * K, 1, Wo * K, K};
std::array<ck::index_t, 2> in_left_pad{1, 1}; std::array<ck::index_t, 2> in_left_pad{1, 1};
std::array<ck::index_t, 2> in_right_pad{1, 1}; std::array<ck::index_t, 2> in_right_pad{1, 1};
std::array<ck::index_t, 2> conv_strides{2, 2}; std::array<ck::index_t, 2> conv_strides{2, 2};
...@@ -162,11 +161,12 @@ int main(int argc, char* argv[]) ...@@ -162,11 +161,12 @@ int main(int argc, char* argv[])
} }
} }
std::cout << "Best Perf: " << std::setw(10) << best_avg_time << " ms, " << best_tflops
<< " TFlops, " << best_gb_per_sec << " GB/s, " << best_op_name << std::endl;
// run the best intance // run the best intance
if(best_op_id != -1)
{ {
std::cout << "Best Perf: " << std::setw(10) << best_avg_time << " ms, " << best_tflops
<< " TFlops, " << best_gb_per_sec << " GB/s, " << best_op_name << std::endl;
auto& op_ptr = op_ptrs[best_op_id]; auto& op_ptr = op_ptrs[best_op_id];
std::cout << "Run the best instance without timing: " << op_ptr->GetTypeString() std::cout << "Run the best instance without timing: " << op_ptr->GetTypeString()
<< std::endl; << std::endl;
......
client_example/09_quantization/conv2d_fwd_bias_relu_perlayer_quantization.cpp
View file @ ff46bd90
...@@ -26,15 +26,15 @@ using OutElementOp = ck::tensor_operation::element_wise::Add_Activation_Mul_Clam ...@@ -26,15 +26,15 @@ using OutElementOp = ck::tensor_operation::element_wise::Add_Activation_Mul_Clam
static constexpr ck::index_t NumDimSpatial = 2; static constexpr ck::index_t NumDimSpatial = 2;
static constexpr ck::index_t G = 1; static constexpr ck::index_t G = 1;
static constexpr ck::index_t N = 4; static constexpr ck::index_t N = 4; // batch size
static constexpr ck::index_t K = 64; static constexpr ck::index_t K = 64; // output channel
static constexpr ck::index_t C = 32; static constexpr ck::index_t C = 192; // input channel
static constexpr ck::index_t Y = 3; static constexpr ck::index_t Y = 3; // filter H
static constexpr ck::index_t X = 3; static constexpr ck::index_t X = 3; // filter W
static constexpr ck::index_t Hi = 71; static constexpr ck::index_t Hi = 71; // input H
static constexpr ck::index_t Wi = 71; static constexpr ck::index_t Wi = 71; // input W
static constexpr ck::index_t Ho = 36; static constexpr ck::index_t Ho = 36; // output H
static constexpr ck::index_t Wo = 36; static constexpr ck::index_t Wo = 36; // output W
struct SimpleDeviceMem struct SimpleDeviceMem
{ {
...@@ -60,8 +60,8 @@ int main(int argc, char* argv[]) ...@@ -60,8 +60,8 @@ int main(int argc, char* argv[])
std::array<ck::index_t, 5> weight_strides{K * Y * X * C, Y * X * C, 1, X * C, C}; std::array<ck::index_t, 5> weight_strides{K * Y * X * C, Y * X * C, 1, X * C, C};
std::array<ck::index_t, 5> bias_lengths{G, N, K, Ho, Wo}; std::array<ck::index_t, 5> bias_lengths{G, N, K, Ho, Wo};
std::array<ck::index_t, 5> bias_strides{K, 0, 1, 0, 0}; std::array<ck::index_t, 5> bias_strides{K, 0, 1, 0, 0};
std::array<ck::index_t, 5> out_lengths{G, N, C, Ho, Wo}; std::array<ck::index_t, 5> out_lengths{G, N, K, Ho, Wo};
std::array<ck::index_t, 5> out_strides{N * Ho * Wo * C, Ho * Wo * C, 1, Wo * C, C}; std::array<ck::index_t, 5> out_strides{N * Ho * Wo * K, Ho * Wo * K, 1, Wo * K, K};
std::array<ck::index_t, 2> in_left_pad{1, 1}; std::array<ck::index_t, 2> in_left_pad{1, 1};
std::array<ck::index_t, 2> in_right_pad{1, 1}; std::array<ck::index_t, 2> in_right_pad{1, 1};
std::array<ck::index_t, 2> conv_strides{2, 2}; std::array<ck::index_t, 2> conv_strides{2, 2};
...@@ -156,11 +156,12 @@ int main(int argc, char* argv[]) ...@@ -156,11 +156,12 @@ int main(int argc, char* argv[])
} }
} }
std::cout << "Best Perf: " << std::setw(10) << best_avg_time << " ms, " << best_tflops
<< " TFlops, " << best_gb_per_sec << " GB/s, " << best_op_name << std::endl;
// run the best intance // run the best intance
if(best_op_id != -1)
{ {
std::cout << "Best Perf: " << std::setw(10) << best_avg_time << " ms, " << best_tflops
<< " TFlops, " << best_gb_per_sec << " GB/s, " << best_op_name << std::endl;
auto& op_ptr = op_ptrs[best_op_id]; auto& op_ptr = op_ptrs[best_op_id];
std::cout << "Run the best instance without timing: " << op_ptr->GetTypeString() std::cout << "Run the best instance without timing: " << op_ptr->GetTypeString()
<< std::endl; << std::endl;
......
client_example/09_quantization/conv2d_fwd_perchannel_quantization.cpp
View file @ ff46bd90
...@@ -26,15 +26,15 @@ using OutElementOp = ck::tensor_operation::element_wise::Activation_Mul2_C ...@@ -26,15 +26,15 @@ using OutElementOp = ck::tensor_operation::element_wise::Activation_Mul2_C
static constexpr ck::index_t NumDimSpatial = 2; static constexpr ck::index_t NumDimSpatial = 2;
static constexpr ck::index_t G = 1; static constexpr ck::index_t G = 1;
static constexpr ck::index_t N = 4; static constexpr ck::index_t N = 4; // batch size
static constexpr ck::index_t K = 64; static constexpr ck::index_t K = 64; // output channel
static constexpr ck::index_t C = 32; static constexpr ck::index_t C = 192; // input channel
static constexpr ck::index_t Y = 3; static constexpr ck::index_t Y = 3; // filter H
static constexpr ck::index_t X = 3; static constexpr ck::index_t X = 3; // filter W
static constexpr ck::index_t Hi = 71; static constexpr ck::index_t Hi = 71; // input H
static constexpr ck::index_t Wi = 71; static constexpr ck::index_t Wi = 71; // input W
static constexpr ck::index_t Ho = 36; static constexpr ck::index_t Ho = 36; // output H
static constexpr ck::index_t Wo = 36; static constexpr ck::index_t Wo = 36; // output W
struct SimpleDeviceMem struct SimpleDeviceMem
{ {
...@@ -60,8 +60,8 @@ int main(int argc, char* argv[]) ...@@ -60,8 +60,8 @@ int main(int argc, char* argv[])
std::array<ck::index_t, 5> weight_strides{K * Y * X * C, Y * X * C, 1, X * C, C}; std::array<ck::index_t, 5> weight_strides{K * Y * X * C, Y * X * C, 1, X * C, C};
std::array<ck::index_t, 5> requant_scale_lengths{G, N, K, Ho, Wo}; std::array<ck::index_t, 5> requant_scale_lengths{G, N, K, Ho, Wo};
std::array<ck::index_t, 5> requant_scale_strides{K, 0, 1, 0, 0}; std::array<ck::index_t, 5> requant_scale_strides{K, 0, 1, 0, 0};
std::array<ck::index_t, 5> out_lengths{G, N, C, Ho, Wo}; std::array<ck::index_t, 5> out_lengths{G, N, K, Ho, Wo};
std::array<ck::index_t, 5> out_strides{N * Ho * Wo * C, Ho * Wo * C, 1, Wo * C, C}; std::array<ck::index_t, 5> out_strides{N * Ho * Wo * K, Ho * Wo * K, 1, Wo * K, K};
std::array<ck::index_t, 2> in_left_pad{1, 1}; std::array<ck::index_t, 2> in_left_pad{1, 1};
std::array<ck::index_t, 2> in_right_pad{1, 1}; std::array<ck::index_t, 2> in_right_pad{1, 1};
std::array<ck::index_t, 2> conv_strides{2, 2}; std::array<ck::index_t, 2> conv_strides{2, 2};
...@@ -156,11 +156,12 @@ int main(int argc, char* argv[]) ...@@ -156,11 +156,12 @@ int main(int argc, char* argv[])
} }
} }
std::cout << "Best Perf: " << std::setw(10) << best_avg_time << " ms, " << best_tflops
<< " TFlops, " << best_gb_per_sec << " GB/s, " << best_op_name << std::endl;
// run the best intance // run the best intance
if(best_op_id != -1)
{ {
std::cout << "Best Perf: " << std::setw(10) << best_avg_time << " ms, " << best_tflops
<< " TFlops, " << best_gb_per_sec << " GB/s, " << best_op_name << std::endl;
auto& op_ptr = op_ptrs[best_op_id]; auto& op_ptr = op_ptrs[best_op_id];
std::cout << "Run the best instance without timing: " << op_ptr->GetTypeString() std::cout << "Run the best instance without timing: " << op_ptr->GetTypeString()
<< std::endl; << std::endl;
......
client_example/09_quantization/conv2d_fwd_perlayer_quantization.cpp
View file @ ff46bd90
...@@ -24,15 +24,15 @@ using OutElementOp = ck::tensor_operation::element_wise::Activation_Mul_Clamp<Ac ...@@ -24,15 +24,15 @@ using OutElementOp = ck::tensor_operation::element_wise::Activation_Mul_Clamp<Ac
static constexpr ck::index_t NumDimSpatial = 2; static constexpr ck::index_t NumDimSpatial = 2;
static constexpr ck::index_t G = 1; static constexpr ck::index_t G = 1;
static constexpr ck::index_t N = 4; static constexpr ck::index_t N = 4; // batch size
static constexpr ck::index_t K = 64; static constexpr ck::index_t K = 64; // output channel
static constexpr ck::index_t C = 32; static constexpr ck::index_t C = 192; // input channel
static constexpr ck::index_t Y = 3; static constexpr ck::index_t Y = 3; // filter H
static constexpr ck::index_t X = 3; static constexpr ck::index_t X = 3; // filter W
static constexpr ck::index_t Hi = 71; static constexpr ck::index_t Hi = 71; // input H
static constexpr ck::index_t Wi = 71; static constexpr ck::index_t Wi = 71; // input W
static constexpr ck::index_t Ho = 36; static constexpr ck::index_t Ho = 36; // output H
static constexpr ck::index_t Wo = 36; static constexpr ck::index_t Wo = 36; // output W
struct SimpleDeviceMem struct SimpleDeviceMem
{ {
...@@ -56,8 +56,8 @@ int main(int argc, char* argv[]) ...@@ -56,8 +56,8 @@ int main(int argc, char* argv[])
std::array<ck::index_t, 5> in_strides{N * Hi * Wi * C, Hi * Wi * C, 1, Wi * C, C}; std::array<ck::index_t, 5> in_strides{N * Hi * Wi * C, Hi * Wi * C, 1, Wi * C, C};
std::array<ck::index_t, 5> weight_lengths{G, K, C, Y, X}; std::array<ck::index_t, 5> weight_lengths{G, K, C, Y, X};
std::array<ck::index_t, 5> weight_strides{K * Y * X * C, Y * X * C, 1, X * C, C}; std::array<ck::index_t, 5> weight_strides{K * Y * X * C, Y * X * C, 1, X * C, C};
std::array<ck::index_t, 5> out_lengths{G, N, C, Ho, Wo}; std::array<ck::index_t, 5> out_lengths{G, N, K, Ho, Wo};
std::array<ck::index_t, 5> out_strides{N * Ho * Wo * C, Ho * Wo * C, 1, Wo * C, C}; std::array<ck::index_t, 5> out_strides{N * Ho * Wo * K, Ho * Wo * K, 1, Wo * K, K};
std::array<ck::index_t, 2> in_left_pad{1, 1}; std::array<ck::index_t, 2> in_left_pad{1, 1};
std::array<ck::index_t, 2> in_right_pad{1, 1}; std::array<ck::index_t, 2> in_right_pad{1, 1};
std::array<ck::index_t, 2> conv_strides{2, 2}; std::array<ck::index_t, 2> conv_strides{2, 2};
...@@ -150,11 +150,11 @@ int main(int argc, char* argv[]) ...@@ -150,11 +150,11 @@ int main(int argc, char* argv[])
} }
} }
std::cout << "Best Perf: " << std::setw(10) << best_avg_time << " ms, " << best_tflops if(best_op_id != -1)
<< " TFlops, " << best_gb_per_sec << " GB/s, " << best_op_name << std::endl;
// run the best intance
{ {
std::cout << "Best Perf: " << std::setw(10) << best_avg_time << " ms, " << best_tflops
<< " TFlops, " << best_gb_per_sec << " GB/s, " << best_op_name << std::endl;
auto& op_ptr = op_ptrs[best_op_id]; auto& op_ptr = op_ptrs[best_op_id];
std::cout << "Run the best instance without timing: " << op_ptr->GetTypeString() std::cout << "Run the best instance without timing: " << op_ptr->GetTypeString()
<< std::endl; << std::endl;
......
library/include/ck/library/tensor_operation_instance/gpu/quantization/grouped_convolution_bias_forward_perchannel_quantization.hpp
View file @ ff46bd90
...@@ -18,7 +18,7 @@ namespace device { ...@@ -18,7 +18,7 @@ namespace device {
namespace instance { namespace instance {
// grouped conv2d forward, GNHWC/GKYXC/GNHWK // grouped conv2d forward, GNHWC/GKYXC/GNHWK
void add_device_conv2d_bias_perchannel_quantization_int8_instances( void add_device_conv2d_dl_bias_perchannel_quantization_int8_instances(
std::vector< std::vector<
std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, GNHWC,
...@@ -34,7 +34,38 @@ void add_device_conv2d_bias_perchannel_quantization_int8_instances( ...@@ -34,7 +34,38 @@ void add_device_conv2d_bias_perchannel_quantization_int8_instances(
Add_Activation_Mul2_Clamp<PassThrough>>>>& Add_Activation_Mul2_Clamp<PassThrough>>>>&
instances); instances);
void add_device_conv2d_bias_relu_perchannel_quantization_int8_instances( void add_device_conv2d_dl_bias_relu_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC,
GKYXC,
GK_GK_Tuple,
GNHWK,
int8_t,
int8_t,
I32_F32_Tuple,
int8_t,
PassThrough,
PassThrough,
Add_Activation_Mul2_Clamp<Relu>>>>&
instances);
void add_device_conv2d_xdl_bias_perchannel_quantization_int8_instances(
std::vector<
std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC,
GKYXC,
GK_GK_Tuple,
GNHWK,
int8_t,
int8_t,
I32_F32_Tuple,
int8_t,
PassThrough,
PassThrough,
Add_Activation_Mul2_Clamp<PassThrough>>>>&
instances);
void add_device_conv2d_xdl_bias_relu_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, GNHWC,
GKYXC, GKYXC,
...@@ -98,9 +129,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -98,9 +129,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
is_same_v<DsDataType, I32_F32_Tuple> && is_same_v<OutDataType, int8_t>) is_same_v<DsDataType, I32_F32_Tuple> && is_same_v<OutDataType, int8_t>)
{ {
if constexpr(is_same_v<Activation, PassThrough>) if constexpr(is_same_v<Activation, PassThrough>)
add_device_conv2d_bias_perchannel_quantization_int8_instances(op_ptrs); {
add_device_conv2d_dl_bias_perchannel_quantization_int8_instances(op_ptrs);
add_device_conv2d_xdl_bias_perchannel_quantization_int8_instances(op_ptrs);
}
else if constexpr(is_same_v<Activation, Relu>) else if constexpr(is_same_v<Activation, Relu>)
add_device_conv2d_bias_relu_perchannel_quantization_int8_instances(op_ptrs); {
add_device_conv2d_dl_bias_relu_perchannel_quantization_int8_instances(op_ptrs);
add_device_conv2d_xdl_bias_relu_perchannel_quantization_int8_instances(op_ptrs);
}
} }
} }
......
library/include/ck/library/tensor_operation_instance/gpu/quantization/grouped_convolution_bias_forward_perlayer_quantization.hpp
View file @ ff46bd90
...@@ -18,7 +18,7 @@ namespace device { ...@@ -18,7 +18,7 @@ namespace device {
namespace instance { namespace instance {
// grouped conv2d forward, GNHWC/GKYXC/GNHWK // grouped conv2d forward, GNHWC/GKYXC/GNHWK
void add_device_conv2d_bias_perlayer_quantization_int8_instances( void add_device_conv2d_dl_bias_perlayer_quantization_int8_instances(
std::vector< std::vector<
std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, GNHWC,
...@@ -34,7 +34,38 @@ void add_device_conv2d_bias_perlayer_quantization_int8_instances( ...@@ -34,7 +34,38 @@ void add_device_conv2d_bias_perlayer_quantization_int8_instances(
Add_Activation_Mul_Clamp<PassThrough>>>>& Add_Activation_Mul_Clamp<PassThrough>>>>&
instances); instances);
void add_device_conv2d_bias_relu_perlayer_quantization_int8_instances( void add_device_conv2d_dl_bias_relu_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC,
GKYXC,
GK_Tuple,
GNHWK,
int8_t,
int8_t,
I32_Tuple,
int8_t,
PassThrough,
PassThrough,
Add_Activation_Mul_Clamp<Relu>>>>&
instances);
void add_device_conv2d_xdl_bias_perlayer_quantization_int8_instances(
std::vector<
std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC,
GKYXC,
GK_Tuple,
GNHWK,
int8_t,
int8_t,
I32_Tuple,
int8_t,
PassThrough,
PassThrough,
Add_Activation_Mul_Clamp<PassThrough>>>>&
instances);
void add_device_conv2d_xdl_bias_relu_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, GNHWC,
GKYXC, GKYXC,
...@@ -98,9 +129,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -98,9 +129,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
is_same_v<DsDataType, I32_Tuple> && is_same_v<OutDataType, int8_t>) is_same_v<DsDataType, I32_Tuple> && is_same_v<OutDataType, int8_t>)
{ {
if constexpr(is_same_v<Activation, PassThrough>) if constexpr(is_same_v<Activation, PassThrough>)
add_device_conv2d_bias_perlayer_quantization_int8_instances(op_ptrs); {
add_device_conv2d_dl_bias_perlayer_quantization_int8_instances(op_ptrs);
add_device_conv2d_xdl_bias_perlayer_quantization_int8_instances(op_ptrs);
}
else if constexpr(is_same_v<Activation, Relu>) else if constexpr(is_same_v<Activation, Relu>)
add_device_conv2d_bias_relu_perlayer_quantization_int8_instances(op_ptrs); {
add_device_conv2d_dl_bias_relu_perlayer_quantization_int8_instances(op_ptrs);
add_device_conv2d_xdl_bias_relu_perlayer_quantization_int8_instances(op_ptrs);
}
} }
} }
......
library/include/ck/library/tensor_operation_instance/gpu/quantization/grouped_convolution_forward_perchannel_quantization.hpp
View file @ ff46bd90
...@@ -18,7 +18,7 @@ namespace device { ...@@ -18,7 +18,7 @@ namespace device {
namespace instance { namespace instance {
// grouped conv2d forward, GNHWC/GKYXC/GNHWK // grouped conv2d forward, GNHWC/GKYXC/GNHWK
void add_device_conv2d_perchannel_quantization_int8_instances( void add_device_conv2d_dl_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, GNHWC,
GKYXC, GKYXC,
...@@ -33,7 +33,37 @@ void add_device_conv2d_perchannel_quantization_int8_instances( ...@@ -33,7 +33,37 @@ void add_device_conv2d_perchannel_quantization_int8_instances(
Activation_Mul2_Clamp<PassThrough>>>>& Activation_Mul2_Clamp<PassThrough>>>>&
instances); instances);
void add_device_conv2d_relu_perchannel_quantization_int8_instances( void add_device_conv2d_dl_relu_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC,
GKYXC,
GK_Tuple,
GNHWK,
int8_t,
int8_t,
F32_Tuple,
int8_t,
PassThrough,
PassThrough,
Activation_Mul2_Clamp<Relu>>>>&
instances);
void add_device_conv2d_xdl_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC,
GKYXC,
GK_Tuple,
GNHWK,
int8_t,
int8_t,
F32_Tuple,
int8_t,
PassThrough,
PassThrough,
Activation_Mul2_Clamp<PassThrough>>>>&
instances);
void add_device_conv2d_xdl_relu_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, GNHWC,
GKYXC, GKYXC,
...@@ -97,9 +127,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -97,9 +127,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
is_same_v<OutDataType, int8_t>) is_same_v<OutDataType, int8_t>)
{ {
if constexpr(is_same_v<Activation, PassThrough>) if constexpr(is_same_v<Activation, PassThrough>)
add_device_conv2d_perchannel_quantization_int8_instances(op_ptrs); {
add_device_conv2d_dl_perchannel_quantization_int8_instances(op_ptrs);
add_device_conv2d_xdl_perchannel_quantization_int8_instances(op_ptrs);
}
else if constexpr(is_same_v<Activation, Relu>) else if constexpr(is_same_v<Activation, Relu>)
add_device_conv2d_relu_perchannel_quantization_int8_instances(op_ptrs); {
add_device_conv2d_dl_relu_perchannel_quantization_int8_instances(op_ptrs);
add_device_conv2d_xdl_relu_perchannel_quantization_int8_instances(op_ptrs);
}
} }
} }
......
library/include/ck/library/tensor_operation_instance/gpu/quantization/grouped_convolution_forward_perlayer_quantization.hpp
View file @ ff46bd90
...@@ -18,7 +18,7 @@ namespace device { ...@@ -18,7 +18,7 @@ namespace device {
namespace instance { namespace instance {
// grouped conv2d forward, GNHWC/GKYXC/GNHWK // grouped conv2d forward, GNHWC/GKYXC/GNHWK
void add_device_conv2d_perlayer_quantization_int8_instances( void add_device_conv2d_dl_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, GNHWC,
GKYXC, GKYXC,
...@@ -33,7 +33,37 @@ void add_device_conv2d_perlayer_quantization_int8_instances( ...@@ -33,7 +33,37 @@ void add_device_conv2d_perlayer_quantization_int8_instances(
Activation_Mul_Clamp<PassThrough>>>>& Activation_Mul_Clamp<PassThrough>>>>&
instances); instances);
void add_device_conv2d_relu_perlayer_quantization_int8_instances( void add_device_conv2d_dl_relu_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC,
GKYXC,
Empty_Tuple,
GNHWK,
int8_t,
int8_t,
Empty_Tuple,
int8_t,
PassThrough,
PassThrough,
Activation_Mul_Clamp<Relu>>>>&
instances);
void add_device_conv2d_xdl_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC,
GKYXC,
Empty_Tuple,
GNHWK,
int8_t,
int8_t,
Empty_Tuple,
int8_t,
PassThrough,
PassThrough,
Activation_Mul_Clamp<PassThrough>>>>&
instances);
void add_device_conv2d_xdl_relu_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, GNHWC,
GKYXC, GKYXC,
...@@ -94,9 +124,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -94,9 +124,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
is_same_v<OutDataType, int8_t>) is_same_v<OutDataType, int8_t>)
{ {
if constexpr(is_same_v<Activation, PassThrough>) if constexpr(is_same_v<Activation, PassThrough>)
add_device_conv2d_perlayer_quantization_int8_instances(op_ptrs); {
add_device_conv2d_dl_perlayer_quantization_int8_instances(op_ptrs);
add_device_conv2d_xdl_perlayer_quantization_int8_instances(op_ptrs);
}
else if constexpr(is_same_v<Activation, Relu>) else if constexpr(is_same_v<Activation, Relu>)
add_device_conv2d_relu_perlayer_quantization_int8_instances(op_ptrs); {
add_device_conv2d_dl_relu_perlayer_quantization_int8_instances(op_ptrs);
add_device_conv2d_xdl_relu_perlayer_quantization_int8_instances(op_ptrs);
}
} }
} }
......
library/src/tensor_operation_instance/gpu/quantization/CMakeLists.txt
View file @ ff46bd90
set(CONV2D_PERLAYER_QUANT_SRC
conv2d_fwd/device_conv2d_dl_perlayer_quantization_int8_instance.cpp
conv2d_fwd/device_conv2d_xdl_perlayer_quantization_int8_instance.cpp
)
set(CONV2D_PERCHANNEL_QUANT_SRC
conv2d_fwd/device_conv2d_dl_perchannel_quantization_int8_instance.cpp
conv2d_fwd/device_conv2d_xdl_perchannel_quantization_int8_instance.cpp
)
set(CONV2D_BIAS_PERLAYER_QUANT_SRC
conv2d_fwd/device_conv2d_dl_bias_perlayer_quantization_int8_instance.cpp
conv2d_fwd/device_conv2d_xdl_bias_perlayer_quantization_int8_instance.cpp
)
set(CONV2D_BIAS_PERCHANNEL_QUANT_SRC
conv2d_fwd/device_conv2d_dl_bias_perchannel_quantization_int8_instance.cpp
conv2d_fwd/device_conv2d_xdl_bias_perchannel_quantization_int8_instance.cpp
)
add_instance_library(device_quantization_instance add_instance_library(device_quantization_instance
conv2d_fwd/device_conv2d_bias_perchannel_quantization_int8_instance.cpp ${CONV2D_PERLAYER_QUANT_SRC}
conv2d_fwd/device_conv2d_bias_perlayer_quantization_int8_instance.cpp ${CONV2D_PERCHANNEL_QUANT_SRC}
conv2d_fwd/device_conv2d_perchannel_quantization_int8_instance.cpp ${CONV2D_BIAS_PERLAYER_QUANT_SRC}
conv2d_fwd/device_conv2d_perlayer_quantization_int8_instance.cpp ${CONV2D_BIAS_PERCHANNEL_QUANT_SRC}
) )
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/conv2d_quantization_common.hpp 0 → 100644
View file @ ff46bd90
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/convolution_forward_specialization.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using Empty_Tuple = ck::Tuple<>;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using GNHWC = ck::tensor_layout::convolution::GNHWC;
using GKYXC = ck::tensor_layout::convolution::GKYXC;
using GNHWK = ck::tensor_layout::convolution::GNHWK;
using GK = ck::tensor_layout::convolution::G_K;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using Relu = ck::tensor_operation::element_wise::Relu;
using GK_Tuple = ck::Tuple<GK>;
using GK_GK_Tuple = ck::Tuple<GK, GK>;
using I32_Tuple = ck::Tuple<int32_t>;
using F32_Tuple = ck::Tuple<float>;
using I32_F32_Tuple = ck::Tuple<int32_t, float>;
using Mul_Clamp = ck::tensor_operation::element_wise::Activation_Mul_Clamp<PassThrough>;
using Relu_Mul_Clamp = ck::tensor_operation::element_wise::Activation_Mul_Clamp<Relu>;
using Add_Mul_Clamp = ck::tensor_operation::element_wise::Add_Activation_Mul_Clamp<PassThrough>;
using Add_Relu_Mul_Clamp = ck::tensor_operation::element_wise::Add_Activation_Mul_Clamp<Relu>;
using Mul2_Clamp = ck::tensor_operation::element_wise::Activation_Mul2_Clamp<PassThrough>;
using Relu_Mul2_Clamp = ck::tensor_operation::element_wise::Activation_Mul2_Clamp<Relu>;
using Add_Mul2_Clamp = ck::tensor_operation::element_wise::Add_Activation_Mul2_Clamp<PassThrough>;
using Add_Relu_Mul2_Clamp = ck::tensor_operation::element_wise::Add_Activation_Mul2_Clamp<Relu>;
static constexpr ck::index_t NDimSpatial = 2;
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
static constexpr auto ConvFwdDefault =
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
static constexpr auto ConvFwd1x1P0 =
ck::tensor_operation::device::ConvolutionForwardSpecialization::Filter1x1Pad0;
static constexpr auto ConvFwd1x1S1P0 =
ck::tensor_operation::device::ConvolutionForwardSpecialization::Filter1x1Stride1Pad0;
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_dl_bias_perchannel_quantization_int8_instance.cpp 0 → 100644
View file @ ff46bd90
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "device_conv2d_dl_int8_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
void add_device_conv2d_dl_bias_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC,
GKYXC,
GK_GK_Tuple,
GNHWK,
int8_t,
int8_t,
I32_F32_Tuple,
int8_t,
PassThrough,
PassThrough,
Add_Mul2_Clamp>>>& instances)
{
// dl
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_GK_Tuple,
I32_F32_Tuple,
Add_Mul2_Clamp,
ConvFwdDefault,
4>{});
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_GK_Tuple,
I32_F32_Tuple,
Add_Mul2_Clamp,
ConvFwd1x1P0,
4>{});
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_GK_Tuple,
I32_F32_Tuple,
Add_Mul2_Clamp,
ConvFwd1x1S1P0,
4>{});
}
void add_device_conv2d_dl_bias_relu_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC,
GKYXC,
GK_GK_Tuple,
GNHWK,
int8_t,
int8_t,
I32_F32_Tuple,
int8_t,
PassThrough,
PassThrough,
Add_Relu_Mul2_Clamp>>>& instances)
{
// dl
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_GK_Tuple,
I32_F32_Tuple,
Add_Relu_Mul2_Clamp,
ConvFwdDefault,
4>{});
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_GK_Tuple,
I32_F32_Tuple,
Add_Relu_Mul2_Clamp,
ConvFwd1x1P0,
4>{});
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_GK_Tuple,
I32_F32_Tuple,
Add_Relu_Mul2_Clamp,
ConvFwd1x1S1P0,
4>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_dl_bias_perlayer_quantization_int8_instance.cpp 0 → 100644
View file @ ff46bd90
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "device_conv2d_dl_int8_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
void add_device_conv2d_dl_bias_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC,
GKYXC,
GK_Tuple,
GNHWK,
int8_t,
int8_t,
I32_Tuple,
int8_t,
PassThrough,
PassThrough,
Add_Mul_Clamp>>>& instances)
{
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple,
I32_Tuple,
Add_Mul_Clamp,
ConvFwdDefault,
4>{});
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple,
I32_Tuple,
Add_Mul_Clamp,
ConvFwd1x1P0,
4>{});
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple,
I32_Tuple,
Add_Mul_Clamp,
ConvFwd1x1S1P0,
4>{});
}
void add_device_conv2d_dl_bias_relu_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC,
GKYXC,
GK_Tuple,
GNHWK,
int8_t,
int8_t,
I32_Tuple,
int8_t,
PassThrough,
PassThrough,
Add_Relu_Mul_Clamp>>>& instances)
{
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple,
I32_Tuple,
Add_Relu_Mul_Clamp,
ConvFwdDefault,
4>{});
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple,
I32_Tuple,
Add_Relu_Mul_Clamp,
ConvFwd1x1P0,
4>{});
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple,
I32_Tuple,
Add_Relu_Mul_Clamp,
ConvFwd1x1S1P0,
4>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_dl_int8_instance.hpp 0 → 100644
View file @ ff46bd90
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "conv2d_quantization_common.hpp"
#include "ck/tensor_operation/gpu/device/device_grouped_conv_fwd_dl_multiple_d_nhwc_kyxc_nhwk.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// clang-format off
template <typename DsLayout,
typename DsDatatype,
typename OutElementOp,
ConvolutionForwardSpecialization ConvSpec,
index_t DstScalarPerVector>
using device_grouped_conv2d_dl_int8_instances =
std::tuple<
// ###########################################| 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| | |
// ###########################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGroupedConvFwdDlMultipleD_NHWC_KYXC_NHWK< NDimSpatial, int8_t, int8_t, DsDatatype, int8_t, int32_t, GNHWC, GKYXC, DsLayout, GNHWK, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 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, DstScalarPerVector>
>;
// clang-format on
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_dl_perchannel_quantization_int8_instance.cpp 0 → 100644
View file @ ff46bd90
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "device_conv2d_dl_int8_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
void add_device_conv2d_dl_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC,
GKYXC,
GK_Tuple,
GNHWK,
int8_t,
int8_t,
F32_Tuple,
int8_t,
PassThrough,
PassThrough,
Mul2_Clamp>>>& instances)
{
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple,
F32_Tuple,
Mul2_Clamp,
ConvFwdDefault,
4>{});
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple,
F32_Tuple,
Mul2_Clamp,
ConvFwd1x1P0,
4>{});
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple,
F32_Tuple,
Mul2_Clamp,
ConvFwd1x1S1P0,
4>{});
}
void add_device_conv2d_dl_relu_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC,
GKYXC,
GK_Tuple,
GNHWK,
int8_t,
int8_t,
F32_Tuple,
int8_t,
PassThrough,
PassThrough,
Relu_Mul2_Clamp>>>& instances)
{
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple,
F32_Tuple,
Relu_Mul2_Clamp,
ConvFwdDefault,
4>{});
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple,
F32_Tuple,
Relu_Mul2_Clamp,
ConvFwd1x1P0,
4>{});
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple,
F32_Tuple,
Relu_Mul2_Clamp,
ConvFwd1x1S1P0,
4>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_dl_perlayer_quantization_int8_instance.cpp 0 → 100644
View file @ ff46bd90
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "device_conv2d_dl_int8_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
void add_device_conv2d_dl_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC,
GKYXC,
Empty_Tuple,
GNHWK,
int8_t,
int8_t,
Empty_Tuple,
int8_t,
PassThrough,
PassThrough,
Mul_Clamp>>>& instances)
{
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<Empty_Tuple,
Empty_Tuple,
Mul_Clamp,
ConvFwdDefault,
4>{});
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<Empty_Tuple,
Empty_Tuple,
Mul_Clamp,
ConvFwd1x1P0,
4>{});
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<Empty_Tuple,
Empty_Tuple,
Mul_Clamp,
ConvFwd1x1S1P0,
4>{});
}
void add_device_conv2d_dl_relu_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC,
GKYXC,
Empty_Tuple,
GNHWK,
int8_t,
int8_t,
Empty_Tuple,
int8_t,
PassThrough,
PassThrough,
Relu_Mul_Clamp>>>& instances)
{
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<Empty_Tuple,
Empty_Tuple,
Relu_Mul_Clamp,
ConvFwdDefault,
4>{});
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<Empty_Tuple,
Empty_Tuple,
Relu_Mul_Clamp,
ConvFwd1x1P0,
4>{});
add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<Empty_Tuple,
Empty_Tuple,
Relu_Mul_Clamp,
ConvFwd1x1S1P0,
4>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_int8_instance.hpp deleted 100644 → 0
View file @ dc7b6568
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_fwd_multiple_d_xdl_cshuffle.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using Empty_Tuple = ck::Tuple<>;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using GNHWC = ck::tensor_layout::convolution::GNHWC;
using GKYXC = ck::tensor_layout::convolution::GKYXC;
using GNHWK = ck::tensor_layout::convolution::GNHWK;
using GK = ck::tensor_layout::convolution::G_K;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using Relu = ck::tensor_operation::element_wise::Relu;
using GK_Tuple = ck::Tuple<GK>;
using GK_GK_Tuple = ck::Tuple<GK, GK>;
using I32_Tuple = ck::Tuple<int32_t>;
using F32_Tuple = ck::Tuple<float>;
using I32_F32_Tuple = ck::Tuple<int32_t, float>;
using Mul_Clamp = ck::tensor_operation::element_wise::Activation_Mul_Clamp<PassThrough>;
using Relu_Mul_Clamp = ck::tensor_operation::element_wise::Activation_Mul_Clamp<Relu>;
using Add_Mul_Clamp = ck::tensor_operation::element_wise::Add_Activation_Mul_Clamp<PassThrough>;
using Add_Relu_Mul_Clamp = ck::tensor_operation::element_wise::Add_Activation_Mul_Clamp<Relu>;
using Mul2_Clamp = ck::tensor_operation::element_wise::Activation_Mul2_Clamp<PassThrough>;
using Relu_Mul2_Clamp = ck::tensor_operation::element_wise::Activation_Mul2_Clamp<Relu>;
using Add_Mul2_Clamp = ck::tensor_operation::element_wise::Add_Activation_Mul2_Clamp<PassThrough>;
using Add_Relu_Mul2_Clamp = ck::tensor_operation::element_wise::Add_Activation_Mul2_Clamp<Relu>;
static constexpr ck::index_t NDimSpatial = 2;
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
static constexpr auto ConvFwdDefault =
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
static constexpr auto ConvFwd1x1P0 =
ck::tensor_operation::device::ConvolutionForwardSpecialization::Filter1x1Pad0;
static constexpr auto ConvFwd1x1S1P0 =
ck::tensor_operation::device::ConvolutionForwardSpecialization::Filter1x1Stride1Pad0;
template <typename DsLayout,
typename DsDatatype,
typename OutElementOp,
ConvolutionForwardSpecialization ConvSpec,
index_t DstScalarPerVector = 16>
// clang-format off
using device_grouped_conv2d_xdl_int8_instances =
std::tuple <
//########################################| NumDim| A| B| Ds| E| AData| BData| AccData| CShuffle| Ds| EData| A| B| CDE| ConvForward| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
//########################################| Spatial| Layout| Layout| Layout| Layout| Type| Type| Type| DataType| DataType| Type| Elementwise| Elementwise| Elementwise| Specialization| Specialization| Prefetch| Size| Block| Block| Block| | | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector|
//########################################| | | | | | | | | | | | Operation| Operation| Operation| | | Stage| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
//########################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle< 2, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 256, 128, 64, 16, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle< 2, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 128, 256, 64, 16, 16, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle< 2, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 128, 128, 64, 16, 16, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle< 2, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 128, 128, 64, 16, 16, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle< 2, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 128, 64, 64, 16, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 2>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle< 2, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 64, 128, 64, 16, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle< 2, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 64, 64, 64, 64, 16, 16, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 2>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle< 2, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 128, 64, 64, 16, 16, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle< 2, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 64, 128, 64, 16, 16, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle< 2, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 128, 32, 64, 16, 16, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 2>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle< 2, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 32, 128, 64, 16, 16, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle< 2, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 64, 64, 32, 64, 16, 16, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 2>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle< 2, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 64, 32, 64, 64, 16, 16, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 2>, DstScalarPerVector>
>;
// clang-format on
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_bias_perchannel_quantization_int8_instance.cpp → library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_xdl_bias_perchannel_quantization_int8_instance.cpp
View file @ ff46bd90
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "device_conv2d_int8_instance.hpp" #include "device_conv2d_xdl_int8_instance.hpp"
namespace ck { namespace ck {
namespace tensor_operation { namespace tensor_operation {
namespace device { namespace device {
namespace instance { namespace instance {
void add_device_conv2d_bias_perchannel_quantization_int8_instances( void add_device_conv2d_xdl_bias_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, GNHWC,
GKYXC, GKYXC,
...@@ -41,7 +41,7 @@ void add_device_conv2d_bias_perchannel_quantization_int8_instances( ...@@ -41,7 +41,7 @@ void add_device_conv2d_bias_perchannel_quantization_int8_instances(
8>{}); 8>{});
} }
void add_device_conv2d_bias_relu_perchannel_quantization_int8_instances( void add_device_conv2d_xdl_bias_relu_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, GNHWC,
GKYXC, GKYXC,
......
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_bias_perlayer_quantization_int8_instance.cpp → library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_xdl_bias_perlayer_quantization_int8_instance.cpp
View file @ ff46bd90
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "device_conv2d_int8_instance.hpp" #include "device_conv2d_xdl_int8_instance.hpp"
namespace ck { namespace ck {
namespace tensor_operation { namespace tensor_operation {
namespace device { namespace device {
namespace instance { namespace instance {
void add_device_conv2d_bias_perlayer_quantization_int8_instances( void add_device_conv2d_xdl_bias_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, GNHWC,
GKYXC, GKYXC,
...@@ -41,7 +41,7 @@ void add_device_conv2d_bias_perlayer_quantization_int8_instances( ...@@ -41,7 +41,7 @@ void add_device_conv2d_bias_perlayer_quantization_int8_instances(
8>{}); 8>{});
} }
void add_device_conv2d_bias_relu_perlayer_quantization_int8_instances( void add_device_conv2d_xdl_bias_relu_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, GNHWC,
GKYXC, GKYXC,
......
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_xdl_int8_instance.hpp 0 → 100644
View file @ ff46bd90
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "conv2d_quantization_common.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_fwd_multiple_d_xdl_cshuffle.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// clang-format off
template <typename DsLayout,
typename DsDatatype,
typename OutElementOp,
ConvolutionForwardSpecialization ConvSpec,
index_t DstScalarPerVector>
using device_grouped_conv2d_xdl_int8_instances =
std::tuple <
//########################################| NumDim| A| B| Ds| E| AData| BData| AccData| CShuffle| Ds| EData| A| B| CDE| ConvForward| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
//########################################| Spatial| Layout| Layout| Layout| Layout| Type| Type| Type| DataType| DataType| Type| Elementwise| Elementwise| Elementwise| Specialization| Specialization| Prefetch| Size| Block| Block| Block| | | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector|
//########################################| | | | | | | | | | | | Operation| Operation| Operation| | | Stage| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
//########################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 256, 128, 64, 16, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 128, 256, 64, 16, 16, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 128, 128, 64, 16, 16, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 128, 128, 64, 16, 16, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 128, 64, 64, 16, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 2>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 64, 128, 64, 16, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 64, 64, 64, 64, 16, 16, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 2>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 128, 64, 64, 16, 16, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 64, 128, 64, 16, 16, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 128, 32, 64, 16, 16, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 2>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 32, 128, 64, 16, 16, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 64, 64, 32, 64, 16, 16, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 2>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 64, 32, 64, 64, 16, 16, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 2>, DstScalarPerVector>
>;
// clang-format on
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_perchannel_quantization_int8_instance.cpp → library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_xdl_perchannel_quantization_int8_instance.cpp
View file @ ff46bd90
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "device_conv2d_int8_instance.hpp" #include "device_conv2d_xdl_int8_instance.hpp"
namespace ck { namespace ck {
namespace tensor_operation { namespace tensor_operation {
namespace device { namespace device {
namespace instance { namespace instance {
void add_device_conv2d_perchannel_quantization_int8_instances( void add_device_conv2d_xdl_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, GNHWC,
GKYXC, GKYXC,
...@@ -41,7 +41,7 @@ void add_device_conv2d_perchannel_quantization_int8_instances( ...@@ -41,7 +41,7 @@ void add_device_conv2d_perchannel_quantization_int8_instances(
8>{}); 8>{});
} }
void add_device_conv2d_relu_perchannel_quantization_int8_instances( void add_device_conv2d_xdl_relu_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, GNHWC,
GKYXC, GKYXC,
......
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