Example #1
0
void SymmetricEuclideanDistanceMatrix(El::UpperOrLower uplo, direction_t dir,
    T alpha, const El::Matrix<T> &A, T beta, El::Matrix<T> &C) {

    T *c = C.Buffer();
    int ldC = C.LDim();

    if (dir == base::COLUMNS) {
        El::Herk(uplo, El::ADJOINT, -2.0 * alpha, A, beta, C);
        //El::Gemm(El::ADJOINT, El::NORMAL, T(-2.0) * alpha, A, A, beta, C);

        El::Matrix<T> N;
        ColumnNrm2(A, N);
        T *nn = N.Buffer();;

        int n = base::Width(A);

        for(El::Int j = 0; j < n; j++)
            for(El::Int i = ((uplo == El::UPPER) ? 0 : j);
                i < ((uplo == El::UPPER) ? (j + 1) : n); i++)
                c[j * ldC + i] += alpha * (nn[i] * nn[i] + nn[j] * nn[j]);

    }

    // TODO the rest of the cases.
}
Example #2
0
void EuclideanDistanceMatrix(direction_t dirA, direction_t dirB, T alpha,
    const El::Matrix<T> &A, const El::Matrix<T> &B,
    T beta, El::Matrix<T> &C) {

    T *c = C.Buffer();
    El::Int ldC = C.LDim();

    if (dirA == base::COLUMNS && dirB == base::COLUMNS) {
        base::Gemm(El::ADJOINT, El::NORMAL, T(-2.0) * alpha, A, B, beta, C);

        El::Matrix<T> NA, NB;
        ColumnNrm2(A, NA);
        ColumnNrm2(B, NB);
        T *na = NA.Buffer(), *nb = NB.Buffer();

        El::Int m = base::Width(A);
        El::Int n = base::Width(B);

        for(El::Int j = 0; j < n; j++)
            for(El::Int i = 0; i < m; i++)
                c[j * ldC + i] += alpha * (na[i] * na[i] + nb[j] * nb[j]);

    }

    // TODO the rest of the cases.
}
void lbann_callback_dump_minibatch_sample_indices::dump_to_file(model *m, Layer *l, int64_t step) {
  // Print minibatch sample indices of input layers
  auto *input = dynamic_cast<generic_input_layer*>(l);
  if (input != nullptr) {
    El::Matrix<El::Int>* indices = l->get_sample_indices_per_mb();
    if (indices == nullptr
        || indices->Height() == 0
        || indices->Width() == 0) {
      return;
    }

    std::ostringstream s;
    s << "mkdir -p " << m_basename;
    const int dir= system(s.str().c_str());
    if (dir< 0) {
      LBANN_ERROR("callback_dump_minibatch_sample_indices is unable to create the target director");
    }

    const std::string file
      = (m_basename
         + _to_string(m->get_execution_mode())
         + "-model" + std::to_string(m->get_comm()->get_trainer_rank())
         + "-rank" + std::to_string(m->get_comm()->get_rank_in_trainer())
         + "-epoch" + std::to_string(m->get_cur_epoch())
         + "-step" + std::to_string(m->get_cur_step())
         + "-" + l->get_name()
         + "-MB_Sample_Indices");
    El::Write(*indices, file, El::ASCII);
  }
}
Example #4
0
void L1DistanceMatrix(direction_t dirA, direction_t dirB, T alpha,
    const El::Matrix<T> &A, const El::Matrix<T> &B,
    T beta, El::Matrix<T> &C) {

    // TODO verify sizes

    const T *a = A.LockedBuffer();
    El::Int ldA = A.LDim();

    const T *b = B.LockedBuffer();
    El::Int ldB = B.LDim();

    T *c = C.Buffer();
    El::Int ldC = C.LDim();

    El::Int d = A.Height();

    /* Not the most efficient way... but mimicking BLAS is too much work! */
    if (dirA == base::COLUMNS && dirB == base::COLUMNS) {
        for (El::Int j = 0; j < B.Width(); j++)
            for (El::Int i = 0; i < A.Width(); i++) {
                T v = 0.0;
                for (El::Int k = 0; k < d; k++)
                    v += std::abs(b[j * ldB + k] - a[i * ldA + k]);
                c[j * ldC + i] = beta * c[j * ldC + i] + alpha * v;
            }

    }

    // TODO the rest of the cases.
}
Example #5
0
    void apply_inverse_impl(El::Matrix<ValueType>& A,
                            skylark::sketch::columnwise_tag) const {
        ValueType* AA = A.Buffer();
        int j;

#       ifdef SKYLARK_HAVE_OPENMP
#       pragma omp parallel for private(j)
#       endif
        for (j = 0; j < A.Width(); j++)
            ExecuteFun(_plan_inverse, AA + j * A.LDim(), AA + j * A.LDim());
    }
Example #6
0
    void apply_impl(El::Matrix<value_type>& A,
                    skylark::sketch::columnwise_tag) const {
        ValueType* AA = A.Buffer();
        int j;

#       ifdef SKYLARK_HAVE_OPENMP
#       pragma omp parallel for private(j)
#       endif
        for (j = 0; j < A.Width(); j++)
            wht_apply(_tree, 1, AA + j * A.LDim());
    }
Example #7
0
    void apply_inverse_impl(El::Matrix<value_type>& A,
        skylark::sketch::rowwise_tag) const {
        ValueType* AA = A.Buffer();
        int j;

#       ifdef SKYLARK_HAVE_OPENMP
#       pragma omp parallel for private(j)
#       endif
        for (j = 0; j < A.Width(); j++)
            wht_apply(_tree, A.Height(), AA + j);
        // Not sure stride is used correctly here.
    }
Example #8
0
    void apply_impl(El::Matrix<ValueType>& A,
                    skylark::sketch::rowwise_tag) const {
        // Using transpositions instead of moving to the advanced interface
        // of FFTW
        El::Matrix<ValueType> matrix;
        El::Transpose(A, matrix);
        ValueType* matrix_buffer = matrix.Buffer();
        int j;

#       ifdef SKYLARK_HAVE_OPENMP
#       pragma omp parallel for private(j)
#       endif
        for (j = 0; j < matrix.Width(); j++)
            ExecuteFun(_plan, matrix_buffer + j * matrix.LDim(),
                matrix_buffer + j * matrix.LDim());
        El::Transpose(matrix, A);
    }
Example #9
0
void SymmetricL1DistanceMatrix(El::UpperOrLower uplo, direction_t dir, T alpha,
    const El::Matrix<T> &A, T beta, El::Matrix<T> &C) {

    const T *a = A.LockedBuffer();
    El::Int ldA = A.LDim();

    T *c = C.Buffer();
    El::Int ldC = C.LDim();

    El::Int n = A.Width();
    El::Int d = A.Height();

    /* Not the most efficient way... but mimicking BLAS is too much work! */
    if (dir == base::COLUMNS) {
        for (El::Int j = 0; j < n; j++)
            for(El::Int i = ((uplo == El::UPPER) ? 0 : j);
                i < ((uplo == El::UPPER) ? (j + 1) : n); i++)
            for (El::Int i = 0; i < A.Width(); i++) {
                T v = 0.0;
                for (El::Int k = 0; k < d; k++)
                    v += std::abs(a[j * ldA + k] - a[i * ldA + k]);
                c[j * ldC + i] = beta * c[j * ldC + i] + alpha * v;
            }

    }

    // TODO the rest of the cases.
}
Example #10
0
inline void Gemv(El::Orientation oA,
    T alpha, const sparse_matrix_t<T>& A, const El::Matrix<T>& x,
    T beta, El::Matrix<T>& y) {
    // TODO verify sizes etc.

    const int* indptr = A.indptr();
    const int* indices = A.indices();
    const double *values = A.locked_values();
    double *yd = y.Buffer();
    const double *xd = x.LockedBuffer();

    int n = A.width();

    if (oA == El::NORMAL) {
        El::Scale(beta, y);

#       if SKYLARK_HAVE_OPENMP
#       pragma omp parallel for
#       endif
        for(int col = 0; col < n; col++) {
            T xv = alpha * xd[col];
            for (int j = indptr[col]; j < indptr[col + 1]; j++) {
                     int row = indices[j];
                     T val = values[j];
                     yd[row] += val * xv;
                 }
        }

    } else {

#       if SKYLARK_HAVE_OPENMP
#       pragma omp parallel for
#       endif
        for(int col = 0; col < n; col++) {
            double yv = beta * yd[col];
            for (int j = indptr[col]; j < indptr[col + 1]; j++) {
                     int row = indices[j];
                     T val = values[j];
                     yv += alpha * val * xd[row];
                 }
            yd[col] = yv;
        }

    }
}
Example #11
0
int Width(const El::Matrix<T>& A) {
    return A.Width();
}
Example #12
0
int Height(const El::Matrix<T>& A) {
    return A.Height();
}
Example #13
0
inline void ColumnView(El::Matrix<T>& A, El::Matrix<T>& B,
    int j, int width) {
    El::View(A, B, 0, j, B.Height(), width);
}
Example #14
0
inline
const El::Matrix<T> RowView(const El::Matrix<T>& B, int i, int height) {
    El::Matrix<T> A;
    El::LockedView(A, B, i, 0, height, B.Width());
    return A;
}
Example #15
0
inline void RowView(El::Matrix<T>& A, El::Matrix<T>& B,
    int i, int height) {
    El::View(A, B, i, 0, height, B.Width());
}
Example #16
0
inline
const El::Matrix<T> ColumnView(const El::Matrix<T>& B, int j, int width) {
    El::Matrix<T> A;
    El::LockedView(A, B, 0, j, B.Height(), width);
    return A;
}
Example #17
0
int max(El::Matrix<double> Y) {
    int k =  (int) *std::max_element(Y.Buffer(), Y.Buffer() + Y.Height());
    return k;
}