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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# import required libs\n",
"import glob\n",
"import os\n",
"\n",
"import tensorflow as tf\n",
"import tensorflow_model_analysis as tfma\n",
"print('TF version: {}'.format(tf.version.VERSION))\n",
"print('TFMA version: {}'.format(tfma.version.VERSION_STRING))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Read artifact information from metadata store.\n",
"import beam_dag_runner\n",
"\n",
"from tfx.orchestration import metadata\n",
"from tfx.types import standard_artifacts\n",
"\n",
"metadata_connection_config = metadata.sqlite_metadata_connection_config(\n",
" beam_dag_runner.METADATA_PATH)\n",
"with metadata.Metadata(metadata_connection_config) as store:\n",
" model_eval_artifacts = store.get_artifacts_by_type(standard_artifacts.ModelEvaluation.TYPE_NAME)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# configure output paths\n",
"# Exact paths to output artifacts can be found in the execution logs\n",
"# or KFP Web UI if you are using kubeflow.\n",
"model_eval_path = model_eval_artifacts[-1].uri\n",
"print(\"Generated model evaluation result:{}\".format(model_eval_path))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Install Jupyter Extensions\n",
"Note: If running in a local Jupyter notebook, then these Jupyter extensions must be installed in the environment before running Jupyter.\n",
"\n",
"```bash\n",
"jupyter nbextension enable --py widgetsnbextension\n",
"jupyter nbextension install --py --symlink tensorflow_model_analysis\n",
"jupyter nbextension enable --py tensorflow_model_analysis\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"eval_result = tfma.load_eval_result(model_eval_path)\n",
"tfma.view.render_slicing_metrics(eval_result, slicing_spec = tfma.slicer.SingleSliceSpec(columns=['trip_start_hour']))"
]
}
],
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"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
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"name": "ipython",
"version": 3
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.5rc1"
},
"pycharm": {
"stem_cell": {
"cell_type": "raw",
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