sbrl-github/research-rainfallradar
1
0
Fork 0
mirror of https://github.com/sbrl/research-rainfallradar synced 2024-07-02 11:24:56 +00:00
Code Issues Packages Projects Releases Wiki Activity

pretrain_predict: default to parallel_reads=0

Browse source
This commit is contained in:
Starbeamrainbowlabs 2022-10-19 16:59:45 +01:00
parent 63e909d9fc
commit 488f78fca5
Signed by: sbrl
GPG key ID: 1BE5172E637709C2
1 changed files with 2 additions and 2 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

4
aimodel/src/subcommands/pretrain_predict.py
View file

@ -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