Machine-learning-data-lifecycle-in-production - issue with C2_W1_Lab_1

Course Q&A Machine Learning Engineering for Production(MLOps) Machine Learning Data Lifecycle in Production
1

Convert dataframe to CSV since slice_functions works only with tfdv.generate_statistics_from_csv

CSV_PATH = ‘slice_sample.csv’

train_df.to_csv(CSV_PATH)

​

Calculate statistics for the sliced dataset

sliced_stats = tfdv.generate_statistics_from_csv(CSV_PATH, stats_options=slice_stats_options)

WARNING:root:Make sure that locally built Python SDK docker image has Python 3.8 interpreter.

WARNING:tensorflow:From /opt/conda/lib/python3.8/site-packages/tensorflow_data_validation/utils/stats_util.py:247: tf_record_iterator (from tensorflow.python.lib.io.tf_record) is deprecated and will be removed in a future version. Instructions for updating: Use eager execution and: tf.data.TFRecordDataset(path)

WARNING:tensorflow:From /opt/conda/lib/python3.8/site-packages/tensorflow_data_validation/utils/stats_util.py:247: tf_record_iterator (from tensorflow.python.lib.io.tf_record) is deprecated and will be removed in a future version. Instructions for updating: Use eager execution and: tf.data.TFRecordDataset(path)

2

Hi Samara! Are you still having issues with this? Can you please explain the problem you are facing? Thanks!

3

Just want to clarify that these are warning messages. It doesn’t hinder from continuing the nb

4

I’ve updated the title of this thread to be a general description without the notebook URL.