# -*- coding: utf-8 -*-
from setuptools import setup

package_dir = \
{'': 'src'}

packages = \
['neptune',
 'neptune.common',
 'neptune.common.backends',
 'neptune.common.hardware',
 'neptune.common.hardware.cgroup',
 'neptune.common.hardware.gauges',
 'neptune.common.hardware.gpu',
 'neptune.common.hardware.metrics',
 'neptune.common.hardware.metrics.reports',
 'neptune.common.hardware.metrics.service',
 'neptune.common.hardware.resources',
 'neptune.common.hardware.system',
 'neptune.common.patches',
 'neptune.common.storage',
 'neptune.common.websockets',
 'neptune.legacy',
 'neptune.legacy.internal',
 'neptune.legacy.internal.api_clients',
 'neptune.legacy.internal.api_clients.hosted_api_clients',
 'neptune.legacy.internal.backends',
 'neptune.legacy.internal.channels',
 'neptune.legacy.internal.execution',
 'neptune.legacy.internal.experiments',
 'neptune.legacy.internal.notebooks',
 'neptune.legacy.internal.streams',
 'neptune.legacy.internal.threads',
 'neptune.legacy.internal.utils',
 'neptune.legacy.internal.websockets',
 'neptune.management',
 'neptune.management.internal',
 'neptune.new',
 'neptune.new.attributes',
 'neptune.new.attributes.atoms',
 'neptune.new.attributes.series',
 'neptune.new.attributes.sets',
 'neptune.new.cli',
 'neptune.new.integrations',
 'neptune.new.integrations.fastai',
 'neptune.new.integrations.kedro',
 'neptune.new.integrations.lightgbm',
 'neptune.new.integrations.optuna',
 'neptune.new.integrations.prophet',
 'neptune.new.integrations.pytorch_lightning',
 'neptune.new.integrations.sacred',
 'neptune.new.integrations.sklearn',
 'neptune.new.integrations.tensorflow_keras',
 'neptune.new.integrations.transformers',
 'neptune.new.integrations.xgboost',
 'neptune.new.internal',
 'neptune.new.internal.artifacts',
 'neptune.new.internal.artifacts.drivers',
 'neptune.new.internal.backends',
 'neptune.new.internal.hardware',
 'neptune.new.internal.hardware.gpu',
 'neptune.new.internal.init',
 'neptune.new.internal.notebooks',
 'neptune.new.internal.operation_processors',
 'neptune.new.internal.streams',
 'neptune.new.internal.threading',
 'neptune.new.internal.types',
 'neptune.new.internal.utils',
 'neptune.new.internal.websockets',
 'neptune.new.logging',
 'neptune.new.metadata_containers',
 'neptune.new.sync',
 'neptune.new.types',
 'neptune.new.types.atoms',
 'neptune.new.types.series',
 'neptune.new.types.sets',
 'neptune.vendor']

package_data = \
{'': ['*']}

install_requires = \
['GitPython>=2.0.8',
 'Pillow>=1.1.6',
 'PyJWT',
 'boto3>=1.16.0',
 'bravado>=11.0.0,<12.0.0',
 'click>=7.0',
 'future>=0.17.1',
 'oauthlib>=2.1.0',
 'packaging',
 'pandas',
 'psutil',
 'requests-oauthlib>=1.0.0',
 'requests>=2.20.0',
 'six>=1.12.0',
 'swagger-spec-validator>=2.7.4',
 'urllib3',
 'websocket-client>=0.35.0,!=1.0.0']

extras_require = \
{':python_version < "3.7"': ['dataclasses>=0.6'],
 ':python_version < "3.8"': ['importlib-metadata'],
 'dev': ['altair',
         'bokeh',
         'freezegun',
         'matplotlib',
         'mock',
         'moto[s3]',
         'munch',
         'plotly',
         'pre-commit',
         'pytest',
         'pytest-cov',
         'pytest-mock',
         'pytest-timeout',
         'pytest-xdist',
         'tensorflow',
         'torch',
         'vega_datasets'],
 'e2e': ['Faker',
         'optuna',
         'sklearn',
         'torchvision',
         'pytorch-lightning',
         'transformers'],
 'fastai': ['neptune-fastai'],
 'kedro:python_version < "3.11"': ['kedro-neptune'],
 'lightgbm': ['neptune-lightgbm'],
 'optuna': ['neptune-optuna'],
 'prophet': ['neptune-prophet'],
 'pytorch-lightning': ['pytorch-lightning'],
 'sacred': ['neptune-sacred'],
 'sklearn': ['neptune-sklearn'],
 'tensorflow-keras': ['neptune-tensorflow-keras'],
 'transformers': ['transformers'],
 'xgboost': ['neptune-xgboost']}

entry_points = \
{'console_scripts': ['neptune = neptune.new.cli.__main__:main']}

setup_kwargs = {
    'name': 'neptune-client',
    'version': '0.16.13',
    'description': 'Neptune Client',
    'long_description': '<div align="center">\n    <img src="https://neptune.ai/wp-content/uploads/neptune-logo-less-margin-e1611939742683.png" width="300" /><br><br>\n</div>\n\n<div align="center">\n    <a href="https://badge.fury.io/py/neptune-client"><img src="https://badge.fury.io/py/neptune-client.svg" alt="PyPI version"></a>\n    <a href="https://docs.neptune.ai/"><img src="https://img.shields.io/badge/Neptune-docs-informational?logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADIAAAAgCAYAAABQISshAAAACXBIWXMAAA7DAAAOwwHHb6hkAAAF6klEQVRYCa2YXWiWZRjH301nGWVTa36ESWqb1bTSorSTUg8kwg4iSIhOgo49yDoIOomgjiqQPCroIEGQqA6ighoIZYbZNEtnhU1rUc3U5fzY3Nbv//hcT//33rN37zu74Nr1fV33fd1fz95KpQaMjo7OHBsb2wy+A74HbgXbaoTUZSLHevBj8A/wGLiNWjfVFdyokxJT4CMwhb0obm40X/iT9zHiB9KkyF3Yrg+//4WSdBq4s6RYqN6GaWq0GDGLwePgRLCl0Zw1/amyDhyaqBr6U2B7zSQlRmJeLcvJSoR6P8w1JaGNq0jUBO6IzDm9CB1OdFsbyU7sQvDXJMfZRL6EvKGRvOHbHIzRpfAbTT4L/zj4FHjB9I/SyRkmT8Y+jIMf6N3Ia8HtFjgNfpPJU2fpyJakS7siG/ous52DXxW2WhS/ZvB9ixX7pGJoxhL4k2Y7At/woa9aEZKqI+qcw2cm7DF+Jvw6kydkGdgCjPebwwD815Kbmpp+CV4ysAxcnXEN/KmaCEl1rXqSIeRuy3cAfszkhxikJl8TyKuVu9GcjsD3SsY2CvlKfA7K92AI9dKqiRB0HzjHgvvgj4bMoA/BnwsZugrdPJMnYtdg8FoHmMBFc94PrwkFPFBPg8JZ1JNLVkGHHxBOhYLi6uLxkKFt6FaYPI7NB5SeJa1sAfiojrZbQCc6bce6oZgIgbqBfFspiTrnnRpEp6IBik9jwhZ0LsztIUAvgVrZAqjxG8LPhaJSuQG+ZoPMN2OLiSC1ge2Jw3cuU1Dnw8+MzKtHRkZqvfLKOV+OOZyEFttVOvLqWvfJNaNLV1GuE4JPZCles83zPHyPycFqIr5KnRSdFcYSuhJdi+k1iX6Tg00bpPNXq0ERl9F0ItPN+jv8MZODVedOhwBdxESWmJyydyWKQ/gPJzqJB8ER03fCX2dyFcskV4CvgM/xbMzxgS+u8ry8GmcSncS4yeJd0HtyB/itjA75yy+bQ9VBN4OuZK1U3IKL4G8Bx/kz+Dnod4CarLZmh6/IVVIapAc9MxGUvi3Sp10PX507PXABWgk/C6EX/RP0sxMNcp+MZyKq5w1a7xPZhfF4HnUC5505X0Z07zusxL/sYbwVJ3Uv4C/8fgzBKQ3Sbabt5VDaIBxuA/38/FNsLRLtYytsgN6N04Hm5uayg54VYTAH85WZkSkqlQ50s+G1NRzUtaIGfA9xf7uD8+Toxu4qnQPdYH65aCtlW8oce7xIhcGrW6UdsyAlko/ufu1hwXx0uvXSiejGctBBV+dLAZuu+4tgbPPlTKQVuZg8ssa8HHTY51vLDZPxp3HwN0Yr43u2QsFxOny6ayUmRg3qM58FeYNMlW3VZabQah2c0kRIruBvLJnYdD/rI9EL6tHzySumCnhY1aDDptTKVDUIWSuvSyRgAKZnShPJM2givnc7GYhv1XbsftBPINfcti0tLcqXXrd3onPQQddqB/Sykn1XMhHdMPrcCFjOSs0NAaoV8olpW50xeynLoNQg/1dBB95vxPSgf9/f33/+Siail9/fBH0J68YLuCcYUQbzJXYfoJsLHh9tP22XAH1wZv/LkENXWkcYcrq/ra1t3Gd84jOxSEHdPuk/RI8ogoLXQu4Vn4O+23aHMAntxe7nROchcrXC+4oMI/sYsuK+DbBPDrw7Gxn0CBign4meAV8LRU734nv15BkvexCjbygHvXGbULwpJXzYDsPPyqLQzANfB7vAlziwlw11VCVJKzGHQU8uMYUX60hXuJB3DQkuKEkMGpqNXiR0mN8oghDeVYDBy0ND+pyqD4h7wWLL2DMo0yu0ZnL8p4MfKpkNWqLL+q1tbZEIQdvBYQ/B/v9D4VvG4LuA4J+UIC2aJ902ODhY9d1RlifVkUv/t6c/4OUpM/IWf/+7rBA+ldoGsR2xocLEbiZGHfI84j8HsxsnHWg9MumeVUrlTeATZH8Usx/I2lF+ASrgAwovrKdI6kPsE2A3KOgD9TvvlCcR+cnxNKgf7QRHwec5x+N+wPsX+f7UoKzjPDEAAAAASUVORK5CYII=" alt="Neptune Docs"></a>\n    <a href="https://neptune.ai/blog"><img src="https://img.shields.io/badge/Neptune-blog-informational?logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADIAAAAgCAYAAABQISshAAAACXBIWXMAAA7DAAAOwwHHb6hkAAAF6klEQVRYCa2YXWiWZRjH301nGWVTa36ESWqb1bTSorSTUg8kwg4iSIhOgo49yDoIOomgjiqQPCroIEGQqA6ighoIZYbZNEtnhU1rUc3U5fzY3Nbv//hcT//33rN37zu74Nr1fV33fd1fz95KpQaMjo7OHBsb2wy+A74HbgXbaoTUZSLHevBj8A/wGLiNWjfVFdyokxJT4CMwhb0obm40X/iT9zHiB9KkyF3Yrg+//4WSdBq4s6RYqN6GaWq0GDGLwePgRLCl0Zw1/amyDhyaqBr6U2B7zSQlRmJeLcvJSoR6P8w1JaGNq0jUBO6IzDm9CB1OdFsbyU7sQvDXJMfZRL6EvKGRvOHbHIzRpfAbTT4L/zj4FHjB9I/SyRkmT8Y+jIMf6N3Ia8HtFjgNfpPJU2fpyJakS7siG/ous52DXxW2WhS/ZvB9ixX7pGJoxhL4k2Y7At/woa9aEZKqI+qcw2cm7DF+Jvw6kydkGdgCjPebwwD815Kbmpp+CV4ysAxcnXEN/KmaCEl1rXqSIeRuy3cAfszkhxikJl8TyKuVu9GcjsD3SsY2CvlKfA7K92AI9dKqiRB0HzjHgvvgj4bMoA/BnwsZugrdPJMnYtdg8FoHmMBFc94PrwkFPFBPg8JZ1JNLVkGHHxBOhYLi6uLxkKFt6FaYPI7NB5SeJa1sAfiojrZbQCc6bce6oZgIgbqBfFspiTrnnRpEp6IBik9jwhZ0LsztIUAvgVrZAqjxG8LPhaJSuQG+ZoPMN2OLiSC1ge2Jw3cuU1Dnw8+MzKtHRkZqvfLKOV+OOZyEFttVOvLqWvfJNaNLV1GuE4JPZCles83zPHyPycFqIr5KnRSdFcYSuhJdi+k1iX6Tg00bpPNXq0ERl9F0ItPN+jv8MZODVedOhwBdxESWmJyydyWKQ/gPJzqJB8ER03fCX2dyFcskV4CvgM/xbMzxgS+u8ry8GmcSncS4yeJd0HtyB/itjA75yy+bQ9VBN4OuZK1U3IKL4G8Bx/kz+Dnod4CarLZmh6/IVVIapAc9MxGUvi3Sp10PX507PXABWgk/C6EX/RP0sxMNcp+MZyKq5w1a7xPZhfF4HnUC5505X0Z07zusxL/sYbwVJ3Uv4C/8fgzBKQ3Sbabt5VDaIBxuA/38/FNsLRLtYytsgN6N04Hm5uayg54VYTAH85WZkSkqlQ50s+G1NRzUtaIGfA9xf7uD8+Toxu4qnQPdYH65aCtlW8oce7xIhcGrW6UdsyAlko/ufu1hwXx0uvXSiejGctBBV+dLAZuu+4tgbPPlTKQVuZg8ssa8HHTY51vLDZPxp3HwN0Yr43u2QsFxOny6ayUmRg3qM58FeYNMlW3VZabQah2c0kRIruBvLJnYdD/rI9EL6tHzySumCnhY1aDDptTKVDUIWSuvSyRgAKZnShPJM2givnc7GYhv1XbsftBPINfcti0tLcqXXrd3onPQQddqB/Sykn1XMhHdMPrcCFjOSs0NAaoV8olpW50xeynLoNQg/1dBB95vxPSgf9/f33/+Siail9/fBH0J68YLuCcYUQbzJXYfoJsLHh9tP22XAH1wZv/LkENXWkcYcrq/ra1t3Gd84jOxSEHdPuk/RI8ogoLXQu4Vn4O+23aHMAntxe7nROchcrXC+4oMI/sYsuK+DbBPDrw7Gxn0CBign4meAV8LRU734nv15BkvexCjbygHvXGbULwpJXzYDsPPyqLQzANfB7vAlziwlw11VCVJKzGHQU8uMYUX60hXuJB3DQkuKEkMGpqNXiR0mN8oghDeVYDBy0ND+pyqD4h7wWLL2DMo0yu0ZnL8p4MfKpkNWqLL+q1tbZEIQdvBYQ/B/v9D4VvG4LuA4J+UIC2aJ902ODhY9d1RlifVkUv/t6c/4OUpM/IWf/+7rBA+ldoGsR2xocLEbiZGHfI84j8HsxsnHWg9MumeVUrlTeATZH8Usx/I2lF+ASrgAwovrKdI6kPsE2A3KOgD9TvvlCcR+cnxNKgf7QRHwec5x+N+wPsX+f7UoKzjPDEAAAAASUVORK5CYII=" alt="neptune-blog"></a>\n    <a href="https://twitter.com/neptune_ai"><img src="https://img.shields.io/twitter/follow/neptune_ai.svg?label=Follow" alt="twitter"></a>\n    <a href="https://www.youtube.com/channel/UCvOJU-ubyUqxGSDRN7xK4Ng"><img src="https://img.shields.io/youtube/views/9iX6DxcijO8?style=social" alt="youtube"></a>\n</div>\n\n## Flexible metadata store for MLOps, built for research and production teams that run a lot of experiments.\n\nNeptune is a lightweight solution designed for:\n\n* **Experiment tracking:** log, display, organize, and compare ML experiments in a single place.\n* **Model registry:** version, store, manage, and query trained models and model-building metadata.\n* **Monitoring ML runs live:** record and monitor model training, evaluation, or production runs live.\n&nbsp;\n\n### Getting started\n\n**Step 1:** Sign up for a **[free account](https://neptune.ai/register)**\n\n**Step 2:** Install the Neptune client library\n\n```bash\npip install neptune-client\n```\n\n**Step 3:** Connect Neptune to your code\n\n```python\nimport neptune.new as neptune\n\nrun = neptune.init_run(\n    project="common/quickstarts",\n    api_token=neptune.ANONYMOUS_API_TOKEN,\n)\n\nrun["parameters"] = {\n    "batch_size": 64,\n    "dropout": 0.2,\n    "optim": {"learning_rate": 0.001, "optimizer": "Adam"},\n}\n\nfor epoch in range(100):\n    run["train/accuracy"].log(epoch * 0.6)\n    run["train/loss"].log(epoch * 0.4)\n\nrun["f1_score"] = 0.66\n```\n\n[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neptune-ai/examples/blob/master/how-to-guides/hello-world/notebooks/Neptune_hello_world.ipynb)\n\n<div align="center">\n    <a href="https://youtu.be/15p-mAuIMlA" target="_blank">\n      <img border="0" alt="W3Schools" src="https://neptune.ai/wp-content/uploads/manage-all-your-model-building-metadat-in-a-single-place.jpg" width="600">\n    </a>\n</div>\n&nbsp;\n\nLearn more in the [documentation](https://docs.neptune.ai/) or check our [video tutorials](https://www.youtube.com/c/NeptuneAI/) to find your specific use case.\n\n### Features\n\n***Log and display***\n\nNeptune [supports log and display](https://docs.neptune.ai/logging/what_you_can_log) for many different types of metadata generated during the ML model lifecycle:\n* metrics and learning curves\n* parameters, tags, and properties\n* code, Git info, files, and Jupyter notebooks\n* hardware consumption (CPU, GPU, memory)\n* images, interactive charts, and HTML objects\n* audio and video files\n* tables and CSV files\n* and [more](https://docs.neptune.ai/logging/what_you_can_log)\n\n<div align="center">\n     <img border="0" alt="W3Schools" src="https://neptune.ai/wp-content/uploads/Log-and-display.gif" width="600">\n</div>\n&nbsp;\n\n***Compare***\n\nYou can [compare model-building runs](https://docs.neptune.ai/app/comparison) you log to Neptune using various comparison views:\n* **Charts:** where you can compare learning curves for metrics or losses\n* **Images:** where you can compare images across runs\n* **Parallel coordinates:** where you can see parameters and metrics displayed on a parallel coordinates plot\n* **Side-by-side:** which shows you the difference between runs in a table format\n* **Artifacts:** where you can compare datasets, models, and other artifacts that you version in Neptune\n* **Notebooks:** which shows you the difference between notebooks (or checkpoints of the same notebook) logged to the project\n\n<div align="center">\n     <img border="0" alt="W3Schools" src="https://neptune.ai/wp-content/uploads/Compare.gif" width="600">\n</div>\n&nbsp;\n\n***Filter and organize***\n\nFilter, sort, and group model training runs using [highly configurable dashboards](https://docs.neptune.ai/app/custom_dashboard/).\n\n<div align="center">\n     <img border="0" alt="W3Schools" src="https://neptune.ai/wp-content/uploads/Filter-and-organize-3688604602-1644927778194.png" width="600">\n</div>\n&nbsp;\n\n***Collaborate***\n\nImprove [team management and collaboration](https://docs.neptune.ai/about/collaboration/) by grouping all experiments into projects and workspaces and quickly sharing any result or visualization within the team.\n\n<div align="center">\n     <img border="0" alt="W3Schools" src="https://neptune.ai/wp-content/uploads/Collaboration.gif" width="600">\n</div>\n&nbsp;\n\n### Integrate with your favourite ML libraries\nNeptune comes with **25+ integrations with Python libraries** popular in machine learning, deep learning and reinforcement learning.\nAvailable integrations:\n* PyTorch and PyTorch Lightning\n* TensorFlow / Keras and TensorBoard\n* Scikit-learn, LightGBM, and XGBoost\n* Optuna, Scikit-Optimize, and Keras Tuner\n* Bokeh, Altair, Plotly, and Matplotlib\n* and [more](https://docs.neptune.ai/integrations)\n\n#### PyTorch Lightning\n\n<img src="https://neptune.ai/wp-content/uploads/PyTorch-Lightning.png" width="350" /><br><br>\n\nExample:\n\n```python\nfrom pytorch_lightning import Trainer\nfrom pytorch_lightning.loggers import NeptuneLogger\n\n# Create NeptuneLogger\nneptune_logger = NeptuneLogger(\n    api_key="ANONYMOUS",  # replace with your own\n    project="common/pytorch-lightning-integration",  # "WORKSPACE_NAME/PROJECT_NAME"\n    tags=["training", "resnet"],  # optional\n)\n\n# Pass it to the Trainer\ntrainer = Trainer(max_epochs=10, logger=neptune_logger)\n\n# Run training\ntrainer.fit(my_model, my_dataloader)\n```\n\n[![neptune-pl](https://img.shields.io/badge/PytorchLightning-experiment-success?logo=data:image/png;base64,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)](https://app.neptune.ai/common/pytorch-lightning-integration/experiments?split=tbl&dash=charts&viewId=faa75e77-5bd6-42b9-9379-863fe7a33227)\n&nbsp;\n\n[![github-code](https://img.shields.io/badge/GitHub-code-informational?logo=github)](https://github.com/neptune-ai/examples/tree/main/integrations-and-supported-tools/pytorch-lightning/scripts)\n[![jupyter-code](https://img.shields.io/badge/Jupyter-code-informational?logo=jupyter)](https://github.com/neptune-ai/examples/blob/main/integrations-and-supported-tools/pytorch-lightning/notebooks/Neptune_PyTorch_Lightning.ipynb)\n[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neptune-ai/examples/blob/main/integrations-and-supported-tools/pytorch-lightning/notebooks/Neptune_PyTorch_Lightning.ipynb)\n[<img src="https://img.shields.io/badge/docs-PyTorch%20Lightning-yellow">](https://docs.neptune.ai/integrations/lightning/)\n\n#### TensorFow/Keras\n\n<img src="https://neptune.ai/wp-content/uploads/TensorFowKeras.png" width="400" /><br><br>\n\nExample:\n\n```python\nimport tensorflow as tf\nimport neptune.new as neptune\nfrom neptune.new.integrations.tensorflow_keras import NeptuneCallback\n\nrun = neptune.init_run(\n    project="common/tf-keras-integration",\n    api_token=neptune.ANONYMOUS_API_TOKEN,\n)\n\nmnist = tf.keras.datasets.mnist\n(x_train, y_train), (x_test, y_test) = mnist.load_data()\nx_train, x_test = x_train / 255.0, x_test / 255.0\n\nmodel = tf.keras.models.Sequential(\n    [\n        tf.keras.layers.Flatten(),\n        tf.keras.layers.Dense(256, activation=tf.keras.activations.relu),\n        tf.keras.layers.Dropout(0.5),\n        tf.keras.layers.Dense(10, activation=tf.keras.activations.softmax),\n    ]\n)\n\noptimizer = tf.keras.optimizers.SGD(\n    learning_rate=0.005,\n    momentum=0.4,\n)\n\nmodel.compile(\n    optimizer=optimizer, loss="sparse_categorical_crossentropy", metrics=["accuracy"]\n)\n\nneptune_cbk = NeptuneCallback(run=run, base_namespace="metrics")\nmodel.fit(x_train, y_train, epochs=5, batch_size=64, callbacks=[neptune_cbk])\n```\n\n[![neptune-pl](https://img.shields.io/badge/TF/Keras-experiment-success?logo=data:image/png;base64,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)](https://app.neptune.ai/common/tf-keras-integration/e/TFK-18/all)\n&nbsp;\n\n[![github-code](https://img.shields.io/badge/GitHub-code-informational?logo=github)](https://github.com/neptune-ai/examples/tree/main/integrations-and-supported-tools/tensorflow-keras/scripts)\n[![jupyter-code](https://img.shields.io/badge/Jupyter-code-informational?logo=jupyter)](https://github.com/neptune-ai/examples/blob/main/integrations-and-supported-tools/tensorflow-keras/notebooks/Neptune_TensorFlow_Keras.ipynb)\n[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neptune-ai/examples/blob/master/integrations-and-supported-tools/tensorflow-keras/notebooks/Neptune_TensorFlow_Keras.ipynb)\n[<img src="https://img.shields.io/badge/docs-TensorFow%2FKeras-yellow">](https://docs.neptune.ai/integrations/keras/)\n\n#### Scikit-learn\n\n<img src="https://neptune.ai/wp-content/uploads/Scikit-learn.png" width="200" /><br><br>\n\nExample:\n\n```python\nfrom sklearn.datasets import load_digits\nfrom sklearn.ensemble import GradientBoostingClassifier\nfrom sklearn.model_selection import train_test_split\nimport neptune.new as neptune\nimport neptune.new.integrations.sklearn as npt_utils\n\nrun = neptune.init_run(\n    project="common/sklearn-integration",\n    api_token=neptune.ANONYMOUS_API_TOKEN,\n    name="classification-example",\n    tags=["GradientBoostingClassifier", "classification"],\n)\n\nparameters = {\n    "n_estimators": 120,\n    "learning_rate": 0.12,\n    "min_samples_split": 3,\n    "min_samples_leaf": 2,\n}\n\ngbc = GradientBoostingClassifier(**parameters)\n\nX, y = load_digits(return_X_y=True)\nX_train, X_test, y_train, y_test = train_test_split(\n    X, y, test_size=0.20, random_state=28743\n)\n\ngbc.fit(X_train, y_train)\n\nrun["cls_summary"] = npt_utils.create_classifier_summary(\n    gbc, X_train, X_test, y_train, y_test\n)\n```\n\n[![neptune-pl](https://img.shields.io/badge/sklearn-experiment-success?logo=data:image/png;base64,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)](https://app.neptune.ai/common/sklearn-integration/e/SKLEAR-97/all?path=rfr_summary%2Fdiagnostics_charts&attribute=feature_importance)\n&nbsp;\n\n[![github-code](https://img.shields.io/badge/GitHub-code-informational?logo=github)](https://github.com/neptune-ai/examples/tree/main/integrations-and-supported-tools/sklearn/scripts)\n[![jupyter-code](https://img.shields.io/badge/Jupyter-code-informational?logo=jupyter)](https://github.com/neptune-ai/examples/blob/main/integrations-and-supported-tools/sklearn/notebooks/Neptune_Scikit_learn.ipynb)\n[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neptune-ai/examples/blob/master/integrations-and-supported-tools/sklearn/notebooks/Neptune_Scikit_learn.ipynb)\n[<img src="https://img.shields.io/badge/docs-Scikit--learn-yellow">](https://docs.neptune.ai/integrations/sklearn/)\n\n#### fastai\n\n<img src="https://neptune.ai/wp-content/uploads/fastai-1.png" width="150" /><br><br>\n\nExample:\n\n```python\nimport fastai\nfrom neptune.new.integrations.fastai import NeptuneCallback\nfrom fastai.vision.all import *\nimport neptune.new as neptune\n\nrun = neptune.init_run(\n    project="common/fastai-integration",\n    api_token=neptune.ANONYMOUS_API_TOKEN,\n    tags="basic",\n)\n\npath = untar_data(URLs.MNIST_TINY)\ndls = ImageDataLoaders.from_csv(path)\n\n# Log all training phases of the learner\nlearn = cnn_learner(\n    dls, resnet18, cbs=[NeptuneCallback(run=run, base_namespace="experiment")]\n)\nlearn.fit_one_cycle(2)\nlearn.fit_one_cycle(1)\n\nrun.stop()\n```\n\n[![neptune-pl](https://img.shields.io/badge/fastai-experiment-success?logo=data:image/png;base64,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)](https://app.neptune.ai/common/fastai-integration/e/FAS-61/dashboard/fastai-dashboard-1f456716-f509-4432-b8b3-a7f5242703b6)\n&nbsp;\n\n[![github-code](https://img.shields.io/badge/GitHub-code-informational?logo=github)](https://github.com/neptune-ai/examples/tree/main/integrations-and-supported-tools/fastai/scripts)\n[![jupyter-code](https://img.shields.io/badge/Jupyter-code-informational?logo=jupyter)](https://github.com/neptune-ai/examples/blob/main/integrations-and-supported-tools/fastai/notebooks/Neptune_fastai.ipynb)\n[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neptune-ai/examples/blob/main/integrations-and-supported-tools/fastai/notebooks/Neptune_fastai.ipynb)\n[<img src="https://img.shields.io/badge/docs-fastai-yellow">](https://docs.neptune.ai/integrations/fastai/)\n\n#### Optuna\n\n<img src="https://neptune.ai/wp-content/uploads/Optuna-1.png" width="300" /><br><br>\n\nExample:\n\n```python\nimport lightgbm as lgb\nimport neptune.new as neptune\nimport neptune.new.integrations.optuna as optuna_utils\nimport optuna\nfrom sklearn.datasets import load_breast_cancer\nfrom sklearn.metrics import roc_auc_score\nfrom sklearn.model_selection import train_test_split\n\ndef objective(trial):\n    data, target = load_breast_cancer(return_X_y=True)\n    train_x, test_x, train_y, test_y = train_test_split(data, target, test_size=0.25)\n    dtrain = lgb.Dataset(train_x, label=train_y)\n\n    param = {\n        "verbose": -1,\n        "objective": "binary",\n        "metric": "binary_logloss",\n        "num_leaves": trial.suggest_int("num_leaves", 2, 256),\n        "feature_fraction": trial.suggest_uniform("feature_fraction", 0.2, 1.0),\n        "bagging_fraction": trial.suggest_uniform("bagging_fraction", 0.2, 1.0),\n        "min_child_samples": trial.suggest_int("min_child_samples", 3, 100),\n    }\n\n    gbm = lgb.train(param, dtrain)\n    preds = gbm.predict(test_x)\n    accuracy = roc_auc_score(test_y, preds)\n\n    return accuracy\n\n\n# Create a Neptune run\nrun = neptune.init_run(\n    api_token=neptune.ANONYMOUS_API_TOKEN,\n    project="common/optuna-integration",\n)\n\n# Create a NeptuneCallback for Optuna\nneptune_callback = optuna_utils.NeptuneCallback(run)\n\n# Pass NeptuneCallback to Optuna Study .optimize()\nstudy = optuna.create_study(direction="maximize")\nstudy.optimize(objective, n_trials=20, callbacks=[neptune_callback])\n\n# Stop logging to the run\nrun.stop()\n```\n\n[![neptune-pl](https://img.shields.io/badge/Optuna-experiment-success?logo=data:image/png;base64,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)](https://app.neptune.ai/common/optuna-integration/experiments?split=bth&dash=parallel-coordinates-plot&viewId=b6190a29-91be-4e64-880a-8f6085a6bb78)\n&nbsp;\n\n[![github-code](https://img.shields.io/badge/GitHub-code-informational?logo=github)](https://github.com/neptune-ai/examples/tree/main/integrations-and-supported-tools/optuna/scripts)\n[![jupyter-code](https://img.shields.io/badge/Jupyter-code-informational?logo=jupyter)](https://github.com/neptune-ai/examples/blob/main/integrations-and-supported-tools/optuna/notebooks/Neptune_Optuna_integration.ipynb)\n[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neptune-ai/examples/blob/master/integrations-and-supported-tools/optuna/notebooks/Neptune_Optuna_integration.ipynb)\n[<img src="https://img.shields.io/badge/docs-Optuna-yellow">](https://docs.neptune.ai/integrations/optuna/)\n\n### Neptune.ai is trusted by great companies\n&nbsp;\n\n<div align="center">\n    <img src="https://neptune.ai/wp-content/uploads/Neptune-customers.png" width="900" />\n</div>\n&nbsp;\n\nRead how various customers use Neptune to [improve their workflow](https://neptune.ai/customers).\n\n### Support\n\nIf you get stuck or simply want to talk to us about something, here are your options:\n* Check our [FAQ page](https://docs.neptune.ai/getting_help/).\n* Chat! In the app, click the blue message icon in the bottom-right corner and send a message. A real person will talk to you ASAP (typically very ASAP).\n* You can just shoot us an email at [support@neptune.ai](mailto:support@neptune.ai).\n\n### People behind Neptune\n\nCreated with :heart: by the [Neptune.ai team](https://neptune.ai/about-us):\n\nPiotr, Jakub, Paulina, Kamil, Magdalena, Małgorzata, Piotr, Aleksandra, Marcin, Hubert, Adam, Jakub, Paweł, Patrycja, Marcin, Jakub, Prince, Rafał, Dominika, Karolina, Parth, Rafał, Stephen, Sabine, Martyna, Artur, Franciszek, Aleksiej, Kshiteej, Tomasz, Tymoteusz, Piotr, Chaz, Michał, Siddhant, Karolina, Valentina, Bartosz, Alexandra, Patryk, Aleksander, and [you?](https://neptune.ai/jobs)\n',
    'author': 'neptune.ai',
    'author_email': 'contact@neptune.ai',
    'maintainer': 'None',
    'maintainer_email': 'None',
    'url': 'https://neptune.ai/',
    'package_dir': package_dir,
    'packages': packages,
    'package_data': package_data,
    'install_requires': install_requires,
    'extras_require': extras_require,
    'entry_points': entry_points,
    'python_requires': '>=3.7,<4.0',
}


setup(**setup_kwargs)
