def read_config(self, fname):
config = cfg()
config.read(fname)
# Convert config to a dict
res = {s: dict(config.items(s)) for s in config.sections()}
if "outdir" not in res["IO"]:
res["IO"]["outdir"] = ""
if "covar_data" not in res["cosmo_paramsParams"]:
res["cosmo_paramsParams"]["covar_data"] = ""
# Run Options
self.quantity = res["RunOptions"].pop("quantity")
self.xval = res["RunOptions"].pop("xval")
self.framework = res["RunOptions"].pop("framework")
self.relax = bool(res["RunOptions"].pop("relax"))
self.nthreads = int(res["RunOptions"].pop("nthreads"))
# Derived params and quantities
dparams = json.loads(res["RunOptions"].pop("der_params"))
dquants = json.loads(res["RunOptions"].pop("der_quants"))
self.n_dparams = len(dparams)
self.blobs = dparams + dquants
# Fit-options
self.fit_type = res["FitOptions"].pop("fit_type")
# MCMC-specific
self.nwalkers = int(res["MCMC"].pop("nwalkers"))
self.nsamples = int(res["MCMC"].pop("nsamples"))
self.burnin = json.loads(res["MCMC"].pop("burnin"))
# Downhill-specific
self.downhill_kwargs = {
k: json.loads(v) for k, v in list(res["Downhill"].items())
}
del res["Downhill"]
# IO-specific
self.outdir = res["IO"].pop("outdir", None)
self.chunks = int(res["IO"].pop("chunks"))
# Data-specific
self.data_file = res["Data"].pop("data_file")
self.cov_file = res["Data"].pop("cov_file", None)
# Model-specific
self.model = res.pop("Model")
self.model_pickle = self.model.pop("model_file", None)
for k in self.model:
self.model[k] = json.loads(self.model[k])
self.constraints = {
k: json.loads(v) for k, v in list(res["Constraints"].items())
}
return {k: res.pop(k) for k in list(res.keys()) if k.endswith("Params")}
def read_config(self, fname):
config = cfg()
config.read(fname)
# Convert config to a dict
res = {s: dict(config.items(s)) for s in config.sections()}
if "outdir" not in res["IO"]:
res["IO"]["outdir"] = ""
if "covar_data" not in res["cosmo_paramsParams"]:
res["cosmo_paramsParams"]['covar_data'] = ''
# Run Options
self.quantity = res["RunOptions"].pop("quantity")
self.xval = res["RunOptions"].pop("xval")
self.framework = res["RunOptions"].pop("framework")
self.relax = bool(res["RunOptions"].pop("relax"))
self.nthreads = int(res["RunOptions"].pop("nthreads"))
# Derived params and quantities
dparams = json.loads(res["RunOptions"].pop("der_params"))
dquants = json.loads(res["RunOptions"].pop("der_quants"))
self.n_dparams = len(dparams)
self.blobs = dparams + dquants
# Fit-options
self.fit_type = res['FitOptions'].pop("fit_type")
# MCMC-specific
self.nwalkers = int(res["MCMC"].pop("nwalkers"))
self.nsamples = int(res["MCMC"].pop("nsamples"))
self.burnin = json.loads(res["MCMC"].pop("burnin"))
# Downhill-specific
self.downhill_kwargs = {k: json.loads(v) for k, v in list(res['Downhill'].items())}
del res["Downhill"]
# IO-specific
self.outdir = res["IO"].pop("outdir", None)
self.chunks = int(res["IO"].pop("chunks"))
# Data-specific
self.data_file = res["Data"].pop("data_file")
self.cov_file = res["Data"].pop("cov_file", None)
# Model-specific
self.model = res.pop("Model")
self.model_pickle = self.model.pop("model_file", None)
for k in self.model:
try:
self.model[k] = json.loads(self.model[k])
except:
pass
self.constraints = {k: json.loads(v) for k, v in list(res["Constraints"].items())}
param_dict = {k: res.pop(k) for k in list(res.keys()) if k.endswith("Params")}
return param_dict
VerticalFlip,
HorizontalFlip,
OneOf,
CLAHE,
Normalize,
RandomBrightnessContrast,
Cutout,
RandomGamma,
ShiftScaleRotate,
GaussNoise,
Blur,
MotionBlur,
GaussianBlur,
)
dr_config = cfg()
dr_config.read('dr_config.ini')
random_id = ''.join(random.SystemRandom().choice(string.ascii_uppercase +
string.digits)
for _ in range(10))
params = dr_config['params']
# for k, v in config['params'].items():print(k,v)
n_fold = int(params['n_fold'])
fold = int(params['fold'])
SEED = int(params['SEED'])
batch_size = int(params['batch_size'])
sz = int(params['sz'])
learning_rate = float(params['learning_rate'])
patience = int(params['patience'])
accum_step = int(params['accum_step'])
num_class = int(params['num_class'])
with tempf("w+", dir=codepath,
suffix=".abe") as codef, tempf("w+",
dir=codepath,
suffix=".txt") as inpf:
codef.write(code)
inpf.write(data)
codef.flush()
inpf.flush()
# If it fails, bubbles up TimeoutError + CalledProcessError
codef.seek(0)
output = subprocess.run(
f'osabie "{codef.name}" < "{inpf.name}"',
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
timeout=timeout,
shell=True,
encoding="UTF-8",
)
return output.stdout
if __name__ == "__main__":
if not bot_key:
cf = cfg()
cf.read("key.cfg")
bot_key = cf["DEFAULT"]["key"]
try:
rosy.run(bot_key)
except KeyboardInterrupt:
print("Received exit, exiting")