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Commit c5138aa1 authored by Artur Wojcik's avatar Artur Wojcik
Browse files

Merge branch 'develop' into uif2-initial

parents 7830272f 82f3a835
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Showing with 470 additions and 302 deletions
include/ck/utility/data_type.hpp
View file @ c5138aa1
...@@ -9,15 +9,9 @@ namespace ck { ...@@ -9,15 +9,9 @@ namespace ck {
using bhalf_t = ushort; using bhalf_t = ushort;
using half_t = _Float16; using half_t = _Float16;
#ifdef CK_EXPERIMENTAL_BIT_INT_EXTENSION_INT4 using int4_t = _BitInt(4);
using int4_t = _BitInt(4); using f8_t = _BitInt(8);
#endif using bf8_t = unsigned _BitInt(8);
#if defined CK_ENABLE_FP8
using f8_t = _BitInt(8);
#endif
#if defined CK_ENABLE_BF8
using bf8_t = unsigned _BitInt(8);
#endif
// vector_type // vector_type
template <typename T, index_t N> template <typename T, index_t N>
...@@ -148,23 +142,19 @@ struct scalar_type<int4_t> ...@@ -148,23 +142,19 @@ struct scalar_type<int4_t>
}; };
#endif #endif
#if defined CK_ENABLE_FP8
template <> template <>
struct scalar_type<f8_t> struct scalar_type<f8_t>
{ {
using type = f8_t; using type = f8_t;
static constexpr index_t vector_size = 1; static constexpr index_t vector_size = 1;
}; };
#endif
#if defined CK_ENABLE_BF8
template <> template <>
struct scalar_type<bf8_t> struct scalar_type<bf8_t>
{ {
using type = bf8_t; using type = bf8_t;
static constexpr index_t vector_size = 1; static constexpr index_t vector_size = 1;
}; };
#endif
template <typename T> template <typename T>
struct vector_type<T, 1> struct vector_type<T, 1>
...@@ -968,24 +958,20 @@ using int8x32_t = typename vector_type<int8_t, 32>::type; ...@@ -968,24 +958,20 @@ using int8x32_t = typename vector_type<int8_t, 32>::type;
using int8x64_t = typename vector_type<int8_t, 64>::type; using int8x64_t = typename vector_type<int8_t, 64>::type;
// f8 // f8
#if defined CK_ENABLE_FP8
using f8x2_t = typename vector_type<f8_t, 2>::type; using f8x2_t = typename vector_type<f8_t, 2>::type;
using f8x4_t = typename vector_type<f8_t, 4>::type; using f8x4_t = typename vector_type<f8_t, 4>::type;
using f8x8_t = typename vector_type<f8_t, 8>::type; using f8x8_t = typename vector_type<f8_t, 8>::type;
using f8x16_t = typename vector_type<f8_t, 16>::type; using f8x16_t = typename vector_type<f8_t, 16>::type;
using f8x32_t = typename vector_type<f8_t, 32>::type; using f8x32_t = typename vector_type<f8_t, 32>::type;
using f8x64_t = typename vector_type<f8_t, 64>::type; using f8x64_t = typename vector_type<f8_t, 64>::type;
#endif
// bf8 // bf8
#if defined CK_ENABLE_BF8
using bf8x2_t = typename vector_type<bf8_t, 2>::type; using bf8x2_t = typename vector_type<bf8_t, 2>::type;
using bf8x4_t = typename vector_type<bf8_t, 4>::type; using bf8x4_t = typename vector_type<bf8_t, 4>::type;
using bf8x8_t = typename vector_type<bf8_t, 8>::type; using bf8x8_t = typename vector_type<bf8_t, 8>::type;
using bf8x16_t = typename vector_type<bf8_t, 16>::type; using bf8x16_t = typename vector_type<bf8_t, 16>::type;
using bf8x32_t = typename vector_type<bf8_t, 32>::type; using bf8x32_t = typename vector_type<bf8_t, 32>::type;
using bf8x64_t = typename vector_type<bf8_t, 64>::type; using bf8x64_t = typename vector_type<bf8_t, 64>::type;
#endif
template <typename T> template <typename T>
struct NumericLimits struct NumericLimits
...@@ -1033,7 +1019,6 @@ struct NumericLimits<int4_t> ...@@ -1033,7 +1019,6 @@ struct NumericLimits<int4_t>
}; };
#endif // CK_EXPERIMENTAL_BIT_INT_EXTENSION_INT4 #endif // CK_EXPERIMENTAL_BIT_INT_EXTENSION_INT4
#if defined CK_ENABLE_FP8
template <> template <>
struct NumericLimits<f8_t> struct NumericLimits<f8_t>
{ {
...@@ -1056,9 +1041,7 @@ struct NumericLimits<f8_t> ...@@ -1056,9 +1041,7 @@ struct NumericLimits<f8_t>
__host__ __device__ static constexpr f8_t QuietNaN() { return f8_t(binary_qnan); } __host__ __device__ static constexpr f8_t QuietNaN() { return f8_t(binary_qnan); }
}; };
#endif
#if defined CK_ENABLE_BF8
template <> template <>
struct NumericLimits<bf8_t> struct NumericLimits<bf8_t>
{ {
...@@ -1081,7 +1064,6 @@ struct NumericLimits<bf8_t> ...@@ -1081,7 +1064,6 @@ struct NumericLimits<bf8_t>
__host__ __device__ static constexpr bf8_t QuietNaN() { return bf8_t(binary_qnan); } __host__ __device__ static constexpr bf8_t QuietNaN() { return bf8_t(binary_qnan); }
}; };
#endif
template <typename T> template <typename T>
struct NumericUtils struct NumericUtils
...@@ -1120,22 +1102,18 @@ struct NumericUtils<half_t> ...@@ -1120,22 +1102,18 @@ struct NumericUtils<half_t>
using bitwise_type = uint16_t; using bitwise_type = uint16_t;
}; };
#if defined CK_ENABLE_FP8
template <> template <>
struct NumericUtils<f8_t> struct NumericUtils<f8_t>
{ {
static constexpr int exp = 4; static constexpr int exp = 4;
static constexpr int mant = 3; static constexpr int mant = 3;
}; };
#endif
#if defined CK_ENABLE_BF8
template <> template <>
struct NumericUtils<bf8_t> struct NumericUtils<bf8_t>
{ {
static constexpr int exp = 5; static constexpr int exp = 5;
static constexpr int mant = 2; static constexpr int mant = 2;
}; };
#endif //
} // namespace ck } // namespace ck
include/ck/utility/f8_utils.hpp
View file @ c5138aa1
...@@ -6,8 +6,6 @@ ...@@ -6,8 +6,6 @@
#include "ck/utility/data_type.hpp" #include "ck/utility/data_type.hpp"
// these conversions are disabled if native conversions available // these conversions are disabled if native conversions available
#if !defined(__gfx940__) && !defined(__gfx941__) && !defined(__gfx942__)
#if defined CK_ENABLE_FP8 || defined CK_ENABLE_BF8
namespace ck { namespace ck {
// fp8 rounding modes // fp8 rounding modes
...@@ -244,5 +242,3 @@ __host__ __device__ Y cast_from_f8(X x) ...@@ -244,5 +242,3 @@ __host__ __device__ Y cast_from_f8(X x)
} }
} // namespace ck::utils } // namespace ck::utils
#endif // #if defined CK_ENABLE_FP8 || defined CK_ENABLE_BF8
#endif // #if !defined(__gfx940__) && !defined(__gfx941__) && !defined(__gfx942__)
include/ck/utility/math.hpp
View file @ c5138aa1
...@@ -150,28 +150,6 @@ __host__ __device__ constexpr T clamp(const T& x, const T& lowerbound, const T& ...@@ -150,28 +150,6 @@ __host__ __device__ constexpr T clamp(const T& x, const T& lowerbound, const T&
return min(max(x, lowerbound), upperbound); return min(max(x, lowerbound), upperbound);
} }
// disallow implicit type casting
template <typename T>
__device__ T exp(T x);
// TODO: add f16 support using v_exp_f16
template <>
__device__ float exp<float>(float x)
{
return __expf(x);
}
template <>
__device__ double exp<double>(double x)
{
return exp(x);
}
static inline __host__ float exp(float x) { return std::expf(x); }
static inline __host__ double exp(double x) { return std::exp(x); }
// greatest common divisor, aka highest common factor // greatest common divisor, aka highest common factor
__host__ __device__ constexpr index_t gcd(index_t x, index_t y) __host__ __device__ constexpr index_t gcd(index_t x, index_t y)
{ {
......
include/ck/utility/math_v2.hpp
View file @ c5138aa1
...@@ -9,6 +9,7 @@ ...@@ -9,6 +9,7 @@
#include "ck/utility/data_type.hpp" #include "ck/utility/data_type.hpp"
#include "ck/utility/type.hpp" #include "ck/utility/type.hpp"
#include "ck/utility/type_convert.hpp"
namespace ck { namespace ck {
namespace math { namespace math {
...@@ -92,14 +93,96 @@ static inline __host__ float sqrt(float x) { return std::sqrt(x); }; ...@@ -92,14 +93,96 @@ static inline __host__ float sqrt(float x) { return std::sqrt(x); };
static inline __host__ double sqrt(double x) { return std::sqrt(x); }; static inline __host__ double sqrt(double x) { return std::sqrt(x); };
static inline __host__ half_t tanh(half_t x) template <typename T>
inline __host__ T tanh(T x)
{ {
return static_cast<half_t>(std::tanh(static_cast<float>(x))); return ck::type_convert<T>(std::tanhf(ck::type_convert<float>(x)));
}; };
static inline __host__ float tanh(float x) { return std::tanh(x); }; template <>
inline __host__ float tanh<float>(float x)
{
return std::tanhf(x);
};
template <>
inline __host__ double tanh<double>(double x)
{
return std::tanh(x);
};
template <typename T>
inline __host__ T exp(T x)
{
return ck::type_convert<T>(std::expf(ck::type_convert<float>(x)));
}
template <>
inline __host__ float exp<float>(float x)
{
return std::expf(x);
}
static inline __host__ double tanh(double x) { return std::tanh(x); }; template <>
inline __host__ double exp<double>(double x)
{
return std::exp(x);
}
template <typename T>
inline __host__ T log(T x)
{
return ck::type_convert<T>(std::logf(ck::type_convert<float>(x)));
}
template <>
inline __host__ float log<float>(float x)
{
return std::logf(x);
}
template <>
inline __host__ double log<double>(double x)
{
return std::log(x);
}
template <typename T>
inline __host__ T pow(T x, T gamma)
{
return ck::type_convert<T>(
std::powf(ck::type_convert<float>(x), ck::type_convert<float>(gamma)));
}
template <>
inline __host__ float pow<float>(float x, float gamma)
{
return std::powf(x, gamma);
}
template <>
inline __host__ double pow<double>(double x, double gamma)
{
return std::pow(x, gamma);
}
template <typename T>
inline __host__ T expm1(T x)
{
return ck::type_convert<T>(std::expm1f(ck::type_convert<float>(x)));
}
template <>
inline __host__ float expm1<float>(float x)
{
return std::expm1f(x);
}
template <>
inline __host__ double expm1<double>(double x)
{
return std::expm1(x);
}
// math functions for the HIP kernel, some are implemented by calling hip builtin functions // math functions for the HIP kernel, some are implemented by calling hip builtin functions
...@@ -181,14 +264,107 @@ static inline __device__ float sqrt(float x) { return __builtin_amdgcn_sqrtf(x); ...@@ -181,14 +264,107 @@ static inline __device__ float sqrt(float x) { return __builtin_amdgcn_sqrtf(x);
static inline __device__ double sqrt(double x) { return __builtin_amdgcn_sqrt(x); }; static inline __device__ double sqrt(double x) { return __builtin_amdgcn_sqrt(x); };
static inline __device__ half_t tanh(half_t x) template <typename T>
inline __device__ T tanh(T x)
{
return ck::type_convert<T>(::tanhf(ck::type_convert<float>(x)));
};
template <>
inline __device__ float tanh<float>(float x)
{ {
return static_cast<half_t>(::tanhf(static_cast<float>(x))); return ::tanhf(x);
}; };
static inline __device__ float tanh(float x) { return ::tanhf(x); }; template <>
inline __device__ double tanh<double>(double x)
{
return ::tanh(x);
};
template <typename T>
inline __device__ T exp(T x)
{
return ck::type_convert<T>(__expf(ck::type_convert<float>(x)));
};
template <>
inline __device__ half_t exp<half_t>(half_t x)
{
return hexp(x);
};
template <>
inline __device__ float exp<float>(float x)
{
return __expf(x);
};
static inline __device__ double tanh(double x) { return ::tanh(x); }; template <>
inline __device__ double exp<double>(double x)
{
return exp(x);
};
template <typename T>
inline __device__ T log(T x)
{
return ck::type_convert<T>(__logf(ck::type_convert<float>(x)));
};
template <>
inline __device__ half_t log<half_t>(half_t x)
{
return hlog(x);
};
template <>
inline __device__ float log<float>(float x)
{
return __logf(x);
};
template <>
inline __device__ double log<double>(double x)
{
return log(x);
};
template <typename T>
inline __device__ T pow(T x, T gamma)
{
return ck::type_convert<T>(powf(ck::type_convert<float>(x), ck::type_convert<float>(gamma)));
};
template <>
inline __device__ float pow<float>(float x, float gamma)
{
return powf(x, gamma);
};
template <>
inline __device__ double pow<double>(double x, double gamma)
{
return pow(x, gamma);
};
template <typename T>
inline __device__ T expm1(T x)
{
return ck::type_convert<T>(expm1f(ck::type_convert<float>(x)));
};
template <>
inline __device__ float expm1<float>(float x)
{
return expm1f(x);
};
template <>
inline __device__ double expm1<double>(double x)
{
return expm1(x);
};
} // namespace math } // namespace math
} // namespace ck } // namespace ck
include/ck/utility/statically_indexed_array_multi_index.hpp
View file @ c5138aa1
...@@ -5,6 +5,7 @@ ...@@ -5,6 +5,7 @@
#define CK_STATICALLY_INDEXED_ARRAY_MULTI_INDEX_HPP #define CK_STATICALLY_INDEXED_ARRAY_MULTI_INDEX_HPP
#include "common_header.hpp" #include "common_header.hpp"
#include "ck/utility/math_v2.hpp"
namespace ck { namespace ck {
......
include/ck/utility/type_convert.hpp
View file @ c5138aa1
...@@ -95,7 +95,6 @@ inline __host__ __device__ constexpr bhalf_t type_convert<bhalf_t, int8_t>(int8_ ...@@ -95,7 +95,6 @@ inline __host__ __device__ constexpr bhalf_t type_convert<bhalf_t, int8_t>(int8_
return type_convert<bhalf_t>(x_fp32); return type_convert<bhalf_t>(x_fp32);
} }
#if defined CK_ENABLE_FP8
// convert fp32 to fp8 // convert fp32 to fp8
template <> template <>
inline __host__ __device__ f8_t type_convert<f8_t, float>(float x) inline __host__ __device__ f8_t type_convert<f8_t, float>(float x)
...@@ -173,9 +172,7 @@ inline __host__ __device__ half_t type_convert<half_t, f8_t>(f8_t x) ...@@ -173,9 +172,7 @@ inline __host__ __device__ half_t type_convert<half_t, f8_t>(f8_t x)
return type_convert<half_t>(type_convert<float>(x)); return type_convert<half_t>(type_convert<float>(x));
#endif #endif
} }
#endif
#if defined CK_ENABLE_BF8
// convert fp32 to bf8 // convert fp32 to bf8
template <> template <>
inline __host__ __device__ bf8_t type_convert<bf8_t, float>(float x) inline __host__ __device__ bf8_t type_convert<bf8_t, float>(float x)
...@@ -253,7 +250,6 @@ inline __host__ __device__ half_t type_convert<half_t, bf8_t>(bf8_t x) ...@@ -253,7 +250,6 @@ inline __host__ __device__ half_t type_convert<half_t, bf8_t>(bf8_t x)
return type_convert<half_t>(type_convert<float>(x)); return type_convert<half_t>(type_convert<float>(x));
#endif #endif
} }
#endif
// Declare a template function for bf16 conversion using RTN // Declare a template function for bf16 conversion using RTN
template <typename Y, typename X> template <typename Y, typename X>
...@@ -316,7 +312,6 @@ inline __host__ __device__ constexpr bhalf_t bf16_convert_rtn<bhalf_t, half_t>(h ...@@ -316,7 +312,6 @@ inline __host__ __device__ constexpr bhalf_t bf16_convert_rtn<bhalf_t, half_t>(h
template <typename Y, typename X> template <typename Y, typename X>
__host__ __device__ constexpr Y f8_convert_sr(X x); __host__ __device__ constexpr Y f8_convert_sr(X x);
#if defined CK_ENABLE_FP8
// convert fp32 to fp8 with stochastic rounding // convert fp32 to fp8 with stochastic rounding
template <> template <>
inline __host__ __device__ f8_t f8_convert_sr<f8_t, float>(float x) inline __host__ __device__ f8_t f8_convert_sr<f8_t, float>(float x)
...@@ -365,9 +360,7 @@ inline __host__ __device__ f8_t f8_convert_sr<f8_t, half_t>(half_t x) ...@@ -365,9 +360,7 @@ inline __host__ __device__ f8_t f8_convert_sr<f8_t, half_t>(half_t x)
return f8_convert_sr<f8_t>(type_convert<float>(x)); return f8_convert_sr<f8_t>(type_convert<float>(x));
#endif #endif
} }
#endif
#if defined CK_ENABLE_BF8
// convert fp32 to bf8 with stochastic rounding // convert fp32 to bf8 with stochastic rounding
template <> template <>
inline __host__ __device__ bf8_t f8_convert_sr<bf8_t, float>(float x) inline __host__ __device__ bf8_t f8_convert_sr<bf8_t, float>(float x)
...@@ -417,6 +410,5 @@ inline __host__ __device__ bf8_t f8_convert_sr<bf8_t, half_t>(half_t x) ...@@ -417,6 +410,5 @@ inline __host__ __device__ bf8_t f8_convert_sr<bf8_t, half_t>(half_t x)
return f8_convert_sr<bf8_t>(type_convert<float>(x)); return f8_convert_sr<bf8_t>(type_convert<float>(x));
#endif #endif
} }
#endif
} // namespace ck } // namespace ck
library/include/ck/library/reference_tensor_operation/cpu/reference_conv_fwd.hpp
View file @ c5138aa1
...@@ -128,11 +128,9 @@ struct ReferenceConvFwd : public device::BaseOperator ...@@ -128,11 +128,9 @@ struct ReferenceConvFwd : public device::BaseOperator
} }
} }
float v_out; OutDataType v_out;
arg.out_element_op_(v_out, ck::type_convert<OutDataType>(v_acc));
arg.out_element_op_(v_out, v_acc); arg.output_(g, n, k, wo) = v_out;
arg.output_(g, n, k, wo) = ck::type_convert<OutDataType>(v_out);
}; };
make_ParallelTensorFunctor(func, make_ParallelTensorFunctor(func,
...@@ -184,11 +182,9 @@ struct ReferenceConvFwd : public device::BaseOperator ...@@ -184,11 +182,9 @@ struct ReferenceConvFwd : public device::BaseOperator
} }
} }
float v_out; OutDataType v_out;
arg.out_element_op_(v_out, ck::type_convert<OutDataType>(v_acc));
arg.out_element_op_(v_out, v_acc); arg.output_(g, n, k, ho, wo) = v_out;
arg.output_(g, n, k, ho, wo) = ck::type_convert<OutDataType>(v_out);
}; };
make_ParallelTensorFunctor(func, make_ParallelTensorFunctor(func,
...@@ -253,11 +249,9 @@ struct ReferenceConvFwd : public device::BaseOperator ...@@ -253,11 +249,9 @@ struct ReferenceConvFwd : public device::BaseOperator
} }
} }
float v_out; OutDataType v_out;
arg.out_element_op_(v_out, ck::type_convert<OutDataType>(v_acc));
arg.out_element_op_(v_out, v_acc); arg.output_(g, n, k, d_o, ho, wo) = v_out;
arg.output_(g, n, k, d_o, ho, wo) = ck::type_convert<OutDataType>(v_out);
}; };
make_ParallelTensorFunctor(func, make_ParallelTensorFunctor(func,
......
library/include/ck/library/reference_tensor_operation/cpu/reference_groupnorm.hpp
View file @ c5138aa1
...@@ -20,8 +20,9 @@ template <typename XDataType, ...@@ -20,8 +20,9 @@ template <typename XDataType,
typename GammaDataType, typename GammaDataType,
typename BetaDataType, typename BetaDataType,
typename YDataType, typename YDataType,
typename AccDataType, typename SaveMeanInvStdDataType,
typename AccElementwiseOperation> typename ComputeDataType,
typename YElementwiseOperation>
struct ReferenceGroupnorm : public device::BaseOperator struct ReferenceGroupnorm : public device::BaseOperator
{ {
// x = [N, H, W, G, C] // x = [N, H, W, G, C]
...@@ -35,14 +36,18 @@ struct ReferenceGroupnorm : public device::BaseOperator ...@@ -35,14 +36,18 @@ struct ReferenceGroupnorm : public device::BaseOperator
const Tensor<GammaDataType>& gamma, const Tensor<GammaDataType>& gamma,
const Tensor<BetaDataType>& beta, const Tensor<BetaDataType>& beta,
Tensor<YDataType>& y, Tensor<YDataType>& y,
AccElementwiseOperation acc_elementwise_op, Tensor<SaveMeanInvStdDataType>& save_mean,
Tensor<SaveMeanInvStdDataType>& save_inv_std,
YElementwiseOperation y_elementwise_op,
const std::vector<index_t> lengths, const std::vector<index_t> lengths,
AccDataType epsilon) ComputeDataType epsilon)
: x_(x), : x_(x),
gamma_(gamma), gamma_(gamma),
beta_(beta), beta_(beta),
y_(y), y_(y),
acc_elementwise_op_(acc_elementwise_op), save_mean_(save_mean),
save_inv_std_(save_inv_std),
y_elementwise_op_(y_elementwise_op),
lengths_(lengths), lengths_(lengths),
epsilon_(epsilon) epsilon_(epsilon)
{ {
...@@ -52,9 +57,11 @@ struct ReferenceGroupnorm : public device::BaseOperator ...@@ -52,9 +57,11 @@ struct ReferenceGroupnorm : public device::BaseOperator
const Tensor<XDataType> gamma_; const Tensor<XDataType> gamma_;
const Tensor<XDataType> beta_; const Tensor<XDataType> beta_;
Tensor<YDataType>& y_; Tensor<YDataType>& y_;
AccElementwiseOperation acc_elementwise_op_; Tensor<SaveMeanInvStdDataType>& save_mean_;
Tensor<SaveMeanInvStdDataType>& save_inv_std_;
YElementwiseOperation y_elementwise_op_;
std::vector<index_t> lengths_; std::vector<index_t> lengths_;
AccDataType epsilon_; ComputeDataType epsilon_;
}; };
// Invoker // Invoker
...@@ -68,8 +75,8 @@ struct ReferenceGroupnorm : public device::BaseOperator ...@@ -68,8 +75,8 @@ struct ReferenceGroupnorm : public device::BaseOperator
int G = arg.lengths_[3]; int G = arg.lengths_[3];
int C = arg.lengths_[4]; int C = arg.lengths_[4];
Tensor<AccDataType> mean({N, G}); Tensor<ComputeDataType> mean({N, G});
Tensor<AccDataType> var({N, G}); Tensor<ComputeDataType> var({N, G});
// Compute mean & var in [H, W, C] by Welford Algorithm // Compute mean & var in [H, W, C] by Welford Algorithm
// TODO - parallel for each HWC // TODO - parallel for each HWC
...@@ -78,9 +85,9 @@ struct ReferenceGroupnorm : public device::BaseOperator ...@@ -78,9 +85,9 @@ struct ReferenceGroupnorm : public device::BaseOperator
{ {
for(int g = 0; g < G; ++g) for(int g = 0; g < G; ++g)
{ {
AccDataType mean_val = type_convert<AccDataType>(0.0f); ComputeDataType mean_val = type_convert<ComputeDataType>(0.0f);
AccDataType var_val = type_convert<AccDataType>(0.0f); ComputeDataType var_val = type_convert<ComputeDataType>(0.0f);
int32_t curr_count = 0; int32_t curr_count = 0;
for(int h = 0; h < H; ++h) for(int h = 0; h < H; ++h)
{ {
...@@ -89,10 +96,11 @@ struct ReferenceGroupnorm : public device::BaseOperator ...@@ -89,10 +96,11 @@ struct ReferenceGroupnorm : public device::BaseOperator
for(int c = 0; c < C; ++c) for(int c = 0; c < C; ++c)
{ {
curr_count++; curr_count++;
AccDataType x = type_convert<AccDataType>(arg.x_(n, h, w, g, c)); ComputeDataType x =
AccDataType delta = x - mean_val; type_convert<ComputeDataType>(arg.x_(n, h, w, g, c));
ComputeDataType delta = x - mean_val;
mean_val += delta / curr_count; mean_val += delta / curr_count;
AccDataType delta2 = x - mean_val; ComputeDataType delta2 = x - mean_val;
var_val += delta * delta2; var_val += delta * delta2;
} }
} }
...@@ -100,6 +108,12 @@ struct ReferenceGroupnorm : public device::BaseOperator ...@@ -100,6 +108,12 @@ struct ReferenceGroupnorm : public device::BaseOperator
mean(n, g) = mean_val; mean(n, g) = mean_val;
var(n, g) = var_val / curr_count; var(n, g) = var_val / curr_count;
arg.save_mean_(n, g) = ck::type_convert<SaveMeanInvStdDataType>(mean(n, g));
ComputeDataType divisor =
static_cast<ComputeDataType>(1) / ck::math::sqrt(var(n, g) + arg.epsilon_);
arg.save_inv_std_(n, g) = ck::type_convert<SaveMeanInvStdDataType>(divisor);
} }
} }
...@@ -114,15 +128,19 @@ struct ReferenceGroupnorm : public device::BaseOperator ...@@ -114,15 +128,19 @@ struct ReferenceGroupnorm : public device::BaseOperator
{ {
for(int c = 0; c < C; ++c) for(int c = 0; c < C; ++c)
{ {
AccDataType x = type_convert<AccDataType>(arg.x_(n, h, w, g, c)); ComputeDataType x =
AccDataType gamma = type_convert<AccDataType>(arg.gamma_(g, c)); type_convert<ComputeDataType>(arg.x_(n, h, w, g, c));
AccDataType beta = type_convert<AccDataType>(arg.beta_(g, c)); ComputeDataType gamma =
AccDataType mean_val = type_convert<AccDataType>(mean(n, g)); type_convert<ComputeDataType>(arg.gamma_(g, c));
AccDataType var_val = type_convert<AccDataType>(var(n, g)); ComputeDataType beta =
AccDataType y = gamma * (x - mean_val) / type_convert<ComputeDataType>(arg.beta_(g, c));
ck::math::sqrt(arg.epsilon_ + var_val) + ComputeDataType mean_val =
beta; type_convert<ComputeDataType>(mean(n, g));
arg.acc_elementwise_op_(y, y); ComputeDataType var_val = type_convert<ComputeDataType>(var(n, g));
ComputeDataType y = gamma * (x - mean_val) /
ck::math::sqrt(arg.epsilon_ + var_val) +
beta;
arg.y_elementwise_op_(y, y);
arg.y_(n, h, w, g, c) = type_convert<YDataType>(y); arg.y_(n, h, w, g, c) = type_convert<YDataType>(y);
} }
} }
...@@ -159,11 +177,14 @@ struct ReferenceGroupnorm : public device::BaseOperator ...@@ -159,11 +177,14 @@ struct ReferenceGroupnorm : public device::BaseOperator
const Tensor<GammaDataType>& gamma, const Tensor<GammaDataType>& gamma,
const Tensor<BetaDataType>& beta, const Tensor<BetaDataType>& beta,
Tensor<YDataType>& y, Tensor<YDataType>& y,
AccElementwiseOperation acc_elementwise_op, Tensor<SaveMeanInvStdDataType>& save_mean,
Tensor<SaveMeanInvStdDataType>& save_inv_std,
YElementwiseOperation y_elementwise_op,
const std::vector<index_t> lengths, const std::vector<index_t> lengths,
AccDataType epsilon) ComputeDataType epsilon)
{ {
return Argument{x, gamma, beta, y, acc_elementwise_op, lengths, epsilon}; return Argument{
x, gamma, beta, y, save_mean, save_inv_std, y_elementwise_op, lengths, epsilon};
} }
static auto MakeInvoker() { return Invoker{}; } static auto MakeInvoker() { return Invoker{}; }
......
library/include/ck/library/reference_tensor_operation/cpu/reference_layernorm.hpp
View file @ c5138aa1
...@@ -20,8 +20,9 @@ template <typename XDataType, ...@@ -20,8 +20,9 @@ template <typename XDataType,
typename GammaDataType, typename GammaDataType,
typename BetaDataType, typename BetaDataType,
typename YDataType, typename YDataType,
typename AccDataType, typename SaveMeanInvStdDataType,
typename AccElementwiseOperation, typename ComputeDataType,
typename YElementwiseOperation,
index_t Rank, index_t Rank,
index_t NumReduceDim> index_t NumReduceDim>
struct ReferenceLayernorm : public device::BaseOperator struct ReferenceLayernorm : public device::BaseOperator
...@@ -36,15 +37,19 @@ struct ReferenceLayernorm : public device::BaseOperator ...@@ -36,15 +37,19 @@ struct ReferenceLayernorm : public device::BaseOperator
const Tensor<GammaDataType>& gamma_n, const Tensor<GammaDataType>& gamma_n,
const Tensor<BetaDataType>& beta_n, const Tensor<BetaDataType>& beta_n,
Tensor<YDataType>& y_m_n, Tensor<YDataType>& y_m_n,
AccElementwiseOperation acc_elementwise_op, Tensor<SaveMeanInvStdDataType>& save_mean_m,
Tensor<SaveMeanInvStdDataType>& save_inv_std_m,
YElementwiseOperation y_elementwise_op,
const std::vector<index_t> lengths, const std::vector<index_t> lengths,
const std::vector<index_t> reduceDims, const std::vector<index_t> reduceDims,
AccDataType epsilon) ComputeDataType epsilon)
: x_m_n_(x_m_n), : x_m_n_(x_m_n),
gamma_n_(gamma_n), gamma_n_(gamma_n),
beta_n_(beta_n), beta_n_(beta_n),
y_m_n_(y_m_n), y_m_n_(y_m_n),
acc_elementwise_op_(acc_elementwise_op), save_mean_m_(save_mean_m),
save_inv_std_m_(save_inv_std_m),
y_elementwise_op_(y_elementwise_op),
lengths_(lengths), lengths_(lengths),
reduceDims_(reduceDims), reduceDims_(reduceDims),
epsilon_(epsilon) epsilon_(epsilon)
...@@ -55,10 +60,12 @@ struct ReferenceLayernorm : public device::BaseOperator ...@@ -55,10 +60,12 @@ struct ReferenceLayernorm : public device::BaseOperator
const Tensor<XDataType> gamma_n_; const Tensor<XDataType> gamma_n_;
const Tensor<XDataType> beta_n_; const Tensor<XDataType> beta_n_;
Tensor<YDataType>& y_m_n_; Tensor<YDataType>& y_m_n_;
AccElementwiseOperation acc_elementwise_op_; Tensor<SaveMeanInvStdDataType>& save_mean_m_;
Tensor<SaveMeanInvStdDataType>& save_inv_std_m_;
YElementwiseOperation y_elementwise_op_;
std::vector<index_t> lengths_; std::vector<index_t> lengths_;
std::vector<index_t> reduceDims_; std::vector<index_t> reduceDims_;
AccDataType epsilon_; ComputeDataType epsilon_;
}; };
// Invoker // Invoker
...@@ -69,8 +76,8 @@ struct ReferenceLayernorm : public device::BaseOperator ...@@ -69,8 +76,8 @@ struct ReferenceLayernorm : public device::BaseOperator
int M = arg.lengths_[0]; int M = arg.lengths_[0];
int N = arg.lengths_[1]; int N = arg.lengths_[1];
Tensor<AccDataType> mean({M}); Tensor<ComputeDataType> mean({M});
Tensor<AccDataType> var({M}); Tensor<ComputeDataType> var({M});
for(int m = 0; m < M; ++m) for(int m = 0; m < M; ++m)
{ {
...@@ -79,7 +86,7 @@ struct ReferenceLayernorm : public device::BaseOperator ...@@ -79,7 +86,7 @@ struct ReferenceLayernorm : public device::BaseOperator
for(int n = 0; n < N; ++n) for(int n = 0; n < N; ++n)
{ {
auto x_val = ck::type_convert<AccDataType>(arg.x_m_n_(m, n)); auto x_val = ck::type_convert<ComputeDataType>(arg.x_m_n_(m, n));
mean(m) += x_val; mean(m) += x_val;
var(m) += x_val * x_val; var(m) += x_val * x_val;
} }
...@@ -90,17 +97,21 @@ struct ReferenceLayernorm : public device::BaseOperator ...@@ -90,17 +97,21 @@ struct ReferenceLayernorm : public device::BaseOperator
for(int m = 0; m < M; ++m) for(int m = 0; m < M; ++m)
{ {
AccDataType divisor = ComputeDataType divisor =
static_cast<AccDataType>(1) / ck::math::sqrt(var(m) + arg.epsilon_); static_cast<ComputeDataType>(1) / ck::math::sqrt(var(m) + arg.epsilon_);
for(int n = 0; n < N; ++n) for(int n = 0; n < N; ++n)
{ {
auto x_val = ck::type_convert<AccDataType>(arg.x_m_n_(m, n)); auto x_val = ck::type_convert<ComputeDataType>(arg.x_m_n_(m, n));
auto y_val = (x_val - mean(m)) * divisor; auto gamma_val = ck::type_convert<ComputeDataType>(arg.gamma_n_(n));
y_val = (y_val * arg.gamma_n_(n)) + arg.beta_n_(n); auto beta_val = ck::type_convert<ComputeDataType>(arg.beta_n_(n));
arg.acc_elementwise_op_(y_val, y_val); auto y_val = (x_val - mean(m)) * divisor;
y_val = (y_val * gamma_val) + beta_val;
arg.y_elementwise_op_(y_val, y_val);
arg.y_m_n_(m, n) = ck::type_convert<YDataType>(y_val); arg.y_m_n_(m, n) = ck::type_convert<YDataType>(y_val);
} }
arg.save_mean_m_(m) = ck::type_convert<SaveMeanInvStdDataType>(mean(m));
arg.save_inv_std_m_(m) = ck::type_convert<SaveMeanInvStdDataType>(divisor);
} }
return 0; return 0;
...@@ -140,13 +151,23 @@ struct ReferenceLayernorm : public device::BaseOperator ...@@ -140,13 +151,23 @@ struct ReferenceLayernorm : public device::BaseOperator
const Tensor<GammaDataType>& gamma_n, const Tensor<GammaDataType>& gamma_n,
const Tensor<BetaDataType>& beta_n, const Tensor<BetaDataType>& beta_n,
Tensor<YDataType>& y_m_n, Tensor<YDataType>& y_m_n,
AccElementwiseOperation acc_elementwise_op, Tensor<SaveMeanInvStdDataType>& save_mean_m,
Tensor<SaveMeanInvStdDataType>& save_inv_std_m,
YElementwiseOperation y_elementwise_op,
const std::vector<index_t> lengths, const std::vector<index_t> lengths,
const std::vector<index_t> reduceDims, const std::vector<index_t> reduceDims,
AccDataType epsilon) ComputeDataType epsilon)
{ {
return Argument{ return Argument{x_m_n,
x_m_n, gamma_n, beta_n, y_m_n, acc_elementwise_op, lengths, reduceDims, epsilon}; gamma_n,
beta_n,
y_m_n,
save_mean_m,
save_inv_std_m,
y_elementwise_op,
lengths,
reduceDims,
epsilon};
} }
static auto MakeInvoker() { return Invoker{}; } static auto MakeInvoker() { return Invoker{}; }
......
library/include/ck/library/tensor_operation_instance/device_operation_instance_factory.hpp
View file @ c5138aa1
...@@ -20,12 +20,8 @@ using F16 = ck::half_t; ...@@ -20,12 +20,8 @@ using F16 = ck::half_t;
using BF16 = ck::bhalf_t; using BF16 = ck::bhalf_t;
using I8 = int8_t; using I8 = int8_t;
using I32 = int32_t; using I32 = int32_t;
#if defined CK_ENABLE_FP8 using F8 = ck::f8_t;
using F8 = ck::f8_t; using BF8 = ck::bf8_t;
#endif
#if defined CK_ENABLE_BF8
using BF8 = ck::bf8_t;
#endif
using Empty_Tuple = ck::Tuple<>; using Empty_Tuple = ck::Tuple<>;
......
library/include/ck/library/tensor_operation_instance/gpu/convolution_backward_data.hpp
View file @ c5138aa1
...@@ -240,11 +240,13 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceConvBw ...@@ -240,11 +240,13 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceConvBw
if constexpr(NumDimSpatial == 1 && is_same_v<InLayout, NWC> && is_same_v<WeiLayout, KXC> && if constexpr(NumDimSpatial == 1 && is_same_v<InLayout, NWC> && is_same_v<WeiLayout, KXC> &&
is_same_v<OutLayout, NWK>) is_same_v<OutLayout, NWK>)
{ {
#ifdef CK_ENABLE_FP32
if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> && if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> &&
is_same_v<OutDataType, float>) is_same_v<OutDataType, float>)
{ {
add_device_conv1d_bwd_data_xdl_nwc_kxc_nwk_f32_instances(op_ptrs); add_device_conv1d_bwd_data_xdl_nwc_kxc_nwk_f32_instances(op_ptrs);
} }
#endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>) is_same_v<OutDataType, half_t>)
...@@ -267,17 +269,23 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceConvBw ...@@ -267,17 +269,23 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceConvBw
} }
#endif #endif
} }
else if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, NHWC> && if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, NHWC> &&
is_same_v<WeiLayout, KYXC> && is_same_v<OutLayout, NHWK>) is_same_v<WeiLayout, KYXC> && is_same_v<OutLayout, NHWK>)
{ {
#ifdef CK_ENABLE_FP32
if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> && if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> &&
is_same_v<OutDataType, float>) is_same_v<OutDataType, float>)
{ {
add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f32_instances(op_ptrs); add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f32_instances(op_ptrs);
#ifdef DL_KERNELS }
add_device_conv2d_bwd_data_dl_nhwc_kyxc_nhwk_f32_instances(op_ptrs);
#endif #endif
#if defined(DL_KERNELS) && defined(CK_ENABLE_FP32)
if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> &&
is_same_v<OutDataType, float>)
{
add_device_conv2d_bwd_data_dl_nhwc_kyxc_nhwk_f32_instances(op_ptrs);
} }
#endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>) is_same_v<OutDataType, half_t>)
...@@ -306,14 +314,16 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceConvBw ...@@ -306,14 +314,16 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceConvBw
} }
#endif #endif
} }
else if constexpr(NumDimSpatial == 3 && is_same_v<InLayout, NDHWC> && if constexpr(NumDimSpatial == 3 && is_same_v<InLayout, NDHWC> &&
is_same_v<WeiLayout, KZYXC> && is_same_v<OutLayout, NDHWK>) is_same_v<WeiLayout, KZYXC> && is_same_v<OutLayout, NDHWK>)
{ {
#ifdef CK_ENABLE_FP32
if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> && if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> &&
is_same_v<OutDataType, float>) is_same_v<OutDataType, float>)
{ {
add_device_conv3d_bwd_data_xdl_ndhwc_kzyxc_ndhwk_f32_instances(op_ptrs); add_device_conv3d_bwd_data_xdl_ndhwc_kzyxc_ndhwk_f32_instances(op_ptrs);
} }
#endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>) is_same_v<OutDataType, half_t>)
......
library/include/ck/library/tensor_operation_instance/gpu/convolution_forward.hpp
View file @ c5138aa1
...@@ -98,30 +98,31 @@ struct DeviceOperationInstanceFactory< ...@@ -98,30 +98,31 @@ struct DeviceOperationInstanceFactory<
if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, NHWC> && if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, NHWC> &&
is_same_v<WeiLayout, KYXC> && is_same_v<OutLayout, NHWK>) is_same_v<WeiLayout, KYXC> && is_same_v<OutLayout, NHWK>)
{ {
#ifdef CK_ENABLE_FP32
if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> && if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> &&
is_same_v<OutDataType, float>) is_same_v<OutDataType, float>)
{ {
add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_f32_instances(op_ptrs); add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_f32_instances(op_ptrs);
} }
#endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>) is_same_v<OutDataType, half_t>)
{ {
add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_f16_instances(op_ptrs); add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_f16_instances(op_ptrs);
add_device_conv2d_fwd_xdl_c_shuffle_nhwc_kyxc_nhwk_f16_instances(op_ptrs); add_device_conv2d_fwd_xdl_c_shuffle_nhwc_kyxc_nhwk_f16_instances(op_ptrs);
} }
#endif #endif
#ifdef CK_ENABLE_BF16 #ifdef CK_ENABLE_BF16
else if constexpr(is_same_v<InDataType, ck::bhalf_t> && if constexpr(is_same_v<InDataType, ck::bhalf_t> &&
is_same_v<WeiDataType, ck::bhalf_t> && is_same_v<WeiDataType, ck::bhalf_t> && is_same_v<OutDataType, ck::bhalf_t>)
is_same_v<OutDataType, ck::bhalf_t>)
{ {
add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_bf16_instances(op_ptrs); add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_bf16_instances(op_ptrs);
} }
#endif #endif
#ifdef CK_ENABLE_INT8 #ifdef CK_ENABLE_INT8
else if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> && if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> &&
is_same_v<OutDataType, int8_t>) is_same_v<OutDataType, int8_t>)
{ {
add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_int8_instances(op_ptrs); add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_int8_instances(op_ptrs);
} }
......
library/include/ck/library/tensor_operation_instance/gpu/gemm_splitk.hpp
View file @ c5138aa1
...@@ -155,7 +155,7 @@ struct DeviceOperationInstanceFactory< ...@@ -155,7 +155,7 @@ struct DeviceOperationInstanceFactory<
std::vector<std::unique_ptr<DeviceOp>> op_ptrs; std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
#ifdef CK_ENABLE_FP32 #ifdef CK_ENABLE_FP32
if constexpr(is_same_v<ADataType, float> && is_same_v<BDataType, float> && if constexpr(is_same_v<ADataType, float> && is_same_v<BDataType, float> &&
is_same_v<CDataType, float>) is_same_v<CDataType, float> && is_same_v<ComputeType, float>)
{ {
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> && if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
is_same_v<CLayout, Row>) is_same_v<CLayout, Row>)
...@@ -180,8 +180,8 @@ struct DeviceOperationInstanceFactory< ...@@ -180,8 +180,8 @@ struct DeviceOperationInstanceFactory<
} }
#endif #endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
else if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> && if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
is_same_v<CDataType, half_t> && is_same_v<ComputeType, half_t>) is_same_v<CDataType, half_t> && is_same_v<ComputeType, half_t>)
{ {
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> && if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
is_same_v<CLayout, Row>) is_same_v<CLayout, Row>)
...@@ -206,8 +206,8 @@ struct DeviceOperationInstanceFactory< ...@@ -206,8 +206,8 @@ struct DeviceOperationInstanceFactory<
} }
#endif #endif
#if(defined(CK_ENABLE_FP16) || defined(CK_ENABLE_FP8)) #if(defined(CK_ENABLE_FP16) || defined(CK_ENABLE_FP8))
else if constexpr(is_same_v<ADataType, f8_t> && is_same_v<BDataType, half_t> && if constexpr(is_same_v<ADataType, f8_t> && is_same_v<BDataType, half_t> &&
is_same_v<CDataType, half_t>) is_same_v<CDataType, half_t> && is_same_v<ComputeType, half_t>)
{ {
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> && if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
is_same_v<CLayout, Row>) is_same_v<CLayout, Row>)
...@@ -230,8 +230,8 @@ struct DeviceOperationInstanceFactory< ...@@ -230,8 +230,8 @@ struct DeviceOperationInstanceFactory<
add_device_gemm_xdl_splitk_f8_f16_f16_km_nk_mn_instances(op_ptrs); add_device_gemm_xdl_splitk_f8_f16_f16_km_nk_mn_instances(op_ptrs);
} }
} }
else if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, f8_t> && if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, f8_t> &&
is_same_v<CDataType, half_t>) is_same_v<CDataType, half_t> && is_same_v<ComputeType, half_t>)
{ {
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> && if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
is_same_v<CLayout, Row>) is_same_v<CLayout, Row>)
......
library/include/ck/library/tensor_operation_instance/gpu/grouped_convolution_backward_weight.hpp
View file @ c5138aa1
...@@ -627,8 +627,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -627,8 +627,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>) is_same_v<OutDataType, half_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv1d_bwd_weight_dl_gnwc_gkxc_gnwk_f16_instances(op_ptrs); add_device_grouped_conv1d_bwd_weight_dl_gnwc_gkxc_gnwk_f16_instances(op_ptrs);
...@@ -637,9 +637,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -637,9 +637,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_BF16 #ifdef CK_ENABLE_BF16
else if constexpr(is_same_v<InDataType, ck::bhalf_t> && if constexpr(is_same_v<InDataType, ck::bhalf_t> && is_same_v<WeiDataType, float> &&
is_same_v<WeiDataType, float> && is_same_v<OutDataType, ck::bhalf_t>)
is_same_v<OutDataType, ck::bhalf_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv1d_bwd_weight_dl_gnwc_gkxc_gnwk_bf16_f32_bf16_instances( add_device_grouped_conv1d_bwd_weight_dl_gnwc_gkxc_gnwk_bf16_f32_bf16_instances(
...@@ -650,8 +649,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -650,8 +649,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
} }
else if constexpr(is_same_v<InLayout, NWGC> && is_same_v<WeiLayout, GKXC> && if constexpr(is_same_v<InLayout, NWGC> && is_same_v<WeiLayout, GKXC> &&
is_same_v<OutLayout, NWGK>) is_same_v<OutLayout, NWGK>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
#ifdef CK_ENABLE_FP32 #ifdef CK_ENABLE_FP32
...@@ -662,16 +661,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -662,16 +661,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>) is_same_v<OutDataType, half_t>)
{ {
add_device_grouped_conv1d_bwd_weight_dl_nwgc_gkxc_nwgk_f16_instances(op_ptrs); add_device_grouped_conv1d_bwd_weight_dl_nwgc_gkxc_nwgk_f16_instances(op_ptrs);
} }
#endif #endif
#ifdef CK_ENABLE_BF16 #ifdef CK_ENABLE_BF16
else if constexpr(is_same_v<InDataType, ck::bhalf_t> && if constexpr(is_same_v<InDataType, ck::bhalf_t> && is_same_v<WeiDataType, float> &&
is_same_v<WeiDataType, float> && is_same_v<OutDataType, ck::bhalf_t>)
is_same_v<OutDataType, ck::bhalf_t>)
{ {
add_device_grouped_conv1d_bwd_weight_dl_nwgc_gkxc_nwgk_bf16_f32_bf16_instances( add_device_grouped_conv1d_bwd_weight_dl_nwgc_gkxc_nwgk_bf16_f32_bf16_instances(
op_ptrs); op_ptrs);
...@@ -680,7 +678,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -680,7 +678,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
#endif #endif
} }
} }
else if constexpr(NumDimSpatial == 2) if constexpr(NumDimSpatial == 2)
{ {
if constexpr(is_same_v<InLayout, GNHWC> && is_same_v<WeiLayout, GKYXC> && if constexpr(is_same_v<InLayout, GNHWC> && is_same_v<WeiLayout, GKYXC> &&
is_same_v<OutLayout, GNHWK>) is_same_v<OutLayout, GNHWK>)
...@@ -698,8 +696,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -698,8 +696,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>) is_same_v<OutDataType, half_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv2d_bwd_weight_dl_gnhwc_gkyxc_gnhwk_f16_instances( add_device_grouped_conv2d_bwd_weight_dl_gnhwc_gkyxc_gnhwk_f16_instances(
...@@ -710,9 +708,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -710,9 +708,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_BF16 #ifdef CK_ENABLE_BF16
else if constexpr(is_same_v<InDataType, ck::bhalf_t> && if constexpr(is_same_v<InDataType, ck::bhalf_t> && is_same_v<WeiDataType, float> &&
is_same_v<WeiDataType, float> && is_same_v<OutDataType, ck::bhalf_t>)
is_same_v<OutDataType, ck::bhalf_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv2d_bwd_weight_dl_gnhwc_gkyxc_gnhwk_bf16_f32_bf16_instances( add_device_grouped_conv2d_bwd_weight_dl_gnhwc_gkyxc_gnhwk_bf16_f32_bf16_instances(
...@@ -723,8 +720,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -723,8 +720,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
} }
else if constexpr(is_same_v<InLayout, NHWGC> && is_same_v<WeiLayout, GKYXC> && if constexpr(is_same_v<InLayout, NHWGC> && is_same_v<WeiLayout, GKYXC> &&
is_same_v<OutLayout, NHWGK>) is_same_v<OutLayout, NHWGK>)
{ {
#ifdef CK_ENABLE_FP32 #ifdef CK_ENABLE_FP32
if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> && if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> &&
...@@ -739,8 +736,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -739,8 +736,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>) is_same_v<OutDataType, half_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv2d_bwd_weight_dl_nhwgc_gkyxc_nhwgk_f16_instances( add_device_grouped_conv2d_bwd_weight_dl_nhwgc_gkyxc_nhwgk_f16_instances(
...@@ -751,9 +748,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -751,9 +748,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_BF16 #ifdef CK_ENABLE_BF16
else if constexpr(is_same_v<InDataType, ck::bhalf_t> && if constexpr(is_same_v<InDataType, ck::bhalf_t> && is_same_v<WeiDataType, float> &&
is_same_v<WeiDataType, float> && is_same_v<OutDataType, ck::bhalf_t>)
is_same_v<OutDataType, ck::bhalf_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv2d_bwd_weight_dl_nhwgc_gkyxc_nhwgk_bf16_f32_bf16_instances( add_device_grouped_conv2d_bwd_weight_dl_nhwgc_gkyxc_nhwgk_bf16_f32_bf16_instances(
...@@ -765,7 +761,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -765,7 +761,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
#endif #endif
} }
} }
else if constexpr(NumDimSpatial == 3) if constexpr(NumDimSpatial == 3)
{ {
if constexpr(is_same_v<InLayout, GNDHWC> && is_same_v<WeiLayout, GKZYXC> && if constexpr(is_same_v<InLayout, GNDHWC> && is_same_v<WeiLayout, GKZYXC> &&
is_same_v<OutLayout, GNDHWK>) is_same_v<OutLayout, GNDHWK>)
...@@ -783,8 +779,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -783,8 +779,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>) is_same_v<OutDataType, half_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv3d_bwd_weight_dl_gndhwc_gkzyxc_gndhwk_f16_instances( add_device_grouped_conv3d_bwd_weight_dl_gndhwc_gkzyxc_gndhwk_f16_instances(
...@@ -799,9 +795,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -799,9 +795,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_BF16 #ifdef CK_ENABLE_BF16
else if constexpr(is_same_v<InDataType, ck::bhalf_t> && if constexpr(is_same_v<InDataType, ck::bhalf_t> && is_same_v<WeiDataType, float> &&
is_same_v<WeiDataType, float> && is_same_v<OutDataType, ck::bhalf_t>)
is_same_v<OutDataType, ck::bhalf_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv3d_bwd_weight_dl_gndhwc_gkzyxc_gndhwk_bf16_f32_bf16_instances( add_device_grouped_conv3d_bwd_weight_dl_gndhwc_gkzyxc_gndhwk_bf16_f32_bf16_instances(
...@@ -822,8 +817,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -822,8 +817,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
} }
else if constexpr(is_same_v<InLayout, NDHWGC> && is_same_v<WeiLayout, GKZYXC> && if constexpr(is_same_v<InLayout, NDHWGC> && is_same_v<WeiLayout, GKZYXC> &&
is_same_v<OutLayout, NDHWGK>) is_same_v<OutLayout, NDHWGK>)
{ {
#ifdef CK_ENABLE_FP32 #ifdef CK_ENABLE_FP32
if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> && if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> &&
...@@ -838,10 +833,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -838,10 +833,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t> && is_same_v<OutDataType, half_t> && is_same_v<ComputeTypeA, half_t> &&
is_same_v<ComputeTypeA, half_t> && is_same_v<ComputeTypeB, half_t>)
is_same_v<ComputeTypeB, half_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv3d_bwd_weight_dl_ndhwgc_gkzyxc_ndhwgk_f16_instances( add_device_grouped_conv3d_bwd_weight_dl_ndhwgc_gkzyxc_ndhwgk_f16_instances(
...@@ -856,9 +850,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -856,9 +850,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_BF16 #ifdef CK_ENABLE_BF16
else if constexpr(is_same_v<InDataType, ck::bhalf_t> && if constexpr(is_same_v<InDataType, ck::bhalf_t> && is_same_v<WeiDataType, float> &&
is_same_v<WeiDataType, float> && is_same_v<OutDataType, ck::bhalf_t>)
is_same_v<OutDataType, ck::bhalf_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv3d_bwd_weight_dl_ndhwgc_gkzyxc_ndhwgk_bf16_f32_bf16_instances( add_device_grouped_conv3d_bwd_weight_dl_ndhwgc_gkzyxc_ndhwgk_bf16_f32_bf16_instances(
...@@ -879,9 +872,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -879,9 +872,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#if defined CK_ENABLE_FP16 && defined CK_ENABLE_FP8 && defined CK_ENABLE_BF8 #if defined CK_ENABLE_FP16 && defined CK_ENABLE_FP8 && defined CK_ENABLE_BF8
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t> && is_same_v<OutDataType, half_t> && is_same_v<ComputeTypeA, bf8_t> &&
is_same_v<ComputeTypeA, bf8_t> && is_same_v<ComputeTypeB, f8_t>) is_same_v<ComputeTypeB, f8_t>)
{ {
add_device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_f16_comp_bf8_f8_instances( add_device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_f16_comp_bf8_f8_instances(
op_ptrs); op_ptrs);
......
library/include/ck/library/tensor_operation_instance/gpu/normalization.hpp
View file @ c5138aa1
...@@ -19,13 +19,13 @@ namespace instance { ...@@ -19,13 +19,13 @@ namespace instance {
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
// FP16 // FP16
void add_device_normalization_rank_2_1_f16_instances( void add_device_normalization_rank_2_1_f16_instances(
std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F32, F16, PassThrough, 2, 1>>>&); std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F16, F32, PassThrough, 2, 1>>>&);
void add_device_normalization_rank_4_3_f16_instances( void add_device_normalization_rank_4_3_f16_instances(
std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F32, F16, PassThrough, 4, 3>>>&); std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F16, F32, PassThrough, 4, 3>>>&);
void add_device_normalization_rank_5_3_f16_instances( void add_device_normalization_rank_5_3_f16_instances(
std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F32, F16, PassThrough, 5, 3>>>&); std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F16, F32, PassThrough, 5, 3>>>&);
#endif #endif
#ifdef CK_ENABLE_FP32 #ifdef CK_ENABLE_FP32
// FP32 // FP32
...@@ -42,14 +42,15 @@ template <typename XDataType, ...@@ -42,14 +42,15 @@ template <typename XDataType,
typename GammaDataType, typename GammaDataType,
typename BetaDataType, typename BetaDataType,
typename YDataType, typename YDataType,
typename SaveMeanInvStdDataType,
index_t Rank, index_t Rank,
index_t NumReduceDim> index_t NumReduceDim>
struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceNormalization< struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceNormalization<
XDataType, XDataType,
GammaDataType, GammaDataType,
BetaDataType, BetaDataType,
F32,
YDataType, YDataType,
SaveMeanInvStdDataType,
ck::tensor_operation::element_wise::PassThrough, ck::tensor_operation::element_wise::PassThrough,
Rank, Rank,
NumReduceDim>> NumReduceDim>>
...@@ -57,8 +58,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceNormal ...@@ -57,8 +58,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceNormal
using DeviceOp = DeviceNormalization<XDataType, using DeviceOp = DeviceNormalization<XDataType,
GammaDataType, GammaDataType,
BetaDataType, BetaDataType,
F32,
YDataType, YDataType,
SaveMeanInvStdDataType,
ck::tensor_operation::element_wise::PassThrough, ck::tensor_operation::element_wise::PassThrough,
Rank, Rank,
NumReduceDim>; NumReduceDim>;
...@@ -68,7 +69,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceNormal ...@@ -68,7 +69,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceNormal
std::vector<std::unique_ptr<DeviceOp>> op_ptrs; std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
if constexpr(is_same_v<XDataType, F16> && is_same_v<GammaDataType, F16> && if constexpr(is_same_v<XDataType, F16> && is_same_v<GammaDataType, F16> &&
is_same_v<BetaDataType, F16> && is_same_v<YDataType, F16>) is_same_v<BetaDataType, F16> && is_same_v<YDataType, F16> &&
is_same_v<SaveMeanInvStdDataType, F32>)
{ {
if constexpr(Rank == 2 && NumReduceDim == 1) if constexpr(Rank == 2 && NumReduceDim == 1)
{ {
...@@ -86,7 +88,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceNormal ...@@ -86,7 +88,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceNormal
#endif #endif
#ifdef CK_ENABLE_FP32 #ifdef CK_ENABLE_FP32
if constexpr(is_same_v<XDataType, F32> && is_same_v<GammaDataType, F32> && if constexpr(is_same_v<XDataType, F32> && is_same_v<GammaDataType, F32> &&
is_same_v<BetaDataType, F32> && is_same_v<YDataType, F32>) is_same_v<BetaDataType, F32> && is_same_v<YDataType, F32> &&
is_same_v<SaveMeanInvStdDataType, F32>)
{ {
if constexpr(Rank == 2 && NumReduceDim == 1) if constexpr(Rank == 2 && NumReduceDim == 1)
{ {
......
library/include/ck/library/tensor_operation_instance/gpu/normalization_swish.hpp
View file @ c5138aa1
...@@ -19,7 +19,7 @@ namespace instance { ...@@ -19,7 +19,7 @@ namespace instance {
// FP16 // FP16
void add_device_normalization_rank_5_3_swish_f16_instances( void add_device_normalization_rank_5_3_swish_f16_instances(
std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F32, F16, Swish, 5, 3>>>&); std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F16, F32, Swish, 5, 3>>>&);
// FP32 // FP32
void add_device_normalization_rank_5_3_swish_f32_instances( void add_device_normalization_rank_5_3_swish_f32_instances(
...@@ -27,20 +27,21 @@ void add_device_normalization_rank_5_3_swish_f32_instances( ...@@ -27,20 +27,21 @@ void add_device_normalization_rank_5_3_swish_f32_instances(
// [x, gamma, beta, y] = [f16, f32, f32, f16] // [x, gamma, beta, y] = [f16, f32, f32, f16]
void add_device_normalization_rank_5_3_swish_f16_f32_f32_f16_instances( void add_device_normalization_rank_5_3_swish_f16_f32_f32_f16_instances(
std::vector<std::unique_ptr<DeviceNormalization<F16, F32, F32, F32, F16, Swish, 5, 3>>>&); std::vector<std::unique_ptr<DeviceNormalization<F16, F32, F32, F16, F32, Swish, 5, 3>>>&);
template <typename XDataType, template <typename XDataType,
typename GammaDataType, typename GammaDataType,
typename BetaDataType, typename BetaDataType,
typename YDataType, typename YDataType,
typename SaveMeanInvStdDataType,
index_t Rank, index_t Rank,
index_t NumReduceDim> index_t NumReduceDim>
struct DeviceOperationInstanceFactory< struct DeviceOperationInstanceFactory<
ck::tensor_operation::device::DeviceNormalization<XDataType, ck::tensor_operation::device::DeviceNormalization<XDataType,
GammaDataType, GammaDataType,
BetaDataType, BetaDataType,
F32,
YDataType, YDataType,
SaveMeanInvStdDataType,
ck::tensor_operation::element_wise::Swish, ck::tensor_operation::element_wise::Swish,
Rank, Rank,
NumReduceDim>> NumReduceDim>>
...@@ -48,8 +49,8 @@ struct DeviceOperationInstanceFactory< ...@@ -48,8 +49,8 @@ struct DeviceOperationInstanceFactory<
using DeviceOp = DeviceNormalization<XDataType, using DeviceOp = DeviceNormalization<XDataType,
GammaDataType, GammaDataType,
BetaDataType, BetaDataType,
F32,
YDataType, YDataType,
SaveMeanInvStdDataType,
ck::tensor_operation::element_wise::Swish, ck::tensor_operation::element_wise::Swish,
Rank, Rank,
NumReduceDim>; NumReduceDim>;
...@@ -59,7 +60,8 @@ struct DeviceOperationInstanceFactory< ...@@ -59,7 +60,8 @@ struct DeviceOperationInstanceFactory<
std::vector<std::unique_ptr<DeviceOp>> op_ptrs; std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
if constexpr(is_same_v<XDataType, F16> && is_same_v<GammaDataType, F16> && if constexpr(is_same_v<XDataType, F16> && is_same_v<GammaDataType, F16> &&
is_same_v<BetaDataType, F16> && is_same_v<YDataType, F16>) is_same_v<BetaDataType, F16> && is_same_v<YDataType, F16> &&
is_same_v<SaveMeanInvStdDataType, F32>)
{ {
if constexpr(Rank == 5 && NumReduceDim == 3) if constexpr(Rank == 5 && NumReduceDim == 3)
{ {
...@@ -67,7 +69,8 @@ struct DeviceOperationInstanceFactory< ...@@ -67,7 +69,8 @@ struct DeviceOperationInstanceFactory<
} }
} }
else if constexpr(is_same_v<XDataType, F32> && is_same_v<GammaDataType, F32> && else if constexpr(is_same_v<XDataType, F32> && is_same_v<GammaDataType, F32> &&
is_same_v<BetaDataType, F32> && is_same_v<YDataType, F32>) is_same_v<BetaDataType, F32> && is_same_v<YDataType, F32> &&
is_same_v<SaveMeanInvStdDataType, F32>)
{ {
if constexpr(Rank == 5 && NumReduceDim == 3) if constexpr(Rank == 5 && NumReduceDim == 3)
{ {
...@@ -75,7 +78,8 @@ struct DeviceOperationInstanceFactory< ...@@ -75,7 +78,8 @@ struct DeviceOperationInstanceFactory<
} }
} }
else if constexpr(is_same_v<XDataType, F16> && is_same_v<GammaDataType, F32> && else if constexpr(is_same_v<XDataType, F16> && is_same_v<GammaDataType, F32> &&
is_same_v<BetaDataType, F32> && is_same_v<YDataType, F16>) is_same_v<BetaDataType, F32> && is_same_v<YDataType, F16> &&
is_same_v<SaveMeanInvStdDataType, F32>)
{ {
if constexpr(Rank == 5 && NumReduceDim == 3) if constexpr(Rank == 5 && NumReduceDim == 3)
{ {
......
library/include/ck/library/utility/check_err.hpp
View file @ c5138aa1
...@@ -230,7 +230,6 @@ check_err(const Range& out, ...@@ -230,7 +230,6 @@ check_err(const Range& out,
return res; return res;
} }
#if defined CK_ENABLE_FP8
template <typename Range, typename RefRange> template <typename Range, typename RefRange>
std::enable_if_t<(std::is_same_v<ranges::range_value_t<Range>, ranges::range_value_t<RefRange>> && std::enable_if_t<(std::is_same_v<ranges::range_value_t<Range>, ranges::range_value_t<RefRange>> &&
std::is_same_v<ranges::range_value_t<Range>, f8_t>), std::is_same_v<ranges::range_value_t<Range>, f8_t>),
...@@ -275,9 +274,7 @@ check_err(const Range& out, ...@@ -275,9 +274,7 @@ check_err(const Range& out,
} }
return res; return res;
} }
#endif
#if defined CK_ENABLE_BF8
template <typename Range, typename RefRange> template <typename Range, typename RefRange>
std::enable_if_t<(std::is_same_v<ranges::range_value_t<Range>, ranges::range_value_t<RefRange>> && std::enable_if_t<(std::is_same_v<ranges::range_value_t<Range>, ranges::range_value_t<RefRange>> &&
std::is_same_v<ranges::range_value_t<Range>, bf8_t>), std::is_same_v<ranges::range_value_t<Range>, bf8_t>),
...@@ -322,7 +319,6 @@ check_err(const Range& out, ...@@ -322,7 +319,6 @@ check_err(const Range& out,
} }
return res; return res;
} }
#endif
} // namespace utils } // namespace utils
} // namespace ck } // namespace ck
library/src/tensor_operation_instance/gpu/CMakeLists.txt
View file @ c5138aa1
...@@ -5,44 +5,44 @@ function(add_instance_library INSTANCE_NAME) ...@@ -5,44 +5,44 @@ function(add_instance_library INSTANCE_NAME)
message("adding instance ${INSTANCE_NAME}") message("adding instance ${INSTANCE_NAME}")
set(result 1) set(result 1)
if(DEFINED DTYPES) if(DEFINED DTYPES)
foreach(source IN LISTS ARGN) foreach(source IN LISTS ARGN)
set(test 0) set(test 0)
foreach(type IN LISTS DTYPES) foreach(type IN LISTS DTYPES)
if(type MATCHES "fp16") if(type MATCHES "fp16")
set(type1 "_f16") set(type1 "_f16")
elseif(type MATCHES "fp32") elseif(type MATCHES "fp32")
set(type1 "_f32") set(type1 "_f32")
elseif(type MATCHES "fp8") elseif(type MATCHES "fp8")
set(type1 "_f8") set(type1 "_f8")
elseif(type MATCHES "bf16") elseif(type MATCHES "bf16")
set(type1 "_b16") set(type1 "_b16")
elseif(type MATCHES "fp64") elseif(type MATCHES "fp64")
set(type1 "_f64") set(type1 "_f64")
elseif(type MATCHES "int8") elseif(type MATCHES "int8")
set(type1 "_i8") set(type1 "_i8")
endif() endif()
#make an exception for reduction kernels #make an exception for reduction kernels
if("${source}" MATCHES "${type}" OR "${source}" MATCHES "${type1}" OR "${source}" MATCHES "device_reduce_instance") if("${source}" MATCHES "${type}" OR "${source}" MATCHES "${type1}" OR "${source}" MATCHES "device_reduce_instance" OR ${source} MATCHES "device_image_to_column")
#if filename matches any selected type, exit type loop and do no exclude the file from the list #if filename matches any selected type, exit type loop and do no exclude the file from the list
set(test 0) set(test 0)
break() break()
elseif((source MATCHES "fp8" OR source MATCHES "fp32" OR source MATCHES "fp64" OR source MATCHES "bf16" OR source MATCHES "int8" OR source MATCHES "fp16" OR elseif((source MATCHES "fp8" OR source MATCHES "fp32" OR source MATCHES "fp64" OR source MATCHES "bf16" OR source MATCHES "int8" OR source MATCHES "fp16" OR
source MATCHES "_f8" OR source MATCHES "_f32" OR source MATCHES "_f64" OR source MATCHES "_i8" OR source MATCHES "_f16" OR source MATCHES "_b16") AND source MATCHES "_f8" OR source MATCHES "_f32" OR source MATCHES "_f64" OR source MATCHES "_i8" OR source MATCHES "_f16" OR source MATCHES "_b16") AND
NOT(source MATCHES type OR source MATCHES type1)) NOT(source MATCHES type OR source MATCHES type1))
#if filename contains a type which doesn't match any selected type, mark it for removal #if filename contains a type which doesn't match any selected type, mark it for removal
set(test 1) set(test 1)
endif() endif()
endforeach() endforeach()
if(test EQUAL 1) if(test EQUAL 1)
message("removing instance ${source} ") message("removing instance ${source} ")
list(REMOVE_ITEM ARGN "${source}") list(REMOVE_ITEM ARGN "${source}")
endif() endif()
endforeach() endforeach()
endif() endif()
foreach(source IN LISTS ARGN) foreach(source IN LISTS ARGN)
if(NOT DEFINED DL_KERNELS AND source MATCHES "_dl") if(NOT DEFINED DL_KERNELS AND source MATCHES "_dl")
message("removing dl instance ${source} ") message("removing dl instance ${source} ")
list(REMOVE_ITEM ARGN "${source}") list(REMOVE_ITEM ARGN "${source}")
endif() endif()
endforeach() endforeach()
#only continue if there are some source files left on the list #only continue if there are some source files left on the list
...@@ -52,8 +52,10 @@ function(add_instance_library INSTANCE_NAME) ...@@ -52,8 +52,10 @@ function(add_instance_library INSTANCE_NAME)
set_target_properties(${INSTANCE_NAME} PROPERTIES POSITION_INDEPENDENT_CODE ON) set_target_properties(${INSTANCE_NAME} PROPERTIES POSITION_INDEPENDENT_CODE ON)
clang_tidy_check(${INSTANCE_NAME}) clang_tidy_check(${INSTANCE_NAME})
set(result 0) set(result 0)
message("add_instance_library ${INSTANCE_NAME}")
else()
message("skip_instance_libary ${INSTANCE_NAME}")
endif() endif()
#message("add_instance_library returns ${result}")
set(result ${result} PARENT_SCOPE) set(result ${result} PARENT_SCOPE)
endfunction(add_instance_library INSTANCE_NAME) endfunction(add_instance_library INSTANCE_NAME)
...@@ -61,65 +63,70 @@ endfunction(add_instance_library INSTANCE_NAME) ...@@ -61,65 +63,70 @@ endfunction(add_instance_library INSTANCE_NAME)
file(GLOB dir_list LIST_DIRECTORIES true *) file(GLOB dir_list LIST_DIRECTORIES true *)
set(CK_DEVICE_INSTANCES) set(CK_DEVICE_INSTANCES)
FOREACH(subdir_path ${dir_list}) FOREACH(subdir_path ${dir_list})
set(target_dir) set(target_dir)
IF(IS_DIRECTORY "${subdir_path}") IF(IS_DIRECTORY "${subdir_path}")
set(cmake_instance) set(cmake_instance)
file(READ "${subdir_path}/CMakeLists.txt" cmake_instance) file(READ "${subdir_path}/CMakeLists.txt" cmake_instance)
set(add_inst 0) set(add_inst 0)
if(("${cmake_instance}" MATCHES "_fp8" OR "${cmake_instance}" MATCHES "_f8") AND DTYPES MATCHES "fp8") if(("${cmake_instance}" MATCHES "_fp8" OR "${cmake_instance}" MATCHES "_f8") AND DTYPES MATCHES "fp8")
message("fp8 instance found!") message("fp8 instance found!")
set(add_inst 1) set(add_inst 1)
endif() endif()
if(("${cmake_instance}" MATCHES "_fp16" OR "${cmake_instance}" MATCHES "_f16") AND DTYPES MATCHES "fp16") if(("${cmake_instance}" MATCHES "_fp16" OR "${cmake_instance}" MATCHES "_f16") AND DTYPES MATCHES "fp16")
message("fp16 instance found!") message("fp16 instance found!")
set(add_inst 1) set(add_inst 1)
endif() endif()
if(("${cmake_instance}" MATCHES "_fp32" OR "${cmake_instance}" MATCHES "_f32") AND DTYPES MATCHES "fp32") if(("${cmake_instance}" MATCHES "_fp32" OR "${cmake_instance}" MATCHES "_f32") AND DTYPES MATCHES "fp32")
message("fp32 instance found!") message("fp32 instance found!")
set(add_inst 1) set(add_inst 1)
endif() endif()
if(("${cmake_instance}" MATCHES "_fp64" OR "${cmake_instance}" MATCHES "_f64") AND DTYPES MATCHES "fp64") if(("${cmake_instance}" MATCHES "_fp64" OR "${cmake_instance}" MATCHES "_f64") AND DTYPES MATCHES "fp64")
message("fp64 instance found!") message("fp64 instance found!")
set(add_inst 1) set(add_inst 1)
endif() endif()
if("${cmake_instance}" MATCHES "_bf16" AND DTYPES MATCHES "bf16") if("${cmake_instance}" MATCHES "_bf16" AND DTYPES MATCHES "bf16")
message("bf16 instance found!") message("bf16 instance found!")
set(add_inst 1) set(add_inst 1)
endif() endif()
if(("${cmake_instance}" MATCHES "_int8" OR "${cmake_instance}" MATCHES "_i8") AND DTYPES MATCHES "int8") if(("${cmake_instance}" MATCHES "_int8" OR "${cmake_instance}" MATCHES "_i8") AND DTYPES MATCHES "int8")
message("int8 instance found!") message("int8 instance found!")
set(add_inst 1) set(add_inst 1)
endif() endif()
if(NOT "${cmake_instance}" MATCHES "_fp8" OR if(NOT ("${cmake_instance}" MATCHES "_fp8" OR
NOT "${cmake_instance}" MATCHES "_f8" OR "${cmake_instance}" MATCHES "_f8" OR
NOT "${cmake_instance}" MATCHES "_fp16" OR "${cmake_instance}" MATCHES "_fp16" OR
NOT "${cmake_instance}" MATCHES "_f16" OR "${cmake_instance}" MATCHES "_f16" OR
NOT "${cmake_instance}" MATCHES "_fp32" OR "${cmake_instance}" MATCHES "_fp32" OR
NOT "${cmake_instance}" MATCHES "_f32" OR "${cmake_instance}" MATCHES "_f32" OR
NOT "${cmake_instance}" MATCHES "_fp64" OR "${cmake_instance}" MATCHES "_fp64" OR
NOT "${cmake_instance}" MATCHES "_f64" OR "${cmake_instance}" MATCHES "_f64" OR
NOT "${cmake_instance}" MATCHES "_bf16" OR "${cmake_instance}" MATCHES "_bf16" OR
NOT "${cmake_instance}" MATCHES "_int8" OR "${cmake_instance}" MATCHES "_int8" OR
NOT "${cmake_instance}" MATCHES "_i8" OR "${cmake_instance}" MATCHES "_i8" OR
NOT "${cmake_instance}" MATCHES "_int4" OR "${cmake_instance}" MATCHES "_int4"))
NOT DEFINED DTYPES) message("instance should be built for all types!")
message("instance should be built for all types!") set(add_inst 1)
set(add_inst 1) endif()
endif() if(NOT DEFINED DTYPES)
if("${cmake_instance}" MATCHES "quantization" AND DEFINED DTYPES AND NOT DTYPES MATCHES "int8") set(add_inst 1)
message("quantization instances will not be built!") endif()
set(add_inst 0) if(("${cmake_instance}" MATCHES "quantization") AND (DEFINED DTYPES) AND (NOT DTYPES MATCHES "int8"))
endif() message("quantization instances will not be built!")
if("${cmake_instance}" MATCHES "ONLY DL_KERNELS" AND NOT DEFINED DL_KERNELS)
message("Found only dl instances, but DL_KERNELS is not set. Skipping.")
set(add_inst 0) set(add_inst 0)
endif() endif()
if(add_inst EQUAL 1) if(("${cmake_instance}" MATCHES "ONLY DL_KERNELS") AND (NOT DEFINED DL_KERNELS))
get_filename_component(target_dir ${subdir_path} NAME) message("Found only dl instances, but DL_KERNELS is not set. Skipping.")
add_subdirectory(${target_dir}) set(add_inst 0)
list(APPEND CK_DEVICE_INSTANCES $<TARGET_OBJECTS:device_${target_dir}_instance>) endif()
endif() if((add_inst EQUAL 1))
ENDIF() get_filename_component(target_dir ${subdir_path} NAME)
add_subdirectory(${target_dir})
list(APPEND CK_DEVICE_INSTANCES $<TARGET_OBJECTS:device_${target_dir}_instance>)
message("add_instance_directory ${subdir_path}")
else()
message("skip_instance_directory ${subdir_path}")
endif()
ENDIF()
ENDFOREACH() ENDFOREACH()
add_library(device_operations STATIC ${CK_DEVICE_INSTANCES}) add_library(device_operations STATIC ${CK_DEVICE_INSTANCES})
...@@ -162,11 +169,11 @@ target_compile_options(device_operations PRIVATE ...@@ -162,11 +169,11 @@ target_compile_options(device_operations PRIVATE
# install(TARGETS device_operations LIBRARY DESTINATION lib) # install(TARGETS device_operations LIBRARY DESTINATION lib)
rocm_install(TARGETS device_operations rocm_install(TARGETS device_operations
EXPORT device_operationsTargets) EXPORT device_operationsTargets)
rocm_install(DIRECTORY ${DEV_OPS_INC_DIRS} DESTINATION ${CMAKE_INSTALL_INCLUDEDIR}/ck) rocm_install(DIRECTORY ${DEV_OPS_INC_DIRS} DESTINATION ${CMAKE_INSTALL_INCLUDEDIR}/ck)
rocm_install(EXPORT device_operationsTargets rocm_install(EXPORT device_operationsTargets
FILE composable_kerneldevice_operationsTargets.cmake FILE composable_kerneldevice_operationsTargets.cmake
NAMESPACE composable_kernel:: NAMESPACE composable_kernel::
DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/composable_kernel DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/composable_kernel
) )
library/src/tensor_operation_instance/gpu/gemm/CMakeLists.txt
View file @ c5138aa1
...@@ -96,13 +96,9 @@ list(APPEND GEMM_INSTANCES device_gemm_xdl_c_shuffle_fp8_fp8_fp8_mk_kn_mn_instan ...@@ -96,13 +96,9 @@ list(APPEND GEMM_INSTANCES device_gemm_xdl_c_shuffle_fp8_fp8_fp8_mk_kn_mn_instan
add_instance_library(device_gemm_instance ${GEMM_INSTANCES}) add_instance_library(device_gemm_instance ${GEMM_INSTANCES})
set(ENABLE_PIPELINE_V2_OPT OFF) set(ENABLE_PIPELINE_V2_OPT)
if (ENABLE_PIPELINE_V2_OPT) if (ENABLE_PIPELINE_V2_OPT)
set(MAX_ILP_OPTS
-mllvm
-amdgpu-enable-max-ilp-scheduling-strategy
)
set(WAVES_PER_EU_DEFS set(WAVES_PER_EU_DEFS
CK_USE_WAVES_PER_EU=1 CK_USE_WAVES_PER_EU=1
CK_MIN_WAVES_PER_EU=1 CK_MIN_WAVES_PER_EU=1
...@@ -118,7 +114,7 @@ if (ENABLE_PIPELINE_V2_OPT) ...@@ -118,7 +114,7 @@ if (ENABLE_PIPELINE_V2_OPT)
COMPILE_DEFINITIONS "${WAVES_PER_EU_DEFS};${IGLP_OPT_DEFS}") COMPILE_DEFINITIONS "${WAVES_PER_EU_DEFS};${IGLP_OPT_DEFS}")
# layout=NN # layout=NN
set_source_files_properties(device_gemm_xdl_f16_f16_f16/km_nk_mn_default_pipeline_v2_opt_instance.cpp PROPERTIES set_source_files_properties(device_gemm_xdl_f16_f16_f16/km_nk_mn_default_pipeline_v2_opt_instance.cpp PROPERTIES
COMPILE_OPTIONS "${MAX_ILP_OPTS}" COMPILE_OPTIONS ";;"
COMPILE_DEFINITIONS "${WAVES_PER_EU_DEFS};${IGLP_OPT_DEFS}") COMPILE_DEFINITIONS "${WAVES_PER_EU_DEFS};${IGLP_OPT_DEFS}")
# layout=TT # layout=TT
set_source_files_properties(device_gemm_xdl_f16_f16_f16/mk_kn_mn_default_pipeline_v2_opt_instance.cpp PROPERTIES set_source_files_properties(device_gemm_xdl_f16_f16_f16/mk_kn_mn_default_pipeline_v2_opt_instance.cpp PROPERTIES
...@@ -126,7 +122,7 @@ if (ENABLE_PIPELINE_V2_OPT) ...@@ -126,7 +122,7 @@ if (ENABLE_PIPELINE_V2_OPT)
COMPILE_DEFINITIONS "${WAVES_PER_EU_DEFS};${IGLP_OPT_DEFS}") COMPILE_DEFINITIONS "${WAVES_PER_EU_DEFS};${IGLP_OPT_DEFS}")
# layout=TN # layout=TN
set_source_files_properties(device_gemm_xdl_f16_f16_f16/mk_nk_mn_default_pipeline_v2_opt_instance.cpp PROPERTIES set_source_files_properties(device_gemm_xdl_f16_f16_f16/mk_nk_mn_default_pipeline_v2_opt_instance.cpp PROPERTIES
COMPILE_OPTIONS "${MAX_ILP_OPTS}" COMPILE_OPTIONS ";;"
COMPILE_DEFINITIONS "${WAVES_PER_EU_DEFS};${IGLP_OPT_DEFS}") COMPILE_DEFINITIONS "${WAVES_PER_EU_DEFS};${IGLP_OPT_DEFS}")
endif(ENABLE_PIPELINE_V2_OPT) endif(ENABLE_PIPELINE_V2_OPT)
library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_data/CMakeLists.txt
View file @ c5138aa1
add_instance_library(device_grouped_conv3d_bwd_data_instance set(GROUPED_CONV3D_BWD_DATA
xdl/device_grouped_conv3d_bwd_data_xdl_gndhwc_gkzyxc_gndhwk_f16_instance.cpp xdl/device_grouped_conv3d_bwd_data_xdl_gndhwc_gkzyxc_gndhwk_f16_instance.cpp
xdl/device_grouped_conv3d_bwd_data_xdl_gndhwc_gkzyxc_gndhwk_bf16_instance.cpp xdl/device_grouped_conv3d_bwd_data_xdl_gndhwc_gkzyxc_gndhwk_bf16_instance.cpp
xdl/device_grouped_conv3d_bwd_data_xdl_gndhwc_gkzyxc_gndhwk_f32_instance.cpp xdl/device_grouped_conv3d_bwd_data_xdl_gndhwc_gkzyxc_gndhwk_f32_instance.cpp
xdl/device_grouped_conv3d_bwd_data_xdl_ndhwgc_gkzyxc_ndhwgk_f16_instance.cpp xdl/device_grouped_conv3d_bwd_data_xdl_ndhwgc_gkzyxc_ndhwgk_f16_instance.cpp
xdl/device_grouped_conv3d_bwd_data_xdl_ndhwgc_gkzyxc_ndhwgk_bf16_instance.cpp xdl/device_grouped_conv3d_bwd_data_xdl_ndhwgc_gkzyxc_ndhwgk_bf16_instance.cpp
xdl/device_grouped_conv3d_bwd_data_xdl_ndhwgc_gkzyxc_ndhwgk_f32_instance.cpp xdl/device_grouped_conv3d_bwd_data_xdl_ndhwgc_gkzyxc_ndhwgk_f32_instance.cpp
xdl/device_grouped_conv3d_bwd_data_xdl_ndhwgc_gkzyxc_ndhwgk_input_f16_comp_bf8_f8_instance.cpp
wmma/device_grouped_conv3d_bwd_data_wmma_gndhwc_gkzyxc_gndhwk_f16_instance.cpp wmma/device_grouped_conv3d_bwd_data_wmma_gndhwc_gkzyxc_gndhwk_f16_instance.cpp
wmma/device_grouped_conv3d_bwd_data_wmma_ndhwgc_gkzyxc_ndhwgk_f16_instance.cpp wmma/device_grouped_conv3d_bwd_data_wmma_ndhwgc_gkzyxc_ndhwgk_f16_instance.cpp
wmma/device_grouped_conv3d_bwd_data_wmma_gndhwc_gkzyxc_gndhwk_i8_instance.cpp wmma/device_grouped_conv3d_bwd_data_wmma_gndhwc_gkzyxc_gndhwk_i8_instance.cpp
...@@ -13,5 +12,11 @@ add_instance_library(device_grouped_conv3d_bwd_data_instance ...@@ -13,5 +12,11 @@ add_instance_library(device_grouped_conv3d_bwd_data_instance
wmma/device_grouped_conv3d_bwd_data_wmma_gndhwc_gkzyxc_gndhwk_f16_1x1s1p0_instance.cpp wmma/device_grouped_conv3d_bwd_data_wmma_gndhwc_gkzyxc_gndhwk_f16_1x1s1p0_instance.cpp
wmma/device_grouped_conv3d_bwd_data_wmma_ndhwgc_gkzyxc_ndhwgk_f16_1x1s1p0_instance.cpp wmma/device_grouped_conv3d_bwd_data_wmma_ndhwgc_gkzyxc_ndhwgk_f16_1x1s1p0_instance.cpp
wmma/device_grouped_conv3d_bwd_data_wmma_gndhwc_gkzyxc_gndhwk_i8_1x1s1p0_instance.cpp wmma/device_grouped_conv3d_bwd_data_wmma_gndhwc_gkzyxc_gndhwk_i8_1x1s1p0_instance.cpp
wmma/device_grouped_conv3d_bwd_data_wmma_ndhwgc_gkzyxc_ndhwgk_i8_1x1s1p0_instance.cpp wmma/device_grouped_conv3d_bwd_data_wmma_ndhwgc_gkzyxc_ndhwgk_i8_1x1s1p0_instance.cpp)
)
if((DTYPES MATCHES "fp8" AND DTYPES MATCHES "bf8" AND DTYPES MATCHES "fp16") OR NOT DEFINED DTYPES)
list(APPEND GROUPED_CONV3D_BWD_DATA
xdl/device_grouped_conv3d_bwd_data_xdl_ndhwgc_gkzyxc_ndhwgk_input_f16_comp_bf8_f8_instance.cpp)
endif()
add_instance_library(device_grouped_conv3d_bwd_data_instance ${GROUPED_CONV3D_BWD_DATA})
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