experiments/STT-tensorflow
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updating testcases to work correctly with ROCm

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This commit is contained in:
Deven Desai 2019-08-08 20:42:22 +00:00
parent fb2f10e281
commit 2eecf54f92
4 changed files with 40 additions and 6 deletions
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10
tensorflow/core/common_runtime/direct_session_test.cc
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@ -51,9 +51,11 @@ limitations under the License.
#include "tensorflow/core/public/session_options.h" #include "tensorflow/core/public/session_options.h"
#include "tensorflow/core/util/device_name_utils.h" #include "tensorflow/core/util/device_name_utils.h"
#ifdef GOOGLE_CUDA #if GOOGLE_CUDA
#include "third_party/gpus/cuda/include/cuda.h" #include "third_party/gpus/cuda/include/cuda.h"
#include "third_party/gpus/cuda/include/cuda_runtime_api.h" #include "third_party/gpus/cuda/include/cuda_runtime_api.h"
#elif TENSORFLOW_USE_ROCM
#include "rocm/include/hip/hip_runtime.h"
#endif // GOOGLE_CUDA #endif // GOOGLE_CUDA
namespace tensorflow { namespace tensorflow {
@ -2089,6 +2091,12 @@ bool IsCUDATensor(const Tensor& t) {
if (err == cudaErrorInvalidValue) return false; if (err == cudaErrorInvalidValue) return false;
CHECK_EQ(cudaSuccess, err) << cudaGetErrorString(err); CHECK_EQ(cudaSuccess, err) << cudaGetErrorString(err);
return (attributes.memoryType == cudaMemoryTypeDevice); return (attributes.memoryType == cudaMemoryTypeDevice);
#elif TENSORFLOW_USE_ROCM
hipPointerAttribute_t attributes;
hipError_t err = hipPointerGetAttributes(&attributes, t.tensor_data().data());
if (err == hipErrorInvalidValue) return false;
CHECK_EQ(hipSuccess, err) << hipGetErrorString(err);
return (attributes.memoryType == hipMemoryTypeDevice);
#else #else
return false; return false;
#endif #endif

14
tensorflow/core/common_runtime/process_function_library_runtime_test.cc
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@ -33,9 +33,11 @@ limitations under the License.
#include "tensorflow/core/public/session_options.h" #include "tensorflow/core/public/session_options.h"
#include "tensorflow/core/public/version.h" #include "tensorflow/core/public/version.h"
#ifdef GOOGLE_CUDA #if GOOGLE_CUDA
#include "third_party/gpus/cuda/include/cuda.h" #include "third_party/gpus/cuda/include/cuda.h"
#include "third_party/gpus/cuda/include/cuda_runtime_api.h" #include "third_party/gpus/cuda/include/cuda_runtime_api.h"
#elif TENSORFLOW_USE_ROCM
#include "rocm/include/hip/hip_runtime.h"
#endif // GOOGLE_CUDA #endif // GOOGLE_CUDA
namespace tensorflow { namespace tensorflow {
@ -122,7 +124,7 @@ class ProcessFunctionLibraryRuntimeTest : public ::testing::Test {
} }
Tensor GPUToCPU(const Tensor& device_tensor) { Tensor GPUToCPU(const Tensor& device_tensor) {
#ifdef GOOGLE_CUDA #if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
CHECK(gpu_device_); CHECK(gpu_device_);
CHECK(gpu_device_->tensorflow_gpu_device_info() != nullptr); CHECK(gpu_device_->tensorflow_gpu_device_info() != nullptr);
DeviceContext* device_context = DeviceContext* device_context =
@ -146,7 +148,7 @@ class ProcessFunctionLibraryRuntimeTest : public ::testing::Test {
} }
Tensor CPUToGPU(const Tensor& cpu_tensor) { Tensor CPUToGPU(const Tensor& cpu_tensor) {
#ifdef GOOGLE_CUDA #if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
CHECK(gpu_device_); CHECK(gpu_device_);
CHECK(gpu_device_->tensorflow_gpu_device_info() != nullptr); CHECK(gpu_device_->tensorflow_gpu_device_info() != nullptr);
DeviceContext* device_context = DeviceContext* device_context =
@ -461,6 +463,12 @@ bool IsCUDATensor(const Tensor& t) {
if (err == cudaErrorInvalidValue) return false; if (err == cudaErrorInvalidValue) return false;
CHECK_EQ(cudaSuccess, err) << cudaGetErrorString(err); CHECK_EQ(cudaSuccess, err) << cudaGetErrorString(err);
return (attributes.memoryType == cudaMemoryTypeDevice); return (attributes.memoryType == cudaMemoryTypeDevice);
#elif TENSORFLOW_USE_ROCM
hipPointerAttribute_t attributes;
hipError_t err = hipPointerGetAttributes(&attributes, t.tensor_data().data());
if (err == hipErrorInvalidValue) return false;
CHECK_EQ(hipSuccess, err) << hipGetErrorString(err);
return (attributes.memoryType == hipMemoryTypeDevice);
#else #else
CHECK(false) CHECK(false)
<< "IsCUDATensor should not be called when CUDA is not available"; << "IsCUDATensor should not be called when CUDA is not available";

20
tensorflow/core/grappler/clusters/utils_test.cc
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@ -40,6 +40,18 @@ TEST(UtilsTest, GetLocalGPUInfo) {
properties = GetLocalGPUInfo(PlatformGpuId(0)); properties = GetLocalGPUInfo(PlatformGpuId(0));
EXPECT_EQ("GPU", properties.type()); EXPECT_EQ("GPU", properties.type());
EXPECT_EQ("NVIDIA", properties.vendor()); EXPECT_EQ("NVIDIA", properties.vendor());
#elif TENSORFLOW_USE_ROCM
LOG(INFO) << "ROCm is enabled.";
DeviceProperties properties;
// Invalid platform GPU ID.
properties = GetLocalGPUInfo(PlatformGpuId(100));
EXPECT_EQ("UNKNOWN", properties.type());
// Succeed when a valid platform GPU id was inserted.
properties = GetLocalGPUInfo(PlatformGpuId(0));
EXPECT_EQ("GPU", properties.type());
EXPECT_EQ("Advanced Micro Devices, Inc", properties.vendor());
#else #else
LOG(INFO) << "CUDA is not enabled."; LOG(INFO) << "CUDA is not enabled.";
DeviceProperties properties; DeviceProperties properties;
@ -73,6 +85,8 @@ TEST(UtilsTest, GetDeviceInfo) {
EXPECT_EQ("GPU", properties.type()); EXPECT_EQ("GPU", properties.type());
#if GOOGLE_CUDA #if GOOGLE_CUDA
EXPECT_EQ("NVIDIA", properties.vendor()); EXPECT_EQ("NVIDIA", properties.vendor());
#elif TENSORFLOW_USE_ROCM
EXPECT_EQ("Advanced Micro Devices, Inc", properties.vendor());
#endif #endif
// TF to platform GPU id mapping entry doesn't exist. // TF to platform GPU id mapping entry doesn't exist.
@ -81,7 +95,7 @@ TEST(UtilsTest, GetDeviceInfo) {
properties = GetDeviceInfo(device); properties = GetDeviceInfo(device);
EXPECT_EQ("UNKNOWN", properties.type()); EXPECT_EQ("UNKNOWN", properties.type());
#if GOOGLE_CUDA #if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
// Invalid platform GPU id. // Invalid platform GPU id.
TF_ASSERT_OK( TF_ASSERT_OK(
GpuIdManager::InsertTfPlatformGpuIdPair(TfGpuId(0), PlatformGpuId(100))); GpuIdManager::InsertTfPlatformGpuIdPair(TfGpuId(0), PlatformGpuId(100)));
@ -94,7 +108,11 @@ TEST(UtilsTest, GetDeviceInfo) {
device.id = 1; device.id = 1;
properties = GetDeviceInfo(device); properties = GetDeviceInfo(device);
EXPECT_EQ("GPU", properties.type()); EXPECT_EQ("GPU", properties.type());
#if GOOGLE_CUDA
EXPECT_EQ("NVIDIA", properties.vendor()); EXPECT_EQ("NVIDIA", properties.vendor());
#elif TENSORFLOW_USE_ROCM
EXPECT_EQ("Advanced Micro Devices, Inc", properties.vendor());
#endif
#endif #endif
} }

2
tensorflow/core/grappler/optimizers/pin_to_host_optimizer_test.cc
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@ -203,7 +203,7 @@ TEST_F(PinToHostOptimizerTest, Identity) {
// If CUDA, then there is a GPU kernel registration that is pinned to Host // If CUDA, then there is a GPU kernel registration that is pinned to Host
// memory. Consequently, `b` will be mapped to Host correct if there is // memory. Consequently, `b` will be mapped to Host correct if there is
// a GPU kernel registered. // a GPU kernel registered.
#if GOOGLE_CUDA #if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
EXPECT_EQ(node.device(), "/device:CPU:0"); EXPECT_EQ(node.device(), "/device:CPU:0");
#else #else
EXPECT_TRUE(node.device().empty()); EXPECT_TRUE(node.device().empty());