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https://github.com/sbrl/research-rainfallradar
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ai pretrain-predict: fix - → _ in cli parsing
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2 changed files with 6 additions and 1 deletions
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@ -25,7 +25,7 @@ For more information, do src/index.py <subcommand> --help.
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""")
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""")
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exit(0)
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exit(0)
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subcommand = re.sub(r'[^a-z0-9-]', '', sys.argv[1])
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subcommand = re.sub(r'-', '_', re.sub(r'[^a-z0-9-]', '', sys.argv[1]))
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subcommand_argparser = importlib.import_module(f"subcommands.{subcommand}").parse_args
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subcommand_argparser = importlib.import_module(f"subcommands.{subcommand}").parse_args
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@ -68,12 +68,17 @@ def run(args):
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if filepath_output != "-":
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if filepath_output != "-":
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handle = io.open(filepath_output, "w")
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handle = io.open(filepath_output, "w")
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i = 0
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for rainfall, water in ai.embed(dataset):
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for rainfall, water in ai.embed(dataset):
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handle.write(json.dumps({
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handle.write(json.dumps({
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"rainfall": rainfall.numpy().tolist(),
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"rainfall": rainfall.numpy().tolist(),
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"water": water.numpy().tolist()
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"water": water.numpy().tolist()
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}, separators=(',', ':'))+"\n") # Ref https://stackoverflow.com/a/64710892/1460422
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}, separators=(',', ':'))+"\n") # Ref https://stackoverflow.com/a/64710892/1460422
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if i == 0 or i % 1000 == 0:
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sys.stderr.write(f"[pretrain:predict] STEP {i}\r")
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i += 1
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handle.close()
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handle.close()
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sys.stderr.write(">>> Complete\n")
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sys.stderr.write(">>> Complete\n")
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