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def cublasDgemv(handle, trans, m, n, alpha, A, lda, x, incx, beta, y, incy): """ Matrix-vector product for real general matrix. """ status = _libcublas.cublasDgemv_v2(handle, _CUBLAS_OP[trans], m, n, ctypes.byref(ctypes.c_do...
Matrix-vector product for real general matrix.
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def cublasCgemv(handle, trans, m, n, alpha, A, lda, x, incx, beta, y, incy): """ Matrix-vector product for complex general matrix. """ status = _libcublas.cublasCgemv_v2(handle, _CUBLAS_OP[trans], m, n, ctypes.byref(cuda.cuF...
Matrix-vector product for complex general matrix.
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def cublasZgemv(handle, trans, m, n, alpha, A, lda, x, incx, beta, y, incy): """ Matrix-vector product for complex general matrix. """ status = _libcublas.cublasZgemv_v2(handle, _CUBLAS_OP[trans], m, n, ctypes.byref(cuda.cuD...
Matrix-vector product for complex general matrix.
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def cublasSger(handle, m, n, alpha, x, incx, y, incy, A, lda): """ Rank-1 operation on real general matrix. """ status = _libcublas.cublasSger_v2(handle, m, n, ctypes.byref(ctypes.c_float(alpha)), ...
Rank-1 operation on real general matrix.
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def cublasDger(handle, m, n, alpha, x, incx, y, incy, A, lda): """ Rank-1 operation on real general matrix. """ status = _libcublas.cublasDger_v2(handle, m, n, ctypes.byref(ctypes.c_double(alpha)), ...
Rank-1 operation on real general matrix.
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def cublasCgeru(handle, m, n, alpha, x, incx, y, incy, A, lda): """ Rank-1 operation on complex general matrix. """ status = _libcublas.cublasCgeru_v2(handle, m, n, ctypes.byref(cuda.cuFloatComplex(alpha.real, ...
Rank-1 operation on complex general matrix.
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def cublasZgerc(handle, m, n, alpha, x, incx, y, incy, A, lda): """ Rank-1 operation on complex general matrix. """ status = _libcublas.cublasZgerc_v2(handle, m, n, ctypes.byref(cuda.cuDoubleComplex(alpha.real, ...
Rank-1 operation on complex general matrix.
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def cublasSsbmv(handle, uplo, n, k, alpha, A, lda, x, incx, beta, y, incy): """ Matrix-vector product for real symmetric-banded matrix. """ status = _libcublas.cublasSsbmv_v2(handle, _CUBLAS_FILL_MODE[uplo], n, k, ctypes.byr...
Matrix-vector product for real symmetric-banded matrix.
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def cublasDsbmv(handle, uplo, n, k, alpha, A, lda, x, incx, beta, y, incy): """ Matrix-vector product for real symmetric-banded matrix. """ status = _libcublas.cublasDsbmv_v2(handle, _CUBLAS_FILL_MODE[uplo], n, k, ctypes.byr...
Matrix-vector product for real symmetric-banded matrix.
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def cublasSspmv(handle, uplo, n, alpha, AP, x, incx, beta, y, incy): """ Matrix-vector product for real symmetric-packed matrix. """ status = _libcublas.cublasSspmv_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ...
Matrix-vector product for real symmetric-packed matrix.
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def cublasDspmv(handle, uplo, n, alpha, AP, x, incx, beta, y, incy): """ Matrix-vector product for real symmetric-packed matrix. """ status = _libcublas.cublasDspmv_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ...
Matrix-vector product for real symmetric-packed matrix.
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def cublasSspr(handle, uplo, n, alpha, x, incx, AP): """ Rank-1 operation on real symmetric-packed matrix. """ status = _libcublas.cublasSspr_v2(handle, _CUBLAS_FILL_MODE[uplo], n, c...
Rank-1 operation on real symmetric-packed matrix.
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def cublasDspr(handle, uplo, n, alpha, x, incx, AP): """ Rank-1 operation on real symmetric-packed matrix. """ status = _libcublas.cublasDspr_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctype...
Rank-1 operation on real symmetric-packed matrix.
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def cublasSspr2(handle, uplo, n, alpha, x, incx, y, incy, AP): """ Rank-2 operation on real symmetric-packed matrix. """ status = _libcublas.cublasSspr2_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(ctypes.c_float(al...
Rank-2 operation on real symmetric-packed matrix.
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def cublasDspr2(handle, uplo, n, alpha, x, incx, y, incy, AP): """ Rank-2 operation on real symmetric-packed matrix. """ status = _libcublas.cublasDspr2_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(ctypes.c_double(a...
Rank-2 operation on real symmetric-packed matrix.
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def cublasSsymv(handle, uplo, n, alpha, A, lda, x, incx, beta, y, incy): """ Matrix-vector product for real symmetric matrix. """ status = _libcublas.cublasSsymv_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(...
Matrix-vector product for real symmetric matrix.
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def cublasDsymv(handle, uplo, n, alpha, A, lda, x, incx, beta, y, incy): """ Matrix-vector product for real symmetric matrix. """ status = _libcublas.cublasDsymv_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(ctyp...
Matrix-vector product for real symmetric matrix.
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def cublasCsymv(handle, uplo, n, alpha, A, lda, x, incx, beta, y, incy): """ Matrix-vector product for complex symmetric matrix. """ status = _libcublas.cublasCsymv_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(cud...
Matrix-vector product for complex symmetric matrix.
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def cublasZsymv(handle, uplo, n, alpha, A, lda, x, incx, beta, y, incy): """ Matrix-vector product for complex symmetric matrix. """ status = _libcublas.cublasZsymv_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(cud...
Matrix-vector product for complex symmetric matrix.
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def cublasSsyr(handle, uplo, n, alpha, x, incx, A, lda): """ Rank-1 operation on real symmetric matrix. """ status = _libcublas.cublasSsyr_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(ctypes.c_float(alpha)), ...
Rank-1 operation on real symmetric matrix.
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def cublasDsyr(handle, uplo, n, alpha, x, incx, A, lda): """ Rank-1 operation on real symmetric matrix. """ status = _libcublas.cublasDsyr_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(ctypes.c_double(alpha)), ...
Rank-1 operation on real symmetric matrix.
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def cublasCsyr(handle, uplo, n, alpha, x, incx, A, lda): """ Rank-1 operation on complex symmetric matrix. """ status = _libcublas.cublasCsyr_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(cuda.cuFloatComplex(alpha.r...
Rank-1 operation on complex symmetric matrix.
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def cublasZsyr(handle, uplo, n, alpha, x, incx, A, lda): """ Rank-1 operation on complex symmetric matrix. """ status = _libcublas.cublasZsyr_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(cuda.cuDoubleComplex(alpha....
Rank-1 operation on complex symmetric matrix.
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def cublasSsyr2(handle, uplo, n, alpha, x, incx, y, incy, A, lda): """ Rank-2 operation on real symmetric matrix. """ status = _libcublas.cublasSsyr2_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(ctypes.c_float(alpha)...
Rank-2 operation on real symmetric matrix.
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def cublasDsyr2(handle, uplo, n, alpha, x, incx, y, incy, A, lda): """ Rank-2 operation on real symmetric matrix. """ status = _libcublas.cublasDsyr2_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(ctypes.c_double(alph...
Rank-2 operation on real symmetric matrix.
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def cublasStbmv(handle, uplo, trans, diag, n, k, A, lda, x, incx): """ Matrix-vector product for real triangular-banded matrix. """ status = _libcublas.cublasStbmv_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[trans],...
Matrix-vector product for real triangular-banded matrix.
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def cublasStpmv(handle, uplo, trans, diag, n, AP, x, incx): """ Matrix-vector product for real triangular-packed matrix. """ status = _libcublas.cublasStpmv_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[trans], ...
Matrix-vector product for real triangular-packed matrix.
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def cublasCtpmv(handle, uplo, trans, diag, n, AP, x, incx): """ Matrix-vector product for complex triangular-packed matrix. """ status = _libcublas.cublasCtpmv_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[trans], ...
Matrix-vector product for complex triangular-packed matrix.
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def cublasDtpmv(handle, uplo, trans, diag, n, AP, x, incx): """ Matrix-vector product for real triangular-packed matrix. """ status = _libcublas.cublasDtpmv_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[trans], ...
Matrix-vector product for real triangular-packed matrix.
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def cublasZtpmv(handle, uplo, trans, diag, n, AP, x, incx): """ Matrix-vector product for complex triangular-packed matrix. """ status = _libcublas.cublasZtpmv_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[trans], ...
Matrix-vector product for complex triangular-packed matrix.
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def cublasStpsv(handle, uplo, trans, diag, n, AP, x, incx): """ Solve real triangular-packed system with one right-hand side. """ status = _libcublas.cublasStpsv_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[trans], ...
Solve real triangular-packed system with one right-hand side.
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def cublasDtpsv(handle, uplo, trans, diag, n, AP, x, incx): """ Solve real triangular-packed system with one right-hand side. """ status = _libcublas.cublasDtpsv_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[trans], ...
Solve real triangular-packed system with one right-hand side.
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def cublasCtpsv(handle, uplo, trans, diag, n, AP, x, incx): """ Solve complex triangular-packed system with one right-hand side. """ status = _libcublas.cublasCtpsv_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[tra...
Solve complex triangular-packed system with one right-hand side.
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def cublasZtpsv(handle, uplo, trans, diag, n, AP, x, incx): """ Solve complex triangular-packed system with one right-hand size. """ status = _libcublas.cublasZtpsv_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[trans]...
Solve complex triangular-packed system with one right-hand size.
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def cublasCtrmv(handle, uplo, trans, diag, n, A, lda, x, incx): """ Matrix-vector product for complex triangular matrix. """ status = _libcublas.cublasCtrmv_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[trans], ...
Matrix-vector product for complex triangular matrix.
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def cublasDtrmv(handle, uplo, trans, diag, n, A, lda, x, inx): """ Matrix-vector product for real triangular matrix. """ status = _libcublas.cublasDtrmv_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[trans], ...
Matrix-vector product for real triangular matrix.
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def cublasChpmv(handle, uplo, n, alpha, AP, x, incx, beta, y, incy): """ Matrix-vector product for Hermitian-packed matrix. """ status = _libcublas.cublasChpmv_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(cuda.c...
Matrix-vector product for Hermitian-packed matrix.
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def cublasZhpmv(handle, uplo, n, alpha, AP, x, incx, beta, y, incy): """ Matrix-vector product for Hermitian-packed matrix. """ status = _libcublas.cublasZhpmv_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(cuda.cu...
Matrix-vector product for Hermitian-packed matrix.
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def cublasCher(handle, uplo, n, alpha, x, incx, A, lda): """ Rank-1 operation on Hermitian matrix. """ status = _libcublas.cublasCher_v2(handle, _CUBLAS_FILL_MODE[uplo], n, alpha, int(x), incx, int(A), lda) cublasCheckSt...
Rank-1 operation on Hermitian matrix.
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def cublasZher(handle, uplo, n, alpha, x, incx, A, lda): """ Rank-1 operation on Hermitian matrix. """ status = _libcublas.cublasZher_v2(handle, _CUBLAS_FILL_MODE[uplo], n, alpha, int(x), incx, int(A), lda) cublasChe...
Rank-1 operation on Hermitian matrix.
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def cublasChpr(handle, uplo, n, alpha, x, incx, AP): """ Rank-1 operation on Hermitian-packed matrix. """ status = _libcublas.cublasChpr_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(ctypes.c_float(alpha)), ...
Rank-1 operation on Hermitian-packed matrix.
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def cublasZhpr(handle, uplo, n, alpha, x, incx, AP): """ Rank-1 operation on Hermitian-packed matrix. """ status = _libcublas.cublasZhpr_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(ctypes.c_double(alpha)), ...
Rank-1 operation on Hermitian-packed matrix.
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def cublasChpr2(handle, uplo, n, alpha, x, inx, y, incy, AP): """ Rank-2 operation on Hermitian-packed matrix. """ status = _libcublas.cublasChpr2_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(cuda.cuFloatComplex...
Rank-2 operation on Hermitian-packed matrix.
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def cublasZhpr2(handle, uplo, n, alpha, x, inx, y, incy, AP): """ Rank-2 operation on Hermitian-packed matrix. """ status = _libcublas.cublasZhpr2_v2(handle, _CUBLAS_FILL_MODE[uplo], n, ctypes.byref(cuda.cuDoubleComple...
Rank-2 operation on Hermitian-packed matrix.
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def cublasSgemm(handle, transa, transb, m, n, k, alpha, A, lda, B, ldb, beta, C, ldc): """ Matrix-matrix product for real general matrix. """ status = _libcublas.cublasSgemm_v2(handle, _CUBLAS_OP[transa], _CUBLAS_OP[transb],...
Matrix-matrix product for real general matrix.
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def cublasDgemm(handle, transa, transb, m, n, k, alpha, A, lda, B, ldb, beta, C, ldc): """ Matrix-matrix product for real general matrix. """ status = _libcublas.cublasDgemm_v2(handle, _CUBLAS_OP[transa], _CUBLAS_OP[transb],...
Matrix-matrix product for real general matrix.
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def cublasZgemm(handle, transa, transb, m, n, k, alpha, A, lda, B, ldb, beta, C, ldc): """ Matrix-matrix product for complex general matrix. """ status = _libcublas.cublasZgemm_v2(handle, _CUBLAS_OP[transa], _CUBLAS_OP[trans...
Matrix-matrix product for complex general matrix.
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def cublasSsymm(handle, side, uplo, m, n, alpha, A, lda, B, ldb, beta, C, ldc): """ Matrix-matrix product for symmetric matrix. """ status = _libcublas.cublasSsymm_v2(handle, _CUBLAS_SIDE_MODE[side], _CUBLAS_FILL_MODE[u...
Matrix-matrix product for symmetric matrix.
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def cublasDsymm(handle, side, uplo, m, n, alpha, A, lda, B, ldb, beta, C, ldc): """ Matrix-matrix product for real symmetric matrix. """ status = _libcublas.cublasDsymm_v2(handle, _CUBLAS_SIDE_MODE[side], _CUBLAS_FILL_M...
Matrix-matrix product for real symmetric matrix.
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def cublasCsymm(handle, side, uplo, m, n, alpha, A, lda, B, ldb, beta, C, ldc): """ Matrix-matrix product for complex symmetric matrix. """ status = _libcublas.cublasCsymm_v2(handle, _CUBLAS_SIDE_MODE[side], _CUBLAS_FI...
Matrix-matrix product for complex symmetric matrix.
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def cublasSsyrk(handle, uplo, trans, n, k, alpha, A, lda, beta, C, ldc): """ Rank-k operation on real symmetric matrix. """ status = _libcublas.cublasSsyrk_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[trans], ...
Rank-k operation on real symmetric matrix.
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def cublasDsyrk(handle, uplo, trans, n, k, alpha, A, lda, beta, C, ldc): """ Rank-k operation on real symmetric matrix. """ status = _libcublas.cublasDsyrk_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[trans], ...
Rank-k operation on real symmetric matrix.
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def cublasZsyrk(handle, uplo, trans, n, k, alpha, A, lda, beta, C, ldc): """ Rank-k operation on complex symmetric matrix. """ status = _libcublas.cublasZsyrk_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[trans], ...
Rank-k operation on complex symmetric matrix.
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def cublasSsyr2k(handle, uplo, trans, n, k, alpha, A, lda, B, ldb, beta, C, ldc): """ Rank-2k operation on real symmetric matrix. """ status = _libcublas.cublasSsyr2k_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[tra...
Rank-2k operation on real symmetric matrix.
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def cublasDsyr2k(handle, uplo, trans, n, k, alpha, A, lda, B, ldb, beta, C, ldc): """ Rank-2k operation on real symmetric matrix. """ status = _libcublas.cublasDsyr2k_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[trans]...
Rank-2k operation on real symmetric matrix.
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def cublasStrmm(handle, side, uplo, trans, diag, m, n, alpha, A, lda, B, ldb, C, ldc): """ Matrix-matrix product for real triangular matrix. """ status = _libcublas.cublasStrmm_v2(handle, _CUBLAS_SIDE_MODE[side], _CUBLA...
Matrix-matrix product for real triangular matrix.
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def cublasZtrmm(handle, side, uplo, trans, diag, m, n, alpha, A, lda, B, ldb, C, ldc): """ Matrix-matrix product for complex triangular matrix. """ status = _libcublas.cublasZtrmm_v2(handle, _CUBLAS_SIDE_MODE[side], _C...
Matrix-matrix product for complex triangular matrix.
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def cublasStrsm(handle, side, uplo, trans, diag, m, n, alpha, A, lda, B, ldb): """ Solve a real triangular system with multiple right-hand sides. """ status = _libcublas.cublasStrsm_v2(handle, _CUBLAS_SIDE_MODE[side], ...
Solve a real triangular system with multiple right-hand sides.
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def cublasDtrsm(handle, side, uplo, trans, diag, m, n, alpha, A, lda, B, ldb): """ Solve a real triangular system with multiple right-hand sides. """ status = _libcublas.cublasDtrsm_v2(handle, _CUBLAS_SIDE_MODE[side], ...
Solve a real triangular system with multiple right-hand sides.
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def cublasZtrsm(handle, side, uplo, transa, diag, m, n, alpha, A, lda, B, ldb): """ Solve complex triangular system with multiple right-hand sides. """ status = _libcublas.cublasZtrsm_v2(handle, _CUBLAS_SIDE_MODE[side], ...
Solve complex triangular system with multiple right-hand sides.
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def cublasZherk(handle, uplo, trans, n, k, alpha, A, lda, beta, C, ldc): """ Rank-k operation on Hermitian matrix. """ status = _libcublas.cublasZherk_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[trans], ...
Rank-k operation on Hermitian matrix.
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def cublasCher2k(handle, uplo, trans, n, k, alpha, A, lda, B, ldb, beta, C, ldc): """ Rank-2k operation on Hermitian matrix. """ status = _libcublas.cublasCher2k_v2(handle, _CUBLAS_FILL_MODE[uplo], _CUBLAS_OP[trans],...
Rank-2k operation on Hermitian matrix.
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def cublasSdgmm(handle, mode, m, n, A, lda, x, incx, C, ldc): """ Matrix-diagonal matrix product for real general matrix. """ status = _libcublas.cublasSdgmm(handle, _CUBLAS_SIDE[mode], m, n, ...
Matrix-diagonal matrix product for real general matrix.
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def load_EROS_lc(filename='lm0010n22323.time'): """ Read an EROS light curve and return its data. Parameters ---------- filename : str, optional A light-curve filename. Returns ------- dates : numpy.ndarray An array of dates. magnitudes : numpy.ndarray An ar...
Read an EROS light curve and return its data. Parameters ---------- filename : str, optional A light-curve filename. Returns ------- dates : numpy.ndarray An array of dates. magnitudes : numpy.ndarray An array of magnitudes. errors : numpy.ndarray An arr...
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def load_rf_model(): """ Return the UPSILoN random forests classifier. The classifier is trained using OGLE and EROS periodic variables (Kim et al. 2015). Returns ------- clf : sklearn.ensemble.RandomForestClassifier The UPSILoN random forests classifier. """ import gzip ...
Return the UPSILoN random forests classifier. The classifier is trained using OGLE and EROS periodic variables (Kim et al. 2015). Returns ------- clf : sklearn.ensemble.RandomForestClassifier The UPSILoN random forests classifier.
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def sample_dropout_mask(x, dropout_probability=.5, columns=None, stream=None, target=None, dropout_mask=None, dropout_prob_array=None): """ Samples a dropout mask and applies it in place""" assert x.flags.c_contiguous if columns is not None: assert len(columns) == 2 ...
Samples a dropout mask and applies it in place
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def reads(s, filename=None, loader=None, implicit_tuple=True, allow_errors=False): """Load but don't evaluate a GCL expression from a string.""" return ast.reads(s, filename=filename or '<input>', loader=loader or default_loader, implicit_tuple=implicit_tuple, allow_errors=allow_errors)
Load but don't evaluate a GCL expression from a string.
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def read(filename, loader=None, implicit_tuple=True, allow_errors=False): """Load but don't evaluate a GCL expression from a file.""" with open(filename, 'r') as f: return reads(f.read(), filename=filename, loader=loader, implicit_tuple=implicit_tuple, ...
Load but don't evaluate a GCL expression from a file.
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def loads(s, filename=None, loader=None, implicit_tuple=True, env={}, schema=None): """Load and evaluate a GCL expression from a string.""" ast = reads(s, filename=filename, loader=loader, implicit_tuple=implicit_tuple) if not isinstance(env, framework.Environment): # For backwards compatibility we accept an ...
Load and evaluate a GCL expression from a string.
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def load(filename, loader=None, implicit_tuple=True, env={}, schema=None): """Load and evaluate a GCL expression from a file.""" with open(filename, 'r') as f: return loads(f.read(), filename=filename, loader=loader, implicit_tuple=implicit_tuple, ...
Load and evaluate a GCL expression from a file.
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def linear_scheduler_up(init_value, target_value, duration): """ Increases linearly and then stays flat """ value = init_value t = 0 while True: yield value t += 1 if t < duration: value = init_value + t * (target_value - init_value) / duration else: ...
Increases linearly and then stays flat
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def linear_scheduler_up_down(init_value, target_value, final_value, duration_up, t_decrease, duration_down): """ Increases linearly to target_value, stays at target_value until t_decrease and then decreases linearly """ value = init_value t = 0 while True: ...
Increases linearly to target_value, stays at target_value until t_decrease and then decreases linearly
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def load(stream, overrides=None, **kwargs): """ Loads a YAML configuration from a string or file-like object. Parameters ---------- stream : str or object Either a string containing valid YAML or a file-like object supporting the .read() interface. overrides : dict, optional ...
Loads a YAML configuration from a string or file-like object. Parameters ---------- stream : str or object Either a string containing valid YAML or a file-like object supporting the .read() interface. overrides : dict, optional A dictionary containing overrides to apply. The loc...
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def load_path(path, overrides=None, **kwargs): """ Convenience function for loading a YAML configuration from a file. Parameters ---------- path : str The path to the file to load on disk. overrides : dict, optional A dictionary containing overrides to apply. The location of ...
Convenience function for loading a YAML configuration from a file. Parameters ---------- path : str The path to the file to load on disk. overrides : dict, optional A dictionary containing overrides to apply. The location of the override is specified in the key as a dot-delimite...
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def handle_overrides(graph, overrides): """ Handle any overrides for this model configuration. Parameters ---------- graph : dict or object A dictionary (or an ObjectProxy) containing the object graph loaded from a YAML file. overrides : dict A dictionary containing over...
Handle any overrides for this model configuration. Parameters ---------- graph : dict or object A dictionary (or an ObjectProxy) containing the object graph loaded from a YAML file. overrides : dict A dictionary containing overrides to apply. The location of the override...
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def instantiate_all(graph): """ Instantiate all ObjectProxy objects in a nested hierarchy. Parameters ---------- graph : dict or object A dictionary (or an ObjectProxy) containing the object graph loaded from a YAML file. Returns ------- graph : dict or object T...
Instantiate all ObjectProxy objects in a nested hierarchy. Parameters ---------- graph : dict or object A dictionary (or an ObjectProxy) containing the object graph loaded from a YAML file. Returns ------- graph : dict or object The dictionary or object resulting after ...
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def multi_constructor(loader, tag_suffix, node): """ Constructor function passed to PyYAML telling it how to construct objects from argument descriptions. See PyYAML documentation for details on the call signature. """ yaml_src = yaml.serialize(node) mapping = loader.construct_mapping(node) ...
Constructor function passed to PyYAML telling it how to construct objects from argument descriptions. See PyYAML documentation for details on the call signature.
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def multi_constructor_pkl(loader, tag_suffix, node): """ Constructor function passed to PyYAML telling it how to load objects from paths to .pkl files. See PyYAML documentation for details on the call signature. """ mapping = loader.construct_yaml_str(node) if tag_suffix != "" and tag_suffi...
Constructor function passed to PyYAML telling it how to load objects from paths to .pkl files. See PyYAML documentation for details on the call signature.
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def initialize(): """ Initialize the configuration system by installing YAML handlers. Automatically done on first call to load() specified in this file. """ global is_initialized # Add the custom multi-constructor yaml.add_multi_constructor('!obj:', multi_constructor) yaml.add_multi_con...
Initialize the configuration system by installing YAML handlers. Automatically done on first call to load() specified in this file.
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def instantiate(self): """ Instantiate this object with the supplied parameters in `self.kwds`, or if already instantiated, return the cached instance. """ if self.instance is None: self.instance = checked_call(self.cls, self.kwds) #endif try: ...
Instantiate this object with the supplied parameters in `self.kwds`, or if already instantiated, return the cached instance.
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def feed_forward(self, input_data, prediction=False): """Propagate forward through the layer. **Parameters:** input_data : ``GPUArray`` Inpute data to compute activations for. prediction : bool, optional Whether to use prediction model. Only relevant when using...
Propagate forward through the layer. **Parameters:** input_data : ``GPUArray`` Inpute data to compute activations for. prediction : bool, optional Whether to use prediction model. Only relevant when using dropout. If true, then weights are multiplied by ...
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def fasper(x, y, ofac, hifac, n_threads, MACC=4): """ Given abscissas x (which need not be equally spaced) and ordinates y, and given a desired oversampling factor ofac (a typical value being 4 or larger). this routine creates an array wk1 with a sequence of nout increasing frequencies (not angular ...
Given abscissas x (which need not be equally spaced) and ordinates y, and given a desired oversampling factor ofac (a typical value being 4 or larger). this routine creates an array wk1 with a sequence of nout increasing frequencies (not angular frequencies) up to hifac times the "average" Nyquist frequ...
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def get_no_validate(self, key): """Return an item without validating the schema.""" x, env = self.get_thunk_env(key) # Check if this is a Thunk that needs to be lazily evaluated before we # return it. if isinstance(x, framework.Thunk): x = framework.eval(x, env) return x
Return an item without validating the schema.
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def env(self, current_scope): """Return an environment that will look up in current_scope for keys in this tuple, and the parent env otherwise. """ return self.__env_cache.get( current_scope.ident, framework.Environment, current_scope, names=self.keys(), p...
Return an environment that will look up in current_scope for keys in this tuple, and the parent env otherwise.
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def get_thunk_env(self, k): """Return the thunk AND environment for validating it in for the given key. There might be different envs in case the thunk comes from a different (composed) tuple. If the thunk needs its environment bound on retrieval, that will be done here. """ if k not in self.__item...
Return the thunk AND environment for validating it in for the given key. There might be different envs in case the thunk comes from a different (composed) tuple. If the thunk needs its environment bound on retrieval, that will be done here.
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def attach_schema(self, schem): """Add a tuple schema to this object (externally imposed)""" self.tuple_schema = schema.AndSchema.make(self.tuple_schema, schem)
Add a tuple schema to this object (externally imposed)
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def get_schema_spec(self, key): """Return the evaluated schema expression from a subkey.""" member_node = self._ast_node.member.get(key, None) if not member_node: return schema.AnySchema() s = framework.eval(member_node.member_schema, self.env(self)) if not isinstance(s, schema.Schema): ...
Return the evaluated schema expression from a subkey.
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def get_required_fields(self): """Return the names of fields that are required according to the schema.""" return [m.name for m in self._ast_node.members if m.member_schema.required]
Return the names of fields that are required according to the schema.
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def get_member_node(self, key): """Return the AST node for the given member, from the first tuple that serves it.""" for tup, _ in self.lookups: if key in tup: return tup.get_member_node(key) raise RuntimeError('Key not found in composite tuple: %r' % key)
Return the AST node for the given member, from the first tuple that serves it.
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def exportable_keys(self): """Return a list of keys that are exportable from this tuple. Returns all keys that are not private in any of the tuples. """ keys = collections.defaultdict(list) for tup in self._tuples: for key, private in tup._keys_and_privacy().items(): keys[key].append(...
Return a list of keys that are exportable from this tuple. Returns all keys that are not private in any of the tuples.
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def resolve(self, current_file, rel_path): """Search the filesystem.""" search_path = [path.dirname(current_file)] + self.search_path target_path = None for search in search_path: if self.exists(path.join(search, rel_path)): target_path = path.normpath(path.join(search, rel_path)) ...
Search the filesystem.
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def resolve(self, current_file, rel_path): """Search the filesystem.""" p = path.join(path.dirname(current_file), rel_path) if p not in self.file_dict: raise RuntimeError('No such fake file: %r' % p) return p, p
Search the filesystem.
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def check_call_arguments(to_call, kwargs): """ Check the call signature against a dictionary of proposed arguments, raising an informative exception in the case of mismatch. Parameters ---------- to_call : class or callable Function or class to examine (in the case of classes, the ...
Check the call signature against a dictionary of proposed arguments, raising an informative exception in the case of mismatch. Parameters ---------- to_call : class or callable Function or class to examine (in the case of classes, the constructor call signature is analyzed) kwargs :...
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def predict(rf_model, features): """ Return label and probability estimated. Parameters ---------- rf_model : sklearn.ensemble.RandomForestClassifier The UPSILoN random forests model. features : array_like A list of features estimated by UPSILoN. Returns ------- lab...
Return label and probability estimated. Parameters ---------- rf_model : sklearn.ensemble.RandomForestClassifier The UPSILoN random forests model. features : array_like A list of features estimated by UPSILoN. Returns ------- label : str A predicted label (i.e. clas...
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def fmt(str, args=None, env=None): """fmt(string, [tuple]) -> string Interpolate a string, replacing {patterns} with the variables with the same name. If given a tuple, use the keys from the tuple to substitute. If not given a tuple, uses the current environment as the variable source. """ # Normally, we'd...
fmt(string, [tuple]) -> string Interpolate a string, replacing {patterns} with the variables with the same name. If given a tuple, use the keys from the tuple to substitute. If not given a tuple, uses the current environment as the variable source.
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def compose_all(tups): """Compose all given tuples together.""" from . import ast # I weep for humanity return functools.reduce(lambda x, y: x.compose(y), map(ast.make_tuple, tups), ast.make_tuple({}))
Compose all given tuples together.
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def has_key(tup, key): """has(tuple, string) -> bool Return whether a given tuple has a key and the key is bound. """ if isinstance(tup, framework.TupleLike): return tup.is_bound(key) if isinstance(tup, dict): return key in tup if isinstance(tup, list): if not isinstance(key, int): raise ...
has(tuple, string) -> bool Return whether a given tuple has a key and the key is bound.
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def flatten(list_of_lists): """flatten([[A]]) -> [A] Flatten a list of lists. """ ret = [] for lst in list_of_lists: if not isinstance(lst, list): raise ValueError('%r is not a list' % lst) ret.extend(lst) return ret
flatten([[A]]) -> [A] Flatten a list of lists.
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def extract_dark(prihdr, scihdu): """Extract superdark data from ``DARKFILE`` or ``DRKCFILE``. Parameters ---------- prihdr : obj FITS primary header HDU. scihdu : obj Extension HDU of the science image. This is only used to extract subarray data. Returns ------- ...
Extract superdark data from ``DARKFILE`` or ``DRKCFILE``. Parameters ---------- prihdr : obj FITS primary header HDU. scihdu : obj Extension HDU of the science image. This is only used to extract subarray data. Returns ------- dark : ndarray or `None` Super...
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def extract_flash(prihdr, scihdu): """Extract postflash data from ``FLSHFILE``. Parameters ---------- prihdr : obj FITS primary header HDU. scihdu : obj Extension HDU of the science image. This is only used to extract subarray data. Returns ------- flash : ndar...
Extract postflash data from ``FLSHFILE``. Parameters ---------- prihdr : obj FITS primary header HDU. scihdu : obj Extension HDU of the science image. This is only used to extract subarray data. Returns ------- flash : ndarray or `None` Postflash, if any. S...
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