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Fix some nits.

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Change-Id: I1af74d6ae8c6c368642989f1b1e857999264a454
This commit is contained in:
Sameer Agarwal
2022-02-08 13:40:39 -08:00
parent 36d6d86908
commit 2092a720ec
3 changed files with 90 additions and 97 deletions
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internal/ceres/dense_cholesky.cc
+86 -94
View File
@@ -145,9 +145,9 @@ LinearSolverTerminationType LAPACKDenseCholesky::Factorize(
if (info < 0) {
termination_type_ = LINEAR_SOLVER_FATAL_ERROR;
LOG(FATAL) << "Congratulations, you found a bug in Ceres."
<< "Please report it."
<< "LAPACK::dpotrf fatal error."
LOG(FATAL) << "Congratulations, you found a bug in Ceres. "
<< "Please report it. "
<< "LAPACK::dpotrf fatal error. "
<< "Argument: " << -info << " is invalid.";
} else if (info > 0) {
termination_type_ = LINEAR_SOLVER_FAILURE;
@@ -175,9 +175,9 @@ LinearSolverTerminationType LAPACKDenseCholesky::Solve(const double* rhs,
if (info < 0) {
termination_type_ = LINEAR_SOLVER_FATAL_ERROR;
LOG(FATAL) << "Congratulations, you found a bug in Ceres."
<< "Please report it."
<< "LAPACK::dpotrs fatal error."
LOG(FATAL) << "Congratulations, you found a bug in Ceres. "
<< "Please report it. "
<< "LAPACK::dpotrs fatal error. "
<< "Argument: " << -info << " is invalid.";
}
@@ -201,7 +201,8 @@ bool CUDADenseCholesky32Bit::Init(std::string* message) {
cusolverDnDestroy(cusolver_handle_);
return false;
}
if (cusolverDnSetStream(cusolver_handle_, stream_) != CUSOLVER_STATUS_SUCCESS) {
if (cusolverDnSetStream(cusolver_handle_, stream_) !=
CUSOLVER_STATUS_SUCCESS) {
*message = "cuSolverDN::cusolverDnSetStream failed.";
cudaStreamDestroy(stream_);
cusolverDnDestroy(cusolver_handle_);
@@ -220,9 +221,7 @@ CUDADenseCholesky32Bit::~CUDADenseCholesky32Bit() {
}
LinearSolverTerminationType CUDADenseCholesky32Bit::Factorize(
int num_cols,
double* lhs,
std::string* message) {
int num_cols, double* lhs, std::string* message) {
factorize_result_ = LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR;
// Allocate GPU memory if necessary.
lhs_.Reserve(num_cols * num_cols);
@@ -232,11 +231,11 @@ LinearSolverTerminationType CUDADenseCholesky32Bit::Factorize(
// Allocate scratch space on GPU.
int device_workspace_size = 0;
if (cusolverDnDpotrf_bufferSize(cusolver_handle_,
CUBLAS_FILL_MODE_LOWER,
num_cols,
lhs_.data(),
num_cols,
&device_workspace_size) !=
CUBLAS_FILL_MODE_LOWER,
num_cols,
lhs_.data(),
num_cols,
&device_workspace_size) !=
CUSOLVER_STATUS_SUCCESS) {
*message = "cuSolverDN::cusolverDnDpotrf_bufferSize failed.";
return LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR;
@@ -245,18 +244,18 @@ LinearSolverTerminationType CUDADenseCholesky32Bit::Factorize(
device_workspace_.Reserve(device_workspace_size);
// Run the actual factorization (potrf)
if (cusolverDnDpotrf(cusolver_handle_,
CUBLAS_FILL_MODE_LOWER,
num_cols,
lhs_.data(),
num_cols,
reinterpret_cast<double*>(device_workspace_.data()),
device_workspace_.size(),
error_.data()) != CUSOLVER_STATUS_SUCCESS) {
CUBLAS_FILL_MODE_LOWER,
num_cols,
lhs_.data(),
num_cols,
reinterpret_cast<double*>(device_workspace_.data()),
device_workspace_.size(),
error_.data()) != CUSOLVER_STATUS_SUCCESS) {
*message = "cuSolverDN::cusolverDnDpotrf failed.";
return LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR;
}
if (cudaDeviceSynchronize() != cudaSuccess ||
cudaStreamSynchronize(stream_), cudaSuccess) {
if (cudaDeviceSynchronize() != cudaSuccess || cudaStreamSynchronize(stream_),
cudaSuccess) {
*message = "Cuda device synchronization failed.";
return LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR;
}
@@ -266,7 +265,7 @@ LinearSolverTerminationType CUDADenseCholesky32Bit::Factorize(
if (error < 0) {
LOG(FATAL) << "Congratulations, you found a bug in Ceres - "
<< "please report it. "
<< "cuSolverDN::cusolverDnXpotrf fatal error."
<< "cuSolverDN::cusolverDnXpotrf fatal error. "
<< "Argument: " << -error << " is invalid.";
// The following line is unreachable, but return failure just to be
// pedantic, since the compiler does not know that.
@@ -285,9 +284,7 @@ LinearSolverTerminationType CUDADenseCholesky32Bit::Factorize(
}
LinearSolverTerminationType CUDADenseCholesky32Bit::Solve(
const double* rhs,
double* solution,
std::string* message) {
const double* rhs, double* solution, std::string* message) {
if (factorize_result_ != LinearSolverTerminationType::LINEAR_SOLVER_SUCCESS) {
*message = "Factorize did not complete succesfully previously.";
return factorize_result_;
@@ -296,19 +293,19 @@ LinearSolverTerminationType CUDADenseCholesky32Bit::Solve(
rhs_.CopyToGpu(rhs, num_cols_);
// Solve the system.
if (cusolverDnDpotrs(cusolver_handle_,
CUBLAS_FILL_MODE_LOWER,
num_cols_,
1,
lhs_.data(),
num_cols_,
rhs_.data(),
num_cols_,
error_.data()) != CUSOLVER_STATUS_SUCCESS) {
CUBLAS_FILL_MODE_LOWER,
num_cols_,
1,
lhs_.data(),
num_cols_,
rhs_.data(),
num_cols_,
error_.data()) != CUSOLVER_STATUS_SUCCESS) {
*message = "cuSolverDN::cusolverDnDpotrs failed.";
return LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR;
}
if (cudaDeviceSynchronize() != cudaSuccess ||
cudaStreamSynchronize(stream_), cudaSuccess) {
if (cudaDeviceSynchronize() != cudaSuccess || cudaStreamSynchronize(stream_),
cudaSuccess) {
*message = "Cuda device synchronization failed.";
return LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR;
}
@@ -317,9 +314,9 @@ LinearSolverTerminationType CUDADenseCholesky32Bit::Solve(
// Copy X from GPU to host.
rhs_.CopyToHost(solution, num_cols_);
if (error != 0) {
LOG(FATAL) << "Congratulations, you found a bug in Ceres."
LOG(FATAL) << "Congratulations, you found a bug in Ceres. "
<< "Please report it."
<< "cuSolverDN::cusolverDnDpotrs fatal error."
<< "cuSolverDN::cusolverDnDpotrs fatal error. "
<< "Argument: " << -error << " is invalid.";
}
// Copy error variable from GPU to host.
@@ -329,7 +326,7 @@ LinearSolverTerminationType CUDADenseCholesky32Bit::Solve(
}
std::unique_ptr<CUDADenseCholesky32Bit> CUDADenseCholesky32Bit::Create(
const LinearSolver::Options& options) {
const LinearSolver::Options& options) {
if (options.dense_linear_algebra_library_type != CUDA) {
// The user called the wrong factory method.
return nullptr;
@@ -346,7 +343,7 @@ std::unique_ptr<CUDADenseCholesky32Bit> CUDADenseCholesky32Bit::Create(
}
std::unique_ptr<CUDADenseCholesky64Bit> CUDADenseCholesky64Bit::Create(
const LinearSolver::Options& options) {
const LinearSolver::Options& options) {
if (options.dense_linear_algebra_library_type != CUDA) {
// The user called the wrong factory method.
return nullptr;
@@ -373,17 +370,15 @@ bool CUDADenseCholesky64Bit::Init(std::string* message) {
return false;
}
LinearSolverTerminationType CUDADenseCholesky64Bit::Factorize(
int,
double*,
std::string*) {
LinearSolverTerminationType CUDADenseCholesky64Bit::Factorize(int,
double*,
std::string*) {
return LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR;
}
LinearSolverTerminationType CUDADenseCholesky64Bit::Solve(
const double*,
double*,
std::string*) {
LinearSolverTerminationType CUDADenseCholesky64Bit::Solve(const double*,
double*,
std::string*) {
return LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR;
}
@@ -399,7 +394,8 @@ bool CUDADenseCholesky64Bit::Init(std::string* message) {
cusolverDnDestroy(cusolver_handle_);
return false;
}
if (cusolverDnSetStream(cusolver_handle_, stream_) != CUSOLVER_STATUS_SUCCESS) {
if (cusolverDnSetStream(cusolver_handle_, stream_) !=
CUSOLVER_STATUS_SUCCESS) {
*message = "cuSolverDN::cusolverDnSetStream failed.";
cudaStreamDestroy(stream_);
cusolverDnDestroy(cusolver_handle_);
@@ -418,9 +414,7 @@ CUDADenseCholesky64Bit::~CUDADenseCholesky64Bit() {
}
LinearSolverTerminationType CUDADenseCholesky64Bit::Factorize(
int num_cols,
double* lhs,
std::string* message) {
int num_cols, double* lhs, std::string* message) {
factorize_result_ = LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR;
// Allocate GPU memory if necessary.
lhs_.Reserve(num_cols * num_cols);
@@ -431,15 +425,15 @@ LinearSolverTerminationType CUDADenseCholesky64Bit::Factorize(
size_t host_workspace_size = 0;
size_t device_workspace_size = 0;
if (cusolverDnXpotrf_bufferSize(cusolver_handle_,
nullptr,
CUBLAS_FILL_MODE_LOWER,
num_cols,
CUDA_R_64F,
lhs_.data(),
num_cols,
CUDA_R_64F,
&device_workspace_size,
&host_workspace_size) !=
nullptr,
CUBLAS_FILL_MODE_LOWER,
num_cols,
CUDA_R_64F,
lhs_.data(),
num_cols,
CUDA_R_64F,
&device_workspace_size,
&host_workspace_size) !=
CUSOLVER_STATUS_SUCCESS) {
*message = "cuSolverDN::cusolverDnXpotrf_bufferSize failed.";
return LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR;
@@ -450,18 +444,18 @@ LinearSolverTerminationType CUDADenseCholesky64Bit::Factorize(
device_workspace_.Reserve(device_workspace_size);
// Run the actual factorization (potrf)
if (cusolverDnXpotrf(cusolver_handle_,
nullptr,
CUBLAS_FILL_MODE_LOWER,
num_cols,
CUDA_R_64F,
lhs_.data(),
num_cols,
CUDA_R_64F,
device_workspace_.data(),
device_workspace_.size(),
host_workspace_.data(),
host_workspace_.size(),
error_.data()) != CUSOLVER_STATUS_SUCCESS) {
nullptr,
CUBLAS_FILL_MODE_LOWER,
num_cols,
CUDA_R_64F,
lhs_.data(),
num_cols,
CUDA_R_64F,
device_workspace_.data(),
device_workspace_.size(),
host_workspace_.data(),
host_workspace_.size(),
error_.data()) != CUSOLVER_STATUS_SUCCESS) {
*message = "cuSolverDN::cusolverDnXpotrf failed.";
return LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR;
}
@@ -476,7 +470,7 @@ LinearSolverTerminationType CUDADenseCholesky64Bit::Factorize(
if (error < 0) {
LOG(FATAL) << "Congratulations, you found a bug in Ceres - "
<< "please report it. "
<< "cuSolverDN::cusolverDnXpotrf fatal error."
<< "cuSolverDN::cusolverDnXpotrf fatal error. "
<< "Argument: " << -error << " is invalid.";
// The following line is unreachable, but return failure just to be
// pedantic, since the compiler does not know that.
@@ -496,9 +490,7 @@ LinearSolverTerminationType CUDADenseCholesky64Bit::Factorize(
}
LinearSolverTerminationType CUDADenseCholesky64Bit::Solve(
const double* rhs,
double* solution,
std::string* message) {
const double* rhs, double* solution, std::string* message) {
if (factorize_result_ != LinearSolverTerminationType::LINEAR_SOLVER_SUCCESS) {
*message = "Factorize did not complete succesfully previously.";
return factorize_result_;
@@ -507,17 +499,17 @@ LinearSolverTerminationType CUDADenseCholesky64Bit::Solve(
rhs_.CopyToGpu(rhs, num_cols_);
// Solve the system.
if (cusolverDnXpotrs(cusolver_handle_,
nullptr,
CUBLAS_FILL_MODE_LOWER,
num_cols_,
1,
CUDA_R_64F,
lhs_.data(),
num_cols_,
CUDA_R_64F,
rhs_.data(),
num_cols_,
error_.data()) != CUSOLVER_STATUS_SUCCESS) {
nullptr,
CUBLAS_FILL_MODE_LOWER,
num_cols_,
1,
CUDA_R_64F,
lhs_.data(),
num_cols_,
CUDA_R_64F,
rhs_.data(),
num_cols_,
error_.data()) != CUSOLVER_STATUS_SUCCESS) {
*message = "cuSolverDN::cusolverDnXpotrs failed.";
return LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR;
}
@@ -531,9 +523,9 @@ LinearSolverTerminationType CUDADenseCholesky64Bit::Solve(
// Copy error variable from GPU to host.
error_.CopyToHost(&error, 1);
if (error != 0) {
LOG(FATAL) << "Congratulations, you found a bug in Ceres."
<< "Please report it."
<< "cuSolverDN::cusolverDnXpotrs fatal error."
LOG(FATAL) << "Congratulations, you found a bug in Ceres. "
<< "Please report it. "
<< "cuSolverDN::cusolverDnXpotrs fatal error. "
<< "Argument: " << -error << " is invalid.";
}
// Copy X from GPU to host.
@@ -542,7 +534,7 @@ LinearSolverTerminationType CUDADenseCholesky64Bit::Solve(
return LinearSolverTerminationType::LINEAR_SOLVER_SUCCESS;
}
#endif // CERES_CUDA_NO_64BIT_SOLVER_API
#endif // CERES_CUDA_NO_64BIT_SOLVER_API
#endif // CERES_NO_CUDA
internal/ceres/dense_qr.cc
+1
View File
@@ -32,6 +32,7 @@
#include <algorithm>
#include <memory>
#include <string>
#ifndef CERES_NO_LAPACK
internal/ceres/schur_complement_solver.cc
+3 -3
View File
@@ -119,7 +119,7 @@ SchurComplementSolver::SchurComplementSolver(
: options_(options) {
CHECK_GT(options.elimination_groups.size(), 1);
CHECK_GT(options.elimination_groups[0], 0);
CHECK(options.context != NULL);
CHECK(options.context != nullptr);
}
SchurComplementSolver::~SchurComplementSolver() {}
@@ -132,7 +132,7 @@ LinearSolver::Summary SchurComplementSolver::SolveImpl(
EventLogger event_logger("SchurComplementSolver::Solve");
const CompressedRowBlockStructure* bs = A->block_structure();
if (eliminator_.get() == NULL) {
if (eliminator_.get() == nullptr) {
const int num_eliminate_blocks = options_.elimination_groups[0];
const int num_f_blocks = bs->cols.size() - num_eliminate_blocks;
@@ -370,7 +370,7 @@ SparseSchurComplementSolver::SolveReducedLinearSystemUsingConjugateGradients(
// Only SCHUR_JACOBI is supported over here right now.
CHECK_EQ(options().preconditioner_type, SCHUR_JACOBI);
if (preconditioner_.get() == NULL) {
if (preconditioner_.get() == nullptr) {
preconditioner_.reset(new BlockRandomAccessDiagonalMatrix(blocks_));
}