From 488f78fca5655fd8839a039398a4de551a2fe4b5 Mon Sep 17 00:00:00 2001 From: Starbeamrainbowlabs Date: Wed, 19 Oct 2022 16:59:45 +0100 Subject: [PATCH] pretrain_predict: default to parallel_reads=0 --- aimodel/src/subcommands/pretrain_predict.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/aimodel/src/subcommands/pretrain_predict.py b/aimodel/src/subcommands/pretrain_predict.py index 5e1ab84..c714754 100644 --- a/aimodel/src/subcommands/pretrain_predict.py +++ b/aimodel/src/subcommands/pretrain_predict.py @@ -29,7 +29,7 @@ def parse_args(): parser.add_argument("--records-per-file", help="Optional. If specified, this limits the number of records written to each file. When using this option, you MUST have the string '+d' (without quotes) somewhere in your output filepath.", type=int) parser.add_argument("--checkpoint", "-c", help="Checkpoint file to load model weights from.", required=True) parser.add_argument("--params", "-p", help="Optional. The file containing the model hyperparameters (usually called 'params.json'). If not specified, it's location will be determined automatically.") - parser.add_argument("--reads-multiplier", help="Optional. The multiplier for the number of files we should read from at once. Defaults to 1.5, which means read ceil(NUMBER_OF_CORES * 1.5). Set to a higher number of systems with high read latency to avoid starving the GPU of data.") + parser.add_argument("--reads-multiplier", help="Optional. The multiplier for the number of files we should read from at once. Defaults to 0. If using this start at a value of 1.5, which means read ceil(NUMBER_OF_CORES * 1.5). Set to a higher number of systems with high read latency to avoid starving the GPU of data. CAUTION: If this is set to greater than 0, then it will SCRAMBLE THE INPUTS!") return parser @@ -47,7 +47,7 @@ def run(args): if (not hasattr(args, "params")) or args.params == None: args.params = find_paramsjson(args.checkpoint) if (not hasattr(args, "read_multiplier")) or args.read_multiplier == None: - args.read_multiplier = 1.5 + args.read_multiplier = 0 if (not hasattr(args, "records_per_file")) or args.records_per_file == None: args.records_per_file = 0 # 0 = unlimited