microsoft
/
hummingbird
зеркало из https://github.com/microsoft/hummingbird.git
1
0
Форкнуть 0
Код Задачи Пакеты Проекты Релизы Вики Активность

deprecate torch1.7, push to macOS11 (#594)

This commit is contained in:
Karla Saur 2022-06-20 19:05:25 -07:00 коммит произвёл GitHub
Родитель 833447520f
Коммит a4aaabf0ee
Не найден ключ, соответствующий данной подписи
Идентификатор ключа GPG: 4AEE18F83AFDEB23
11 изменённых файлов: 26 добавлений и 95 удалений
Показать статистику Скачать Patch файл Скачать Diff файл Показать все файлы Свернуть все файлы

55
.github/workflows/pythonapp.yml поставляемый
Просмотреть файл

@ -18,7 +18,7 @@ jobs:
runs-on: ${{ matrix.os }}
strategy:
matrix:
os: [ubuntu-18.04, macos-10.15, windows-2019]
os: [ubuntu-18.04, macos-11, windows-2019]
python-version: [3.8, 3.9]
steps:
@ -36,19 +36,11 @@ jobs:
# The GitHub editor is 127 chars wide
flake8 . --count --max-complexity=10 --max-line-length=127 --statistics
# PyTorch for Mac has different pip syntax wrt Win and Linux.
# We want to test torch 1.6.0 (in this case on python3.7) and torch 1.11.x.
# The following cases address the situations above.
- name: Install pytorch 1.6.0 if python 3.7 (mac)
if: ${{ matrix.python-version == '3.7' && matrix.os == 'macos-10.15' }}
run: pip install torch==1.6.0
- name: Install pytorch 1.11.0 if python > 3.7 (mac)
if: ${{ matrix.python-version != '3.7' && matrix.os == 'macos-10.15' }}
- name: Install pytorch 1.11.0 if mac
if: ${{ matrix.os == 'macos-11' }}
run: pip install torch==1.11.0
- name: Install pytorch 1.6.0+cpu if python 3.7 (not mac)
if: ${{ matrix.python-version == '3.7' && matrix.os != 'macos-10.15' }}
run: pip install torch==1.6.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
- name: Install pytorch 1.11.0+cpu if python > 3.7 (not mac)
if: ${{ matrix.python-version != '3.7' && matrix.os != 'macos-10.15' }}
- name: Install pytorch 1.11.0+cpu if not mac
if: ${{ matrix.os != 'macos-11' }}
run: pip install torch==1.11.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
- name: Install basic dependencies
run: |
@ -58,7 +50,7 @@ jobs:
- name: Coverage on basic tests without extra
run: coverage run -a -m pytest tests/test_no_extra_install.py
- name: If mac, install libomp to facilitate lgbm install
if: matrix.os == 'macos-10.15'
if: matrix.os == 'macos-11'
run: |
wget https://raw.githubusercontent.com/Homebrew/homebrew-core/fb8323f2b170bd4ae97e1bac9bf3e2983af3fdb0/Formula/libomp.rb
brew unlink libomp
@ -97,19 +89,19 @@ jobs:
git submodule update --recursive --init
cmake -E make_directory build
- name: Get LLVM on Linux
if: ${{ steps.cache.outputs.cache-hit != 'true' && matrix.python-version != '3.7' && matrix.os == 'ubuntu-18.04' }}
if: ${{ steps.cache.outputs.cache-hit != 'true' && matrix.os == 'ubuntu-18.04' }}
working-directory: ../../../tvm
run: |
wget https://github.com/llvm/llvm-project/releases/download/llvmorg-10.0.0/clang+llvm-10.0.0-x86_64-linux-gnu-ubuntu-18.04.tar.xz
tar -xf clang+llvm-10.0.0-x86_64-linux-gnu-ubuntu-18.04.tar.xz && mv clang+llvm-10.0.0-x86_64-linux-gnu-ubuntu-18.04 llvm
- name: Get LLVM on Mac
if: ${{ steps.cache.outputs.cache-hit != 'true' && matrix.python-version != '3.7' && matrix.os == 'macos-10.15' }}
if: ${{ steps.cache.outputs.cache-hit != 'true' && matrix.os == 'macos-11' }}
working-directory: ../../../tvm
run: |
wget https://github.com/llvm/llvm-project/releases/download/llvmorg-10.0.0/clang+llvm-10.0.0-x86_64-apple-darwin.tar.xz
tar -xf clang+llvm-10.0.0-x86_64-apple-darwin.tar.xz && mv clang+llvm-10.0.0-x86_64-apple-darwin llvm
- name: CMake TVM
if: ${{ steps.cache.outputs.cache-hit != 'true' && matrix.python-version != '3.7' && matrix.os != 'windows-2019' }}
if: ${{ steps.cache.outputs.cache-hit != 'true' && matrix.os != 'windows-2019' }}
working-directory: ../../../tvm/build
run: >-
cmake
@ -118,51 +110,40 @@ jobs:
"-DUSE_LLVM=../llvm/bin/llvm-config"
..
- name: Build TVM
if: ${{ steps.cache.outputs.cache-hit != 'true' && matrix.python-version != '3.7' && matrix.os != 'windows-2019' }}
if: ${{ steps.cache.outputs.cache-hit != 'true' && matrix.os != 'windows-2019' }}
working-directory: ../../../tvm/build
run: |
make -j3
- name: Install python TVM
if: ${{ matrix.python-version != '3.7' && matrix.os != 'windows-2019' }}
if: ${{ matrix.os != 'windows-2019' }}
working-directory: ../../../tvm/python
run: |
python setup.py install
- name: pip list
run: pip list
# We don't run pytest for Linux py3.7 since we do coverage for that case.
# We don't run pytest for Linux py3.8 since we do coverage for that case.
- name: Test with pytest
if: ${{ matrix.python-version != '3.7' || matrix.os != 'ubuntu-18.04' }}
if: ${{ matrix.python-version != '3.8' || matrix.os != 'ubuntu-18.04' }}
run: pytest
# Run and push coverage only for two runs (Linux py3.7 and py3.8).
- name: Coverage 3.7 Linux
if: ${{ matrix.python-version == '3.7' && matrix.os == 'ubuntu-18.04' }}
run: |
coverage run -a -m pytest tests
coverage xml
# Run and push coverage only for Linux py3.8
- name: Coverage 3.8 Linux
if: ${{ matrix.python-version == '3.8' && matrix.os == 'ubuntu-18.04' }}
run: |
coverage run -a -m pytest tests
coverage xml
- name: Upload coverage to Codecov 3.7
if: ${{ matrix.python-version == '3.7' && matrix.os == 'ubuntu-18.04' }}
uses: codecov/codecov-action@v1
with:
file: ./coverage.xml
flags: unittests
- name: Upload coverage to Codecov 8
- name: Upload coverage to Codecov
if: ${{ matrix.python-version == '3.8' && matrix.os == 'ubuntu-18.04' }}
uses: codecov/codecov-action@v1
with:
file: ./coverage.xml
flags: unittests
# Compile and push documentation only for one of the runs (Linux py3.7).
# Compile and push documentation only for one of the runs (Linux py3.8).
- name: Generate Documentation
if: ${{ matrix.python-version == '3.7' && matrix.os == 'ubuntu-18.04' }}
if: ${{ matrix.python-version == '3.8' && matrix.os == 'ubuntu-18.04' }}
run: |
make sphinx-site -C website/
- name: Deploy to GitHub pages 🚀
if: ${{ github.ref == 'refs/heads/main' && matrix.python-version == '3.7' && matrix.os == 'ubuntu-18.04' }}
if: ${{ github.ref == 'refs/heads/main' && matrix.python-version == '3.9' && matrix.os == 'ubuntu-18.04' }}
uses: JamesIves/github-pages-deploy-action@4.0.0
with:
branch: gh-pages

5
hummingbird/ml/_utils.py
Просмотреть файл

@ -25,6 +25,9 @@ def torch_installed():
"""
try:
import torch
assert (
LooseVersion(torch.__version__) > LooseVersion("1.7.0")
), "Please install torch >1.7.0"
return True
except ImportError:
@ -32,7 +35,7 @@ def torch_installed():
def assert_torch_installed():
assert torch_installed(), "To use Hummingbird you need to install torch."
assert torch_installed(), "To use Hummingbird you need to install torch>1.7.0."
def onnx_ml_tools_installed():

8
hummingbird/ml/operator_converters/_gbdt_commons.py
Просмотреть файл

@ -52,15 +52,7 @@ def convert_gbdt_classifier_common(
n_classes -= 1
if classes is None:
classes = [i for i in range(n_classes)]
# There is a bug in torch < 1.7.0 that causes a mismatch. See Issue #10
if n_classes > 2:
from distutils.version import LooseVersion
import torch
if LooseVersion(torch.__version__) < LooseVersion("1.7.0"):
import warnings
warnings.warn("torch < 1.7.0 may give a mismatch on multiclass. See issue #10.")
reorder_trees = True
if constants.REORDER_TREES in extra_config:
reorder_trees = extra_config[constants.REORDER_TREES]

10
hummingbird/ml/operator_converters/sklearn/decision_tree.py
Просмотреть файл

@ -35,16 +35,6 @@ def convert_sklearn_random_forest_classifier(operator, device, extra_config):
n_features = operator.raw_operator.n_features_
classes = operator.raw_operator.classes_.tolist()
# There is a bug in torch < 1.7.0 that causes a mismatch. See Issue #10
if len(classes) > 2:
from distutils.version import LooseVersion
import torch
if LooseVersion(torch.__version__) < LooseVersion("1.7.0"):
import warnings
warnings.warn("torch < 1.7.0 may give a mismatch on multiclass. See issue #10.")
# For Sklearn Trees we need to know how many trees are there for normalization.
extra_config[constants.NUM_TREES] = len(tree_infos)

9
hummingbird/ml/operator_converters/sklearn/linear.py
Просмотреть файл

@ -32,15 +32,6 @@ def convert_sklearn_linear_model(operator, device, extra_config):
supported_loss = {"log", "modified_huber", "squared_hinge"}
classes = [0] if not hasattr(operator.raw_operator, "classes_") else operator.raw_operator.classes_
# There is a bug in torch < 1.7.0 that causes a mismatch. See Issue #10
if len(classes) > 2:
from distutils.version import LooseVersion
import torch
if LooseVersion(torch.__version__) < LooseVersion("1.7.0"):
import warnings
warnings.warn("torch < 1.7.0 may give a mismatch on multiclass. See issue #10.")
if not all(["int" in str(type(x)) for x in classes]):
raise RuntimeError(

10
hummingbird/ml/operator_converters/sklearn/mlp.py
Просмотреть файл

@ -30,16 +30,6 @@ def convert_sklearn_mlp_classifier(operator, device, extra_config):
assert operator is not None, "Cannot convert None operator"
classes = operator.raw_operator.classes_
# There is a bug in torch < 1.7.0 that causes a mismatch. See Issue #10
if len(classes) > 2:
from distutils.version import LooseVersion
import torch
if LooseVersion(torch.__version__) < LooseVersion("1.7.0"):
import warnings
warnings.warn("torch < 1.7.0 may give a mismatch on multiclass. See issue #10.")
if not all([type(x) in [int, np.int32, np.int64] for x in classes]):
raise RuntimeError("Hummingbird supports only integer labels for class labels.")

4
setup.py
Просмотреть файл

@ -26,7 +26,7 @@ install_requires = [
"onnxconverter-common>=1.6.0",
"scipy",
"scikit-learn",
"torch>=1.4",
"torch>1.7.0",
"psutil",
"dill",
"protobuf>=3.20.0,<=3.20.1",
@ -69,5 +69,5 @@ setup(
"Operating System :: OS Independent",
"License :: OSI Approved :: MIT License",
],
python_requires=">=3.6",
python_requires=">=3.8",
)

3
tests/test_prophet.py
Просмотреть файл

@ -54,9 +54,6 @@ class TestProphet(unittest.TestCase):
@unittest.skipIf(
not (pandas_installed() and prophet_installed()), reason="Test requires Prophet, Pandas and ONNX runtime.",
)
@unittest.skipIf(
LooseVersion(torch.__version__) < LooseVersion("1.8.1"), reason="Test requires Torch 1.8.1.",
)
@unittest.skipIf(
not onnx_runtime_installed() or LooseVersion(onnxruntime.__version__) < LooseVersion("1.7.0"),
reason="Prophet test requires onnxruntime => 1.7.0",

6
tests/test_sklearn_decision_tree_converter.py
Просмотреть файл

@ -54,11 +54,7 @@ class TestSklearnTreeConverter(unittest.TestCase):
self.assertIsNotNone(torch_model)
np.testing.assert_allclose(model.predict_proba(X), torch_model.predict_proba(X), rtol=1e-06, atol=1e-06)
from distutils.version import LooseVersion
import torch
if LooseVersion(torch.__version__) >= LooseVersion("1.7.0"):
np.testing.assert_allclose(model.predict(X), torch_model.predict(X), rtol=1e-06, atol=1e-06)
np.testing.assert_allclose(model.predict(X), torch_model.predict(X), rtol=1e-06, atol=1e-06)
# Random forest binary classifier
def test_random_forest_classifier_binary_converter(self):

10
tests/test_sklearn_linear_converter.py
Просмотреть файл

@ -201,9 +201,6 @@ class TestSklearnLinearClassifiers(unittest.TestCase):
self._test_sgd_classifier(3)
# SGDClassifier with modified huber loss
@unittest.skipIf(
LooseVersion(torch.__version__) < LooseVersion("1.7.0"), reason="Modified Huber loss test requires torch >= 1.7.0"
)
def test_modified_huber(self):
X = np.array([[-0.5, -1], [-1, -1], [-0.1, -0.1], [0.1, -0.2], [0.5, 1], [1, 1], [0.1, 0.1], [-0.1, 0.2]])
Y = np.array([1, 1, 1, 1, 2, 2, 2, 2])
@ -217,9 +214,6 @@ class TestSklearnLinearClassifiers(unittest.TestCase):
inputs = [[-1, -1], [1, 1], [-0.2, 0.1], [0.2, -0.1]]
np.testing.assert_allclose(model.predict_proba(inputs), hb_model.predict_proba(inputs), rtol=1e-6, atol=1e-6)
@unittest.skipIf(
LooseVersion(torch.__version__) < LooseVersion("1.7.0"), reason="Modified Huber loss test requires torch >= 1.7.0"
)
def test_modified_huber2(self):
X = np.array([[-0.5, -1], [-1, -1], [-0.1, -0.1], [0.1, -0.2], [0.5, 1], [1, 1], [0.1, 0.1], [-0.1, 0.2]])
Y = np.array([1, 1, 1, 1, 2, 2, 2, 2])
@ -232,10 +226,6 @@ class TestSklearnLinearClassifiers(unittest.TestCase):
np.testing.assert_allclose(model.predict_proba(X), hb_model.predict_proba(X), rtol=1e-6, atol=1e-6)
# SGDClassifier with modified huber loss multiclass
@unittest.skipIf(
LooseVersion(torch.__version__) < LooseVersion("1.7.0"), reason="Modified Huber loss test requires torch >= 1.7.0"
)
def test_modified_huber_multi(self):
X = np.array([[-0.5, -1], [-1, -1], [-0.1, -0.1], [0.1, -0.2], [0.5, 1], [1, 1], [0.1, 0.1], [-0.1, 0.2]])
Y = np.array([0, 1, 1, 1, 2, 2, 2, 2])

1
website/Makefile
Просмотреть файл

@ -24,6 +24,7 @@ clean-sphinx-site:
sphinx-site: #clean-sphinx-site
pip install sphinx sphinx_rtd_theme psutil
# TODO: There is a bug with torch 1.6 causing a "has no attribute 'training')" error. Using 1.5 for now.
# Update: there are even more bugs with newer versions. I'm not quite sure what to do.
pip install torch==1.5.1+cpu -f https://download.pytorch.org/whl/torch_stable.html
sphinx-apidoc --private -o sphinx/api -t sphinx/_templates ../hummingbird -d 1 -f -e
$(MAKE) -C sphinx