float16 type support enhance (#12181)

* cherry picked

* "cherry picked platform"

* "add comment"

* "fix ci"

paddle/fluid/platform/CMakeLists.txt

@@ -60,3 +60,7 @@ cc_test(profiler_test SRCS profiler_test.cc DEPS profiler)
 
 nv_test(float16_gpu_test SRCS float16_test.cu DEPS lod_tensor)
 cc_test(float16_test SRCS float16_test.cc DEPS lod_tensor)
+
+IF(WITH_GPU)
+  nv_test(cuda_helper_test SRCS cuda_helper_test.cu)
+ENDIF()

paddle/fluid/platform/cuda_device_function.h

@@ -14,6 +14,10 @@ limitations under the License. */
 
 #pragma once
 #include <cuda.h>
+// NOTE(): support float16 to half in header file.
+#define PADDLE_CUDA_FP16
+#include <cuda_fp16.h>
+#include "paddle/fluid/platform/float16.h"
 
 namespace paddle {
 namespace platform {
@@ -36,6 +40,18 @@ __forceinline__ __device__ T CudaShuffleDownSync(unsigned mask, T val,
 #endif
 }
 
+// CUDA 9.0 have native compatible float16 shfl_down
+#if CUDA_VERSION < 9000
+template <>
+__forceinline__ __device__ float16 CudaShuffleDownSync(unsigned mask,
+                                                       float16 val, int delta,
+                                                       int width) {
+  half tmp = static_cast<half>(val);
+  __shfl_down(tmp, static_cast<unsigned>(delta), width);
+  return float16(tmp);
+}
+#endif
+
 template <typename T>
 __forceinline__ __device__ T CudaShuffleSync(unsigned mask, T val, int src_line,
                                              int width = 32) {
@@ -46,6 +62,11 @@ __forceinline__ __device__ T CudaShuffleSync(unsigned mask, T val, int src_line,
 #endif
 }
 
+template <typename T>
+HOSTDEVICE T Infinity() {
+  return INFINITY;
+}
+
 template <typename T>
 __device__ T reduceSum(T val, int tid, int len) {
   // NOTE(zcd): The warp size should be taken from the

paddle/fluid/platform/cuda_helper_test.cu

+// 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 <gtest/gtest.h>
+#include <bitset>
+#include <iostream>
+#include <random>
+
+#define PADDLE_CUDA_FP16
+#include "paddle/fluid/platform/cuda_device_function.h"
+#include "paddle/fluid/platform/cuda_primitives.h"
+#include "paddle/fluid/platform/float16.h"
+
+using paddle::platform::PADDLE_CUDA_NUM_THREADS;
+using paddle::platform::float16;
+
+#define CUDA_ATOMIC_KERNEL(op, T)                                      \
+  __global__ void op##Kernel(const T* data_a, T* data_b, size_t num) { \
+    for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < num;       \
+         i += blockDim.x * gridDim.x) {                                \
+      paddle::platform::CudaAtomic##op(&data_b[i], data_a[i]);         \
+    }                                                                  \
+  }
+
+template <typename T>
+struct AddFunctor {
+  T operator()(const T& a, const T& b) { return a + b; }
+};
+
+template <typename T>
+struct SubFunctor {
+  T operator()(const T& a, const T& b) { return a - b; }
+};
+
+// NOTE(dzhwinter): the float16 add has small underflow/overflow
+// so we use EXPECT_NEAR to check the result.
+#define ARITHMETIC_KERNEL_LAUNCH(op, T)                                 \
+  void Test##T##op(size_t num) {                                        \
+    T *in1, *in2, *out;                                                 \
+    T *d_in1, *d_in2;                                                   \
+    size_t size = sizeof(T) * num;                                      \
+    cudaMalloc(reinterpret_cast<void**>(&d_in1), size);                 \
+    cudaMalloc(reinterpret_cast<void**>(&d_in2), size);                 \
+    in1 = reinterpret_cast<T*>(malloc(size));                           \
+    in2 = reinterpret_cast<T*>(malloc(size));                           \
+    out = reinterpret_cast<T*>(malloc(size));                           \
+    std::minstd_rand engine;                                            \
+    std::uniform_real_distribution<double> dist(0.0, 1.0);              \
+    for (size_t i = 0; i < num; ++i) {                                  \
+      in1[i] = static_cast<T>(dist(engine));                            \
+      in2[i] = static_cast<T>(dist(engine));                            \
+    }                                                                   \
+    cudaMemcpy(d_in1, in1, size, cudaMemcpyHostToDevice);               \
+    cudaMemcpy(d_in2, in2, size, cudaMemcpyHostToDevice);               \
+    op##Kernel<<<1, PADDLE_CUDA_NUM_THREADS>>>(d_in1, d_in2, num);      \
+    cudaDeviceSynchronize();                                            \
+    cudaMemcpy(out, d_in2, size, cudaMemcpyDeviceToHost);               \
+    cudaDeviceSynchronize();                                            \
+    for (size_t i = 0; i < num; ++i) {                                  \
+      EXPECT_NEAR(static_cast<float>(out[i]),                           \
+                  static_cast<float>(op##Functor<T>()(in1[i], in2[i])), \
+                  0.001);                                               \
+    }                                                                   \
+    free(in1);                                                          \
+    free(in2);                                                          \
+    free(out);                                                          \
+    cudaFree(d_in1);                                                    \
+    cudaFree(d_in2);                                                    \
+  }
+CUDA_ATOMIC_KERNEL(Add, float);
+CUDA_ATOMIC_KERNEL(Add, double);
+CUDA_ATOMIC_KERNEL(Add, float16);
+
+ARITHMETIC_KERNEL_LAUNCH(Add, float);
+ARITHMETIC_KERNEL_LAUNCH(Add, double);
+ARITHMETIC_KERNEL_LAUNCH(Add, float16);
+
+namespace paddle {
+namespace platform {
+USE_CUDA_ATOMIC(Sub, int);
+};
+};
+CUDA_ATOMIC_KERNEL(Sub, int);
+ARITHMETIC_KERNEL_LAUNCH(Sub, int);
+
+// cuda primitives
+TEST(CudaAtomic, Add) {
+  TestfloatAdd(static_cast<size_t>(10));
+  TestfloatAdd(static_cast<size_t>(1024 * 1024));
+  TestdoubleAdd(static_cast<size_t>(10));
+  TestdoubleAdd(static_cast<size_t>(1024 * 1024));
+}
+
+TEST(CudaAtomic, Sub) {
+  TestintSub(static_cast<size_t>(10));
+  TestintSub(static_cast<size_t>(1024 * 1024));
+}
+
+TEST(CudaAtomic, float16) {
+  using paddle::platform::float16;
+  Testfloat16Add(static_cast<size_t>(1));
+  Testfloat16Add(static_cast<size_t>(2));
+  Testfloat16Add(static_cast<size_t>(3));
+
+  Testfloat16Add(static_cast<size_t>(10));
+  Testfloat16Add(static_cast<size_t>(1024 * 1024));
+}

paddle/fluid/platform/cuda_primitives.h

@@ -14,12 +14,14 @@ limitations under the License. */
 
 #pragma once
 #include <cuda.h>
+#include <stdio.h>
+#include "paddle/fluid/platform/float16.h"
 
 namespace paddle {
 namespace platform {
 
 #define CUDA_ATOMIC_WRAPPER(op, T) \
-  __device__ __forceinline__ T CudaAtomic##op(T* address, const T val)
+  __device__ __forceinline__ T CudaAtomic##op(T *address, const T val)
 
 #define USE_CUDA_ATOMIC(op, T) \
   CUDA_ATOMIC_WRAPPER(op, T) { return atomic##op(address, val); }
@@ -42,17 +44,17 @@ CUDA_ATOMIC_WRAPPER(Add, int64_t) {
   static_assert(sizeof(int64_t) == sizeof(long long int),  // NOLINT
                 "long long should be int64");
   return CudaAtomicAdd(
-      reinterpret_cast<unsigned long long int*>(address),  // NOLINT
-      static_cast<unsigned long long int>(val));           // NOLINT
+      reinterpret_cast<unsigned long long int *>(address),  // NOLINT
+      static_cast<unsigned long long int>(val));            // NOLINT
 }
 
 #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 600
 USE_CUDA_ATOMIC(Add, double);
 #else
 CUDA_ATOMIC_WRAPPER(Add, double) {
-  unsigned long long int* address_as_ull =                 // NOLINT
-      reinterpret_cast<unsigned long long int*>(address);  // NOLINT
-  unsigned long long int old = *address_as_ull, assumed;   // NOLINT
+  unsigned long long int *address_as_ull =                  // NOLINT
+      reinterpret_cast<unsigned long long int *>(address);  // NOLINT
+  unsigned long long int old = *address_as_ull, assumed;    // NOLINT
 
   do {
     assumed = old;
@@ -64,6 +66,67 @@ CUDA_ATOMIC_WRAPPER(Add, double) {
 
   return __longlong_as_double(old);
 }
+#endif
+
+#ifdef PADDLE_CUDA_FP16
+// NOTE(dzhwinter): cuda do not have atomicCAS for half.
+// Just use the half address as a unsigned value address and
+// do the atomicCAS. According to the value store at high 16 bits
+// or low 16 bits, then do a different sum and CAS.
+// Given most warp-threads will failed on the atomicCAS, so this
+// implemented should be avoided in high concurrency. It's will be
+// slower than the way convert value into 32bits and do a full atomicCAS.
+
+// convert the value into float and do the add arithmetic.
+// then store the result into a uint32.
+inline __device__ uint32_t add_to_low_half(uint32_t val, float x) {
+  float16 low_half;
+  // the float16 in lower 16bits
+  low_half.x = static_cast<uint16_t>(val & 0xffffu);
+  low_half = static_cast<float16>(static_cast<float>(low_half) + x);
+  return (val & 0xffff0000u) | low_half.x;
+}
+
+inline __device__ uint32_t add_to_high_half(uint32_t val, float x) {
+  float16 high_half;
+  // the float16 in higher 16bits
+  high_half.x = static_cast<uint16_t>(val >> 16);
+  high_half = static_cast<float16>(static_cast<float>(high_half) + x);
+  return (val & 0xffffu) | (static_cast<uint32_t>(high_half.x) << 16);
+}
+
+CUDA_ATOMIC_WRAPPER(Add, float16) {
+  // concrete packed float16 value may exsits in lower or higher 16bits
+  // of the 32bits address.
+  uint32_t *address_as_ui =
+      reinterpret_cast<uint32_t *>(reinterpret_cast<char *>(address) -
+                                   (reinterpret_cast<size_t>(address) & 2));
+  float val_f = static_cast<float>(val);
+  uint32_t old = *address_as_ui;
+  uint32_t sum;
+  uint32_t newval;
+  uint32_t assumed;
+  if (((size_t)address & 2) == 0) {
+    // the float16 value stay at lower 16 bits of the address.
+    do {
+      assumed = old;
+      old = atomicCAS(address_as_ui, assumed, add_to_low_half(assumed, val_f));
+    } while (old != assumed);
+    float16 ret;
+    ret.x = old & 0xffffu;
+    return ret;
+  } else {
+    // the float16 value stay at higher 16 bits of the address.
+    do {
+      assumed = old;
+      old = atomicCAS(address_as_ui, assumed, add_to_high_half(assumed, val_f));
+    } while (old != assumed);
+    float16 ret;
+    ret.x = old >> 16;
+    return ret;
+  }
+}
+
 #endif
 }  // namespace platform
 }  // namespace paddle

paddle/fluid/platform/float16.h

@@ -67,8 +67,11 @@ struct float16;
 }  // namespace platform
 }  // namespace paddle
 
+// NOTE():
+// Do not move the eigen.h header, otherwise the eigen_vector<bool> will failed.
 #include "paddle/fluid/framework/eigen.h"
 #include "paddle/fluid/platform/hostdevice.h"
+#include "unsupported/Eigen/CXX11/Tensor"
 
 namespace paddle {
 namespace platform {
@@ -898,6 +901,30 @@ struct is_pod<paddle::platform::float16> {
       is_standard_layout<paddle::platform::float16>::value;
 };
 
+template <>
+struct is_floating_point<paddle::platform::float16>
+    : std::integral_constant<
+          bool, std::is_same<paddle::platform::float16,
+                             typename std::remove_cv<
+                                 paddle::platform::float16>::type>::value> {};
+template <>
+struct is_signed<paddle::platform::float16> {
+  static const bool value = true;
+};
+
+template <>
+struct is_unsigned<paddle::platform::float16> {
+  static const bool value = false;
+};
+
+inline bool isnan(const paddle::platform::float16& a) {
+  return paddle::platform::isnan(a);
+}
+
+inline bool isinf(const paddle::platform::float16& a) {
+  return paddle::platform::isinf(a);
+}
+
 template <>
 struct numeric_limits<paddle::platform::float16> {
   static const bool is_specialized = true;

paddle/fluid/platform/float16_test.cc

@@ -141,10 +141,36 @@ TEST(float16, lod_tensor_cpu) {
   }
 }
 
+TEST(float16, floating) {
+  // compile time assert.
+  PADDLE_ASSERT(std::is_floating_point<float16>::value);
+}
+
 TEST(float16, print) {
   float16 a = float16(1.0f);
   std::cout << a << std::endl;
 }
 
+// CPU test
+TEST(float16, isinf) {
+  float16 a;
+  a.x = 0x7c00;
+  float16 b = float16(INFINITY);
+  float16 c = static_cast<float16>(INFINITY);
+  EXPECT_EQ(std::isinf(a), true);
+  EXPECT_EQ(std::isinf(b), true);
+  EXPECT_EQ(std::isinf(c), true);
+}
+
+TEST(float16, isnan) {
+  float16 a;
+  a.x = 0x7fff;
+  float16 b = float16(NAN);
+  float16 c = static_cast<float16>(NAN);
+  EXPECT_EQ(std::isnan(a), true);
+  EXPECT_EQ(std::isnan(b), true);
+  EXPECT_EQ(std::isnan(c), true);
+}
+
 }  // namespace platform
 }  // namespace paddle

paddle/fluid/platform/float16_test.cu

@@ -11,11 +11,13 @@ limitations under the License. */
 
 #include "paddle/fluid/platform/float16.h"
 
+#include <glog/logging.h>
 #include <gtest/gtest.h>
+#include <bitset>
+#include <iostream>
 
 #include "paddle/fluid/framework/lod_tensor.h"
 #include "paddle/fluid/framework/tensor_util.h"
-#include "paddle/legacy/utils/Logging.h"
 
 #define ARITHMETIC_KERNEL(op_type, sign)                                 \
   __global__ void op_type(const half* in1, const half* in2, half* out) { \
@@ -241,6 +243,72 @@ TEST(float16, lod_tensor_on_gpu) {
   }
 }
 
+template <typename T>
+struct Functor {
+  bool operator()(const T& val) {
+    return std::type_index(typeid(T)) ==
+           std::type_index(typeid(platform::float16));
+  }
+};
+
+TEST(float16, typeid) {
+  // the framework heavily used typeid hash
+  Functor<float16> functor;
+  float16 a = float16(.0f);
+  Functor<int> functor2;
+  int b(0);
+
+  // compile time assert
+  PADDLE_ASSERT(functor(a) == true);
+  PADDLE_ASSERT(functor2(b) == false);
+}
+
+// GPU test
+TEST(float16, isinf) {
+  float16 a;
+  a.x = 0x7c00;
+  float16 b = float16(INFINITY);
+  // underflow to 0
+  float16 native_a(5e-40f);
+  // overflow to inf
+  float16 native_b(5e40f);
+  EXPECT_EQ(std::isinf(a), true);
+  EXPECT_EQ(std::isinf(b), true);
+  EXPECT_EQ(std::isinf(native_b), true);
+  EXPECT_EQ(native_a, float16(0));
+}
+
+TEST(float16, isnan) {
+  float16 a;
+  a.x = 0x7fff;
+  float16 b = float16(NAN);
+  float16 c = float16(5e40);
+  // inf * +-0 will get a nan
+  float16 d = c * float16(0);
+  EXPECT_EQ(std::isnan(a), true);
+  EXPECT_EQ(std::isnan(b), true);
+  EXPECT_EQ(std::isnan(d), true);
+}
+
+TEST(float16, cast) {
+  float16 a;
+  a.x = 0x0070;
+  auto b = a;
+  {
+    // change semantic, keep the same value
+    float16 c = reinterpret_cast<float16&>(reinterpret_cast<unsigned&>(b));
+    EXPECT_EQ(b, c);
+  }
+
+  {
+    // use uint32 low 16 bit store float16
+    uint32_t c = reinterpret_cast<uint32_t&>(b);
+    float16 d;
+    d.x = c;
+    EXPECT_EQ(b, d);
+  }
+}
+
 }  // namespace platform
 }  // namespace paddle
 #endif  // PADDLE_CUDA_FP16