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Feature/structured data tutorial #45
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This changes types.FloatInput to use tf.float32 for its feature_spec attribute to address potential incompatibility with using tf.float64 type in TensorFlow Transform.
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* Update check_tfrecords to use new dataset load function. * Add tfrecord_dir to create_tfrecords output. * Restructure test image directory to match expected format. * Feature/dataclass (#44) * Added data classes for types. * Checking in progress. * Checking in more changes. * Converted types to classes and refactored schema into OO pattern. * Changed OrderedDict import to support py3.6. * Changed OrderedDict import to support py3.6. * Updated setup.py for version. * fixing setup.py * Patched requirements and setup. * Addressed comments in code review. * Addressed code comments round 2. * refactored IMAGE_CSV_SCHEMA. * Merged check_test.py from dev Co-authored-by: Carlos Ezequiel <cezequiel@google.com> * Feature/structured data tutorial (#45) * Converted types to classes and refactored schema into OO pattern. * Add tutorial on structured data conversion. This changes types.FloatInput to use tf.float32 for its feature_spec attribute to address potential incompatibility with using tf.float64 type in TensorFlow Transform. Co-authored-by: Mike Bernico <mikebernico@google.com> * Update structured data tutorial to use output dir. * Clarify need for proper header when using create_tfrecords. Fixes #47. * Clean up README and update image directory notebook. * Feature/test image dir (#49) * Restructure test image directory to match expected format. * Clean up README and update image directory notebook. * Fix minor issues * Add an explicit error message for missing train split * Configure automated tests for Jupyter notebooks. * Add convert_and_load function. Also refactor create_tfrecords to convert. * Refactor check and common modules to utils. * Add test targets for py files and notebooks. * Feature/convert and load (#55) * Add convert_and_load function. Also refactor create_tfrecords to convert. * Refactor check and common modules to utils. * Add test targets for py files and notebooks. * Update version in setup.py and release notes. * Fix issues with GCS path parsing. Co-authored-by: Mike Bernico <mikebernico@google.com> Co-authored-by: Sergii Khomenko <khomenko@brainscode.com>
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Description
Add a Jupyter notebook tutorial on converting structured data to TFRecords.
This also changes types.FloatInput to use tf.float32 for its feature_spec
attribute to address potential incompatibility with using tf.float64
type in TensorFlow Transform.
Type of change
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Checklist
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make pylintand code is rated 10/10make testand all tests pass