From 930e27d115489363b4cb6e5b9324ca9474fb0149 Mon Sep 17 00:00:00 2001
From: Joan Massich <sik@visor.udg.edu>
Date: Fri, 1 Mar 2019 16:10:27 +0100
Subject: [PATCH 01/39] [skip ci] Trigger PR


From f40dcca834dbc5fdc65f53f08efc665aa3a1b683 Mon Sep 17 00:00:00 2001
From: Joan Massich <sik@visor.udg.edu>
Date: Fri, 1 Mar 2019 16:52:32 +0100
Subject: [PATCH 02/39] Move weith_vector to a template

---
 sklearn/utils/setup.py                                    | 4 +++-
 sklearn/utils/{weight_vector.pxd => weight_vector.pxd.tp} | 0
 2 files changed, 3 insertions(+), 1 deletion(-)
 rename sklearn/utils/{weight_vector.pxd => weight_vector.pxd.tp} (100%)

diff --git a/sklearn/utils/setup.py b/sklearn/utils/setup.py
index f3002ed3ffed9..4b5246fd7b5b1 100644
--- a/sklearn/utils/setup.py
+++ b/sklearn/utils/setup.py
@@ -48,7 +48,9 @@ def configuration(parent_package='', top_path=None):
 
     # generate files from a template
     pyx_templates = ['sklearn/utils/seq_dataset.pyx.tp',
-                     'sklearn/utils/seq_dataset.pxd.tp']
+                     'sklearn/utils/seq_dataset.pxd.tp',
+                     'sklearn/utils/weight_vector.pxd.tp',
+                     ]
 
     for pyxfiles in pyx_templates:
         outfile = pyxfiles.replace('.tp', '')
diff --git a/sklearn/utils/weight_vector.pxd b/sklearn/utils/weight_vector.pxd.tp
similarity index 100%
rename from sklearn/utils/weight_vector.pxd
rename to sklearn/utils/weight_vector.pxd.tp

From c158a791b6cd56c3dec8bdd338e042d19c9b9a05 Mon Sep 17 00:00:00 2001
From: Joan Massich <sik@visor.udg.edu>
Date: Fri, 1 Mar 2019 16:53:25 +0100
Subject: [PATCH 03/39] transform weight_vector.pxd.tp into a template

---
 sklearn/utils/weight_vector.pxd.tp | 58 +++++++++++++++++++++---------
 1 file changed, 42 insertions(+), 16 deletions(-)

diff --git a/sklearn/utils/weight_vector.pxd.tp b/sklearn/utils/weight_vector.pxd.tp
index 4ba4374c05e6c..144f84669afbd 100644
--- a/sklearn/utils/weight_vector.pxd.tp
+++ b/sklearn/utils/weight_vector.pxd.tp
@@ -1,30 +1,56 @@
+{{py:
+
+"""
+Efficient (dense) parameter vector implementation for linear models. 
+
+Template file for easily generate fused types consistent code using Tempita
+(https://github.com/cython/cython/blob/master/Cython/Tempita/_tempita.py).
+
+Generated file: weight_vector.pxd
+
+Each class is duplicated for all dtypes (float and double). The keywords
+between double braces are substituted in setup.py.
+"""
+
+# name, c_type
+dtypes = [('64', 'double'),
+          ('32', 'float')]
+
+def get_dispatch(dtypes):
+    for name, c_type in dtypes:
+        yield name, c_type
+
+}}
+
 # cython: language_level=3
-"""Efficient (dense) parameter vector implementation for linear models. """
 
 cimport numpy as np
 
+{{for name, c_type in get_dispatch(dtypes)}}
 
 cdef extern from "math.h":
-    cdef extern double sqrt(double x)
+    cdef extern {{c_type}} sqrt({{c_type}} x)
 
 
-cdef class WeightVector(object):
+cdef class WeightVector{{name}}(object):
     cdef np.ndarray w
     cdef np.ndarray aw
-    cdef double *w_data_ptr
-    cdef double *aw_data_ptr
-    cdef double wscale
-    cdef double average_a
-    cdef double average_b
+    cdef {{c_type}} *w_data_ptr
+    cdef {{c_type}} *aw_data_ptr
+    cdef {{c_type}} wscale
+    cdef {{c_type}} average_a
+    cdef {{c_type}} average_b
     cdef int n_features
-    cdef double sq_norm
+    cdef {{c_type}} sq_norm
 
-    cdef void add(self,  double *x_data_ptr, int *x_ind_ptr,
-                  int xnnz, double c) nogil
-    cdef void add_average(self,  double *x_data_ptr, int *x_ind_ptr,
-                          int xnnz, double c, double num_iter) nogil
-    cdef double dot(self, double *x_data_ptr, int *x_ind_ptr,
+    cdef void add(self,  {{c_type}} *x_data_ptr, int *x_ind_ptr,
+                  int xnnz, {{c_type}} c) nogil
+    cdef void add_average(self,  {{c_type}} *x_data_ptr, int *x_ind_ptr,
+                          int xnnz, {{c_type}} c, {{c_type}} num_iter) nogil
+    cdef {{c_type}} dot(self, {{c_type}} *x_data_ptr, int *x_ind_ptr,
                     int xnnz) nogil
-    cdef void scale(self, double c) nogil
+    cdef void scale(self, {{c_type}} c) nogil
     cdef void reset_wscale(self) nogil
-    cdef double norm(self) nogil
+    cdef {{c_type}} norm(self) nogil
+
+{{endfor}}
\ No newline at end of file

From d1139a10b544fc60a7e67ebee095968d64819c85 Mon Sep 17 00:00:00 2001
From: Joan Massich <sik@visor.udg.edu>
Date: Fri, 1 Mar 2019 16:56:39 +0100
Subject: [PATCH 04/39] move pyx into pyx.tp

---
 sklearn/utils/{weight_vector.pyx => weight_vector.pyx.tp} | 0
 1 file changed, 0 insertions(+), 0 deletions(-)
 rename sklearn/utils/{weight_vector.pyx => weight_vector.pyx.tp} (100%)

diff --git a/sklearn/utils/weight_vector.pyx b/sklearn/utils/weight_vector.pyx.tp
similarity index 100%
rename from sklearn/utils/weight_vector.pyx
rename to sklearn/utils/weight_vector.pyx.tp

From ef6ca46850ed48c14afc33c01775ec68a4ea7c76 Mon Sep 17 00:00:00 2001
From: Joan Massich <sik@visor.udg.edu>
Date: Fri, 1 Mar 2019 17:39:20 +0100
Subject: [PATCH 05/39] first pass in changing doubles

---
 sklearn/utils/setup.py             |   1 +
 sklearn/utils/weight_vector.pyx.tp | 100 ++++++++++++++++++-----------
 2 files changed, 65 insertions(+), 36 deletions(-)

diff --git a/sklearn/utils/setup.py b/sklearn/utils/setup.py
index 4b5246fd7b5b1..8c13ffec21ecf 100644
--- a/sklearn/utils/setup.py
+++ b/sklearn/utils/setup.py
@@ -49,6 +49,7 @@ def configuration(parent_package='', top_path=None):
     # generate files from a template
     pyx_templates = ['sklearn/utils/seq_dataset.pyx.tp',
                      'sklearn/utils/seq_dataset.pxd.tp',
+                     'sklearn/utils/weight_vector.pyx.tp',
                      'sklearn/utils/weight_vector.pxd.tp',
                      ]
 
diff --git a/sklearn/utils/weight_vector.pyx.tp b/sklearn/utils/weight_vector.pyx.tp
index 91c5273d210e4..4cb9a2059b21c 100644
--- a/sklearn/utils/weight_vector.pyx.tp
+++ b/sklearn/utils/weight_vector.pyx.tp
@@ -1,3 +1,27 @@
+{{py:
+
+"""
+Efficient (dense) parameter vector implementation for linear models. 
+
+Template file for easily generate fused types consistent code using Tempita
+(https://github.com/cython/cython/blob/master/Cython/Tempita/_tempita.py).
+
+Generated file: weight_vector.pxd
+
+Each class is duplicated for all dtypes (float and double). The keywords
+between double braces are substituted in setup.py.
+"""
+
+# name, c_type
+dtypes = [('64', 'double'),
+          ('32', 'float')]
+
+def get_dispatch(dtypes):
+    for name, c_type in dtypes:
+        yield name, c_type
+
+}}
+
 # cython: cdivision=True
 # cython: boundscheck=False
 # cython: wraparound=False
@@ -21,7 +45,9 @@ from ._cython_blas cimport _dot, _scal, _axpy
 np.import_array()
 
 
-cdef class WeightVector(object):
+{{for name, c_type in get_dispatch(dtypes)}}
+
+cdef class WeightVector{{name}}(object):
     """Dense vector represented by a scalar and a numpy array.
 
     The class provides methods to ``add`` a sparse vector
@@ -31,24 +57,24 @@ cdef class WeightVector(object):
 
     Attributes
     ----------
-    w : ndarray, dtype=double, order='C'
+    w : ndarray, dtype={{c_type}}, order='C'
         The numpy array which backs the weight vector.
-    aw : ndarray, dtype=double, order='C'
+    aw : ndarray, dtype={{c_type}}, order='C'
         The numpy array which backs the average_weight vector.
-    w_data_ptr : double*
+    w_data_ptr : {{c_type}}*
         A pointer to the data of the numpy array.
-    wscale : double
+    wscale : {{c_type}}
         The scale of the vector.
     n_features : int
         The number of features (= dimensionality of ``w``).
-    sq_norm : double
+    sq_norm : {{c_type}}
         The squared norm of ``w``.
     """
 
     def __cinit__(self,
-                  np.ndarray[double, ndim=1, mode='c'] w,
-                  np.ndarray[double, ndim=1, mode='c'] aw):
-        cdef double *wdata = <double *>w.data
+                  np.ndarray[{{c_type}}, ndim=1, mode='c'] w,
+                  np.ndarray[{{c_type}}, ndim=1, mode='c'] aw):
+        cdef {{c_type}} *wdata = <{{c_type}} *>w.data
 
         if w.shape[0] > INT_MAX:
             raise ValueError("More than %d features not supported; got %d."
@@ -57,7 +83,7 @@ cdef class WeightVector(object):
         self.w_data_ptr = wdata
         self.wscale = 1.0
         self.n_features = w.shape[0]
-        self.sq_norm = _dot(<int>w.shape[0], wdata, 1, wdata, 1)
+        self.sq_norm = _dot(w.shape[0], wdata, 1, wdata, 1)
 
         self.aw = aw
         if self.aw is not None:
@@ -65,32 +91,32 @@ cdef class WeightVector(object):
             self.average_a = 0.0
             self.average_b = 1.0
 
-    cdef void add(self, double *x_data_ptr, int *x_ind_ptr, int xnnz,
-                  double c) nogil:
+    cdef void add(self, {{c_type}} *x_data_ptr, int *x_ind_ptr, int xnnz,
+                  {{c_type}} c) nogil:
         """Scales sample x by constant c and adds it to the weight vector.
 
         This operation updates ``sq_norm``.
 
         Parameters
         ----------
-        x_data_ptr : double*
+        x_data_ptr : {{c_type}}*
             The array which holds the feature values of ``x``.
         x_ind_ptr : np.intc*
             The array which holds the feature indices of ``x``.
         xnnz : int
             The number of non-zero features of ``x``.
-        c : double
+        c : {{c_type}}
             The scaling constant for the example.
         """
         cdef int j
         cdef int idx
-        cdef double val
-        cdef double innerprod = 0.0
-        cdef double xsqnorm = 0.0
+        cdef {{c_type}} val
+        cdef {{c_type}} innerprod = 0.0
+        cdef {{c_type}} xsqnorm = 0.0
 
         # the next two lines save a factor of 2!
-        cdef double wscale = self.wscale
-        cdef double* w_data_ptr = self.w_data_ptr
+        cdef {{c_type}} wscale = self.wscale
+        cdef {{c_type}}* w_data_ptr = self.w_data_ptr
 
         for j in range(xnnz):
             idx = x_ind_ptr[j]
@@ -104,30 +130,30 @@ cdef class WeightVector(object):
     # Update the average weights according to the sparse trick defined
     # here: https://research.microsoft.com/pubs/192769/tricks-2012.pdf
     # by Leon Bottou
-    cdef void add_average(self, double *x_data_ptr, int *x_ind_ptr, int xnnz,
-                          double c, double num_iter) nogil:
+    cdef void add_average(self, {{c_type}} *x_data_ptr, int *x_ind_ptr, int xnnz,
+                          {{c_type}} c, {{c_type}} num_iter) nogil:
         """Updates the average weight vector.
 
         Parameters
         ----------
-        x_data_ptr : double*
+        x_data_ptr : {{c_type}}*
             The array which holds the feature values of ``x``.
         x_ind_ptr : np.intc*
             The array which holds the feature indices of ``x``.
         xnnz : int
             The number of non-zero features of ``x``.
-        c : double
+        c : {{c_type}}
             The scaling constant for the example.
-        num_iter : double
+        num_iter : {{c_type}}
             The total number of iterations.
         """
         cdef int j
         cdef int idx
-        cdef double val
-        cdef double mu = 1.0 / num_iter
-        cdef double average_a = self.average_a
-        cdef double wscale = self.wscale
-        cdef double* aw_data_ptr = self.aw_data_ptr
+        cdef {{c_type}} val
+        cdef {{c_type}} mu = 1.0 / num_iter
+        cdef {{c_type}} average_a = self.average_a
+        cdef {{c_type}} wscale = self.wscale
+        cdef {{c_type}}* aw_data_ptr = self.aw_data_ptr
 
         for j in range(xnnz):
             idx = x_ind_ptr[j]
@@ -140,13 +166,13 @@ cdef class WeightVector(object):
             self.average_b /= (1.0 - mu)
         self.average_a += mu * self.average_b * wscale
 
-    cdef double dot(self, double *x_data_ptr, int *x_ind_ptr,
+    cdef {{c_type}} dot(self, {{c_type}} *x_data_ptr, int *x_ind_ptr,
                     int xnnz) nogil:
         """Computes the dot product of a sample x and the weight vector.
 
         Parameters
         ----------
-        x_data_ptr : double*
+        x_data_ptr : {{c_type}}*
             The array which holds the feature values of ``x``.
         x_ind_ptr : np.intc*
             The array which holds the feature indices of ``x``.
@@ -155,20 +181,20 @@ cdef class WeightVector(object):
 
         Returns
         -------
-        innerprod : double
+        innerprod : {{c_type}}
             The inner product of ``x`` and ``w``.
         """
         cdef int j
         cdef int idx
-        cdef double innerprod = 0.0
-        cdef double* w_data_ptr = self.w_data_ptr
+        cdef {{c_type}} innerprod = 0.0
+        cdef {{c_type}}* w_data_ptr = self.w_data_ptr
         for j in range(xnnz):
             idx = x_ind_ptr[j]
             innerprod += w_data_ptr[idx] * x_data_ptr[j]
         innerprod *= self.wscale
         return innerprod
 
-    cdef void scale(self, double c) nogil:
+    cdef void scale(self, {{c_type}} c) nogil:
         """Scales the weight vector by a constant ``c``.
 
         It updates ``wscale`` and ``sq_norm``. If ``wscale`` gets too
@@ -191,6 +217,8 @@ cdef class WeightVector(object):
         _scal(<int>self.w.shape[0], self.wscale, <double *>self.w.data, 1)
         self.wscale = 1.0
 
-    cdef double norm(self) nogil:
+    cdef {{c_type}} norm(self) nogil:
         """The L2 norm of the weight vector. """
         return sqrt(self.sq_norm)
+
+{{endfor}}
\ No newline at end of file

From 04ce5c9ac5ac63dd559a7e937950a39e326dac3e Mon Sep 17 00:00:00 2001
From: Joan Massich <sik@visor.udg.edu>
Date: Fri, 1 Mar 2019 17:40:55 +0100
Subject: [PATCH 06/39] change all double that were missing

---
 sklearn/utils/weight_vector.pyx.tp | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/sklearn/utils/weight_vector.pyx.tp b/sklearn/utils/weight_vector.pyx.tp
index 4cb9a2059b21c..0dbee605e9a3d 100644
--- a/sklearn/utils/weight_vector.pyx.tp
+++ b/sklearn/utils/weight_vector.pyx.tp
@@ -87,7 +87,7 @@ cdef class WeightVector{{name}}(object):
 
         self.aw = aw
         if self.aw is not None:
-            self.aw_data_ptr = <double *>aw.data
+            self.aw_data_ptr = <{{c_type}} *>aw.data
             self.average_a = 0.0
             self.average_b = 1.0
 
@@ -208,13 +208,13 @@ cdef class WeightVector{{name}}(object):
         """Scales each coef of ``w`` by ``wscale`` and resets it to 1. """
         if self.aw is not None:
             _axpy(<int>self.aw.shape[0], self.average_a,
-                  <double *>self.w.data, 1, <double *>self.aw.data, 1)
+                  <{{c_type}} *>self.w.data, 1, <{{c_type}} *>self.aw.data, 1)
             _scal(<int>self.aw.shape[0], 1.0 / self.average_b,
-                  <double *>self.aw.data, 1)
+                  <{{c_type}} *>self.aw.data, 1)
             self.average_a = 0.0
             self.average_b = 1.0
 
-        _scal(<int>self.w.shape[0], self.wscale, <double *>self.w.data, 1)
+        _scal(<int>self.w.shape[0], self.wscale, <{{c_type}} *>self.w.data, 1)
         self.wscale = 1.0
 
     cdef {{c_type}} norm(self) nogil:

From 50de2663befcbd755db0fa62535dfdb71ed27c4a Mon Sep 17 00:00:00 2001
From: Joan Massich <sik@visor.udg.edu>
Date: Fri, 1 Mar 2019 17:45:11 +0100
Subject: [PATCH 07/39] fix compilation

---
 sklearn/linear_model/sgd_fast.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/linear_model/sgd_fast.pyx b/sklearn/linear_model/sgd_fast.pyx
index ddea4b9710501..1b98e8c907f2b 100644
--- a/sklearn/linear_model/sgd_fast.pyx
+++ b/sklearn/linear_model/sgd_fast.pyx
@@ -22,7 +22,7 @@ from numpy.math cimport INFINITY
 cdef extern from "sgd_fast_helpers.h":
     bint skl_isfinite(double) nogil
 
-from sklearn.utils.weight_vector cimport WeightVector
+from sklearn.utils.weight_vector cimport WeightVector64 as WeightVector
 from sklearn.utils.seq_dataset cimport SequentialDataset64 as SequentialDataset
 
 np.import_array()

From 3a05e422833c742c978dc7bcbeffde186d1c5aae Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Wed, 7 Jul 2021 12:39:48 +0200
Subject: [PATCH 08/39] Add newlines to template files.

---
 sklearn/utils/_weight_vector.pxd.tp | 2 +-
 sklearn/utils/_weight_vector.pyx.tp | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/sklearn/utils/_weight_vector.pxd.tp b/sklearn/utils/_weight_vector.pxd.tp
index 144f84669afbd..cba9c18520722 100644
--- a/sklearn/utils/_weight_vector.pxd.tp
+++ b/sklearn/utils/_weight_vector.pxd.tp
@@ -53,4 +53,4 @@ cdef class WeightVector{{name}}(object):
     cdef void reset_wscale(self) nogil
     cdef {{c_type}} norm(self) nogil
 
-{{endfor}}
\ No newline at end of file
+{{endfor}}
diff --git a/sklearn/utils/_weight_vector.pyx.tp b/sklearn/utils/_weight_vector.pyx.tp
index 0dbee605e9a3d..19ad52b24b107 100644
--- a/sklearn/utils/_weight_vector.pyx.tp
+++ b/sklearn/utils/_weight_vector.pyx.tp
@@ -221,4 +221,4 @@ cdef class WeightVector{{name}}(object):
         """The L2 norm of the weight vector. """
         return sqrt(self.sq_norm)
 
-{{endfor}}
\ No newline at end of file
+{{endfor}}

From f8bd689cda74584e30d6ef5bd612211287519eb9 Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Wed, 7 Jul 2021 14:18:42 +0200
Subject: [PATCH 09/39] Git-ignore `.pyx` and `.pxd` files generated by Tempita
 from `weight_vector` templates

---
 .gitignore | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/.gitignore b/.gitignore
index 3ebd8e2bb1699..2c3dd0c4794c1 100644
--- a/.gitignore
+++ b/.gitignore
@@ -78,4 +78,6 @@ _configtest.o.d
 # files generated from a template
 sklearn/utils/_seq_dataset.pyx
 sklearn/utils/_seq_dataset.pxd
+sklearn/utils/_weight_vector.pyx
+sklearn/utils/_weight_vector.pxd
 sklearn/linear_model/_sag_fast.pyx

From 41d9a0dc8ea27fd64494793c436da35874b3dda7 Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Wed, 7 Jul 2021 14:21:39 +0200
Subject: [PATCH 10/39] Remove `get_dispatch` unnecessary function and iterate
 directly over the`dtypes` list in Tempita `.tp` files

---
 sklearn/linear_model/_sag_fast.pyx.tp | 22 +++++++++-------------
 sklearn/utils/_seq_dataset.pxd.tp     |  6 +-----
 sklearn/utils/_seq_dataset.pyx.tp     |  6 +-----
 sklearn/utils/_weight_vector.pxd.tp   |  6 +-----
 sklearn/utils/_weight_vector.pyx.tp   |  7 +------
 5 files changed, 13 insertions(+), 34 deletions(-)

diff --git a/sklearn/linear_model/_sag_fast.pyx.tp b/sklearn/linear_model/_sag_fast.pyx.tp
index 8508340e3b329..d9989f60aa23a 100644
--- a/sklearn/linear_model/_sag_fast.pyx.tp
+++ b/sklearn/linear_model/_sag_fast.pyx.tp
@@ -23,10 +23,6 @@ License: BSD 3 clause
 dtypes = [('64', 'double', 'np.float64'),
           ('32', 'float', 'np.float32')]
 
-def get_dispatch(dtypes):
-    for name, c_type, np_type in dtypes:
-        yield name, c_type, np_type
-
 }}
 
 #------------------------------------------------------------------------------
@@ -61,7 +57,7 @@ from libc.stdio cimport printf
 np.import_array()
 
 
-{{for name, c_type, np_type in get_dispatch(dtypes)}}
+{{for name, c_type, np_type in dtypes}}
 
 cdef extern from "_sgd_fast_helpers.h":
     bint skl_isfinite{{name}}({{c_type}}) nogil
@@ -69,7 +65,7 @@ cdef extern from "_sgd_fast_helpers.h":
 
 {{endfor}}
 
-{{for name, c_type, np_type in get_dispatch(dtypes)}}
+{{for name, c_type, np_type in dtypes}}
 
 cdef inline {{c_type}} fmax{{name}}({{c_type}} x, {{c_type}} y) nogil:
     if x > y:
@@ -79,7 +75,7 @@ cdef inline {{c_type}} fmax{{name}}({{c_type}} x, {{c_type}} y) nogil:
 {{endfor}}
 
 
-{{for name, c_type, np_type in get_dispatch(dtypes)}}
+{{for name, c_type, np_type in dtypes}}
 
 cdef {{c_type}} _logsumexp{{name}}({{c_type}}* arr, int n_classes) nogil:
     """Computes the sum of arr assuming arr is in the log domain.
@@ -105,7 +101,7 @@ cdef {{c_type}} _logsumexp{{name}}({{c_type}}* arr, int n_classes) nogil:
 {{endfor}}
 
 
-{{for name, c_type, np_type in get_dispatch(dtypes)}}
+{{for name, c_type, np_type in dtypes}}
 
 cdef class MultinomialLogLoss{{name}}:
     cdef {{c_type}} _loss(self, {{c_type}}* prediction, {{c_type}} y, int n_classes,
@@ -209,7 +205,7 @@ cdef class MultinomialLogLoss{{name}}:
 
 {{endfor}}
 
-{{for name, c_type, np_type in get_dispatch(dtypes)}}
+{{for name, c_type, np_type in dtypes}}
 
 cdef inline {{c_type}} _soft_thresholding{{name}}({{c_type}} x, {{c_type}} shrinkage) nogil:
     return fmax{{name}}(x - shrinkage, 0) - fmax{{name}}(- x - shrinkage, 0)
@@ -217,7 +213,7 @@ cdef inline {{c_type}} _soft_thresholding{{name}}({{c_type}} x, {{c_type}} shrin
 {{endfor}}
 
 
-{{for name, c_type, np_type in get_dispatch(dtypes)}}
+{{for name, c_type, np_type in dtypes}}
 
 def sag{{name}}(SequentialDataset{{name}} dataset,
         np.ndarray[{{c_type}}, ndim=2, mode='c'] weights_array,
@@ -553,7 +549,7 @@ def sag{{name}}(SequentialDataset{{name}} dataset,
 {{endfor}}
 
 
-{{for name, c_type, np_type in get_dispatch(dtypes)}}
+{{for name, c_type, np_type in dtypes}}
 
 cdef int scale_weights{{name}}({{c_type}}* weights, {{c_type}}* wscale,
                                int n_features,
@@ -592,7 +588,7 @@ cdef int scale_weights{{name}}({{c_type}}* weights, {{c_type}}* wscale,
 {{endfor}}
 
 
-{{for name, c_type, np_type in get_dispatch(dtypes)}}
+{{for name, c_type, np_type in dtypes}}
 
 cdef int lagged_update{{name}}({{c_type}}* weights, {{c_type}} wscale, int xnnz,
                                int n_samples, int n_classes, int sample_itr,
@@ -683,7 +679,7 @@ cdef int lagged_update{{name}}({{c_type}}* weights, {{c_type}} wscale, int xnnz,
 {{endfor}}
 
 
-{{for name, c_type, np_type in get_dispatch(dtypes)}}
+{{for name, c_type, np_type in dtypes}}
 
 cdef void predict_sample{{name}}({{c_type}}* x_data_ptr, int* x_ind_ptr, int xnnz,
                                  {{c_type}}* w_data_ptr, {{c_type}} wscale,
diff --git a/sklearn/utils/_seq_dataset.pxd.tp b/sklearn/utils/_seq_dataset.pxd.tp
index be2d94a05b015..9e4237fc0f51a 100644
--- a/sklearn/utils/_seq_dataset.pxd.tp
+++ b/sklearn/utils/_seq_dataset.pxd.tp
@@ -16,12 +16,8 @@ between double braces are substituted in setup.py.
 dtypes = [('64', 'double'),
           ('32', 'float')]
 
-def get_dispatch(dtypes):
-    for name, c_type in dtypes:
-        yield name, c_type
-
 }}
-{{for name, c_type in get_dispatch(dtypes)}}
+{{for name, c_type in dtypes}}
 
 #------------------------------------------------------------------------------
 
diff --git a/sklearn/utils/_seq_dataset.pyx.tp b/sklearn/utils/_seq_dataset.pyx.tp
index 44edb9216dc62..a5173fb60c0da 100644
--- a/sklearn/utils/_seq_dataset.pyx.tp
+++ b/sklearn/utils/_seq_dataset.pyx.tp
@@ -24,12 +24,8 @@ License: BSD 3 clause
 dtypes = [('64', 'double', 'np.float64'),
           ('32', 'float', 'np.float32')]
 
-def get_dispatch(dtypes):
-    for name, c_type, np_type in dtypes:
-        yield name, c_type, np_type
-
 }}
-{{for name, c_type, np_type in get_dispatch(dtypes)}}
+{{for name, c_type, np_type in dtypes}}
 
 #------------------------------------------------------------------------------
 
diff --git a/sklearn/utils/_weight_vector.pxd.tp b/sklearn/utils/_weight_vector.pxd.tp
index cba9c18520722..7ef0fd017bd69 100644
--- a/sklearn/utils/_weight_vector.pxd.tp
+++ b/sklearn/utils/_weight_vector.pxd.tp
@@ -16,17 +16,13 @@ between double braces are substituted in setup.py.
 dtypes = [('64', 'double'),
           ('32', 'float')]
 
-def get_dispatch(dtypes):
-    for name, c_type in dtypes:
-        yield name, c_type
-
 }}
 
 # cython: language_level=3
 
 cimport numpy as np
 
-{{for name, c_type in get_dispatch(dtypes)}}
+{{for name, c_type in dtypes}}
 
 cdef extern from "math.h":
     cdef extern {{c_type}} sqrt({{c_type}} x)
diff --git a/sklearn/utils/_weight_vector.pyx.tp b/sklearn/utils/_weight_vector.pyx.tp
index 19ad52b24b107..b36f475183c2a 100644
--- a/sklearn/utils/_weight_vector.pyx.tp
+++ b/sklearn/utils/_weight_vector.pyx.tp
@@ -16,10 +16,6 @@ between double braces are substituted in setup.py.
 dtypes = [('64', 'double'),
           ('32', 'float')]
 
-def get_dispatch(dtypes):
-    for name, c_type in dtypes:
-        yield name, c_type
-
 }}
 
 # cython: cdivision=True
@@ -44,8 +40,7 @@ from ._cython_blas cimport _dot, _scal, _axpy
 
 np.import_array()
 
-
-{{for name, c_type in get_dispatch(dtypes)}}
+{{for name, c_type in dtypes}}
 
 cdef class WeightVector{{name}}(object):
     """Dense vector represented by a scalar and a numpy array.

From c383712440bc7ce040031d5256fe140accbfcc3e Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Tue, 13 Jul 2021 09:15:25 +0200
Subject: [PATCH 11/39] Test that files generated by templates are git-ignored.

---
 sklearn/utils/tests/test_cython_templating.py | 15 +++++++++++++++
 1 file changed, 15 insertions(+)
 create mode 100644 sklearn/utils/tests/test_cython_templating.py

diff --git a/sklearn/utils/tests/test_cython_templating.py b/sklearn/utils/tests/test_cython_templating.py
new file mode 100644
index 0000000000000..79d71e3993f68
--- /dev/null
+++ b/sklearn/utils/tests/test_cython_templating.py
@@ -0,0 +1,15 @@
+import pathlib
+import pytest
+import sklearn
+
+TEMPITA_EXTENSION = "tp"
+
+
+def test_files_generated_by_templates_are_git_ignored():
+    gitignore_file = pathlib.Path(sklearn.__file__).parent.parent / ".gitignore"
+    if not gitignore_file.exists():
+        pytest.skip("Tests are not run from the source folder")
+    base_dir = pathlib.Path(sklearn.__file__).parent
+    for filename in base_dir.glob(f"**/*.{TEMPITA_EXTENSION}"):
+        filename_wo_tempita_suffix = filename.with_suffix("")
+        assert not filename_wo_tempita_suffix.exists()

From c6625c0eee909135d6f6a690f4cf940fbdae8275 Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Tue, 13 Jul 2021 19:14:35 +0200
Subject: [PATCH 12/39] Add `_sag_fast` templates to `setup.py` + git-ignore
 the generated files.

---
 .gitignore             | 1 +
 sklearn/utils/setup.py | 1 +
 2 files changed, 2 insertions(+)

diff --git a/.gitignore b/.gitignore
index 2c3dd0c4794c1..95a87a876d8a1 100644
--- a/.gitignore
+++ b/.gitignore
@@ -81,3 +81,4 @@ sklearn/utils/_seq_dataset.pxd
 sklearn/utils/_weight_vector.pyx
 sklearn/utils/_weight_vector.pxd
 sklearn/linear_model/_sag_fast.pyx
+sklearn/linear_model/_sag_fast.pxd
diff --git a/sklearn/utils/setup.py b/sklearn/utils/setup.py
index eba6daf26d5fd..7069478d513c0 100644
--- a/sklearn/utils/setup.py
+++ b/sklearn/utils/setup.py
@@ -55,6 +55,7 @@ def configuration(parent_package="", top_path=None):
         "sklearn/utils/_seq_dataset.pxd.tp",
         "sklearn/utils/_weight_vector.pyx.tp",
         "sklearn/utils/_weight_vector.pxd.tp",
+        "sklearn/linear_model/_sag_fast.pyx.tp",
     ]
 
     gen_from_templates(templates, top_path)

From 1bc6be834ccd3e14bee17cf98f60509cf4149158 Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 26 Jul 2021 11:10:13 +0200
Subject: [PATCH 13/39] Read `.gitignore` file content and check files
 generated by Tempita templates are included.

---
 sklearn/utils/tests/test_cython_templating.py | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/sklearn/utils/tests/test_cython_templating.py b/sklearn/utils/tests/test_cython_templating.py
index 79d71e3993f68..124045d84b08f 100644
--- a/sklearn/utils/tests/test_cython_templating.py
+++ b/sklearn/utils/tests/test_cython_templating.py
@@ -9,7 +9,12 @@ def test_files_generated_by_templates_are_git_ignored():
     gitignore_file = pathlib.Path(sklearn.__file__).parent.parent / ".gitignore"
     if not gitignore_file.exists():
         pytest.skip("Tests are not run from the source folder")
+
     base_dir = pathlib.Path(sklearn.__file__).parent
+    ignored_files = open(gitignore_file, "r").readlines()
+    ignored_files = list(map(lambda line: line.strip("\n"), ignored_files))
+
     for filename in base_dir.glob(f"**/*.{TEMPITA_EXTENSION}"):
-        filename_wo_tempita_suffix = filename.with_suffix("")
-        assert not filename_wo_tempita_suffix.exists()
+        filename = str(filename).split("scikit-learn/")[-1]
+        filename_wo_tempita_suffix = filename.strip(f".{TEMPITA_EXTENSION}")
+        assert filename_wo_tempita_suffix in ignored_files

From c05767b6328409376b4dff0c4d582d833ebb7629 Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 26 Jul 2021 11:16:56 +0200
Subject: [PATCH 14/39] Set `w` and `aw` attributes as `readonly`.

---
 sklearn/utils/_weight_vector.pxd.tp | 4 ++--
 sklearn/utils/_weight_vector.pyx.tp | 3 +++
 2 files changed, 5 insertions(+), 2 deletions(-)

diff --git a/sklearn/utils/_weight_vector.pxd.tp b/sklearn/utils/_weight_vector.pxd.tp
index 7ef0fd017bd69..b70c8e8eccd52 100644
--- a/sklearn/utils/_weight_vector.pxd.tp
+++ b/sklearn/utils/_weight_vector.pxd.tp
@@ -29,8 +29,8 @@ cdef extern from "math.h":
 
 
 cdef class WeightVector{{name}}(object):
-    cdef np.ndarray w
-    cdef np.ndarray aw
+    cdef readonly np.ndarray w
+    cdef readonly np.ndarray aw
     cdef {{c_type}} *w_data_ptr
     cdef {{c_type}} *aw_data_ptr
     cdef {{c_type}} wscale
diff --git a/sklearn/utils/_weight_vector.pyx.tp b/sklearn/utils/_weight_vector.pyx.tp
index b36f475183c2a..b77488b73a725 100644
--- a/sklearn/utils/_weight_vector.pyx.tp
+++ b/sklearn/utils/_weight_vector.pyx.tp
@@ -66,6 +66,9 @@ cdef class WeightVector{{name}}(object):
         The squared norm of ``w``.
     """
 
+    cdef readonly np.ndarray w
+    cdef readonly np.ndarray aw
+
     def __cinit__(self,
                   np.ndarray[{{c_type}}, ndim=1, mode='c'] w,
                   np.ndarray[{{c_type}}, ndim=1, mode='c'] aw):

From bedf4cfb6589b1b5cf23b09eb470ef8a1d36dbaf Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 26 Jul 2021 13:01:38 +0200
Subject: [PATCH 15/39] Add test for type invariance for `WeightVector`
 interface.

---
 sklearn/utils/tests/test_weight_vector.py | 23 +++++++++++++++++++++++
 1 file changed, 23 insertions(+)
 create mode 100644 sklearn/utils/tests/test_weight_vector.py

diff --git a/sklearn/utils/tests/test_weight_vector.py b/sklearn/utils/tests/test_weight_vector.py
new file mode 100644
index 0000000000000..21fe69a9e2e82
--- /dev/null
+++ b/sklearn/utils/tests/test_weight_vector.py
@@ -0,0 +1,23 @@
+# Author: Mathis Batoul <batoulmathis@gmail.com>
+#
+# License: BSD 3 clause
+
+import numpy as np
+from sklearn.utils._weight_vector import (
+    WeightVector32,
+    WeightVector64,
+)
+
+
+def test_type_invariance():
+    weights32 = np.random.rand(100).astype(np.float32)
+    average_weights32 = np.random.rand(100).astype(np.float32)
+    weight_vector32 = WeightVector32(weights32, average_weights32)
+    assert weight_vector32.w.dtype is np.dtype(np.float32)
+    assert weight_vector32.aw.dtype is np.dtype(np.float32)
+
+    weights64 = np.random.rand(100).astype(np.float64)
+    average_weights64 = np.random.rand(100).astype(np.float64)
+    weight_vector64 = WeightVector64(weights64, average_weights64)
+    assert weight_vector64.w.dtype is np.dtype(np.float64)
+    assert weight_vector64.aw.dtype is np.dtype(np.float64)

From bf766571124e24d97090670f381c027e028cd059 Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 26 Jul 2021 13:24:26 +0200
Subject: [PATCH 16/39] Remove unnecessary file from `gitignore`.

---
 .gitignore | 1 -
 1 file changed, 1 deletion(-)

diff --git a/.gitignore b/.gitignore
index 95a87a876d8a1..2c3dd0c4794c1 100644
--- a/.gitignore
+++ b/.gitignore
@@ -81,4 +81,3 @@ sklearn/utils/_seq_dataset.pxd
 sklearn/utils/_weight_vector.pyx
 sklearn/utils/_weight_vector.pxd
 sklearn/linear_model/_sag_fast.pyx
-sklearn/linear_model/_sag_fast.pxd

From df6e5490c25a3d92c262f2861501e0ef60278d2f Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 26 Jul 2021 13:24:59 +0200
Subject: [PATCH 17/39] Move lines of code to reduce diff.

---
 sklearn/utils/setup.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/sklearn/utils/setup.py b/sklearn/utils/setup.py
index 7069478d513c0..2b54918ac12ca 100644
--- a/sklearn/utils/setup.py
+++ b/sklearn/utils/setup.py
@@ -49,6 +49,10 @@ def configuration(parent_package="", top_path=None):
         libraries=libraries,
     )
 
+    config.add_extension(
+        "_openmp_helpers", sources=["_openmp_helpers.pyx"], libraries=libraries
+    )
+
     # generate files from a template
     templates = [
         "sklearn/utils/_seq_dataset.pyx.tp",
@@ -60,10 +64,6 @@ def configuration(parent_package="", top_path=None):
 
     gen_from_templates(templates, top_path)
 
-    config.add_extension(
-        "_openmp_helpers", sources=["_openmp_helpers.pyx"], libraries=libraries
-    )
-
     config.add_extension(
         "_seq_dataset", sources=["_seq_dataset.pyx"], include_dirs=[numpy.get_include()]
     )

From 77fa38299b380337944f87209ae28092556dc588 Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 26 Jul 2021 14:14:54 +0200
Subject: [PATCH 18/39] Remove outdated argument of `gen_from_templates`
 function.

---
 sklearn/_build_utils/__init__.py | 2 +-
 sklearn/linear_model/setup.py    | 2 +-
 sklearn/utils/setup.py           | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/sklearn/_build_utils/__init__.py b/sklearn/_build_utils/__init__.py
index 670297dab3d22..be83b4c4d8baf 100644
--- a/sklearn/_build_utils/__init__.py
+++ b/sklearn/_build_utils/__init__.py
@@ -80,7 +80,7 @@ def cythonize_extensions(top_path, config):
     )
 
 
-def gen_from_templates(templates, top_path):
+def gen_from_templates(templates):
     """Generate cython files from a list of templates"""
     # Lazy import because cython is not a runtime dependency.
     from Cython import Tempita
diff --git a/sklearn/linear_model/setup.py b/sklearn/linear_model/setup.py
index cc5d277e13502..74d7d9e2b05ea 100644
--- a/sklearn/linear_model/setup.py
+++ b/sklearn/linear_model/setup.py
@@ -29,7 +29,7 @@ def configuration(parent_package="", top_path=None):
 
     # generate sag_fast from template
     templates = ["sklearn/linear_model/_sag_fast.pyx.tp"]
-    gen_from_templates(templates, top_path)
+    gen_from_templates(templates)
 
     config.add_extension(
         "_sag_fast", sources=["_sag_fast.pyx"], include_dirs=numpy.get_include()
diff --git a/sklearn/utils/setup.py b/sklearn/utils/setup.py
index 2b54918ac12ca..4df5ac39a6bfe 100644
--- a/sklearn/utils/setup.py
+++ b/sklearn/utils/setup.py
@@ -62,7 +62,7 @@ def configuration(parent_package="", top_path=None):
         "sklearn/linear_model/_sag_fast.pyx.tp",
     ]
 
-    gen_from_templates(templates, top_path)
+    gen_from_templates(templates)
 
     config.add_extension(
         "_seq_dataset", sources=["_seq_dataset.pyx"], include_dirs=[numpy.get_include()]

From d772d43389352ecf45019508c08ef4a8f6dc7b7e Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 26 Jul 2021 14:24:31 +0200
Subject: [PATCH 19/39] Parametrize `test_type_invariance`.

---
 sklearn/utils/tests/test_weight_vector.py | 26 ++++++++++++-----------
 1 file changed, 14 insertions(+), 12 deletions(-)

diff --git a/sklearn/utils/tests/test_weight_vector.py b/sklearn/utils/tests/test_weight_vector.py
index 21fe69a9e2e82..93ca628b8d520 100644
--- a/sklearn/utils/tests/test_weight_vector.py
+++ b/sklearn/utils/tests/test_weight_vector.py
@@ -3,21 +3,23 @@
 # License: BSD 3 clause
 
 import numpy as np
+import pytest
 from sklearn.utils._weight_vector import (
     WeightVector32,
     WeightVector64,
 )
 
 
-def test_type_invariance():
-    weights32 = np.random.rand(100).astype(np.float32)
-    average_weights32 = np.random.rand(100).astype(np.float32)
-    weight_vector32 = WeightVector32(weights32, average_weights32)
-    assert weight_vector32.w.dtype is np.dtype(np.float32)
-    assert weight_vector32.aw.dtype is np.dtype(np.float32)
-
-    weights64 = np.random.rand(100).astype(np.float64)
-    average_weights64 = np.random.rand(100).astype(np.float64)
-    weight_vector64 = WeightVector64(weights64, average_weights64)
-    assert weight_vector64.w.dtype is np.dtype(np.float64)
-    assert weight_vector64.aw.dtype is np.dtype(np.float64)
+@pytest.mark.parametrize(
+    "dtype, weight_vector_class",
+    [
+        (np.float32, WeightVector32),
+        (np.float64, WeightVector64),
+    ],
+)
+def test_type_invariance(dtype, weight_vector_class):
+    weights = np.random.rand(100).astype(dtype)
+    average_weights = np.random.rand(100).astype(dtype)
+    weight_vector = weight_vector_class(weights, average_weights)
+    assert weight_vector.w.dtype is np.dtype(dtype)
+    assert weight_vector.aw.dtype is np.dtype(dtype)

From 9456ba37980141c029a997468ab552c25a609f21 Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 26 Jul 2021 14:46:11 +0200
Subject: [PATCH 20/39] Add test for source files generation from templates.

---
 sklearn/utils/tests/test_utils.py | 23 +++++++++++++++++++++++
 1 file changed, 23 insertions(+)

diff --git a/sklearn/utils/tests/test_utils.py b/sklearn/utils/tests/test_utils.py
index 76d12abf10f6d..244de855c00bd 100644
--- a/sklearn/utils/tests/test_utils.py
+++ b/sklearn/utils/tests/test_utils.py
@@ -5,6 +5,9 @@
 import timeit
 
 import pytest
+import os
+import sklearn
+import pathlib
 import numpy as np
 import scipy.sparse as sp
 
@@ -31,6 +34,7 @@
 from sklearn.utils import _to_object_array
 from sklearn.utils._mocking import MockDataFrame
 from sklearn import config_context
+from sklearn._build_utils import gen_from_templates
 
 # toy array
 X_toy = np.arange(9).reshape((3, 3))
@@ -685,3 +689,22 @@ def test_to_object_array(sequence):
     assert isinstance(out, np.ndarray)
     assert out.dtype.kind == "O"
     assert out.ndim == 1
+
+
+@pytest.mark.parametrize("file_extension", ["pyx", "pxd"])
+def test_files_generation_from_templates(file_extension):
+    base_dir = base_dir = pathlib.Path(sklearn.__file__).parent.parent
+    template_filename = f"dummy.{file_extension}.tp"
+    template_file = base_dir / template_filename
+
+    f = open(template_file, "a")
+    f.close()
+
+    templates = [template_filename]
+    gen_from_templates(templates)
+
+    generated_file = base_dir / f"dummy.{file_extension}"
+    assert generated_file.exists()
+
+    template_file.unlink()
+    generated_file.unlink()

From 9a64435921f16f777d55b7ca0016e3264ea8944c Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 26 Jul 2021 14:57:48 +0200
Subject: [PATCH 21/39] Remove `sklearn/linear_model/_sag_fast.pyx.tp` from
 `sklearn/utils/setup.py`.

---
 sklearn/utils/setup.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/sklearn/utils/setup.py b/sklearn/utils/setup.py
index 4df5ac39a6bfe..cdb7b77ac0844 100644
--- a/sklearn/utils/setup.py
+++ b/sklearn/utils/setup.py
@@ -59,7 +59,6 @@ def configuration(parent_package="", top_path=None):
         "sklearn/utils/_seq_dataset.pxd.tp",
         "sklearn/utils/_weight_vector.pyx.tp",
         "sklearn/utils/_weight_vector.pxd.tp",
-        "sklearn/linear_model/_sag_fast.pyx.tp",
     ]
 
     gen_from_templates(templates)

From d39edd1d8546ee82416cd51ffb0416784e71f57e Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 26 Jul 2021 15:17:48 +0200
Subject: [PATCH 22/39] Remove duplicated `cdef` declaration in `WeightVector`
 class.

---
 sklearn/utils/_weight_vector.pyx.tp | 3 ---
 1 file changed, 3 deletions(-)

diff --git a/sklearn/utils/_weight_vector.pyx.tp b/sklearn/utils/_weight_vector.pyx.tp
index b77488b73a725..b36f475183c2a 100644
--- a/sklearn/utils/_weight_vector.pyx.tp
+++ b/sklearn/utils/_weight_vector.pyx.tp
@@ -66,9 +66,6 @@ cdef class WeightVector{{name}}(object):
         The squared norm of ``w``.
     """
 
-    cdef readonly np.ndarray w
-    cdef readonly np.ndarray aw
-
     def __cinit__(self,
                   np.ndarray[{{c_type}}, ndim=1, mode='c'] w,
                   np.ndarray[{{c_type}}, ndim=1, mode='c'] aw):

From da946c6ad437ac4d17fb267af4a73b5206b8e2a2 Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 26 Jul 2021 15:24:30 +0200
Subject: [PATCH 23/39] Remove `cython: language_level=3` from `weight_vector`
 template files.

---
 sklearn/utils/_weight_vector.pxd.tp | 2 --
 sklearn/utils/_weight_vector.pyx.tp | 1 -
 2 files changed, 3 deletions(-)

diff --git a/sklearn/utils/_weight_vector.pxd.tp b/sklearn/utils/_weight_vector.pxd.tp
index b70c8e8eccd52..d9a4bebf74fa5 100644
--- a/sklearn/utils/_weight_vector.pxd.tp
+++ b/sklearn/utils/_weight_vector.pxd.tp
@@ -18,8 +18,6 @@ dtypes = [('64', 'double'),
 
 }}
 
-# cython: language_level=3
-
 cimport numpy as np
 
 {{for name, c_type in dtypes}}
diff --git a/sklearn/utils/_weight_vector.pyx.tp b/sklearn/utils/_weight_vector.pyx.tp
index b36f475183c2a..b9d80799081e1 100644
--- a/sklearn/utils/_weight_vector.pyx.tp
+++ b/sklearn/utils/_weight_vector.pyx.tp
@@ -21,7 +21,6 @@ dtypes = [('64', 'double'),
 # cython: cdivision=True
 # cython: boundscheck=False
 # cython: wraparound=False
-# cython: language_level=3
 #
 # Author: Peter Prettenhofer <peter.prettenhofer@gmail.com>
 #         Lars Buitinck

From ea2470be1c6cf08a837744b14088b71c57f7d535 Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 26 Jul 2021 15:24:49 +0200
Subject: [PATCH 24/39] Remove useless constant variable in
 `test_cython_templating`.

---
 sklearn/utils/tests/test_cython_templating.py | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/sklearn/utils/tests/test_cython_templating.py b/sklearn/utils/tests/test_cython_templating.py
index 124045d84b08f..4cc5e6dae1fee 100644
--- a/sklearn/utils/tests/test_cython_templating.py
+++ b/sklearn/utils/tests/test_cython_templating.py
@@ -2,8 +2,6 @@
 import pytest
 import sklearn
 
-TEMPITA_EXTENSION = "tp"
-
 
 def test_files_generated_by_templates_are_git_ignored():
     gitignore_file = pathlib.Path(sklearn.__file__).parent.parent / ".gitignore"
@@ -14,7 +12,7 @@ def test_files_generated_by_templates_are_git_ignored():
     ignored_files = open(gitignore_file, "r").readlines()
     ignored_files = list(map(lambda line: line.strip("\n"), ignored_files))
 
-    for filename in base_dir.glob(f"**/*.{TEMPITA_EXTENSION}"):
+    for filename in base_dir.glob("**/*.tp"):
         filename = str(filename).split("scikit-learn/")[-1]
-        filename_wo_tempita_suffix = filename.strip(f".{TEMPITA_EXTENSION}")
+        filename_wo_tempita_suffix = filename.strip(".tp")
         assert filename_wo_tempita_suffix in ignored_files

From fc8a32d299a8f11ce03861f5c7b2eea8c5441c4f Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 2 Aug 2021 16:13:21 +0200
Subject: [PATCH 25/39] Remove unused import.

---
 sklearn/utils/tests/test_utils.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/sklearn/utils/tests/test_utils.py b/sklearn/utils/tests/test_utils.py
index 244de855c00bd..edb1deb6d2031 100644
--- a/sklearn/utils/tests/test_utils.py
+++ b/sklearn/utils/tests/test_utils.py
@@ -5,7 +5,6 @@
 import timeit
 
 import pytest
-import os
 import sklearn
 import pathlib
 import numpy as np

From 2794c77a20aea53d79d5f631167321fa5cbf6369 Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 2 Aug 2021 16:14:37 +0200
Subject: [PATCH 26/39] Fix
 `test_files_generated_by_templates_are_git_ignored`.

---
 sklearn/utils/tests/test_cython_templating.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/sklearn/utils/tests/test_cython_templating.py b/sklearn/utils/tests/test_cython_templating.py
index 4cc5e6dae1fee..47d054562b4cd 100644
--- a/sklearn/utils/tests/test_cython_templating.py
+++ b/sklearn/utils/tests/test_cython_templating.py
@@ -13,6 +13,6 @@ def test_files_generated_by_templates_are_git_ignored():
     ignored_files = list(map(lambda line: line.strip("\n"), ignored_files))
 
     for filename in base_dir.glob("**/*.tp"):
-        filename = str(filename).split("scikit-learn/")[-1]
-        filename_wo_tempita_suffix = filename.strip(".tp")
-        assert filename_wo_tempita_suffix in ignored_files
+        filename = filename.relative_to(base_dir.parent)
+        filename_wo_tempita_suffix = filename.with_suffix("")
+        assert str(filename_wo_tempita_suffix) in ignored_files

From 9452515501c1fb80e640ad9e609aad7544986a87 Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 2 Aug 2021 16:42:19 +0200
Subject: [PATCH 27/39] Revert "Add test for source files generation from
 templates."

This reverts commit 9456ba37980141c029a997468ab552c25a609f21.
---
 sklearn/utils/tests/test_utils.py | 22 ----------------------
 1 file changed, 22 deletions(-)

diff --git a/sklearn/utils/tests/test_utils.py b/sklearn/utils/tests/test_utils.py
index edb1deb6d2031..76d12abf10f6d 100644
--- a/sklearn/utils/tests/test_utils.py
+++ b/sklearn/utils/tests/test_utils.py
@@ -5,8 +5,6 @@
 import timeit
 
 import pytest
-import sklearn
-import pathlib
 import numpy as np
 import scipy.sparse as sp
 
@@ -33,7 +31,6 @@
 from sklearn.utils import _to_object_array
 from sklearn.utils._mocking import MockDataFrame
 from sklearn import config_context
-from sklearn._build_utils import gen_from_templates
 
 # toy array
 X_toy = np.arange(9).reshape((3, 3))
@@ -688,22 +685,3 @@ def test_to_object_array(sequence):
     assert isinstance(out, np.ndarray)
     assert out.dtype.kind == "O"
     assert out.ndim == 1
-
-
-@pytest.mark.parametrize("file_extension", ["pyx", "pxd"])
-def test_files_generation_from_templates(file_extension):
-    base_dir = base_dir = pathlib.Path(sklearn.__file__).parent.parent
-    template_filename = f"dummy.{file_extension}.tp"
-    template_file = base_dir / template_filename
-
-    f = open(template_file, "a")
-    f.close()
-
-    templates = [template_filename]
-    gen_from_templates(templates)
-
-    generated_file = base_dir / f"dummy.{file_extension}"
-    assert generated_file.exists()
-
-    template_file.unlink()
-    generated_file.unlink()

From 0d2af891080d1e23c7b0a54683dce3dcefd36bed Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 2 Aug 2021 16:43:56 +0200
Subject: [PATCH 28/39] Remove top file author.

---
 sklearn/utils/tests/test_weight_vector.py | 4 ----
 1 file changed, 4 deletions(-)

diff --git a/sklearn/utils/tests/test_weight_vector.py b/sklearn/utils/tests/test_weight_vector.py
index 93ca628b8d520..18308f086d003 100644
--- a/sklearn/utils/tests/test_weight_vector.py
+++ b/sklearn/utils/tests/test_weight_vector.py
@@ -1,7 +1,3 @@
-# Author: Mathis Batoul <batoulmathis@gmail.com>
-#
-# License: BSD 3 clause
-
 import numpy as np
 import pytest
 from sklearn.utils._weight_vector import (

From 68282bef81181c59578b0c025f31461c1a18ee94 Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Mon, 2 Aug 2021 17:23:53 +0200
Subject: [PATCH 29/39] Use typed-memoryview for `WeightVector` interface.

---
 sklearn/utils/_weight_vector.pxd.tp       |  4 ++--
 sklearn/utils/_weight_vector.pyx.tp       | 22 ++++++++++------------
 sklearn/utils/tests/test_weight_vector.py |  4 ++--
 3 files changed, 14 insertions(+), 16 deletions(-)

diff --git a/sklearn/utils/_weight_vector.pxd.tp b/sklearn/utils/_weight_vector.pxd.tp
index d9a4bebf74fa5..c947872bee026 100644
--- a/sklearn/utils/_weight_vector.pxd.tp
+++ b/sklearn/utils/_weight_vector.pxd.tp
@@ -27,8 +27,8 @@ cdef extern from "math.h":
 
 
 cdef class WeightVector{{name}}(object):
-    cdef readonly np.ndarray w
-    cdef readonly np.ndarray aw
+    cdef readonly {{c_type}}[::1] w
+    cdef readonly {{c_type}}[::1] aw
     cdef {{c_type}} *w_data_ptr
     cdef {{c_type}} *aw_data_ptr
     cdef {{c_type}} wscale
diff --git a/sklearn/utils/_weight_vector.pyx.tp b/sklearn/utils/_weight_vector.pyx.tp
index b9d80799081e1..a57ec6e9cd145 100644
--- a/sklearn/utils/_weight_vector.pyx.tp
+++ b/sklearn/utils/_weight_vector.pyx.tp
@@ -66,22 +66,21 @@ cdef class WeightVector{{name}}(object):
     """
 
     def __cinit__(self,
-                  np.ndarray[{{c_type}}, ndim=1, mode='c'] w,
-                  np.ndarray[{{c_type}}, ndim=1, mode='c'] aw):
-        cdef {{c_type}} *wdata = <{{c_type}} *>w.data
+                  {{c_type}}[::1] w,
+                  {{c_type}}[::1] aw):
 
         if w.shape[0] > INT_MAX:
             raise ValueError("More than %d features not supported; got %d."
                              % (INT_MAX, w.shape[0]))
         self.w = w
-        self.w_data_ptr = wdata
+        self.w_data_ptr = &w[0]
         self.wscale = 1.0
         self.n_features = w.shape[0]
-        self.sq_norm = _dot(w.shape[0], wdata, 1, wdata, 1)
+        self.sq_norm = _dot(self.n_features, self.w_data_ptr, 1, self.w_data_ptr, 1)
 
         self.aw = aw
         if self.aw is not None:
-            self.aw_data_ptr = <{{c_type}} *>aw.data
+            self.aw_data_ptr = &aw[0]
             self.average_a = 0.0
             self.average_b = 1.0
 
@@ -200,15 +199,14 @@ cdef class WeightVector{{name}}(object):
 
     cdef void reset_wscale(self) nogil:
         """Scales each coef of ``w`` by ``wscale`` and resets it to 1. """
-        if self.aw is not None:
-            _axpy(<int>self.aw.shape[0], self.average_a,
-                  <{{c_type}} *>self.w.data, 1, <{{c_type}} *>self.aw.data, 1)
-            _scal(<int>self.aw.shape[0], 1.0 / self.average_b,
-                  <{{c_type}} *>self.aw.data, 1)
+        if self.aw_data_ptr != NULL:
+            _axpy(self.n_features, self.average_a,
+                  self.w_data_ptr, 1, self.aw_data_ptr, 1)
+            _scal(self.n_features, 1.0 / self.average_b, self.aw_data_ptr, 1)
             self.average_a = 0.0
             self.average_b = 1.0
 
-        _scal(<int>self.w.shape[0], self.wscale, <{{c_type}} *>self.w.data, 1)
+        _scal(self.n_features, self.wscale, self.w_data_ptr, 1)
         self.wscale = 1.0
 
     cdef {{c_type}} norm(self) nogil:
diff --git a/sklearn/utils/tests/test_weight_vector.py b/sklearn/utils/tests/test_weight_vector.py
index 18308f086d003..fa83648ea3b72 100644
--- a/sklearn/utils/tests/test_weight_vector.py
+++ b/sklearn/utils/tests/test_weight_vector.py
@@ -17,5 +17,5 @@ def test_type_invariance(dtype, weight_vector_class):
     weights = np.random.rand(100).astype(dtype)
     average_weights = np.random.rand(100).astype(dtype)
     weight_vector = weight_vector_class(weights, average_weights)
-    assert weight_vector.w.dtype is np.dtype(dtype)
-    assert weight_vector.aw.dtype is np.dtype(dtype)
+    assert np.asarray(weight_vector.w).dtype is np.dtype(dtype)
+    assert np.asarray(weight_vector.aw).dtype is np.dtype(dtype)

From 1043fa091db0bf169218af8c43f8c4d913cee015 Mon Sep 17 00:00:00 2001
From: Mathis Batoul <batoulmathis@gmail.com>
Date: Wed, 4 Aug 2021 11:00:16 +0200
Subject: [PATCH 30/39] Pass class name argument to
 parametrize`test_weight_vector`.

Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>
---
 sklearn/utils/tests/test_weight_vector.py | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/sklearn/utils/tests/test_weight_vector.py b/sklearn/utils/tests/test_weight_vector.py
index fa83648ea3b72..3177c8bcaf2ee 100644
--- a/sklearn/utils/tests/test_weight_vector.py
+++ b/sklearn/utils/tests/test_weight_vector.py
@@ -7,15 +7,17 @@
 
 
 @pytest.mark.parametrize(
-    "dtype, weight_vector_class",
+    "dtype, WeightVector",
     [
         (np.float32, WeightVector32),
         (np.float64, WeightVector64),
     ],
 )
-def test_type_invariance(dtype, weight_vector_class):
+def test_type_invariance(dtype, WeightVector):
     weights = np.random.rand(100).astype(dtype)
     average_weights = np.random.rand(100).astype(dtype)
-    weight_vector = weight_vector_class(weights, average_weights)
+    
+    weight_vector = WeightVector(weights, average_weights)
+    
     assert np.asarray(weight_vector.w).dtype is np.dtype(dtype)
     assert np.asarray(weight_vector.aw).dtype is np.dtype(dtype)

From 1ad9ae3ef0324af0a5919f6fd47dcf625a3b5cca Mon Sep 17 00:00:00 2001
From: Mathis Batoul <batoulmathis@gmail.com>
Date: Wed, 4 Aug 2021 11:01:04 +0200
Subject: [PATCH 31/39] Add comment to `test_cython_templating`.

Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>
---
 sklearn/utils/tests/test_cython_templating.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/sklearn/utils/tests/test_cython_templating.py b/sklearn/utils/tests/test_cython_templating.py
index 47d054562b4cd..f39b3ab161fcc 100644
--- a/sklearn/utils/tests/test_cython_templating.py
+++ b/sklearn/utils/tests/test_cython_templating.py
@@ -14,5 +14,6 @@ def test_files_generated_by_templates_are_git_ignored():
 
     for filename in base_dir.glob("**/*.tp"):
         filename = filename.relative_to(base_dir.parent)
+        # From "path/to/template.p??.tp" to "path/to/template.p??" 
         filename_wo_tempita_suffix = filename.with_suffix("")
         assert str(filename_wo_tempita_suffix) in ignored_files

From a8d7cf96ef6da4c5c7946dc74c502d90b4fabf2f Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Wed, 4 Aug 2021 12:12:58 +0200
Subject: [PATCH 32/39] Add type to epsilon for comparison in
 `WeightVector#scale`.

---
 sklearn/utils/_weight_vector.pyx.tp | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/sklearn/utils/_weight_vector.pyx.tp b/sklearn/utils/_weight_vector.pyx.tp
index a57ec6e9cd145..4c28d19dad017 100644
--- a/sklearn/utils/_weight_vector.pyx.tp
+++ b/sklearn/utils/_weight_vector.pyx.tp
@@ -194,7 +194,8 @@ cdef class WeightVector{{name}}(object):
         small we call ``reset_swcale``."""
         self.wscale *= c
         self.sq_norm *= (c * c)
-        if self.wscale < 1e-9:
+        cdef {{c_type}} epsilon = 1e-9
+        if self.wscale < epsilon:
             self.reset_wscale()
 
     cdef void reset_wscale(self) nogil:

From ac353026032a07ca05f188e87890a259e7789971 Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Wed, 4 Aug 2021 12:18:24 +0200
Subject: [PATCH 33/39] Remove whitespaces.

---
 sklearn/utils/tests/test_cython_templating.py | 2 +-
 sklearn/utils/tests/test_weight_vector.py     | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/sklearn/utils/tests/test_cython_templating.py b/sklearn/utils/tests/test_cython_templating.py
index f39b3ab161fcc..06ad89135fb87 100644
--- a/sklearn/utils/tests/test_cython_templating.py
+++ b/sklearn/utils/tests/test_cython_templating.py
@@ -14,6 +14,6 @@ def test_files_generated_by_templates_are_git_ignored():
 
     for filename in base_dir.glob("**/*.tp"):
         filename = filename.relative_to(base_dir.parent)
-        # From "path/to/template.p??.tp" to "path/to/template.p??" 
+        # From "path/to/template.p??.tp" to "path/to/template.p??"
         filename_wo_tempita_suffix = filename.with_suffix("")
         assert str(filename_wo_tempita_suffix) in ignored_files
diff --git a/sklearn/utils/tests/test_weight_vector.py b/sklearn/utils/tests/test_weight_vector.py
index 3177c8bcaf2ee..350520e02fab8 100644
--- a/sklearn/utils/tests/test_weight_vector.py
+++ b/sklearn/utils/tests/test_weight_vector.py
@@ -16,8 +16,8 @@
 def test_type_invariance(dtype, WeightVector):
     weights = np.random.rand(100).astype(dtype)
     average_weights = np.random.rand(100).astype(dtype)
-    
+
     weight_vector = WeightVector(weights, average_weights)
-    
+
     assert np.asarray(weight_vector.w).dtype is np.dtype(dtype)
     assert np.asarray(weight_vector.aw).dtype is np.dtype(dtype)

From 0f4b057999ecbb67b35aeee88679d64c93d15b36 Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Thu, 5 Aug 2021 15:27:25 +0200
Subject: [PATCH 34/39] Rename Tempita variable `name` as `name_suffix` in
 `.tp` files.

---
 sklearn/linear_model/_sag_fast.pyx.tp | 74 +++++++++++++--------------
 sklearn/utils/_seq_dataset.pxd.tp     | 10 ++--
 sklearn/utils/_seq_dataset.pyx.tp     | 10 ++--
 sklearn/utils/_weight_vector.pxd.tp   |  6 +--
 sklearn/utils/_weight_vector.pyx.tp   |  6 +--
 5 files changed, 53 insertions(+), 53 deletions(-)

diff --git a/sklearn/linear_model/_sag_fast.pyx.tp b/sklearn/linear_model/_sag_fast.pyx.tp
index d9989f60aa23a..1a4f188a91fbc 100644
--- a/sklearn/linear_model/_sag_fast.pyx.tp
+++ b/sklearn/linear_model/_sag_fast.pyx.tp
@@ -19,7 +19,7 @@ Authors: Danny Sullivan <dbsullivan23@gmail.com>
 License: BSD 3 clause
 """
 
-# name, c_type
+# name_suffix, c_type
 dtypes = [('64', 'double', 'np.float64'),
           ('32', 'float', 'np.float32')]
 
@@ -57,17 +57,17 @@ from libc.stdio cimport printf
 np.import_array()
 
 
-{{for name, c_type, np_type in dtypes}}
+{{for name_suffix, c_type, np_type in dtypes}}
 
 cdef extern from "_sgd_fast_helpers.h":
-    bint skl_isfinite{{name}}({{c_type}}) nogil
+    bint skl_isfinite{{name_suffix}}({{c_type}}) nogil
 
 
 {{endfor}}
 
-{{for name, c_type, np_type in dtypes}}
+{{for name_suffix, c_type, np_type in dtypes}}
 
-cdef inline {{c_type}} fmax{{name}}({{c_type}} x, {{c_type}} y) nogil:
+cdef inline {{c_type}} fmax{{name_suffix}}({{c_type}} x, {{c_type}} y) nogil:
     if x > y:
         return x
     return y
@@ -75,9 +75,9 @@ cdef inline {{c_type}} fmax{{name}}({{c_type}} x, {{c_type}} y) nogil:
 {{endfor}}
 
 
-{{for name, c_type, np_type in dtypes}}
+{{for name_suffix, c_type, np_type in dtypes}}
 
-cdef {{c_type}} _logsumexp{{name}}({{c_type}}* arr, int n_classes) nogil:
+cdef {{c_type}} _logsumexp{{name_suffix}}({{c_type}}* arr, int n_classes) nogil:
     """Computes the sum of arr assuming arr is in the log domain.
 
     Returns log(sum(exp(arr))) while minimizing the possibility of
@@ -101,9 +101,9 @@ cdef {{c_type}} _logsumexp{{name}}({{c_type}}* arr, int n_classes) nogil:
 {{endfor}}
 
 
-{{for name, c_type, np_type in dtypes}}
+{{for name_suffix, c_type, np_type in dtypes}}
 
-cdef class MultinomialLogLoss{{name}}:
+cdef class MultinomialLogLoss{{name_suffix}}:
     cdef {{c_type}} _loss(self, {{c_type}}* prediction, {{c_type}} y, int n_classes,
                       {{c_type}} sample_weight) nogil:
         r"""Multinomial Logistic regression loss.
@@ -141,7 +141,7 @@ cdef class MultinomialLogLoss{{name}}:
         Bishop, C. M. (2006). Pattern recognition and machine learning.
         Springer. (Chapter 4.3.4)
         """
-        cdef {{c_type}} logsumexp_prediction = _logsumexp{{name}}(prediction, n_classes)
+        cdef {{c_type}} logsumexp_prediction = _logsumexp{{name_suffix}}(prediction, n_classes)
         cdef {{c_type}} loss
 
         # y is the indice of the correct class of current sample.
@@ -187,7 +187,7 @@ cdef class MultinomialLogLoss{{name}}:
         Bishop, C. M. (2006). Pattern recognition and machine learning.
         Springer. (Chapter 4.3.4)
         """
-        cdef {{c_type}} logsumexp_prediction = _logsumexp{{name}}(prediction, n_classes)
+        cdef {{c_type}} logsumexp_prediction = _logsumexp{{name_suffix}}(prediction, n_classes)
         cdef int class_ind
 
         for class_ind in range(n_classes):
@@ -201,21 +201,21 @@ cdef class MultinomialLogLoss{{name}}:
             gradient_ptr[class_ind] *= sample_weight
 
     def __reduce__(self):
-        return MultinomialLogLoss{{name}}, ()
+        return MultinomialLogLoss{{name_suffix}}, ()
 
 {{endfor}}
 
-{{for name, c_type, np_type in dtypes}}
+{{for name_suffix, c_type, np_type in dtypes}}
 
-cdef inline {{c_type}} _soft_thresholding{{name}}({{c_type}} x, {{c_type}} shrinkage) nogil:
-    return fmax{{name}}(x - shrinkage, 0) - fmax{{name}}(- x - shrinkage, 0)
+cdef inline {{c_type}} _soft_thresholding{{name_suffix}}({{c_type}} x, {{c_type}} shrinkage) nogil:
+    return fmax{{name_suffix}}(x - shrinkage, 0) - fmax{{name_suffix}}(- x - shrinkage, 0)
 
 {{endfor}}
 
 
-{{for name, c_type, np_type in dtypes}}
+{{for name_suffix, c_type, np_type in dtypes}}
 
-def sag{{name}}(SequentialDataset{{name}} dataset,
+def sag{{name_suffix}}(SequentialDataset{{name_suffix}} dataset,
         np.ndarray[{{c_type}}, ndim=2, mode='c'] weights_array,
         np.ndarray[{{c_type}}, ndim=1, mode='c'] intercept_array,
         int n_samples,
@@ -356,11 +356,11 @@ def sag{{name}}(SequentialDataset{{name}} dataset,
     # Wether the loss function is multinomial
     cdef bint multinomial = False
     # Multinomial loss function
-    cdef MultinomialLogLoss{{name}} multiloss
+    cdef MultinomialLogLoss{{name_suffix}} multiloss
 
     if loss_function == "multinomial":
         multinomial = True
-        multiloss = MultinomialLogLoss{{name}}()
+        multiloss = MultinomialLogLoss{{name_suffix}}()
     elif loss_function == "log":
         loss = Log()
     elif loss_function == "squared":
@@ -395,7 +395,7 @@ def sag{{name}}(SequentialDataset{{name}} dataset,
 
                 # make the weight updates
                 if sample_itr > 0:
-                   status = lagged_update{{name}}(weights, wscale, xnnz,
+                   status = lagged_update{{name_suffix}}(weights, wscale, xnnz,
                                                   n_samples, n_classes,
                                                   sample_itr,
                                                   cumulative_sums,
@@ -410,7 +410,7 @@ def sag{{name}}(SequentialDataset{{name}} dataset,
                        break
 
                 # find the current prediction
-                predict_sample{{name}}(x_data_ptr, x_ind_ptr, xnnz, weights, wscale,
+                predict_sample{{name_suffix}}(x_data_ptr, x_ind_ptr, xnnz, weights, wscale,
                                        intercept, prediction, n_classes)
 
                 # compute the gradient for this sample, given the prediction
@@ -455,7 +455,7 @@ def sag{{name}}(SequentialDataset{{name}} dataset,
                                  num_seen * intercept_decay)
 
                         # check to see that the intercept is not inf or NaN
-                        if not skl_isfinite{{name}}(intercept[class_ind]):
+                        if not skl_isfinite{{name_suffix}}(intercept[class_ind]):
                             status = -1
                             break
                     # Break from the n_samples outer loop if an error happened
@@ -484,7 +484,7 @@ def sag{{name}}(SequentialDataset{{name}} dataset,
                     if verbose:
                         with gil:
                             print("rescaling...")
-                    status = scale_weights{{name}}(
+                    status = scale_weights{{name_suffix}}(
                         weights, &wscale, n_features, n_samples, n_classes,
                         sample_itr, cumulative_sums,
                         cumulative_sums_prox,
@@ -500,7 +500,7 @@ def sag{{name}}(SequentialDataset{{name}} dataset,
 
             # we scale the weights every n_samples iterations and reset the
             # just-in-time update system for numerical stability.
-            status = scale_weights{{name}}(weights, &wscale, n_features,
+            status = scale_weights{{name_suffix}}(weights, &wscale, n_features,
                                            n_samples,
                                            n_classes, n_samples - 1,
                                            cumulative_sums,
@@ -514,8 +514,8 @@ def sag{{name}}(SequentialDataset{{name}} dataset,
             max_change = 0.0
             max_weight = 0.0
             for idx in range(n_features * n_classes):
-                max_weight = fmax{{name}}(max_weight, fabs(weights[idx]))
-                max_change = fmax{{name}}(max_change,
+                max_weight = fmax{{name_suffix}}(max_weight, fabs(weights[idx]))
+                max_change = fmax{{name_suffix}}(max_change,
                                   fabs(weights[idx] -
                                        previous_weights[idx]))
                 previous_weights[idx] = weights[idx]
@@ -549,9 +549,9 @@ def sag{{name}}(SequentialDataset{{name}} dataset,
 {{endfor}}
 
 
-{{for name, c_type, np_type in dtypes}}
+{{for name_suffix, c_type, np_type in dtypes}}
 
-cdef int scale_weights{{name}}({{c_type}}* weights, {{c_type}}* wscale,
+cdef int scale_weights{{name_suffix}}({{c_type}}* weights, {{c_type}}* wscale,
                                int n_features,
                                int n_samples, int n_classes, int sample_itr,
                                {{c_type}}* cumulative_sums,
@@ -570,7 +570,7 @@ cdef int scale_weights{{name}}({{c_type}}* weights, {{c_type}}* wscale,
     """
 
     cdef int status
-    status = lagged_update{{name}}(weights, wscale[0], n_features,
+    status = lagged_update{{name_suffix}}(weights, wscale[0], n_features,
                                    n_samples, n_classes, sample_itr + 1,
                                    cumulative_sums,
                                    cumulative_sums_prox,
@@ -588,9 +588,9 @@ cdef int scale_weights{{name}}({{c_type}}* weights, {{c_type}}* wscale,
 {{endfor}}
 
 
-{{for name, c_type, np_type in dtypes}}
+{{for name_suffix, c_type, np_type in dtypes}}
 
-cdef int lagged_update{{name}}({{c_type}}* weights, {{c_type}} wscale, int xnnz,
+cdef int lagged_update{{name_suffix}}({{c_type}}* weights, {{c_type}} wscale, int xnnz,
                                int n_samples, int n_classes, int sample_itr,
                                {{c_type}}* cumulative_sums,
                                {{c_type}}* cumulative_sums_prox,
@@ -626,7 +626,7 @@ cdef int lagged_update{{name}}({{c_type}}* weights, {{c_type}} wscale, int xnnz,
                 weights[idx] -= cum_sum * sum_gradient[idx]
                 if reset:
                     weights[idx] *= wscale
-                    if not skl_isfinite{{name}}(weights[idx]):
+                    if not skl_isfinite{{name_suffix}}(weights[idx]):
                         # returning here does not require the gil as the return
                         # type is a C integer
                         return -1
@@ -639,7 +639,7 @@ cdef int lagged_update{{name}}({{c_type}}* weights, {{c_type}} wscale, int xnnz,
                     # efficient than unrolling all the lagged updates.
                     # Idea taken from scikit-learn-contrib/lightning.
                     weights[idx] -= cum_sum * sum_gradient[idx]
-                    weights[idx] = _soft_thresholding{{name}}(weights[idx],
+                    weights[idx] = _soft_thresholding{{name_suffix}}(weights[idx],
                                                       cum_sum_prox)
                 else:
                     last_update_ind = feature_hist[feature_ind]
@@ -656,13 +656,13 @@ cdef int lagged_update{{name}}({{c_type}}* weights, {{c_type}} wscale, int xnnz,
                             grad_step = cumulative_sums[lagged_ind]
                             prox_step = cumulative_sums_prox[lagged_ind]
                         weights[idx] -= sum_gradient[idx] * grad_step
-                        weights[idx] = _soft_thresholding{{name}}(weights[idx],
+                        weights[idx] = _soft_thresholding{{name_suffix}}(weights[idx],
                                                           prox_step)
 
                 if reset:
                     weights[idx] *= wscale
                     # check to see that the weight is not inf or NaN
-                    if not skl_isfinite{{name}}(weights[idx]):
+                    if not skl_isfinite{{name_suffix}}(weights[idx]):
                         return -1
         if reset:
             feature_hist[feature_ind] = sample_itr % n_samples
@@ -679,9 +679,9 @@ cdef int lagged_update{{name}}({{c_type}}* weights, {{c_type}} wscale, int xnnz,
 {{endfor}}
 
 
-{{for name, c_type, np_type in dtypes}}
+{{for name_suffix, c_type, np_type in dtypes}}
 
-cdef void predict_sample{{name}}({{c_type}}* x_data_ptr, int* x_ind_ptr, int xnnz,
+cdef void predict_sample{{name_suffix}}({{c_type}}* x_data_ptr, int* x_ind_ptr, int xnnz,
                                  {{c_type}}* w_data_ptr, {{c_type}} wscale,
                                  {{c_type}}* intercept, {{c_type}}* prediction,
                                  int n_classes) nogil:
diff --git a/sklearn/utils/_seq_dataset.pxd.tp b/sklearn/utils/_seq_dataset.pxd.tp
index 9e4237fc0f51a..428f44a2c0358 100644
--- a/sklearn/utils/_seq_dataset.pxd.tp
+++ b/sklearn/utils/_seq_dataset.pxd.tp
@@ -12,12 +12,12 @@ Each class is duplicated for all dtypes (float and double). The keywords
 between double braces are substituted in setup.py.
 """
 
-# name, c_type
+# name_suffix, c_type
 dtypes = [('64', 'double'),
           ('32', 'float')]
 
 }}
-{{for name, c_type in dtypes}}
+{{for name_suffix, c_type in dtypes}}
 
 #------------------------------------------------------------------------------
 
@@ -32,7 +32,7 @@ cimport numpy as np
 # iterators over the rows of a matrix X and corresponding target values y.
 
 
-cdef class SequentialDataset{{name}}:
+cdef class SequentialDataset{{name_suffix}}:
     cdef int current_index
     cdef np.ndarray index
     cdef int *index_data_ptr
@@ -52,7 +52,7 @@ cdef class SequentialDataset{{name}}:
                     int *nnz, {{c_type}} *y, {{c_type}} *sample_weight) nogil
 
 
-cdef class ArrayDataset{{name}}(SequentialDataset{{name}}):
+cdef class ArrayDataset{{name_suffix}}(SequentialDataset{{name_suffix}}):
     cdef np.ndarray X
     cdef np.ndarray Y
     cdef np.ndarray sample_weights
@@ -65,7 +65,7 @@ cdef class ArrayDataset{{name}}(SequentialDataset{{name}}):
     cdef {{c_type}} *sample_weight_data
 
 
-cdef class CSRDataset{{name}}(SequentialDataset{{name}}):
+cdef class CSRDataset{{name_suffix}}(SequentialDataset{{name_suffix}}):
     cdef np.ndarray X_data
     cdef np.ndarray X_indptr
     cdef np.ndarray X_indices
diff --git a/sklearn/utils/_seq_dataset.pyx.tp b/sklearn/utils/_seq_dataset.pyx.tp
index a5173fb60c0da..8bc901194a24e 100644
--- a/sklearn/utils/_seq_dataset.pyx.tp
+++ b/sklearn/utils/_seq_dataset.pyx.tp
@@ -20,12 +20,12 @@ Author: Peter Prettenhofer <peter.prettenhofer@gmail.com>
 License: BSD 3 clause
 """
 
-# name, c_type, np_type
+# name_suffix, c_type, np_type
 dtypes = [('64', 'double', 'np.float64'),
           ('32', 'float', 'np.float32')]
 
 }}
-{{for name, c_type, np_type in dtypes}}
+{{for name_suffix, c_type, np_type in dtypes}}
 
 #------------------------------------------------------------------------------
 
@@ -43,7 +43,7 @@ np.import_array()
 
 from ._random cimport our_rand_r
 
-cdef class SequentialDataset{{name}}:
+cdef class SequentialDataset{{name_suffix}}:
     """Base class for datasets with sequential data access.
 
     SequentialDataset is used to iterate over the rows of a matrix X and
@@ -215,7 +215,7 @@ cdef class SequentialDataset{{name}}:
         return (x_data, x_indices, x_indptr), y, sample_weight, sample_idx
 
 
-cdef class ArrayDataset{{name}}(SequentialDataset{{name}}):
+cdef class ArrayDataset{{name_suffix}}(SequentialDataset{{name_suffix}}):
     """Dataset backed by a two-dimensional numpy array.
 
     The dtype of the numpy array is expected to be ``{{np_type}}`` ({{c_type}})
@@ -284,7 +284,7 @@ cdef class ArrayDataset{{name}}(SequentialDataset{{name}}):
         sample_weight[0] = self.sample_weight_data[sample_idx]
 
 
-cdef class CSRDataset{{name}}(SequentialDataset{{name}}):
+cdef class CSRDataset{{name_suffix}}(SequentialDataset{{name_suffix}}):
     """A ``SequentialDataset`` backed by a scipy sparse CSR matrix. """
 
     def __cinit__(self, np.ndarray[{{c_type}}, ndim=1, mode='c'] X_data,
diff --git a/sklearn/utils/_weight_vector.pxd.tp b/sklearn/utils/_weight_vector.pxd.tp
index c947872bee026..6fd3af5c5482e 100644
--- a/sklearn/utils/_weight_vector.pxd.tp
+++ b/sklearn/utils/_weight_vector.pxd.tp
@@ -12,7 +12,7 @@ Each class is duplicated for all dtypes (float and double). The keywords
 between double braces are substituted in setup.py.
 """
 
-# name, c_type
+# name_suffix, c_type
 dtypes = [('64', 'double'),
           ('32', 'float')]
 
@@ -20,13 +20,13 @@ dtypes = [('64', 'double'),
 
 cimport numpy as np
 
-{{for name, c_type in dtypes}}
+{{for name_suffix, c_type in dtypes}}
 
 cdef extern from "math.h":
     cdef extern {{c_type}} sqrt({{c_type}} x)
 
 
-cdef class WeightVector{{name}}(object):
+cdef class WeightVector{{name_suffix}}(object):
     cdef readonly {{c_type}}[::1] w
     cdef readonly {{c_type}}[::1] aw
     cdef {{c_type}} *w_data_ptr
diff --git a/sklearn/utils/_weight_vector.pyx.tp b/sklearn/utils/_weight_vector.pyx.tp
index 4c28d19dad017..aa3db0b44910b 100644
--- a/sklearn/utils/_weight_vector.pyx.tp
+++ b/sklearn/utils/_weight_vector.pyx.tp
@@ -12,7 +12,7 @@ Each class is duplicated for all dtypes (float and double). The keywords
 between double braces are substituted in setup.py.
 """
 
-# name, c_type
+# name_suffix, c_type
 dtypes = [('64', 'double'),
           ('32', 'float')]
 
@@ -39,9 +39,9 @@ from ._cython_blas cimport _dot, _scal, _axpy
 
 np.import_array()
 
-{{for name, c_type in dtypes}}
+{{for name_suffix, c_type in dtypes}}
 
-cdef class WeightVector{{name}}(object):
+cdef class WeightVector{{name_suffix}}(object):
     """Dense vector represented by a scalar and a numpy array.
 
     The class provides methods to ``add`` a sparse vector

From 393f835030cbb0048f7ee6e0dac796b14c3a6780 Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Thu, 5 Aug 2021 15:46:11 +0200
Subject: [PATCH 35/39] Set `reset_wscale_threshold` at `1e-6` for float32 and
 `1e-09` for float64.

---
 sklearn/utils/_weight_vector.pyx.tp | 14 ++++++++------
 1 file changed, 8 insertions(+), 6 deletions(-)

diff --git a/sklearn/utils/_weight_vector.pyx.tp b/sklearn/utils/_weight_vector.pyx.tp
index aa3db0b44910b..b942cc45e1c99 100644
--- a/sklearn/utils/_weight_vector.pyx.tp
+++ b/sklearn/utils/_weight_vector.pyx.tp
@@ -12,9 +12,9 @@ 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', 'double'),
-          ('32', 'float')]
+# name_suffix, c_type, reset_wscale_threshold
+dtypes = [('64', 'double', 1e-9),
+          ('32', 'float', 1e-6)]
 
 }}
 
@@ -39,7 +39,7 @@ from ._cython_blas cimport _dot, _scal, _axpy
 
 np.import_array()
 
-{{for name_suffix, c_type in dtypes}}
+{{for name_suffix, c_type, reset_wscale_threshold in dtypes}}
 
 cdef class WeightVector{{name_suffix}}(object):
     """Dense vector represented by a scalar and a numpy array.
@@ -194,8 +194,10 @@ cdef class WeightVector{{name_suffix}}(object):
         small we call ``reset_swcale``."""
         self.wscale *= c
         self.sq_norm *= (c * c)
-        cdef {{c_type}} epsilon = 1e-9
-        if self.wscale < epsilon:
+
+        cdef {{c_type}} threshold = {{reset_wscale_threshold}}
+
+        if self.wscale < threshold:
             self.reset_wscale()
 
     cdef void reset_wscale(self) nogil:

From 3c56e7ca699769f191680511a42b171598ac940c Mon Sep 17 00:00:00 2001
From: mbatoul <batoulmathis@gmail.com>
Date: Fri, 6 Aug 2021 12:19:21 +0200
Subject: [PATCH 36/39] Update `setup.cfg` file.

---
 setup.cfg | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/setup.cfg b/setup.cfg
index 8ee90da7436c0..34d462f506f7f 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -65,6 +65,8 @@ allow_redefinition = True
 [check-manifest]
 # ignore files missing in VCS
 ignore =
-    sklearn/linear_model/_sag_fast.pyx
-    sklearn/utils/_seq_dataset.pxd
     sklearn/utils/_seq_dataset.pyx
+    sklearn/utils/_seq_dataset.pxd
+    sklearn/utils/_weight_vector.pyx
+    sklearn/utils/_weight_vector.pxd
+    sklearn/linear_model/_sag_fast.pyx

From d52c6767fdb3b2626c829ec3666b47587222c77c Mon Sep 17 00:00:00 2001
From: Mathis Batoul <batoulmathis@gmail.com>
Date: Fri, 6 Aug 2021 14:47:25 +0200
Subject: [PATCH 37/39] Keep alphanumerical order of files in `setup.cfg`.

Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>
---
 setup.cfg | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.cfg b/setup.cfg
index 34d462f506f7f..7d1ca5c07cc33 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -65,8 +65,8 @@ allow_redefinition = True
 [check-manifest]
 # ignore files missing in VCS
 ignore =
+    sklearn/linear_model/_sag_fast.pyx
     sklearn/utils/_seq_dataset.pyx
     sklearn/utils/_seq_dataset.pxd
     sklearn/utils/_weight_vector.pyx
     sklearn/utils/_weight_vector.pxd
-    sklearn/linear_model/_sag_fast.pyx

From 033f3f4b5ebda3fd117604c5a2ae283f3912cf90 Mon Sep 17 00:00:00 2001
From: Mathis Batoul <batoulmathis@gmail.com>
Date: Mon, 9 Aug 2021 21:08:39 +0200
Subject: [PATCH 38/39] Stop storing `reset_wscale_threshold` in a variable.

Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>
---
 sklearn/utils/_weight_vector.pyx.tp | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/sklearn/utils/_weight_vector.pyx.tp b/sklearn/utils/_weight_vector.pyx.tp
index b942cc45e1c99..a5bda689ae247 100644
--- a/sklearn/utils/_weight_vector.pyx.tp
+++ b/sklearn/utils/_weight_vector.pyx.tp
@@ -195,9 +195,7 @@ cdef class WeightVector{{name_suffix}}(object):
         self.wscale *= c
         self.sq_norm *= (c * c)
 
-        cdef {{c_type}} threshold = {{reset_wscale_threshold}}
-
-        if self.wscale < threshold:
+        if self.wscale < {{reset_wscale_threshold}}:
             self.reset_wscale()
 
     cdef void reset_wscale(self) nogil:

From 6abf315074d0b030d87c88d7793d3b39aecab2b8 Mon Sep 17 00:00:00 2001
From: Mathis Batoul <batoulmathis@gmail.com>
Date: Mon, 9 Aug 2021 21:11:47 +0200
Subject: [PATCH 39/39] Improve docstrings.

Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>
---
 sklearn/linear_model/_sag_fast.pyx.tp         | 2 +-
 sklearn/utils/_weight_vector.pxd.tp           | 6 +++---
 sklearn/utils/_weight_vector.pyx.tp           | 2 +-
 sklearn/utils/tests/test_cython_templating.py | 1 +
 sklearn/utils/tests/test_weight_vector.py     | 1 +
 5 files changed, 7 insertions(+), 5 deletions(-)

diff --git a/sklearn/linear_model/_sag_fast.pyx.tp b/sklearn/linear_model/_sag_fast.pyx.tp
index 1a4f188a91fbc..6ca141fe99305 100644
--- a/sklearn/linear_model/_sag_fast.pyx.tp
+++ b/sklearn/linear_model/_sag_fast.pyx.tp
@@ -19,7 +19,7 @@ Authors: Danny Sullivan <dbsullivan23@gmail.com>
 License: BSD 3 clause
 """
 
-# name_suffix, c_type
+# name_suffix, c_type, np_type
 dtypes = [('64', 'double', 'np.float64'),
           ('32', 'float', 'np.float32')]
 
diff --git a/sklearn/utils/_weight_vector.pxd.tp b/sklearn/utils/_weight_vector.pxd.tp
index 6fd3af5c5482e..8b0fc234713fb 100644
--- a/sklearn/utils/_weight_vector.pxd.tp
+++ b/sklearn/utils/_weight_vector.pxd.tp
@@ -1,7 +1,7 @@
 {{py:
 
 """
-Efficient (dense) parameter vector implementation for linear models. 
+Efficient (dense) parameter vector implementation for linear models.
 
 Template file for easily generate fused types consistent code using Tempita
 (https://github.com/cython/cython/blob/master/Cython/Tempita/_tempita.py).
@@ -37,9 +37,9 @@ cdef class WeightVector{{name_suffix}}(object):
     cdef int n_features
     cdef {{c_type}} sq_norm
 
-    cdef void add(self,  {{c_type}} *x_data_ptr, int *x_ind_ptr,
+    cdef void add(self, {{c_type}} *x_data_ptr, int *x_ind_ptr,
                   int xnnz, {{c_type}} c) nogil
-    cdef void add_average(self,  {{c_type}} *x_data_ptr, int *x_ind_ptr,
+    cdef void add_average(self, {{c_type}} *x_data_ptr, int *x_ind_ptr,
                           int xnnz, {{c_type}} c, {{c_type}} num_iter) nogil
     cdef {{c_type}} dot(self, {{c_type}} *x_data_ptr, int *x_ind_ptr,
                     int xnnz) nogil
diff --git a/sklearn/utils/_weight_vector.pyx.tp b/sklearn/utils/_weight_vector.pyx.tp
index a5bda689ae247..0e8ec45121438 100644
--- a/sklearn/utils/_weight_vector.pyx.tp
+++ b/sklearn/utils/_weight_vector.pyx.tp
@@ -1,7 +1,7 @@
 {{py:
 
 """
-Efficient (dense) parameter vector implementation for linear models. 
+Efficient (dense) parameter vector implementation for linear models.
 
 Template file for easily generate fused types consistent code using Tempita
 (https://github.com/cython/cython/blob/master/Cython/Tempita/_tempita.py).
diff --git a/sklearn/utils/tests/test_cython_templating.py b/sklearn/utils/tests/test_cython_templating.py
index 06ad89135fb87..572d1db523cf8 100644
--- a/sklearn/utils/tests/test_cython_templating.py
+++ b/sklearn/utils/tests/test_cython_templating.py
@@ -4,6 +4,7 @@
 
 
 def test_files_generated_by_templates_are_git_ignored():
+    """Check the consistence of the files generated from template files."""
     gitignore_file = pathlib.Path(sklearn.__file__).parent.parent / ".gitignore"
     if not gitignore_file.exists():
         pytest.skip("Tests are not run from the source folder")
diff --git a/sklearn/utils/tests/test_weight_vector.py b/sklearn/utils/tests/test_weight_vector.py
index 350520e02fab8..627d46d1fda06 100644
--- a/sklearn/utils/tests/test_weight_vector.py
+++ b/sklearn/utils/tests/test_weight_vector.py
@@ -14,6 +14,7 @@
     ],
 )
 def test_type_invariance(dtype, WeightVector):
+    """Check the `dtype` consistency of `WeightVector`."""
     weights = np.random.rand(100).astype(dtype)
     average_weights = np.random.rand(100).astype(dtype)