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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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| #! /usr/bin/env python | ||
| # coding=utf-8 | ||
| # Copyright (c) 2019 Uber Technologies, Inc. | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
| # ============================================================================== | ||
| from __future__ import absolute_import | ||
| from __future__ import division | ||
| from __future__ import print_function | ||
|
|
||
| import argparse | ||
| import logging | ||
| import sys | ||
|
|
||
| from ludwig.contrib import contrib_command | ||
| from ludwig.globals import set_on_master, is_on_master, LUDWIG_VERSION | ||
| from ludwig.predict import full_predict | ||
| from ludwig.utils.print_utils import logging_level_registry, print_ludwig | ||
|
|
||
|
|
||
| def cli(sys_argv): | ||
| parser = argparse.ArgumentParser( | ||
| description='This script loads a pretrained model ' | ||
| 'and tests its performance by comparing' | ||
| 'its predictions with ground truth.', | ||
| prog='ludwig test', | ||
| usage='%(prog)s [options]' | ||
| ) | ||
|
|
||
| # --------------- | ||
| # Data parameters | ||
| # --------------- | ||
| group = parser.add_mutually_exclusive_group(required=True) | ||
| group.add_argument( | ||
| '--data_csv', | ||
| help='input data CSV file. ' | ||
| 'If it has a split column, it will be used for splitting ' | ||
| '(0: train, 1: validation, 2: test), ' | ||
| 'otherwise the dataset will be randomly split' | ||
| ) | ||
| group.add_argument( | ||
| '--data_hdf5', | ||
| help='input data HDF5 file. It is an intermediate preprocess version of' | ||
| ' the input CSV created the first time a CSV file is used in the ' | ||
| 'same directory with the same name and a hdf5 extension' | ||
| ) | ||
| parser.add_argument( | ||
| '--train_set_metadata_json', | ||
| help='input metadata JSON file. It is an intermediate preprocess file ' | ||
| 'containing the mappings of the input CSV created the first time ' | ||
| 'a CSV file is used in the same directory with the same name and ' | ||
| 'a json extension' | ||
| ) | ||
|
|
||
| parser.add_argument( | ||
| '-s', | ||
| '--split', | ||
| default='test', | ||
| choices=['training', 'validation', 'test', 'full'], | ||
| help='the split to test the model on' | ||
| ) | ||
|
|
||
| # ---------------- | ||
| # Model parameters | ||
| # ---------------- | ||
| parser.add_argument( | ||
| '-m', | ||
| '--model_path', | ||
| help='model to load', | ||
| required=True | ||
| ) | ||
|
|
||
| # ------------------------- | ||
| # Output results parameters | ||
| # ------------------------- | ||
| parser.add_argument( | ||
| '-od', | ||
| '--output_directory', | ||
| type=str, | ||
| default='results', | ||
| help='directory that contains the results' | ||
| ) | ||
| parser.add_argument( | ||
| '-ssuo', | ||
| '--skip_save_unprocessed_output', | ||
| help='skips saving intermediate NPY output files', | ||
| action='store_true', default=False | ||
| ) | ||
|
|
||
| # ------------------ | ||
| # Generic parameters | ||
| # ------------------ | ||
| parser.add_argument( | ||
| '-bs', | ||
| '--batch_size', | ||
| type=int, | ||
| default=128, | ||
| help='size of batches' | ||
| ) | ||
|
|
||
| # ------------------ | ||
| # Runtime parameters | ||
| # ------------------ | ||
| parser.add_argument( | ||
| '-g', | ||
| '--gpus', | ||
| type=int, | ||
| default=0, | ||
| help='list of gpu to use' | ||
| ) | ||
| parser.add_argument( | ||
| '-gf', | ||
| '--gpu_fraction', | ||
| type=float, | ||
| default=1.0, | ||
| help='fraction of gpu memory to initialize the process with' | ||
| ) | ||
| parser.add_argument( | ||
| '-uh', | ||
| '--use_horovod', | ||
| action='store_true', | ||
| default=False, | ||
| help='uses horovod for distributed training' | ||
| ) | ||
| parser.add_argument( | ||
| '-dbg', | ||
| '--debug', | ||
| action='store_true', | ||
| default=False, | ||
| help='enables debugging mode' | ||
| ) | ||
| parser.add_argument( | ||
| '-l', | ||
| '--logging_level', | ||
| default='info', | ||
| help='the level of logging to use', | ||
| choices=['critical', 'error', 'warning', 'info', 'debug', 'notset'] | ||
| ) | ||
|
|
||
| args = parser.parse_args(sys_argv) | ||
| args.evaluate_performance = True | ||
|
|
||
| logging.basicConfig( | ||
| stream=sys.stdout, | ||
| level=logging_level_registry[args.logging_level], | ||
| format='%(message)s' | ||
| ) | ||
|
|
||
| set_on_master(args.use_horovod) | ||
|
|
||
| if is_on_master(): | ||
| print_ludwig('Test', LUDWIG_VERSION) | ||
|
|
||
| full_predict(**vars(args)) | ||
|
|
||
|
|
||
| if __name__ == '__main__': | ||
| contrib_command("test", *sys.argv) | ||
| cli(sys.argv[1:]) |