test_cpu_vec.cc 11.1 KB
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/* Copyright (c) 2018 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. */

#include <cmath>
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#include <cstring>
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#include <random>
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#include "glog/logging.h"
#include "gtest/gtest.h"
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#include "paddle/phi/backends/dynload/port.h"
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#include "paddle/phi/kernels/funcs/cpu_vec.h"

namespace phi {
namespace tests {
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inline double GetCurrentUS() {
  struct timeval time;
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  gettimeofday(&time, nullptr);
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  return 1e+6 * time.tv_sec + time.tv_usec;
}
constexpr int repeat = 1000;

template <typename T>
inline T _sigmoid(T x) {
  const T min = SIGMOID_THRESHOLD_MIN;
  const T max = SIGMOID_THRESHOLD_MAX;
  T tmp = (x < min) ? min : ((x > max) ? max : x);
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  return static_cast<T>(1) / (static_cast<T>(1) + std::exp(-tmp));
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}

template <typename T>
inline T _tanh(T x) {
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  return static_cast<T>(2) * _sigmoid<T>(static_cast<T>(2) * x) -
         static_cast<T>(1);
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}

template <typename T>
void ref_sigmoid(const int n, const T* x, T* y) {
  for (int i = 0; i < n; ++i) {
    y[i] = _sigmoid(x[i]);
  }
}

template <typename T>
void ref_tanh(const int n, const T* x, T* y) {
  for (int i = 0; i < n; ++i) {
    y[i] = _tanh(x[i]);
  }
}
template <typename T>
void ref_relu(const int n, const T* x, T* y) {
  for (int i = 0; i < n; ++i) {
    y[i] = x[i] > 0 ? x[i] : 0;
  }
}

template <typename T>
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void RandomVec(const int n,
               T* a,
               const T lower = static_cast<T>(-20.f),
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               const T upper = static_cast<T>(20.f)) {
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  static unsigned int seed = 100;
  std::mt19937 rng(seed++);
  std::uniform_real_distribution<double> uniform_dist(0, 1);
  for (int i = 0; i < n; ++i) {
    a[i] = static_cast<T>(uniform_dist(rng) * (upper - lower) + lower);
  }
}

template <typename T>
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void TestAndBench(const int n,
                  std::function<void(const int, const T*, T*)> tgt,
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                  std::function<void(const int, const T*, T*)> ref) {
  std::vector<T> x(n);
  std::vector<T> ytgt(n), yref(n);
  RandomVec<T>(n, x.data());

  const T* x_data = x.data();
  T* ytgt_data = ytgt.data();
  T* yref_data = yref.data();
  auto st = GetCurrentUS();
  for (int i = 0; i < repeat; ++i) {
    tgt(n, x_data, ytgt_data);
  }
  auto mt = GetCurrentUS();
  for (int i = 0; i < repeat; ++i) {
    ref(n, x_data, yref_data);
  }
  auto et = GetCurrentUS();

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  VLOG(3) << "Vec size " << n << ": refer takes: " << (et - mt) / repeat
          << " us, tgt takes: " << (mt - st) / repeat;
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  for (int i = 0; i < n; ++i) {
    EXPECT_NEAR(ytgt_data[i], yref_data[i], 1e-3);
  }
}

TEST(CpuVecTest, sigmoid) {
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  using namespace phi::funcs;  // NOLINT
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  for (auto sz : {1, 2, 15, 16, 30, 32, 128, 200, 512}) {
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    TestAndBench<float>(sz, vec_sigmoid<float>, ref_sigmoid<float>);
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    TestAndBench<float>(
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        sz, vec_sigmoid<float, backends::cpu::avx>, ref_sigmoid<float>);
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    TestAndBench<float>(
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        sz, vec_sigmoid<float, backends::cpu::avx2>, ref_sigmoid<float>);
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    TestAndBench<float>(
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        sz, vec_sigmoid<float, backends::cpu::avx512f>, ref_sigmoid<float>);
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  }
  TestAndBench<double>(30, vec_sigmoid<double>, ref_sigmoid<double>);
}

TEST(CpuVecTest, tanh) {
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  using namespace phi::funcs;  // NOLINT
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  for (auto sz : {1, 2, 15, 16, 30, 32, 128, 200, 512}) {
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    TestAndBench<float>(sz, vec_tanh<float>, ref_tanh<float>);
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    TestAndBench<float>(
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        sz, vec_tanh<float, backends::cpu::avx>, ref_tanh<float>);
    TestAndBench<float>(
        sz, vec_tanh<float, backends::cpu::avx2>, ref_tanh<float>);
    TestAndBench<float>(
        sz, vec_tanh<float, backends::cpu::avx512f>, ref_tanh<float>);
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  }
  TestAndBench<double>(30, vec_tanh<double>, ref_tanh<double>);
}

TEST(CpuVecTest, relu) {
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  using namespace phi::funcs;  // NOLINT
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  for (auto sz : {1, 2, 15, 16, 30, 32, 128, 200, 512}) {
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    TestAndBench<float>(sz, vec_relu<float>, ref_relu<float>);
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    TestAndBench<float>(
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        sz, vec_relu<float, backends::cpu::avx>, ref_relu<float>);
    TestAndBench<float>(
        sz, vec_relu<float, backends::cpu::avx2>, ref_relu<float>);
    TestAndBench<float>(
        sz, vec_relu<float, backends::cpu::avx512f>, ref_relu<float>);
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  }
  TestAndBench<double>(30, vec_relu<double>, ref_relu<double>);
}
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template <typename T>
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void compare_sum(size_t n,
                 std::function<void(const size_t, const T*, T*)> tgt,
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                 std::function<void(const size_t, const T*, T*)> ref) {
  std::vector<T> x(n);
  T ytgt_data, yref_data;
  RandomVec<T>(n, x.data(), static_cast<T>(-2), static_cast<T>(2));

  const T* x_data = x.data();
  tgt(n, x_data, &ytgt_data);
  ref(n, x_data, &yref_data);
  EXPECT_NEAR(ytgt_data, yref_data, 1e-3);
}

TEST(CpuVecTest, vec_sum) {
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  using namespace phi::funcs;  // NOLINT
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  for (size_t sz : {1, 2, 15, 16, 30, 32, 128, 200, 512}) {
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    compare_sum<float>(
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        sz, vec_sum<float>, vec_sum<float, backends::cpu::isa_any>);
    compare_sum<float>(sz,
                       vec_sum<float, backends::cpu::avx>,
                       vec_sum<float, backends::cpu::isa_any>);
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  }
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  compare_sum<double>(
      30U, vec_sum<double>, vec_sum<double, backends::cpu::isa_any>);
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}

template <typename T>
void compare_clip(
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    size_t n,
    T threshold,
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    std::function<void(const size_t, const T, const T*, T*)> tgt,
    std::function<void(const size_t, const T, const T*, T*)> ref) {
  std::vector<T> x(n);
  std::vector<T> ytgt(n), yref(n);
  RandomVec<T>(n, x.data(), static_cast<T>(-2), static_cast<T>(2));

  const T* x_data = x.data();
  T* yref_data = yref.data();
  T* ytgt_data = ytgt.data();
  tgt(n, threshold, x_data, ytgt_data);
  ref(n, threshold, x_data, yref_data);
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  for (size_t i = 0; i < n; ++i) {
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    EXPECT_NEAR(ytgt_data[i], yref_data[i], 1e-3);
  }
}

TEST(CpuVecTest, vec_clip) {
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  using namespace phi::funcs;  // NOLINT
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  for (size_t sz : {1, 2, 15, 16, 30, 32, 128, 200, 512}) {
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    compare_clip<float>(
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        sz, -4.f, vec_clip<float>, vec_clip<float, backends::cpu::isa_any>);
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    compare_clip<float>(sz,
                        -1.1f,
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                        vec_clip<float, backends::cpu::avx>,
                        vec_clip<float, backends::cpu::isa_any>);
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  }
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  compare_clip<double>(
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      30U, 1.0, vec_clip<double>, vec_clip<double, backends::cpu::isa_any>);
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}

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template <typename T>
void compare_mul(
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    size_t n,
    std::function<void(const size_t, const T*, const T*, T*)> tgt,
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    std::function<void(const size_t, const T*, const T*, T*)> ref) {
  std::vector<T> x(n), y(n);
  std::vector<T> ztgt(n), zref(n);

  RandomVec<T>(n, x.data(), static_cast<T>(-2), static_cast<T>(2));
  RandomVec<T>(n, y.data(), static_cast<T>(-2), static_cast<T>(2));

  const T* x_data = x.data();
  const T* y_data = y.data();
  T* ztgt_data = ztgt.data();
  T* zref_data = zref.data();

  tgt(n, x_data, y_data, ztgt_data);
  ref(n, x_data, y_data, zref_data);
  for (size_t i = 0; i < n; ++i) {
    EXPECT_NEAR(ztgt_data[i], zref_data[i], 1e-3);
  }
}

TEST(CpuVecTest, vec_mul) {
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  using namespace phi::funcs;  // NOLINT
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  for (size_t sz : {1, 2, 15, 16, 30, 32, 128, 200, 512}) {
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    compare_mul<float>(
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        sz, vec_mul<float>, vec_mul<float, backends::cpu::isa_any>);
    compare_mul<float>(sz,
                       vec_mul<float, backends::cpu::avx>,
                       vec_mul<float, backends::cpu::isa_any>);
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  }
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  compare_mul<double>(
      30U, vec_mul<double>, vec_mul<double, backends::cpu::isa_any>);
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}

template <typename T>
void compare_mul_reduce(
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    size_t n,
    std::function<void(const size_t, const T*, const T*, T*)> tgt,
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    std::function<void(const size_t, const T*, const T*, T*)> ref) {
  std::vector<T> x(n), y(n);
  T ztgt_data, zref_data;

  RandomVec<T>(n, x.data(), static_cast<T>(-2), static_cast<T>(2));
  RandomVec<T>(n, y.data(), static_cast<T>(-2), static_cast<T>(2));

  const T* x_data = x.data();
  const T* y_data = y.data();

  tgt(n, x_data, y_data, &ztgt_data);
  ref(n, x_data, y_data, &zref_data);
  EXPECT_NEAR(ztgt_data, zref_data, 1e-3);
}

TEST(CpuVecTest, vec_mul_reduce) {
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  using namespace phi::funcs;  // NOLINT
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  for (size_t sz : {1, 2, 15, 16, 30, 32, 128, 200, 512}) {
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    compare_mul_reduce<float>(sz,
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                              vec_mul_reduce<float>,
                              vec_mul_reduce<float, backends::cpu::isa_any>);
    compare_mul_reduce<float>(sz,
                              vec_mul_reduce<float, backends::cpu::avx>,
                              vec_mul_reduce<float, backends::cpu::isa_any>);
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  }
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  compare_mul_reduce<double>(30U,
                             vec_mul_reduce<double>,
                             vec_mul_reduce<double, backends::cpu::isa_any>);
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}

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template <typename T>
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void TestInplace(const int n,
                 std::function<void(const int, const T*, T*)> tgt,
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                 std::function<void(const int, const T*, T*)> ref) {
  std::vector<T> x(n);
  std::vector<T> ytgt(n), yref(n);
  RandomVec<T>(n, x.data());

  const T* x_data = x.data();
  T* yref_data = yref.data();
  T* ytgt_data = ytgt.data();
  std::memcpy(yref_data, x_data, sizeof(T) * n);
  std::memcpy(ytgt_data, x_data, sizeof(T) * n);

  ref(n, yref_data, yref_data);
  tgt(n, ytgt_data, ytgt_data);

  for (int i = 0; i < n; ++i) {
    EXPECT_NEAR(ytgt_data[i], yref_data[i], 1e-3);
  }
}

TEST(CpuVecTest, inplace_sigmoid) {
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  using namespace phi::funcs;  // NOLINT
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  for (auto sz : {1, 2, 15, 16, 30, 32, 128, 200, 512}) {
    TestInplace<float>(sz, vec_sigmoid<float>, ref_sigmoid<float>);
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    TestInplace<float>(
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        sz, vec_sigmoid<float, backends::cpu::avx>, ref_sigmoid<float>);
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    TestInplace<float>(
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        sz, vec_sigmoid<float, backends::cpu::avx2>, ref_sigmoid<float>);
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    TestInplace<float>(
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        sz, vec_sigmoid<float, backends::cpu::avx512f>, ref_sigmoid<float>);
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  }
  TestInplace<double>(30, vec_sigmoid<double>, ref_sigmoid<double>);
}

TEST(CpuVecTest, inplace_tanh) {
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  using namespace phi::funcs;  // NOLINT
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  for (auto sz : {1, 2, 15, 16, 30, 32, 128, 200, 512}) {
    TestInplace<float>(sz, vec_tanh<float>, ref_tanh<float>);
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    TestInplace<float>(
        sz, vec_tanh<float, backends::cpu::avx>, ref_tanh<float>);
    TestInplace<float>(
        sz, vec_tanh<float, backends::cpu::avx2>, ref_tanh<float>);
    TestInplace<float>(
        sz, vec_tanh<float, backends::cpu::avx512f>, ref_tanh<float>);
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  }
  TestInplace<double>(30, vec_tanh<double>, ref_tanh<double>);
}

TEST(CpuVecTest, inplace_relu) {
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  using namespace phi::funcs;  // NOLINT
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  for (auto sz : {1, 2, 15, 16, 30, 32, 128, 200, 512}) {
    TestInplace<float>(sz, vec_relu<float>, ref_relu<float>);
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    TestInplace<float>(
        sz, vec_relu<float, backends::cpu::avx>, ref_relu<float>);
    TestInplace<float>(
        sz, vec_relu<float, backends::cpu::avx2>, ref_relu<float>);
    TestInplace<float>(
        sz, vec_relu<float, backends::cpu::avx512f>, ref_relu<float>);
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  }
  TestInplace<double>(30, vec_relu<double>, ref_relu<double>);
}
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}  // namespace tests
}  // namespace phi