happyz
/
gemma.cpp
mirror of https://github.com/google/gemma.cpp.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity
gemma.cpp/gemma/ops_test.cc

709 lines
24 KiB
C++
Raw Blame History

// Copyright 2023 Google LLC
// SPDX-License-Identifier: Apache-2.0
//
// 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.
#include <memory>
#ifndef HWY_DISABLED_TARGETS
#define HWY_DISABLED_TARGETS HWY_SCALAR
#endif
#include <stddef.h>
#include <stdio.h>
#include <algorithm>
#include <array>
#include <cmath>
#include <random>
#include <vector>
#include "compression/compress.h"
#include "hwy/aligned_allocator.h"
#include "hwy/base.h"
#include "hwy/contrib/thread_pool/thread_pool.h"
// clang-format off
#undef HWY_TARGET_INCLUDE
#define HWY_TARGET_INCLUDE "gemma/ops_test.cc" //NOLINT
// clang-format on
#include "hwy/foreach_target.h" // IWYU pragma: keep
#include "hwy/highway.h"
#include "hwy/tests/test_util-inl.h"
// After highway.h
#include "gemma/ops.h"
HWY_BEFORE_NAMESPACE();
namespace gcpp {
namespace HWY_NAMESPACE {
namespace hn = hwy::HWY_NAMESPACE;
template <class Test>
struct ForeachCountAndMisalign {
template <typename T, class D>
HWY_NOINLINE void operator()(T /*unused*/, D d) const {
hwy::RandomState rng;
const size_t N = Lanes(d);
const size_t misalignments[3] = {0, N / 4, 3 * N / 5};
for (size_t count = 0; count < 2 * N; ++count) {
for (size_t ma : misalignments) {
for (size_t mb : misalignments) {
Test()(d, count, ma, mb, rng);
}
}
}
}
};
template <typename T>
T Random(hwy::RandomState& rng) {
const int32_t bits = static_cast<int32_t>(Random32(&rng)) & 1023;
const double val = (bits - 512) / 64.0;
// Clamp negative to zero for unsigned types.
return hwy::ConvertScalarTo<T>(
HWY_MAX(hwy::ConvertScalarTo<double>(hwy::LowestValue<T>()), val));
}
HWY_NOINLINE void SourceAddFrom(const float* HWY_RESTRICT other,
float* HWY_RESTRICT x, size_t size) {
for (size_t i = 0; i < size; ++i) {
x[i] += other[i];
}
}
HWY_NOINLINE void SourceMulBy(const float* HWY_RESTRICT other,
float* HWY_RESTRICT x, size_t size,
size_t max_pos) {
HWY_DASSERT(max_pos <= size);
for (size_t i = 0; i < max_pos; ++i) {
x[i] *= other[i];
}
}
HWY_NOINLINE void SourceMulByConst(float c, float* HWY_RESTRICT x, size_t size,
size_t max_pos) {
for (size_t i = 0; i < max_pos; ++i) {
x[i] *= c;
}
}
HWY_NOINLINE void SourceMulByConstAndAdd(float c, const float* HWY_RESTRICT x,
float* HWY_RESTRICT out, size_t size,
size_t max_pos) {
for (size_t i = 0; i < max_pos; ++i) {
out[i] += x[i] * c;
}
}
HWY_NOINLINE void SourceSoftmax(float* HWY_RESTRICT x, size_t size,
size_t mask_pos) {
HWY_DASSERT(size != 0);
HWY_DASSERT(mask_pos <= size);
float sum = 0.0;
const float maxval = *std::max_element(x, x + mask_pos);
for (size_t i = 0; i < mask_pos; ++i) {
x[i] = std::exp(x[i] - maxval);
sum += x[i];
}
const float scale = 1.0f / sum;
for (size_t i = 0; i < mask_pos; ++i) {
x[i] *= scale;
}
}
template <size_t k>
HWY_NOINLINE std::discrete_distribution<int> SourceCreateDistribution(
std::array<float, k>& top_k, float temperature) {
// re-normalize distribution
for (size_t i = 0; i < k; ++i) {
top_k[i] = exp(log(top_k[i]) / temperature);
}
float denominator = 0.0f;
for (size_t i = 0; i < k; ++i) {
denominator += top_k[i];
}
denominator = 1.0f / denominator;
MulByConst(denominator, top_k.data(), k);
return std::discrete_distribution<int>(std::begin(top_k), std::end(top_k));
}
struct TestAddFrom {
template <class D>
void operator()(D d, size_t count, size_t misalign_a, size_t misalign_b,
hwy::RandomState& rng) {
using T = hn::TFromD<D>;
hwy::AlignedFreeUniquePtr<T[]> px =
hwy::AllocateAligned<T>(HWY_MAX(1, misalign_a + count));
hwy::AlignedFreeUniquePtr<T[]> pe =
hwy::AllocateAligned<T>(HWY_MAX(1, misalign_a + count));
hwy::AlignedFreeUniquePtr<T[]> po =
hwy::AllocateAligned<T>(HWY_MAX(1, misalign_b + count));
HWY_ASSERT(px && pe && po);
T* x = px.get() + misalign_a;
T* e = pe.get() + misalign_a;
T* o = po.get() + misalign_b;
for (size_t i = 0; i < count; ++i) {
x[i] = Random<T>(rng);
e[i] = x[i];
o[i] = Random<T>(rng);
}
SourceAddFrom(o, e, count);
AddFrom(o, x, count);
hwy::AssertArraySimilar(e, x, count, hwy::TargetName(HWY_TARGET), __FILE__,
__LINE__);
}
};
struct TestMulBy {
template <class D>
void operator()(D d, size_t count, size_t misalign_a, size_t misalign_b,
hwy::RandomState& rng) {
using T = hn::TFromD<D>;
hwy::AlignedFreeUniquePtr<T[]> px =
hwy::AllocateAligned<T>(HWY_MAX(1, misalign_a + count));
hwy::AlignedFreeUniquePtr<T[]> pe =
hwy::AllocateAligned<T>(HWY_MAX(1, misalign_a + count));
hwy::AlignedFreeUniquePtr<T[]> po =
hwy::AllocateAligned<T>(HWY_MAX(1, misalign_b + count));
HWY_ASSERT(px && pe && po);
T* x = px.get() + misalign_a;
T* e = pe.get() + misalign_a;
T* o = po.get() + misalign_b;
for (size_t i = 0; i < count; ++i) {
x[i] = Random<T>(rng);
e[i] = x[i];
o[i] = Random<T>(rng);
}
SourceMulBy(o, e, count, count);
MulBy(o, x, count, count);
hwy::AssertArraySimilar(e, x, count, hwy::TargetName(HWY_TARGET), __FILE__,
__LINE__);
}
};
struct TestMulByConstAndAdd {
template <class D>
void operator()(D d, size_t count, size_t misalign_a, size_t misalign_b,
hwy::RandomState& rng) {
using T = hn::TFromD<D>;
hwy::AlignedFreeUniquePtr<T[]> px =
hwy::AllocateAligned<T>(HWY_MAX(1, misalign_a + count));
hwy::AlignedFreeUniquePtr<T[]> pe =
hwy::AllocateAligned<T>(HWY_MAX(1, misalign_a + count));
hwy::AlignedFreeUniquePtr<T[]> po =
hwy::AllocateAligned<T>(HWY_MAX(1, misalign_b + count));
HWY_ASSERT(px && pe && po);
T* x = px.get() + misalign_a;
T* e = pe.get() + misalign_a;
T* o = po.get() + misalign_b;
for (size_t i = 0; i < count; ++i) {
x[i] = Random<T>(rng);
e[i] = x[i];
o[i] = Random<T>(rng);
}
T constant = Random<T>(rng);
SourceMulByConstAndAdd(constant, o, e, count, count);
MulByConstAndAdd(constant, o, x, count, count);
hwy::AssertArraySimilar(e, x, count, hwy::TargetName(HWY_TARGET), __FILE__,
__LINE__);
}
};
struct TestMulByConst {
template <class D>
void operator()(D d, size_t count, size_t misalign_a, size_t misalign_b,
hwy::RandomState& rng) {
if (misalign_b == 0) return;
using T = hn::TFromD<D>;
hwy::AlignedFreeUniquePtr<T[]> px =
hwy::AllocateAligned<T>(HWY_MAX(1, misalign_a + count));
hwy::AlignedFreeUniquePtr<T[]> pe =
hwy::AllocateAligned<T>(HWY_MAX(1, misalign_a + count));
HWY_ASSERT(px && pe);
T* x = px.get() + misalign_a;
T* e = pe.get() + misalign_a;
for (size_t i = 0; i < count; ++i) {
x[i] = Random<T>(rng);
e[i] = x[i];
}
T constant = Random<T>(rng);
SourceMulByConst(constant, e, count, count);
MulByConst(constant, x, count, count);
hwy::AssertArraySimilar(e, x, count, hwy::TargetName(HWY_TARGET), __FILE__,
__LINE__);
}
};
struct TestSoftmax {
template <class D>
void operator()(D d, size_t count, size_t misalign_a, size_t misalign_b,
hwy::RandomState& rng) {
if (count == 0) return; // *Softmax would assert
if (misalign_b == 0) return;
using T = hn::TFromD<D>;
hwy::AlignedFreeUniquePtr<T[]> px =
hwy::AllocateAligned<T>(HWY_MAX(1, misalign_a + count));
hwy::AlignedFreeUniquePtr<T[]> pe =
hwy::AllocateAligned<T>(HWY_MAX(1, misalign_a + count));
HWY_ASSERT(px && pe);
T* x = px.get() + misalign_a;
T* e = pe.get() + misalign_a;
for (size_t i = 0; i < count; ++i) {
x[i] = Random<T>(rng);
e[i] = x[i];
}
SourceSoftmax(e, count, count);
Softmax(x, count, count);
T sum = 0.0f;
for (size_t i = 0; i < count; ++i) {
sum += x[i];
double rel = std::abs(x[i] - e[i]) / e[i];
ASSERT_LT(rel, 1e-6) << "Mismatch on coordinate " << i << " out of "
<< count;
}
ASSERT_NEAR(sum, 1.0, 1e-6);
}
};
template <size_t k>
struct TestCreateDistribution {
void operator()(hwy::RandomState& rng) {
std::array<float, k> x;
std::array<float, k> e;
for (size_t i = 0; i < k; ++i) {
x[i] = Random<float>(rng);
e[i] = x[i];
}
const float constant = Random<float>(rng);
auto expected = SourceCreateDistribution(e, constant);
auto output = create_distribution(x, constant);
AssertEqual(expected, output, hwy::TargetName(HWY_TARGET), __FILE__,
__LINE__);
}
};
void TestAllAddFrom() {
hn::ForPartialVectors<ForeachCountAndMisalign<TestAddFrom>>()(float());
}
void TestAllMulBy() {
hn::ForPartialVectors<ForeachCountAndMisalign<TestMulBy>>()(float());
}
void TestAllMulByConst() {
hn::ForPartialVectors<ForeachCountAndMisalign<TestMulByConst>>()(float());
}
void TestAllMulByConstAndAdd() {
hn::ForPartialVectors<ForeachCountAndMisalign<TestMulByConstAndAdd>>()(
float());
}
void TestAllSoftmax() {
hn::ForPartialVectors<ForeachCountAndMisalign<TestSoftmax>>()(float());
}
void TestAllCreateDistribution() {
TestCreateDistribution<2048>();
TestCreateDistribution<5000>();
}
template <typename MatT, size_t kOuter, size_t kInner>
CompressedArray<MatT, kOuter * kInner> GenerateMat(size_t offset,
hwy::ThreadPool& pool) {
gcpp::CompressWorkingSet ws;
CompressedArray<MatT, kOuter * kInner> mat;
std::array<float, kOuter * kInner> content;
const float scale = 1.0f / kInner;
pool.Run(0, kOuter, [&](const size_t i, size_t /*thread*/) {
for (size_t j = 0; j < kInner; j++) {
content[i * kInner + j] =
static_cast<float>((i * kInner + j + offset) * scale);
}
});
Compress(content, ws, mat, pool);
mat.set_scale(1.0f);
return mat;
}
template <typename MatT, size_t kOuter, size_t kInner>
CompressedArray<MatT, kOuter * kInner> GenerateZeroMat(hwy::ThreadPool& pool) {
gcpp::CompressWorkingSet ws;
CompressedArray<MatT, kOuter * kInner> mat;
std::array<MatT, kOuter * kInner> content;
pool.Run(0, kOuter, [&](const size_t i, size_t thread) {
hwy::ZeroBytes(&content[i * kInner], kInner * sizeof(content[0]));
});
Compress(content, ws, mat, pool);
mat.set_scale(1.0f);
return mat;
}
template <typename MatT, size_t kOuter, size_t kInner>
std::unique_ptr<CompressedArray<MatT, kOuter * kInner>> GenerateMatHeap(
size_t offset, hwy::ThreadPool& pool) {
gcpp::CompressWorkingSet ws;
std::unique_ptr<CompressedArray<MatT, kOuter * kInner>> mat =
std::unique_ptr<CompressedArray<MatT, kOuter * kInner>>(
new CompressedArray<MatT, kOuter * kInner>);
hwy::AlignedFreeUniquePtr<float[]> content =
hwy::AllocateAligned<float>(kOuter * kInner);
const float scale = 1.875f / (kInner * kOuter + offset);
pool.Run(0, kOuter, [&](const size_t i, size_t /*thread*/) {
for (size_t j = 0; j < kInner; j++) {
content[i * kInner + j] =
static_cast<float>((i * kInner + j + offset) * scale);
}
});
Compress(content.get(), kOuter * kInner, ws, kOuter * kInner, mat->data(), 0,
pool);
mat->set_scale(1.0f);
return mat;
}
template <typename MatT, size_t kOuter, size_t kInner>
std::unique_ptr<CompressedArray<MatT, kOuter * kInner>>
GenerateTransposeMatHeap(size_t offset, hwy::ThreadPool& pool) {
gcpp::CompressWorkingSet ws;
std::unique_ptr<CompressedArray<MatT, kOuter * kInner>> mat =
std::unique_ptr<CompressedArray<MatT, kOuter * kInner>>(
new CompressedArray<MatT, kOuter * kInner>);
hwy::AlignedFreeUniquePtr<float[]> content =
hwy::AllocateAligned<float>(kOuter * kInner);
const float scale = 1.875f / (kInner * kOuter + offset);
pool.Run(0, kOuter, [&](const size_t i, size_t /*thread*/) {
for (size_t j = 0; j < kInner; j++) {
content[j * kOuter + i] =
static_cast<float>((i * kInner + j + offset) * scale);
}
});
Compress(content.get(), kOuter * kInner, ws, kOuter * kInner, mat->data(), 0,
pool);
mat->set_scale(1.0f);
return mat;
}
template <typename MatT, size_t kOuter, size_t kInner>
std::unique_ptr<CompressedArray<MatT, kOuter * kInner>> GenerateZeroMatHeap(
hwy::ThreadPool& pool) {
gcpp::CompressWorkingSet ws;
std::unique_ptr<CompressedArray<MatT, kOuter * kInner>> mat =
std::unique_ptr<CompressedArray<MatT, kOuter * kInner>>(
new CompressedArray<MatT, kOuter * kInner>);
hwy::AlignedFreeUniquePtr<float[]> content =
hwy::AllocateAligned<float>(kOuter * kInner);
pool.Run(0, kOuter, [&](const size_t i, size_t thread) {
hwy::ZeroBytes(&content[i * kInner], kInner * sizeof(content[0]));
});
Compress(content.get(), kOuter * kInner, ws, kOuter * kInner, mat->data(), 0,
pool);
mat->set_scale(1.0f);
return mat;
}
template <size_t length>
hwy::AlignedFreeUniquePtr<float[]> GenerateVec(size_t offset) {
hwy::AlignedFreeUniquePtr<float[]> vec = hwy::AllocateAligned<float>(length);
HWY_ASSERT(vec);
for (size_t idx = 0; idx < length; idx++) {
vec[idx] = static_cast<float>(idx + offset);
}
return vec;
}
// A simple matrix multiplication. No optimization / tiling.
template <size_t kM, size_t kN, size_t kK>
hwy::AlignedFreeUniquePtr<float[]> SimpleMatMul(
const hwy::AlignedFreeUniquePtr<float[]>& a,
const hwy::AlignedFreeUniquePtr<float[]>& b) {
hwy::AlignedFreeUniquePtr<float[]> out = hwy::AllocateAligned<float>(kM * kK);
hwy::ZeroBytes(out.get(), kM * kK * sizeof(float));
int i, j, k;
for (i = 0; i < kM; ++i) {
for (j = 0; j < kK; ++j) {
for (k = 0; k < kN; ++k) {
out[i * kK + j] += a[i * kN + k] * b[k * kK + j];
}
}
}
return out;
}
template <size_t kOuter, size_t kInner>
hwy::AlignedFreeUniquePtr<float[]> SimpleMatVecAdd(
const CompressedArray<float, kOuter * kInner>& mat,
const hwy::AlignedFreeUniquePtr<float[]>& vec,
const hwy::AlignedFreeUniquePtr<float[]>& add) {
hwy::AlignedFreeUniquePtr<float[]> uncompressed_mat =
hwy::AllocateAligned<float>(kOuter * kInner);
hwy::AlignedFreeUniquePtr<float[]> out = hwy::AllocateAligned<float>(kOuter);
HWY_ASSERT(uncompressed_mat && out);
Decompress(mat, 0, uncompressed_mat.get(), kOuter * kInner);
for (size_t idx_row = 0; idx_row < kOuter; idx_row++) {
out[idx_row] = add[idx_row];
for (size_t idx_col = 0; idx_col < kInner; idx_col++) {
out[idx_row] +=
uncompressed_mat[kInner * idx_row + idx_col] * vec[idx_col];
}
}
return out;
}
template <size_t length>
void AssertClose(const hwy::AlignedFreeUniquePtr<float[]>& a,
const hwy::AlignedFreeUniquePtr<float[]>& b) {
for (size_t idx = 0; idx < length; idx++) {
const float rel_abs_delta = std::abs(a[idx] - b[idx]) /
std::max(std::abs(a[idx]), std::abs(b[idx]));
EXPECT_LT(rel_abs_delta, 2e-6)
<< "a[" << idx << "]=" << a[idx] << ", b[" << idx << "]=" << b[idx];
}
}
template <size_t kM, size_t kN, size_t kK, bool kAdd, typename MatTA,
typename MatTB = MatTA>
void TestTiledBatchMatMul() {
fprintf(stderr, "TestTiledBatchMatMul %lu, %lu, %lu, add=%d ", kM, kN, kK,
kAdd);
hwy::ThreadPool pool(3);
std::unique_ptr<CompressedArray<MatTA, kM * kN>> a =
GenerateMatHeap<MatTA, kM, kN>(0, pool);
std::unique_ptr<CompressedArray<MatTB, kN * kK>> b =
GenerateMatHeap<MatTB, kN, kK>(0, pool);
std::unique_ptr<CompressedArray<float, kK>> add =
GenerateMatHeap<float, 1, kK>(0, pool);
std::unique_ptr<CompressedArray<float, kM * kK>> c_slow =
GenerateZeroMatHeap<float, kM, kK>(pool);
MatMulSlowBatch<kN, kK>(kM, a->data(), b->data(),
kAdd ? add->data() : nullptr, c_slow->data());
hwy::AlignedFreeUniquePtr<float[]> c = hwy::AllocateAligned<float>(kM * kK);
std::unique_ptr<CompressedArray<MatTB, kN * kK>> b_trans =
GenerateTransposeMatHeap<MatTB, kN, kK>(0, pool);
if (kAdd) {
MatMul_4x4_Batch_Add<kN, kK, kAdd>(kM, a->data(), b_trans->data(), c.get(),
add->data(), pool);
} else {
MatMul_4x4_Batch<kN, kK>(kM, a->data(), b_trans->data(), c.get(), pool);
}
AssertClose(c_slow->data(), c.get(), kM * kK);
}
void TestAllTiledBatchMatMul() {
using BF16 = hwy::bfloat16_t;
using F32 = float;
using SFP = SfpStream;
// medium-sized square test
TestTiledBatchMatMul<512, 512, 512, /*kAdd=*/false, F32>();
TestTiledBatchMatMul<512, 512, 512, /*kAdd=*/true, BF16>();
TestTiledBatchMatMul<512, 512, 512, /*kAdd=*/false, F32, BF16>();
TestTiledBatchMatMul<512, 512, 512, /*kAdd=*/true, BF16, F32>();
TestTiledBatchMatMul<512, 512, 512, /*kAdd=*/false, F32, SFP>();
TestTiledBatchMatMul<512, 512, 512, /*kAdd=*/true, BF16, SFP>();
// minimal non-square test. kK must be at least 2 vectors.
TestTiledBatchMatMul<35, 128, 32, /*kAdd=*/false, F32>();
TestTiledBatchMatMul<34, 128, 32, /*kAdd=*/true, BF16>();
TestTiledBatchMatMul<33, 128, 32, /*kAdd=*/false, F32, BF16>();
TestTiledBatchMatMul<33, 128, 32, /*kAdd=*/true, BF16, F32>();
TestTiledBatchMatMul<31, 128, 32, /*kAdd=*/false, F32, SFP>();
TestTiledBatchMatMul<29, 128, 32, /*kAdd=*/true, BF16, SFP>();
TestTiledBatchMatMul<4, 128, 32, /*kAdd=*/true, F32>();
TestTiledBatchMatMul<4, 128, 32, /*kAdd=*/false, BF16>();
TestTiledBatchMatMul<4, 128, 32, /*kAdd=*/true, F32, BF16>();
TestTiledBatchMatMul<4, 128, 32, /*kAdd=*/false, BF16, F32>();
TestTiledBatchMatMul<4, 128, 32, /*kAdd=*/true, F32, SFP>();
TestTiledBatchMatMul<4, 128, 32, /*kAdd=*/false, BF16, SFP>();
TestTiledBatchMatMul<3, 128, 32, /*kAdd=*/false, F32>();
TestTiledBatchMatMul<3, 128, 32, /*kAdd=*/true, BF16>();
TestTiledBatchMatMul<3, 128, 32, /*kAdd=*/false, F32, BF16>();
TestTiledBatchMatMul<3, 128, 32, /*kAdd=*/true, BF16, F32>();
TestTiledBatchMatMul<3, 128, 32, /*kAdd=*/false, F32, SFP>();
TestTiledBatchMatMul<3, 128, 32, /*kAdd=*/true, BF16, SFP>();
TestTiledBatchMatMul<2, 128, 64, /*kAdd=*/true, F32>();
TestTiledBatchMatMul<2, 128, 64, /*kAdd=*/false, BF16>();
TestTiledBatchMatMul<2, 128, 64, /*kAdd=*/true, F32, BF16>();
TestTiledBatchMatMul<2, 128, 64, /*kAdd=*/false, BF16, F32>();
TestTiledBatchMatMul<2, 128, 64, /*kAdd=*/true, F32, SFP>();
TestTiledBatchMatMul<2, 128, 64, /*kAdd=*/false, BF16, SFP>();
TestTiledBatchMatMul<1, 128, 32, /*kAdd=*/false, F32>();
TestTiledBatchMatMul<1, 128, 32, /*kAdd=*/true, BF16>();
TestTiledBatchMatMul<1, 128, 32, /*kAdd=*/false, F32, BF16>();
TestTiledBatchMatMul<1, 128, 32, /*kAdd=*/true, BF16, F32>();
TestTiledBatchMatMul<1, 128, 32, /*kAdd=*/false, F32, SFP>();
TestTiledBatchMatMul<1, 128, 32, /*kAdd=*/true, BF16, SFP>();
// large-scale test
// TODO(philculliton): investigate rounding issues with large matrices.
// Causes test timeout.
// TestTiledBatchMatMul<512, 24576, 3072, float>();
}
void TestMatVecAdd() {
hwy::ThreadPool pool(hwy::ThreadPool::MaxThreads());
constexpr size_t kOuter = 128 * 3;
constexpr size_t kInner = 128 * 5;
CompressedArray<float, kOuter * kInner> mat =
GenerateMat<float, kOuter, kInner>(0, pool);
hwy::AlignedFreeUniquePtr<float[]> vec = GenerateVec<kInner>(0);
hwy::AlignedFreeUniquePtr<float[]> add = GenerateVec<kOuter>(0);
hwy::AlignedFreeUniquePtr<float[]> even_odd =
hwy::AllocateAligned<float>(kInner * pool.NumWorkers());
hwy::AlignedFreeUniquePtr<float[]> expected_out =
SimpleMatVecAdd<kOuter, kInner>(mat, vec, add);
hwy::AlignedFreeUniquePtr<float[]> actual_out =
hwy::AllocateAligned<float>(kOuter);
HWY_ASSERT(vec && add && even_odd && expected_out && actual_out);
MatVecAdd<kOuter, kInner>(mat, 0, vec.get(), add.get(), even_odd.get(),
actual_out.get(), pool);
AssertClose<kOuter>(actual_out, expected_out);
}
void TestTwoMatVecAdd() {
hwy::ThreadPool pool(hwy::ThreadPool::MaxThreads());
constexpr size_t kOuter = 128 * 3;
constexpr size_t kInner = 128 * 5;
CompressedArray<float, kOuter * kInner> mat0 =
GenerateMat<float, kOuter, kInner>(0, pool);
CompressedArray<float, kOuter * kInner> mat1 =
GenerateMat<float, kOuter, kInner>(1, pool);
hwy::AlignedFreeUniquePtr<float[]> vec = GenerateVec<kInner>(0);
hwy::AlignedFreeUniquePtr<float[]> add0 = GenerateVec<kOuter>(0);
hwy::AlignedFreeUniquePtr<float[]> add1 = GenerateVec<kOuter>(1);
hwy::AlignedFreeUniquePtr<float[]> expected_out0 =
SimpleMatVecAdd<kOuter, kInner>(mat0, vec, add0);
hwy::AlignedFreeUniquePtr<float[]> expected_out1 =
SimpleMatVecAdd<kOuter, kInner>(mat1, vec, add1);
hwy::AlignedFreeUniquePtr<float[]> actual_out0 =
hwy::AllocateAligned<float>(kOuter);
hwy::AlignedFreeUniquePtr<float[]> actual_out1 =
hwy::AllocateAligned<float>(kOuter);
HWY_ASSERT(vec && add0 && add1 && expected_out0 && actual_out0 &&
expected_out1 && actual_out1);
TwoMatVecAdd<kOuter, kInner>(mat0, mat1, 0, vec.get(), add0.get(), add1.get(),
actual_out0.get(), actual_out1.get(), pool);
AssertClose<kOuter>(actual_out0, expected_out0);
AssertClose<kOuter>(actual_out1, expected_out1);
}
void TestTwoOfsMatVecAddLoop() {
hwy::ThreadPool pool(hwy::ThreadPool::MaxThreads());
constexpr size_t kOuter = 128 * 3;
constexpr size_t kInner = 128 * 5;
CompressedArray<float, kOuter * kInner> mat =
GenerateMat<float, kOuter, kInner>(0, pool);
hwy::AlignedFreeUniquePtr<float[]> vec = GenerateVec<kInner>(0);
hwy::AlignedFreeUniquePtr<float[]> add0 = GenerateVec<kOuter>(0);
hwy::AlignedFreeUniquePtr<float[]> add1 = GenerateVec<kOuter>(1);
hwy::AlignedFreeUniquePtr<float[]> expected_out0 =
SimpleMatVecAdd<kOuter, kInner>(mat, vec, add0);
hwy::AlignedFreeUniquePtr<float[]> expected_out1 =
SimpleMatVecAdd<kOuter, kInner>(mat, vec, add1);
hwy::AlignedFreeUniquePtr<float[]> actual_out0 =
hwy::AllocateAligned<float>(kOuter);
hwy::AlignedFreeUniquePtr<float[]> actual_out1 =
hwy::AllocateAligned<float>(kOuter);
HWY_ASSERT(vec && add0 && add1 && expected_out0 && actual_out0 &&
expected_out1 && actual_out1);
TwoOfsMatVecAddLoop<kOuter, kInner>(mat, 0, 0, vec.get(), add0.get(),
add1.get(), actual_out0.get(),
actual_out1.get());
AssertClose<kOuter>(actual_out0, expected_out0);
AssertClose<kOuter>(actual_out1, expected_out1);
}
void TestSigmoid() {
std::vector<float> values;
for (int i = -150; i <= 150; ++i) {
values.push_back(.1f * i);
}
std::vector<float> result = values;
Sigmoid(result.data(), result.size());
for (size_t i = 0; i < values.size(); i++) {
const float max_error = 0.00007;
float value = values[i];
float approx = result[i];
float expected = (1 / (1 + std::exp(-values[i])));
EXPECT_NEAR(approx, expected, max_error) << "Input: " << value;
}
}
// NOLINTNEXTLINE(google-readability-namespace-comments)
} // namespace HWY_NAMESPACE
} // namespace gcpp
HWY_AFTER_NAMESPACE();
#if HWY_ONCE
namespace gcpp {
HWY_BEFORE_TEST(OpsTest);
HWY_EXPORT_AND_TEST_P(OpsTest, TestAllAddFrom);
HWY_EXPORT_AND_TEST_P(OpsTest, TestAllMulBy);
HWY_EXPORT_AND_TEST_P(OpsTest, TestAllMulByConst);
HWY_EXPORT_AND_TEST_P(OpsTest, TestAllMulByConstAndAdd);
HWY_EXPORT_AND_TEST_P(OpsTest, TestAllSoftmax);
HWY_EXPORT_AND_TEST_P(OpsTest, TestAllCreateDistribution);
HWY_EXPORT_AND_TEST_P(OpsTest, TestAllTiledBatchMatMul);
HWY_EXPORT_AND_TEST_P(OpsTest, TestMatVecAdd);
HWY_EXPORT_AND_TEST_P(OpsTest, TestTwoMatVecAdd);
HWY_EXPORT_AND_TEST_P(OpsTest, TestTwoOfsMatVecAddLoop);
HWY_EXPORT_AND_TEST_P(OpsTest, TestSigmoid);
#ifdef HWY_AFTER_TEST
HWY_AFTER_TEST();
#endif
} // namespace gcpp
#endif
Reference in New Issue View Git Blame Copy Permalink