def __init__(self,
space,
param_file=None,
param_string=None,
output_format=None):
LOG.debug('Starting sbuild...')
self.space = space
self.param = Parameters()
self.conveyor = Conveyor()
# identify the workflow type
self.conveyor.setOrigin('slearn')
# generate a unique modelID
self.conveyor.addMeta('modelID', utils.id_generator())
LOG.debug(
f'Generated new space with modelID: {self.conveyor.getMeta("modelID")}'
)
# load parameters
if param_file is not None:
# use the param_file to update existing parameters at the space
# directory and save changes to make them persistent
success, message = self.param.delta(space,
0,
param_file,
iformat='YAML',
isSpace=True)
elif param_string is not None:
success, message = self.param.delta(space,
0,
param_string,
iformat='JSONS',
isSpace=True)
else:
# load parameter file at the space directory
success, message = self.param.loadYaml(space, 0, isSpace=True)
# being unable to load parameters is a critical error
if not success:
LOG.critical(
f'Unable to load space parameters. {message}. Aborting...')
sys.exit(1)
# add additional output formats included in the constructor
# this is requiered to add JSON format as output when the object is
# instantiated from a web service call, requiring this output
if output_format is not None:
if output_format not in self.param.getVal('output_format'):
self.param.appVal('output_format', output_format)
def action_predictions_result (label, output='text'):
'''
try to retrieve the prediction result with the label used as argument
returns
- (False, Null) if it there is no directory or the predictions
pickle files cannot be found
- (True, object) with the results otherwyse
'''
# get de model repo path
predictions_path = pathlib.Path(utils.predictions_repository_path())
label_path = predictions_path.joinpath(label)
if not os.path.isdir(label_path):
if output != 'text':
return False, {'code':0, 'message': f'directory {label_path} not found'}
print (f'directory {label_path} not found')
return False, None
result_path = label_path.joinpath('prediction-results.pkl')
if not result_path.is_file():
if output != 'text':
return False, {'code':0, 'message': f'predictions not found for {label} directory'}
print (f'predictions not found for {label} directory')
return False, None
iconveyor = Conveyor()
with open(result_path, 'rb') as handle:
success, message = iconveyor.load(handle)
if not success:
if output != 'text':
return False, {'code':1, 'message': f'error reading prediction results with message {message}'}
print (f'error reading prediction results with message {message}')
return False, None
# console output
print_prediction_result(('obj_num','number of objects',iconveyor.getVal('obj_num')))
if iconveyor.isKey('external-validation'):
for val in iconveyor.getVal('external-validation'):
print_prediction_result (val)
if iconveyor.isKey('values'):
for i in range (iconveyor.getVal('obj_num')):
print (iconveyor.getVal('obj_nam')[i], '\t', float("{0:.4f}".format(iconveyor.getVal('values')[i])))
# return iconveyor
return True, iconveyor
def __init__(self, model, version, output_format=None):
LOG.debug('Starting predict...')
self.model = model
self.version = version
self.param = Parameters()
self.conveyor = Conveyor()
if not self.param.loadYaml(model, version):
LOG.critical('Unable to load model parameters. Aborting...')
sys.exit()
# add additional output formats included in the constructor
# this is requiered to add JSON format as output when the object is
# instantiated from a web service call, requiring this output
if output_format != None:
if output_format not in self.param.getVal('output_format'):
self.param.appVal('output_format',output_format)
return
def action_info(model, version, output='text'):
'''
Returns a text or JSON with results info for a given model and version
'''
if model is None:
return False, 'Empty model label'
rdir = utils.model_path(model, version)
if not os.path.isfile(os.path.join(rdir, 'results.pkl')):
# compatibity method. use info.pkl
if not os.path.isfile(os.path.join(rdir, 'info.pkl')):
return False, 'Info file not found'
with open(os.path.join(rdir, 'info.pkl'), 'rb') as handle:
#retrieve a pickle file containing the keys 'model_build'
#and 'model_validate' of results
info = pickle.load(handle)
info += pickle.load(handle)
# end of compatibility method
else:
# new method, use results.pkl
if not os.path.isfile(os.path.join(rdir, 'results.pkl')):
return False, 'Info file not found'
from flame.conveyor import Conveyor
conveyor = Conveyor()
with open(os.path.join(rdir, 'results.pkl'), 'rb') as handle:
conveyor.load(handle)
info = conveyor.getVal('model_build_info')
info += conveyor.getVal('model_valid_info')
if info == None:
return False, 'Info not found'
# when this function is called from the console, output is 'text'
# write and exit
if output == 'text':
LOG.info(f'informing model {model} version {version}')
for val in info:
if len(val) < 3:
LOG.info(val)
else:
LOG.info(f'{val[0]} ({val[1]}) : {val[2]}')
return True, 'model informed OK'
# this is only reached when this funcion is called from a web service
# asking for a JSON
# this code serializes the results in a list and then converts it
# to a JSON
json_results = []
for i in info:
json_results.append(conveyor.modelInfoJSON(i))
#print (json.dumps(json_results))
return True, json.dumps(json_results)
def action_info(model, version, output='text'):
'''
Returns a text or JSON with results info for a given model and version
'''
if model is None:
return False, 'Empty model label'
rdir = utils.model_path(model, version)
if not os.path.isfile(os.path.join(rdir, 'results.pkl')):
return False, 'Info file not found'
from flame.conveyor import Conveyor
conveyor = Conveyor()
with open(os.path.join(rdir, 'results.pkl'), 'rb') as handle:
conveyor.load(handle)
# if there is an error, return the error Message
if conveyor.getError():
error = conveyor.getErrorMessage()
return False, error
# collect warnings
warning = conveyor.getWarningMessage()
# collect build and validation info
build_info = conveyor.getVal('model_build_info')
valid_info = conveyor.getVal('model_valid_info')
# merge everything
info = None
for iinfo in (warning, build_info, valid_info):
if info == None:
info = iinfo
else:
if iinfo != None:
info+=iinfo
if info == None:
return False, 'No relevant information found'
# when this function is called from the console, output is 'text'
# write and exit
if output == 'text':
LOG.info (f'informing model {model} version {version}')
for val in info:
if len(val) < 3:
LOG.info(val)
else:
LOG.info(f'{val[0]} ({val[1]}) : {val[2]}')
return True, 'model informed OK'
# this is only reached when this funcion is called from a web service
# asking for a JSON
# this code serializes the results in a list and then converts it
# to a JSON
json_results = []
for i in info:
json_results.append(conveyor.modelInfoJSON(i))
#print (json.dumps(json_results))
return True, json.dumps(json_results)
