105 lines
3.6 KiB
Cython
105 lines
3.6 KiB
Cython
# WARNING: Do not edit this file directly.
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# It is automatically generated from 'sklearn\\utils\\_seq_dataset.pxd.tp'.
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# Changes must be made there.
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"""Dataset abstractions for sequential data access."""
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cimport numpy as cnp
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# SequentialDataset and its two concrete subclasses are (optionally randomized)
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# iterators over the rows of a matrix X and corresponding target values y.
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#------------------------------------------------------------------------------
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cdef class SequentialDataset64:
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cdef int current_index
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cdef int[::1] index
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cdef int *index_data_ptr
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cdef Py_ssize_t n_samples
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cdef cnp.uint32_t seed
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cdef void shuffle(self, cnp.uint32_t seed) noexcept nogil
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cdef int _get_next_index(self) noexcept nogil
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cdef int _get_random_index(self) noexcept nogil
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cdef void _sample(self, double **x_data_ptr, int **x_ind_ptr,
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int *nnz, double *y, double *sample_weight,
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int current_index) noexcept nogil
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cdef void next(self, double **x_data_ptr, int **x_ind_ptr,
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int *nnz, double *y, double *sample_weight) noexcept nogil
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cdef int random(self, double **x_data_ptr, int **x_ind_ptr,
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int *nnz, double *y, double *sample_weight) noexcept nogil
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cdef class ArrayDataset64(SequentialDataset64):
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cdef const double[:, ::1] X
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cdef const double[::1] Y
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cdef const double[::1] sample_weights
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cdef Py_ssize_t n_features
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cdef cnp.npy_intp X_stride
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cdef double *X_data_ptr
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cdef double *Y_data_ptr
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cdef const int[::1] feature_indices
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cdef int *feature_indices_ptr
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cdef double *sample_weight_data
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cdef class CSRDataset64(SequentialDataset64):
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cdef const double[::1] X_data
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cdef const int[::1] X_indptr
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cdef const int[::1] X_indices
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cdef const double[::1] Y
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cdef const double[::1] sample_weights
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cdef double *X_data_ptr
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cdef int *X_indptr_ptr
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cdef int *X_indices_ptr
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cdef double *Y_data_ptr
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cdef double *sample_weight_data
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#------------------------------------------------------------------------------
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cdef class SequentialDataset32:
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cdef int current_index
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cdef int[::1] index
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cdef int *index_data_ptr
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cdef Py_ssize_t n_samples
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cdef cnp.uint32_t seed
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cdef void shuffle(self, cnp.uint32_t seed) noexcept nogil
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cdef int _get_next_index(self) noexcept nogil
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cdef int _get_random_index(self) noexcept nogil
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cdef void _sample(self, float **x_data_ptr, int **x_ind_ptr,
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int *nnz, float *y, float *sample_weight,
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int current_index) noexcept nogil
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cdef void next(self, float **x_data_ptr, int **x_ind_ptr,
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int *nnz, float *y, float *sample_weight) noexcept nogil
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cdef int random(self, float **x_data_ptr, int **x_ind_ptr,
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int *nnz, float *y, float *sample_weight) noexcept nogil
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cdef class ArrayDataset32(SequentialDataset32):
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cdef const float[:, ::1] X
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cdef const float[::1] Y
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cdef const float[::1] sample_weights
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cdef Py_ssize_t n_features
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cdef cnp.npy_intp X_stride
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cdef float *X_data_ptr
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cdef float *Y_data_ptr
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cdef const int[::1] feature_indices
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cdef int *feature_indices_ptr
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cdef float *sample_weight_data
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cdef class CSRDataset32(SequentialDataset32):
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cdef const float[::1] X_data
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cdef const int[::1] X_indptr
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cdef const int[::1] X_indices
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cdef const float[::1] Y
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cdef const float[::1] sample_weights
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cdef float *X_data_ptr
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cdef int *X_indptr_ptr
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cdef int *X_indices_ptr
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cdef float *Y_data_ptr
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cdef float *sample_weight_data
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