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        "author": "Shkarupa Alex",
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            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Software Development",
            "Topic :: Software Development :: Libraries",
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        "description": "# tf1\n\nF1-score metrics for classification models in TensorFlow.\nThere are 3 average modes provided:\n- binary\n- macro\n- micro\n\n## Usage\n\n```python\nfrom tf1 import f1_binary\n\n# use f1_binary as any other metric from tf.metrics.*\n```\n\nNote, that due to streaming nature of metric computation process,\n\"macro\" and \"micro\" average metrics should know total number of\nclasses. Use them as follows:\n\n```python\nfrom tf1 import f1_macro, f1_micro\n\ndef my_task_f1_macro(\n    labels, predictions, num_classes, weights=None,\n    metrics_collections=None, updates_collections=None,\n    name=None):\n\n    return f1_macro(\n        labels=labels,\n        predictions=predictions,\n        num_classes=123,  # Required\n        weights=weights,\n        metrics_collections=metrics_collections,\n        updates_collections=updates_collections,\n        name=name\n    )\n\n# use my_task_f1_macro as any other metric from tf.metrics.*\n```",
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