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    "info": {
        "author": "Google Inc.",
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        "description": "<!-- See: www.tensorflow.org/tfx/transform/ -->\n\n# TensorFlow Transform\n\n[![Python](https://img.shields.io/pypi/pyversions/tensorflow-transform.svg?style=plastic)](https://github.com/tensorflow/transform)\n[![PyPI](https://badge.fury.io/py/tensorflow-transform.svg)](https://badge.fury.io/py/tensorflow-transform)\n[![Documentation](https://img.shields.io/badge/api-reference-blue.svg)](https://www.tensorflow.org/tfx/transform/api_docs/python/tft)\n\n*TensorFlow Transform* is a library for preprocessing data with TensorFlow.\n`tf.Transform` is useful for data that requires a full-pass, such as:\n\n* Normalize an input value by mean and standard deviation.\n* Convert strings to integers by generating a vocabulary over all input values.\n* Convert floats to integers by assigning them to buckets based on the observed\n  data distribution.\n\nTensorFlow has built-in support for manipulations on a single example or a batch\nof examples. `tf.Transform` extends these capabilities to support full-passes\nover the example data.\n\nThe output of `tf.Transform` is exported as a\n[TensorFlow graph](http://tensorflow.org/guide/graphs) to use for training and serving.\nUsing the same graph for both training and serving can prevent skew since the\nsame transformations are applied in both stages.\n\nFor an introduction to `tf.Transform`, see the `tf.Transform` section of the\nTFX Dev Summit talk on TFX\n([link](https://www.youtube.com/watch?v=vdG7uKQ2eKk&feature=youtu.be&t=199)).\n\nCaution: `tf.Transform` may be backwards incompatible before version 1.0.\n\n## Installation\n\nThe `tensorflow-transform`\n[PyPI package](https://pypi.org/project/tensorflow-transform/) is the\nrecommended way to install `tf.Transform`:\n\n```bash\npip install tensorflow-transform\n```\n\n### Build TFT from source\n\nTo build from source follow the following steps:\nCreate a virtual environment by running the commands\n\n```\npython3 -m venv <virtualenv_name>\nsource <virtualenv_name>/bin/activate\npip3 install setuptools wheel\ngit clone https://github.com/tensorflow/transform.git\ncd transform\npython3 setup.py bdist_wheel\n```\n\nThis will build the TFT wheel in the dist directory. To install the wheel from\ndist directory run the commands\n\n```\ncd dist\npip3 install tensorflow_transform-<version>-py3-none-any.whl\n```\n\n### Nightly Packages\n\nTFT also hosts nightly packages at https://pypi-nightly.tensorflow.org on\nGoogle Cloud. To install the latest nightly package, please use the following\ncommand:\n\n```bash\npip install --extra-index-url https://pypi-nightly.tensorflow.org/simple tensorflow-transform\n```\n\nThis will install the nightly packages for the major dependencies of TFT such\nas TensorFlow Metadata (TFMD), TFX Basic Shared Libraries (TFX-BSL).\n\n### Notable Dependencies\n\nTensorFlow is required.\n\n[Apache Beam](https://beam.apache.org/) is required; it's the way that efficient\ndistributed computation is supported. By default, Apache Beam runs in local\nmode but can also run in distributed mode using\n[Google Cloud Dataflow](https://cloud.google.com/dataflow/) and other Apache\nBeam\n[runners](https://beam.apache.org/documentation/runners/capability-matrix/).\n\n[Apache Arrow](https://arrow.apache.org/) is also required. TFT uses Arrow to\nrepresent data internally in order to make use of vectorized numpy functions.\n\n## Compatible versions\n\nThe following table is the `tf.Transform` package versions that are\ncompatible with each other. This is determined by our testing framework, but\nother *untested* combinations may also work.\n\ntensorflow-transform                                                            | apache-beam[gcp] | pyarrow | tensorflow        | tensorflow-metadata | tfx-bsl |\n------------------------------------------------------------------------------- | -----------------| --------|-------------------|---------------------|---------|\n[GitHub master](https://github.com/tensorflow/transform/blob/master/RELEASE.md) | 2.38.0           | 5.0.0   | nightly (1.x/2.x) | 1.8.0               | 1.8.0   |\n[1.8.0](https://github.com/tensorflow/transform/blob/v1.8.0/RELEASE.md)         | 2.38.0           | 5.0.0   | 1.15.5 / 2.8      | 1.8.0               | 1.8.0   |\n[1.7.0](https://github.com/tensorflow/transform/blob/v1.7.0/RELEASE.md)         | 2.36.0           | 5.0.0   | 1.15.5 / 2.8      | 1.7.0               | 1.7.0   |\n[1.6.1](https://github.com/tensorflow/transform/blob/v1.6.1/RELEASE.md)         | 2.35.0           | 5.0.0   | 1.15.5 / 2.8      | 1.6.0               | 1.6.0   |\n[1.6.0](https://github.com/tensorflow/transform/blob/v1.6.0/RELEASE.md)         | 2.35.0           | 5.0.0   | 1.15.5 / 2.7      | 1.6.0               | 1.6.0   |\n[1.5.0](https://github.com/tensorflow/transform/blob/v1.5.0/RELEASE.md)         | 2.34.0           | 5.0.0   | 1.15.2 / 2.7      | 1.5.0               | 1.5.0   |\n[1.4.1](https://github.com/tensorflow/transform/blob/v1.4.1/RELEASE.md)         | 2.33.0           | 4.0.1   | 1.15.2 / 2.6      | 1.4.0               | 1.4.0   |\n[1.4.0](https://github.com/tensorflow/transform/blob/v1.4.0/RELEASE.md)         | 2.33.0           | 4.0.1   | 1.15.2 / 2.6      | 1.4.0               | 1.4.0   |\n[1.3.0](https://github.com/tensorflow/transform/blob/v1.3.0/RELEASE.md)         | 2.31.0           | 2.0.0   | 1.15.2 / 2.6      | 1.2.0               | 1.3.0   |\n[1.2.0](https://github.com/tensorflow/transform/blob/v1.2.0/RELEASE.md)         | 2.31.0           | 2.0.0   | 1.15.2 / 2.5      | 1.2.0               | 1.2.0   |\n[1.1.1](https://github.com/tensorflow/transform/blob/v1.1.1/RELEASE.md)         | 2.29.0           | 2.0.0   | 1.15.2 / 2.5      | 1.1.0               | 1.1.1   |\n[1.1.0](https://github.com/tensorflow/transform/blob/v1.1.0/RELEASE.md)         | 2.29.0           | 2.0.0   | 1.15.2 / 2.5      | 1.1.0               | 1.1.0   |\n[1.0.0](https://github.com/tensorflow/transform/blob/v1.0.0/RELEASE.md)         | 2.29.0           | 2.0.0   | 1.15 / 2.5        | 1.0.0               | 1.0.0   |\n[0.30.0](https://github.com/tensorflow/transform/blob/v0.30.0/RELEASE.md)       | 2.28.0           | 2.0.0   | 1.15 / 2.4        | 0.30.0              | 0.30.0  |\n[0.29.0](https://github.com/tensorflow/transform/blob/v0.29.0/RELEASE.md)       | 2.28.0           | 2.0.0   | 1.15 / 2.4        | 0.29.0              | 0.29.0  |\n[0.28.0](https://github.com/tensorflow/transform/blob/v0.28.0/RELEASE.md)       | 2.28.0           | 2.0.0   | 1.15 / 2.4        | 0.28.0              | 0.28.1  |\n[0.27.0](https://github.com/tensorflow/transform/blob/v0.27.0/RELEASE.md)       | 2.27.0           | 2.0.0   | 1.15 / 2.4        | 0.27.0              | 0.27.0  |\n[0.26.0](https://github.com/tensorflow/transform/blob/v0.26.0/RELEASE.md)       | 2.25.0           | 0.17.0  | 1.15 / 2.3        | 0.26.0              | 0.26.0  |\n[0.25.0](https://github.com/tensorflow/transform/blob/v0.25.0/RELEASE.md)       | 2.25.0           | 0.17.0  | 1.15 / 2.3        | 0.25.0              | 0.25.0  |\n[0.24.1](https://github.com/tensorflow/transform/blob/v0.24.1/RELEASE.md)       | 2.24.0           | 0.17.0  | 1.15 / 2.3        | 0.24.0              | 0.24.1  |\n[0.24.0](https://github.com/tensorflow/transform/blob/v0.24.0/RELEASE.md)       | 2.23.0           | 0.17.0  | 1.15 / 2.3        | 0.24.0              | 0.24.0  |\n[0.23.0](https://github.com/tensorflow/transform/blob/v0.23.0/RELEASE.md)       | 2.23.0           | 0.17.0  | 1.15 / 2.3        | 0.23.0              | 0.23.0  |\n[0.22.0](https://github.com/tensorflow/transform/blob/v0.22.0/RELEASE.md)       | 2.20.0           | 0.16.0  | 1.15 / 2.2        | 0.22.0              | 0.22.0  |\n[0.21.2](https://github.com/tensorflow/transform/blob/v0.21.2/RELEASE.md)       | 2.17.0           | 0.15.0  | 1.15 / 2.1        | 0.21.0              | 0.21.3  |\n[0.21.0](https://github.com/tensorflow/transform/blob/v0.21.0/RELEASE.md)       | 2.17.0           | 0.15.0  | 1.15 / 2.1        | 0.21.0              | 0.21.0  |\n[0.15.0](https://github.com/tensorflow/transform/blob/v0.15.0/RELEASE.md)       | 2.16.0           | 0.14.0  | 1.15 / 2.0        | 0.15.0              | 0.15.0  |\n[0.14.0](https://github.com/tensorflow/transform/blob/v0.14.0/RELEASE.md)       | 2.14.0           | 0.14.0  | 1.14              | 0.14.0              | n/a     |\n[0.13.0](https://github.com/tensorflow/transform/blob/v0.13.0/RELEASE.md)       | 2.11.0           | n/a     | 1.13              | 0.12.1              | n/a     |\n[0.12.0](https://github.com/tensorflow/transform/blob/v0.12.0/RELEASE.md)       | 2.10.0           | n/a     | 1.12              | 0.12.0              | n/a     |\n[0.11.0](https://github.com/tensorflow/transform/blob/v0.11.0/RELEASE.md)       | 2.8.0            | n/a     | 1.11              | 0.9.0               | n/a     |\n[0.9.0](https://github.com/tensorflow/transform/blob/v0.9.0/RELEASE.md)         | 2.6.0            | n/a     | 1.9               | 0.9.0               | n/a     |\n[0.8.0](https://github.com/tensorflow/transform/blob/v0.8.0/RELEASE.md)         | 2.5.0            | n/a     | 1.8               | n/a                 | n/a     |\n[0.6.0](https://github.com/tensorflow/transform/blob/v0.6.0/RELEASE.md)         | 2.4.0            | n/a     | 1.6               | n/a                 | n/a     |\n[0.5.0](https://github.com/tensorflow/transform/blob/v0.5.0/RELEASE.md)         | 2.3.0            | n/a     | 1.5               | n/a                 | n/a     |\n[0.4.0](https://github.com/tensorflow/transform/blob/v0.4.0/RELEASE.md)         | 2.2.0            | n/a     | 1.4               | n/a                 | n/a     |\n[0.3.1](https://github.com/tensorflow/transform/blob/v0.3.1/RELEASE.md)         | 2.1.1            | n/a     | 1.3               | n/a                 | n/a     |\n[0.3.0](https://github.com/tensorflow/transform/blob/v0.3.0/RELEASE.md)         | 2.1.1            | n/a     | 1.3               | n/a                 | n/a     |\n[0.1.10](https://github.com/tensorflow/transform/blob/v0.1.10/RELEASE.md)       | 2.0.0            | n/a     | 1.0               | n/a                 | n/a     |\n\n## Questions\n\nPlease direct any questions about working with `tf.Transform` to\n[Stack Overflow](https://stackoverflow.com) using the\n[tensorflow-transform](https://stackoverflow.com/questions/tagged/tensorflow-transform)\ntag.\n",
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