sglang_v0.5.2/pytorch_2.8.0/third_party/XNNPACK/test/vbinary-microkernel-tester.h

470 lines
22 KiB
C++

// Copyright 2019 Google LLC
//
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree.
#pragma once
#include <algorithm>
#include <cassert>
#include <cmath>
#include <cstddef>
#include <cstdint>
#include <cstdlib>
#include <type_traits>
#include <gtest/gtest.h>
#include "xnnpack/isa-checks.h"
#include "xnnpack/math.h"
#include "xnnpack/microfnptr.h"
using std::copysign;
inline xnn_float16 copysign(xnn_float16 a, xnn_float16 b) {
return (xnn_float16)std::copysign((float)a, (float)b);
}
class VBinaryMicrokernelTester {
public:
enum class OpType {
Add,
CopySign,
RCopySign,
Div,
RDiv,
Max,
Min,
Mul,
Sub,
RSub,
SqrDiff,
Prelu,
RPrelu,
};
template <typename A, typename B, typename Result>
void reference_op_impl(const A* a, const B* b, Result* result, size_t n, OpType op_type) const {
size_t stride_b = broadcast_b() ? 0 : 1;
for (size_t i = 0; i < n; ++i) {
switch (op_type) {
case OpType::Add:
result[i] = a[i] + b[i * stride_b];
break;
case OpType::CopySign:
result[i] = copysign(a[i], b[i * stride_b]);
break;
case OpType::RCopySign:
result[i] = copysign(b[i * stride_b], a[i]);
break;
case OpType::Div:
result[i] = a[i] / b[i * stride_b];
break;
case OpType::RDiv:
result[i] = b[i * stride_b] / a[i];
break;
case OpType::Max:
result[i] = std::max(a[i], b[i * stride_b]);
break;
case OpType::Min:
result[i] = std::min(a[i], b[i * stride_b]);
break;
case OpType::Mul:
if (std::is_integral<A>::value && std::is_integral<B>::value) {
// Overflow is the expected behavior.
int64_t result_wide = static_cast<int64_t>(a[i]) * static_cast<int64_t>(b[i * stride_b]);
result[i] = result_wide & ((static_cast<int64_t>(1) << (sizeof(Result) * 8)) - 1);
} else {
result[i] = a[i] * b[i * stride_b];
}
break;
case OpType::Prelu:
result[i] = a[i] < 0 ? static_cast<Result>(a[i] * b[i * stride_b]) : static_cast<Result>(a[i]);
break;
case OpType::RPrelu:
result[i] = b[i * stride_b] < 0 ? static_cast<Result>(a[i] * b[i * stride_b]) : static_cast<Result>(b[i * stride_b]);
break;
case OpType::SqrDiff: {
const double diff = static_cast<double>(a[i]) - static_cast<double>(b[i * stride_b]);
result[i] = diff * diff;
break;
}
case OpType::Sub:
result[i] = a[i] - b[i * stride_b];
break;
case OpType::RSub:
result[i] = b[i * stride_b] - a[i];
break;
}
}
}
VBinaryMicrokernelTester& batch_size(size_t batch_size) {
assert(batch_size != 0);
this->batch_size_ = batch_size;
return *this;
}
size_t batch_size() const { return this->batch_size_; }
VBinaryMicrokernelTester& inplace_a(bool inplace_a) {
this->inplace_a_ = inplace_a;
return *this;
}
bool inplace_a() const { return this->inplace_a_; }
VBinaryMicrokernelTester& inplace_b(bool inplace_b) {
this->inplace_b_ = inplace_b;
return *this;
}
bool inplace_b() const { return this->inplace_b_; }
VBinaryMicrokernelTester& broadcast_b(bool broadcast_b) {
this->broadcast_b_ = broadcast_b;
return *this;
}
bool broadcast_b() const { return this->broadcast_b_; }
VBinaryMicrokernelTester& a_scale(float a_scale) {
assert(a_scale > 0.0f);
assert(std::isnormal(a_scale));
this->a_scale_ = a_scale;
return *this;
}
float a_scale() const { return this->a_scale_; }
VBinaryMicrokernelTester& a_zero_point(uint8_t a_zero_point) {
this->a_zero_point_ = a_zero_point;
return *this;
}
uint8_t a_zero_point() const { return this->a_zero_point_; }
VBinaryMicrokernelTester& b_scale(float b_scale) {
assert(b_scale > 0.0f);
assert(std::isnormal(b_scale));
this->b_scale_ = b_scale;
return *this;
}
float b_scale() const { return this->b_scale_; }
VBinaryMicrokernelTester& b_zero_point(uint8_t b_zero_point) {
this->b_zero_point_ = b_zero_point;
return *this;
}
uint8_t b_zero_point() const { return this->b_zero_point_; }
VBinaryMicrokernelTester& y_scale(float y_scale) {
assert(y_scale > 0.0f);
assert(std::isnormal(y_scale));
this->y_scale_ = y_scale;
return *this;
}
float y_scale() const { return this->y_scale_; }
VBinaryMicrokernelTester& y_zero_point(uint8_t y_zero_point) {
this->y_zero_point_ = y_zero_point;
return *this;
}
uint8_t y_zero_point() const { return this->y_zero_point_; }
VBinaryMicrokernelTester& qmin(uint8_t qmin) {
this->qmin_ = qmin;
return *this;
}
uint8_t qmin() const { return this->qmin_; }
VBinaryMicrokernelTester& qmax(uint8_t qmax) {
this->qmax_ = qmax;
return *this;
}
uint8_t qmax() const { return this->qmax_; }
VBinaryMicrokernelTester& iterations(size_t iterations) {
this->iterations_ = iterations;
return *this;
}
size_t iterations() const { return this->iterations_; }
void Test(xnn_f16_vbinary_ukernel_fn vbinary, OpType op_type,
xnn_init_f16_default_params_fn init_params = nullptr) const;
void Test(xnn_f32_vbinary_ukernel_fn vbinary, OpType op_type,
xnn_init_f32_default_params_fn init_params = nullptr) const;
void Test(xnn_qu8_vadd_minmax_ukernel_fn vadd_minmax,
xnn_init_qu8_add_minmax_params_fn init_params) const;
void Test(xnn_qu8_vmul_minmax_ukernel_fn vmul_minmax,
xnn_init_qu8_mul_minmax_params_fn init_params) const;
void Test(xnn_qs8_vadd_minmax_ukernel_fn vadd_minmax,
xnn_init_qs8_add_minmax_params_fn init_params) const;
void Test(xnn_qs8_vmul_minmax_ukernel_fn vmul_minmax,
xnn_init_qs8_mul_minmax_params_fn init_params) const;
private:
size_t batch_size_{1};
bool inplace_a_{false};
bool inplace_b_{false};
bool broadcast_b_{false};
float a_scale_{0.75f};
float b_scale_{1.25f};
float y_scale_{0.96875f};
uint8_t a_zero_point_{121};
uint8_t b_zero_point_{127};
uint8_t y_zero_point_{133};
uint8_t qmin_{0};
uint8_t qmax_{255};
size_t iterations_{15};
};
#define XNN_TEST_BINARY_BATCH_EQ(ukernel, arch_flags, batch_tile, is_binaryc, \
datatype, ...) \
TEST(ukernel, batch_eq) { \
TEST_REQUIRES_ARCH_FLAGS(arch_flags); \
const size_t batch_scale = get_batch_scale<datatype>(); \
VBinaryMicrokernelTester() \
.batch_size(batch_tile* batch_scale) \
.broadcast_b(is_binaryc) \
.Test(__VA_ARGS__); \
}
#define XNN_TEST_BINARY_BATCH_DIV(ukernel, arch_flags, batch_tile, is_binaryc, \
datatype, ...) \
TEST(ukernel, batch_div) { \
TEST_REQUIRES_ARCH_FLAGS(arch_flags); \
const size_t batch_scale = get_batch_scale<datatype>(); \
if (batch_tile == 1 && batch_scale == 1) return; \
for (size_t batch_size = batch_tile * batch_scale * 2; \
batch_size < batch_tile * batch_scale * 10; \
batch_size += batch_tile * batch_scale) { \
VBinaryMicrokernelTester() \
.batch_size(batch_size) \
.broadcast_b(is_binaryc) \
.Test(__VA_ARGS__); \
} \
}
#define XNN_TEST_BINARY_BATCH_LT(ukernel, arch_flags, batch_tile, is_binaryc, \
datatype, ...) \
TEST(ukernel, batch_lt) { \
TEST_REQUIRES_ARCH_FLAGS(arch_flags); \
const size_t batch_scale = get_batch_scale<datatype>(); \
if (batch_tile == 1 && batch_scale == 1) return; \
for (size_t batch_size = batch_scale; \
batch_size < batch_tile * batch_scale; batch_size++) { \
VBinaryMicrokernelTester() \
.batch_size(batch_size) \
.broadcast_b(is_binaryc) \
.Test(__VA_ARGS__); \
} \
}
#define XNN_TEST_BINARY_BATCH_GT(ukernel, arch_flags, batch_tile, is_binaryc, \
datatype, ...) \
TEST(ukernel, batch_gt) { \
TEST_REQUIRES_ARCH_FLAGS(arch_flags); \
const size_t batch_scale = get_batch_scale<datatype>(); \
const size_t batch_end = batch_tile == 1 ? 10 : batch_tile * 2; \
const size_t batch_step = batch_scale == 1 ? 1 : batch_tile * 2; \
for (size_t batch_size = batch_tile + 1; batch_size < batch_end; \
batch_size += batch_step) { \
VBinaryMicrokernelTester() \
.batch_size(batch_size) \
.broadcast_b(is_binaryc) \
.Test(__VA_ARGS__); \
} \
}
#define XNN_TEST_BINARY_INPLACE_A(ukernel, arch_flags, batch_tile, is_binaryc, \
datatype, ...) \
TEST(ukernel, inplace_a) { \
TEST_REQUIRES_ARCH_FLAGS(arch_flags); \
const size_t batch_scale = get_batch_scale<datatype>(); \
for (size_t batch_size = 1; batch_size <= batch_tile * batch_scale * 5; \
batch_size += std::max(1, batch_tile - 1) * batch_scale) { \
VBinaryMicrokernelTester() \
.batch_size(batch_size) \
.inplace_a(true) \
.broadcast_b(is_binaryc) \
.Test(__VA_ARGS__); \
} \
}
#define XNN_TEST_BINARY_INPLACE_B(ukernel, arch_flags, batch_tile, is_binaryc, \
datatype, ...) \
TEST(ukernel, inplace_b) { \
TEST_REQUIRES_ARCH_FLAGS(arch_flags); \
const size_t batch_scale = get_batch_scale<datatype>(); \
for (size_t batch_size = 1; batch_size <= batch_tile * batch_scale * 5; \
batch_size += std::max(1, batch_tile - 1) * batch_scale) { \
VBinaryMicrokernelTester() \
.batch_size(batch_size) \
.inplace_b(true) \
.broadcast_b(is_binaryc) \
.Test(__VA_ARGS__); \
} \
}
#define XNN_TEST_BINARY_INPLACE_A_AND_B(ukernel, arch_flags, batch_tile, \
is_binaryc, datatype, ...) \
TEST(ukernel, inplace_a_and_b) { \
TEST_REQUIRES_ARCH_FLAGS(arch_flags); \
const size_t batch_scale = get_batch_scale<datatype>(); \
for (size_t batch_size = 1; batch_size <= batch_tile * batch_scale * 5; \
batch_size += std::max(1, batch_tile - 1) * batch_scale) { \
VBinaryMicrokernelTester() \
.batch_size(batch_size) \
.inplace_a(true) \
.inplace_b(true) \
.broadcast_b(is_binaryc) \
.Test(__VA_ARGS__); \
} \
}
#define XNN_TEST_BINARY_A_ZERO_POINT(ukernel, arch_flags, batch_tile, \
is_binaryc, datatype, ...) \
TEST(ukernel, a_zero_point) { \
TEST_REQUIRES_ARCH_FLAGS(arch_flags); \
const size_t batch_scale = get_batch_scale<datatype>(); \
for (size_t batch_size = 1; batch_size <= batch_tile * batch_scale * 5; \
batch_size += std::max(1, batch_tile - 1) * batch_scale) { \
for (int32_t a_zero_point = -128; a_zero_point <= 127; \
a_zero_point += 51) { \
VBinaryMicrokernelTester() \
.batch_size(batch_size) \
.a_zero_point(a_zero_point) \
.broadcast_b(is_binaryc) \
.Test(__VA_ARGS__); \
} \
} \
}
#define XNN_TEST_BINARY_B_ZERO_POINT(ukernel, arch_flags, batch_tile, \
is_binaryc, datatype, ...) \
TEST(ukernel, b_zero_point) { \
TEST_REQUIRES_ARCH_FLAGS(arch_flags); \
const size_t batch_scale = get_batch_scale<datatype>(); \
for (size_t batch_size = 1; batch_size <= batch_tile * batch_scale * 5; \
batch_size += std::max(1, batch_tile - 1) * batch_scale) { \
for (int32_t b_zero_point = -128; b_zero_point <= 127; \
b_zero_point += 51) { \
VBinaryMicrokernelTester() \
.batch_size(batch_size) \
.b_zero_point(b_zero_point) \
.broadcast_b(is_binaryc) \
.Test(__VA_ARGS__); \
} \
} \
}
#define XNN_TEST_BINARY_Y_ZERO_POINT(ukernel, arch_flags, batch_tile, \
is_binaryc, datatype, ...) \
TEST(ukernel, y_zero_point) { \
TEST_REQUIRES_ARCH_FLAGS(arch_flags); \
const size_t batch_scale = get_batch_scale<datatype>(); \
for (size_t batch_size = 1; batch_size <= batch_tile * batch_scale * 5; \
batch_size += std::max(1, batch_tile - 1) * batch_scale) { \
for (int32_t y_zero_point = -128; y_zero_point <= 127; \
y_zero_point += 51) { \
VBinaryMicrokernelTester() \
.batch_size(batch_size) \
.y_zero_point(y_zero_point) \
.broadcast_b(is_binaryc) \
.Test(__VA_ARGS__); \
} \
} \
}
#define XNN_TEST_BINARY_A_SCALE(ukernel, arch_flags, batch_tile, is_binaryc, \
datatype, ...) \
TEST(ukernel, a_scale) { \
TEST_REQUIRES_ARCH_FLAGS(arch_flags); \
const size_t batch_scale = get_batch_scale<datatype>(); \
for (size_t batch_size = 1; batch_size <= batch_tile * batch_scale * 5; \
batch_size += std::max(1, batch_tile - 1) * batch_scale) { \
for (float a_scale = 0.1f; a_scale <= 10.0f; a_scale *= 3.14f) { \
VBinaryMicrokernelTester() \
.batch_size(batch_size) \
.a_scale(a_scale) \
.broadcast_b(is_binaryc) \
.Test(__VA_ARGS__); \
} \
} \
}
#define XNN_TEST_BINARY_B_SCALE(ukernel, arch_flags, batch_tile, is_binaryc, \
datatype, ...) \
TEST(ukernel, b_scale) { \
TEST_REQUIRES_ARCH_FLAGS(arch_flags); \
const size_t batch_scale = get_batch_scale<datatype>(); \
for (size_t batch_size = 1; batch_size <= batch_tile * batch_scale * 5; \
batch_size += std::max(1, batch_tile - 1) * batch_scale) { \
for (float b_scale = 0.1f; b_scale <= 10.0f; b_scale *= 3.14f) { \
VBinaryMicrokernelTester() \
.batch_size(batch_size) \
.b_scale(b_scale) \
.broadcast_b(is_binaryc) \
.Test(__VA_ARGS__); \
} \
} \
}
#define XNN_TEST_BINARY_Y_SCALE(ukernel, arch_flags, batch_tile, is_binaryc, \
datatype, ...) \
TEST(ukernel, y_scale) { \
TEST_REQUIRES_ARCH_FLAGS(arch_flags); \
const size_t batch_scale = get_batch_scale<datatype>(); \
for (size_t batch_size = 1; batch_size <= batch_tile * batch_scale * 5; \
batch_size += std::max(1, batch_tile - 1) * batch_scale) { \
for (float y_scale = 0.1f; y_scale <= 10.0f; y_scale *= 3.14f) { \
VBinaryMicrokernelTester() \
.batch_size(batch_size) \
.y_scale(y_scale) \
.broadcast_b(is_binaryc) \
.Test(__VA_ARGS__); \
} \
} \
}
#define XNN_TEST_BINARY_QMIN(ukernel, arch_flags, batch_tile, is_binaryc, \
datatype, ...) \
TEST(ukernel, qmin) { \
TEST_REQUIRES_ARCH_FLAGS(arch_flags); \
const size_t batch_scale = get_batch_scale<datatype>(); \
for (size_t batch_size = 1; batch_size <= batch_tile * batch_scale * 5; \
batch_size += std::max(1, batch_tile - 1) * batch_scale) { \
VBinaryMicrokernelTester() \
.batch_size(batch_size) \
.qmin(128) \
.broadcast_b(is_binaryc) \
.Test(__VA_ARGS__); \
} \
}
#define XNN_TEST_BINARY_QMAX(ukernel, arch_flags, batch_tile, is_binaryc, \
datatype, ...) \
TEST(ukernel, qmax) { \
TEST_REQUIRES_ARCH_FLAGS(arch_flags); \
const size_t batch_scale = get_batch_scale<datatype>(); \
for (size_t batch_size = 1; batch_size <= batch_tile * batch_scale * 5; \
batch_size += std::max(1, batch_tile - 1) * batch_scale) { \
VBinaryMicrokernelTester() \
.batch_size(batch_size) \
.qmax(128) \
.broadcast_b(is_binaryc) \
.Test(__VA_ARGS__); \
} \
}