Integrate float16 into data_type_transform (#8619)
* test cpu float16 data transform * add isnan etc * small fix * fix containsNAN test error * add data_type transform GPU test * add float16 GPU example * fix error * fix GPU test error * add context waitshanyi15-patch-2
kexinzhao
7 years ago
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GitHub
parent
78c884d7a7
commit
266ccaa843
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data_type_transform.cc
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/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "paddle/fluid/framework/data_type_transform.h"
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#include "paddle/fluid/framework/tensor_util.h"
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#include "gtest/gtest.h"
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TEST(DataTypeTransform, GPUTransform) {
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using namespace paddle::framework;
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using namespace paddle::platform;
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auto cpu_place = CPUPlace();
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auto gpu_place = CUDAPlace(0);
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CUDADeviceContext context(gpu_place);
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auto kernel_fp16 = OpKernelType(proto::VarType::FP16, gpu_place,
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DataLayout::kAnyLayout, LibraryType::kPlain);
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auto kernel_fp32 = OpKernelType(proto::VarType::FP32, gpu_place,
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DataLayout::kAnyLayout, LibraryType::kPlain);
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auto kernel_fp64 = OpKernelType(proto::VarType::FP64, gpu_place,
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DataLayout::kAnyLayout, LibraryType::kPlain);
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auto kernel_int32 = OpKernelType(proto::VarType::INT32, gpu_place,
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DataLayout::kAnyLayout, LibraryType::kPlain);
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auto kernel_int64 = OpKernelType(proto::VarType::INT64, gpu_place,
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DataLayout::kAnyLayout, LibraryType::kPlain);
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auto kernel_bool = OpKernelType(proto::VarType::BOOL, gpu_place,
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DataLayout::kAnyLayout, LibraryType::kPlain);
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// data type transform from float32
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{
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Tensor in;
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Tensor in_gpu;
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Tensor out_gpu;
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Tensor out;
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float* in_ptr = in.mutable_data<float>(make_ddim({2, 3}), cpu_place);
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float arr[6] = {0, 1, 2, 3, 4, 5};
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int data_number = sizeof(arr) / sizeof(arr[0]);
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memcpy(in_ptr, arr, sizeof(arr));
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TensorCopy(in, gpu_place, context, &in_gpu);
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TransDataType(kernel_fp32, kernel_fp64, in_gpu, &out_gpu);
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TensorCopy(out_gpu, cpu_place, context, &out);
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context.Wait();
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double* out_data_double = out.data<double>();
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for (int i = 0; i < data_number; ++i) {
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ASSERT_EQ(out_data_double[i], static_cast<double>(arr[i]));
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}
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TransDataType(kernel_fp32, kernel_int32, in_gpu, &out_gpu);
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TensorCopy(out_gpu, cpu_place, context, &out);
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context.Wait();
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int* out_data_int = out.data<int>();
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for (int i = 0; i < data_number; ++i) {
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ASSERT_EQ(out_data_int[i], static_cast<int>(arr[i]));
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}
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}
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// data type transform from/to float16
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{
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Tensor in;
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Tensor in_gpu;
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Tensor out_gpu;
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Tensor out;
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float16* ptr = in.mutable_data<float16>(make_ddim({2, 3}), cpu_place);
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float16 arr[6] = {float16(0), float16(1), float16(2),
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float16(3), float16(4), float16(5)};
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int data_number = sizeof(arr) / sizeof(arr[0]);
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memcpy(ptr, arr, sizeof(arr));
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TensorCopy(in, gpu_place, context, &in_gpu);
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// transform from float16 to other data types
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TransDataType(kernel_fp16, kernel_fp32, in_gpu, &out_gpu);
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TensorCopy(out_gpu, cpu_place, context, &out);
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context.Wait();
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float* out_data_float = out.data<float>();
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for (int i = 0; i < data_number; ++i) {
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ASSERT_EQ(out_data_float[i], static_cast<float>(ptr[i]));
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}
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TransDataType(kernel_fp16, kernel_fp64, in_gpu, &out_gpu);
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TensorCopy(out_gpu, cpu_place, context, &out);
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context.Wait();
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double* out_data_double = out.data<double>();
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for (int i = 0; i < data_number; ++i) {
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ASSERT_EQ(out_data_double[i], static_cast<double>(ptr[i]));
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}
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TransDataType(kernel_fp16, kernel_int32, in_gpu, &out_gpu);
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TensorCopy(out_gpu, cpu_place, context, &out);
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context.Wait();
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int* out_data_int = out.data<int>();
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for (int i = 0; i < data_number; ++i) {
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ASSERT_EQ(out_data_int[i], static_cast<int>(ptr[i]));
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}
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TransDataType(kernel_fp16, kernel_int64, in_gpu, &out_gpu);
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TensorCopy(out_gpu, cpu_place, context, &out);
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context.Wait();
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int64_t* out_data_int64 = out.data<int64_t>();
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for (int i = 0; i < data_number; ++i) {
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ASSERT_EQ(out_data_int64[i], static_cast<int64_t>(ptr[i]));
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}
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TransDataType(kernel_fp16, kernel_bool, in_gpu, &out_gpu);
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TensorCopy(out_gpu, cpu_place, context, &out);
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context.Wait();
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bool* out_data_bool = out.data<bool>();
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for (int i = 0; i < data_number; ++i) {
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ASSERT_EQ(out_data_bool[i], static_cast<bool>(ptr[i]));
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}
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// transform float to float16
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float* in_data_float = in.mutable_data<float>(make_ddim({2, 3}), cpu_place);
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for (int i = 0; i < data_number; ++i) {
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in_data_float[i] = i;
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}
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TensorCopy(in, gpu_place, context, &in_gpu);
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TransDataType(kernel_fp32, kernel_fp16, in_gpu, &out_gpu);
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TensorCopy(out_gpu, cpu_place, context, &out);
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context.Wait();
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ptr = out.data<float16>();
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for (int i = 0; i < data_number; ++i) {
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ASSERT_EQ(ptr[i].x, static_cast<float16>(in_data_float[i]).x);
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}
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// transform double to float16
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double* in_data_double =
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in.mutable_data<double>(make_ddim({2, 3}), cpu_place);
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for (int i = 0; i < data_number; ++i) {
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in_data_double[i] = i;
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}
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TensorCopy(in, gpu_place, context, &in_gpu);
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TransDataType(kernel_fp64, kernel_fp16, in_gpu, &out_gpu);
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TensorCopy(out_gpu, cpu_place, context, &out);
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context.Wait();
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ptr = out.data<float16>();
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for (int i = 0; i < data_number; ++i) {
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ASSERT_EQ(ptr[i].x, static_cast<float16>(in_data_double[i]).x);
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}
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// transform int to float16
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int* in_data_int = in.mutable_data<int>(make_ddim({2, 3}), cpu_place);
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for (int i = 0; i < data_number; ++i) {
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in_data_int[i] = i;
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}
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TensorCopy(in, gpu_place, context, &in_gpu);
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TransDataType(kernel_int32, kernel_fp16, in_gpu, &out_gpu);
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TensorCopy(out_gpu, cpu_place, context, &out);
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context.Wait();
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ptr = out.data<float16>();
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for (int i = 0; i < data_number; ++i) {
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ASSERT_EQ(ptr[i].x, static_cast<float16>(in_data_int[i]).x);
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}
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// transform int64 to float16
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int64_t* in_data_int64 =
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in.mutable_data<int64_t>(make_ddim({2, 3}), cpu_place);
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for (int i = 0; i < data_number; ++i) {
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in_data_int64[i] = i;
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}
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TensorCopy(in, gpu_place, context, &in_gpu);
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TransDataType(kernel_int64, kernel_fp16, in_gpu, &out_gpu);
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TensorCopy(out_gpu, cpu_place, context, &out);
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context.Wait();
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ptr = out.data<float16>();
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for (int i = 0; i < data_number; ++i) {
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ASSERT_EQ(ptr[i].x, static_cast<float16>(in_data_int64[i]).x);
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}
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// transform bool to float16
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bool* in_data_bool = in.mutable_data<bool>(make_ddim({2, 3}), cpu_place);
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for (int i = 0; i < data_number; ++i) {
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in_data_bool[i] = i;
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}
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TensorCopy(in, gpu_place, context, &in_gpu);
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TransDataType(kernel_bool, kernel_fp16, in_gpu, &out_gpu);
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TensorCopy(out_gpu, cpu_place, context, &out);
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context.Wait();
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ptr = out.data<float16>();
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for (int i = 0; i < data_number; ++i) {
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ASSERT_EQ(ptr[i].x, static_cast<float16>(in_data_bool[i]).x);
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}
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}
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}
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