some new features

.venv/lib/python3.12/site-packages/sklearn/utils/_seq_dataset.pxd.tp

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+{{py:
+
+"""
+Dataset abstractions for sequential data access.
+
+Template file for easily generate fused types consistent code using Tempita
+(https://github.com/cython/cython/blob/master/Cython/Tempita/_tempita.py).
+
+Generated file: _seq_dataset.pxd
+
+Each class is duplicated for all dtypes (float and double). The keywords
+between double braces are substituted in setup.py.
+"""
+
+# name_suffix, c_type
+dtypes = [('64', 'float64_t'),
+          ('32', 'float32_t')]
+
+}}
+"""Dataset abstractions for sequential data access."""
+
+from ._typedefs cimport float32_t, float64_t, intp_t, uint32_t
+
+# SequentialDataset and its two concrete subclasses are (optionally randomized)
+# iterators over the rows of a matrix X and corresponding target values y.
+
+{{for name_suffix, c_type in dtypes}}
+
+#------------------------------------------------------------------------------
+
+cdef class SequentialDataset{{name_suffix}}:
+    cdef int current_index
+    cdef int[::1] index
+    cdef int *index_data_ptr
+    cdef Py_ssize_t n_samples
+    cdef uint32_t seed
+
+    cdef void shuffle(self, uint32_t seed) noexcept nogil
+    cdef int _get_next_index(self) noexcept nogil
+    cdef int _get_random_index(self) noexcept nogil
+
+    cdef void _sample(self, {{c_type}} **x_data_ptr, int **x_ind_ptr,
+                      int *nnz, {{c_type}} *y, {{c_type}} *sample_weight,
+                      int current_index) noexcept nogil
+    cdef void next(self, {{c_type}} **x_data_ptr, int **x_ind_ptr,
+                   int *nnz, {{c_type}} *y, {{c_type}} *sample_weight) noexcept nogil
+    cdef int random(self, {{c_type}} **x_data_ptr, int **x_ind_ptr,
+                    int *nnz, {{c_type}} *y, {{c_type}} *sample_weight) noexcept nogil
+
+
+cdef class ArrayDataset{{name_suffix}}(SequentialDataset{{name_suffix}}):
+    cdef const {{c_type}}[:, ::1] X
+    cdef const {{c_type}}[::1] Y
+    cdef const {{c_type}}[::1] sample_weights
+    cdef Py_ssize_t n_features
+    cdef intp_t X_stride
+    cdef {{c_type}} *X_data_ptr
+    cdef {{c_type}} *Y_data_ptr
+    cdef const int[::1] feature_indices
+    cdef int *feature_indices_ptr
+    cdef {{c_type}} *sample_weight_data
+
+
+cdef class CSRDataset{{name_suffix}}(SequentialDataset{{name_suffix}}):
+    cdef const {{c_type}}[::1] X_data
+    cdef const int[::1] X_indptr
+    cdef const int[::1] X_indices
+    cdef const {{c_type}}[::1] Y
+    cdef const {{c_type}}[::1] sample_weights
+    cdef {{c_type}} *X_data_ptr
+    cdef int *X_indptr_ptr
+    cdef int *X_indices_ptr
+    cdef {{c_type}} *Y_data_ptr
+    cdef {{c_type}} *sample_weight_data
+
+{{endfor}}