mirror of
https://github.com/vale981/ray
synced 2025-03-08 19:41:38 -05:00
39 lines
1.3 KiB
Python
39 lines
1.3 KiB
Python
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import argparse
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import boto3
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import os
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import numpy as np
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import ray
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import ray.services as services
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import ray.datasets.imagenet as imagenet
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import functions
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parser = argparse.ArgumentParser(description="Parse information for data loading.")
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parser.add_argument("--s3-bucket", type=str, help="Name of the bucket that contains the image data.")
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parser.add_argument("--key-prefix", default="ILSVRC2012_img_train/n015", type=str, help="Prefix for files to fetch.")
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parser.add_argument("--drop-ipython", default=False, type=bool, help="Drop into IPython at the end?")
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if __name__ == "__main__":
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args = parser.parse_args()
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test_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "worker.py")
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services.start_singlenode_cluster(return_drivers=False, num_workers_per_objstore=5, worker_path=test_path)
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s3 = boto3.resource("s3")
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imagenet_bucket = s3.Bucket(args.s3_bucket)
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objects = imagenet_bucket.objects.filter(Prefix=args.key_prefix)
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images = [obj.key for obj in objects.all()]
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x = imagenet.load_tarfiles_from_s3(args.s3_bucket, map(str, images), [256, 256]) # TODO(pcm): implement unicode serialization
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mean_image = functions.compute_mean_image(x)
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mean_image = ray.pull(mean_image)
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print "The mean image is:"
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print mean_image
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if args.drop_ipython:
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import IPython
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IPython.embed()
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services.cleanup()
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