Add new dependences versions for develop (backport #914) (#958)

* Add new dependences versions for develop (support python 3.10) (#914)

(cherry picked from commit 7ab09b6)

# Conflicts:
#	requirements-dev.txt

* resolve conflicts

Co-authored-by: Pavel Yakovlev <pavel.yakovlev@intel.com>

generator/format.py

@@ -163,7 +163,7 @@ def __init__(self, name, typ, const, dflt, inpt, algo, doc):
  # they are passed as (ptr, dim1, dim2)
  if typ_cy == 'data_or_file':
  decl_c = "double* {0}_p, size_t {0}_nrows,"\
- " size_t {0}_ncols, ssize_t {0}_layout".format(d4pname)
+ " size_t {0}_ncols, Py_ssize_t {0}_layout".format(d4pname)
  arg_c = "data_or_file({0}_p, {0}_ncols,"\
  " {0}_nrows, {0}_layout)".format(d4pname)
  # default values (see above pydefaults)

requirements-dev.txt

@@ -1,6 +1,8 @@
-Cython==0.29.24
-Jinja2==3.0.2
+Cython==0.29.24 ; python_version <= '3.9'
+Cython==0.29.25 ; python_version >= '3.10'
+Jinja2==3.0.3
 numpy==1.19.2 ; python_version <= '3.8'
-numpy==1.19.3 ; python_version >= '3.9'
+numpy==1.19.3 ; python_version == '3.9'
+numpy==1.21.3 ; python_version >= '3.10'
 pybind11==2.8.0
 cmake==3.21.3

src/daal4py.h

@@ -171,7 +171,7 @@ struct data_or_file
  mutable daal::data_management::NumericTablePtr table;
  std::string file;
  template<typename T>
- inline data_or_file(T * ptr, size_t ncols, size_t nrows, ssize_t layout)
+ inline data_or_file(T * ptr, size_t ncols, size_t nrows, Py_ssize_t layout)
  : table(), file()
  {
  if(layout > 0) throw std::invalid_argument("Supporting only homogeneous, contiguous arrays.");

src/gettree.pyx

@@ -31,12 +31,12 @@ cdef extern from "daal4py.h":
 
 cdef extern from "tree_visitor.h":
  cdef struct skl_tree_node:
- ssize_t left_child
- ssize_t right_child
- ssize_t feature
+ Py_ssize_t left_child
+ Py_ssize_t right_child
+ Py_ssize_t feature
  double threshold
  double impurity
- ssize_t n_node_samples
+ Py_ssize_t n_node_samples
  double weighted_n_node_samples
 
  cdef struct TreeState:

src/tree_visitor.h

@@ -29,12 +29,12 @@
 // cython will convert this struct into an numpy structured array
 // This is the layout that sklearn expects for its tree traversal mechanics
 struct skl_tree_node {
- ssize_t left_child;
- ssize_t right_child;
- ssize_t feature;
+ Py_ssize_t left_child;
+ Py_ssize_t right_child;
+ Py_ssize_t feature;
  double threshold;
  double impurity;
- ssize_t n_node_samples;
+ Py_ssize_t n_node_samples;
  double weighted_n_node_samples;
 
  skl_tree_node()
@@ -128,7 +128,7 @@ class toSKLearnTreeObjectVisitor : public TNVT<M>::visitor_type, public TreeStat
 
  size_t node_id;
  size_t max_n_classes;
- std::vector<ssize_t> parents;
+ std::vector<Py_ssize_t> parents;
 };
 
 // This is the function for getting the tree state from a forest which we use in cython
@@ -199,7 +199,7 @@ bool NodeDepthCountNodeVisitor<M>::onSplitNode(const typename TNVT<M>::split_des
 template<typename M>
 toSKLearnTreeObjectVisitor<M>::toSKLearnTreeObjectVisitor(size_t _depth, size_t _n_nodes, size_t _n_leafs, size_t _max_n_classes)
  : node_id(0),
- parents(arange<ssize_t>(-1, _depth-1))
+ parents(arange<Py_ssize_t>(-1, _depth-1))
 {
  max_n_classes = _max_n_classes;
  node_count = _n_nodes;
@@ -216,7 +216,7 @@ bool toSKLearnTreeObjectVisitor<M>::onSplitNode(const typename TNVT<M>::split_de
 {
  if(desc.level > 0) {
  // has parents
- ssize_t parent = parents[desc.level - 1];
+ Py_ssize_t parent = parents[desc.level - 1];
  if(node_ar[parent].left_child > 0) {
  assert(node_ar[node_id].right_child < 0);
  node_ar[parent].right_child = node_id;
@@ -254,7 +254,7 @@ template<typename M>
 bool toSKLearnTreeObjectVisitor<M>::_onLeafNode(const daal::algorithms::tree_utils::NodeDescriptor &desc)
 {
  if(desc.level) {
- ssize_t parent = parents[desc.level - 1];
+ Py_ssize_t parent = parents[desc.level - 1];
  if(node_ar[parent].left_child > 0) {
  assert(node_ar[node_id].right_child < 0);
  node_ar[parent].right_child = node_id;