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remove a newly introduced redundant typedef - sorry.

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This commit is contained in:
Benoit Jacob 2015-02-18 15:05:01 -05:00
parent 9bd8a4bab5
commit 0ed00d5438
1 changed files with 3 additions and 2 deletions
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5
Eigen/src/Core/products/GeneralBlockPanelKernel.h
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@ -83,9 +83,10 @@ inline void manage_caching_sizes(Action action, std::ptrdiff_t* l1, std::ptrdiff
template<typename LhsScalar, typename RhsScalar, int KcFactor> template<typename LhsScalar, typename RhsScalar, int KcFactor>
void computeProductBlockingSizes(Index& k, Index& m, Index& n, Index num_threads = 1) void computeProductBlockingSizes(Index& k, Index& m, Index& n, Index num_threads = 1)
{ {
typedef gebp_traits<LhsScalar,RhsScalar> Traits;
#ifdef EIGEN_TEST_SPECIFIC_BLOCKING_SIZES #ifdef EIGEN_TEST_SPECIFIC_BLOCKING_SIZES
EIGEN_UNUSED_VARIABLE(num_threads); EIGEN_UNUSED_VARIABLE(num_threads);
typedef gebp_traits<LhsScalar,RhsScalar> Traits;
enum { enum {
kr = 16, kr = 16,
mr = Traits::mr, mr = Traits::mr,
@ -99,6 +100,7 @@ void computeProductBlockingSizes(Index& k, Index& m, Index& n, Index num_threads
if (n > nr) n -= n % nr; if (n > nr) n -= n % nr;
return; return;
#endif #endif
// Explanations: // Explanations:
// Let's recall that the product algorithms form mc x kc vertical panels A' on the lhs and // Let's recall that the product algorithms form mc x kc vertical panels A' on the lhs and
// kc x nc blocks B' on the rhs. B' has to fit into L2/L3 cache. Moreover, A' is processed // kc x nc blocks B' on the rhs. B' has to fit into L2/L3 cache. Moreover, A' is processed
@ -108,7 +110,6 @@ void computeProductBlockingSizes(Index& k, Index& m, Index& n, Index num_threads
manage_caching_sizes(GetAction, &l1, &l2, &l3); manage_caching_sizes(GetAction, &l1, &l2, &l3);
if (num_threads > 1) { if (num_threads > 1) {
typedef gebp_traits<LhsScalar,RhsScalar> Traits;
typedef typename Traits::ResScalar ResScalar; typedef typename Traits::ResScalar ResScalar;
enum { enum {
kdiv = KcFactor * (Traits::mr * sizeof(LhsScalar) + Traits::nr * sizeof(RhsScalar)), kdiv = KcFactor * (Traits::mr * sizeof(LhsScalar) + Traits::nr * sizeof(RhsScalar)),