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fix various typos

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This commit is contained in:
sciencewhiz
2021-09-22 16:15:06 +00:00
committed by Antonio Sánchez
parent 3753e6a2b3
commit 4b6036e276
32 changed files with 43 additions and 43 deletions
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6
unsupported/Eigen/CXX11/src/Tensor/TensorContractionSycl.h
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@@ -522,10 +522,10 @@ class TensorContractionKernel {
* \param rhs_scratch_extract : determines the RHS tile memory. It is either private or local memory based on the
* selected contraction_type.
*
* \param lhs_extract_index: determins the position of each thread on a local memory for lhs input. When private
* \param lhs_extract_index: determines the position of each thread on a local memory for lhs input. When private
* memory is used this is set to zero as this is not applicable in case of private memory.
*
* \param rhs_extract_index: determins the position of each thread on a local memory for rhs input. When private
* \param rhs_extract_index: determines the position of each thread on a local memory for rhs input. When private
* memory is used this is set to zero as this is not applicable in case of private memory.
*
* \param lhs_scratch_compute : determines the location to load for computation for lhs_local memory. This is the
@@ -1236,7 +1236,7 @@ struct GeneralVectorTensor {
*
* \param out_res: determines the output tensor containing the contraction result
*
* \param rng: determins the total input data size
* \param rng: determines the total input data size
*/
template <typename OutScalar, typename LhsScalar, typename RhsScalar, typename OutAccessor, typename LhsMapper,
typename RhsMapper, typename StorageIndex, bool Vectorizable>

4
unsupported/Eigen/CXX11/src/Tensor/TensorContractionThreadPool.h
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@@ -98,7 +98,7 @@ struct TensorEvaluator<const TensorContractionOp<Indices, LeftArgType, RightArgT
// context from the heap.
//
// (*) EvalParallelContext & EvalShardedByInnerDimContext owns all the state
// and temporary buffers, requried for executing the tensor contraction.
// and temporary buffers, required for executing the tensor contraction.
// They are responsible for cleaning it up after contraction is done.
static const bool IsEvalInSyncMode =
std::is_same<DoneCallback, NoCallback>::value;
@@ -700,7 +700,7 @@ struct TensorEvaluator<const TensorContractionOp<Indices, LeftArgType, RightArgT
!is_rhs && std::is_same<BlockType, LhsBlock>::value;
static const bool kIsRhs =
is_rhs && std::is_same<BlockType, RhsBlock>::value;
static_assert(kIsLhs || kIsRhs, "Unkown block type");
static_assert(kIsLhs || kIsRhs, "Unknown block type");
using Blocks = ThreadLocalBlocks<BlockType>;

4
unsupported/Eigen/CXX11/src/Tensor/TensorDeviceSycl.h
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@@ -246,7 +246,7 @@ class QueueInterface {
}
/// The memcpyHostToDevice is used to copy the data from host to device
/// The destination pointer could be deleted before the copy happend which is
/// The destination pointer could be deleted before the copy happened which is
/// why a callback function is needed. By default if none is provided, the
/// function is blocking.
EIGEN_STRONG_INLINE void memcpyHostToDevice(
@@ -274,7 +274,7 @@ class QueueInterface {
}
/// The memcpyDeviceToHost is used to copy the data from device to host.
/// The source pointer could be deleted before the copy happend which is
/// The source pointer could be deleted before the copy happened which is
/// why a callback function is needed. By default if none is provided, the
/// function is blocking.
EIGEN_STRONG_INLINE void memcpyDeviceToHost(

2
unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h
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@@ -31,7 +31,7 @@ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T* constCast(const T* data) {
}
// The StorageMemory class is a container of the device specific pointer
// used for refering to a Pointer on TensorEvaluator class. While the TensorExpression
// used for referring to a Pointer on TensorEvaluator class. While the TensorExpression
// is a device-agnostic type and need MakePointer class for type conversion,
// the TensorEvaluator class can be specialized for a device, hence it is possible
// to construct different types of temproray storage memory in TensorEvaluator

4
unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h
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@@ -142,7 +142,7 @@ template <typename T> class UniformRandomGenerator {
// but for SYCL ((CLOCK * 6364136223846793005ULL) + 0xda3e39cb94b95bdbULL) is passed to each thread and each thread adds
// the (global_thread_id* 6364136223846793005ULL) for itself only once, in order to complete the construction
// similar to CUDA Therefore, the thread Id injection is not available at this stage.
//However when the operator() is called the thread ID will be avilable. So inside the opeator,
//However when the operator() is called the thread ID will be available. So inside the opeator,
// we add the thrreadID, BlockId,... (which is equivalent of i)
//to the seed and construct the unique m_state per thead similar to cuda.
m_exec_once =false;
@@ -252,7 +252,7 @@ template <typename T> class NormalRandomGenerator {
//the same for all the thread. As unlike CUDA, the thread.ID, BlockID, etc is not a global function.
// and only available on the Operator() function (which is called on the GPU).
// Therefore, the thread Id injection is not available at this stage. However when the operator()
//is called the thread ID will be avilable. So inside the opeator,
//is called the thread ID will be available. So inside the operator,
// we add the thrreadID, BlockId,... (which is equivalent of i)
//to the seed and construct the unique m_state per thead similar to cuda.
m_exec_once =false;

4
unsupported/Eigen/CXX11/src/ThreadPool/EventCount.h
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@@ -87,7 +87,7 @@ class EventCount {
CheckState(state, true);
uint64_t newstate;
if ((state & kSignalMask) != 0) {
// Consume the signal and return immidiately.
// Consume the signal and return immediately.
newstate = state - kWaiterInc - kSignalInc;
} else {
// Remove this thread from pre-wait counter and add to the waiter stack.
@@ -114,7 +114,7 @@ class EventCount {
CheckState(state, true);
uint64_t newstate = state - kWaiterInc;
// We don't know if the thread was also notified or not,
// so we should not consume a signal unconditionaly.
// so we should not consume a signal unconditionally.
// Only if number of waiters is equal to number of signals,
// we know that the thread was notified and we must take away the signal.
if (((state & kWaiterMask) >> kWaiterShift) ==

2
unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h
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@@ -165,7 +165,7 @@ void constrained_cg(const TMatrix& A, const CMatrix& C, VectorX& x,
p = z + gamma*p;
++iter;
// one dimensionnal optimization
// one dimensional optimization
q = A * p;
lambda = rho / q.dot(p);
for (Index i = 0; i < C.rows(); ++i)

4
unsupported/Eigen/src/IterativeSolvers/IDRS.h
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@@ -20,7 +20,7 @@ namespace Eigen
namespace internal
{
/** \internal Low-level Induced Dimension Reduction algoritm
/** \internal Low-level Induced Dimension Reduction algorithm
\param A The matrix A
\param b The right hand side vector b
\param x On input and initial solution, on output the computed solution.
@@ -372,7 +372,7 @@ namespace Eigen
/** \internal */
/** Loops over the number of columns of b and does the following:
1. sets the tolerence and maxIterations
1. sets the tolerance and maxIterations
2. Calls the function that has the core solver routine
*/
template <typename Rhs, typename Dest>