updated version to v0.1.0 (open-mmlab#906)

* updated version to v0.1.0
* updated project description
* capped python version to <3.8, added classifiers and project_urls to setup.py
* Removed hard dependency on mxnet for autogluon.core and autogluon.tabular
* Removed gluoncv dependency in Tabular

NOTICE

@@ -1,2 +1,2 @@
-AutoML Toolkit with MXNet Gluon
+AutoML for Text, Image, and Tabular Data
 Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved. 

VERSION

@@ -1 +1 @@
-0.0.16
+0.1.0

autogluon/setup.py

@@ -1,11 +1,8 @@
 #!/usr/bin/env python
 import os
-import shutil
-import subprocess
-import codecs
 import os.path
 
-from setuptools import setup, find_packages, find_namespace_packages
+from setuptools import setup, find_packages
 
 cwd = os.path.dirname(os.path.abspath(__file__))
 
@@ -46,7 +43,7 @@ def create_version_file():
 
 long_description = open(os.path.join('..', 'README.md')).read()
 
-MIN_PYTHON_VERSION = '>=3.6.*'
+python_requires = '>=3.6, <3.8'
 
 requirements = [
     f'autogluon.core=={version}',
@@ -70,10 +67,10 @@ def create_version_file():
         version=version,
         author='AutoGluon Community',
         url='https://github.com/awslabs/autogluon',
-        description='AutoML Toolkit with MXNet Gluon',
+        description='AutoML for Text, Image, and Tabular Data',
         long_description=long_description,
         long_description_content_type='text/markdown',
-        license='Apache',
+        license='Apache-2.0',
 
         # Package info
         packages=find_packages('src'),
@@ -82,10 +79,39 @@ def create_version_file():
         zip_safe=True,
         include_package_data=True,
         install_requires=requirements + test_requirements,
-        python_requires=MIN_PYTHON_VERSION,
+        python_requires=python_requires,
         package_data={'autogluon': [
             'LICENSE',
         ]},
         entry_points={
         },
+        # TODO: Move classifiers / project_urls / other arguments to a shared file across all submodules?
+        classifiers=[
+            "Development Status :: 4 - Beta",
+            "Intended Audience :: Education",
+            "Intended Audience :: Developers",
+            "Intended Audience :: Science/Research",
+            "Intended Audience :: Customer Service",
+            "Intended Audience :: Financial and Insurance Industry",
+            "Intended Audience :: Healthcare Industry",
+            "Intended Audience :: Telecommunications Industry",
+            "License :: OSI Approved :: Apache Software License",
+            "Operating System :: MacOS",
+            "Operating System :: Microsoft :: Windows",
+            "Operating System :: POSIX",
+            "Operating System :: Unix",
+            'Programming Language :: Python :: 3',
+            "Programming Language :: Python :: 3.6",
+            "Programming Language :: Python :: 3.7",
+            "Topic :: Software Development",
+            "Topic :: Scientific/Engineering :: Artificial Intelligence",
+            "Topic :: Scientific/Engineering :: Information Analysis",
+            "Topic :: Scientific/Engineering :: Image Recognition",
+        ],
+        project_urls={
+            'Documentation': 'https://auto.gluon.ai',
+            'Bug Reports': 'https://github.com/awslabs/autogluon/issues',
+            'Source': 'https://github.com/awslabs/autogluon/',
+            'Contribute!': 'https://github.com/awslabs/autogluon/blob/master/CONTRIBUTING.md',
+        },
     )

core/setup.py

@@ -40,7 +40,7 @@ def create_version_file():
 
 long_description = open(os.path.join('..', 'README.md')).read()
 
-MIN_PYTHON_VERSION = '>=3.6.*'  # TODO v0.1: Also specify max version? (We don't support 3.8)
+python_requires = '>=3.6, <3.8'
 
 requirements = [
     'numpy>=1.20',
@@ -75,10 +75,10 @@ def create_version_file():
         version=version,
         author='AutoGluon Community',
         url='https://github.com/awslabs/autogluon',
-        description='AutoML Toolkit with MXNet Gluon',
+        description='AutoML for Text, Image, and Tabular Data',
         long_description=long_description,
         long_description_content_type='text/markdown',
-        license='Apache',
+        license='Apache-2.0',
 
         # Package info
         packages=find_packages('src'),
@@ -87,7 +87,7 @@ def create_version_file():
         zip_safe=True,
         include_package_data=True,
         install_requires=requirements + test_requirements,
-        python_requires=MIN_PYTHON_VERSION,
+        python_requires=python_requires,
         package_data={'autogluon': [
             'LICENSE',
         ]},

core/src/autogluon/core/metrics/__init__.py

@@ -6,7 +6,7 @@
 import scipy.stats
 import sklearn.metrics
 
-from . import classification_metrics, softclass_metrics
+from . import classification_metrics
 from .util import sanitize_array
 from ..constants import PROBLEM_TYPES, PROBLEM_TYPES_REGRESSION, PROBLEM_TYPES_CLASSIFICATION
 from ..utils.miscs import warning_filter
@@ -405,10 +405,6 @@ def customized_log_loss(y_true, y_pred, eps=1e-15):
                         greater_is_better=True,
                         needs_proba=True)
 
-# Score for soft-classification (with soft, probabilistic labels):
-soft_log_loss = make_scorer('soft_log_loss', softclass_metrics.soft_log_loss,
-                            greater_is_better=False, needs_proba=True)
-
 REGRESSION_METRICS = dict()
 for scorer in [r2, mean_squared_error, root_mean_squared_error, mean_absolute_error,
                    median_absolute_error, spearmanr, pearsonr]:
@@ -495,8 +491,7 @@ def calculate_score(solution, prediction, task_type, metric,
 def get_metric(metric, problem_type=None, metric_type=None) -> Scorer:
     """Returns metric function by using its name if the metric is str.
     Performs basic check for metric compatibility with given problem type."""
-    all_available_metric_names = list(CLASSIFICATION_METRICS.keys())\
-                                 + list(REGRESSION_METRICS.keys()) + [soft_log_loss]
+    all_available_metric_names = list(CLASSIFICATION_METRICS.keys()) + list(REGRESSION_METRICS.keys()) + ['soft_log_loss']
     if metric is not None and isinstance(metric, str):
         if metric in CLASSIFICATION_METRICS:
             if problem_type is not None and problem_type not in PROBLEM_TYPES_CLASSIFICATION:
@@ -507,6 +502,8 @@ def get_metric(metric, problem_type=None, metric_type=None) -> Scorer:
                 raise ValueError(f"{metric_type}={metric} can only be used for regression problems")
             return REGRESSION_METRICS[metric]
         elif metric == 'soft_log_loss':
+            # Requires mxnet
+            from .softclass_metrics import soft_log_loss
             return soft_log_loss
         else:
             raise ValueError(

core/src/autogluon/core/metrics/softclass_metrics.py

@@ -2,9 +2,14 @@
 
 import logging
 
-import mxnet as mx
 import numpy as np
 
+from . import make_scorer
+from ..utils.try_import import try_import_mxnet
+
+try_import_mxnet()
+import mxnet as mx
+
 logger = logging.getLogger(__name__)
 
 EPS = 1e-10  # clipping threshold to prevent NaN
@@ -13,7 +18,7 @@
 softloss = mx.gluon.loss.SoftmaxCrossEntropyLoss(sparse_label=False, from_logits=True)
 
 
-def soft_log_loss(true_probs, predicted_probs):
+def _soft_log_loss(true_probs, predicted_probs):
     """ Both args must be 2D pandas/numpy arrays """
     true_probs = np.array(true_probs)
     predicted_probs = np.array(predicted_probs)
@@ -28,3 +33,8 @@ def soft_log_loss(true_probs, predicted_probs):
     predicted_probs = predicted_probs / predicted_probs.sum(axis=1, keepdims=1)
     losses = softloss(mx.nd.log(mx.nd.array(predicted_probs)), mx.nd.array(true_probs))
     return mx.nd.mean(losses).asscalar()
+
+
+# Score for soft-classification (with soft, probabilistic labels):
+soft_log_loss = make_scorer('soft_log_loss', _soft_log_loss,
+                            greater_is_better=False, needs_proba=True)

docs/config.ini

@@ -12,7 +12,7 @@ author = AutoGluon contributors
 
 copyright = 2019, All developers. Licensed under the Apache License, Version 2.0.
 
-release = 0.0.16
+release = 0.1.0
 
 [html]
 

docs/root_index.html

@@ -9,7 +9,7 @@
       <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
       <meta http-equiv="x-ua-compatible" content="ie=edge">
 
-      <title>AutoGluon: AutoML Toolkit for Deep Learning &#8212; AutoGluon Documentation</title>
+      <title>AutoGluon: AutoML for Text, Image, and Tabular Data &#8212; AutoGluon Documentation</title>
 
       <link rel="stylesheet" href="_static/basic.css" type="text/css"/>
       <link rel="stylesheet" href="_static/pygments.css" type="text/css"/>

docs/versions.rst

@@ -3,5 +3,5 @@ Available Documentation for AutoGluon
 
 Web-based documentation is available for versions listed below:
 
-- `AutoGluon 0.0.16 (dev) documentation <https://auto.gluon.ai/dev/index.html>`_
+- `AutoGluon 0.1.0 (dev) documentation <https://auto.gluon.ai/dev/index.html>`_
 - `AutoGluon 0.0.15 (stable) documentation <https://auto.gluon.ai/stable/index.html>`_

extra/setup.py

@@ -42,7 +42,7 @@ def create_version_file():
 
 long_description = open(os.path.join('..', 'README.md')).read()
 
-MIN_PYTHON_VERSION = '>=3.6.*'
+python_requires = '>=3.6, <3.8'
 
 requirements = [
     'numpy>=1.20',
@@ -68,10 +68,10 @@ def create_version_file():
         version=version,
         author='AutoGluon Community',
         url='https://github.com/awslabs/autogluon',
-        description='AutoML Toolkit with MXNet Gluon',
+        description='AutoML for Text, Image, and Tabular Data',
         long_description=long_description,
         long_description_content_type='text/markdown',
-        license='Apache',
+        license='Apache-2.0',
 
         # Package info
         packages=find_packages('src'),
@@ -80,7 +80,7 @@ def create_version_file():
         zip_safe=True,
         include_package_data=True,
         install_requires=requirements + test_requirements,
-        python_requires=MIN_PYTHON_VERSION,
+        python_requires=python_requires,
         package_data={'autogluon': [
             'LICENSE',
         ]},

features/setup.py

@@ -40,7 +40,7 @@ def create_version_file():
 
 long_description = open(os.path.join('..', 'README.md')).read()
 
-MIN_PYTHON_VERSION = '>=3.6.*'
+python_requires = '>=3.6, <3.8'
 
 requirements = [
     'numpy>=1.20',
@@ -61,10 +61,10 @@ def create_version_file():
         version=version,
         author='AutoGluon Community',
         url='https://github.com/awslabs/autogluon',
-        description='AutoML Toolkit with MXNet Gluon',
+        description='AutoML for Text, Image, and Tabular Data',
         long_description=long_description,
         long_description_content_type='text/markdown',
-        license='Apache',
+        license='Apache-2.0',
 
         # Package info
         packages=find_packages('src'),
@@ -73,7 +73,7 @@ def create_version_file():
         zip_safe=True,
         include_package_data=True,
         install_requires=requirements + test_requirements,
-        python_requires=MIN_PYTHON_VERSION,
+        python_requires=python_requires,
         package_data={'autogluon': [
             'LICENSE',
         ]},

mxnet/setup.py

@@ -40,7 +40,7 @@ def create_version_file():
 
 long_description = open(os.path.join('..', 'README.md')).read()
 
-MIN_PYTHON_VERSION = '>=3.6.*'
+python_requires = '>=3.6, <3.8'
 
 requirements = [
     'Pillow<=6.2.1',
@@ -64,10 +64,10 @@ def create_version_file():
         version=version,
         author='AutoGluon Community',
         url='https://github.com/awslabs/autogluon',
-        description='AutoML Toolkit with MXNet Gluon',
+        description='AutoML for Text, Image, and Tabular Data',
         long_description=long_description,
         long_description_content_type='text/markdown',
-        license='Apache',
+        license='Apache-2.0',
 
         # Package info
         packages=find_packages('src'),
@@ -76,7 +76,7 @@ def create_version_file():
         zip_safe=True,
         include_package_data=True,
         install_requires=requirements + test_requirements,
-        python_requires=MIN_PYTHON_VERSION,
+        python_requires=python_requires,
         package_data={'autogluon': [
             'LICENSE',
         ]},

setup.cfg

@@ -1,6 +1,6 @@
 [pycodestyle]
-max_line_length = 120
+max_line_length = 160
 
 
 [flake8]
-max-line-length = 120
+max-line-length = 160

tabular/setup.py

@@ -40,7 +40,7 @@ def create_version_file():
 
 long_description = open(os.path.join('..', 'README.md')).read()
 
-MIN_PYTHON_VERSION = '>=3.6.*'
+python_requires = '>=3.6, <3.8'
 
 requirements = [
     'numpy>=1.20',
@@ -52,7 +52,6 @@ def create_version_file():
     'psutil>=5.0.0,<=5.7.0',  # TODO: psutil 5.7.1/5.7.2 has non-deterministic error on CI doc build -  ImportError: cannot import name '_psutil_linux' from 'psutil'
     'scikit-learn>=0.22.0,<0.24',
     'networkx>=2.3,<3.0',
-    'gluoncv>=0.9.1,<1.0',  # TODO: v0.1 consider using only minimum required code from gluoncv and drop dependency
     'torch>=1.0,<2.0',  # TODO: v0.1 make optional
     'fastai>=1.0,<2.0',  # TODO: v0.1 make optional
     f'autogluon.core=={version}',
@@ -71,10 +70,10 @@ def create_version_file():
         version=version,
         author='AutoGluon Community',
         url='https://github.com/awslabs/autogluon',
-        description='AutoML Toolkit with MXNet Gluon',
+        description='AutoML for Text, Image, and Tabular Data',
         long_description=long_description,
         long_description_content_type='text/markdown',
-        license='Apache',
+        license='Apache-2.0',
 
         # Package info
         packages=find_packages('src'),
@@ -83,7 +82,7 @@ def create_version_file():
         zip_safe=True,
         include_package_data=True,
         install_requires=requirements + test_requirements,
-        python_requires=MIN_PYTHON_VERSION,
+        python_requires=python_requires,
         package_data={'autogluon': [
             'LICENSE',
         ]},

tabular/src/autogluon/tabular/models/catboost/catboost_softclass_utils.py

@@ -1,7 +1,7 @@
 import math
 import numpy as np
 
-from autogluon.core.metrics import soft_log_loss
+from autogluon.core.metrics.softclass_metrics import soft_log_loss
 from autogluon.core.utils import try_import_catboost, try_import_catboostdev
 
 from .catboost_utils import CustomMetric