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Part two of renaming Cuda?DLaunchConfig to Gpu?DLaunchConfig: fix call sites.

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PiperOrigin-RevId: 248708765
This commit is contained in:
A. Unique TensorFlower 2019-05-17 06:29:17 -07:00 committed by TensorFlower Gardener
parent cc03fdce67
commit f9a4227ae5
4 changed files with 15 additions and 15 deletions
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4
tensorflow/core/kernels/concat_lib_gpu_impl.cu.cc
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@ -140,8 +140,8 @@ void ConcatGPUImpl(const Eigen::GpuDevice& gpu_device,
const GpuDeviceArrayStruct<IntType>& output_scan,
bool fixed_size, int split_size,
typename TTypes<T, 2>::Matrix* output) {
auto config = GetCuda2DLaunchConfig(output->dimension(1),
output->dimension(0), gpu_device);
auto config = GetGpu2DLaunchConfig(output->dimension(1), output->dimension(0),
gpu_device);
if (fixed_size) {
TF_CHECK_OK(CudaLaunchKernel(

2
tensorflow/core/kernels/split_lib_gpu.cu.cc
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@ -222,7 +222,7 @@ void SplitVOpGPULaunch<T, IntType>::Run(
gpu_device.stream(), input_ptr, total_rows,
total_cols, output_ptr_data));
} else {
auto config = GetCuda2DLaunchConfig(total_cols, total_rows, gpu_device);
auto config = GetGpu2DLaunchConfig(total_cols, total_rows, gpu_device);
IntType smem_max = gpu_device.sharedMemPerBlock();
IntType smem_usage = output_scan.size * sizeof(IntType);
// performance crossover is less than using maximum available shared

4
tensorflow/core/kernels/svd_op_gpu.cu.cc
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@ -59,7 +59,7 @@ namespace {
// The result is stored in V[batch] and has the same sign as the
// real value of V (which should be computed)
template <class Scalar>
__global__ void ComputeValueOfVKernel(Cuda2DLaunchConfig config, int64 m,
__global__ void ComputeValueOfVKernel(Gpu2DLaunchConfig config, int64 m,
int64 ldu, const Scalar* M,
const Scalar* U, const Scalar* S,
Scalar* V) {
@ -195,7 +195,7 @@ class SvdOpGpu : public AsyncOpKernel {
// 1. compute the (batched) sum
const GPUDevice& d = context->eigen_device<GPUDevice>();
d.memset(outputV_ptr, 0, batch_size * sizeof(Scalar));
Cuda2DLaunchConfig cfg2D = GetCuda2DLaunchConfig(batch_size, m, d);
Gpu2DLaunchConfig cfg2D = GetCuda2DLaunchConfig(batch_size, m, d);
TF_CHECK_OK(CudaLaunchKernel(ComputeValueOfVKernel<Scalar>,
cfg2D.block_count, cfg2D.thread_per_block, 0,
d.stream(), cfg2D, m, full_matrices_ ? m : p,

20
tensorflow/core/util/gpu_kernel_helper_test.cu.cc
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@ -54,7 +54,7 @@ __global__ void Count1D(GpuLaunchConfig config, int bufsize, int* outbuf) {
atomicAdd(&outbuf[x % bufsize], 1);
}
}
__global__ void Count2D(Cuda2DLaunchConfig config, int bufsize, int* outbuf) {
__global__ void Count2D(Gpu2DLaunchConfig config, int bufsize, int* outbuf) {
CUDA_AXIS_KERNEL_LOOP(x, config.virtual_thread_count.x, X) {
if (x < 0) { // x might overflow when testing extreme case
break;
@ -68,7 +68,7 @@ __global__ void Count2D(Cuda2DLaunchConfig config, int bufsize, int* outbuf) {
}
}
}
__global__ void Count3D(Cuda3DLaunchConfig config, int bufsize, int* outbuf) {
__global__ void Count3D(Gpu3DLaunchConfig config, int bufsize, int* outbuf) {
CUDA_AXIS_KERNEL_LOOP(x, config.virtual_thread_count.x, X) {
if (x < 0) { // x might overflow when testing extreme case
break;
@ -189,7 +189,7 @@ TEST_F(GpuLaunchConfigTest, GetGpuLaunchConfig) {
#undef TEST_LAUNCH_PARAMETER
}
bool operator==(const Cuda2DLaunchConfig& a, const Cuda2DLaunchConfig& b) {
bool operator==(const Gpu2DLaunchConfig& a, const Cuda2DLaunchConfig& b) {
return a.thread_per_block.x == b.thread_per_block.x &&
a.thread_per_block.y == b.thread_per_block.y &&
a.thread_per_block.z == b.thread_per_block.z &&
@ -201,8 +201,8 @@ bool operator==(const Cuda2DLaunchConfig& a, const Cuda2DLaunchConfig& b) {
a.thread_per_block.z == b.thread_per_block.z;
}
TEST_F(GpuLaunchConfigTest, GetCuda2DLaunchConfig) {
Cuda2DLaunchConfig cfg;
TEST_F(GpuLaunchConfigTest, GetGpu2DLaunchConfig) {
Gpu2DLaunchConfig cfg;
GpuLaunchConfig cfg1d;
// test valid inputs
@ -212,7 +212,7 @@ TEST_F(GpuLaunchConfigTest, GetCuda2DLaunchConfig) {
cfg1d.thread_per_block, 0, d.stream(), cfg1d, \
outbuf)); \
CUDA_ASSERT_SUCCESS \
cfg = GetCuda2DLaunchConfig(dimx, dimy, d); \
cfg = GetGpu2DLaunchConfig(dimx, dimy, d); \
TF_EXPECT_OK(CudaLaunchKernel(Count2D, cfg.block_count, \
cfg.thread_per_block, 0, d.stream(), cfg, \
bufsize, outbuf)); \
@ -224,7 +224,7 @@ TEST_F(GpuLaunchConfigTest, GetCuda2DLaunchConfig) {
cfg1d.thread_per_block, 0, d.stream(), cfg1d, \
outbuf)); \
CUDA_ASSERT_SUCCESS \
cfg = GetCuda2DLaunchConfig(dimx, dimy, d, Count2D, 0, 0); \
cfg = GetGpu2DLaunchConfig(dimx, dimy, d, Count2D, 0, 0); \
TF_EXPECT_OK(CudaLaunchKernel(Count2D, cfg.block_count, \
cfg.thread_per_block, 0, d.stream(), cfg, \
bufsize, outbuf)); \
@ -245,8 +245,8 @@ TEST_F(GpuLaunchConfigTest, GetCuda2DLaunchConfig) {
#undef TEST_LAUNCH_PARAMETER
}
TEST_F(GpuLaunchConfigTest, GetCuda3DLaunchConfig) {
Cuda3DLaunchConfig cfg;
TEST_F(GpuLaunchConfigTest, GetGpu3DLaunchConfig) {
Gpu3DLaunchConfig cfg;
GpuLaunchConfig cfg1d;
// test valid inputs
@ -256,7 +256,7 @@ TEST_F(GpuLaunchConfigTest, GetCuda3DLaunchConfig) {
cfg1d.thread_per_block, 0, d.stream(), cfg1d, \
outbuf)); \
CUDA_ASSERT_SUCCESS \
cfg = GetCuda3DLaunchConfig(dimx, dimy, dimz, d, Count3D, 0, 0); \
cfg = GetGpu3DLaunchConfig(dimx, dimy, dimz, d, Count3D, 0, 0); \
TF_EXPECT_OK(CudaLaunchKernel(Count3D, cfg.block_count, \
cfg.thread_per_block, 0, d.stream(), cfg, \
bufsize, outbuf)); \