Scripts¶
Standalone Processing Examples¶
Using Scaler Train and Test Helper¶
Train a DNN using the Scaler-Normalized AntiNex Django Dataset. This builds the train and test datasets using the antinex_utils.build_scaler_train_and_test_datasets.py method from the internal modules.
Using Manual Scaler Objects¶
Train a DNN using the Scaler-Normalized AntiNex Django Dataset. This builds the train and test datasets manually to verify the process before editing the antinex_utils.build_scaler_dataset_from_records.py method.
Convert Bottom Rows from a CSV File into JSON¶
When testing live DNN predictions you can use this utility script to print a few JSON-ready dictionaries out to stdout
.
Usage:
convert_bottom_rows_to_json.py -f <CSV File> -b <Optional - number of rows from the bottom>
S3 Testing¶
Run this script to verify S3 is working.
Set Environment Variables¶
Set these as needed for your S3 deployment
export S3_ACCESS_KEY=<access key>
export S3_SECRET_KEY=<secret key>
export S3_REGION_NAME=<region name: us-east-1>
export S3_ADDRESS=<S3 endpoint address host:port like: minio-service:9000>
export S3_UPLOAD_FILE=<path to file to upload>
export S3_BUCKET=<bucket name - s3-verification-tests default>
export S3_BUCKET_KEY=<bucket key name - s3-worked-on-%Y-%m-%d-%H-%M-%S default>
export S3_SECURE=<use ssl '1', disable with '0' which is the default>