// Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. /** * \file This file contains all the intrinsics available to be used in CUDA code * generated by CodeGen. */ #pragma once #include extern "C" { #define CINN_UINT8_MIN 0 #define CINN_UINT8_MAX 255 #define CINN_INT16_MIN -32768 #define CINN_INT16_MAX 32767 #define CINN_INT32_MIN -2147483648 #define CINN_INT32_MAX 2147483647 #define CINN_INT64_MAX 0x7fffffffffffffffLL #define CINN_INT64_MIN -CINN_INT64_MAX - 1 #define CINN_FP32_MAX 3.40282347e+38F #define CINN_FP64_MAX 1.79769313486231571e+308 #define CINN_FP16_MIN (float16) __ushort_as_half(0xfbff) #define CINN_FP16_MAX (float16) __ushort_as_half(0x7bff) // *************************************************************** // // bool unary and binary operator #define FN_BOOL(func) cinn_nvgpu_##func##_bool __device__ inline bool FN_BOOL(bitwise_and)(bool a, bool b) { return a & b; } __device__ inline bool FN_BOOL(bitwise_or)(bool a, bool b) { return a | b; } __device__ inline bool FN_BOOL(bitwise_xor)(bool a, bool b) { return a ^ b; } __device__ inline bool FN_BOOL(bitwise_not)(bool a) { return !a; } // *************************************************************** // // uint8 unary and binary operator #define FN_UINT8(func) cinn_nvgpu_##func##_uint8 __device__ inline uint8_t FN_UINT8(bitwise_and)(uint8_t a, uint8_t b) { return a & b; } __device__ inline uint8_t FN_UINT8(bitwise_or)(uint8_t a, uint8_t b) { return a | b; } __device__ inline uint8_t FN_UINT8(bitwise_xor)(uint8_t a, uint8_t b) { return a ^ b; } __device__ inline uint8_t FN_UINT8(bitwise_not)(uint8_t a) { return ~a; } __device__ inline uint8_t FN_UINT8(logical_right_shift)(uint8_t a, uint8_t b) { return ((uint8_t)a >> b); } // *************************************************************** // // int8 unary and binary operator #define FN_INT8(func) cinn_nvgpu_##func##_int8 __device__ inline int8_t FN_INT8(bitwise_and)(int8_t a, int8_t b) { return a & b; } __device__ inline int8_t FN_INT8(bitwise_or)(int8_t a, int8_t b) { return a | b; } __device__ inline int8_t FN_INT8(bitwise_xor)(int8_t a, int8_t b) { return a ^ b; } __device__ inline int8_t FN_INT8(bitwise_not)(int8_t a) { return ~a; } __device__ inline int8_t FN_INT8(logical_right_shift)(int8_t a, int8_t b) { return ((uint8_t)a >> b); } // *************************************************************** // // int16 unary and binary operator #define FN_INT16(func) cinn_nvgpu_##func##_int16 __device__ inline int16_t FN_INT16(bitwise_and)(int16_t a, int16_t b) { return a & b; } __device__ inline int16_t FN_INT16(bitwise_or)(int16_t a, int16_t b) { return a | b; } __device__ inline int16_t FN_INT16(bitwise_xor)(int16_t a, int16_t b) { return a ^ b; } __device__ inline int16_t FN_INT16(bitwise_not)(int16_t a) { return ~a; } __device__ inline int16_t FN_INT16(logical_right_shift)(int16_t a, int16_t b) { return ((uint16_t)a >> b); } // *************************************************************** // // float32 unary and binary operator #define FN_FP32(func) cinn_nvgpu_##func##_fp32 // NOTE Due to function override, we don't need to use type (such as '_fp32') as // the suffix of function's name. __device__ inline float FN_FP32(sin)(float x) { return sin(x); } __device__ inline float FN_FP32(cos)(float x) { return cos(x); } __device__ inline float FN_FP32(tan)(float x) { return tan(x); } __device__ inline float FN_FP32(sinh)(float x) { return sinh(x); } __device__ inline float FN_FP32(cosh)(float x) { return cosh(x); } __device__ inline float FN_FP32(tanh)(float x) { return tanh(x); } __device__ inline float FN_FP32(asin)(float x) { return asin(x); } __device__ inline float FN_FP32(acos)(float x) { return acos(x); } __device__ inline float FN_FP32(atan)(float x) { return atan(x); } __device__ inline float FN_FP32(asinh)(float x) { return asinh(x); } __device__ inline float FN_FP32(acosh)(float x) { return acosh(x); } __device__ inline float FN_FP32(atanh)(float x) { return atanh(x); } __device__ inline float FN_FP32(ceil)(float x) { return ceil(x); } __device__ inline float FN_FP32(rint)(float x) { return rint(x); } __device__ inline float FN_FP32(round)(float x) { return round(x); } __device__ inline float FN_FP32(trunc)(float x) { return trunc(x); } __device__ inline float FN_FP32(abs)(float x) { return abs(x); } __device__ inline float FN_FP32(floor)(float x) { return floor(x); } __device__ inline float FN_FP32(log)(float x) { return log(x); } __device__ inline float FN_FP32(log2)(float x) { return log2(x); } __device__ inline float FN_FP32(log10)(float x) { return log10(x); } __device__ inline float FN_FP32(exp)(float x) { return exp(x); } __device__ inline float FN_FP32(erf)(float x) { return erf(x); } __device__ inline float FN_FP32(sigmoid)(float x) { return 1.0f / (1.0f + exp(-x)); } __device__ inline float FN_FP32(sqrt)(float x) { return sqrt(x); } __device__ inline float FN_FP32(rsqrt)(float x) { return rsqrt(x); } __device__ inline float FN_FP32(cbrt)(float x) { return cbrt(x); } __device__ inline bool FN_FP32(isfinite)(float x) { return isfinite(x); } __device__ inline bool FN_FP32(isinf)(float x) { return isinf(x); } __device__ inline bool FN_FP32(isnan)(float x) { return isnan(x); } __device__ inline float FN_FP32(pow)(float a, float b) { return powf(a, b); } __device__ inline float FN_FP32(mod)(float a, float b) { float res = fmodf(a, b); if ((res != 0.0f) && ((res < 0.0f) != (b < 0.0f))) res += b; return res; } __device__ inline float FN_FP32(rcp)(float x) { float res; asm("rcp.approx.ftz.f32 %0, %1;" : "=f"(res) : "f"(x)); return res; } __device__ inline float FN_FP32(tanh_approx)(float x) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 750 float res; asm("tanh.approx.f32 %0, %1;" : "=f"(res) : "f"(x)); return res; #else return tanh(x); #endif } // *************************************************************** // // float64 unary and binary operator #define FN_FP64(func) cinn_nvgpu_##func##_fp64 __device__ inline double FN_FP64(sin)(double x) { return sin(x); } __device__ inline double FN_FP64(cos)(double x) { return cos(x); } __device__ inline double FN_FP64(tan)(double x) { return tan(x); } __device__ inline double FN_FP64(sinh)(double x) { return sinh(x); } __device__ inline double FN_FP64(cosh)(double x) { return cosh(x); } __device__ inline double FN_FP64(tanh)(double x) { return tanh(x); } __device__ inline double FN_FP64(asin)(double x) { return asin(x); } __device__ inline double FN_FP64(acos)(double x) { return acos(x); } __device__ inline double FN_FP64(atan)(double x) { return atan(x); } __device__ inline double FN_FP64(asinh)(double x) { return asinh(x); } __device__ inline double FN_FP64(acosh)(double x) { return acosh(x); } __device__ inline double FN_FP64(atanh)(double x) { return atanh(x); } __device__ inline double FN_FP64(ceil)(double x) { return ceil(x); } __device__ inline double FN_FP64(rint)(double x) { return rint(x); } __device__ inline double FN_FP64(round)(double x) { return round(x); } __device__ inline double FN_FP64(trunc)(double x) { return trunc(x); } __device__ inline double FN_FP64(abs)(double x) { return abs(x); } __device__ inline double FN_FP64(floor)(double x) { return floor(x); } __device__ inline double FN_FP64(log)(double x) { return log(x); } __device__ inline double FN_FP64(log2)(double x) { return log2(x); } __device__ inline double FN_FP64(log10)(double x) { return log10(x); } __device__ inline double FN_FP64(exp)(double x) { return exp(x); } __device__ inline double FN_FP64(erf)(double x) { return erf(x); } __device__ inline double FN_FP64(sigmoid)(double x) { return 1.0 / (1.0 + exp(-x)); } __device__ inline double FN_FP64(sqrt)(double x) { return sqrt(x); } __device__ inline double FN_FP64(rsqrt)(double x) { return rsqrt(x); } __device__ inline double FN_FP64(cbrt)(double x) { return cbrt(x); } __device__ inline bool FN_FP64(isfinite)(double x) { return isfinite(x); } __device__ inline bool FN_FP64(isinf)(double x) { return isinf(x); } __device__ inline bool FN_FP64(isnan)(double x) { return isnan(x); } __device__ inline double FN_FP64(pow)(double a, double b) { return pow(a, b); } __device__ inline double FN_FP64(mod)(double a, double b) { double res = fmod(a, b); if ((res != 0.0) && ((res < 0.0) != (b < 0.0))) res += b; return res; } __device__ inline double FN_FP64(rcp)(double x) { double res; asm("rcp.approx.ftz.f64 %0, %1;" : "=d"(res) : "d"(x)); return res; } } // *************************************************************** // // welford struct and operators #define WELFORD_STRUCT_MACRO(TYPENAME, DTYPE) \ struct TYPENAME { \ DTYPE mean; \ DTYPE m2; \ DTYPE weight; \ __device__ TYPENAME(){}; \ __device__ explicit TYPENAME(DTYPE value) \ : mean(value), m2(0), weight(1) {} \ __device__ TYPENAME(DTYPE mean, DTYPE m2, DTYPE weight) \ : mean(mean), m2(m2), weight(weight) {} \ __device__ explicit operator DTYPE() const { return m2 / weight; } \ }; #define WELFORD_COMBINE_MACRO(TYPENAME, DTYPE, RCP_FUNC) \ __device__ inline TYPENAME operator+(const TYPENAME &a, const TYPENAME &b) { \ DTYPE delta = b.mean - a.mean; \ DTYPE weight = a.weight + b.weight; \ DTYPE mean = a.mean + delta * RCP_FUNC(weight); \ DTYPE m2 = a.m2 + delta * (b.mean - mean); \ return {mean, m2, weight}; \ } #define WELFORD_SHFL_SYNC_MACRO(TYPENAME, DTYPE, SHFL_FUNC, ARG2_TYPE, ARG2) \ __device__ inline TYPENAME SHFL_FUNC( \ unsigned mask, const TYPENAME &var, ARG2_TYPE ARG2, int width = 32) { \ DTYPE mean = SHFL_FUNC(mask, var.mean, ARG2, width); \ DTYPE m2 = SHFL_FUNC(mask, var.m2, ARG2, width); \ DTYPE weight = SHFL_FUNC(mask, var.weight, ARG2, width); \ return {mean, m2, weight}; \ } #define EXPAND_WELFORD_MACRO(TYPE_SUFFIX, DTYPE) \ WELFORD_STRUCT_MACRO(welford_##TYPE_SUFFIX, DTYPE) \ WELFORD_COMBINE_MACRO( \ welford_##TYPE_SUFFIX, DTYPE, cinn_nvgpu_rcp_##TYPE_SUFFIX) \ WELFORD_SHFL_SYNC_MACRO( \ welford_##TYPE_SUFFIX, DTYPE, __shfl_down_sync, unsigned, delta) \ WELFORD_SHFL_SYNC_MACRO( \ welford_##TYPE_SUFFIX, DTYPE, __shfl_xor_sync, int, laneMask) EXPAND_WELFORD_MACRO(fp32, float) EXPAND_WELFORD_MACRO(fp64, double) #undef WELFORD_STRUCT_MACRO #undef WELFORD_COMBINE_MACRO #undef WELFORD_SHFL_SYNC_MACRO #undef EXPAND_WELFORD_MACRO // arg reduce arg index struct #define ARGIDX_STRUCT_MACRO(TYPENAME, DTYPE, ITYPE, IINIT) \ struct TYPENAME { \ DTYPE value; \ ITYPE index; \ __device__ TYPENAME() {} \ __device__ explicit TYPENAME(DTYPE value) : value(value), index(IINIT) {} \ __device__ TYPENAME(DTYPE value, ITYPE index) \ : value(value), index(index) {} \ __device__ explicit operator ITYPE() { return index; } \ }; // TODO(heqianyue): improve the memory access pattern, make it SoA layout #define ARGIDX_COMBINE_MACRO(TYPENAME) \ __device__ TYPENAME cinn_min_##TYPENAME(TYPENAME a, TYPENAME b) { \ return a.value == b.value ? (a.index < b.index ? a : b) \ : (a.value < b.value ? a : b); \ } \ __device__ TYPENAME cinn_max_##TYPENAME(TYPENAME a, TYPENAME b) { \ return a.value == b.value ? (a.index < b.index ? a : b) \ : (a.value > b.value ? a : b); \ } \ __device__ TYPENAME min(TYPENAME a, TYPENAME b) { \ return a.value <= b.value ? a : b; \ } \ __device__ TYPENAME max(TYPENAME a, TYPENAME b) { \ return a.value >= b.value ? a : b; \ } // shfl primitives for argidx #define ARGIDX_SHFL_SYNC_MACRO( \ TYPENAME, DTYPE, ITYPE, SHFL_FUNC, ARG2_TYPE, ARG2) \ __device__ inline TYPENAME SHFL_FUNC( \ unsigned mask, const TYPENAME &var, ARG2_TYPE ARG2, int width = 32) { \ DTYPE value = SHFL_FUNC(mask, var.value, ARG2, width); \ ITYPE index = SHFL_FUNC(mask, var.index, ARG2, width); \ return {value, index}; \ } #define EXPAND_ARGIDX_DTYPE_MACRO_IMPL( \ DTYPE, DNAME, DMIN, DMAX, ITYPE, INAME, IMAX) \ ARGIDX_STRUCT_MACRO(argidx_##DNAME##_##INAME, DTYPE, ITYPE, IMAX) \ ARGIDX_COMBINE_MACRO(argidx_##DNAME##_##INAME) \ ARGIDX_SHFL_SYNC_MACRO(argidx_##DNAME##_##INAME, \ DTYPE, \ ITYPE, \ __shfl_down_sync, \ unsigned, \ delta) \ ARGIDX_SHFL_SYNC_MACRO( \ argidx_##DNAME##_##INAME, DTYPE, ITYPE, __shfl_xor_sync, int, laneMask) #define EXPAND_ARGIDX_DTYPE_MACRO(DTYPE, DNAME, DMIN, DMAX) \ EXPAND_ARGIDX_DTYPE_MACRO_IMPL(DTYPE, DNAME, DMIN, DMAX, int, i32, 0) \ EXPAND_ARGIDX_DTYPE_MACRO_IMPL(DTYPE, DNAME, DMIN, DMAX, int64_t, i64, 0LL) #ifdef CINN_CUDA_FP16 EXPAND_ARGIDX_DTYPE_MACRO(float16, fp16, -CINN_FP16_MAX, CINN_FP16_MAX) #endif // CINN_CUDA_FP16 EXPAND_ARGIDX_DTYPE_MACRO(float, fp32, -CINN_FP32_MAX, CINN_FP32_MAX) EXPAND_ARGIDX_DTYPE_MACRO(double, fp64, -CINN_FP64_MAX, CINN_FP64_MAX) EXPAND_ARGIDX_DTYPE_MACRO(int16_t, i16, CINN_INT16_MIN, CINN_INT16_MAX) EXPAND_ARGIDX_DTYPE_MACRO(int, i32, CINN_INT32_MIN, CINN_INT32_MAX) EXPAND_ARGIDX_DTYPE_MACRO(int64_t, i64, CINN_INT64_MIN, CINN_INT64_MAX) EXPAND_ARGIDX_DTYPE_MACRO(uint8_t, u8, CINN_UINT8_MIN, CINN_UINT8_MAX) #undef EXPAND_ARGIDX_DTYPE_MACRO #undef EXPAND_ARGIDX_DTYPE_MACRO_IMPL #undef ARGIDX_STRUCT_MACRO #undef ARGIDX_COMBINE_MACRO #undef ARGIDX_SHFL_SYNC_MACRO #undef ARGIDX_SHFL_SYNC_MACRO extern "C" { // *************************************************************** // // int32 unary and binary operator #define FN_INT32(func) cinn_nvgpu_##func##_int32 __device__ inline int FN_INT32(pow)(int a, int b) { if (a == 0 && b < 0) { return 0; } float res = pow(__int2float_rd(a), __int2float_rd(b)); return __float2int_rn(res); } __device__ inline int FN_INT32(left_shift)(int a, int b) { return a << b; } __device__ inline int FN_INT32(right_shift)(int a, int b) { return a >> b; } __device__ inline int FN_INT32(bitwise_and)(int a, int b) { return a & b; } __device__ inline int FN_INT32(bitwise_or)(int a, int b) { return a | b; } __device__ inline int FN_INT32(bitwise_xor)(int a, int b) { return a ^ b; } __device__ inline int FN_INT32(bitwise_not)(int a) { return ~a; } __device__ inline int FN_INT32(clz)(int a) { return __clz(a); } __device__ inline int FN_INT32(popc)(int a) { return __popc(a); } __device__ inline int FN_INT32(logical_right_shift)(int a, int b) { return ((unsigned int)a >> b); } __device__ inline int FN_INT32(trunc)(int a) { return a; } __device__ inline int FN_INT32(max)(int a, int b) { return max(a, b); } __device__ inline int FN_INT32(min)(int a, int b) { return min(a, b); } __device__ inline int FN_INT32(abs)(int x) { return abs(x); } __device__ inline int FN_INT32(mod)(int a, int b) { int res = a % b; if ((res != 0) && ((b ^ res) < 0)) res += b; return res; } __device__ inline int FN_INT32(exp)(int a) { float res = exp(__int2float_rd(a)); return __float2int_rn(res); } // *************************************************************** // // int64 unary and binary operator #define FN_INT64(func) cinn_nvgpu_##func##_int64 __device__ inline int64_t FN_INT64(bitwise_and)(int64_t a, int64_t b) { return a & b; } __device__ inline int64_t FN_INT64(bitwise_or)(int64_t a, int64_t b) { return a | b; } __device__ inline int64_t FN_INT64(bitwise_xor)(int64_t a, int64_t b) { return a ^ b; } __device__ inline int64_t FN_INT64(bitwise_not)(int64_t a) { return ~a; } __device__ inline int64_t FN_INT64(clz)(int64_t a) { return __clzll(a); } __device__ inline int64_t FN_INT64(popc)(int64_t a) { return __popcll(a); } __device__ inline int64_t FN_INT64(abs)(int64_t x) { return llabs(x); } __device__ inline int64_t FN_INT64(logical_right_shift)(int64_t a, int64_t b) { return ((uint64_t)a >> b); } __device__ inline int64_t FN_INT64(trunc)(int64_t a) { return a; } __device__ inline int64_t FN_INT64(mod)(int64_t a, int64_t b) { int64_t res = a % b; if ((res != 0) && ((b ^ res) < 0)) res += b; return res; } __device__ inline int64_t FN_INT64(exp)(int64_t a) { double res = exp(__ll2double_rd(a)); return __double2ll_rn(res); } __device__ inline int64_t FN_INT64(pow)(int64_t a, int64_t b) { if (a == 0 && b < 0) { return 0; } double res = pow(__ll2double_rd(a), __ll2double_rd(b)); return __double2ll_rn(res); } // *************************************************************** // // bfloat16 unary and binary operator #ifdef CINN_CUDA_BF16 #define FN_BF16(func) cinn_nvgpu_##func##_bf16 __device__ inline bfloat16 FN_BF16(ceil)(bfloat16 x) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 800 return bfloat16(hceil(x.to_nv_bfloat16())); #else return bfloat16(FN_FP32(ceil)(static_cast(x))); #endif } __device__ inline bfloat16 FN_BF16(floor)(bfloat16 x) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 800 return bfloat16(hfloor(x.to_nv_bfloat16())); #else return bfloat16(FN_FP32(floor)(static_cast(x))); #endif } __device__ inline bfloat16 FN_BF16(rint)(bfloat16 x) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 800 return bfloat16(hrint(x.to_nv_bfloat16())); #else return bfloat16(FN_FP32(rint)(static_cast(x))); #endif } __device__ inline bfloat16 FN_BF16(round)(bfloat16 x) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 800 return bfloat16(hrint(x.to_nv_bfloat16())); #else return bfloat16(FN_FP32(round)(static_cast(x))); #endif } __device__ inline bfloat16 FN_BF16(trunc)(bfloat16 x) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 800 return bfloat16(htrunc(x.to_nv_bfloat16())); #else return bfloat16(FN_FP32(trunc)(static_cast(x))); #endif } __device__ inline bfloat16 FN_BF16(sin)(bfloat16 x) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 800 return bfloat16(hsin(x.to_nv_bfloat16())); #else return bfloat16(FN_FP32(sin)(static_cast(x))); #endif } __device__ inline bfloat16 FN_BF16(cos)(bfloat16 x) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 800 return bfloat16(hcos(x.to_nv_bfloat16())); #else return bfloat16(FN_FP32(cos)(static_cast(x))); #endif } __device__ inline bfloat16 FN_BF16(exp)(bfloat16 x) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 800 return bfloat16(hexp(x.to_nv_bfloat16())); #else return bfloat16(FN_FP32(exp)(static_cast(x))); #endif } __device__ inline bfloat16 FN_BF16(log)(bfloat16 x) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 800 return bfloat16(hlog(x.to_nv_bfloat16())); #else return bfloat16(FN_FP32(log)(static_cast(x))); #endif } __device__ inline bfloat16 FN_BF16(log2)(bfloat16 x) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 800 return bfloat16(hlog2(x.to_nv_bfloat16())); #else return bfloat16(FN_FP32(log2)(static_cast(x))); #endif } __device__ inline bfloat16 FN_BF16(log10)(bfloat16 x) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 800 return bfloat16(hlog10(x.to_nv_bfloat16())); #else return bfloat16(FN_FP32(log10)(static_cast(x))); #endif } __device__ inline bfloat16 FN_BF16(sqrt)(bfloat16 x) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 800 return bfloat16(hsqrt(x.to_nv_bfloat16())); #else return bfloat16(FN_FP32(sqrt)(static_cast(x))); #endif } __device__ inline bfloat16 FN_BF16(rsqrt)(bfloat16 x) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 800 return bfloat16(hrsqrt(x.to_nv_bfloat16())); #else return bfloat16(FN_FP32(rsqrt)(static_cast(x))); #endif } __device__ inline bfloat16 FN_BF16(cbrt)(bfloat16 x) { return bfloat16(FN_FP32(cbrt)(static_cast(x))); } __device__ inline bfloat16 FN_BF16(abs)(bfloat16 x) { return cinn::common::abs(x); } __device__ inline bool FN_BF16(isnan)(bfloat16 x) { return cinn::common::isnan(x); } __device__ inline bool FN_BF16(isinf)(bfloat16 x) { return cinn::common::isinf(x); } __device__ inline bool FN_BF16(isfinite)(bfloat16 x) { return cinn::common::isfinite(x); } __device__ inline bfloat16 FN_BF16(erf)(bfloat16 x) { return bfloat16(FN_FP32(erf)(static_cast(x))); } __device__ inline bfloat16 FN_BF16(tan)(bfloat16 x) { return bfloat16(FN_FP32(tan)(static_cast(x))); } __device__ inline bfloat16 FN_BF16(sinh)(bfloat16 x) { return bfloat16(FN_FP32(sinh)(static_cast(x))); } __device__ inline bfloat16 FN_BF16(cosh)(bfloat16 x) { return bfloat16(FN_FP32(cosh)(static_cast(x))); } __device__ inline bfloat16 FN_BF16(tanh)(bfloat16 x) { return bfloat16(FN_FP32(tanh_approx)(static_cast(x))); } __device__ inline bfloat16 FN_BF16(asin)(bfloat16 x) { return bfloat16(FN_FP32(asin)(static_cast(x))); } __device__ inline bfloat16 FN_BF16(acos)(bfloat16 x) { return bfloat16(FN_FP32(acos)(static_cast(x))); } __device__ inline bfloat16 FN_BF16(atan)(bfloat16 x) { return bfloat16(FN_FP32(atan)(static_cast(x))); } __device__ inline bfloat16 FN_BF16(asinh)(bfloat16 x) { return bfloat16(FN_FP32(asinh)(static_cast(x))); } __device__ inline bfloat16 FN_BF16(acosh)(bfloat16 x) { return bfloat16(FN_FP32(acosh)(static_cast(x))); } __device__ inline bfloat16 FN_BF16(atanh)(bfloat16 x) { return bfloat16(FN_FP32(atanh)(static_cast(x))); } __device__ inline bfloat16 FN_BF16(sigmoid)(bfloat16 x) { return bfloat16(FN_FP32(sigmoid)(static_cast(x))); } __device__ inline bfloat16 FN_BF16(mod)(bfloat16 a, bfloat16 b) { return bfloat16(FN_FP32(mod)(static_cast(a), static_cast(b))); } __device__ inline bfloat16 FN_BF16(pow)(bfloat16 a, bfloat16 b) { return bfloat16(FN_FP32(pow)(static_cast(a), static_cast(b))); } #endif // *************************************************************** // // float16 unary and binary operator #ifdef CINN_CUDA_FP16 #define FN_FP16(func) cinn_nvgpu_##func##_fp16 __device__ inline float16 FN_FP16(ceil)(float16 x) { return float16(hceil(x.to_half())); } __device__ inline float16 FN_FP16(floor)(float16 x) { return float16(hfloor(x.to_half())); } __device__ inline float16 FN_FP16(rint)(float16 x) { return float16(FN_FP32(rint)(static_cast(x))); } __device__ inline float16 FN_FP16(round)(float16 x) { return float16(FN_FP32(round)(static_cast(x))); } __device__ inline float16 FN_FP16(trunc)(float16 x) { return float16(htrunc(x.to_half())); } __device__ inline float16 FN_FP16(sin)(float16 x) { return float16(hsin(x.to_half())); } __device__ inline float16 FN_FP16(cos)(float16 x) { return float16(hcos(x.to_half())); } __device__ inline float16 FN_FP16(exp)(float16 x) { return float16(hexp(x.to_half())); } __device__ inline float16 FN_FP16(log)(float16 x) { return float16(hlog(x.to_half())); } __device__ inline float16 FN_FP16(log2)(float16 x) { return float16(hlog2(x.to_half())); } __device__ inline float16 FN_FP16(log10)(float16 x) { return float16(hlog10(x.to_half())); } __device__ inline float16 FN_FP16(sqrt)(float16 x) { return float16(hsqrt(x.to_half())); } __device__ inline float16 FN_FP16(rsqrt)(float16 x) { return float16(hrsqrt(x.to_half())); } __device__ inline float16 FN_FP16(cbrt)(float16 x) { return float16(FN_FP32(cbrt)(static_cast(x))); } __device__ inline float16 FN_FP16(abs)(float16 x) { return cinn::common::abs(x); } __device__ inline bool FN_FP16(isnan)(float16 x) { return cinn::common::isnan(x); } __device__ inline bool FN_FP16(isinf)(float16 x) { return cinn::common::isinf(x); } __device__ inline bool FN_FP16(isfinite)(float16 x) { return cinn::common::isfinite(x); } __device__ inline float16 FN_FP16(erf)(float16 x) { return float16(FN_FP32(erf)(static_cast(x))); } __device__ inline float16 FN_FP16(tan)(float16 x) { return float16(FN_FP32(tan)(static_cast(x))); } __device__ inline float16 FN_FP16(sinh)(float16 x) { return float16(FN_FP32(sinh)(static_cast(x))); } __device__ inline float16 FN_FP16(cosh)(float16 x) { return float16(FN_FP32(cosh)(static_cast(x))); } __device__ inline float16 FN_FP16(tanh)(float16 x) { return float16(FN_FP32(tanh_approx)(static_cast(x))); } __device__ inline float16 FN_FP16(asin)(float16 x) { return float16(FN_FP32(asin)(static_cast(x))); } __device__ inline float16 FN_FP16(acos)(float16 x) { return float16(FN_FP32(acos)(static_cast(x))); } __device__ inline float16 FN_FP16(atan)(float16 x) { return float16(FN_FP32(atan)(static_cast(x))); } __device__ inline float16 FN_FP16(asinh)(float16 x) { return float16(FN_FP32(asinh)(static_cast(x))); } __device__ inline float16 FN_FP16(acosh)(float16 x) { return float16(FN_FP32(acosh)(static_cast(x))); } __device__ inline float16 FN_FP16(atanh)(float16 x) { return float16(FN_FP32(atanh)(static_cast(x))); } __device__ inline float16 FN_FP16(sigmoid)(float16 x) { return float16(FN_FP32(sigmoid)(static_cast(x))); } __device__ inline float16 FN_FP16(mod)(float16 a, float16 b) { return float16(FN_FP32(mod)(static_cast(a), static_cast(b))); } __device__ inline float16 FN_FP16(pow)(float16 a, float16 b) { return float16(FN_FP32(pow)(static_cast(a), static_cast(b))); } #endif // *************************************************************** // #define EXPAND_ARGIDX_OP_MACRO_IMPL(MACRO, TYPENAME, METHOD, DINIT, IINIT) \ MACRO(METHOD##_##TYPENAME, TYPENAME(DINIT, IINIT), TYPENAME) #define EXPAND_ARGIDX_OP_MACRO(OP_MACRO, DNAME, DMIN, DMAX, INAME) \ EXPAND_ARGIDX_OP_MACRO_IMPL( \ OP_MACRO, argidx_##DNAME##_##INAME, min, DMAX, 0) \ EXPAND_ARGIDX_OP_MACRO_IMPL(OP_MACRO, argidx_##DNAME##_##INAME, max, DMIN, 0) // modify this macro to support more types #define EXPAND_ARGIDX_OP_ALL_DTYPE_MACRO(MACRO, ITYPE, INAME) \ EXPAND_ARGIDX_OP_MACRO(MACRO, fp16, -CINN_FP16_MAX, CINN_FP16_MAX, INAME) \ EXPAND_ARGIDX_OP_MACRO(MACRO, fp32, -CINN_FP32_MAX, CINN_FP32_MAX, INAME) \ EXPAND_ARGIDX_OP_MACRO(MACRO, fp64, -CINN_FP64_MAX, CINN_FP64_MAX, INAME) \ EXPAND_ARGIDX_OP_MACRO(MACRO, i16, CINN_INT16_MIN, CINN_INT16_MAX, INAME) \ EXPAND_ARGIDX_OP_MACRO(MACRO, i32, CINN_INT32_MIN, CINN_INT32_MAX, INAME) \ EXPAND_ARGIDX_OP_MACRO(MACRO, i64, CINN_INT64_MIN, CINN_INT64_MAX, INAME) \ EXPAND_ARGIDX_OP_MACRO(MACRO, u8, CINN_UINT8_MIN, CINN_UINT8_MAX, INAME) #define EXPAND_ARGIDX_OP_ALL_DTYPE_ITYPE_MACRO(MACRO) \ EXPAND_ARGIDX_OP_ALL_DTYPE_MACRO(MACRO, int, i32) \ EXPAND_ARGIDX_OP_ALL_DTYPE_MACRO(MACRO, int64_t, i64) // *************************************************************** // // reduce operator, need `--expt-relaxed-constexpr` option to call std function // in device kernel #define EXPAND_REDUCE_INT32_MACRO(MACRO, ...) \ MACRO(sum_int32, 0, int, ##__VA_ARGS__) \ MACRO(prod_int32, 1, int, ##__VA_ARGS__) \ MACRO(max_int32, CINN_INT32_MIN, int, ##__VA_ARGS__) \ MACRO(min_int32, CINN_INT32_MAX, int, ##__VA_ARGS__) // parallel reduction template for welford variance type reduction #define WELFORD_PARALLEL_COMBINE_MACRO(DTYPE, TYPE_SUFFIX) \ __device__ inline welford_##TYPE_SUFFIX cinn_sum_welford_##TYPE_SUFFIX( \ welford_##TYPE_SUFFIX a, welford_##TYPE_SUFFIX b) { \ DTYPE delta = b.mean - a.mean; \ DTYPE weight = a.weight + b.weight; \ DTYPE w2_over_w = b.weight * cinn_nvgpu_rcp_##TYPE_SUFFIX(weight); \ w2_over_w = weight == 0 ? (DTYPE)0 : w2_over_w; \ DTYPE mean = a.mean + delta * w2_over_w; \ DTYPE m2 = a.m2 + b.m2 + delta * delta * a.weight * w2_over_w; \ return {mean, m2, weight}; \ } __device__ inline int cinn_sum_int32(const int left, const int right) { return left + right; } __device__ inline int cinn_prod_int32(const int left, const int right) { return left * right; } __device__ inline int cinn_max_int32(const int left, const int right) { return max(left, right); } __device__ inline int cinn_min_int32(const int left, const int right) { return min(left, right); } #define EXPAND_REDUCE_INT64_MACRO(MACRO, ...) \ MACRO(sum_int64, 0, int64_t, ##__VA_ARGS__) \ MACRO(prod_int64, 1, int64_t, ##__VA_ARGS__) \ MACRO(max_int64, -9223372036854775808, int64_t, ##__VA_ARGS__) \ MACRO(min_int64, 9223372036854775807, int64_t, ##__VA_ARGS__) __device__ inline int64_t cinn_sum_int64(const int64_t left, const int64_t right) { return left + right; } __device__ inline int64_t cinn_prod_int64(const int64_t left, const int64_t right) { return left * right; } __device__ inline int64_t cinn_max_int64(const int64_t left, const int64_t right) { return max(left, right); } __device__ inline int64_t cinn_min_int64(const int64_t left, const int64_t right) { return min(left, right); } #define EXPAND_REDUCE_FP32_MACRO(MACRO, ...) \ MACRO(sum_fp32, 0.0f, float, ##__VA_ARGS__) \ MACRO(prod_fp32, 1.0f, float, ##__VA_ARGS__) \ MACRO(max_fp32, -CINN_FP32_MAX, float, ##__VA_ARGS__) \ MACRO(min_fp32, CINN_FP32_MAX, float, ##__VA_ARGS__) \ MACRO(sum_welford_fp32, \ welford_fp32(0.0f, 0.0f, 0.0f), \ welford_fp32, \ ##__VA_ARGS__) __device__ inline float cinn_sum_fp32(const float left, const float right) { return left + right; } __device__ inline float cinn_prod_fp32(const float left, const float right) { return left * right; } __device__ inline float cinn_max_fp32(const float left, const float right) { return max(left, right); } __device__ inline float cinn_min_fp32(const float left, const float right) { return min(left, right); } WELFORD_PARALLEL_COMBINE_MACRO(float, fp32) #ifdef CINN_CUDA_BF16 #define EXPAND_REDUCE_BF16_MACRO(MACRO, ...) \ MACRO(sum_bf16, bfloat16(0.0), bfloat16, ##__VA_ARGS__) \ MACRO(prod_bf16, bfloat16(1.0), bfloat16, ##__VA_ARGS__) \ MACRO(max_bf16, \ cinn::common::raw_uint16_to_bfloat16(0xfbff), \ bfloat16, \ ##__VA_ARGS__) \ MACRO(min_bf16, \ cinn::common::raw_uint16_to_bfloat16(0x7bff), \ bfloat16, \ ##__VA_ARGS__) __device__ inline bfloat16 cinn_sum_bf16(const bfloat16 left, const bfloat16 right) { return left + right; } __device__ inline bfloat16 cinn_prod_bf16(const bfloat16 left, const bfloat16 right) { return left * right; } __device__ inline bfloat16 cinn_max_bf16(const bfloat16 left, const bfloat16 right) { return max(left, right); } __device__ inline bfloat16 cinn_min_bf16(const bfloat16 left, const bfloat16 right) { return min(left, right); } #endif #ifdef CINN_CUDA_FP16 #define EXPAND_REDUCE_FP16_MACRO(MACRO, ...) \ MACRO(sum_fp16, float16(0.0), float16, ##__VA_ARGS__) \ MACRO(prod_fp16, float16(1.0), float16, ##__VA_ARGS__) \ MACRO(max_fp16, CINN_FP16_MIN, float16, ##__VA_ARGS__) \ MACRO(min_fp16, CINN_FP16_MAX, float16, ##__VA_ARGS__) __device__ inline float16 cinn_sum_fp16(const float16 left, const float16 right) { return left + right; } __device__ inline float16 cinn_prod_fp16(const float16 left, const float16 right) { return left * right; } __device__ inline float16 cinn_max_fp16(const float16 left, const float16 right) { return max(left, right); } __device__ inline float16 cinn_min_fp16(const float16 left, const float16 right) { return min(left, right); } #endif #define EXPAND_REDUCE_FP64_MACRO(MACRO, ...) \ MACRO(sum_fp64, 0.0, double, ##__VA_ARGS__) \ MACRO(prod_fp64, 1.0, double, ##__VA_ARGS__) \ MACRO(max_fp64, -CINN_FP64_MAX, double, ##__VA_ARGS__) \ MACRO(min_fp64, CINN_FP64_MAX, double, ##__VA_ARGS__) \ MACRO(sum_welford_fp64, \ welford_fp64(0.0, 0.0, 0.0), \ welford_fp64, \ ##__VA_ARGS__) __device__ inline double cinn_sum_fp64(const double left, const double right) { return left + right; } __device__ inline double cinn_prod_fp64(const double left, const double right) { return left * right; } __device__ inline double cinn_max_fp64(const double left, const double right) { return max(left, right); } __device__ inline double cinn_min_fp64(const double left, const double right) { return min(left, right); } WELFORD_PARALLEL_COMBINE_MACRO(double, fp64) #undef WELFORD_PARALLEL_COMBINE_MACRO #define EXPAND_REDUCE_BOOL_MACRO(MACRO, ...) \ MACRO(all, true, bool, ##__VA_ARGS__) \ MACRO(any, false, bool, ##__VA_ARGS__) __device__ inline bool cinn_all(const bool left, const bool right) { return left && right; } __device__ inline bool cinn_any(const bool left, const bool right) { return left || right; } #define CINN_WARP_SHUFFLE_INTERNAL_IMPL(REDUCE_TYPE, INITIAL_VALUE, DTYPE) \ __device__ inline DTYPE cinn_warp_shuffle_##REDUCE_TYPE##_internal( \ const DTYPE value) { \ DTYPE tmp_val = value; \ unsigned int mask = __activemask(); \ unsigned int lane = __popc(mask); \ if (lane < 32) { \ for (int offset = 16; offset > 0; offset >>= 1) { \ DTYPE shfl_res = __shfl_down_sync(mask, tmp_val, offset); \ if ((threadIdx.x & 0x1f) + offset >= lane) { \ shfl_res = (DTYPE)(INITIAL_VALUE); \ } \ tmp_val = cinn_##REDUCE_TYPE(tmp_val, shfl_res); \ } \ } else { \ for (int offset = 16; offset > 0; offset >>= 1) { \ tmp_val = cinn_##REDUCE_TYPE(tmp_val, \ __shfl_xor_sync(mask, tmp_val, offset)); \ } \ } \ return tmp_val; \ } EXPAND_REDUCE_INT32_MACRO(CINN_WARP_SHUFFLE_INTERNAL_IMPL) EXPAND_REDUCE_INT64_MACRO(CINN_WARP_SHUFFLE_INTERNAL_IMPL) EXPAND_REDUCE_FP32_MACRO(CINN_WARP_SHUFFLE_INTERNAL_IMPL) EXPAND_REDUCE_FP64_MACRO(CINN_WARP_SHUFFLE_INTERNAL_IMPL) EXPAND_REDUCE_BOOL_MACRO(CINN_WARP_SHUFFLE_INTERNAL_IMPL) EXPAND_ARGIDX_OP_ALL_DTYPE_ITYPE_MACRO(CINN_WARP_SHUFFLE_INTERNAL_IMPL) #ifdef CINN_CUDA_BF16 EXPAND_REDUCE_BF16_MACRO(CINN_WARP_SHUFFLE_INTERNAL_IMPL) #endif #ifdef CINN_CUDA_FP16 EXPAND_REDUCE_FP16_MACRO(CINN_WARP_SHUFFLE_INTERNAL_IMPL) #endif #undef CINN_WARP_SHUFFLE_INTERNAL_IMPL #define CINN_BLOCK_REDUCE_IMPL(DTYPE, cinn_warp_shuffle_internal) \ DTYPE tmp_val = cinn_warp_shuffle_internal(value); \ if (return_warp || blockDim.x <= 32) { \ return tmp_val; \ } \ __syncthreads(); \ if (threadIdx.x % 32 == 0) { \ shm[threadIdx.x / 32] = tmp_val; \ } \ __syncthreads(); \ if (threadIdx.x < (blockDim.x + 31) / 32) { \ tmp_val = cinn_warp_shuffle_internal(shm[threadIdx.x]); \ if (threadIdx.x == 0) { \ shm[0] = tmp_val; \ } \ } \ __syncthreads(); \ return shm[0]; #define CINN_BLOCK_REDUCE_MACRO(REDUCE_TYPE, INITIAL_VALUE, DTYPE) \ __device__ inline DTYPE cinn_block_reduce_##REDUCE_TYPE( \ const DTYPE value, DTYPE *shm, bool return_warp = false) { \ CINN_BLOCK_REDUCE_IMPL(DTYPE, cinn_warp_shuffle_##REDUCE_TYPE##_internal); \ } EXPAND_REDUCE_INT32_MACRO(CINN_BLOCK_REDUCE_MACRO) EXPAND_REDUCE_INT64_MACRO(CINN_BLOCK_REDUCE_MACRO) EXPAND_REDUCE_FP32_MACRO(CINN_BLOCK_REDUCE_MACRO) EXPAND_REDUCE_FP64_MACRO(CINN_BLOCK_REDUCE_MACRO) EXPAND_REDUCE_BOOL_MACRO(CINN_BLOCK_REDUCE_MACRO) EXPAND_ARGIDX_OP_ALL_DTYPE_ITYPE_MACRO(CINN_BLOCK_REDUCE_MACRO) #ifdef CINN_CUDA_BF16 EXPAND_REDUCE_BF16_MACRO(CINN_BLOCK_REDUCE_MACRO) #endif #ifdef CINN_CUDA_FP16 EXPAND_REDUCE_FP16_MACRO(CINN_BLOCK_REDUCE_MACRO) #endif #undef CINN_BLOCK_REDUCE_IMPL #undef CINN_BLOCK_REDUCE_MACRO #define CINN_DISCRETE_REDUCE_IMPL(REDUCE_TYPE, value) \ int tid = threadIdx.y * blockDim.x + threadIdx.x; \ __syncthreads(); \ shm[tid] = value; \ __syncthreads(); \ for (int offset = blockDim.y / 2; offset > 0; offset >>= 1) { \ if (threadIdx.y < offset) { \ shm[tid] = cinn_##REDUCE_TYPE(shm[tid], shm[tid + offset * blockDim.x]); \ } \ __syncthreads(); \ } \ return shm[threadIdx.x]; #define CINN_DISCRETE_REDUCE_MACRO(REDUCE_TYPE, INITIAL_VALUE, DTYPE) \ __device__ inline DTYPE cinn_discrete_reduce_##REDUCE_TYPE( \ const DTYPE value, DTYPE *shm) { \ CINN_DISCRETE_REDUCE_IMPL(REDUCE_TYPE, value); \ } EXPAND_REDUCE_INT32_MACRO(CINN_DISCRETE_REDUCE_MACRO) EXPAND_REDUCE_INT64_MACRO(CINN_DISCRETE_REDUCE_MACRO) EXPAND_REDUCE_FP32_MACRO(CINN_DISCRETE_REDUCE_MACRO) EXPAND_REDUCE_FP64_MACRO(CINN_DISCRETE_REDUCE_MACRO) EXPAND_REDUCE_BOOL_MACRO(CINN_DISCRETE_REDUCE_MACRO) EXPAND_ARGIDX_OP_ALL_DTYPE_ITYPE_MACRO(CINN_DISCRETE_REDUCE_MACRO) #ifdef CINN_CUDA_BF16 EXPAND_REDUCE_BF16_MACRO(CINN_DISCRETE_REDUCE_MACRO) #endif #ifdef CINN_CUDA_FP16 EXPAND_REDUCE_FP16_MACRO(CINN_DISCRETE_REDUCE_MACRO) #endif #undef CINN_DISCRETE_REDUCE_IMPL #undef CINN_DISCRETE_REDUCE_MACRO #define CINN_GRID_REDUCE_IMPL(REDUCE_TYPE, init_value, DTYPE) \ cooperative_groups::this_grid().sync(); \ DTYPE tmp_val = init_value; \ for (int y = 0; y < gridDim.y; y++) { \ tmp_val = \ cinn_##REDUCE_TYPE(tmp_val, mem[y * spatial_size + spatial_index]); \ } \ return tmp_val; #define CINN_GRID_REDUCE_MACRO(REDUCE_TYPE, INITIAL_VALUE, DTYPE) \ __device__ inline DTYPE cinn_grid_reduce_##REDUCE_TYPE( \ const DTYPE *mem, int spatial_size, int spatial_index) { \ CINN_GRID_REDUCE_IMPL(REDUCE_TYPE, (DTYPE)(INITIAL_VALUE), DTYPE); \ } EXPAND_REDUCE_INT32_MACRO(CINN_GRID_REDUCE_MACRO) EXPAND_REDUCE_INT64_MACRO(CINN_GRID_REDUCE_MACRO) EXPAND_REDUCE_FP32_MACRO(CINN_GRID_REDUCE_MACRO) EXPAND_REDUCE_FP64_MACRO(CINN_GRID_REDUCE_MACRO) EXPAND_REDUCE_BOOL_MACRO(CINN_GRID_REDUCE_MACRO) EXPAND_ARGIDX_OP_ALL_DTYPE_ITYPE_MACRO(CINN_GRID_REDUCE_MACRO) #ifdef CINN_CUDA_BF16 EXPAND_REDUCE_BF16_MACRO(CINN_GRID_REDUCE_MACRO) #endif #ifdef CINN_CUDA_FP16 EXPAND_REDUCE_FP16_MACRO(CINN_GRID_REDUCE_MACRO) #endif #undef CINN_GRID_REDUCE_IMPL #undef CINN_GRID_REDUCE_MACRO #undef EXPAND_REDUCE_INT32_MACRO #undef EXPAND_REDUCE_INT64_MACRO #undef EXPAND_REDUCE_FP32_MACRO #undef EXPAND_REDUCE_FP64_MACRO #undef EXPAND_REDUCE_BOOL_MACRO #undef EXPAND_ARGIDX_OP_ALL_DTYPE_ITYPE_MACRO #undef EXPAND_ARGIDX_OP_ALL_DTYPE_MACRO #undef EXPAND_ARGIDX_OP_MACRO #undef EXPAND_ARGIDX_OP_MACRO_IMPL #ifdef CINN_CUDA_BF16 #undef EXPAND_REDUCE_BF16_MACRO #endif #ifdef CINN_CUDA_FP16 #undef EXPAND_REDUCE_FP16_MACRO #endif // *************************************************************** // // other function #define __cinn_cuda_find_kernel(buf, size, num, begin, stride) \ do { \ for (int i = (size - 1) * stride + begin; i >= begin; i -= stride) { \ if (buf[i] == num) return (i - begin) / stride; \ } \ return -1; \ } while (0) __device__ inline int cinn_cuda_find_int(const int *buf, int size, int num) { __cinn_cuda_find_kernel(buf, size, num, 0, 1); } __device__ inline int cinn_cuda_find_float(const float *buf, int size, float num) { __cinn_cuda_find_kernel(buf, size, num, 0, 1); } __device__ inline int cinn_cuda_find_int_nd( const int *buf, int size, int num, int begin, int stride) { __cinn_cuda_find_kernel(buf, size, num, begin, stride); } __device__ inline int cinn_cuda_find_float_nd( const float *buf, int size, float num, int begin, int stride) { __cinn_cuda_find_kernel(buf, size, num, begin, stride); } #undef __cinn_cuda_find_kernel __device__ inline int cinn_nvgpu_next_smallest_int32( int *buf, int size, int num, int begin, int stride) { int id = -1; for (int i = begin; i < begin + size * stride; i += stride) { if (id == -1 || buf[i] < buf[id]) { id = i; } } if (id != -1) { buf[id] = CINN_INT32_MAX; return (id - begin) / stride; } return -1; } #define __cinn_cuda_find_from_kernel(buf, size, num, begin) \ do { \ for (int i = begin; i < size; ++i) { \ if (buf[i] == num) return i; \ } \ return -1; \ } while (0) __device__ inline int cinn_cuda_find_int_from(const int *buf, int size, int num, int begin) { __cinn_cuda_find_from_kernel(buf, size, num, begin); } __device__ inline int cinn_cuda_find_float_from(const float *buf, int size, float num, int begin) { __cinn_cuda_find_from_kernel(buf, size, num, begin); } #undef __cinn_cuda_find_from_kernel #define CINN_NVGPU_LT_NUM(TYPE_SUFFIX, TYPE) \ __device__ inline int cinn_nvgpu_lt_num_##TYPE_SUFFIX(const TYPE *buf, \ const int size, \ const TYPE num, \ const int offset, \ const int stride) { \ int out = 0; \ for (int i = (size - 1) * stride + offset; i >= offset; i -= stride) { \ if (buf[i] < num) out++; \ } \ return out; \ } CINN_NVGPU_LT_NUM(fp32, float) CINN_NVGPU_LT_NUM(fp64, double) CINN_NVGPU_LT_NUM(uint8, uint8_t) CINN_NVGPU_LT_NUM(int16, int16_t) CINN_NVGPU_LT_NUM(int32, int) CINN_NVGPU_LT_NUM(int64, int64_t) #ifdef CINN_CUDA_FP16 CINN_NVGPU_LT_NUM(fp16, float16) #endif #undef CINN_NVGPU_LT_NUM #define CINN_NVGPU_GT_NUM(TYPE_SUFFIX, TYPE) \ __device__ inline int cinn_nvgpu_gt_num_##TYPE_SUFFIX(const TYPE *buf, \ const int size, \ const TYPE num, \ const int offset, \ const int stride) { \ int out = 0; \ for (int i = (size - 1) * stride + offset; i >= offset; i -= stride) { \ if (buf[i] > num) out++; \ } \ return out; \ } CINN_NVGPU_GT_NUM(fp32, float) CINN_NVGPU_GT_NUM(fp64, double) CINN_NVGPU_GT_NUM(uint8, uint8_t) CINN_NVGPU_GT_NUM(int16, int16_t) CINN_NVGPU_GT_NUM(int32, int) CINN_NVGPU_GT_NUM(int64, int64_t) #ifdef CINN_CUDA_FP16 CINN_NVGPU_GT_NUM(fp16, float16) #endif #undef CINN_NVGPU_GT_NUM #define CINN_NVGPU_INDEX_ADD(TYPE_SUFFIX, TYPE) \ __device__ inline TYPE cinn_nvgpu_index_add_##TYPE_SUFFIX( \ const TYPE x, \ const int axis_indice, \ const TYPE *__restrict__ y, \ const int offset, \ const int stride, \ const int *__restrict__ index, \ const int index_size) { \ TYPE res = x; \ int idx = -1; \ do { \ idx = cinn_cuda_find_int_from(index, index_size, axis_indice, idx + 1); \ if (idx >= 0) { \ res += y[offset + idx * stride]; \ } \ } while (idx != -1); \ return res; \ } CINN_NVGPU_INDEX_ADD(bool, bool) CINN_NVGPU_INDEX_ADD(int8, int8_t) CINN_NVGPU_INDEX_ADD(int32, int32_t) CINN_NVGPU_INDEX_ADD(int64, int64_t) CINN_NVGPU_INDEX_ADD(fp32, float) CINN_NVGPU_INDEX_ADD(fp64, double) #ifdef CINN_CUDA_FP16 CINN_NVGPU_INDEX_ADD(fp16, float16) #endif #undef CINN_CUDA_INDEX_ADD #define CINN_ENTAIL_LOOP_CONDITION(__loop_var, __cond, __stride) \ } \ for (decltype(__stride) __loop_var = 0; __cond; __loop_var += __stride) { __device__ int cinn_cuda_resize_bilinear(const int *buf, const int c_size, const int in_h, const int in_w, const int out_h, const int out_w, const int n, const int c, const int y, const int x) { float scale_y = static_cast(in_h) / out_h; float scale_x = static_cast(in_w) / out_w; float in_y = (y + 0.5F) * scale_y - 0.5F; float in_x = (x + 0.5F) * scale_x - 0.5F; int in_y_int = static_cast(FN_FP32(floor)(in_y)); int in_x_int = static_cast(FN_FP32(floor)(in_x)); float y_lerp = in_y - in_y_int; float x_lerp = in_x - in_x_int; float p[2][2]; for (int i = 0; i < 2; ++i) { for (int j = 0; j < 2; ++j) { int near_y = in_y_int + i; int near_x = in_x_int + j; near_y = FN_INT32(max)(FN_INT32(min)(near_y, in_h - 1), 0); near_x = FN_INT32(max)(FN_INT32(min)(near_x, in_w - 1), 0); p[i][j] = buf[n * c_size * in_h * in_w + c * in_h * in_w + near_y * in_w + near_x]; } } float top = p[0][0] * (1.0F - x_lerp) + p[0][1] * x_lerp; float bottom = p[1][0] * (1.0F - x_lerp) + p[1][1] * x_lerp; float value = top * (1.0F - y_lerp) + bottom * y_lerp; return value; } __device__ int cinn_cuda_resize_bicubic(const int *buf, const int c_size, const int in_h, const int in_w, const int out_h, const int out_w, const int n, const int c, const int y, const int x) { float scale_y = static_cast(in_h) / out_h; float scale_x = static_cast(in_w) / out_w; float in_y = (y + 0.5F) * scale_y - 0.5F; float in_x = (x + 0.5F) * scale_x - 0.5F; int in_y_int = static_cast(cinn_nvgpu_floor_fp32(in_y)); int in_x_int = static_cast(cinn_nvgpu_floor_fp32(in_x)); float y_fract = in_y - cinn_nvgpu_floor_fp32(in_y); float x_fract = in_x - cinn_nvgpu_floor_fp32(in_x); float p[4][4]; for (int i = 0; i < 4; ++i) { for (int j = 0; j < 4; ++j) { int near_y = in_y_int + i - 1; int near_x = in_x_int + j - 1; near_y = FN_INT32(max)(FN_INT32(min)(near_y, in_h - 1), 0); near_x = FN_INT32(max)(FN_INT32(min)(near_x, in_w - 1), 0); p[i][j] = buf[n * c_size * in_h * in_w + c * in_h * in_w + near_y * in_w + near_x]; } } float alpha = -0.5F; float w[2][4]; for (int i = 0; i < 2; ++i) { float t = (i == 0 ? x_fract : y_fract); float t2 = t * t; float t3 = t * t * t; w[i][0] = alpha * (t3 - 2 * t2 + t); w[i][1] = (alpha + 2) * t3 - (3 + alpha) * t2 + 1; w[i][2] = -(alpha + 2) * t3 + (3 + 2 * alpha) * t2 - alpha * t; w[i][3] = -alpha * t3 + alpha * t2; } float col[4]; for (int i = 0; i < 4; ++i) { col[i] = 0.0F; for (int j = 0; j < 4; ++j) { col[i] += p[i][j] * w[0][j]; } } float value = 0.0F; for (int i = 0; i < 4; ++i) { value += col[i] * w[1][i]; } return value; } // *************************************************************** // // end of macro undef #undef CINN_UINT8_MIN #undef CINN_UINT8_MAX #undef CINN_INT16_MIN #undef CINN_INT16_MAX #undef CINN_INT32_MIN #undef CINN_INT32_MAX #undef CINN_INT64_MAX #undef CINN_INT64_MIN #undef CINN_FP32_MAX #undef CINN_FP64_MAX #undef CINN_FP16_MIN #undef CINN_FP16_MAX #undef FN_BOOL #undef FN_UINT8 #undef FN_INT8 #undef FN_INT16 #undef FN_FP32 #undef FN_FP64 #undef FN_INT32 #undef FN_INT64 #ifdef CINN_CUDA_BF16 #undef FN_BF16 #endif #ifdef CINN_CUDA_FP16 #undef FN_FP16 #endif }