File size: 2,498 Bytes
476455e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | # Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file 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.
import argparse
import json
import os
from packaging.version import Version
def _parse_args_v1():
parser = argparse.ArgumentParser()
# hyperparameters sent by the client are passed as command-line arguments to the script.
parser.add_argument("--epochs", type=int, default=1)
# Data, model, and output directories
parser.add_argument("--output-data-dir", type=str, default=os.environ.get("SM_OUTPUT_DATA_DIR"))
parser.add_argument("--model_dir", type=str)
parser.add_argument("--train", type=str, default=os.environ.get("SM_CHANNEL_TRAINING"))
parser.add_argument("--hosts", type=list, default=json.loads(os.environ.get("SM_HOSTS")))
parser.add_argument("--current-host", type=str, default=os.environ.get("SM_CURRENT_HOST"))
known, unknown = parser.parse_known_args()
return known
def _parse_args_v2():
parser = argparse.ArgumentParser()
parser.add_argument("--train", type=str, default=os.environ["SM_CHANNEL_TRAINING"])
parser.add_argument("--epochs", type=int, default=10)
parser.add_argument("--model_dir", type=str)
parser.add_argument("--max-steps", type=int, default=200)
parser.add_argument("--save-checkpoint-steps", type=int, default=200)
parser.add_argument("--throttle-secs", type=int, default=60)
parser.add_argument("--hosts", type=list, default=json.loads(os.environ["SM_HOSTS"]))
parser.add_argument("--current-host", type=str, default=os.environ["SM_CURRENT_HOST"])
parser.add_argument("--batch-size", type=int, default=100)
parser.add_argument("--export-model-during-training", type=bool, default=False)
return parser.parse_args()
if __name__ == "__main__":
import tensorflow as tf
if Version(tf.__version__) <= Version("2.5"):
from mnist_v1 import main
args = _parse_args_v1()
main(args)
else:
from mnist_v2 import main
args = _parse_args_v2()
main(args)
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