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add python 3.13 (#136)
* py313 * fix ruff * update python version * update pybind11 * fix import issues * fix backprop * lint * fix precision
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11 files changed

+136
-31
lines changed

11 files changed

+136
-31
lines changed

‎CHANGELOGS.rst

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Original file line numberDiff line numberDiff line change
@@ -2,6 +2,11 @@
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Change Logs
33
===========
44

5+
0.5.2
6+
=====
7+
8+
* :pr:`136`: adds Python 3.13 to CI, updates the package to support scikit-learn==1.7.1
9+
510
0.5.1
611
=====
712

‎_cmake/externals/FindLocalPyBind11.cmake

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@@ -8,7 +8,7 @@
88
# pybind11
99
#
1010

11-
set(pybind11_TAG "v2.10.4")
11+
set(pybind11_TAG "v2.13.5")
1212

1313
include(FetchContent)
1414
FetchContent_Declare(
@@ -19,6 +19,8 @@ FetchContent_Declare(
1919
FetchContent_GetProperties(pybind11)
2020
if(NOT pybind11_POPULATED)
2121
FetchContent_Populate(pybind11)
22+
message(STATUS "pybind11_SOURCE_DIR=${pybind11_SOURCE_DIR}")
23+
message(STATUS "pybind11_BINARY_DIR=${pybind11_BINARY_DIR}")
2224
add_subdirectory(${pybind11_SOURCE_DIR} ${pybind11_BINARY_DIR})
2325
else()
2426
message(FATAL_ERROR "Pybind11 was not found.")

‎_doc/index.rst

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@@ -98,5 +98,5 @@ Source are available at `sdpython/mlinsights <https://github.com/sdpython/mlinsi
9898
Older versions
9999
++++++++++++++
100100

101+
* `0.5.2 <../v0.5.1/index.html>`_
101102
* `0.5.1 <../v0.5.1/index.html>`_
102-
* `0.5.0 <../v0.5.0/index.html>`_

‎_unittests/ut_sklapi/test_sklearn_convert.py

Lines changed: 1 addition & 1 deletion
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@@ -58,7 +58,7 @@ def test_pipeline_with_callable(self):
5858
pipe.fit(X_train, y_train)
5959
pred = pipe.predict(X_test)
6060
score = accuracy_score(y_test, pred)
61-
self.assertGreater(score, 0.8)
61+
self.assertGreater(score, 0.75)
6262
score2 = pipe.score(X_test, y_test)
6363
self.assertEqualFloat(score, score2, precision=1e-5)
6464
rp = repr(conv)

‎azure-pipelines.yml

Lines changed: 77 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -1,6 +1,76 @@
11
jobs:
22

3-
- job: 'TestLinuxWheelNoCuda'
3+
- job: 'TestLinuxWheelNoCuda313'
4+
pool:
5+
vmImage: 'ubuntu-latest'
6+
strategy:
7+
matrix:
8+
Python311-Linux:
9+
python.version: '3.13'
10+
maxParallel: 3
11+
12+
steps:
13+
- task: UsePythonVersion@0
14+
inputs:
15+
versionSpec: '$(python.version)'
16+
architecture: 'x64'
17+
- script: sudo apt-get update
18+
displayName: 'AptGet Update'
19+
- script: sudo apt-get install -y graphviz
20+
displayName: 'Install Graphviz'
21+
- script: python -m pip install --upgrade pip setuptools wheel
22+
displayName: 'Install tools'
23+
- script: pip install -r requirements.txt
24+
displayName: 'Install Requirements'
25+
- script: pip install -r requirements-dev.txt
26+
displayName: 'Install Requirements dev'
27+
- script: |
28+
ruff check .
29+
displayName: 'Ruff'
30+
- script: |
31+
black --diff .
32+
displayName: 'Black'
33+
- script: |
34+
cmake-lint _cmake/Find* --disabled-codes C0103 C0113 --line-width=88
35+
cmake-lint _cmake/CMake* --disabled-codes C0103 C0113 --line-width=88
36+
displayName: 'cmake-lint'
37+
- script: |
38+
rstcheck -r ./_doc ./mlinsights
39+
displayName: 'rstcheck'
40+
- script: |
41+
cython-lint .
42+
displayName: 'cython-lint'
43+
- script: |
44+
export USE_CUDA=0
45+
python -m pip install -e . --config-settings="--use_cuda=0" -v
46+
displayName: 'pip install -e . --config-settings="--use_cuda=0" -v'
47+
- script: |
48+
python -m pytest _unittests --durations=10
49+
displayName: 'Runs Unit Tests'
50+
- script: |
51+
# --config-settings does not work yet.
52+
# python -m pip wheel . --config-settings="--use_cuda=0" -v
53+
export USE_CUDA=0
54+
python -m pip wheel . --config-settings="--use_cuda=0" -v
55+
displayName: 'build wheel'
56+
- script: |
57+
mkdir dist
58+
cp mlinsights*.whl dist
59+
displayName: 'copy wheel'
60+
- script: |
61+
pip install auditwheel-symbols
62+
auditwheel-symbols --manylinux 2014 dist/*.whl || exit 0
63+
displayName: 'Audit wheel'
64+
- script: |
65+
pip install abi3audit
66+
abi3audit dist/*.whl || exit 0
67+
displayName: 'abi3audit wheel'
68+
- task: PublishPipelineArtifact@0
69+
inputs:
70+
artifactName: 'wheel-linux-pip-$(python.version)'
71+
targetPath: 'dist'
72+
73+
- job: 'TestLinuxWheelNoCuda312'
474
pool:
575
vmImage: 'ubuntu-latest'
676
strategy:
@@ -70,13 +140,13 @@ jobs:
70140
artifactName: 'wheel-linux-pip-$(python.version)'
71141
targetPath: 'dist'
72142

73-
- job: 'TestLinux'
143+
- job: 'TestLinux311'
74144
pool:
75145
vmImage: 'ubuntu-latest'
76146
strategy:
77147
matrix:
78148
Python311-Linux:
79-
python.version: '3.10'
149+
python.version: '3.11'
80150
maxParallel: 3
81151

82152
steps:
@@ -158,13 +228,13 @@ jobs:
158228
artifactName: 'wheel-linux-$(python.version)'
159229
targetPath: 'dist'
160230

161-
- job: 'TestWindows'
231+
- job: 'TestWindows312'
162232
pool:
163233
vmImage: 'windows-latest'
164234
strategy:
165235
matrix:
166236
Python311-Windows:
167-
python.version: '3.11'
237+
python.version: '3.12'
168238
maxParallel: 3
169239

170240
steps:
@@ -204,13 +274,13 @@ jobs:
204274
artifactName: 'wheel-windows-$(python.version)'
205275
targetPath: 'dist'
206276

207-
- job: 'TestMac'
277+
- job: 'TestMac312'
208278
pool:
209279
vmImage: 'macOS-latest'
210280
strategy:
211281
matrix:
212282
Python311-Mac:
213-
python.version: '3.11'
283+
python.version: '3.12'
214284
maxParallel: 3
215285

216286
steps:

‎mlinsights/__init__.py

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@@ -1,4 +1,4 @@
1-
__version__ = "0.5.1"
1+
__version__ = "0.5.2"
22
__author__ = "Xavier Dupré"
33
__github__ = "https://github.com/sdpython/mlinsights"
44
__url__ = "https://sdpython.github.io/doc/dev/mlinsights/"

‎mlinsights/mlmodel/interval_regressor.py

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@@ -1,7 +1,11 @@
11
import numpy
22
import numpy.random
33
from sklearn.base import RegressorMixin, clone, BaseEstimator
4-
from sklearn.utils._joblib import Parallel, delayed
4+
5+
try:
6+
from sklearn.utils.parallel import Parallel, delayed
7+
except ImportError:
8+
from sklearn.utils._joblib import Parallel, delayed
59

610
try: # noqa: SIM105
711
from tqdm import tqdm

‎mlinsights/mlmodel/piecewise_estimator.py

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@@ -5,7 +5,11 @@
55
from sklearn.tree import DecisionTreeRegressor, DecisionTreeClassifier
66
from sklearn.linear_model import LinearRegression, LogisticRegression
77
from sklearn.preprocessing import KBinsDiscretizer
8-
from sklearn.utils._joblib import Parallel, delayed
8+
9+
try:
10+
from sklearn.utils.parallel import Parallel, delayed
11+
except ImportError:
12+
from sklearn.utils._joblib import Parallel, delayed
913

1014
try: # noqa: SIM105
1115
from tqdm import tqdm

‎mlinsights/mlmodel/quantile_mlpregressor.py

Lines changed: 32 additions & 12 deletions
Original file line numberDiff line numberDiff line change
@@ -14,18 +14,24 @@
1414
from sklearn.metrics import mean_absolute_error
1515

1616

17-
def absolute_loss(y_true, y_pred):
17+
def absolute_loss(y_true, y_pred, sample_weight=None):
1818
"""
1919
Computes the absolute loss for regression.
2020
2121
:param y_true: array-like or label indicator matrix
2222
Ground truth (correct) values.
2323
:param y_pred: array-like or label indicator matrix
2424
Predicted values, as returned by a regression estimator.
25+
:param sample_weight: sample weights
2526
:return: loss, float
2627
The degree to which the samples are correctly predicted.
2728
"""
28-
return np.sum(np.abs(y_true - y_pred)) / y_true.shape[0]
29+
if sample_weight is None:
30+
return np.sum(np.abs(y_true - y_pred)) / y_true.shape[0]
31+
return (
32+
np.average(np.abs(y_true - y_pred), weights=sample_weight, axis=0)
33+
/ y_true.shape[0]
34+
)
2935

3036

3137
def float_sign(a):
@@ -132,7 +138,7 @@ def _modify_loss_derivatives(self, last_deltas):
132138
return DERIVATIVE_LOSS_FUNCTIONS["absolute_loss"](last_deltas)
133139
return last_deltas
134140

135-
def _backprop(self, X, y, activations, deltas, coef_grads, intercept_grads):
141+
def _backprop(self, *args):
136142
"""
137143
Computes the MLP loss function and its corresponding derivatives
138144
with respect to each parameter: weights and bias vectors.
@@ -141,6 +147,8 @@ def _backprop(self, X, y, activations, deltas, coef_grads, intercept_grads):
141147
The input data.
142148
:param y: array-like, shape (n_samples,)
143149
The target values.
150+
:param sample_weight: array-like of shape (n_samples,), default=None
151+
Sample weights.
144152
:param activations: list, length = n_layers - 1
145153
The ith element of the list holds the values of the ith layer.
146154
:param deltas: list, length = n_layers - 1
@@ -155,10 +163,18 @@ def _backprop(self, X, y, activations, deltas, coef_grads, intercept_grads):
155163
:param intercept_grads: list, length = n_layers - 1
156164
The ith element contains the amount of change used to update the
157165
intercept parameters of the ith layer in an iteration.
158-
:return: loss, float
159-
:return: coef_grads, list, length = n_layers - 1
160-
:return: intercept_grads, list, length = n_layers - 1
166+
:return: loss (float),
167+
coef_grads (list, length = n_layers - 1)
168+
intercept_grads: (list, length = n_layers - 1)
169+
170+
161171
"""
172+
if len(args) == 6:
173+
X, y, activations, deltas, coef_grads, intercept_grads = args
174+
sample_weight = None
175+
else:
176+
X, y, sample_weight, activations, deltas, coef_grads, intercept_grads = args
177+
162178
n_samples = X.shape[0]
163179

164180
# Forward propagate
@@ -169,10 +185,12 @@ def _backprop(self, X, y, activations, deltas, coef_grads, intercept_grads):
169185
if loss_func_name == "log_loss" and self.out_activation_ == "logistic":
170186
loss_func_name = "binary_log_loss"
171187
loss_function = self._get_loss_function(loss_func_name)
172-
loss = loss_function(y, activations[-1])
188+
loss = loss_function(y, activations[-1], sample_weight)
173189
# Add L2 regularization term to loss
174190
values = np.sum(np.array([np.dot(s.ravel(), s.ravel()) for s in self.coefs_]))
175-
loss += (0.5 * self.alpha) * values / n_samples
191+
192+
sw_sum = n_samples if sample_weight is None else sample_weight.sum()
193+
loss += (0.5 * self.alpha) * values / sw_sum
176194

177195
# Backward propagate
178196
last = self.n_layers_ - 2
@@ -182,20 +200,22 @@ def _backprop(self, X, y, activations, deltas, coef_grads, intercept_grads):
182200
# sigmoid and binary cross entropy, softmax and categorical cross
183201
# entropy, and identity with squared loss
184202
deltas[last] = activations[-1] - y
203+
if sample_weight is not None:
204+
deltas[last] *= sample_weight.reshape(-1, 1)
185205

186206
# We insert the following modification to modify the gradient
187207
# due to the modification of the loss function.
188208
deltas[last] = self._modify_loss_derivatives(deltas[last])
189209

190210
# Compute gradient for the last layer
191211
temp = self._compute_loss_grad(
192-
last, n_samples, activations, deltas, coef_grads, intercept_grads
212+
last, sw_sum, activations, deltas, coef_grads, intercept_grads
193213
)
194214
if temp is None:
195215
# recent version of scikit-learn
196216
# Compute gradient for the last layer
197217
self._compute_loss_grad(
198-
last, n_samples, activations, deltas, coef_grads, intercept_grads
218+
last, sw_sum, activations, deltas, coef_grads, intercept_grads
199219
)
200220

201221
inplace_derivative = DERIVATIVES[self.activation]
@@ -205,7 +225,7 @@ def _backprop(self, X, y, activations, deltas, coef_grads, intercept_grads):
205225
inplace_derivative(activations[i], deltas[i - 1])
206226

207227
self._compute_loss_grad(
208-
i - 1, n_samples, activations, deltas, coef_grads, intercept_grads
228+
i - 1, sw_sum, activations, deltas, coef_grads, intercept_grads
209229
)
210230
else:
211231
coef_grads, intercept_grads = temp
@@ -220,7 +240,7 @@ def _backprop(self, X, y, activations, deltas, coef_grads, intercept_grads):
220240
coef_grads,
221241
intercept_grads,
222242
) = self._compute_loss_grad(
223-
i - 1, n_samples, activations, deltas, coef_grads, intercept_grads
243+
i - 1, sw_sum, activations, deltas, coef_grads, intercept_grads
224244
)
225245

226246
return loss, coef_grads, intercept_grads

‎pyproject.toml

Lines changed: 5 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -26,7 +26,7 @@ license = {file = "LICENSE.txt"}
2626
name = "mlinsights"
2727
readme = "README.rst"
2828
requires-python = ">=3.10"
29-
version = "0.5.1"
29+
version = "0.5.2"
3030

3131
[project.urls]
3232
homepage = "https://sdpython.github.io/doc/mlinsights/dev/"
@@ -109,7 +109,7 @@ manylinux-x86_64-image = "manylinux2014"
109109
[tool.cibuildwheel.linux]
110110
archs = ["x86_64"]
111111
build = "cp*"
112-
skip = "cp36-* cp37-* cp38-* cp39-* cp313-* cp314-* cp315-* pypy* *musllinux*"
112+
skip = "cp36-* cp37-* cp38-* cp39-* cp310-* cp314-* cp315-* pypy* *musllinux*"
113113
manylinux-x86_64-image = "manylinux2014"
114114
before-build = "pip install auditwheel-symbols abi3audit"
115115
build-verbosity = 1
@@ -127,13 +127,13 @@ environment = """
127127
DYLD_LIBRARY_PATH='$(brew --prefix libomp)/lib:$DYLD_LIBRARY_PATH'
128128
"""
129129
build = "cp*"
130-
skip = "cp36-* cp37-* cp38-* cp39-* cp313-* cp314-* cp315-* pypy* pp*"
130+
skip = "cp36-* cp37-* cp38-* cp39-* cp310-* cp314-* cp315-* pypy* pp*"
131131
before-build = "brew install libomp llvm&&echo 'export PATH=\"/opt/homebrew/opt/llvm/bin:$PATH\"' >> /Users/runner/.bash_profile"
132132

133133
[tool.cibuildwheel.windows]
134134
archs = ["AMD64"]
135135
build = "cp*"
136-
skip = "cp36-* cp37-* cp38-* cp39-* cp313-* cp314-* cp315-* pypy*"
136+
skip = "cp36-* cp37-* cp38-* cp39-* cp310-* cp314-* cp315-* pypy*"
137137

138138
[tool.cython-lint]
139139
max-line-length = 88
@@ -189,7 +189,7 @@ select = [
189189
"C401", "C408", "C413",
190190
"RUF012", "RUF100", "RUF010",
191191
"SIM108", "SIM910", "SIM110", "SIM102", "SIM114", "SIM103", "UP015",
192-
"UP027", "UP031", "UP034", "UP032", "UP006", "UP035", "UP007", "UP038"
192+
"UP027", "UP031", "UP034", "UP032", "UP006", "UP035", "UP007", "UP038", "UP045"
193193
]
194194
"**/plot*.py" = ["B018"]
195195
"_unittests/**.py" = ["B904", "RUF015", "C400"]

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