Examples with BlasFloatMatrix com.tencent.angel.ml.math2.matrix.BlasFloatMatrix used on opensource projects

Example 6 with BlasFloatMatrix

use of com.tencent.angel.ml.math2.matrix.BlasFloatMatrix in project angel by Tencent.

the class DotMatrixExecutor method apply.

private static Vector apply(BlasFloatMatrix mat, boolean trans, IntLongVector v) {
    int m = mat.getNumRows(), n = mat.getNumCols();
    float[] resArr;
    if (trans) {
        assert m == v.getDim();
        resArr = new float[n];
    } else {
        assert n == v.getDim();
        resArr = new float[m];
    }
    int r = mat.getNumRows(), c = mat.getNumCols();
    float[] data = mat.getData();
    if (v.isDense()) {
        float[] tempArray = ArrayCopy.copy(v.getStorage().getValues(), new float[v.getDim()]);
        if (trans) {
            blas.sgemv("N", c, r, 1.0f, data, c, tempArray, 1, 0.0f, resArr, 1);
        } else {
            blas.sgemv("T", c, r, 1.0f, data, c, tempArray, 1, 0.0f, resArr, 1);
        }
    } else if (v.isSparse()) {
        if (trans) {
            for (int j = 0; j < c; j++) {
                ObjectIterator<Int2LongMap.Entry> iter = v.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2LongMap.Entry entry = iter.next();
                    int i = entry.getIntKey();
                    resArr[j] += data[i * c + j] * entry.getLongValue();
                }
            }
        } else {
            for (int i = 0; i < r; i++) {
                ObjectIterator<Int2LongMap.Entry> iter = v.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2LongMap.Entry entry = iter.next();
                    int j = entry.getIntKey();
                    resArr[i] += data[i * c + j] * entry.getLongValue();
                }
            }
        }
    } else {
        // sorted
        if (trans) {
            for (int j = 0; j < r; j++) {
                int[] idxs = v.getStorage().getIndices();
                long[] vals = v.getStorage().getValues();
                for (int k = 0; k < idxs.length; k++) {
                    resArr[j] += data[idxs[k] * c + j] * vals[k];
                }
            }
        } else {
            for (int i = 0; i < r; i++) {
                int[] idxs = v.getStorage().getIndices();
                long[] vals = v.getStorage().getValues();
                for (int k = 0; k < idxs.length; k++) {
                    resArr[i] += data[i * c + idxs[k]] * vals[k];
                }
            }
        }
    }
    IntFloatDenseVectorStorage storage = new IntFloatDenseVectorStorage(resArr);
    return new IntFloatVector(v.getMatrixId(), v.getClock(), 0, resArr.length, storage);
}

Example 7 with BlasFloatMatrix

use of com.tencent.angel.ml.math2.matrix.BlasFloatMatrix in project angel by Tencent.

the class DotMatrixExecutor method apply.

private static Vector apply(BlasFloatMatrix mat, boolean trans, IntDummyVector v) {
    int m = mat.getNumRows(), n = mat.getNumCols();
    float[] resArr;
    if (trans) {
        assert m == v.getDim();
        resArr = new float[n];
    } else {
        assert n == v.getDim();
        resArr = new float[m];
    }
    int r = mat.getNumRows(), c = mat.getNumCols();
    float[] data = mat.getData();
    if (trans) {
        for (int j = 0; j < c; j++) {
            int[] idxs = v.getIndices();
            for (int i : idxs) {
                resArr[j] += data[i * c + j];
            }
        }
    } else {
        for (int i = 0; i < r; i++) {
            int[] idxs = v.getIndices();
            for (int j : idxs) {
                resArr[i] += data[i * c + j];
            }
        }
    }
    IntFloatDenseVectorStorage storage = new IntFloatDenseVectorStorage(resArr);
    return new IntFloatVector(v.getMatrixId(), v.getClock(), 0, resArr.length, storage);
}

Example 8 with BlasFloatMatrix

use of com.tencent.angel.ml.math2.matrix.BlasFloatMatrix in project angel by Tencent.

the class DotMatrixExecutor method apply.

private static Vector apply(BlasFloatMatrix mat, boolean trans, IntFloatVector v) {
    int m = mat.getNumRows(), n = mat.getNumCols();
    float[] resArr;
    if (trans) {
        assert m == v.getDim();
        resArr = new float[n];
    } else {
        assert n == v.getDim();
        resArr = new float[m];
    }
    int r = mat.getNumRows(), c = mat.getNumCols();
    float[] data = mat.getData();
    if (v.isDense()) {
        float[] tempArray = v.getStorage().getValues();
        if (trans) {
            blas.sgemv("N", c, r, 1.0f, data, c, tempArray, 1, 0.0f, resArr, 1);
        } else {
            blas.sgemv("T", c, r, 1.0f, data, c, tempArray, 1, 0.0f, resArr, 1);
        }
    } else if (v.isSparse()) {
        if (trans) {
            for (int j = 0; j < c; j++) {
                ObjectIterator<Int2FloatMap.Entry> iter = v.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2FloatMap.Entry entry = iter.next();
                    int i = entry.getIntKey();
                    resArr[j] += data[i * c + j] * entry.getFloatValue();
                }
            }
        } else {
            for (int i = 0; i < r; i++) {
                ObjectIterator<Int2FloatMap.Entry> iter = v.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2FloatMap.Entry entry = iter.next();
                    int j = entry.getIntKey();
                    resArr[i] += data[i * c + j] * entry.getFloatValue();
                }
            }
        }
    } else {
        // sorted
        if (trans) {
            for (int j = 0; j < r; j++) {
                int[] idxs = v.getStorage().getIndices();
                float[] vals = v.getStorage().getValues();
                for (int k = 0; k < idxs.length; k++) {
                    resArr[j] += data[idxs[k] * c + j] * vals[k];
                }
            }
        } else {
            for (int i = 0; i < r; i++) {
                int[] idxs = v.getStorage().getIndices();
                float[] vals = v.getStorage().getValues();
                for (int k = 0; k < idxs.length; k++) {
                    resArr[i] += data[i * c + idxs[k]] * vals[k];
                }
            }
        }
    }
    IntFloatDenseVectorStorage storage = new IntFloatDenseVectorStorage(resArr);
    return new IntFloatVector(v.getMatrixId(), v.getClock(), 0, resArr.length, storage);
}

Example 9 with BlasFloatMatrix

use of com.tencent.angel.ml.math2.matrix.BlasFloatMatrix in project angel by Tencent.

the class DotMatrixExecutor method apply.

private static Matrix apply(BlasFloatMatrix mat1, boolean trans1, BlasFloatMatrix mat2, boolean trans2) {
    float alpha = 1.0f, beta = 0.0f;
    float[] resBlas;
    int m = mat1.getNumRows(), n = mat1.getNumCols();
    int p = mat2.getNumRows(), q = mat2.getNumCols();
    if (trans1 && trans2) {
        // M1^T * M2^T
        assert m == q;
        resBlas = new float[n * p];
        blas.sgemm("T", "T", p, n, m, alpha, mat2.getData(), q, mat1.getData(), n, beta, resBlas, p);
        return new BlasFloatMatrix(mat1.getMatrixId(), mat1.getClock(), n, p, resBlas);
    } else if (!trans1 && trans2) {
        // M1 * M2^T
        assert n == q;
        resBlas = new float[m * p];
        blas.sgemm("T", "N", p, m, n, alpha, mat2.getData(), q, mat1.getData(), n, beta, resBlas, p);
        return new BlasFloatMatrix(mat1.getMatrixId(), mat1.getClock(), m, p, resBlas);
    } else if (trans1 && !trans2) {
        // M1^T * M2
        assert m == p;
        resBlas = new float[n * q];
        blas.sgemm("N", "T", q, n, m, alpha, mat2.getData(), q, mat1.getData(), n, beta, resBlas, q);
        return new BlasFloatMatrix(mat1.getMatrixId(), mat1.getClock(), n, q, resBlas);
    } else {
        // M1 * M2
        assert n == p;
        resBlas = new float[m * q];
        blas.sgemm("N", "N", q, m, n, alpha, mat2.getData(), q, mat1.getData(), n, beta, resBlas, q);
        return new BlasFloatMatrix(mat1.getMatrixId(), mat1.getClock(), m, q, resBlas);
    }
}

Example 10 with BlasFloatMatrix

use of com.tencent.angel.ml.math2.matrix.BlasFloatMatrix in project angel by Tencent.

the class DotMatrixExecutor method applyParallel.

private static Matrix applyParallel(BlasFloatMatrix mat1, boolean trans1, BlasFloatMatrix mat2, boolean trans2) {
    int m = mat1.getNumRows(), n = mat1.getNumCols();
    int p = mat2.getNumRows(), q = mat2.getNumCols();
    float[] resBlas;
    BlasFloatMatrix retMat;
    BlasFloatMatrix transMat1;
    MatrixExecutors executors = MatrixExecutors.getInstance();
    if (trans1) {
        if (trans2) {
            assert m == q;
            resBlas = new float[n * p];
            retMat = new BlasFloatMatrix(mat1.getMatrixId(), mat1.getClock(), n, p, resBlas);
        } else {
            assert m == p;
            resBlas = new float[n * q];
            retMat = new BlasFloatMatrix(mat1.getMatrixId(), mat1.getClock(), n, q, resBlas);
        }
        // Transform mat1, generate a new matrix
        transMat1 = new BlasFloatMatrix(mat1.getMatrixId(), mat1.getClock(), n, m, transform(mat1));
    } else {
        if (trans2) {
            assert n == q;
            resBlas = new float[m * p];
            retMat = new BlasFloatMatrix(mat1.getMatrixId(), mat1.getClock(), m, p, resBlas);
        } else {
            assert n == p;
            resBlas = new float[m * q];
            retMat = new BlasFloatMatrix(mat1.getMatrixId(), mat1.getClock(), m, q, resBlas);
        }
        transMat1 = mat1;
    }
    // Split the row indices of mat1Trans
    int subM = Math.max(1, transMat1.getNumRows() / executors.getParallel());
    int[] leftRowOffIndices = splitRowIds(transMat1.getNumRows(), subM);
    // Parallel execute use fork-join
    DotForkJoinOp op = new DotForkJoinOp(transMat1, mat2, retMat, leftRowOffIndices, 0, leftRowOffIndices.length, subM, trans2);
    executors.execute(op);
    op.join();
    return retMat;
}