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        "author": "JinQing Lee",
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            "Framework :: Jupyter",
            "Intended Audience :: Developers",
            "Intended Audience :: Education",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: Apache Software License",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Scientific/Engineering :: Visualization"
        ],
        "description": "![](https://github.com/Hourout/tensorview/blob/master/image/tensorview.png)\n\nDynamic visualization training service in Jupyter Notebook for Keras, tf.keras and others.\n\n\n![PyPI version](https://img.shields.io/pypi/pyversions/tensorview.svg)\n![Github license](https://img.shields.io/github/license/Hourout/tensorview.svg)\n[![PyPI](https://img.shields.io/pypi/v/tensorview.svg)](https://pypi.python.org/pypi/tensorview)\n![PyPI format](https://img.shields.io/pypi/format/tensorview.svg)\n![contributors](https://img.shields.io/github/contributors/Hourout/tensorview)\n![downloads](https://img.shields.io/pypi/dm/tensorview.svg)\n\nTensorview is efficient visualization training packages of Keras, enabling the live visualization of loss function and metrics during training process.\n\nTensorview is process in the Jupyter Notebook, so we recommend Jupyter Notebook as Tensorview's developing environment.\n\n![](https://github.com/Hourout/beefly/blob/master/image/plot_metrics000.gif)\n\n| [API Document](https://github.com/Hourout/tensorview/blob/master/document/English_API.md) | [API\u6587\u6863](https://github.com/Hourout/tensorview/blob/master/document/Chinese_API.md) | [\u4e2d\u6587\u4ecb\u7ecd](https://github.com/Hourout/tensorview/blob/master/document/Chinese.md) |\n\n## Installation\n\nTo install [this verson from PyPI](https://pypi.org/project/beefly/), type:\n\n```\npip install tensorview\n```\n\nTo get the newest one from this repo (note that we are in the alpha stage, so there may be frequent updates), type:\n\n```\npip install git+git://github.com/Hourout/tensorview.git\n```\n\n## Feature\n- Visualization of general machine learning training\n  - Support customizing the name of loss function and metric \n  - Support customizing the name of validation set\n  - Support displaying the result of training set and test set in the same plot\n  - Support setting maximum training number of iterations\n  - Support both batch way and epoch way to train\n  - Support visual plotting\n  - Support visual plotting in both batch way and epoch way periodically\n\n- keras backend\n  - Support customizing the name of loss function and metric in epoch way\n  - Support customizing the name of validation set in epoch way\n  - Support displaying the result of training set and test set in the same plot in epoch way\n  - Support setting maximum training number of iterations in epoch way\n  - Support visual plotting in epoch way\n  - Support visual plotting in both batch way and epoch way periodically in epoch way\n  - Support customizing the name of loss function and metric in batch way\n  - Support customizing the name of validation set in batch way\n  - Support displaying the result of training set and test set in the same plot in batch way\n  - Support setting maximum training number of iterations in batch way\n  - Support visual plotting in batch way\n  - Support visual plotting in both batch way and epoch way periodically in batch way\n\n\n## Example\n\n[more example](https://github.com/Hourout/tensorview/blob/master/example/readme.md)\n\n- [tensorview.train.PlotMetrics()](https://github.com/Hourout/tensorview/blob/master/example/tv.train.plot_metrics.ipynb)\n- [tensorview.train.PlotMetricsOnBatch()](https://github.com/Hourout/tensorview/blob/master/example/PlotMetricsOnBatch.ipynb)\n- [tensorview.train.PlotMetricsOnEpoch()](https://github.com/Hourout/tensorview/blob/master/example/PlotMetricsOnEpoch.ipynb)\n\n\n",
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        "license": "Apache License Version 2.0",
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