# WARNING: Do not edit this file directly. # It is automatically generated from 'sklearn/metrics/_pairwise_distances_reduction/_base.pxd.tp'. # Changes must be made there. from cython cimport final from ...utils._typedefs cimport intp_t, float64_t from ._datasets_pair cimport DatasetsPair64 cpdef float64_t[::1] _sqeuclidean_row_norms64( X, intp_t num_threads, ) cdef class BaseDistancesReduction64: """ Base float64 implementation template of the pairwise-distances reduction backends. Implementations inherit from this template and may override the several defined hooks as needed in order to easily extend functionality with minimal redundant code. """ cdef: readonly DatasetsPair64 datasets_pair # The number of threads that can be used is stored in effective_n_threads. # # The number of threads to use in the parallelization strategy # (i.e. parallel_on_X or parallel_on_Y) can be smaller than effective_n_threads: # for small datasets, fewer threads might be needed to loop over pair of chunks. # # Hence, the number of threads that _will_ be used for looping over chunks # is stored in chunks_n_threads, allowing solely using what we need. # # Thus, an invariant is: # # chunks_n_threads <= effective_n_threads # intp_t effective_n_threads intp_t chunks_n_threads intp_t n_samples_chunk, chunk_size intp_t n_samples_X, X_n_samples_chunk, X_n_chunks, X_n_samples_last_chunk intp_t n_samples_Y, Y_n_samples_chunk, Y_n_chunks, Y_n_samples_last_chunk bint execute_in_parallel_on_Y @final cdef void _parallel_on_X(self) noexcept nogil @final cdef void _parallel_on_Y(self) noexcept nogil # Placeholder methods which have to be implemented cdef void _compute_and_reduce_distances_on_chunks( self, intp_t X_start, intp_t X_end, intp_t Y_start, intp_t Y_end, intp_t thread_num, ) noexcept nogil # Placeholder methods which can be implemented cdef void compute_exact_distances(self) noexcept nogil cdef void _parallel_on_X_parallel_init( self, intp_t thread_num, ) noexcept nogil cdef void _parallel_on_X_init_chunk( self, intp_t thread_num, intp_t X_start, intp_t X_end, ) noexcept nogil cdef void _parallel_on_X_pre_compute_and_reduce_distances_on_chunks( self, intp_t X_start, intp_t X_end, intp_t Y_start, intp_t Y_end, intp_t thread_num, ) noexcept nogil cdef void _parallel_on_X_prange_iter_finalize( self, intp_t thread_num, intp_t X_start, intp_t X_end, ) noexcept nogil cdef void _parallel_on_X_parallel_finalize( self, intp_t thread_num ) noexcept nogil cdef void _parallel_on_Y_init( self, ) noexcept nogil cdef void _parallel_on_Y_parallel_init( self, intp_t thread_num, intp_t X_start, intp_t X_end, ) noexcept nogil cdef void _parallel_on_Y_pre_compute_and_reduce_distances_on_chunks( self, intp_t X_start, intp_t X_end, intp_t Y_start, intp_t Y_end, intp_t thread_num, ) noexcept nogil cdef void _parallel_on_Y_synchronize( self, intp_t X_start, intp_t X_end, ) noexcept nogil cdef void _parallel_on_Y_finalize( self, ) noexcept nogil from ._datasets_pair cimport DatasetsPair32 cpdef float64_t[::1] _sqeuclidean_row_norms32( X, intp_t num_threads, ) cdef class BaseDistancesReduction32: """ Base float32 implementation template of the pairwise-distances reduction backends. Implementations inherit from this template and may override the several defined hooks as needed in order to easily extend functionality with minimal redundant code. """ cdef: readonly DatasetsPair32 datasets_pair # The number of threads that can be used is stored in effective_n_threads. # # The number of threads to use in the parallelization strategy # (i.e. parallel_on_X or parallel_on_Y) can be smaller than effective_n_threads: # for small datasets, fewer threads might be needed to loop over pair of chunks. # # Hence, the number of threads that _will_ be used for looping over chunks # is stored in chunks_n_threads, allowing solely using what we need. # # Thus, an invariant is: # # chunks_n_threads <= effective_n_threads # intp_t effective_n_threads intp_t chunks_n_threads intp_t n_samples_chunk, chunk_size intp_t n_samples_X, X_n_samples_chunk, X_n_chunks, X_n_samples_last_chunk intp_t n_samples_Y, Y_n_samples_chunk, Y_n_chunks, Y_n_samples_last_chunk bint execute_in_parallel_on_Y @final cdef void _parallel_on_X(self) noexcept nogil @final cdef void _parallel_on_Y(self) noexcept nogil # Placeholder methods which have to be implemented cdef void _compute_and_reduce_distances_on_chunks( self, intp_t X_start, intp_t X_end, intp_t Y_start, intp_t Y_end, intp_t thread_num, ) noexcept nogil # Placeholder methods which can be implemented cdef void compute_exact_distances(self) noexcept nogil cdef void _parallel_on_X_parallel_init( self, intp_t thread_num, ) noexcept nogil cdef void _parallel_on_X_init_chunk( self, intp_t thread_num, intp_t X_start, intp_t X_end, ) noexcept nogil cdef void _parallel_on_X_pre_compute_and_reduce_distances_on_chunks( self, intp_t X_start, intp_t X_end, intp_t Y_start, intp_t Y_end, intp_t thread_num, ) noexcept nogil cdef void _parallel_on_X_prange_iter_finalize( self, intp_t thread_num, intp_t X_start, intp_t X_end, ) noexcept nogil cdef void _parallel_on_X_parallel_finalize( self, intp_t thread_num ) noexcept nogil cdef void _parallel_on_Y_init( self, ) noexcept nogil cdef void _parallel_on_Y_parallel_init( self, intp_t thread_num, intp_t X_start, intp_t X_end, ) noexcept nogil cdef void _parallel_on_Y_pre_compute_and_reduce_distances_on_chunks( self, intp_t X_start, intp_t X_end, intp_t Y_start, intp_t Y_end, intp_t thread_num, ) noexcept nogil cdef void _parallel_on_Y_synchronize( self, intp_t X_start, intp_t X_end, ) noexcept nogil cdef void _parallel_on_Y_finalize( self, ) noexcept nogil